This front matter contains Series Editor’s Preface, ASME Press Robotics Engineering Book Series, contents, Preface, Acknowledgements eBook keywords: mechatronics, robotics, mobile roving robots, robot motion, tricycle robot, rickshaw robot, Hexapod robot, ICofR, inverse kinematics, driverless vehicles. This chapter explores basic theories related to creating vehicle motion in a ground plane, e.g. a road, using wheels whose axles are always parallel to the ground plane. Wheels that lean, such as with bicycles, are not considered. The idea is to generate vehicle motion concepts based on wheels because wheeled motion, acting as a forerunner to legged motion, is more easily grasped than starting with more complex vehicle motion using legs. Chapter 3 follows up with the real-time programming of an actual wheeled vehicle so the reader can see theory in practice. Later, in chapter 10, these concepts are translated into equivalent motion of a robot using legs such that wheeled vehicle motion is entirely replaced with legs. However, we first start with understanding the simplified motion of a single wheel. The ServoTeach module is a manually adjustable electronic circuit board, figure 2.1, that derives three independent, variable-angle, control signals for Futaba angular displacement servomechanisms, figure 2.2 that are used as artificial muscles for the robots described in this book. These servomechanisms or ‘servos’ actuate the rotation of an output shaft that pushes or pulls mechanical cranks, levers, links and limbs of the robot that produce locomotion. The ServoTeach module manually positions the servo output shaft to a required angle and the angle value integer number can be read at a computer screen. The integer number is derived from a Basic Stamp2 microcomputer. The number represents fractions of degree units that are calibrated in experiments described in following chapters. A forerunner to (i) hexapod and vehicle motion behaviour patterns in a ground plane and (ii) the use of piecewise truncated Taylor series to solve complicated equations using integer numbers Preceding chapters have laid the foundation for vehicle motion in a ground plane helped by a practical application of a wheeled robot in chapter 3. We will extend these ideas in successive chapters to a hybrid 2-wheeled/2-legged robot, figure 4.1, known as the Rickshaw Robot and a six legged robot, figure 4.2, the Hexapod Robot. Servo angles, S1, S2, S3 as a function of Leg Tip cylindrical coordinates, R, Z, θ The previous chapter, chapter 5, formulated the inverse kinematics equations that gave servo angles, S1, S2, S3 as functions of R, Z, θ. This chapter now formulates how to compute these functions, which are largely trigonometrical functions, with an integer-only 16-bit computer, namely the Basic Stamp microcomputer. The chapter concludes with the complete code for controlling one 3dof leg. Computation will only call upon four arithmetic instructions, which are, addition, subtraction, multiplication and division. Trigonometrical functions will not be called upon because, (i) the Basic Stamp does not possess such instructions, (ii) they are not needed and (iii) trigonometrical functions have non-unique solutions. Instead, we will compute the inverse kinematics equations using piecewise truncated Taylor series that rely solely on the ability to add, subtract, multiply and divide integer numbers as shown with equation 6.1, which is a 3-variable Taylor series equation. This chapter is written in the style of a project-based, hands-on teaching and learning experiment based tutorial. As such it is very helpful in understanding the inverse kinematic Taylor series equations as defined in chapter 6, eq. 6.1. It is a stand-alone chapter in that it can be used by students to derive an elementary robot leg walking algorithm together with its real-time code. An omni-directional walking robot requires legs whose leg-tips can independently access 3-dimensional space. ‘Omni-directional’ means the ability to walk in all directions such that the walking robot is able to walk sideways left, sideways right, forwards and backwards, and turn left and right. Furthermore, possession of 3dof legs enables the robot to turn while translating, which is similar to ballroom dancers when they dance the Viennese waltz as already discussed in chapter 1. In fact other complex manoeuvres are possible that include maintaining the body in a level attitude as the legs negotiate uneven terrain. Such motion can be analysed as the body rotating about any Instantaneous Axis of Rotation (note, ‘axis’ as compared to ‘centre’) which is a three dimensional vector as compared to a two dimensional point. (This interesting problem serves as a mathematical challenge to students). The leg tip motion and the leg tip locus have been analysed in detail in chapter 4 so we now consider how leg tip motion can achieve walking gaits and motion control. Code is generic and can be applied to each and any leg of a Chariot or Hexapod robot. The code is lower level and requires a higher level controller, a Central Pattern Generator, to be described in chapters 10 and 11, to create functionality The basic theory of motion of vehicles in a ground plane was covered in chapter 1 where a vehicle can be either a legged or wheeled device. Chapter 3 then used this theory to give motion to a Tricycle Robot which is a 3-wheeled vehicle with no legs. Chapters 4 to 9 then build up a theory of legged motion for a single 3 dof leg. The most important operational technique of leg motion is the ability to guide the leg tip through a programmably shaped and directioned locus, which is explained in chapter 4, and then to develop walking gaits as described in chapter 8. This book leads up finally to the programming of a 6-legged omnidirectional walking robot to carry out a behaviour pattern. However this is a big jump due to the complexity of such a robot. In order to bridge this gap we now introduce a 2-wheeled Rickshaw Robot with 2-legged locomotion, figure 10.1. The Rickshaw Robot is not as complex as the 6-legged robot but brings together the theory of the motion of vehicles whilst introducing the programming of two legs. The Rickshaw Robot thus serves as an ideal ‘bridge-the-gap’ introduction to complex multi-legged walking robots. This chapter is concerned with programming the Central Pattern Generator, the CPG, of an omnidirectional six-legged robot which is called The Hexapod Robot, figure 11.1. The CPG will be programmed to walk the Hexapod Robot through the same figure-of-eight path that was used in preceding chapters for the Tricycle and Rickshaw Robots. Note that chapter 8 should be reviewed because this current chapter delves straight into programming walking gaits that walk the robot CW or CCW around an ICofR. This back matter contains the Brief Biographies of the Authors and Index This book is designed primarily as a laboratory operations manual for fundamental mechatronics and robotics experiential and project-based learning. It is also ordered in that starting with the Tricycle Robot, students build up their knowledge and experience of programming to be able to tackle the Rickshaw Robot and finally the most complex robot, i.e., the Hexapod Robot. The book is aimed at university and college students; however, with robotics curricula extending down into lower grades this book can also be very useful for teachers at any school level. Furthermore, the book provides useful ideas for driverless vehicles and robots, as well as for educators who are developing practical project-based teaching and learning modules. Readers of the book can easily modify the coding, computing language, and hardware to suit personal preferences. This front matter contains Series Editor’s Preface, ASME Press Robotics Engineering Book Series, contents, Preface, Acknowledgements eBook keywords: mechatronics, robotics, mobile roving robots, robot motion, tricycle robot, rickshaw robot, Hexapod robot, ICofR, inverse kinematics, driverless vehicles. This chapter explores basic theories related to creating vehicle motion in a ground plane, e.g. a road, using wheels whose axles are always parallel to the ground plane. Wheels that lean, such as with bicycles, are not considered. The idea is to generate vehicle motion concepts based on wheels because wheeled motion, acting as a forerunner to legged motion, is more easily grasped than starting with more complex vehicle motion using legs. Chapter 3 follows up with the real-time programming of an actual wheeled vehicle so the reader can see theory in practice. Later, in chapter 10, these concepts are translated into equivalent motion of a robot using legs such that wheeled vehicle motion is entirely replaced with legs. However, we first start with understanding the simplified motion of a single wheel. The ServoTeach module is a manually adjustable electronic circuit board, figure 2.1, that derives three independent, variable-angle, control signals for Futaba angular displacement servomechanisms, figure 2.2 that are used as artificial muscles for the robots described in this book. These servomechanisms or ‘servos’ actuate the rotation of an output shaft that pushes or pulls mechanical cranks, levers, links and limbs of the robot that produce locomotion. The ServoTeach module manually positions the servo output shaft to a required angle and the angle value integer number can be read at a computer screen. The integer number is derived from a Basic Stamp2 microcomputer. The number represents fractions of degree units that are calibrated in experiments described in following chapters. A forerunner to (i) hexapod and vehicle motion behaviour patterns in a ground plane and (ii) the use of piecewise truncated Taylor series to solve complicated equations using integer numbers Preceding chapters have laid the foundation for vehicle motion in a ground plane helped by a practical application of a wheeled robot in chapter 3. We will extend these ideas in successive chapters to a hybrid 2-wheeled/2-legged robot, figure 4.1, known as the Rickshaw Robot and a six legged robot, figure 4.2, the Hexapod Robot. Servo angles, S1, S2, S3 as a function of Leg Tip cylindrical coordinates, R, Z, θ The previous chapter, chapter 5, formulated the inverse kinematics equations that gave servo angles, S1, S2, S3 as functions of R, Z, θ. This chapter now formulates how to compute these functions, which are largely trigonometrical functions, with an integer-only 16-bit computer, namely the Basic Stamp microcomputer. The chapter concludes with the complete code for controlling one 3dof leg. Computation will only call upon four arithmetic instructions, which are, addition, subtraction, multiplication and division. Trigonometrical functions will not be called upon because, (i) the Basic Stamp does not possess such instructions, (ii) they are not needed and (iii) trigonometrical functions have non-unique solutions. Instead, we will compute the inverse kinematics equations using piecewise truncated Taylor series that rely solely on the ability to add, subtract, multiply and divide integer numbers as shown with equation 6.1, which is a 3-variable Taylor series equation. This chapter is written in the style of a project-based, hands-on teaching and learning experiment based tutorial. As such it is very helpful in understanding the inverse kinematic Taylor series equations as defined in chapter 6, eq. 6.1. It is a stand-alone chapter in that it can be used by students to derive an elementary robot leg walking algorithm together with its real-time code. An omni-directional walking robot requires legs whose leg-tips can independently access 3-dimensional space. ‘Omni-directional’ means the ability to walk in all directions such that the walking robot is able to walk sideways left, sideways right, forwards and backwards, and turn left and right. Furthermore, possession of 3dof legs enables the robot to turn while translating, which is similar to ballroom dancers when they dance the Viennese waltz as already discussed in chapter 1. In fact other complex manoeuvres are possible that include maintaining the body in a level attitude as the legs negotiate uneven terrain. Such motion can be analysed as the body rotating about any Instantaneous Axis of Rotation (note, ‘axis’ as compared to ‘centre’) which is a three dimensional vector as compared to a two dimensional point. (This interesting problem serves as a mathematical challenge to students). The leg tip motion and the leg tip locus have been analysed in detail in chapter 4 so we now consider how leg tip motion can achieve walking gaits and motion control. Code is generic and can be applied to each and any leg of a Chariot or Hexapod robot. The code is lower level and requires a higher level controller, a Central Pattern Generator, to be described in chapters 10 and 11, to create functionality The basic theory of motion of vehicles in a ground plane was covered in chapter 1 where a vehicle can be either a legged or wheeled device. Chapter 3 then used this theory to give motion to a Tricycle Robot which is a 3-wheeled vehicle with no legs. Chapters 4 to 9 then build up a theory of legged motion for a single 3 dof leg. The most important operational technique of leg motion is the ability to guide the leg tip through a programmably shaped and directioned locus, which is explained in chapter 4, and then to develop walking gaits as described in chapter 8. This book leads up finally to the programming of a 6-legged omnidirectional walking robot to carry out a behaviour pattern. However this is a big jump due to the complexity of such a robot. In order to bridge this gap we now introduce a 2-wheeled Rickshaw Robot with 2-legged locomotion, figure 10.1. The Rickshaw Robot is not as complex as the 6-legged robot but brings together the theory of the motion of vehicles whilst introducing the programming of two legs. The Rickshaw Robot thus serves as an ideal ‘bridge-the-gap’ introduction to complex multi-legged walking robots. This chapter is concerned with programming the Central Pattern Generator, the CPG, of an omnidirectional six-legged robot which is called The Hexapod Robot, figure 11.1. The CPG will be programmed to walk the Hexapod Robot through the same figure-of-eight path that was used in preceding chapters for the Tricycle and Rickshaw Robots. Note that chapter 8 should be reviewed because this current chapter delves straight into programming walking gaits that walk the robot CW or CCW around an ICofR. This back matter contains the Brief Biographies of the Authors and Index

Introduces a revolutionary, quadratic-programming based approach to solving long-standing problems in motion planning and control of redundant manipulators.This book describes a novel quadratic programming approach to solving redundancy resolutions problems with redundant manipulators. Known as “QP-unified motion planning and control of redundant manipulators” theory, it systematically solves difficult optimization problems of inequality-constrained motion planning and control of redundant manipulators that have plagued robotics engineers and systems designers for more than a quarter century. An example of redundancy resolution could involve a robotic limb with six joints, or degrees of freedom (DOFs), with which to position an object. As only five numbers are required to specify the position and orientation of the object, the robot can move with one remaining DOF through practically infinite poses while performing a specified task. In this case redundancy resolution refers to the process of choosing an optimal pose from among that infinite set. A critical issue in robotic systems control, the redundancy resolution problem has been widely studied for decades, and numerous solutions have been proposed. This book investigates various approaches to motion planning and control of redundant robot manipulators and describes the most successful strategy thus far developed for resolving redundancy resolution problems. Provides a fully connected, systematic, methodological, consecutive, and easy approach to solving redundancy resolution problems Describes a new approach to the time-varying Jacobian matrix pseudo inversion, applied to the redundant-manipulator kinematic control Introduces The QP-based unification of robots’ redundancy resolution Illustrates the effectiveness of the methods presented using a large number of computer simulation results based on PUMA560, PA10, and planar robot manipulators Provides technical details for all schemes and solvers presented, for readers to adopt and customize them for specific industrial applications Robot Manipulator Redundancy Resolution is must-reading for advanced undergraduates and graduate students of robotics, mechatronics, mechanical engineering, tracking control, neural dynamics/neural networks, numerical algorithms, computation and optimization, simulation and modelling, analog, and digital circuits. It is also a valuable working resource for practicing robotics engineers and systems designers and industrial researchers. This front matter contains the contents, list of figures, list of tables, preface, acknowledgments, acronyms and is available for free viewing by clicking on the PDF below. eBook keywords: robotics, planning and control, systems design, redundancy, quadratic programming, robotics engineers, motion planning, robot manipulators, kinematics. Recently, robotics has played a more and more important role in scientific research and engineering applications. Being an essential topic, the problem of redundancy resolution (or mostly say, the problem of inverse kinematics, which is related to the kinematic control of some redundant robot manipulator) has attracted the extensive attention of many researchers. The general description of such a problem is that, given the desired Cartesian path r d ( t ) ∈ ℝ m of the end-effector versus time t ∈ [ t 0 , t f ] ⊆ [0, ∞), the corresponding trajectories of joint-variable vector θ ( t ) ∈ ℝ n need to be obtained online (or offline and in advance). In recent years, there have been numerous investigations in to robot manipulators, especially the redundant robot manipulators. Compared with the ordinary robot manipulators, the redundant one has more degrees of freedom (DOF) than necessary for position and orientation. It is worth noting that this characteristic improves the kinematic and the dynamic performance of the robot manipulator, such as increasing dexterity, avoiding obstacles and singularities, and optimizing joint velocity, which makes redundant the manipulators widely applied in the field of robotic manipulator control. As one of the central issues in robot control, path tracking refers to making the end-effector move as expected by controlling the joints of robot manipulators. When the end-effector moves at a desired speed, it is often called path tracking control at the velocity level (JVL), which can fit in with the needs of the operators well with two advantages. One is that the high velocity can economize the execution time while the other one is that the low velocity can enhance the objective precision. So the control at the velocity level is suited particularly well to tasks for machining operations, such as cutting and milling. In recent decades, robotic systems have been playing an increasingly important role in numerous fields of engineering applications. They have been applied in industrial automation to perform repetitive and high-intensitive work, such as painting, welding, ironing, and palletizing. Redundant robot manipulators are robotic devices whose available DOF are more than required for executing a specific end-effector task, which leads to greater dexterity and flexibility for robot manipulators. One fundamental issue in operating the redundant robot manipulator is the redundant resolution problem (i.e., the inverse kinematics problem). In recent years, numerous redundancy-resolution schemes have been presented, developed, and investigated at different levels (e.g., the joint-velocity level and joint-acceleration level) for solving the inverse kinematics problem of redundant robot manipulators. Note that the Z0G1 type scheme and the inverse scheme have already been presented in Chapter 2. By exploiting the powerful gradient dynamics (GD) method and zeroing dynamics (ZD) method, this chapter presents and investigates the Z1G1 type scheme in an inverse-free manner at the joint-acceleration level for the redundant robot manipulator. The Z1G1 type scheme can effectively solve the inverse kinematics problem of redundant robot manipulators without calculating the computationally expensive inverse of Jacobian matrix. The path-tracking simulations and physical experiments are conducted to further substantiate the effectiveness, high accuracy, and physical realizability of the presented inverse-free solution. A redundant manipulator is defined when more degrees of freedom (DOF) are available than the minimum number of DOF required to execute a given end-effector primary task. Our human arm, elephant trunk, and snake are also such redundant systems. Compared to non-redundant manipulators, the redundant manipulator naturally has wider operational space and extra degrees to meet more functional constraints, such as the online avoidance of joint physical limits and environmental obstacles. One of the most fundamental issues in operating the redundant manipulators is the redundancy-resolution problem. That is, given the Cartesian velocity/acceleration trajectories of the end-effector, we are required to generate the corresponding joint velocity, acceleration, and/or torque trajectories in real time. Redundant manipulators can achieve subtasks readily and smartly such as generating cyclic motion, avoiding joint limits, avoiding singularities, tolerating faults, avoiding obstacles, and optimization of multiple performance criteria because they have more DOF than required to execute a desired primary task. Motion planning (or resolving the redundancy problem) of the manipulators is thus an appealing topic in the robotics area. The pseudoinverse-based approach is the conventional method for resolving the redundancy problem of the manipulators. Research in the last decade shows that various online optimization strategies/techniques are preferred methods, and some of these optimization strategies are usually expressed as a quadratic program (QP), which is subject to equality and inequality constraints. Such a QP is then converted into linear variational inequality (LVI), which may be solved approximately by many methods and techniques efficiently, such as numerical methods and some types of neural networks (NNs). In [104], three recurrent NNs are applied to cyclic motion generation. In [61, 105, 106, 137–139], primal-dual NNs formulated in differential equations are used to solve various redundancy resolution problems. In [23], another NN, called zeroing dynamics, is used to solve the time-varying problem. In this chapter, for implementing the scheme on the digital computer and physical hardware system more readily, a numerical algorithm formulated in a difference equation is adopted to solve the QP. Kinematic redundancy can be obtained when a robot manipulator possesses more DOF than the minimum number required to execute a given end-effector task. If a robot manipulator is redundant, the inverse-kinematics problem may admit infinite solutions. How to obtain the required optimal solution, that is, the redundancy resolution problem, is an appealing and significant topic in robotics areas. In the past, many redundancy resolution schemes have been presented, and they can be divided into two main categories; that is, globally optimal control of redundancy and local/instantaneously optimal control of redundancy. The globally optimal concept and method were originally suggested by Whitney, and the early effective global schemes were presented by Uchiyama et al . and Nakamura et al . The global optimal schemes can generate the global optimal solutions, but they require a large amount of computation and are not suitable for real-time kinematic resolution. The detailed discussion can be referred to [143]. Thus, the local/instantaneously optimal control schemes are widely investigated and used in robotics areas. The classic local optimal solution is pseudoinverse-type formulation, which is investigated in Chapter 1; that is, one minimum-norm particular solution plus a homogeneous solution. Based on such a pseudoinverse-type solution, many optimization performance criteria have been exploited in terms of manipulator configurations and interaction with the environment, such as joint-limits avoidance, singularity avoidance, manipulability enhancement, and obstacle avoidance. Recent research shows that the solutions to redundancy resolution problems can be enhanced by using optimization techniques based on quadratic program (QP) methods. Compared with the classic pseudoinverse-based solutions, such QP-based methods do not need to compute the inverse of the Jacobian matrix, and are readily to deal with the inequality and/or bound constraints. Thus, new interests in QP-based methods have been generated. In [90], considering the physical limits, Cheng et al . presented a compact QP method to resolve the constrained kinematic redundancy problem. As a specific example in [90], a repetitive motion planning (RMP) scheme was presented to illustrate the effectiveness of the compact QP method. Note that such an RMP scheme is based on Euclidean norm (or two-norm), and used to remedy the non-repetitive problem of the closed end-effector path (which is different from the path tracked in this chapter). The two-norm was widely used because of its analytical tractability, but minimizing the two-norm solution was not an ideal choice. Thus, some researchers began to investigate the optimization schemes based on the infinity norm and minimizing the infinity norm implied the determination of a minimum-effort solution as opposed to the minimum-energy criterion associated with the Euclidean norm. The torque-level and acceleration-level optimization schemes have also been investigated. It is worth pointing out that various criteria are exploited to optimize different objectives according to the requirements in general. A manipulator is said to be redundant when more DOF are available than necessary for a given end-effector path-tracking task. This implies that redundancy can be established simply with respect to some particular tasks. For non-redundant manipulators, the joint motion is uniquely determined by a prescribed end-effector primary task, and thus there are no redundant freedoms left for executing some secondary tasks, such as handling joint physical limits, environmental constraints, and configuration singularities. In contrast, redundant manipulators have wider operational space and meet more functional constraints, because an infinite number of feasible joint configurations can be available. They have thus been widely applied, for example, in cleanup and remediation of nuclear and hazardous materials, and in space or sea exploration. Therefore, a lot of research into redundant manipulators has been carried out, and much attention has been paid by the research community to motion planning and control of robot manipulators. Kinematically redundant manipulators are those that have more DOF than required for (specific) end-effectors’ position-and-orientation tasks. This implies that redundancy can also be established with respect to some particular tasks; for example, positioning only. For non-redundant manipulators, the joint motion is usually determined uniquely by a prescribed end-effector trajectory and, thus, there is no freedom left to handle secondary tasks, such as the handling of joint physical limits and environmental constraints (e.g., obstacles). In comparison, redundant manipulators have wider operational space and extra DOF to meet a number of functional constraints and performance criteria because there exist an infinite number of joint configurations as feasible solutions (corresponding to a prescribed end-effector task). A manipulator is said to be redundant when more DOF are available than the minimum number required to perform a specific end-effector primary task. For redundant manipulators, as discussed in previous chapters, the inverse kinematic resolution is a fundamental issue in operating the robot systems. The general description of this problem is that, given the desired Cartesian path r d ( t ) ∈ ℝ m for the manipulator’s end-effector to track, how can we generate the corresponding joint trajectory θ ( t ) ∈ ℝ n in real time t ? Note that n > m and, thus, there exist multiple or an infinite number of feasible solutions to the inverse-kinematic problem. In this sense, the redundancy of joint motion, together with kinematic and dynamic nonlinearities, complicate the manipulator control problem significantly. The number of DOF is very vital for a manipulator. A manipulator is kinematically and/or functionally redundant when more DOF are available than the minimum number required to perform the primary task of a specific manipulator. Compared with a non-redundant manipulator, a redundant manipulator has wider operational space and extra degrees to configure the manipulator to meet additional functional constraints without affecting the position (and/or orientation) of the end-effector. Therefore, much attention and effort in the robotic research community have been paid to studies on and applications of redundant robot manipulators. Studies on and applications of a redundant robot manipulator are the topical research issues in the robotic community. In particular, the inverse-kinematics problem, which finds the joint motion for a given manipulator’s end-effector task is one of the important and challenging issues in operating the redundant manipulators. Note that there are an infinite number of joint configurations of a manipulator with respect to a specific task, due to the redundancy; and redundancy resolution is to make a suitable selection from the configurations. This kind of selection is usually used to accomplish some secondary tasks for robot manipulators or generate an optimal solution to achieve some performance criteria, besides finishing the main end-effector path-tracking task. The redundancy-resolution problem can be readily solved by optimization techniques, especially QP. Note that the quadratic program (QP) can be converted to a linear variational inequality (LVI), and the resultant LVI is equivalent to a piecewise-linear equation (PLE) that can be solved by many algorithms and techniques efficiently, such as numerical algorithm E47 and numerical algorithm 94LVI presented in previous chapters as well as recurrent neural networks. The issue of optimal motion control in robotics is becoming a more and more appealing topic as robots are widely applied in scientific research, military and civilian areas, of which the operating environment is much more complicated than that in the past. Redundant manipulators can achieve subtasks such as obstacle avoidance, repetitive motion planning, joint limits, and singularity avoidance, or optimization of various performance criteria, since they have more degrees of freedom (DOF) than required to perform a given end-effector primary task. A fundamental issue in controlling such redundant manipulators is to design suitable redundancy-resolution approaches. The conventional solution to such a redundancy-resolution problem is the pseudoinverse-based formulation. Given they have more DOF than required to perform a given end-effector primary task, redundant robot manipulators can achieve subtasks such as obstacle avoidance, fault tolerance, repetitive motion planning, joint limits, and singularity avoidance. Existing optimal control methods for path planning and control of robot manipulators can be roughly categorized into two types: First, optimal control methods that can handle each robot link separately without regard to robot dynamics by computing set points for low-level (e.g., position- or velocity-level) single-input single-output controllers; Second, optimal control methods that can handle the robot directly by considering robot dynamics and computing motor torques for high-level controllers, specifically, torque-level controllers. The former methods pertain to the description of motion (position, velocity, acceleration, etc.). These methods can perform well if the desired motion is not too fast and does not require large acceleration. The latter methods are related to the explanation of motion in terms of forces and torques and are applicable to numerous practical manipulators. The level at which path planning and control is performed may depend on the type of robot controller. For example, if joints are driven by positionor velocity-controlled servo motors, then a path planning and control scheme at the position or velocity level will generally suffice. However, if controllers can be driven by joint torque or actuator force, then the path planning and control scheme will be designed at the torque level. The computer simulations and experiments in this chapter are based on a six-DOF planar redundant robot manipulator.The manipulator is operated and controlled by pulse signals transmitted from the host computer. Manipulator joints are operated by position- and velocity-controlled servo or stepper motors, and the resultant joint variables (i.e., joint angle and joint velocity) should be converted into pulse per second (PPS) for manipulator control. In consideration of these points, the former optimal control method, which is better suited and much simpler than the latter methods, is exploited to control the six-DOF planar redundant robot manipulator. A robot manipulator is said to be redundant when it has more DOF than necessary to perform a given end-effector task. The fundamental issue to operate such a redundant system is the redundancy-resolution problem. In recent decades, a favorable manner based on online optimization techniques has been applied to solving such redundancy-resolution problem and most of these optimization techniques can be formulated as a (time-varying) quadratic program (QP) subject to equality and inequality constraints. Furthermore, the constrained QP can be transformed into a system of piecewise-linear equations (PLE) and then solved by a number of methods and techniques. This back matter contains the references, and index

For several decades now, mobile robots have been integral to the development of new robotic systems for new applications, even in non-technical areas. Mobile robots have already been developed for such uses as industrial automation, medical care, space exploration, demining operations, surveillance, entertainment, museum guides and many other industrial and non-industrial applications. In some cases these products are readily available on the market. A considerable amount of literature is also available; not all of which pertains to technical issues, as listed in the chapters of this book and its companion. Readers will enjoy this book and its companion and will utilize the knowledge gained with satisfaction and will be assisted by its content in their interdisciplinary work for engineering developments of mobile robots, in both old and new applications. This book and its companion can be used as a graduate level course book or a guide book for the practicing engineer who is working on a specific problem described in one of the chapters. The companion volume for this book, Designs and Prototypes of Mobile Robots, is available separately. This front matter contains the series editors' preface, ASME press robotics engineering book series advisory group members, contributing authors, contents, and preface This chapter provides an overview of underwater robots and describes a method of generating aquatic propulsion, particularly interesting for underwater robots. The design and applications of biomorphic devices are described and illustrated. These design choices represent an important way to achieve attractive performance in navigation. This chapter presents a novel Lighter-Than-Air-Vehicle (LTAV), named Flying Octopus. It is comprised of a helium balloon, four independently controlled wire-driven flapping wings, and a midsection which connects the balloon and flapping wings (as well as housing all the electronics). Each wing is a continuous membrane, and can be bent up to 100 degrees by the wires. The wing flapping is generated by the bending motion. With proper control, the Flying Octopus can fly in 3D space freely, including vertical and horizontal movement. This chapter deals with visual attitude estimation in flying robots, and using this information to stabilize them. Unmanned Air Vehicles (UAVs) are currently in widespread use in many applications ranging from military operations to civilian tasks. Successful control of a UAV requires accurate and fast estimation of the vehicle attitude. Usually inertial navigation systems (INS) are used to obtain this attitude information in UAVs. As an alternative or as an additional sensor, vision systems can also be used to obtain vehicle states. Vision systems are readily available on various UAV platforms and can be used for this purpose. The use of vision for attitude estimation is reliable and affordable. In this chapter we present the use of a vision system that can be used to estimate vehicle attitude. Unlike previous works that use natural or artificial features such as blobs or parallel lines on the environment, this work involves the use of no special feature but the natural scene. Processing of this natural scene around the robot leads to attitude information which is used by the control algorithm to stabilize the robot. The vision processing and control are performed on board the vehicle using a vision computer. First, the algorithm, the UAV modeling and control are presented. A quadrotor flying robot is chosen as an experimental platform in this study. Second, a detailed presentation of the developed quadrotor system and experimental set-up are given. Finally, we present the experiments and the results of the estimation and control algorithms. This chapter provides a brief overview of modeling and control of multi-robot systems or simply robot swarms, from a dynamics and control perspective. First some commonly used agent dynamic models are described and some swarm coordination and control problems are presented. Then, commonly used control design approaches are summarized and some related swarm robotic applications are discussed. The chapter provides an extensive list of references to help the readers find detailed information on most recent key studies in the field. This chapter gives an overview of the applications of mobile ground robots for earth exploration. An introduction of the main examples and projects is given, followed by a short survey on the necessary related technologies. The chapter concludes with an example of an image processing algorithm adopted for autonomous navigation in complex outdoor environments.

For several decades now, mobile robots have been integral to the development of new robotic systems for new applications, even in non-technical areas. Mobile robots have already been developed for such uses as industrial automation, medical care, space exploration, demining operations, surveillance, entertainment, museum guides and many other industrial and non-industrial applications. In some cases these products are readily available on the market. A considerable amount of literature is also available; not all of which pertains to technical issues, as listed in the chapters of this book and its companion. Readers will enjoy this book and its companion and will utilize the knowledge gained with satisfaction and will be assisted by its content in their interdisciplinary work for engineering developments of mobile robots, in both old and new applications. This book and its companion can be used as a graduate level course book or a guide book for the practicing engineer who is working on a specific problem described in one of the chapters. The companion volume for this book, Mobile Robots for Dynamic Environments, is available separately. This front matter contains the series editors' preface, ASME press robotics engineering book series advisory group members, contributing authors, contents, and preface Walking robots are based on the mechanical structures of legs, in which mechanisms play an important role in functionality and performance characteristics. These robots have been developed with a wide variety of solutions over time. A short account of the history of using mechanisms in walking robots is presented in this paper, illustrated through significant examples and an explanation of primary concepts, with the goal of stressing challenges for future development. Robotics is a field of interdisciplinary research, and the development of its relevant disciplines has promoted its rapid progress in recent decades. Exoskeletons and bipeds, which are inspired by humans, have attracted many researchers. Exoskeletons, as the extenders of humans, can enhance a person's strength, power and endurance. They are usually utilized in the medical field to provide assistance for disabled people. Bipeds are capable of assisting humans to do repeatable tasks or to operate tasks in dangerous environments. The significance of studying these two kinds of robots is not only to break through the limitations of human capability, but also to gain a better understanding of human body. This chapter focuses on the history and key technologies of exoskeletons and bipeds. Some representative robots and mechanisms are described in detail. In rescue robotics, mobile robot platforms are used for search and rescue operations in the disaster zone. The design and realization of the robot from the idea to a working prototype require extensive knowledge and experience in mechanical, electrical and computer engineering. In the design and construction steps, mathematical calculations and manufacturing steps are carried out to realize the robot. Both digital and physical prototyping are explained and their differences and necessities are clarified. Later in the optimization stage risk analysis, functional conflicts, availability of materials, manufacturing capabilities and testing are considered and included in the design of a final prototype for better performance. This chapter explains the practice of rescue robot prototyping and the knowledge explained in this study can be applied to other mobile robotic fields. As network technologies have developed, networked control became a main research focus in mobile robots, as well as in many other applications. In this chapter, the advantages and the applications of networked control mobile robots are summarized. Furthermore, the chapter presents the main problems and achievements facilitated by the interplay between networked control, communication and perception. Control over the networks has to deal with drawbacks brought by network communication, such as delays and data loss. The mobility of individual robots brings new challenges to communication and perception. Further study is still needed in the coverage and localization problems of mobile sensor networks. A brief review of our Novel Robotics System for Planetary Exploration (NOROS) and some related works, such as the study of group behaviors, optimal routing design and wireless sensor networks localization, are also presented. This chapter presents a human-machine interface system for mobile robots to capture and replicate human posture. A motion replication system (MoRep) that captures whole body motion using inertia sensor-based measurement units is presented. Multimodal feedback enables users to replicate measured postures. Even though the robot market size is still small at this moment, applied fields of robotics are gradually spreading, from the manufacturing industry to the third industry, as one of the important components to support an aging society. However; the consistent drop in birth rate in developed countries is resulting in a reduction in the number of talented students. This represents a great challenge for universities to motive young people to study science and technology. In this chapter, a survey of basic and advanced mobile robot platforms for educational purposes, at both undergraduate and graduate levels, is given. In particular, the main educational objectives with mobile robots are summarized, and two examples of mobile robot platforms for educational purposes are described, with an example of their actual use at the university level. Finally, research challenges for designing the next generation mobile robots for educational purposes are pointed out.

Accuracy is one of the fundamental characteristics and one of the most important indexes of the quality of machines and robots. It significantly defines their structure and applications and, in turn, depends on their structure and applications. Accuracy provision, maintenance, and enhancement are permanently hot problems in modern manufacturing and manufacturing science. The book is being published in two volumes and comprises the Introduction and four parts including 19 chapters with consecutive numbering, and appendices consisting of codes for above mentioned problems. Each part combines a theoretical chapter with applications to machines and robots of different kinematic types. The formalized consideration is accompanied with application examples, which, as a rule, are explained with numerical solutions using realistic initial values. Volume II continues consideration of the accuracy-related problem as applied to machines and robots started in Volume I. Two themes are developed in Volume II: stiffness-compliance directly associated with the machine and robot accuracy through static deformations (Part I) and computer-aided metrology aimed at final assessments of the accuracy-associated performance indexes (Part II). Volume II is written as a standalone book in its own right and can be used without access to Volume I. The book is intended for machine and robot designers and researchers, university graduate and senior undergraduate students, and may be also useful for instructors in the mechanical engineering field for teaching processes. This front matter contains the series editors' preface, ASME press robotics engineering book series advisory group members, contents, foreword, and acknowledgement eBook keywords: mechanics of accuracy, computer-aided metrology, accuracy-related stiffness problems, actuators compliance-caused deformations, stiffness matrix, critical stiffness value, deterministic metrology of machines and robots, linear-programming procedure, 3-D dimensional chains, geometrical tolerancing problems. Elastic properties of dynamic systems of machines and robots, i.e., stiffness/compliance of the elements, connecting links, and supports, result in displacements of the system points and deformations of supports and elastic elements under external and internal loading. In turn, these displacements and deformations are manifested in deviations of actual positions and trajectories of system elements from the designed positions and motions. Mechanics of the serial kinematics machine can be represented as a multi-DOF kinematic chain combining some elastically connected links, and each link has 1-DOF in its nominal motion (translation or rotation) relative to the neighbor one. In this chapter, only the compliance of the most compliant elements of the mechanical systems – actuated joints along the directions of actuated motion – is taken into account. The purpose is to synthesize the compliance matrix connecting the external load with small displacements of the end-effector (EE). This process is started from formulation of the manipulator Jacobian matrix integrating geometric and kinematic data needed for transformation of the machine joint rates into the angular and linear velocity of the EE [1-4]. Any motion of a rigid body in 3-D space is accompanied with six small deviations along and around its six DOF in infinitesimal motions. Sources of these errors are considered in detail as applied to geometrical errors [1]. For the 6-DOF manipulators, the total geometrical error vector depends on (6 n + 6) components, where n is the number of links, among them only 6 errors are induced by actuated links. This approach is formulated through the variational method of accuracy calculation [2], which models any small displacement of the rigid body as a result of total variation of the nominal function (the form-shaping function [1, 2] fulfils the role of the nominal function as applied to machines and robots). Quality control of machines with heavy demands on accuracy and productivity, such as machine tools, coordinate measuring machines, and industrial robots includes stiffness testing as a regular stage [1, 2]. The testing methods are fixed in national and international standards, which quantitatively limit the minimal effective stiffness value. For example, the standard stiffness test for a universal lathe includes measuring radial and axial displacements of the main spindle caused by given active radial and axial force, respectively. For a given pair “force vs. linear displacement” or “torque vs. angle-of-rotation”, the stiffness value has a simple definition as the ratio of the absolute values of the force (torque) to the linear displacement (angle-of-rotation). The same approach presenting stiffness mapping [3] is regularly applied for stiffness control of the parallel kinematics machines (PKMs) such as hexapod-based and tripod-based machines [4–7]. The application area of the collinear stiffness value (CSV) developed for the static case [1, 2] can be extended to dynamic characteristics of the mechanical system modeled as a massive rigid body (platform) on elastic supports in a current configuration [3]. Here, this approach is applied to evaluation and optimization of the dynamic stiffness of undamped systems using a modified CSV index named the dynamic collinear stiffness value (DynCSV). The minimal value of the DynCSV is used for limitation of the machine and robot workspace and frequency bandwidth. The most important aspect of the proposed approach is that it allows construction of a virtual protective barrier preventing, if necessary, approaching the resonance zone. In the dynamic case, the CSV-based index can be applied taking into account that: The dynamic-related characteristics become both configuration- and frequency-dependent; The zero values of the DynCSV can take place not only in singular configurations as in the static case, but also when a statically regular configuration (with w = 0) falls within one of the natural frequencies; The derived method allows a natural evaluation of the dynamic stiffness for the general case of loading, i.e., for any combination of decoupled translational and angular vibrations. Hence, the allowable workspace of the robot can be limited using the stiffness values instead of traditional methodology when approaching the vicinity of the resonance zone is limited based only on a distance (expressed in w-terms) from the natural frequencies; The DynCSV presents a convenient optimization tool using stiffness-related properties under the general case of the loading, since it estimates the dynamic properties over the entire bandwidth forced frequencies including the natural frequencies, while application of the natural frequencies is an excellent tool for establishing conditions resulting in zero stiffness values, but unsuitable for stiffness evaluation in other conditions. A modern 3D metrology employs measurements on coordinate measuring machines (CMM) for obserThe minimum zone problem in Mathematicaation of actual features (AF) [1–3]. The measurements present initial data for estimation of the geometrical accuracy, and a key step of the estimation process is an optimization procedure. Over a long period of time, only the least mean square (LMS)-based assessments were applied. Nowadays international and national standards for geometrical product specification use the minimax optimization criteria formulated through the tolerance zone limiting the possible location of results of measurement. The zone is formed by one or several geometrically perfect boundaries (lines or surfaces) and featured by minimum value of a single tolerance geometrical element. The results of measurement must lie between or at the boundaries of the minimal zone (MinZ), called tolerance zone. Synthesis of the substitute feature (SF) is shown in the previous chapter to be a necessary step in building the tolerance zone for standard assessment of geometric accuracy [1–3]. Since the SF must be of perfect form, its synthesis uses information about the nominal feature (NF) and includes the deviations leaving the feature shape unchanged – the size, position, and orientation deviations (SPOD). Evaluation of the SF parameters is carried out using the actual feature (AF) data resulting from the point-to-point coordinate measurements of the AF on coordinate measuring machines (CMM). Thus, the SF concentrates the information needed for verification of the manufactured workpiece – information about the NF from the drawing and information about the AF in the form of results of measurements. The term “dimensional chain” (DC) is a fundamental concept related to the tolerancing of size, form, and position of features in machine parts and whole systems relating to different manufacturing stages: design, process planning, machining, measuring, and assembling. Formally, the DC presents a single loop of (linear and/or angular) dimensions, one of which is a closing link (closing dimension) and the others are input dimensions. Thanks to its closeness to the engineering design process and engineering metrology, this concept is successfully used for the establishment and observance of tolerances. This back matter contains the appendices, abbreviations, about the author, and index

The International Conference on Control Engineering and Mechanical Design (CEMD2017) is a leading annual conference for all researchers in China and abroad. Along with an exciting exhibition, CEMD2017 was held in Xiamen, China, October 20-22, 2017. Control engineering or control systems engineering is the engineering discipline that applies control theory to design systems with desired behaviors. Mechanical engineering is the discipline that applies the principles of engineering, physics, and materials science for the design, analysis, manufacturing, and maintenance of mechanical systems. It is the branch of engineering that involves the design, production, and operation of machinery. It is one of the oldest and broadest of the engineering disciplines. This front matter contains the table of contents and preface and is available for free viewing by clicking on the PDF below. eBook keywords: control engineering, automation, mechatronics, mechanical design, digital manufacturing, machinery, robotics, CIP, underactuated linkage mechanism, turbine burner, rail wear measurement, driving torque. The stability, production and coke consumption rate of the blast furnace may be greatly influenced by the uniformity of coke size. Therefore an automated system to measure and estimate the coke size is needed. In this paper, a computer-based vision system was established to acquire coke image by using a CCD camera. A digital scheme that combines various digital image processing techniques was developed to detect the edge of individual coke properly from the coke image. Then a novel approach was proposed to find the minimum width (coke size) of the detected coke shape by using the area moment of inertia principle with rotational search. The system developed was tested on various size of real cokes which include large (>70mm), middle (35∼70mm) and small (<35mm) size coke. The results show that average error of the coke size detected from the coke image was less than 10%. However, the average error of coke size between the detected coke and the real three-dimensional coke could be higher to 20∼30%. Further modification of the measured data by using statistics of the average difference of coke sizes reduces the error to about 10%. The feasibility and usefulness of the system is demonstrated. It is very crucial to have a monitoring system for the elderly people behaviour in case of emergency such as when they fall. Thus, automatically monitoring abnormal activities of the elderly using surveillance cameras at home is very important to home-care and health-care industries. In recent years, falls amongst the elderly are particularly serious and often lead to injury, restricted activities, fear of death. It was shown that many elderly people in the community experience at least one fall every year, and most of the falls lead to injury. In this paper, we propose an automation detection method for abnormal fall to help the elderly to obtain in-time medical treatments as well as identifying reasons of incidents. In this paper, we study moving objects detection in complicated traffic crossroad scenes and put forward a new approach which combines background updating and spatiotemporal saliency detection. When dealing with complex scenes, the learning rate of background updating can not be set too high, which leads to delayed background updates. On the other hand, current spatiotemporal saliency detection can not only detect the moving objects, but also detect the static and odd objects. To solve this problem, we firstly propose a new set of spatiotemporal saliency feature to eliminate the influence of static and odd objects, and then combine the spatiotemporal saliency map and Gaussian mixed model foreground to obtain the final foreground mask. The experimental results show that this approach has better performance than Gaussian mixed model and spatiotemporal saliency detection in moving objects detection. There would be a variety of grasp configurations when underactuated hand enveloping grasp the object, and most configurations are unstable which presents the object away from the fingers. The disadvantages of the hand’s stability based on the grasping kinematics are considered. The relationship of the geometrical parameters of the phalanges and the grasp stability is deduced. The method to determine the main geometrical parameters of the underactuated hand which could be competent to grasp the object is proposed. The experimental study on the three joint linkage underactuated hand which has been developed is carried out, which demonstrates the effectiveness of the method. Continuum Robot has become a hot spot at present. But there are still some changes, such as difficult to control, low bearing capacity, too many drivers. We make a deep research on the continuum robot for these problems, and proposed a novel robot basing on scissor mechanism, which has one translation and two rotation degree of freedom. The six units of the robot are only driven by three motors, which has high bearing capacity, large workspace, fast response, flexible motion characteristics. We design the scissor robot and carry out kinematics analysis and simulation. The research in this paper enriches the configuration of continuum robot. The Wavelet Analysis is one of the important analysis ways for the signal processing after Fourier analysis and it has wide applying prospects in the fields of modern science research and technology. This paper gives an improved wavelet threshold de-noising algorithm based on the analysis of the traditional hard and the soft function. This optimal method has better flexibility, higher SNR and smaller MSE than the hard and the soft algorithms through relevant simulation activities which prove the improved function works well. In this paper, we studied a new type of underactuated elephant trunk robot(the ET robot) used unconventional scissors mechanism, and put forward a kind of method in order to make the mechanics calculation of the scissors mechanism easier. Using this method can remarkably reduce the analysis work of the mechanics calculation, improve the efficiency of analysis, and highly reductive motion of the robot. To verify the validity of the simplified method, we used the automatic dynamic analysis of mechanical systems-the ADAMS to carry an simulation of the ET robot when grab a cylinder before and after use the simplified method. The simulation results show that the simplified method not only can reflect the robot’s motion status but also effectively reduce the calculation time required for analysis. Blind signature is an important cryptographic notion and it has been designed for data authentication in many scenarios such as digital currency, electronic voting. In this paper, we present an attribute based partial blind scheme (AB-PBS). We achieve fine-grained authentication by adopting the properties of attribute based signature. Furthermore, the signer and user can reach an agreement on some certain information in advance, which can prevent the illegal usage of blind signature. By security analysis, our AB-PBS is proved to be satisfied with blindness of unforgeability. A lot of new devices, techniques and architectures have been developed for the next generation of wireless networks (5G), which is positioned to address the demands and business contexts of 2020 and beyond. In this way, similar 5G use cases can be served by one 5G slice and dissimilar ones by different slices. This fact may lead to resource costs because similar 5G use cases also have distinctions and one 5G slice should meet all the requirements. What is more, 5G slice maintenance may also bring some resource costs. Therefore, we propose an optimization model to determine the appropriate number of 5G slices: K, aiming at minimizing the total resource costs. In order to solve this problem, a new distance is proposed and a clustering algorithm is developed. According to the data from different organizations, we compare our clustering algorithm with hierarchy clustering algorithms. The experimental results show that our algorithm can outstrip other methods in determining the number of 5G slices. The conventional Ultra-compact Combustor (UCC) has obvious temperature distortion at the outlet section, which adversely affects the low-pressure turbine rotor blade working in the Interstage Turbine Burner(ITB). In order to solve this problem, the addition of a circumferential struct located on the upstream channel in the circumferential cavity. Disturbance occurs when the main airflow flows through the circumferential struct, enhance the main airflow and circumferential cavity combustion mixture mixing, make combustion reactions more complete, promote high temperature airflow in the circumferential cavity flowing into the main airflow and improve the outlet temperature field. Numerical simulations were conducted on an UCC configuration with circumferential struct. The feasibility of using circumferential strut to improve outlet temperature field of UCC was investigated and design angle optimization of circumferential strut was carried out. The results showed that circumferential strut with angle of 18 degrees could not only effectively improve outlet temperature distribution, but also make UCC obtain good performance of high combustion efficiency and low pollution emissions. An evaluation method of image quality of a video surveillance system is proposed. A test card is designed to evaluate two key indicators which are image definition and coverage range. As an important technical defense means, video surveillance systems have widely been built in important areas to finish many functions, such as security monitor, record and active alert. However the practical use effect is not satisfactory because most of the evaluation methods are developed to evaluate camera performances at laboratory environment. When cameras have been installed on-site, those evaluation methods cannot be work. The test card and related evaluation method proposed in the paper combine the objective and subjective method of image definition evaluation method. They have been used in airports and achieved desired results. The fault diagnosis of rolling element bearings (REB) has attracted substantial attention recently due to its importance for the bearing health management. The methods based on empirical mode decomposition and intelligent classification are widely used for REB fault diagnosis. However, there still exists two shortcomings in the fault diagnosis methods: 1) A large amount of redundant information is difficult to identify and delete; and 2) Aliasing patterns decreased the classification accuracy. To deal with these two shortcomings, an improved fault diagnosis method based on rough set and dependent feature vector (RS-DFV) is proposed in this paper. In RS-DFV method, the dependent feature vector (DFV) is used to optimize the feature set, excavate the essential difference among REB faults and improve the accuracy of fault description. Moreover, rough set is utilized to reasonably describe the aliasing patterns and overcome the problem abnormal termination in DFV extraction process. In order to demonstrate the effectiveness of the improved method, a simulation and four fault diagnosis methods are utilized for the REB fault diagnosis. The results shown that the RS-DFV method is able to select an appropriate feature set, deeply dig the effectiveness of the features and more exactly describe the aliasing patterns. Consequently, it performs better in REB fault diagnosis than the original intelligent methods. In this paper, a single wheel robot that runs on a flexible wire was investigated, and the primary concern was about the influence of the wire’s stiffness on the system’s input torques. The robot was characteristics with a couple of parallel swinging arms and a rotational pole. Considering the pure rolling condition of the single wheel running on the flexible wire, a dynamical model was developed for the system by Lagrange equation. With the model, inverse dynamics was simulated referring to different wire’s stiffness. The results show that, the different wire’s stiffness would correspond to different driving input torques, but there would be a peek torque at a certain stiffness. The work should offer a useful reference for the driving motors’ selection of the robot system. In this paper, the pressure distribution and velocity distribution of gas turbine inlet pipeline are the results from modeling, meshing, setting boundary conditions, numerical simulation of gas flow on gas turbine inlet pipeline with FLUENT, which reflect the velocity and pressure of the airflow while flowing through gas turbine inlet pipeline accurately, and help to find out the main cause of the pressure loss and provides accurate and reliable reference for the design of gas turbine inlet pipe. The rail wear measurement has its importance on the maintenance of railways, and data acquisition and processing are crucial tasks for rail wear measurement. Rail wear directly influences wheel-rail contact and life of rail tracks, so accurate and effective measurement of rail wear is a continuous demand. In this paper, a structured light data acquisition system is developed, and a data processing method for the alignment of point clouds from structured light scanning and CAD model of the rail is proposed for rail wear measurement. For the alignment of the structured light data and CAD model, random points sampling from CAD models is conducted to generate enough points for point clouds registration. In the coarse registration, the curvature of the rail profile is utilized for the point feature histograms(PFH) generation. In the fine registration, the points on different surfaces of the rail are employed by the ICP algorithm. To find more effective registration means, the analysis from software Geomagic Qualify is compared. It reveals that the surfaces on the rail with less or without wear are more suitable for fine registration. Dynamic topology optimization of continuum structures using the hybrid cellular automata method is presented in this paper. The objective was developed by minimizing the dynamic compliance to reduce vibrations of structures. The total structural volume is taken as a constraint. The dynamic topology optimization model of continuum structures subjected to harmonic loading was established. The hybrid cellular automata method is adopted to solve the optimization problem. The proportional control law is used as a local rule to determined the local change in the design variable. The numerical examples are presented to show the feasibility of the proposed approach. In recent years, the illegal use of apartment power has caused major disasters, it is of great significance to study the correct identification of illegal electricity and control technology in real time. In this paper, a technology that using wavelet analysis to analyze waveforms of various loads is proposing, through analytical processing with Matlab, the malignant power load and general load can be distinguished, which can get difference between various capacitive, inductive, and resistive load’s waveforms. It is of great importance to campus apartment for automatic recognition of malignant load, and then to prevent campus fires. In recent years, with the increasing demand for blasting work, a variety of blasting methods have been applied to the blasting work, but the manual placement of explosives to some extent is risky. There are hundreds of casualties in blasting every year in the world. The technology of a remote installation of explosive materials needs to be studied and applied urgently. This paper presents a controllable mobile blasting scheme based on the six-legged robot structure. Its application of the core control technology is based on the Android system, remote video surveillance technology. In the temporary build of the local area network, only an Android mobile client will be able to operate with the explosion of the six-legged robot to reach the designated area. The test for the six-legged robot we made has been able to complete the barrier function. Overall, the system has a portable, easy to operate and so on. The application of this technology in the future will greatly improve the safety factor of the blasting work. In this paper, we propose a scheme of an interactive music game installation based on an open-source electronics platform called Arduino. The software called Vixen is implemented to communicate with the Arduino board, which can analyze the music you choose and make the LED strip shine follow the beat. Six drums are prepared for players to interact with the game, with the objective to make the correct beat at the correct time in relation to the music. Players receive both visual and audio feedback to help them make correct beat. The beat is detected by piezoelectric ceramic vibration sensor and the score is shown on the LCD screen. Some micro-pumps will spray water follow the rhythm as well to increase the visual effect of the game. We also discuss the evaluation of players using this installation. More and more satellites need deployable satellite platforms for on-orbit maintenance and equipment upgrades. This paper provides a kind of deployable truss-type satellite platform. Driving by a motor and two sets of fold-unfold mechanisms, four folding plates of the satellite platform can be folded or unfolded. By using D-H method and ADAMS, the kinematic model of fold-unfold mechanism is established. Some kinematic parameters such as angular displacement, angular velocity and angular acceleration are calculated to verify the smoothness of deployment process. By using ANSYS Workbench, the modal analysis and harmonic response analysis are performed. Dynamic analysis results show that the proposed satellite platform has good stiffness and strength in vibration environment. Due to the inevitable mass imbalance relative to the gimbal rotation center, the stability of stabilized platform system degrades with carrier’s disturbances. The dynamics model of 2-axis stabilized platform is given. An imbalance torque observer based on Extended Kalman Filter(EKF) method is been designed. The simulation result indicates that the error of EKF parameters estimation is less than 0.015mm after 0.4s convergence time. The observation accuracy is about 17% relative to the real imbalance torque. The paper presents a linear model of time-cost optimisation which can aid in the process of the selection of the order of the construction of structures, as well as during the development of a timetable of a multiple-building construction project by a general contractor. The proposed model takes into account indirect costs, direct costs, contractual penalties associated with discontinuous work by work brigades, contractual penalties associated with failing to meet directive deadlines, as well as rewards for completing a structure ahead of a directive dead-line. In order to analyse various orders, the authors used the bruteforce method. The operation of the model has been presented on a calculations example. A lowering of the total costs of the carrying out of a multiple-building construction project equal to a level of 2-5% in comparison to a random solution has been obtained. The model can be useful during the negotiation of directive deadlines or the size of the contractual penalties for delays and rewards for completing a project ahead of schedule. This paper describes the implementation and using of NI myRIO device in renewable energy sources and mechatronics applied in medicine domains. Through the developed applications is shown how the same device and programming technique can be used at educational, research and industry level covering energy and mechatronics domains. We introduce Yasuura’s method of modal expansion taking a simple problem of diffraction by a periodically modulated plane (i.e., a grating) simulating a metamaterial and the surface profile should be determined so that the grating carries out its purpose as a metamaterial. Yasuura’s method would be useful in finding the grating parameters because it is an easy and reliable way of solving boundary-value problems to the Helmholtz’s equation which dominates the grating phenomena. Rolling is a regular method for production of metallic parts in various shapes and sizes. In this method, the raw material place between two rigid rolls and take the shape and size. There are two rolling methods, hot rolling and cold rolling. To achieve higher mechanical properties, and better surface quality and dimensional accuracy, the hot rolled sheets undergo the cold rolling process. The friction between the metal and rolls effects the forming process, increase the required load for forming, reduce the surface quality and increase the wear of tools. The simulation of rolling process will be helpful to improve the forming procedure and quality of products. In this research, the finite element method is used to modeling, simulation and analysis the rolling of St 37 steel sheets in normal friction plane strain conditions. Because of stress strain behavior of material during the forming process and increase of frictional stress due to forming process, the analysis of forming load between the contact surface of rolls and sheet are shown by simulation. Based on the grinding movement relationship of rake and flank face of ball-nose end mill, make use of SolidWorks software for development platform, and took advantage of Visual Basic 6.0 to develop the grinding simulation system and parameters analysis system of ball-nose end mill. Grinded the simulation of the rake face of ball-nose end mill and obtained ideal cutting edge curves. Effect of grinding wheel diameter change on cutting edge curves of ball-nose end mill was investigated and the effect has rarely influences, so as to guide the actual production of ball-nose end mill. The perfect molding must have stability and dexterity, so “stability and dexterity” is the rule that the molding design of farm machineries have to observe. The stable product molding give person with safety, steady heavy felling, has the aesthetics characteristic of the majesty, magnificence, grandiosity and strength. The dexterity product molding give person with lightness, clever felling, has the esthetics characteristic of the vividness, cordialness, motion and liberality. To shape the farm machinery products have stable and dexterity, the several aspects should be carried out from center of gravity of the object, center of visual sense, area of bottom, line’s partition, relation between size of the objects, color distribution to material texture ect., to make their molding give the person beautiful enjoyment while satisfying their function. For improving the reliability and efficiency of the dynamic modeling and analysis for 3-RSR spatial parallel robot mechanism, the corresponding vector bond graph procedure is proposed. By assembling the vector bond graph model of spatial moving rigid body, spatial revolute joint and spherical joint, the vector bond graph model of 3-RSR spatial parallel robot mechanism is made. By effective augment method, the algebraic difficulty brought by differential causality and nonlinear junction structure in the automatic modeling of this spatial parallel robot mechanism is overcome. As a result, the computer automatic dynamic modeling and analysis of 3-RSR spatial parallel robot mechanism is realized by the corresponding algorithm, and the reliability and validity of the procedure proposed is illustrated. Titanium alloy is widely used in human bone as a metal with better compatibility. To investigate the material mechanical properties of medical titanium alloy Ti-6Al-4V ELI, many types mechanical experiments have been carried out. These experiments include hardness, elasticity modulus, tensile experiments. The stress-strain curve has been obtained by the different temperature tensile tests. The results will provide the theory basis for the use of medical titanium alloy Ti-6Al-4V ELI. An input filter is very important to MC, which is used to improve grid side current waveform quality and to filter high harmonic components, as well as to reduce input voltage distortion supplied to the grid side. Because of the effect of the input filter and output power, grid side power factor (PF) is not at unity when input power factor angle is set 0. In this paper the displacement angle between grid side phase current and phase voltage is analyzed. Based on this a new grid side PF at unity compensated strategy is presented. Simulation results indicate that the proposed PF at unity compensation method has good performances and is feasible. Recently, airbags coupled with parachute mechanisms have been deployed in Unmanned Aerial Vehicle (UAV) crash landing recovery systems to attenuate and bring down the imparted shock within allowable structural limits. Platform is decelerated by bag deflation through orifices which itself is under compression by platform. Dynamics of this process depend on the shape and volume of the airbags. A number of airbag shape designs have been analytically modeled to predict critical parameters like platform deceleration, gauge pressure, platform descent speed and bag height; however, no such mathematical formulations are available for the bi-cylindrical airbags. This work entails the development of analytical model for the dynamics involved in UAV landing through bi-cylindrical airbags and its implementation in numerical simulation. Results for a number of airbag sizes and orifice sizes are shown and discussed. Future roadmap for experimental testing is also outlined in the end. This Metrological conditions like icing and rain have been the cause of many aviation accidents due to aerodynamic performance degradation. In this paper icing and heavy rain effects on the aerodynamic performance on GLC305 have been studied. For icing effects study, GLC305 airfoil clean and with 16.7min ice shape (rime 212) and 22.5 min ice shape (glaze 944) is used. For rain modeling, Discrete phase modeling (DPM) has been used to incorporate the rain effects in continuous phase using two phase flow approach. In DPM two phases coupling and its impact on both the phases has been included. In DPM, the wall film is modeled by the injected rain particles in continuous fluid phase of air. GLC305 airfoil showed a significant decrease in lift and increase in drag in simulated Icing and rain environment. In our study it is found that the Icing and heavy rain causes premature boundary-layer transition at low angle of attack (AOA) and separation at high AOA. The water film layer on the surface of the airfoil formed due to rain and the icing on the leading edge of airfoil due to super cooled water droplets are thought to alter the airfoil geometry and increase the mass effectively. It is strongly believed that simulating the icing and rainy conditions combined may help us understand the effects of complex and severe weather conditions on the aircraft performance and maneuverability. This paper focuses on the characteristics of the complex structure and assembly level of aircraft, expounding the method of implementing the dimension engineering, emphasizing the importance of establishing the dimension engineering system under the background of digital manufacturing, and introduces how the dimension of the whole design and production stage is implemented in detail. With the combination of the actual production situation and the theoretical knowledge, the paper introduces and studies the dimension engineering method from the angle of design and production. The proposed method can be applied to the pre-size design of the aircraft parts. At the same time, it can solve the existing dimension problems quickly under the idea of the dimension engineering system and to carry out program evaluation and forecasting of the existing plan. Because of the complex roll system of the 20-High Sendzimir mill, the calculation of the driving torque is different from the 4-High or 6-High rolling mill, except the rolling torque M R , the friction torque M f cannot be ignored, and the friction torque M f is consist of the friction torque caused by the rolling friction between the rolls M f R and the friction torque to overcome the friction in the backing bearings M f B . On the basis of the force analysis of the roll system, the driving torque of the 20-high Sendzimir mill was calculated and analyzed, include the torque M R , M f , M f R and M f B , the composition and distribution law have been gained; what’s more, the contact stress between rolls was also calculated, these are significant for the design of the 20-High Sendzimir mill. With the development of aircraft structure and technology, the coordination accuracy of aircraft manufacturing is becoming more and more stringent. Therefore, it is an inevitable trend to use the digital means to carry out tolerance analysis and realize process optimization. the paper introduces and studies study the deviation analysis and tolerance optimization theory of aircraft component assembly. Based on the software simulation analysis, we can solve the problem of dimension engineering in the actual manufacturing, and optimize the assembly and coordination requirements of winglet. The results show that the application of this theory and technical method improves the process scheme of the winglet and improves the quality of assembly, improves the efficiency of assembly and coordination accuracy analysis, and has certain engineering application value. The valve of a certain type of APU often didn’t close with abnormal vibration noise when it testing under the specified pressure.This paper ensured the key cause of fault and opening range change due to valve structural parameter change by structural principle study, theory character analysis of circular frequency, Fluent simulation analysis and test inspection on-site, the result showed which can change close pressure and opening rate range of the valve by means of control the depth of valve shell, by which can gain the better noise and vibration reduction effect, it is significant and acting to remove this kind fault and optimize valve structure of design. Focusing on the nonlinearity of the relation between mechanical properties and the fabric drapability, a BP neural networks model as well as a support vector machine model are proposed to process the relationship mapping mechanical parameters to the fabric drape function and predicts the fabric drape coefficient. In the case of silk fabric, both the proposed SVM and the BP neural networks can realize excellent performance with respect to the drapability evaluation and prediction. Simulation experiments show that the SVM evaluation model outperforms the BP neural networks model when predicting the drape coefficient even though its approximation capability is less than BP neural networks model in the procedure of learning. The paper independently designs a new extrusion-type 3D printer based on FDM process. Its mechanical parts adopt high-precision ball screw-driven slide unit of gantry three-axis platform structure. The paper also conducts selection and calculation of mechanical parts, and designs a special extrusion mechanism by combining with characteristics of viscous liquid materials. The design effectiveness is finally verified through experiments. Cam mechanisms are popularly used in industry to provide simple ways to achieve different motions, especially for some unusual, irregular or difficult motions. The simple harmonic motion is widely applied in cam mechanism since the design is very simple. In this work, the cam mechanism of a simple harmonic motion is proposed for a practical case. At the very beginning, the cam profile is given to modeling the 3D cam model. Subsequently, the performances of the cam are analyzed in Pro/E and Adams, respectively. The results show the proposed cam mechanism has a good performance. In this investigation, a flexible beam with rib geometry is analyzed through an integration method of localized surface geometry. The main purpose of this analysis is to verify the effect of different shapes of the rib to the properties of the flexible beam. During the modeling process, the ancf beam element is used to define the global geometry and the rib geometry can be defined on the ancf beam element through overlapping method. The Non Uniform Rational B-spline Surface ( nurbs ) is utilized to represent the localized surface geometry, since it can describe the curves and surfaces accurately. Subdomain integration method is employed during the integration process. When performing the analysis process, the properties of the flexible beam is analyzed with different shapes of the rib. The shape of the rib is defined by five parameters. After analysis process, the effect of the rib shape to the properties of the flexible beam can be verified through the analysis results such as node displacement, compliance and stress of different rib shapes.

Accuracy is one of the fundamental characteristics and one of the most important indexes of the quality of machines and robots. It significantly defines their structure and applications and, in turn, depends on their structure and applications. Accuracy provision, maintenance, and enhancement are permanently hot problems in modern manufacturing and manufacturing science. The book is being published in two volumes and comprises the Introduction and four parts including 18 chapters with consecutive numbering, and three appendices. Each part combines a theoretical chapter with applications to machines and robots with different kinematic types. The formalized consideration is accompanied with application examples, which, as a rule, are explained with numerical solutions using realistic initial values. Volume 1 includes Introduction, Parts I and II (Chapters 1-12), and hence, embraces the general accuracy definitions, nominal machine functioning models, and geometrical accuracy problems. Volume 2 includes Parts III and IV and is available separately. The book is intended for machine and robot designers and researchers, university graduate and senior undergraduate students, and may be also useful for instructors in the mechanical engineering field for teaching processes. This front matter contains the series editors' preface, ASME press robotics engineering book series advisory group members, contents, foreword, and acknowledgement. eBook keywords: mechanics of accuracy, accuracy models, nominal machine functioning, serial-kinematics robots, hybrid kinematics machines, Gough-Stewart platform, inverse kinematics, Cartesian robot, error budget, machine accuracy, and robotics. The word “accuracy” has a wide spectrum of everyday applications. “Merriam-Webster’s Online” dictionary defines the accuracy as: (1) freedom from mistake or error, i.e., correctness; (2a) conformity to truth or to a standard or model, i.e., exactness; (2b) degree of conformity of a measure to a standard or a true value; this meaning is close to precision . A working machine (WM) presents equipment (assemblage of parts) transmitting energy, materials, and information by means of controlled mechanical motions with the purpose to displace, replace and simplify physical and/or intellectual works of manual and non-manual workers as well as increase productivity and quality of the manufactured products. Typical representatives of the WMs are industrial robots (IR), machine tools (MT), and coordinate measuring machines (CMM). As modern machinery is developed, automation and computerization level of the WMs is increased to improve such important performance indexes as productivity, accuracy, flexibility, universality, effectiveness, etc. As a rule, it adds complexity to the WM kinematics, drives, and control system: the number of operation-required motions increases and their interrelationship becomes more involved. The mathematical model of the rigid body presents the Cartesian coordinate frame S ≡ OXYZ associated with the body (Fig. 3.1). The origin O and the X -, Y -, and Z -axis are usually associated with the mechanical and manufacturing bases of the link, such as guideways surfaces, axes, accurate planes and cylindrical surfaces, local supports, etc. The point K of the rigid body (Fig. 3.1a) is defined through the Cartesian coordinated x K , y K , and z K presenting elements of a position vector: Pose coordinates of a rigid body define the position and orientation of the body in space, and relationships between a pose of the output link of machine or robot and corresponding parameters of the actuators presents a key-step of position analysis. Vector X describing the pose has six or three elements depending on whether the considered problem is spatial or planar, respectively In the two past decades, the parallel kinematics mechanisms (PKMs) have received wide acceptance for the design of robots and machines of different types. In these mechanisms, the output link – end-effector (EE) – usually presents a multi-degree-of-freedom platform (Fig. 5.1), which is directly and simultaneously (in-parallel) connected with another link (e.g., a fixed base) through several independent kinematic chains. Two parallel chains together with the base and platform form a kinematic closed loop. This fact explains the presently accepted definition of a generalized parallel manipulator, a closed-loop kinematic chain mechanism whose end-effector is linked to the base by several independent kinematic chains [1]. It should be emphasized that introducing the PKMs into real engineering projects has been made possible only by the simultaneous emergence of the modern computerized control systems. The goal of the kinematic setup is to express the ( n+M )parameters q 1 , q 2 ,…, q n+M of the FSF through parameters of the target element (machined workpiece, measured part, assembled parts, etc.). In robotics, this procedure is known as the inverse kinematics problem , whose solution has been studied in detail during past decades. Industrial robots, modern machine tools and CMMs are produced as flexible machines for multifunctional applications to provide a wide spectrum of technological operations. As is customary in high-technology equipment, two interrelated tools are applied to provide flexibility and multi-functionality: The FSF of the planar 3-DOF RRR robot-manipulator (Fig. 7.1) consists of six links ( n = 6), among them three kinetmatic links rotating around the parallel axes and three geometric links fixing the distances between parallel axes. According to Eqs. (4.16-20), the FSF of the robot is Actual machine motions are inevitably accompanied by small non-designed deviations of position and orientation of all the links, relative to each other. The sum of the elementary errors together with their transfer coefficients presents the error budget [1]. The number of the errors associated with all interacting links is several dozens, and an effective way to analyze their contribution to the machine accuracy and precision is formulated as total variation of the FSF [2]. In this chapter, a linearized mathematical model for a budget of geometric and kinematic errors suitable for the FSS of serial-, parallel-, and hybrid-kinematics machines is described. A 1-DOF translational link, also called a linear joint or reciprocating joint, realizes a function of a prismatic kinematic pair and presents one of the basic units of different machines and robots. The link provides the 1-DOF translation by means of an actuator and constraints nominally preventing the relative movement along and about five DOFs. A triplet of linear stages performing the XYZ motions arranged in series presents a regular part of the 3-D Cartesian robots, coordinate measuring machines (CMM), milling machines, CNC milling and machining centers, etc. To provide high stiffness, accuracy and precision, and loading capacity, the linear guideways, also called linear motion bearings, are widely applied. In feed units of machine tools, the most widespread structure of the linear motion stage is a slider actuated by a motor-driven ball screw and moved along prismatic guideways of different forms (Fig. 9.1). Here, three types of prismatic guideways are shown: flat guideways, combined guideways (a set of flat- and V-form), and double V-form guideways. To clear up an interrelationship between the nominal displacements and their deviations in the accuracy-related formulae, the links of the 2-DOF manipulator are renumbered as is shown in Figure 10.1. In these terms, the manipulation matrix, Eqs. (4.7), becomes Consideration of the position error problem uses the models entered for solution of inverse kinematics for parallel-kinematics machines. Obviously, an actual motion of the moving platform of the l i -DOF mechanism ( l i = 2 ÷ 6) is accompanied with the same sextet of position-orientation errors δ xi , δ yi , δ zi , δ θi , δ ψi , δ φi , composing the twist δ for 1-DOF body. Since the set of drives of the moving platform is simultaneously served as a movement issue and as a suspension system, the moving platform can be modelled as a rigid body on six rigid supports whose supports are the limbs. Hence, the solution obtained for the guideways accuracy (Subsection 9.1.2.3 ) can be applied to the position accuracy problem of the moving platform of the parallel mechanism taking into account that: The error budgeting technique presented in Chapter 8 and developed in Chapters 9-11 uses linearization of trigonometric functions realized through the standard error matrices E , Eq. (8.9). However, in studies of accuracy problems, there are specific cases in which the linearization technique is unsuitable for accuracy calculations, and a non-linear problem has to be solved. There are two main groups of such situations: This back matter contains the appendices, abbreviations, index, and about the author

This proceedings publication includes papers and abstracts from a dedicated track focused on Multidisciplinary Engineering, at the November 2015 International Mechanical Engineering Conference and Exposition (IMECE 2015). Innovative solutions to large-scale, complex engineering problems are no longer confined to a particular discipline of science or engineering. Optimal solutions often require a multidisciplinary approach that draws on various concepts and knowledge base in an iterative process. The objective of these papers and abstracts is to highlight the importance of the multidisciplinary approach. This proceedings covers Mechanical Behavior of Materials, Tribology, Cutting Tools and Machining, Polymer Processing, Axiomatic Design, Complexity Theory, On-Line Electric Vehicles, Mobile Harbor and Multidisciplinary Engineering Education. This front matter contains the dedication, preface, acknowledgements, and table of contents. This proceedings publication includes papers and abstracts from a dedicated track focused on Multidisciplinary Engineering, at the November 2015 International Mechanical Engineering Conference and Exposition (IMECE 2015). eBook keywords: multidisciplinary engineering, mechanics, materials, tribology, cutting tools, machining, polymer processing, axiomatic design, complexity theory, on-line electric vehicles, frictional torque, manufacturing. This symposium honors Prof. Nam Pyo Suh, a researcher, teacher, and leader of extraordinary creativity. The theme of the symposium, multidisciplinary engineering, recognizes that contemporary technological problems are rarely solved through the tools of a single discipline. Rather, one must combine knowledge, techniques, insights and approaches from many traditional disciplines to create effective solutions to today’s problems. The multidisciplinary theme also highlights the wide range of Prof. Suh’s own work. In fact, one can view Nam P. Suh as one of the earliest multidisciplinary engineers. The many seminal contributions made by Professor Nam P. Suh to the theories of wear, such as the delamination wear and the solution wear, are well known. The contributions made by him and his associates to the theories of friction, however, are less known; but they are equally significant. In this article, I first briefly survey, to provide an historical context, the laws and theories of sliding friction as proposed over the past centuries and decades. Then the contributions of Prof. Suh and his associates in recent decades are reviewed. Specifically, the role of wear particles in the frictional phenomena of dry and boundary-lubricated sliding is examined. A novel concept of undulating, or patterned, surfaces has been advanced to minimize friction in both dry and boundary-lubricated sliding. The undulating surfaces trap wear debris and thus minimize plowing friction in dry sliding, above the transition temperature in boundary-lubricated sliding, and even in hydrodynamic bearings during start/stop operations. The concept is especially appropriate for heavily loaded tribological systems with tighter clearances in which the likelihood of seizure is imminent. Diamond-like carbon (DLC) films have excellent tribological properties. These include low friction, high wear resistance, high corrosion resistance, and a high anti-seizure resistance. DLC film with and without Si doping (due to its promising effect on friction coefficient), at approximately 1-2 μm thickness, was synthesized by a reactive ion plating method using C 6 H 6 source on WC-Co substrate. Si addition on tribological properties of DLC was evaluated. The effects of relative humidity and contact load are also investigated. When the Si content was increased above 5.9 at. %, tribological properties of the coating were deteriorated. These properties are, however, affected by film deposition parameters and sliding conditions such as normal load, sliding speed, mating materials, and atmospheric conditions. The effect of environment is particularly significant. The present paper proposes a new model and method to detect the occurrence of dynamic instabilities and stick-slip in mechanical face seals used in automotive cooling water pumps, in order to improve their performance. A new tribo-dynamic model is presented and used to examine how many and what design parameters influence stick-slip. Mass, moment of inertia, stiffness, damping ratio, friction relationship, viscosity, roughness and wear, compressive strength of different coupling materials, geometrical specifications and temperature are some of the analyzed parameters. Therefore, this work provides a full overview of the influence of design parameters on the stick-slip phenomenon. The present paper describes the analytical approach to find the static and dynamic performance characteristics of a newly configured non-recess hole-entry hybrid conical journal bearing, considering the speed effect of journal compensated with capillary restrictors. Capillary restrictors are placed in the holes which are drilled over the periphery of the conical journal bearing. These holes are placed at an angle of 30 degree in the circumferential direction. The modified Reynolds equation which governs the lubricant flow in the clearance space of journal and bearing is solved by using Finite Element Method (FEM). The performance characteristics for the non-recess hole-entry hybrid conical journal bearing have been shown for wide range of restrictor design parameter ( C ¯ s 2 = 0.02 − 0.1 ) in terms of bearing flow, direct fluid film stiffness and direct fluid film damping coefficient for different semi cone angles γ = 5deg, 10 deg, 20 deg and 30 deg. The results obtained from the simulation indicates that the non-recess hole-entry hybrid conical journal bearing depicts important performance characteristics for bearing flow ( Q ) and fluid film stiffness which may be useful for bearing designer. However, the non-recess hole-entry hydrostatic conical journal bearing shows desirable performance for fluid film damping coefficient. The reduction of drag torque is an important issue in terms of improving transmission efficiency. Drag torque in a wet clutch occurs because viscous automatic transmission fluid flow narrow gap between friction plate and separate plate. The main purpose of this study is to observe the effects of the various parameters on the drag torque using finite element simulation. In this study, the simulation analysis reveals that as the rotational speed increases, the drag torque generally increases to a critical point and then decreases sharply at a high speed regime. Depth of groove on the friction plate plays an important role in controlling drag torque peak. An increase in the depth of groove causes a decrease in shear stress; thus, the drag torque also decreases according to Newton’s law of viscosity. Also, an observation of the effect of the angle of groove pattern shape shows that the drag torque changes with groove pattern shape. Therefore, the optimum angle of the groove pattern should be determined carefully, considering both the clutch performance and drag reduction. It is expected that the results from this study can be very useful as a database for clutch design and to predict the drag torque for the initial design with respect to various clutch parameters. In this contribution a complementarity formulation for the solution of EHL problem in presence of cavitation is employed in order to investigate the tribological behavior of the conrod small-end of a high performance motorbike engine. The influence of different physical and geometrical parameters is discussed. In particular, the clearance between the conrod small-end and the piston pin, the lubricant physical properties, the surface roughness and the stiffness of the piston pin are investigated, thus providing preliminary guidelines for the correct design of the coupling. Due to the negligible influence of the transversal forces acting on the conrod small-end and of the relative sliding speed between the mating surfaces, a two symmetrical model of the assembly is prepared and results are compared with those obtained adopting a simply symmetrical model. This paper focuses on the analysis of hydraulically balanced external gear pumps, in particular on the lubricating gap between the bushes and the gears. This topic is of key importance for the optimization of the machine efficiency because it both influences the mechanical-viscous friction and the volumetric losses. In this paper the intent is to investigate the role of the elastic deformation of the bushes surfaces, to compare the analysis done with rigid and elastic surfaces and finally to correlate the results with the design of the bushes balancing surfaces. A numerical procedure for the determination of the pressure distribution inside the gap bounded by gears sides and the bushes internal surfaces is presented and applied. With respect to past works of the authors, the procedure has been integrated taking into account the elastic deformation of the internal surfaces of the bushes and the variation of the dynamic viscosity of fluid, two well recognized phenomena that can play a key role on the determination of the bushes behaviour and lubricating gap pressure distribution. It is shown that, when the design of the bushes rear surfaces determines a strong balancing thrust, the bushes themselves need to tilt strongly with respect to the gears to generate an opportune widening thrust to avoiding contact with the gears. Useful suggestions for the bushes balancing surface design may be drawn from the analysis of the balancing maps reported in the paper, which illustrate the widening thrust magnitude and position in both the pure hydrodynamic and elasto-hydrodynamic cases, for different tilted positions and operating conditions. For stable frictional torque transfer, wet clutch pads have the functional requirements of a high traction and a low wear rate with positive μ-V frictional characteristics. However, because of the intrinsic negative μ-V frictional characteristics of a friction material that has a static friction coefficient greater than its kinetic friction coefficient, the frictional torque transfer has unstable vibrations during the clutch-pad engagement. To reduce the vibration mode during the engagement of wet clutch pads, the kinetic friction coefficient should be made greater than the static friction coefficient through modifications in the design parameters as well as in the characteristics of the friction materials. To obtain positive μ-V frictional characteristics, it is important to manipulate the static-friction coefficient, which largely develops in the boundary lubrication stage during the clutch-pad engagement. The formation of the boundary film is described by slip boundary conditions and hydrodynamic lubrication films. It also includes the elastic deformation of the wet pad material due to the contact pressure. The wet clutch pad material is made of a porous structure through which the lubricant can easily spread when the applied load and sliding speed are imposed. The lubrication and the direct contact of the surfaces are simultaneously considered for a frictional torque transfer that lasts for less than one second, depending on the working conditions. In this study, some of the computational results with a measured μ-V friction coefficient covering both the static and kinetic friction during the wet-clutch engagement are obtained for the lubrication and the direct-contact pressures. Performance optimization of a concrete mixer is fundamental in many industrial technologies. Wear is one of the main phenomena to be forecast and tested during the design and service of mechanical components. In all the concrete mixers types, blades suffer the wear more than other components. Two different blade shapes have been tested in order to evaluate the wear rates and which of them has the best performance in terms of wear resistance. One of the two shapes has been designed in order to minimize wear rates and to allow longer durability, on the basis of a theoretical approach. To guarantee the consistence of the comparison, the two different blades have been tested in a dedicated planetary concrete mixer, with the same operating conditions (time-period, same mixture and mixer). The purpose of this paper is to show optical non-contact measurements of worn blades operating in a planetary concrete mixer in order to evaluate wear rates and to validate the efficiency of the new blade design. Surface texture of engine components such as crankshafts and camshafts is one of the most important factors that determine the performance, efficiency and the operating life of an internal combustion engine. Current practices and the challenges faced by design engineers in specifying the target surface topography to meet these goals have been reviewed. Once specified, the surface texture must be measured fast, accurately and repeatably in the rough environment of an engine manufacturing plant. The key components of an automated skidded surface finish measuring gage designed with these criteria in mind are described in this paper. The gage has 7 axes of motion and 3 stylus probes oriented in the axial and radial directions to take axial and facial measurements on journal and cam lobe surfaces and thrust bearing surfaces. The selection of surface texture parameters to best describe the desired surface texture of these engine components was investigated. The final stage of surface preparation is often the superfinishing process. The measurement gage must be able to provide the sensitivity and repeatability that are required for measuring the finely finished surfaces generated by this process. Typical surface texture results of a superfinishing process achieved on crankshafts are described. The results of a Gage Repeatability and Reproducibility (R&R) study performed on the surface texture measuring gage are presented. Surface generation processes involve convergence of both machining and tribological interactions between the tool and the work. Abrasive finishing is one among the many families of surface generation processes, of which grinding process is a sub-set. In a typical grinding process, six different interactions can be identified at the grinding zone resulting in surface generation. Of these six interactions one is governed by the principles of machining, while the other five are governed by the principles of tribology. Thorough analysis of these interactions helps to characterize and understand the role of both tribological mechanisms and machining interactions in a typical grinding process. Moreover, these interactions offer the grinding process a flexibility which has resulted in a series of process innovations over decades transforming the grinding process into a high material removal rate machining process as well as an ultra-fine finishing process. Historical developments as well as recent process innovations are presented in this review paper along with the common frame work for their analysis using a set of microscopic interactions applicable in all these cases. This paper presents a series of experimental and theoretical efforts that we have made in unraveling the tool wear mechanisms under steady state conditions in machining for the last few decades. Two primary modes of steady state tool wear considered in this paper are flank and crater wear. We preface this paper by stating that flank wear is explained as abrasive wear due to the hard phases in a work material while crater wear is a combination of abrasive wear and generalized dissolution wear which encompasses both dissolution wear as well as diffusion wear. However, the flank wear was not a function of the abrasive cementite content when turning low alloy steels with pearlitic microstructures. The machined surfaces of these alloys are examined to confirm the phase transformation (ferrite to austenite), which diminishes the effect of cementite content. In particular, the cementite phase present in low alloy steels dissociates and diffuses into the transformed austenitic phase during machining. Dissolution wear is claimed to describe the behavior of crater wear at high cutting speeds. The original dissolution mechanism explains the crater wear in the machining of ferrous materials and nickel alloys at high cutting speeds, but the generalization of the dissolution wear is necessary for titanium alloys. In machining titanium alloys, the original dissolution mechanism did not show a good correlation with experimental results; generally the diffusivity of the slowest diffusing tool constituent in titanium limits the wear rate. The phase transformation from alpha (HCP) to beta (BCC) phases can also take place in machining titanium alloys, which drastically increases the crater wear due to the few orders of magnitude increase in diffusivity. The most puzzling issue is however the presence of the scoring marks even though no hard inclusion is typically present in titanium alloys. This is finally explained by the heterogeneity in the microstructure due to the anisotropic hardness of alpha (HCP) phase (the hardness in c-direction is 50% higher than the hardness in other directions) and the presence of lamellar microstructure (alternating layers of alpha and beta). The lamellar microstructure has not only the in-plane anisotropic hardness but also a greater hardness than other phases. Even though we cannot claim to fully understand the physics behind tool wear, our combined approaches have unveiled some elementary wear mechanisms. Nowadays, manufacturing enterprises face enormous environmental challenges, due to complex and diverse economic trends, including shorter product life cycles, rapid advances in science and technology, increased diversity in customer demands and globalization of production activities. Consequently, the cost is highly affected by environmentally related factors. Energy efficiency is one of the main factors, which together with waste management, affect manufacturing decisions. The complexity and diversity of the factors that determine energy efficiency require intelligent systems for their optimization at each “manufacturing level”. Manufacturing decisions should be taken as fast as possible and with the highest possible accuracy. Artificial intelligence/machine learning tools have made significant progress during the last decade and are suitable for such applications. The main objective of the current study is that an architecture for the development of a networked, online, decision support tool, be provided towards achieving sustainable value chain management. The main idea behind the proposed design is that stakeholders be assisted in taking decisions towards improving the energy and eco-efficiency of the entire value chain or parts of it. This is suggested within the context of a multi-objective optimization procedure, taking into account other important decision making attributes, such as flexibility, quality and time for the final reduction in the overall cost. This architecture incorporates real time information modules that interact with online monitoring systems, using any available information within the value chain and the existing IT tools. A partial realization of the proposed idea is implemented in the form of a user friendly software tool (the MetaCAM tool). This based, decision support tool aiming to optimize a current production line or to propose alternatives for the manufacturing of a product. The tool performs optimization based on a set of predefined criteria, namely energy, waste, cost and time. For each of these criteria, the end-user selects the desired weight factor in order to drive the optimization procedure accordingly. The tool presents the characteristics of the setup of the proposed optimized line and maintains all used data and calculations in order to be reused when necessary.. For the tool’s validation, three real case studies from different industrial sectors have been used. The first case study comes from the domestic appliances sector (refrigerator door panel), the second one from the automotive sector (a two seat bench for light commercial vehicles) and finally, the third case study derives from the aeronautics sector and deals with the production of the loading ramp hinge of a military aircraft. In a previous study, we analyzed the life cycle cost impacts of component location changes as applied to rolling stock products. Here, we present the results of an analysis that quantifies the costs of changing heavy-duty connection locations in modular fabrication designs. Modules that are fitted together usually include multiple lines of piping, cabling, and other connections, which can be problematic when the design may change due to out-of-tolerance dimensions or design requirements that change prior to installation. Also, design changes after site delivery may require frequent location changes for components that are mounted within modules. Inflexible connections internal to the module or chassis may hinder module-to-module connections in the field, where changes are difficult, hot work is dangerous, and quality of repair is dubious. The aim of this analysis was to evaluate the costs to change various types of pipe connections between modules and the costs to change component locations within modules. In addition to allowing mounting locations to be easily changed between and within modules, adjustable connection points enhance the modularization and customization of products at the lower levels of production associated with the energy, shipbuilding and rolling stock industries. Manual assembly planning methodologies have been in the center of industrial and academic research for many decades, since the manual assembly costs may often account for even half of the total manufacturing expenses. The existing and emerging manufacturing trends, such as mass customization and personalization, require fast responses when it comes to the conception and realization of the relevant manufacturing systems. Even though, work methodologies, such as concurrent engineering, have been proposed and applied, gaps still exist among product development, configuration and manufacturing. The Current Product Lifecycle (PLM) systems focus on the coordination of activities among engineers of different disciplines. However, they are unable to provide actual decision support functionality to decision makers. Moreover, solutions for the different phases of assembly planning have been proposed, without nevertheless taking into account the holistic nature of assembly planning that spans the different engineering phases. The study presented in this paper is based on a methodology that integrates three distinct steps, regarding assembly planning; the generation of assembly related information, from the Computer Aided Design (CAD) files of an assembly, the calculation of the relevant process times from functions, generated through empirical measurements and the assembly line balancing of a line, based on the information gathered. The innovative aspect of this approach relies on the advancement of the relevant technologies as well as on their integration into a common working practice. The methodology enables the estimation of production related values in the later phases of product design or in the early phases of manufacturing planning. The generation of assembly precedence diagrams is made in an automatic way through the extraction of information on collision detection and the parts’ relations. This application is developed in the form of an add-on to a commercial CAD software suite. It utilizes features that are available in a wide range of such systems. The second step relies on the identification of specific features of parts, such as dimensions and mass. This information is then used as input in the functions already proposed in the academic literature for the estimation of the relevant process times for each part. Finally, the assembly line balancing is performed through the generation of the precedence diagram and the estimated process times, via a web-based service, which makes use of advanced optimization techniques. In order for this methodology to be evaluated, a case study is presented by using the CAD file of an automotive sub-assembly. The case study demonstrates each step separately, beginning with the generation of the precedence diagram down to the balancing of the assembly line. Short-term scheduling belongs to the typical decision-making problems in manufacturing that continue to draw attention from industry and academia due to its inherent difficulties. The trend of mass customization and the increasing product variety generate further uncertainties and turbulences on modern shop-floors, thus, making scheduling a challenging daily problem. These challenges dictate the need for replacing rigid centralized scheduling tools with adaptive and robust scheduling solutions. The integration between ICT based decision support tools in manufacturing can be further enhanced to achieve shop-floor awareness and a common information flow, which is necessary to improve decision-making. Towards this objective, advanced monitoring techniques consisting of smart sensor networks and seamless communication procedures can provide the required awareness to decision making process. Further to that, Cloud, as an emerging enabling technology, can support the integration among multiple IT tools and provide ubiquitous access to data. Cloud-based and resource-aware scheduling tools are therefore considered as enablers for increasing the adaptability and agility of a manufacturing system. The proposed research work, presents a cloud-based framework consisting of a monitoring service and a short-term scheduling application that aims to generate and dispatch feasible and highly-productive schedules in a timely manner. The short-term scheduling application is enriched with data obtained by the monitoring service and generates resource-aware schedules by considering not only machine tools suitability but also their imminent status and availability. The scheduling application utilizes an intelligent search algorithm, which allows the generation of alternative schedules and their evaluation though a set of multiple conflicting criteria including among others cost, time and quality. The produced schedules are assessed using a set of performance indicators of makespan and resource utilization. The monitoring service gathers data from two data sources, namely a multi-sensory system and the machine tool operator. Through an information fusion procedure, the monitoring service provides to the scheduling application the machine tools status as well as the machine tools available time windows. The sensory system is deployed on five axes work-centers to monitor the axis and spindle drives in near real-time. The human operator reports to the monitoring system the status of the machine tool, the currently running task, and the cutting-tool availability through mobile devices on the shop-floor. The information fusion technique, consisting of the Analytic Hierarchy Process and the Dempster’s Shafer theory of evidence, processes these heterogeneous information sources and derives the status of the machine tool and future availability windows. The proposed framework is applied and validated in a real-life case study obtained from a high precision mold-making industry. Small precision parts with miniaturized features are increasingly used in components such as sensors, micromedical devices, micro-fuel cells, and others. Mechanical micromachining processes, e.g., turning, drilling, milling and grinding are often used for fabrication of miniaturized components. The small micro-tools (50 μm to 500 μm diameter) used in micromachining limit the surface speeds achieved at the cutting point, unless the rotational speeds are substantially increased. Although the cutting speeds increase to 240 m/min with larger diameter tools (e.g., 500 μm) when using the highest available spindle speed of 150,000 rpm, the cutting speed with the smaller 50 μm tools is limited to 24 m/min. This low cutting speed at the tool tip is much smaller than the speeds required for efficient cutting. For example, in macro-milling of aluminum alloys the recommended speed is on the order of 60-200 m/min. The use of low cutting speeds limits the production rate, increases tool wear and tendency for burr formation, and limits the degree of dimensional tolerance and precision that can be achieved. The purpose of the present paper is to provide preliminary results that show the feasibility of ultra high-speed micro-milling of an aluminum alloy with respect to surface quality and burr formation. A new ultra high-speed spindle was used for micro-milling of an aluminum alloy with micro-end-mills ranging in diameter from 51 μm to 305 μm. Straight channels were machined to obtain an array of square patterns on the surface. High surface cutting speeds up to 340 m/min were achieved at 350,000 rpm. Inspection of the machined surfaces indicated that edge quality and burr formation tendency are related to the undeformed chip thickness, and therefore the cutting speed and feed rate. The quantity of burrs observed on the cut surfaces was generally small, and therefore, the burr types were not systematically determined. Cutting with the 305 μm tool at a cutting speed of 150 m/min produced an excellent cut quality using a chip thickness of 0.13 μm. However, the cut quality deteriorated as the chip thickness was decreased to 0.06 μm by increasing the cutting speed to 340 mm/min. This result is consistent with published data that show the dependence of bur formation on ratio of chip thickness to tool tip radius. The channel widths were also measured and the width of channels cut with the small diameter tools became larger than the tool diameter at higher speeds. The dependence of the channel widths on rotational speed and the fact that a similar variation was not observed for larger diameter tools, suggested that this phenomena is related to dynamic run-out of the tool tip, which increases the channel width at higher speeds. Nickel-based superalloys have long been recognized as difficult-to-machine alloys. Chipping and breakage are understood as the dominant features of tool deterioration particularly in milling of these alloys. But how tool deterioration affects cutting force ( F c ) has not been sufficiently established so that force model base deterioration detection methods can be practically developed. Thus, this study intends to better demonstrate the relationship between modes of tool deterioration and F c . Milling experiments were conducted using 718Plus superalloy and uncoated cemented carbide tool and a commonly used set of milling parameters, with or without the use of coolant. During these experiments, F c was recorded and in between milling passes the traditionally used flank wear value ( VB ) was precisely measured. We have observed that as milling progressed, along with the slow edge wear, edge chipping and fracturing intensified and F c increased. However, before the final catastrophic failure, the rate of increase was relatively small in comparison to the scatters in F c vs VB Max plot. Thus, a model based on F c vs VB Max for detection of tool deterioration may not be suitable. We will explain the reasons for the scatters and relate the fracturing path to the effect of it to cutting edge contact area, thus to F c . This paper elucidates a modified Classical Nucleation Theory (CNT) that considers the effects of stress variations and existence of microvoids in plastic foaming processes. The stress effect has been incorporated into the CNT by a local pressure variation term that describes the dynamic conditions of industrial plastic foaming processes (e.g., extrusion foaming, injection foam molding). Also, the free energy barrier equation has been modified to include nucleation events from existing gas clusters. Both phenomena have been observed experimentally via in-situ plastic foaming visualization to confirm the modified theory. Combining the stress and pre-existing gas clusters considerations, the modified CNT described in this paper improves the traditional CNT in describing cell nucleation phenomena in plastic foaming processes. In this study we present a comprehensive experimental investigation of the effect of polymer blending on the dispersed phase morphology and how the dispersed phase morphology influences the foaming behavior of the semicrystalline polymer matrix using three different material combinations: polyethylene (PE)/polypropylene (PP), PP/polyethylene terephthalate (PET) and PP/polytetrafluoroethylene (PTFE). Samples are prepared such that the dispersed phase domains exhibit either spherical or fibrillated morphologies. Measurements of the uniaxial extensional viscosity, linear viscoelastic properties and crystallization kinetics under ambient pressures and elevated pressures of carbon dioxide (CO 2 ) are performed and the morphological features are identified with the aid of SEM. Batch foaming and lab-scale extrusion foaming experiments are performed, as a screening model for polymer processing, to show the enhancement of the foaming ability as a result of the blend morphology, taking into account the rheological behaviour and the effects of crystallization kinetics. The formation of high aspect ratio fibrils imparts unique characteristics to the semicrystalline matrix such as strain-hardening in uniaxial extensional flow, prolonged relaxation times, pronounced elastic properties and enhanced kinetics of crystallization. In contrast, the regular blends containing spherical dispersed phase domains do not exhibit such properties. Foam processing of the three blends reveals a marked broadening of the foaming window when the dispersed phase domains are fibrillated due to the concurrent increase in crystallization kinetics, improved elastic properties and strain hardening in extensional flow. Large recycled high-density polyethylene (HDPE) structural members, difficult to manufacture by extrusion processes, have been created by the hot plate welding of simple plastic lumber sections. Hot plate welding generates better joint strength than any other welding method currently employed in plastic manufacturing. However, to achieve the desired temperature of the thick plate to melt the polymer uniformly, the process needs a high amount of heat energy requiring furnace (or resistance) heating of a considerable mass. A new method which could combine the heating element and a thin plate into one source could be more efficient in terms of heat loss and thus energy used. The premise of this investigation is to replace the hot plate with a very thin piece of high resistance nickel-chromium alloy ribbon to localize the application of heat within a plastic weld joint in order to reduce energy loss and its associated costs. This resistance ribbon method uses electrical current to reach an adequate temperature to allow for the welding of the HDPE plastic. The ribbon is only slightly larger than the welding surface and very thin to reduce the loss of excess heat through unused surface area and thick sides. The purpose of this project was to weld recycled high-density polyethylene (HDPE) using resistance welding and to match the tensile strength results considered acceptable in industry for hot plate welding, that is, equal to or greater than 80% of the base material strength. Information obtained through literature review and previous investigations in our laboratories established welding (heating) temperature and time as testing factors. Designed experimentation considered these factors in optimizing the process to maximize the weld tensile strength. A wide-ranging full-factorial experimental design using many levels was created for the initial testing plan. Tensile strengths obtained after welding under the various condition combinations of weld temperature and time revealed a region of higher strength values in the response surface. After the wide-range initial testing, the two control parameters, heating temperature and heating time, were ultimately set up in a focused Face Centered Cubic (FCC) Response Surface Method (RSM) testing design and the tensile strength response was then analyzed using statistical software. The results obtained indicated a strong correlation between heating time and heating temperature with strength. All welded samples in the final testing set exhibited tensile strength of over 90% base material, meeting the goal requirements. A full quadratic equation relationship for tensile strength as a function of welding time and temperature was developed and the maximum tensile strength was achieved when using 280°C for 60 seconds. Bismaleimide (BMI) resin with Quartz (AQ581) fiber reinforcement is desirable for systems requiring a high glass transition temperature, low dielectric properties, and high laminate mechanical properties. These properties make quartz/BMI an ideal composite material for complex aerospace structures, and are currently being used in various aircraft engine cowlings and radomes. In addition to moisture absorption, quartz/BMI composite laminates are often exposed to different types of hydraulic fluid contaminants, which may lead to anomalous absorption behavior over the service life of the composite structure. Variations in laminate processing conditions, such as prepreg preconditioning and fabrication cure pressure, can have a significant effect on microstructural features of fiber-reinforced composites. Microstructural features, such as fiber volume fraction and void content, can influence mechanical properties and long term absorption of moisture or other liquid contaminants. In this paper, the process-induced microstructure and hydraulic fluid absorption behavior of quartz/BMI laminates are presented. The laminates are fabricated from preconditioned prepregs and cured at different pressures to generate different levels of microvoids, while keeping the fiber volume fraction constant. Location, size and morphology of microvoids are investigated via SEM images obtained from laminates cured at different processing conditions. Composite samples were prepared and fully-immersed in hydraulic fluid at room temperature, and were not subjected to any prior degradation. The laminate samples immersed in hydraulic fluid exhibited clear non-Fickian absorption behavior, which was successfully predicted by the one-dimensional Hindered Diffusion Model (HDM). The degree of non-Fickian absorption behavior, or hindrance coefficient (μ), ranged from 0.30 to 0.72. Model prediction indicates that as the fabrication pressure increased, the maximum fluid content (M ∞ ) decreased considerably. Additionally, a reduction in maximum fluid content was observed when lower relative humidity environments were used for prepreg preconditioning. A discernable difference was not observed in the absorption dynamics when the prepregs were preconditioned at greater than 70% relative humidity. In this study, expanded polylactide (EPLA) bead foams were produced with cellular morphology ranging from nanocellular to microcellular. This was achieved by using bead foaming technology while a double crystal melting peak structure was generated. The high melting peak crystals generated during the gas saturation played an important role on controlling the cell size and expansion ratio of the foamed beads. As the amount of high melting peak crystals increased, the cell sizes were reduced to around 350 nm while the expansion ratio was around 3-fold. In other words, the induced perfected crystals significantly promoted the heterogeneous cell nucleation while hindering the cell growth. On the other hand, with the reduced amount of these perfected crystals, the cell sizes were increased to around 15 μm and the expansion ratio of the foamed beads increased to 30-fold. In 1977, Nam P Suh proposed a different approach to design research. Suh’s approach was different in that it introduced the notions of domains and layers in a 2-D design thinking and stipulated a set of axioms that describes what is a good design. Following Suh’s 2-D reasoning structure in a zigzagging manner and applying these axioms through the design process should enable the designer to arrive at a good design. In this paper, we present our own experiences in applying Suh’s theories to software design, product design, organizational design, process design, and more in both academic and industrial settings. We also share our experience from teaching the Axiomatic Design theory to students at universities and engineers in industry, and draw conclusions on how best to teach and use this approach, and what results one can expect. The merits of the design axioms are discussed based on the practical experiences that the authors have had in their application. The process developed around the axioms to derive maximum value (solution neutral environment, design domains, what-how relationship, zig-zag process, decomposition, and design matrices) is also discussed and some updates are proposed. KAIST has developed the Shaped Magnetic Field in Resonance (SMFIR) technology that transfers a large amount of energy to electric vehicles when they are running or stationary. The wireless charging SMFIR technology provides a solution to the commercialization barriers of electric vehicles such as the problems of batteries and charging infrastructure. Using 20-kHz wireless power transfer system based on the SMFIR technology, our eco-friendly On Line Electric Vehicle (OLEV) bus was wirelessly powered by 100 kW through a power grid embedded under the road. On the other hand, using high-capacity, high-efficiency and low-cost 60kHz power supply and pickup systems based on the SMFIR technology, tram and high speed train were wirelessly powered by 180 kW and 1 MW through a power grid built in rail roads, respectively. The commercial OLEV tram has been operated commercially from July 2011 in Seoul National Grand Park. Also, the OLEV shuttle bus has been operated for convenience of students and faculty members at KAIST campus since Oct. 2012. In addition, the world’s first intra-city OLEV bus with 100 KW pickup capacity has been operated commercially at Gumi city from March 2014. Then, airgap is about 20 cm and maximum power transfer efficiency is 85 %. Axiomatic Design is becoming a preferred system design process tool for insuring the quality and efficiency of design processes for products and services. One aspect of Axiomatic Design is modeling and analyzing the functional independence of proposed solutions. Axiomatic Design provides for comparing and ranking solutions by three categories of functional coupling: Uncoupled, Decoupled and Coupled. However, given two potential solutions within the same functional coupling category, Axiomatic Design technology cannot further rank these solutions without additional information. This paper proposes that the degree of functional coupling can be assessed to provide further discrimination between solutions within the same coupling category. Using complexity concepts, this paper proposes two additional metrics, the Independence Priority Number (IPN) and the Independence Measure (IM) to further rank the potential robustness of alternative solutions using the Independence Axiom of the Axiomatic Design process. With IPN and IM metrics, design professionals can better assess the functional robustness of their proposal at the earliest phase of design, conceptual design synthesis. Increasing global competition in manufacturing technology puts pressure on lead times for product design and production engineering. By the application of effective methods for systems engineering (engineering design), the development risks can be addressed in a structured manner to minimise chances of delay and guarantee timely market introduction. Concurrent design has proven to be effective in markets for high tech systems; the product and its manufacturing means are simultaneously developed starting at the product definition. Unfortunately, not many systems engineering methodologies do support development well in the early stage of the project where proof of concept is still under investigation. The number of practically applicable tools in this stage is even worse. Industry could use a systems engineering method that combines a structured risk approach, concurrent development, and especially enables application in the early stage of product and equipment design. The belief is that Axiomatic Design can provide with a solid foundation for this need. This paper proposes a ‘Constituent Roadmap of Product Design’, based on the axiomatic design methodology. It offers easy access to a broad range of users, experienced and inexperienced. First, it has the ability to evaluate if knowledge application to a design is relevant and complete. Secondly, it offers more detail within the satisfaction interval of the independence axiom. The constituent roadmap is based on recent work that discloses an analysis on information in axiomatic design. The analysis enables better differentiation on project progression in the conceptual stage of design. The constituent roadmap integrates axiomatic design and the methods that harmonise with it. Hence, it does not jeopardise the effectiveness of the methodology. An important feature is the check matrix, a low threshold interface that unlocks the methodology to a larger audience. Design broadly defined deals with mapping from societal wants or needs to means for satisfying these needs. Axiomatic design is a well-known approach to design that was initially proposed by Nam P. Suh in the late 1970s. Since that time, it has underpinned much academic research in engineering design; it has been taught internationally as part of engineering curricula; and it has been used across many industries. This paper attempts to assess the impact of axiomatic design in guiding design research; its practical, industrial applications; as well as its role in stimulating and renewing engineering education. This paper also provides a brief review of the concepts underlying axiomatic design theory including its motivation and history of development, recent activity within the axiomatic design community, and suggestions for future research directions. The most important design decisions are made in the outset of the designing process, when the knowledge about the final design solution is usually scarce and therefore uncertainty is high. According to the independence axiom of Axiomatic Design (AD), design solutions are classified in the following three basic types: uncoupled, decoupled and coupled, the former being the best type and the latter the poorest. As a rule, coupled designs should be avoided, not only because they infringe the independence axiom but also because their information content is hard to compute. Nonetheless, we argue that the occurrence of coupled solutions is noteworthy in general design, although we recognize that they are questionable and that many times they could be easily avoided. Our motivation is to contribute for changing the current state of affairs by showing how to use the minimum information content axiom to make early decisions in the development of coupled designs. One of the general engineering approaches to deal with multiple-FR, multiple-DP designs is the Response Surface Methodology (RSM). We will show in our paper how RSM can be used to deal with coupled designs as if they were uncoupled. The conclusion is that one can graphically compute the information content of coupled designs with two DPs and an arbitrary number of FRs by using multiple RSM. This means that RSM can be interpreted at the light of Axiomatic Design, and embodies an appropriate approach to support decision-making in the case of coupled designs. Accidents in industry, medical clinics, and transportation lead to loss of lives and property. The costs for such accidents are very high to society, industry and individuals. Recent examples of high profile accidents include the Fukushima disaster and several aircraft accidents. Accidents in hospitals cost as much as $29 Billion per year (WHO estimate) in additional hospitalization, disability, lost income, medical expenses and litigation. Looking at different industries, safety levels are very different. For example, there is a one in a million chance of getting harmed while in an aircraft. In comparison, there is a one in 300 chance of a patient being harmed during health care. Current best practices to increase product safety uses methods which were developed during the period between World War II and 1970. They are essentially based on heuristics around designing and operating systems that were a lot less integrated and complex than current systems, and contained a lot more human participation in the system. A few science-based approaches have began to emerge in recent years. This paper presents the hypothesis that in addition to the benefits proven in traditional design practice, the design axioms can form a scientific basis for an effective method to analyze designs from a product safety perspective. The main cause of the 2005 Buncefield overfill accident in the UK is analyzed using an axiomatic approach to safety. Using the rigor of axiomatic design, it is possible to identify the shortcomings in the design that caused the accident. The same approach is then applied to an alternative solution. The result of this analysis is that the new design should be much more reliable than the previous. In the conclusion, it is shown that it is possible to develop a science base for product safety based on Axiomatic Design. It is shown that such a science based approach enables design practitioners to approach unfamiliar safety related situations in a systematic way to identify risks and propose alternative designs with a lower risk level. Despite the current building sector slowdown in Italy, timber housing industry market is growing. But its growth has been limited mainly by the high costs of ad-hoc full-customized buildings and the lack of customer appreciation for mass-produced buildings. In order to satisfy the current demand for affordable customized housing, building industry should focus on solutions based on the combination of personalized and mass-produced parts. In this way, clients would have the chance to personalize crucial parts, and building industry can limit costs by the mass-production of the others. This combination between mass production and customization involves artefact flexibility and robustness with regard to the designer’s viewpoint. These requirements are set in the conceptual design phase, but in this stage architect’s decision making is not adequately supported. Since Axiomatic Design (AD) is able to support the analysis of designs with respect to the specified requirements, AD is applied to the review of prefabricated housing archetypes and current timber construction systems. This study shows the effectiveness of applying AD to prefabricated building design: crucial design decisions that affect the specified requirements are identified; inputs limiting their fulfilment in the timber building prefabrication are highlighted, and recommendations for developing adequate systems are provided. Axiomatic Design is a technique that has been applied to multiple disciplines for enabling design, analysis, and troubleshooting of complex systems. In this paper, the principles of Axiomatic Design are applied to Wi-Fi networking. Wi-Fi is the information backbone for numerous applications, including Internet connectivity, video surveillance, data collection and inventory tracking in manufacturing and warehouse environments, patient location and health status monitoring in assisted living and hospital environments, along with numerous others. A Wi-Fi system consists of multiple access points working in tandem to provide seamless, high-speed, and high-quality wireless coverage to one or more wireless client devices. To implement such a network effectively, the Wi-Fi engineer must understand and control the interactions between multiple engineering disciplines, most notably information technology, network engineering, radio frequency physics, antenna design, and materials science. Technology development in this field is fast-paced, with new standards and capabilities being introduced into the market every couple of years. Additionally, the customer expectations (i.e. requirements) are changing as well once the Wi-Fi network is installed, as data demands from new types of devices like smartphones, tablets, and network appliances are introduced long after the original network was implemented. This paper shows that there are three primary functional requirements for a Wi-Fi network, namely client usage type, coverage area, and client capacity. When designing, implementing, or troubleshooting a Wi-Fi network, there are four primary design parameters that can be controlled, namely AP antenna / model, location, channel, and transmission power. Axiomatic Design demonstrates that these four design parameters are coupled, and thus cannot be manipulated independently. Nevertheless, by effectively implementing Axiomatic Design techniques to define a set of best practices , these four key parameters can be decoupled and properly linked back to the requirements and constraints of the system to simplify the design, implementation, and troubleshooting of a Wi-Fi network. Axiomatic Design provides a set of axioms and corollaries to help make system design decisions. In this paper, the independence axiom is applied to evaluate alternate low pressure air (LPA) distribution system designs to serve the aeration basins of a wastewater treatment plant. The airflow to each air zone is defined as a functional requirement (FR) in the functional domain. A design parameter (DP) in the physical domain is selected to achieve each FR. The DPs include the LPA motor operated valve (MOV) damper positions and a process air blower inlet guide vane (IGV) position. Three design alternatives are developed and evaluated with the respect to the independence axiom. Each subsequent alternative attempts to reduce the amount of functional coupling. Reduced functional coupling in an LPA system results in a more stable treatment process and greater system longevity through reduced component wear. Lecturing has been effective for mass education. However, its limitations for learning effectiveness have been well known. Many innovative pedagogies have been developed for increasing interaction and student participation in classes. However, they have not been successfully adopted in most classrooms. On the other hand, the gap on educational quality between the industry and the academia, which is mostly attributable to lecture-based education, has been expanding. We propose a simple and effective strategy to transform teaching and learning to be highly interactive and student-participative by eliminating lecturing from classrooms. After sending lecturing to e-learning, teachers do non-lecturing activities including discussion, Q&A, interactive problem solving, team learning, and labs. We share strategies, feedback, and experiences from a university-wide program for implementing such new teaching and learning. The current program for Mechanical Engineering at the RWTH Aachen University in Germany has more than 1500 students enrolled. Lego Mindstorms’ NXT Robots are fully integrated in the current Engineering Education stream to help students practically apply theoretical concepts. The courses Communication and Organizational Development (KOE) and Computer Science in Mechanical Engineering 1 (INFO1), provided by the interdisciplinary institute cluster IMA/ZLW, follow a newly-designed “blended learning” approach. This institute cluster is composed of the Institute of Information Management in Mechanical Engineering (IMA) and the Center for Learning and Knowledge Management (ZLW). These institutes are currently within the Faculty of Mechanical Engineering at RWTH Aachen University. Two years ago, the course KOE was redesigned and redirected towards a “Flipped Classroom” concept by initiating online lectures and a discussion class. Thus, the tutorial class ROBOFLEX as part of the KOE curriculum is introduced. ROBOFLEX is a two-stage business simulation that enables students to experience realistic virtual communication within computer science and engineering disciplines. Students are divided into groups of about thirty people, and become entrepreneurs and founders of start-ups that specialize in the production of innovative robots for the automotive industry. They create these robots using Lego Mindstorms’ NXT. Since its conception, the course INFO1 has been accompanied by a lab component, where students apply the concepts taught in class in a team-focused software design project. In 2011, the lab concept was changed into a two-stage robotics programming project based on Lego Mindstorms’ NXT Robots and the Java programming language. In the first stage, students practice the fundamental programming concepts that are presented in the lecture by completing a series of exercises in a self-paced manner. The second stage focuses on applied problem-solving. In this stage, pairs of students apply the previously-learned programming concepts to program a “pick-and-place” robot that is equipped with various sensors. The integration of Lego Mindstorms’ NXT Robots into these courses also join the concepts of the two described courses. While KOE delivers organizational and communicational skills, INFO1 provides technical and domain-specific skills. Here, the robots represent the connecting element. The problem-based second stage of INFO1 benefits from the skills that are taught in KOE. Because INFO1 is scheduled in the term following the KOE, it offers a direct opportunity for students to transfer the KOE skill set from the lecture where it was taught into a new context that is primarily concerned with a different subject. Both classes have been evaluated and developed independently in the past. Since last year’s introduction of ROBOFLEX in KOE, synergies between both lectures are becoming a main component of their further developments. In this paper the recent developments in both courses will be compared and discussed. Specific measurable effects concerning learning capability, motivation and learning endurance are being portrayed by using blended learning approaches. In February 2012, the College of Engineering created the Strategic Instructional Initiatives Program (SIIP) to transform and revitalize the core engineering courses at the University of Illinois at Urbana-Champaign. As SIIP has evolved, we have learned that in order to achieve these goals, we must first focus on creating collaborative teaching cultures. This effort has sparked the rapid spread of Research-Based Instructional Strategies across the college and created a thriving community of faculty invested in improving undergraduate instruction. In this paper, we describe the current policies and procedures that we use to direct SIIP. In particular, we will focus on the structure of the leadership team and how we have fostered deep collaborations among faculty developers, education researchers, and engineering faculty. We conclude by presenting an evaluation of the program. Through the dedicated efforts of design researchers, practitioners, and educators, the importance of design thinking has been increasingly recognized by the society in general, and by the engineering community in particular. On one hand, innovative design is commonly recognized to be a highly globalized activity that requires the effective collaboration between global stakeholders to deliver. Nevertheless, to date, there remains far from enough global design and/or innovation courses available in the current engineering education system, upon which, the global students can jointly develop, sharpen their collaborative design knowledge, skill and attitude. On the other hand, although technology is widely acknowledged to be a driven force of globalization, relatively few efforts have been devoted to leveraging the power of modern eLearning technologies in order to provide the global design learning experience right on participating student’s home campus with no more expensive international travels. Against such a background, this paper presents some of our best practices of employing innovative design thinking to systemically develop a technology-enabled global design innovation course. Not only we presented a set of domain-independent design thinking principles to guide the course design, but also we elaborated the chosen technologies and the functional requirement that each technology is meant to satisfy. The course in question has been consecutively offered for 6 years so far. An evaluation is conducted upon on the 2014 spring class in order to solicit students’ satisfaction with the course. The capstone project serves as the culminating experience of most engineering programs. Collaborative design and documentation tools are an integral component of a modern product design and development environment. The Engineering Design Guide and Environment (EDGE), is a web-based system which provides engineers with tools for collaboration on multidisciplinary projects. The EDGE system includes version-controlled repositories for project documentation and design files. By examining the history of changes to these repositories, it is possible to view the usage trends of the system and their relationship to curriculum structure. This paper explores these usage trends with respect to the transition from a quarter-based to a semester-based calendar, the cycle of project deliverables within an academic term, and the transition from a one-day-per-week meeting pattern to a two-day-per-week meeting pattern. As part of a broader effort to promote the sustainable adoption of evidence-based pedagogies at our institution, the three-course sequence consisting of Introductory Statics , Introductory Dynamics , and Introductory Solid Mechanics has been redesigned to (1) improve students’ low engagement and enthusiasm, (2) improve instructors’ experience and reduce their high workload, and (3) maintain and elevate the current standards for content. These three courses are the core second-year mechanics classes in our engineering curriculum, serving approximately 2500 students per year from seven engineering departments. To promote sustainability of the reforms, the courses were redesigned through a Community of Practice (CoP), consisting of faculty who collaborated closely to design and implement changes and who developed communal knowledge of the reforms. Evaluation of reforms focused on student satisfaction as expressed through surveys and focus groups. This back matter contains the panel report, and appendices

Proceedings of the 3rd International Conference on Mechanical and Electrical Technology (ICMET 2011), held in Dalian, China, August 26-27, 2011. The primary objective of ICMET 2011 is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in Mechanical and Electrical Technology. This conference provides opportunities for the delegates to exchange new ideas and application experiences face to face, to establish business or research relationships and to find global partners for future collaboration. Submitted conference papers were reviewed by technical committees of the Conference. This front matter contains the preface, a list of the organizing committee and table of contents. During the development of Chinese Agriculture Industry Chains, there are three main forms of organizations. From perspective of the organizational design and structure, the last one is the best organizational mode in all agricultural industry chains; from the perspective of organizational operation, as a form of organization, agriculture industry chains closely relate to its development degree of stages; from the perspective of organizational evolution; the organizational form of agriculture industry chains appears transformed way from the mode of “cooperation between farmers and companies” “operation between specialized markets and farmers” to the mode of “cooperation among the companies, farmer's Economic Cooperation and farmers”. According to the technological requirement of adding medicament to thickener, this paper has designed the medicament addition auto-control system based on the interface analysis instrument which has been designed based on the natural gamma-ray attenuation. The system has realized the automatic closed-loop control on the adding medicament in the thickener and the underflow emissions automatic control. The application of this system has saved the usage of medicament, and has effectively improved the quality of the circulating wash water, ensured high efficient operation of production of the preparation plant, and improved the automatic level of coal preparation plant. With the growth on enterprise application client, server starts to running overloaded caused by much more concurrent access, which has become the bottleneck for systems. To solve this problem, we design and accomplish a dynamic load balancing strategy of DTS, with referring the middleware idea. This strategy can achieve load balancing both in physical layer and service request layer, and reduce the cost of system resources, which makes the system running in optimal state. An efficient procedure for matching two-dimensional contours is described. Firstly, based on the curvatures set and the corners set, the initial matching pair is determined in the process; next, the initial matching pair is validated by the geometry attribute. If the length of the arc and chord of the initial pair segments is the same in the range of error permission, the two segments can be determined as the candidate matching pair; finally, the hausdorff distance between the candidate matching pair is calculated. If the distance is in the range of admitting error, the segments can be determined as a matching pair. The performance of our method is illustrated with a realistic example. The modified multi-features impulse track circuit is dedicated to solving shunt-fault problems confronted by traditional track circuit installed in station. Rail is a primary component of this track circuit. Analyses of rail impedance characteristics under continuous different frequency signals are meaningful for electric characteristic analysis and optimal design of this track circuit. However, the existing measurement systems for impedance characteristics can be only applicable to single-point frequency case. In the framework of Lab VIEW, this paper develops a new system with professional soundcard for achieving impedance measurement of rail or other metal conductors under sweep frequency signals. It can be characterized by multichannel data collecting, highly accuracy and wide frequency range. The system structure and function are introduced from designs of hardware and software. Finally, some measuring examples illustrate predominance of its performance. Based on the Ford-Fulkerson labeling algorithm which can realize network maximum flow, combining with “edge split path” thought, and through the new understanding of “reused link” and “super critical nodes”, an improved algorithm of reducing the network encoding nodes is proposed in this paper. The algorithm can not only reduce the network encoding nodes to know the necessary encoding nodes, but also determine the information transmitted on the network links using simple linear coding method at coding nodes. Simulation shows that, the proposed algorithm reduces the number of encoding nodes obviously while achieving the multicast maximum flow. In order to improve the processing capacity of the MD5 core based on FPGA, the design of MD5 multicore engine based on single pipeline is proposed in the paper. By means of analyzing four different core models, three multi-core engines are designed. And the experimental results show that our method can plan the FPGA resources, working frequency and core structure effectively and improve the system performance. High-speed train customization technology is the main development of high-speed train equipment technology in the future. To satisfy customization requirement, high-speed train common requirement and adaptability requirement are studied. By the analysis and extraction of the concept, high-speed train ontology model is built and representation methods of the knowledge model are researched. On this basis, the configuration method based on requirement analysis is applied in the process of customization, the method with rule-based reasoning for technical target is used to meet requirement changes and improve the configuration efficiency. In cistern liquid level control system, two kinds of solutions to voltage/current signal converter circuit between D/A converter and the device being controlled (electronic modulators) are analyzed, forming voltage/current converter circuit by using integrated circuit is proposed in order to make the whole circuit simple and cheap. It is of great significance to develop universal network comprehensive evaluation support system. A new idea that universal comprehensive evaluation support system based on SaaS mode is proposed by this paper. The specific demands of universal comprehensive evaluation support system are analyzed firstly. Furthermore, the advantages of universal comprehensive evaluation support system based on SaaS are researched. Finally, corresponding solutions in terms of configurable, Multi-Tenant and safety in system designing and developing were proposed. The model slices, based on Extended Finite State Machine (EFSM), have effectively reduced the growing scale of software systems and simplified people's analysis of large complex software. However, the transitivity of data dependence is greatly restricted due to the different structures of EFSM and programs. According to EFSM's features as event, condition and action, this paper redefines the transitivity of Inter-Transition Data Dependence based on Intra-Transition Data Dependence (IaTDD) and Inter-Transition Data Dependence (IeTDD) and therefore solves the transitivity problem in EFSM by putting forward a transitivity method. The determination of material parameters, especially the elastic modulus of the dam body is important for dam safety evaluation. The inversion method of the hybrid model for the elastic modulus of gravity dam is improved though eliminating the measuring point displacement caused by the dam foundation deformation, based on multipoint displacement monitoring data. The example shows that the improved inversion method is feasible to determine the elastic modulus of the dam body. Deformation is an important physical quantity to reflect hydraulic structure, and deformation monitoring is available, and it is the most important monitor at home and abroad. As the special structure of hollow dam, the deformation safety monitoring statistical model should also consider the effect of hollow except considering pressure, temperature load and aging factors as the statistical model of measuring deformation point of conventional concrete dam. In this paper, the effect of hollow factor to dam deformation is researched on the characteristics of hollow dam, on the basis, the principle to build model of safety monitoring statistical model for the hollow dam is researched. Aiming at the coupling effect of target radiation measurement error and trajectory correction threshold to the hitting accuracy on the Last revised bullets, the optimal design solution based on Monte - Carlo method is proposed, and the CEP curve under the conditions of different correction threshold and target measurement errors by simulation is obtained. Moreover, objective indicators of measurement error and the corresponding threshold of amendments are given. A design basis for system development is obtained. Cloud model is a new tool for the uncertain conversion between the qualitative concept and quantitative description. While analyzing the teaching quality by the traditional methods, there are some limitations. But the cloud model can be used to solve the shortcomings of traditional analysis methods, and the useful information can be extracted from the data hidden in large amounts of data to show the comprehensive and objective analysis of the teaching quality. With the increasing number of automobiles in China and other countries in the world, traffic accident has become one of the most serious social problems. Drivers are considered the main part in traffic behaviors, a safe driving assistant system for reducing traffic accidents is developed using the embedded system, sensing and image recognition technology. Functions of the system includes fatigue driving alarm, speeding alarm, rear-end collision alarm, pedestrian alarm and Alarm confirmation, The hardware and software of the system were designed and implemented. A compact CMUT structure with movable floating gate is presented. The new active CMUT structure comprises two traditional CMUT electrodes and MOS transistor well beneath it. Its spice model on DC analysis and transient analysis with time-varying capacitor are investigated. It exhibits low overall parasitic capacitance and low output impedance compared with traditional one. According to Cadence simulation results, the output signal amplitude is 54 uV, while the noise floor is 33.21 nV/Hz 1/2 at 1MHz operation frequency of CMUT receiver, and the output impedance is only about 153Q. These results show advantages to make an interesting potential application on CMUT array imaging. Music style classification becomes more and more application in commercial audiencerecommendation. But any simple and efficient method has not been found for solving the great deal of music online. In this paper we developed a framework based on Naive Bayesian Network (NBN) to perform music style classification. We acquired such important features after deeply studying, and construct our specific NBN for music style classification. The results of the experiments in our method indicated that the simplicity and accuracy of music style classification improved greatly. The defect of existing similarity measure in fingerprinting (watermarking) extraction is discussed, by using the similarity measure, it is found that two obviously different fingerprint (watermark) can be determined to be approximate or the same. According to the defect, an improved similarity measure is presented. The difference and relation between two measures are discussed and the analytic expression for deriving one from the other is also presented. Wireless internet is gaining wide spread usage in teaching affairs, company and other organizations information management, especially in attendance management information system. How attendance checking management information system executed in the classroom can be developed for mobile phones is illustrated and the general framework for designing such attendance checking and attendance query applications is introduced. Using the framework, based on Microsoft database software SQL Server 2000, T-SQL clause is employed to program the data fetch and data update for attendance checking business. The framework utilizes mobile phones simulator software, Nokia WAP Toolkit, which employs WML and WMLScript on the client side, and interacts with some ASP files in conjunction with the associated SQL Server database on the server side. The design and implementation of the management information system are discussed, test results are presented and conclusion is made in the end. This paper first introduced a new kind of target recognition algorithm and then give it's optimize realization and performance evaluation. This algorithm can still recognize the target accurately in case of a poor image. For satisfy its rigorous real time requirements in the real application, this text discussed it's optimize realization in both software and hardware. At last, a performance evaluation has been given based on the platform of ADSP TS201 which cooperates with a FPGA as its own coprocessor. The total running time can be controlled in 500 ms, which can satisfy the real time request for automatic target recognition. To achieve the precision control of phase current or phase flux linkage in switched reluctance motor (SRM), the higher switching frequency of converter is required to increase dynamic response speed. However, higher switching frequency may cause higher switching losses, higher Electro-Magnetic Interference (EMI) and lower overall efficiency. The use of soft-switching techniques in converter can resolve these issues. A novel soft-switching strategy for switched reluctance motor power converter was proposed. Based on the introduction of the topology and characteristics of circuit, the zero voltage turn-on principle of phase switch was analyzed. Finally, detailed simulation study of the complete system is presented and is validated with experimental results. The Signed Directed Graph (SDG) can describe the complicated cause and effect relation and contain mass underlying information. Qualitative simulation can also help to analyze the reason for leading abnormity of material supply process and the result brought by the abnormity. The principle of the qualitative simulation based on the SDG was researched; the qualitative models were founded using the simulation tool, the reason and result paths were got; the efficiency evaluation method using material supply process qualitative simulation was brought out; the strongpoint and shortcoming of SDG was analyzed. The explosion of network information resources brings more difficulty for the grasp of information. To effectively control massive data and extract hot information, we designed hotspot-finding Algorithm about public opinion on network. The algorithm classifies the various categories by using the method of calculating their similarity of Centro, then detects hotspot from every category through the Centro comparison strategy and finally lists all the hotspots in every category according to the attentions they get. This provides an effective analysis for people to grasp public opinions on network. In order to analyze the attitude changing of the antenna in mobile communication process, a dynamical model of SOTM antenna system is proposed. First, a mechanical schema of the SOTM multi-subarray antenna system is described, and the kinetic equation is deduced though Direction Cosine Method and Kinematical Decomposition Method. Then the dynamical equation is derived based on the voltage balance, the moment balance and Euler equation. At last, the model is simulated under the open-loop condition. Simulation results show that the antenna attitude is seriously affected by the disturbance from vehicle. The model proposed and the analysis lays a foundation for the precision pointing control of the antenna to the GEO. A full digital DC speed control system based on DSP is investigated theoretically and experimentally, which uses IGBT to compose H-PWM conversion that is realized by TMS320LF2407A controller. Its feature is that the hardware such as an analog trigger, the current regulator, speed regulator and the logic switch and so on is replaced by DSP. Meanwhile, the hardware and software of the system is designed. On the base of theoretical analyses, an experimental system is setup and finally the experimental results is given. A novel decorrelation algorithm that can eliminate the computation of MUSIC without having aperture loss is presented. Through vector reconstruction by eigenvector of maximum eigenvalue, the algorithm can deal with coherent signal sources. Furthermore, Using MUSIC technique based on whole space and Modified Capon algorithm,high estimation capability can be acquired without knowing the number of signals. Simulation results verify that the proposed algorithm is effective. Different evaluation methods and analysis theory has different emphasis and foothold. Combined with peer-reviewed method, analytic hierarchy process and matter-element analysis theory can not only supply shortage each other but also play to their respective advantages properly, which make the comprehensive evaluation more scientific, objective and accurate. Through the analysis of these theories, combine with the expert evaluation method, improve the matter-element and hierarchical evaluation model, and give an example of it. This model can well solve the problem of project integration for more projects funded and knowledge sharing executing between researchers in project research process. The paper proposes a Wavelet-based watermarking algorithm where watermark information is embedded in the multilevel wavelet coefficients of the cover image. Data embedding in subbands through applying the proposed algorithm which provides a good performance between the transparency and the robustness of watermarks increases the security of watermark information hiding. Experimental results show watermark embedded by the proposed algorithm is effective and robust against common noise and image processing operation. This paper studies the situation of XLPE cables in the electric aging process, compares and analyzes the chaotic characteristics of partial discharge pulse waveform of each aging stage. By means of calculation and comparison of the correlation dimension D (m) and Kolmogorov entropy (KE), the result indicate that the PD pulse waveform of different stage has different chaotic characteristic, so as to provide a new basis for the diagnosis of XPLE cables aging. In order to achieve path following of under-actuated autonomous underwater vehicle (AUV) in unknown disturbance currents, a nonlinear iterative sliding mode control method is presented with common curve parameters and the Serret-Frenet coordinate system described the path tracking error, the equation of under-actuated AUV horizontal tracking error is established to overcome the problem of singular value. Design nonlinear sliding mode controller by iterative method, with no estimation of AUV model uncertainty parameter and current disturbances. Circular reference path can be selected which results prove that the path tracking control method is effective and under-actuated AUV can track the desired horizontal path precisely. In order to understand the heat transfer performances of the liquid metal with low melting point compared with conventional coolants, the heat transfer performances of laminar flow in a circular duct with constant wall heat flux using liquid gallium and water as coolants were theoretically analyzed by considering the influence of thermally developing region, and the effect on heat dissipation was evaluated by using the mean wall temperature. The results indicate that when duct length(Z,) or Re remains constant, the critical Re(Re,c) and critical length( X c ) exist respectively, the cooling effect of liquid gallium is better than that of water only when the Re > Re , c or L < L C . It is found that the critical Re increases linear with duct length and the critical length increases linear with Re. It is also found that increasing Re or lessening the duct length can make the cooling superiority of liquid gallium over water more prominent. All the results provide the theoretical base for better designing the cooling systems that use liquid metal as coolant. Because stock market is a complicated, nonlinear and changeable system, prediction of stock price is far more challenging than ordinary time series problems. This paper proposes a novel approach called Dynamic Ordinary Differential Equation (DyODE) modeling of stock market prediction with Gene Expression Programming (GEP). DyODE selects suitable data as training set to build prediction model and hence avoids prediction error caused by using obsolete data. Prediction accuracy of DyODE is tested on the stock prices series. Results show that the accuracy is much higher than that of traditional approaches. A lord stress method is used to analyze theoretically the stress in drawing-bulging process and the influence of forming limit on the forming condition of spherical shell parts. The effect of process parameters on the forming limit height, such as the blank holder force, friction coefficient, die radius and deep drawing speed, is analyzed by using orthogonal experiment and numerical simulate methods. The results show that the blank holder force, die radius and deep drawing speed have significant effect on drawing process, which contribution rate are BHF 42.47%, 32.09% of friction coefficient, 31.22% of die radius, and 22.21% of deep drawing speed. The auto-generation of stimulation waveform can reduce the manual errors introduced in the process of the technology parameter extraction. So how to automatically generate the correct, concise and complete stimulation waveform is the key of the technology parameter extraction. An auto-generation algorithm of stimulation waveform for sequential cell circuit functional verification is proposed. In the algorithm, state transition diagram can be generated according to the performance function of the sequence cell circuit, and then stimulation waveform can be generated according to all the nodes and all the edges in the traversing state transition diagram. A parallel ant colony algorithm based on multi-core architecture is introduced and OpenMP (multiprocessing and multithreading parallel) is illustrated. TSP (Traveling Salesman Problem) experiments are done successfully and it proves that this algorithm is easy to operate and it makes full use of advantages of parallel computing by the multi-core processor and improves its running efficiency. In Job Shop Scheduling Problem (JSSP), the optimal solution cannot be got through polynomial, leading to low job shop scheduling efficiency. JSSP based on ant colony algorithm is studied to improve job shop scheduling efficiency. Firstly, this algorithm has minimizing process time as the optimization objective, and the crawling path of the ant as the scheduling scheme. The optimal job shop scheduling scheme is got through cooperation and exchange between individuals in the ant colony. Experiments of job shop scheduling test show that ant colony algorithm can improve job shop scheduling efficiency and get the optimal solution within the shortest time period. It is an effective optimal algorithm of job shop scheduling. A flying vehicle with unconventional layout usually has better pneumatic and stealth performance compared with the traditional one. In this paper, we achieve the construction of a T-S fuzzy model for modeling the dynamics of flying-wing, and a fuzzy controller is designed to realize the flight control. An index is proposed to describe the deflection of the multiple-control surface composition to the desired virtual control. Finally, the effectiveness and real-time quality of the method is verified by the simulation. This paper introduces the working principle of laser speedometer. We concentrate on the key hardware technologies and software algorithms of the laser speedometer. In the hardware, we give the corresponding realization diagram and experimental data about the improvement of signal reception, echo energy compensation, and the removal of interferences, which are the important influence factors on the measuring accuracy. The least square method and the design of empirical parameters are applied in the software algorithms. Using the method of literature statistics, 195 documents about college students' English learning motivation are analyzed. 10 papers published on core journals of foreign languages are reviewed in multi-perspectives on several aspects: research contents, authors, document originals, published times, research types, research methods, participants, writing forms and funding supports. On this basis, limitations of research on Chinese college students' English learning motivation are explored, and the further research on this field is prospected then. GOLD code generator is widely used in code division multiple access (CDMA) system. It is mainly used for generating code sequence with good correlation characteristics. Modulation technology can be used in variety types of spread spectrum technology in a CDMA system with multiple users. The most prevalent technology is direct sequence spread spectrum. M-sequence and its composite sequence, balance GOLD sequence are deeply studied in this paper and a kind of balance GOLD generator based on DSP (Digital Signal Processing) is realized. A big number of international companies had entered into China's market for the new business opportunities. As China's government keeps implementing the policy of economic reform, the potential of China's huge market has been continuously attracting the attention of international businesses. Today, many intending multinational corporations (MNCs) had entered into China, most from the marketing environment different from China's. How to enter the China's market and how to choose entry modes are important to them. On the other hand, China has its own unique geographic regions, socio-cultural, legal, economic, political and technology environment, and they have been changing since 1978. How Chinese marketing environment impacts on MNCs' market entry choice has been more and more important. Characterization of High-speed Railway power supply system requires a power or power flow algorithm as a basic tool to determine bus voltages, line currents or power flows through feeder lines. The execution of the algorithm needs efficient search. Sequential Linear Power Flow Method is a efficient tool to solve power flow for AC Railway system. This paper describes a modified Sequential Linear Power Flow Method that uses the initial current distribution of each AT to instead of the initial value of voltage in SLPFM. The computing results of a 8-trains case indicate the algorithm can speed up convergence and reduce the number of iterations, thus that can saved computing time. Therefore, the method is more conducive to real-time flow calculation of the railway traction power supply system. This study aimed to develop a secure, peer to peer-based search intelligence system. The system mentioned in this paper which using the desktop search technology based on metadata can reduce the need of the central server by introducing the parallel computing. We focus on solving the problems including privacy, security and incompletion by introducing a new architecture. The infrastructure provided by the search engine can be utilized to simplify the users' action as well. The system first finishes metadata retrieval, then submits those metadata to the system to let other nodes know these data. The central server helps the nodes to communicate with each other, schedules the nodes actions and track their states. The result shows that the consuming work is moving to the client side, leaving only some analysis work to the server. With the development of computer information technology and deepening of information system application in electric power enterprises, requirements for information security increase gradually. In order to ensure and supervise the security of information intranet of the State Grid Corporation of China, the company organized inspection teams to conduct inspection activities for information intranet. By analyzing the potential security threats of information intranet, and introduces how inspection teams fill leak, eliminate treats and protect the security of information intranet in aspects of technology and management. The course-schedule problem is a multi-objective optimization problem, the global near-optimal solution couldn't be obtained by only using the direct heuristic algorithm, and the constringency would be slow by only using the standard genetic algorithm. So a hybrid genetic algorithm (abbreviated to HGA) which combined the direct heuristic algorithm with the standard genetic algorithm is put forward. By using a new simple intuitive two-dimensional space-time array encoding and a new block crossover operator, HGA only have little course-unit conflicts after crossing and mutating, and the conflict is easy to digest. The experiments show that the global near-optimal solution can be obtained quickly by using HGA. The speed and cost of maintenance resource transportation are considered respectively, related mathematic model is established, programming is simulated by using MATLAB. Through the case of the simulation analysis, maintenance support resource logistics center optimal location for the two models are obtained. The result shows that this method has a strong superiority in the location decision of mobile gen-sets maintenance support logistics center. Single-carrier modulation has been applied widely in wireless systems. However, the traditional time domain equalization (TDE) based on the direct decision feedback equalization is complex, especially when SC and multi-carrier are compatible in a system. In this paper, a novel frequency domain equalizer (FDE) is proposed for the PN-based SC system. This method can simplify the calculation based on LMS algorithm and the PN extension is used to initialize DFE, which have advantages in the convergence speed. Simulation results show that a significant improvement in terms of BER is expected for the new method compared with the linear FDE. Moreover, this method can share the same block diagram and common functions with OFDM system. The theory of traditional deadbeat control is analyzed in detail. The analysis results shows the switching time of inverter will changes abruptly if the reference current varies largely, which decreases the quality of inverter current. To overcome this problem, a method is presented to suppress the switching time change and reduces the THD of inverter current. Simulation experimental results verify the method. In order to resolve the challenge that the load's swing angle and swing angle-velocity of overhead crane or gantry crane were hard to be measured directly in engineering practice, the state observer was designed by using trolley's position information, and estimate the load's swing angle and angle-velocity. The difference value between the state observer's output and the trolley-load system's output was introduced and adjusted by the observer's gain vector, then sent to the observer's input terminal. After the observer's poles were placed on complex plane, the system can estimate the swing angle and swing angle-velocity stably and quickly. Simulation study shows that the method of obtaining load's swing angle information based on state estimation is practicable, and state observer can be available online in 2s, which has strong robust property; along with rising of the pole number, state observer can be adaptive more widely in the changing of load mass and rope length; however, estimation error will change roughly when the pole number is too big; observer is more sensitive to rope length than to load mass. Single factory building is often used the structure of multi-span hinges bent, which made of roof trass, column and foundation. The connection of column top and layer frame is the welding of embedded parts, it can regarded as hinges, the column base and based are casted together, it can regarded as rigid connect. according to the angular displacement equation, multi-span hinges bent equal section column internal force calculation method and the equivalent sidesway rigidity of staircase column were studied. Lastly, the staircase axis internal force calculation method which based on the equivalent sidesway rigidity of staircase column calculation method is established. Through the impact of fully mechanized coal mining face security personnel, equipment, operating environment and the analysis of geological environment, the establishment of a fully mechanized coal mining face safety evaluation index system is presented based on rough sets - Support Vector Machine fully mechanized coal mining face Safety assessment model. Model application method of rough set evaluation index system of attributes, eliminate redundant attributes, thus reducing the input of SVM learning sample dimension, on this basis, the use of SVM regression nonlinear characteristics of good evaluation model Of coal mine production safety mechanized mining face was evaluated, with the final example shows the applicability of this model. Many geologic hazards, such as rock burst, coal and gas outburst, have an inevitable connection with microseismic phenomena in rock mass. In order to provide accurate evidence of underground safety monitoring, inspecting microseismic signal is a good way to make sure the range and the level of underground rock breaking. Previous microseismic system using DSP or single-chip can't obtain the desired data collection, neither for the achievement of advanced algorithm. The real-time microseismic monitoring system realizes the acquisition of multiple microseismic signals and uses wavelet transform algorithm, which gives full scope to the advantages of virtual instruments. The monitoring result was very similar to actual rock burst and the error of orientation results was minor to prescriptive upper limit, which means this new system completes the monitoring of real-time microseismic emission effectively. In order to improve the performance of flight control system, a new flight control system design, based on PIC32 and real-time operating system uC/OS-II, oris proposed for a novel lighter than air unmanned aerial vehicle (UAV). This paper introduces the hardware structure and the interface and then analyzes the functions of different modules and the software flow. This design strategy reduces the system size, improves system reliability and simplifies the design complexity. Based on the questionnaire of college students' English learning motivation developed by Gao Yihong(2000), with 304 college students from some local universities as subjects, the paper aims to discuss the intensity of college students' English learning motivation as well as the most common motivation content, and compare different types of college students' English learning motivation. The results show that the intensity of college students' English learning motivation in local university are above average, which are in the following descending order: personal development, social responsibility, information media, inherent interest, achievement, going abroad and learning situation. The most common five main motivation contents are related to personal development. Undergraduates' intrinsic motivation is significantly lower than that of junior college students. And college students who have done part-time jobs have distinctive higher inherent interest motivation, going abroad motivation, social responsibility motivation, information media motivation than those of students who have no working experiences. The differences of English learning motivation in gender, grade, only child, student status, autoditacte, majors have not been found in this research. Increasing demand for storage and computation has driven the growth of large data centers, the massive server farms that run many of today's Internet and business applications. The massive amounts of computation power required to drive these systems results in many challenging and interesting distributed systems and resource management problems. In this thesis I investigate challenges related to data centers, with a particular emphasis on how new virtualization technologies can be used to simplify deployment, improve resource efficiency. A central problem in utility computing is managing the resources to support the varying demand for these applications. We propose a genetic algorithm to find the optimal allocation of virtual environments in a multi-tier distributed data center. We consider that this allocation problem is NP-hard, so we focus on approximate solutions including a genetic algorithm that appears to perform well in finding an approximate solution. The large difference between speeds of fastest phototransistor (135 GHz) and hetero-junction bipolar transistor (710 GHz) has brought important problem and challenges in designing and manufacturing of fast phototransistor. This problem is more prominent in the microwave region. New approaches are required for recognition of existing problems in the known structures for phototransistor and introducing strategies to improve its performance. In this paper, using of convoluted resonator and waveguide structure in optical detector as well as optical waveguide as an appropriate solution for phototransistor scaling and performance improvements are suggested. Robots are widely used in many applications. They are in industrial plans for doing their special jobs, for example, routing and displacement things in their locations. These robots require small cameras for prevent to encounter things and finding the path. Some of them use their camera to capture the environment changes with low details. In this paper, a new image compression algorithm is presented that uses the combination of wavelet transform and block truncation coding and have suitable efficiency and very low cost. This approach can be used for reduce the captured images. In this paper we present novel wideband quasi fractal geometry for suppression of second and third harmonics in hairpin-line microstrip bandpass filter (HLM-BPF). This new fractal geometry is obtained by modifying Minkowski fractal. HLM-BPFs have two main problems, having narrow passband and spurious bands which are located at the second and third harmonics. The former relates to relatively weak coupling between resonators and the latter relates to the difference between odd and even phase velocities of resonators. By using this novel geometry we could overcome these problems so that the second and third harmonics of fractal filters are suppressed and the bandwidth is increased to 54% of the central frequency. In order to validate the proposed geometry, third-order Chebyshev bandpass filter was designed at 1 GHz with a 25% fractional bandwidth on FR4 substrate. Theoretical and simulated results are presented. This paper presents a three pole microstrip hairpin filter for wireless application. EM simulation method is adopted in designing the hairpin filter. As technology advances, new design methodology arises. EM simulation is one of the new design methodology that makes use of the powerful design software available. The filter is designed using HFSS design software and implemented on FR4 substrate. This paper analyses the interaction of two topics: Supply Chain Management (SCM) and Internet. Merging these two fields is a key area of concern for contemporary managers and researchers. They have realized that Internet can enhance SCM by making real time information available and enabling collaboration between trading partners. The aim of this paper is to define e-SCM, analyze how research in this area has evolved and identify some lines of further research. To provide an overview of E-supply chain management (E-SCM) initiatives, focusing on the evolution and technological drivers of moving to the web. This paper also provides a framework and analysis of current efforts in the automotive, financial services, retail, technology, and transportation sectors. Forest fire is a major ecological problem that results in fall of environment apart from jeopardizing human and wild lives. Detecting the fires at their early stage and reacting in a quick rate so as to prevent the spread is the only feasible and helpful decision to decrease the harm. Thus forest fires require to be detected as early as possible in order to inhibit from being spread. This paper intends to detect forest fires using spatial data structure and spatial data mining primitives. Apriori algorithm is used for classification of meteorological data. Although the maze robot and finding solutions for it is studied for many years, but it still have many applications, because the goal is not just for the maze robots. These solutions can be used for any industrial robots for finding the best path and substitute the related contents. Solving the maze problems is not only relevant to the everyday issues of urban transportation, but is also one of the important models of network and graph theory with many applications. In this paper, we present a new solution for the maze robot based on the virtual square distribution. In this way, all the maze area is virtually divided to square sections and then the robot can specify the coordinates of its path and rotation in each direction cannot disorder the robot situation. Cross language information retrieval (CLIR) is a concept that retrieves information written in different language from the language of the users query. One of the approaches to CLIR is based on the use of Web mining techniques. In this paper we review studies of the growth of the Internet and technologies that are useful for information search and cross-language information retrieval (CLIR). It is concerned with the development of techniques to improve the effectiveness of CLIR using World Wide Web techniques. The new ways to acquire cross-language information retrieval (CLIR) resources using Web mining techniques are explained below. These ways not only improve the efficiency and effectiveness of cross-language web retrieval; but also have wider applications than CLIR. This paper presents the construction of an automatic musical fountain system controlled by audio frequency analysis using FFT algorithm. Audio signals are taken from various sources such as: MP3 Player, Cassette, Laptop, etc and these signals are first amplified and then transferred into a Microcontroller Unit (MCU) to be processed. This MCU changes Analog signals into Digital signals by Analog Digital Converter (ADC). This unit also uses Fast Fourier Transform (FFT) algorithm to give out a range of audio frequency, instead of using a complicated hardware. With this frequency band, turning on and off the valve and light systems will create the lighting and water spray effects which should go well along with showed music. Congestion management is one of the most important issues for secure and reliable system operations in deregulated electricity market. In this paper, an efficient method is proposed for transmission line over load alleviation in deregulated power system using generation rescheduling and load shedding. The proposed method is illustrated using IEEE 300 bus system and the impacts of considering different parameters such as generation rescheduling and load shedding are studied. In this paper an attempt is made to explore the use of generation rescheduling and load shedding for relieving congestion by Evolutionary Programming compared with Improved Quadratic interior point (IQIP) method based an Optimal Power Flow (OPF). The effectiveness of the proposed algorithm has been analyzed on IEEE 300 bus system. In this paper, a fingerprint-based biometric is used and protected by a computationally efficient symmetric bio hash function and generate a digest. The extracted minutiae points from a fingerprint are represented by a fixed length code vector, called bio- minutiae fingerprint code and does not assume a pre-alignment between the test and the stored fingerprint templates. The principal curves algorithm were used to extract the minutiae points from the fingerprint, then using the systematic bio hash function to compute the digital digest. The fingerprint transformation, rotation and the error rate in case of changing the position of the fingerprint has been computed and evaluated. In recent years, Robotics and Robot industries have got momentum and a large number of industrial robots, humanoid robots, and service robots have been developed. Researchers continue to design new robots with greater capabilities to perform more challenging and comprehensive tasks. The contact between the gripper and the object provides prehension and manipulation of objects. A soft hand is required in situation where the damage to the object or fingers is to be avoided. In this context, an attempt is made to determine the strength of robot soft fingers through experiments and numerical simulation. Soft fingers are assumed to be flexible cantilever beam. Two different hyper elastic materials and two different diameters are considered for the analysis. The flexural rigidity of each finger material is determined using flexible beam theory. It is further used in numerical simulation for the strength analysis of the soft fingers. This research presents the design and development of a solar powered carbon monoxide alarm. The prototype of this research was designed on a PIC16F877 microcontroller that performed the acquisition, processing and display of carbon monoxide (CO) data from MiCS-5132 automotive pollution gas sensor and displayed on 7 segment displays. The prototype used the photovoltaic panel for energize energy to the system. The system was tested using carbon monoxide from car exhaust fumes and it worked satisfactory. This paper presents an auto tracking robot using the control system on FPGA in the Development and Education Kit (DE2). There are three components of hardware: Canon Digital DCUS40 camera, DE2 board and a Robot whose front wheel can rotate freely and two rear ones are fixed in the motor. The images received from the Camera are transferred to the tracking system on DE2 FPGA. These images are processed afterward by the image processing module to determine where the color object is and what its relational properties are. After that the output of the image processing module sent to the neural network module and states machine to determine the velocity control signals and navigate control signals. Path planning has applied in many fields such as bioinformatics, CAD/CAM, layout, image processing and especially in robotics. Its target is to find out the best path with respect to some optimization criteria in order that an object can move along the path from a starting point to an ending point in two or higher dimension spaces avoiding a set of obstacles. Path planning mainly follows three approaches: search-based, sampling-based and combinatorial planning. In combinatorial planning, building a visibility graph is a main phase in the whole process and theoretically it takes Θ (nlogn) . However, with some practical applications, for example one which has a large number of obstacles, this phase is very time-consuming. This paper describes a simple and efficient preprocessing technique to reduce computation time when applying the visibility graph approach for path planning in case of many tiny obstacles. With a large set of randomly generated test problems, the experiment result shows that the computation time gets approximately a reduction factor of one-third. Spectral characteristics of speech signal have formerly been studied and reported for its quantitative information in relating the emotional state in persons suffering depression to the level of symptom affect. The spectral energy distributing in the particular bandwidths of audio frequency less than 5 KHz extracted from the subjects' speech sample reveals as the distinct parameter with a property that can represent the severity of symptom in term of energy shifting and amount change found in this study empirically. The acoustical analysis focused on Power Spectral Density (PSD) was performed on speech samples extracted from three different databases collected from the remitted, depressed, and suicidal patient groups. The result of classifications suggests the significant potential of PSD's in separating all categorized patient groups which consistently verifies that the psychomotor disturbance affects speech production system in speaker, clinically known as the central element in depression and other high-risk emotional disorders. This paper describes a neural network model for the up-take of copper during an ion-exchange process. Since the ion-exchange process is a complex and nonlinear process, the modeling based on time related empirical equations is simplistic and difficult to account for all the concomitant processes influencing the process variables. Thus, the time delayed neural networks is used to model this process because of its ability to model complex nonlinear systems without fully understanding the system. The minimum square error (MSE) minimization technique is used to determine the optimal neural network architecture for the process. The simulation results show that time delayed neural networks with two delayed inputs and one hidden layer is sufficient to predict concentration of copper during ion exchange. During repair and maintenance work of three wheeler vehicle, the front fender is used to lift the vehicle. As this fender is not designed to take the load there is need to predict the structural strength of fender. In this paper, the stresses developed in the fender are analyzed by Finite Element Analysis and experimental methods. In this paper an attempt is made to reduce the WAAS associate error and further increase the accuracy of WAAS. The WAAS can be simulated with the help of Matlab Algorithm Availability Simulation Tool (MAAST). Where we can observe that the direct use of multiple frequencies would be more accurate and offer high availability by directly estimating and removing the ionospheric effects and also another way to take advantage of the multiple frequencies is to use the additional GPS frequencies as a backup

Proceedings of the International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011), December 12–13, 2011, Hong Kong. ICIMCS 2011 is a comprehensive conference focused on the various aspects of advances in Instrumentation, Measurement, Circuits and Systems. This conference provides a chance for academic and industry professionals to discuss recent progress in the area of Instrumentation, Measurement, Circuits and Systems. The goal of the conference is to bring together the researchers from academia and industry as well as practitioners to share ideas, problems and solutions relating to the multifaceted aspects of Instrumentation, Measurement, Circuits and Systems. This front matter contains the preface, organizing committee and table of contents. Click on the PDF icon to view the complete front matter. The article is to study environment stimulate brain then response with our analysis results. The first discussion is related to the environment on brain circuits, and then discuss the different input under different brain waves, how the brain waves in different environments, proper operation, accurate measurement of the output signal. The EEG response in the circuit and its related analysis, from the brain waves of further exploration. The article referred to the interaction between the brain and the environment. Differences in the environment can affect brain waves; also affect the brain in learning and memory efficiency. So how to improve the quality and power of brain waves to help people to more breakthroughs in learning or memory. Whole brain development is the future of the paper will discuss in this direction. Currently existing extensometer may not completely correspond with the requirement of precision and linearity in the measurement of enormous structure's strain. The objective of this research is to describe a new structure of high precision extensometer sensor. An half of an annular chip serves as the elastic element of the new extensometer. Theoretical analyses and discussions about the accuracy and linearity of this new elastic element are conducted. Based on the oil sucking machine, the new structure of high precision extensometer sensor is installed to measure the micro strain as an experiment. Statics calculation examine that the deflection of measuring terminal shows linear relationship with the strain of the elastic element in certain position. Theoretically, the feasibility of a series of elastic elements is discussed. The results can provide reference value and significance in the innovation and design of industrial measurement. The design of a new tri-axial accelerometer to measure low level acceleration for low frequency vibration is described in this paper. The accelerometer is mainly composed of MEMS (Micro Electro-Mechanical System) acceleration sensor SCA610 and ultra-low power microcontroller MSP430 platform. According to the characteristics of the acceleration sensor SCA610, a method to accomplish the differential output of the SCA610 is proposed. Meanwhile, other methods based on hardware and software were used to realize the noise reduction. The experimental results show that the accuracy of the accelerometer is effective to meet the demands of low level acceleration measurement. This paper presents area-efficient reverse voltage protection (RVP) scheme for low dropout (LDO) regulator. The modified floating-well bulk-biasing scheme is proposed to protect the internal circuits from reverse supply voltage. The proposed scheme, which exploits Schottky Barrier Diodes and current-limiting resistors, can achieve small area, high latch-up immunity, and low voltage drop. A LDO regulator with proposed RVP scheme is also fabricated. The area portion of the RVP scheme is only 2.5 % in the fabricated LDO regulator. When reverse voltage supply of −16V is applied, reverse current of 10.22 mA is bypassed, and internal circuits are protected. When over voltage supply of 16V is applied, the internal supply voltage is regulated to 5.8 V. The proposed RVP scheme protects the internal circuits even in the reverse supply voltage with small area penalty and high latch-up immunity. The classical problem of a single consensus ranking determination for m rankings of n alternatives has a potential of wide applications in information technologies, and particularly in measurement and instrumentation. The Kemeny rule is one of deeply justified ways to solve the problem allowing to find such a linear order (Kemeny ranking) of alternatives that a distance (defined in terms of a number of pair-wise disagreements between rankings) from it to the initial rankings is minimal. But the approach can give considerably more than one optimal solutions what can reduce its applicability. On computational experiments outcomes, the paper demonstrates that a set of Kemeny rankings cardinality can be extremely large even in small size cases ( m = 4 , n = 15 … 20 ) and, consequently, special efforts to build an appropriate convoluting solution are needed. Success in designing affordable automated control systems for aquaculture will be widely applicable because it will enhance water management. Intensive recirculation systems significantly increase fish production per volume of water but require of dissolved oxygen monitoring and control. An intelligent instrumentation system monitored four tanks with one galvanic dissolved oxygen probe and its transmitter, predicted sensor failures and sent codes to the producer. Peristaltic pumps extracted water from each tank without adding oxygen to the sample and dissolved oxygen measurements were auto-calibrated and statistically diagnosed Dissolved oxygen sensor membrane fouling from algal blooms, sediments or suspended droplets were analyzed; membrane fouling problems were controlled by means of motor vibration and water jets. A photovoltaic system was automatically connected under power failures by the LabView interface to assure carp survival. The virtual prototype model of the cracked rotor system is built by dynamic simulation software ADAMS. The bending and torsional vibration characteristics are analyzed in time and frequency domains through setting different factors, such as speed up process, rotational speed, eccentricity and crack angle. The simulation results are consistent with numerical methods and experiment results. The primary contributions of this paper are to study crack rotor system vibration characteristics, and to validate the feasibility of virtual prototyping technology in the field of rotor dynamic, and provide a new research approach for rotating machinery fault diagnosis. The vertical vibration universally exists in the running process of cold tandem mill system. Due to the rollers chatter, either the bright and dark stripes or the visible thickness difference can come into existence, which will seriously affect the quality and accuracy of products. For studying the characteristics and mechanism of vertical vibration, a lumped- mass model is established, in which nonlinear damper between top and bottom working roller are considered, and the rollers are connected with mill housing by nonlinear spring components. By means of the multiple-scales approach, the first-order analytical approximations of steady-state periodic solutions describing the primary resonance, super-harmonic resonance and sub-harmonic resonance are individually investigated. Through graphically depicting the amplitude- frequency response equations, the jump phenomena caused by nonlinear parameters are analyzed and numerically simulated. In addition, on the basis of the corresponding autonomous system, the stability of equilibrium solutions and self-excited periodic vibration is studied by using the Lyapunov stability theorem, and verified through numerical simulation of time- history and phase-plane trajectory. These research results are significant to reveal the mechanism of chatter, optimize the technology condition and improve the product quality in practical rolling process. The issue of quality focuses attention on the effects that the variation of characteristics produces in performance and cost of products. Currently, it is considered that the variation of characteristics is the main cause of the lack of quality, resulting in reduced performance and increasing the cost of products. In modern industry, the specification of tolerances is no longer a background task, going on to be one of the key roles in product development. The paper is focused on the application of Robust Design methodology in solving specific problems of tolerancing. Several software applications were developed to help the integration of Robust Design techniques into the tolerancing activity, in particular in the choice of dimensional tolerances according to the permissible loss, in the choice of production processes and machine tools in terms of loss of average quality and specification of tolerances of quality parameters on systems with multiple parameters control and various noise parameters as well as in the determination of the best nominal values for the parameters of control with the aim of reducing the variation in the quality parameter. Dynamic capacity prediction provide strong support for develop pre-tactical or tactical flow management program. The prediction procedure of dynamic capacity is proposed and the related calculations for control sector is presented, and the dynamic density function model at different times and various traffic situation is established by using curve fitting method. Based on the new prediction method, the prediction of the sector dynamic capacity at different traffic situation is achieved. The example of dynamic capacity prediction for Shanghai control sector is given, and the results show the feasibility and effectiveness of the new prediction method. A tolerance-analysis-oriented assembly model based on datum-flow-chain (DFC) is proposed in the paper, which describes the inter-relationship among the components and parts and the detail information of their constraint and location relationships. Two steps are utilized to create the model, which are component/part level and feature level assembly model. According to the model, the tolerance chain could be got, which simplifies the tolerance-analysis calculation. Finally, a case of body-in-white assembly is used to illustrate the assembly model. Our project is a mobile application running on the Android operating system and captures an image on a Thai language sign with correct Thai wording. This process can be all done through the camera on an Android device. The process is to obtain the result based on Noise Filtering, Alphabet segmentation and the OCR algorithm. Preliminary results of matching characters show an average of 90% correctness. Furthermore, the translation process, translating from Thai into the English language, will be done by utilizing a dictionary in the database. After processing and interpreting the results, several errors occur because of the curved and contiguous characteristics of Thai font. The paper presents a study of the knowledge development in the ergonomics research field, based on the integration of the co-operant sciences: engineering, management, work safety, labor medicine, informatics etc., for solving complex problems related to occupational risks assessment, by using methods and tools of knowledge management. The complexity of the proposed approach is demonstrated by its multidisciplinary way of dealing with the thematic and by the methods applied to estimate the results (using modern tools of information and communication technologies and knowledge management). The paper presents some international/European trends and the Romanian context of the occupational risks problematic. The presentation will focus on the developed occupational risk management system that will drive on the work for defining the platform for the occupational risk assessment. Some conclusions and research perspectives will be presented in the final part of the paper. Usually in Shell and Tube heat exchangers, at the time of assembly of the Tube bundle assembly, the gasket seating face of the flanges and the gasket seating face of the Tube sheet might get distorted and damaged. Due to this distortion and damage there is a possibility of leakage during hydrotest of the equipment. To correct this distortion and damages, it is necessary to do machining in that area to attain a flat surface with required surface finish. But due to the weight and size of the assemblies it is difficult to move the equipment to the floor boring machine and machine the flat surface. In order to make it easier, a portable machine tool assembly is designed so that this machine can be moved near the equipment and machining can be done. Here a tool will rotate with respect to a horizontal axis and automatic feed is given perpendicular to that axis so that the facing operation is done and the gasket mating surface of the tube sheet is devoid of distortion and damage. Thus, this simple tool ensures leak tight joint and reliable equipment. In this study presents the conclusions of tool wear tests on a new austenitic stainless steel X2Cr16Ni9TiN, which applicated in food processing industry, and describes important concurrent parameters for the cutting zone during the process of finish drilling. The effect of cutting speed are analysed by tool wear mechanisms, and temperature tool. Based on the cutting tests, cutting speeds of 50 to 100 m/min, feed rate of 0.02 to 0.08 mm per rev. and solid a new design of screw drill from sintered carbide with hydraulic holder. Diameter of screw drill is 7.0 mm. Quality outer surface after cutting with roughness parameters down to around 0.54 µm. Very good results were mainly achieved when cutting speed was up 60 m/min to 70 m/min and the feed was interval up 0.02 mm per rev to 0.04 mm per rev. The paper described the cutting process analysis with CAD systems by drilling. Simulation of machining (cutting and drilling). Finite Element Method (FEM) based techniques are used to simulate high speed machining processes and offer several advantages including prediction of tool forces, distribution of stresses, and temperatures, estimation of tool wear, optimization of cutting tool geometry, and cutting conditions. One of the most important property of cutting tool is its durability. Cutting tool durability determines its cutting properties and machinable ability. Technical practice uses a lot of cutting tools made of different materials. According to selecting workpiece have to be defined technological conditions. For all selected technological conditions is important prescribe parameters for machining. The basic parameters for every cutting process are cutting speed, feed and cutting depth. These technological conditions are defined by means of calculation or by means of mechanical engineering tables. Specification of tool wear by means of calculation is very difficult. Durability of cutting tools is defined in standard ISO 3685. In standard ISO 3685 is defined T − v c dependence for different cutting materials and standard included process evaluation of tool durability for cutting materials made of high speed steel, sintered carbide and cutting ceramic. The article describes evaluation of T − v c dependence on the selected type of cutting materials and theirs comparison with measured values T − v c dependence that are defined in standard ISO 3685. The most important part of each new discovery, piece of knowledge or experiment is correct evaluation of outputs. Successfully realized experiment is first and very important step to evaluation of outputs, but very important part is measuring. Inputs are defined before experiment and they are accurately determined and described. Outputs have to be measured and described after experiment. Last step after results evaluation is analytical expression of tested dependence. Analytical expression of dependence represents very important part of experiments, because all tested processes can be described and defined by formula. Very important and often used standard ISO in engineering practice is standard ISO 3685. This standard includes characteristics for various cutting materials. The main part of this standard is T − v c dependence for cutting materials. In standard ISO 3685 are included cutting materials made of high speed steel, sintered carbide and cutting ceramic. The article describes process how to define and analytically express T − v c dependence for cutting ceramic (Al 2 O 3 ) and sintered carbide (P20+TiN). We describe the fusion of two separate methods, used to track a moving object with an autonomous robot. Our robot is equipped amongst others with a Laser Measurement System (LMS) and a web cam. The LMS is a so called line scanner which delivers distance values only in a horizontal plane. Due to the lack of a 3-dimensional representation of the surroundings given by this, the scanner is equipped with a custom built tilt mechanism. In this approach the tilt mechanism is controlled by an estimation from a visual object tracker to ensure, that the scanner always points to the vertical middle of the desired tracking object. This method works for all kinds of tracking objects, different velocities and manifold lighting conditions without adjustments to the parameter set. In this paper, a practical inverse model of MR damper is proposed for current tuning of the actuator to track the desired force by the control unit for vehicle suspension system. The piecewise polynomial method is used to develop a series of simple models for different regions of force-velocity characteristics of the MR damper. Accordingly, the current signal is estimated by linear formulation of minimum and maximum forces generated by MR damper. The effectiveness of the proposed model is validated for a variety of excitation in Hardware-In-the-Loop (HIL) simulation. At the Utrecht University of Applied Science we are developing an agent-based software infrastructure for agile industrial manufacturing of microdevices. This manufacturing is done on special devices called equiplets. A grid of these equiplets connected by a fast network is capable of producing an variety of different products in parallel. The multi-agent-based software infrastructure is responsible for the agile manufacturing. To test our concepts, a simulation was build based on the Jade framework, a Java-based framework for distributed multiagent systems. In this paper, we propose a systematic method (a framework) for automatic test program generation for Network-on-Chip (NoC) based Multi-Processor System-on-Chip (MPSoC) compiler validation. This framework consists of three parts: specification reader, program generator and platform simulator. By applying this framework, specified test programs for compiler validation are automatically generated as well as their corresponding run time results. The validation productivity is enhanced and the expertise requirement is reduced. We also present an example tool called Automatic VESYLA Generator (AVG) implementing this framework. This tool is used in the Dynamic Reconfigurable Resource Array (DRRA) assembler development in our research group. The experiment shows that on a personal PC, AVG tool generates bug-free test programs more than 100 times faster than a human programmer. The computer-aided design scheme of control systems for a new class of thermal generating electromechanical converters is offered. The synthesis of the optimal control systems using the technologies of fuzzy logic controller with the frequency converter as an actuating mechanism for the control of thermal process generated by electromechanical converter is considered. The fuzzy logic controller modelling results with the use of Sugeno algorithms are given. Organizational behavior is a manifestation of knowledge sharing, which has an effect on the overall competitiveness of an organization. Knowledge shape individual behaviors, which sometimes conflicts with the norms, structures and systems of the organization. Knowledge gap is being identified amongst employees within organizations that enable some employees to perform their job effectively. Knowledgeable employees are expected to share their knowledge with others to increase productivity within the organization. Unfortunately, this is not always the case. Generally, employees may behave differently within an organization due to their diverse background or according to their skills and stock of knowledge. A case study was conducted to investigate the impact of knowledge sharing on organizational performance. This includes what triggers employees to behave the way they do and how the organization respond to the behaviors. Contingency theory was employed in the analysis. Two significant indices that measure a country's development are related to science and education. To address the people's peculiar needs as developing nations, which include the aspiration to develop and the desire to compete in a competitive global village, a scientific education that addresses the specific needs of the people has to be in place. Every nation must create and maintain a scientifically educated culture to become developed or sustain its development. In the light of developing economies, they need to establish a program that addresses literacy efficiency in the technical labor force and world aware citizenry. This paper examines how the scientific but people-oriented education, EarthSpace educational system, and EarthSpace, climate change and the renewable energy education initiative may impact sustainable development in the states of its deployment. The widespread adoption of digital mobile devices has paved the way for the development of many innovative applications. Mobile devices provide a lot of services in commercial environment like Mobile ticketing, Mobile banking, Mobile location based services, Mobile auctions, Mobile purchasing and so on. One area in which a mobile device can provide tremendous benefit is in the area of health care. Till today nurses use the pager system only for informing the doctor about emergency condition of a patient. Even today they still rely on the paper based file system to maintain the patient's health records. With the usage of mobile devices, we can improve the health care system by incorporating such ICT technology as research is underway in improving the services in the Health industry, which is evident from the literature. With all these in mind, we here have developed a mobile health record system which would allow doctors and nurses to directly access a patient's health record from a mobile device form almost anywhere, giving them the ability to initiate treatment and also be more efficient in providing the best care to patients. Our proposed system also aims in entering and deleting the patient's record too, based on the need. The implementation has been carried out using JADE-LEAP agent development kit in Java enabled handset. This article presents a different way of applying the examinatios for a given subject, which gives principles that promote the use of evaluation to increment learning and develop skills in students. Competency-based training on the instrument of evaluation considers various methods that make evident the achievement levels of students. It is given a practical proposal for examinations to be applied from the perspective of competency-based training that allows develop and measure the achievement of competence reached by the students. This is a new form of examination that allows a integral development of students in a particular application context. This paper reports the organization of an undergraduate research summer program in 2010 at the University of Texas at Dallas, which is the second iteration of a three-year project sponsored by the National Science Foundation. The primary research subject is “Verification and Validation for Software Safely.” A special focus is on the evolution and refinement using lessons learned from the previous program. In keeping with this trend, we also list our plans for future programs. Precise and reliable information on the machinability of a material before it enters the machining process is a necessity, and hypotheses must be tested through verification by actual methods. This article presents conclusions of machinability tests on new austenitic stainless steels X1Cr14Ni10MoTi with Extra Low Carbon (ELC) and verified with software of CA-X systems. This article presents the results of experiments that concerned the verification of machined surface conditions of workpieces from a new austenitic stainless steel with Extra Low Carbon (ELC) X1Cr14Ni10MoTi and cutting tool wear. The results of cutting zone evaluation under cutting conditions (cutting speed v c = 70 m / min , depth of cut a p = 3,0 m m and feed f = 0.06 m m per rev.) are a definition of shear level angle and the texture angle. For X1Cr14Ni10MoTi steel Φ1 is 35°. The acquired results are interesting in that for the defined conditions we can achieve a quality outer surface after cutting with roughness parameters down to around 0.58 µm. Iron ore tailing (IOT) is a waste material from the iron ore mining processes and constitutes a nuisance both to human health and the environment. A study on its use as a cement replacement material was initiated in Civil Engineering Programmed, Abubakar Tafawa Balewa University, Bauchi, Nigeria. The preliminary tests carried out on the material showed that it has potentials for improving cement mortar and concrete properties. Setting times of cement is delayed and heat of hydration reduced by about 29 percent when cement was replaced with 40 percent IOT by mass. The workability of the concrete was also improved and compressive strength at 10 percent and beyond 28 days of curing compared favourably with the reference mix. The ratio of the flexural strength to splitting tensile strength was about 1.7. Smartcards are becoming increasingly popular in many countries and are deployed, for example, as credit cards, health cards and electronic identification documents. With these devices users control highly sensitive information and may perform security tasks such as electronic authentication and digital signature. As the importance and world-wide spread of smartcards increases, the interoperability of these devices becomes more important along with their security in environments where smartcards from different manufacturers and issuers are used at the same time. In this work we focus on the interoperability of smartcards in digital signature processes. Standard certification criteria, in particular the Common Criteria, define the security requirements; however, Common Criteria certification does not address the problem of secure smartcard interoperability. Here we consider the interoperability problem which arises when various applications interact with different smartcards through a middleware. In such a situation it is possible that a smartcard of type S receives commands that were supposed to be executed on a different smartcard of type S ′. Such “external commands” can interleave with the commands that were supposed to be executed on S . Here we experimentally demonstrate this problem with a Common Criteria certified digital signature process on a commercially available smartcard. Importantly, in some of these cases the digital signature processes terminate without generating an error message or warning to the user. This paper presents results of mapping out the irrigation potential of the sahelian region of Ghana. The irrigation potentials of four watersheds drained by the White Volta, Red Volta, Sissili and Kulpawn rivers were assessed. The irrigation potential for the sub watersheds in the region were computed by combining information on gross irrigation water requirements, area of soil suitable for irrigation and available water resources. The capacity of 80%, 70%, 60% and 50% time of exceedance flow of the available surface water resources in the respective sub watersheds were estimated. The areas that can be irrigated with these flows were computed with selected cropping pattern. Combining the land suitability map and the land use map of the respective sub watersheds, an irrigation potential map was generated showing potential sites in the Upper East Region that can be brought under surface irrigation in the respective sub watersheds. The total area that could be irrigated using the flow at 80% and 50% dependability are over 1000ha and 20000ha respectively This study develops a correlation between surface area of small reservoirs and their storage volumes using radar images (Envisat ASAR). For each reservoir, a bathymetric survey was carried out and the outline determined. The area and volume for each reservoir were calculated using geographic information system. Radar Imagery was acquired processed and reservoir surface areas extracted. Surface areas obtained from the satellite and the field survey were compared and a regression analysis at 95% confidence interval indicated that the variances of the two surface areas were not significantly different (p<0.05) indicating an existence of relationship between the two surface areas. A regression relationship obtained for the capacity estimation showed a power relationship between surface areas and storage capacities of reservoirs as, Capacity = 0.00876 Area 1.44 . This relationship can be used as a tool in integrated water resources planning and management to facilitate the process of decision-making by governments and water managers in their quest for improving water availability for irrigated agriculture and other purposes in semi arid regions The relations of the effective index and the normalized frequency with an index and temperature have researched as filling methanol for photonics crystal fiber (PCF) of the hexagon structure. The theoretical model of the photonics crystal of total internal reflection has studied in plane wave expansion method. The results of the total internal reflection (TIR) PCF temperature characteristic have obtained in filling the liquid material of high refractive index temperature coefficient. The refractive index of filling liquid and temperature affect on the effective refractive index and normalized frequency. The effective refractive index will reduce and normalized frequency will increase as the temperature increases. When the distance between adjacent holes ∧ remains unchanged, the ratio of diameter of holes d and ∧ of d/∧ is greater and the input wavelength is longer, the effective refractive index with the temperature becomes the most sensitively. The properties are valuable for design and application of temperature sensors. In view of the disadvantage of traditional eyesight test method, the article proposed an eyesight early warning test scheme based on STM32F103.The design integrates with embedded technology make tester realize eyesight test of self. Testing procedure has higher scientific and effective utilizing eyesight test algorithm. Using data storage and redisplay technique realize eyesight long time observation and short sight early warning. The paper analysis's the echo signal of the target in sea and a method based on filter in frequency-domain on FRFT is proposed. The method intercalates a band-pass filter in frequency-domain to filter the signal in frequency-domain, and then the filter can filter part clutter. After that transform the signal from frequency-domain to time domain, at this time FRFT can be better detect the target. Experiment using the IPIX data shows that the method of paper has remarkably advantage in increasing the signal-clutter FRFT peak value difference and enhancing the SCR. When the SCR is reduced to −9.5dB, the method can still detect targets easily. The optical flow method is one of the key techniques for obstacle detection. Based primarily on the work by Srinivasan (2000), a C# application was created to implement an algorithm based on the optical flow method. The performance of the application is analyzed with effective experimental results. Significant computational efficiencies were created by expanding the Graphics Processing Unit (GPU) processing to the stages before and after the optical flow process, which made the real-time practical applications of obstacle detection possible. A new design for the vehicle traveling data recorder appeares here, which is based on the ARM9 core and the uC/OS-II. The uC/OS-II is a kind of real time operation system. The new design refers to the national standard of China and the newest research at demestic and overseas these years. To schedule the task created probably, to develop the driver of the I/O, to tackle with the data received, and to store them are the vital parts of the design. Some parts based on the work of the former designer have appeared in this paper. A few experiments in the end testify some functions of the product, which is to prove the feasibility of the products to be designed, and we have made some analysis of the data in the end. Bushing is a kind of important instrument which is widely used in transformer and switch. The bushing's research will take precedence over the development of electrical equipment. This paper uses finite element method to analysis its electric field distribution, based on acquaint the insulator structure characteristic of single ceramic transformer bushing. First mathematics model of bushing is constituted. Then the ANSYS soft is used to calculate it. In the end, some calculated results are analyzed. Some conclusions are got. In this kind of bushing, the most uneven electric strengthen lies between the bushing's teeth, and the most strengthen electric field lies in transformer oil. It is easiest to appear part-discharge. This conclusion has practical instructional meaning to the usage of this bushing. The analysis method using in this paper can widely applied in more complicated condition of various bushing's electric field analysis. This paper presents a recursive weighted least-squares (RWLS) algorithm to jointly estimate carrier frequency offset (CFO) and timing offset (TO) for SC-FDE systems. The Zadoff-Chu (ZC) sequences are put ahead of each SC-FDE symbols as the unique words (UWs). Using the phase difference between the UWs of two consecutive symbols, the proposed method fits a straight line. The intercept and slope of the line are CFO and TO, which can be precisely estimated by weighted least-squares algorithm. It also makes good use of the previous estimated information, combined with current observation values, to compute recursively to obtain the final results. Simulation results show that the proposed algorithm can achieve similar performance as that of the weighted least-squares algorithm with lower computation complexity. Carrier extraction is necessary in wireless receivers, which helps correct phase error and reduce bit-error-rate. Traditional methods usually adopt the squaring loop or Costas loop for carrier extraction. The obvious disadvantages of slow convergence speed and large phase jitter deteriorate the demodulation performance. A new method, Hilbert phase detection algorithm, is proposed in this paper. First, we analyze the method in detail, and then the DBPSK demodulation model using the method is built and verified by FPGAs. A design approach to edge detection filter via utilizing Least Squares Support Vector Regression (LS-SVR) based on Canny's criteria was presented. LS-SVR is a discrete smooth filter. Aimed at the inaccurate localization of 1-D discrete localization criterion by Demigny, we proposed the new 1-D expression of criterion for “good Localization” in order to solve the optimal value. In the paper, we introduced the construction ethod of first and second derivative operators. According to the new criteria, the optimal parameters of Canny edge detection operators were determined by numerical experiment. The approach of 1-D optimal edge detection operators were also realized by adjusting LS-SVR parameters. The corresponding LS-SVR optimal parameters can be calculated. Experimental results showed that utilizing the edge detection operators designed by LS-SVR had better noise resistance ability. Based on operational modular imaging spectrometer (OMIS-II) hyperspectral image data of Qinshihuang's mausoleum area, the profile spectral curve data of the typical ground objects and the ancient site are collected and purified. Then the ancient site spectra database can be established. Taking this spectral database as a reference, the methods of spectral angle mapping (SAM) and spectral information divergence (SID) are used to identify and classify the ground objects and ancient site in study area. Finally, the classification map of the ancient site area is obtained. The results show that the classification and identification of the ancient site area based on spectra database of hyperspectral images (that is, the reference end-members can be obtained directly from the images), is not only reliable in feature selection, but also has a good correlation with image data. The classification accuracy of the above methods is also better than the traditional methods of minimum distance classification (MDC) and maximum likelihood classification (MLC). For the fine classification of typical ground objects in the ancient site area, the methods used in this paper are feasible and have important practical significance for further extracting the precise information of ancient sites. The numerical simulation method was employed in this paper and unsteady simulation methods were involved, used to investigate the unsteady flow behaviors in centrifugal compressor. Near-field aerodynamic noise was obtained, based on the acoustic theories. Results show that the major noise sources locate in the front of main blade, the area between the diffuser inlet and the impeller outlet, and the area between the entrance outlet and the impeller inlet. The acoustic power level inside the volute is lower than that inside the impeller. Skywave over-the-horizon radar (OTHR) often encounters strong transient noise which raises the power spectrum of the return signal and dramatically degrades the target detection performance of the radar system. To locate and eliminate the transient noise without distorting the clutter return (so that the clutter can be properly handled in a subsequent processing), one can transform the received signal into the time-frequency plane using an appropriate time-frequency representation. In this paper, we propose a transient noise excision algorithm based on the S transform and ridge detection. The proposed algorithm has low computational complexity and is more suitable for the skywave OTHR than the existing time- frequency transient noise excision algorithms. Using real experimental skywave OTHR data, simulation results are provided to verify the effectiveness of the new algorithm. According to the aircraft's dynamic motion posture characteristics and the recognition system real time request, this article puts forward the infrared characteristics and the changeless rules amalgamated recognition algorithm. Experiment results show that this algorithm is convenient, simple, and easy to project implementation, significantly improved the system identification speed and accuracy. This paper describes a ZigBee-based passive wireless temperature measuring system in substation. The sensor technology used in the system is SAW-based passive wireless temperature measuring. It has many advantages of no battery- powered, low cost, long life, small size, easy to install, adaptable and so on. The communication technology used is ZigBee-based wireless sensor network technology. It has many advantages of low-power, low cost, low latency, high capacity and so on. This paper gives detailed analysis on the principles of passive wireless temperature measuring and the ZigBee- based wireless sensor network. The equipment temperature measuring system in substation combines the advantages of sensor technology and communication network together, so it has superior performance and broad application prospect. AC servo systems have been widely employed in a certain sorts of gun control equipments (GCEs), and to determine the control strategies to exhibit high robustness and high precision remains the focus of attention. In order to improve the working performance of GCEs, a semi-adaptive fractional order PID control method, which is short for NN-FPID, is proposed and designed. The integration and differentiation orders are simplified as constants and all of the gains are on-line updated based on artificial neural network. The feasibility and availability of the proposed control strategy is assessed by numerical simulation. The simulation results demonstrate that the step response time is 0.5s, and a reduction of the external disturbance to about 1% is obtained. When tracking a sinusoidal command, the tracking error is about 0.024%. It is verified that the proposed NN-FPID is simutaneously of fast response, fine tracking accuracy and high robustness, and it is a fine choice for implementing the novel control strategy of GCEs. This paper introduces a block adjustment method of airborne InSAR images based on 3D model. It provides an efficient way to geocod DEMs as well as grey scale images. This new method requires few GCPs (ground control points) which are difficult to measure in mountain area. As a result, it saves a lot of manpower, financial power and material resources in the process of cartography. The new method was successfully used on InSAR images acquired over Shanxi area (Midwest of China). The experimental results show that the block adjustment based on 3D model could reach the same level of accuracy as the approach of rectifying each single image separately. The later requires a large number of GCPs. The paper introduces the basic design theory of Chebyshev equal ripple wave filter, describes the optical design methods of digital filter, stimulates the designed digital filter using the FDA tool in MATLAB toolboxes, analyzes the stimulating results further, and gives out the implementing assembly software based on digital signal processor TMS320C5509, and finally the realization of this algorithm in digital signal processor is finished. Based on Kogelnik's coupled-wave theory, diffraction efficiency equation of transmission volume Bragg grating is derived. By numerical simulation, it is analyzed that influence of writing parameters such as refractive index modulation, grating thickness, phase-mismatching parameters, deviation of angles and wavelengths on diffraction efficiency The study is shown that the maximal diffraction efficiency is obtained when phase-mismatching do not occur between the incident waves and the diffraction waves, and diffraction efficiency will be improved at the incidence of Bragg angle when the grating thickness and the refractive index modulation increases. When the incident light met all Bragg conditions,diffraction efficiency of the transmission volume Bragg grating of various thickness and different refractive index modulations is 100%. If it deviates slightly from the Bragg conditions, diffraction efficiency will decline instantly. When the deviation is outside a certain range, diffraction efficiency will drop to zero. Furthermore, we have found that it is not true that the deeper refractive index modulation is, the higher diffraction efficiency. A nonlinear background calibration technique for pipelined ADCs is proposed. By dividing the raw output of the pipeline core into different segments addressed by the digital codes defined by the outputs of the first several stages, a code-by-code gain error and offset calibration by using least mean square (LMS) adaptive algorithm is introduced to eliminate the conversion nonlinearity due to circuit nonidealities including nonlinear opamp gain. Behavioral simulation results confirm its effectiveness in significantly improving the conversion accuracy. And comparing to existing techniques, it has less limitation on the nonlinear pattern and requires a smaller hardware overhead. Aero-engine rotor fault endangering safety of aircraft, which needed to be real-time monitored. Flight Data Recorder (FDR) recorded engine parameters can objectively reflect on the engine working conditions, so the analysis of engine parameters and the in-depth study of flight data are significant to effective implementation of aircraft maintenance and condition monitoring. The article mainly uses aircraft engine rotor vibration signals recorded by the FDR to put forward an aero-engine rotor fault diagnosis method, which is based on wavelet analysis and neural network. The method uses wavelet time-frequency analyzes technique to filter the noise and waves of the aero-engine rotor fault vibration signals. Use wavelet packet to decompose quotient and to gain the frequency band energy. To summarize the fault characteristics according to the frequency energy changes, and use BP neural network for fault identification, finally to realize it by using Matlab simulation software. The results show that the method does not require the establishment of aero-engine fault diagnose model, and can effectively enhance the accuracy of aero-engine rotor fault diagnosis. In the Power-line Carrier, the reliability of communication is reduced by neutral Interference. According to the requirements of Power-line Carrier (PLC).This paper introduces how to design a 5-order Butterworth band-pass filter with center frequency of 270 KHz, bandwidth 30KHz for suppressing neutral Interference. The design of Butterworth band-pass filter can be achieved through three steps: firstly, Characteristics of the Butterworth filter is introduced, secondly, it is design of the 5-order Butterworth band-pass filter; finally, The results of the design is simulated and analyzed. The results show that S21 of pass-band is more than -5dB. A projective number display device that uses laser-diode as its light source is introduced in this article. The device can project to a very long distance due to the usage of laser-diode. The direction, shape and size of the fond being projected can also be changed. The overall idea is given in the paper, as well as the structure charts and hardware connecting circuit of the device. The innovation technique about this device has gained Chinese patent of invention. We propose the P2P chord service overlay network model to provide services and make sharing resources among mobile devices easy. The proposed SGN (Spot-based Group Network) has hierarchical service delivery network architecture. It delivers services and resources among distributed mobile devices. We suggested three business models which are plausible ubiquitous service architectures. A fault diagnosis system based on MATLAB is designed for increasing the operation security and reliability of industrial boiler. Under the MATLAB computing environment, a fault diagnosis algorithm based on principal component analysis (PCA) is realized via matrix computation and functions. The fault diagnosis system can exchange data with the boiler distributed control system (DCS) utilize OLE for process control (OPC) technology and monitor the operations and diagnose the fault on line. The effectiveness of the system is illustrated by simulation of known sensor and actuator failures in the industrial field. Plate-fin heat exchangers are used widely in many industrial areas because of good performance. But heat exchangers are subject to interferences from various factors in the course of their work, and coupled with complex heat transfer process, which makes it difficult to obtain good control quality. Therefore accurate mathematic control is proposed on the basis of the traditional control methods, its core technology is the inverse problem algorithm. The good control effects are obtained through the experiments of two-stream plate-fin heat exchangers, which proved that accurate mathematic control really is a new type of high efficient control method, because it can achieve high-quality control efficient. A high efficient inverting-charge-pump White LED(WLED) driver is presented. The driver employs a 1x/−0.5x inverting charge pump, five Low-Dropout current regulators and self-adjusting mode control for each WLED. Due to employing inverting charge pump, the driver does not require bypassing the output of inverting charge pump to ground in 1x mode, which eliminates the effect of bypass switch's dropout voltage. The mode control circuit provides individual self-adjusting mode switch for each WLED, which avoids the effect of WLEDs' forward voltage( V F )'s mismatch. The two points above inceases the efficiency of the driver. The proposed driver is designed by 0.5um BiCMOS process. Simulation and experimental results show that the driver is able to achieve high efficiency (averaging 84%) which is comparable with inductor-based driver while benefiting from the simplicity and cost savings offered by charge-pump solutions. The driver is able to drive 5 parallel WLEDs and each WLED channel allows 20mA output current. A fuzzy PID control strategy was studied to improve the performance of a controlled system of angular displacement of motor shaft. The fuzzy strategy was studied for offering the increments of the PID parameters of PID controller quickly without large quantity of experiments. The PID parameters can be tuned on line according to the error | e | of the controlled angular displacement and its change rate Δ e /Δ t by the fuzzy PID control strategy. Experimental results show that the fuzzy PID control strategy could meet the requirement of computer numerical control machine tool in industry, and is superior to the conventional PID, with such advantages as smaller absolute error, faster response and smaller overshoot. This paper presents an automatic method for Silence/Sonorant/Non-Sonorant detection based on multi-resolution spectral analysis (MRS) and ANOVA method. Our method is composed of two parts. The first is calculation of the MRS by combining several FFT of different lengths. The second is an automatic Silence/Sonorant/Non-Sonorant detection by calculating a classical statistics method such as Standard Deviation and Mean and a statistical test such as the Analysis of Variance ANOVA of each N frames of the MRS FFT. We used our Visual Assistance of Speech Processing (VASP) System applied to a corpus. This corpus was in French Belgian pronounced by Belgian speakers. The analysis of the obtained results shows that automatic Silence/Sonorant/Non-Sonorant detection based on MRS provides better results compared to classical spectral analysis of the corpora used. Classifications with ANOVA was better then the classical methods such as Standard Deviation and Mean. Based on the optical coherent

This front matter contains the preface, organizing committee and table of contents. Click on the PDF icon to view the complete front matter. To satisfy users' rapidly increasing demand for data storage, high performance storage architectures are being developed. This paper proposes a design of server platform equipped with IP storage capability based on Multi-core network processors. Running the iSCSI protocol, the server actually works as an iSCSI initiator when exchanging data with an IP-based storage area network, known as IP-SAN. To evaluate I/O performance of this platform's storage service, an Intel X86 based multicore server is used as a contrast. According to test results, this multi-core network processor based server platform exhibits good storage I/O performance. This article mainly introduces WinAC controller composed process control system and fully elaborate the system structure. Hardware configuration and process control program are realized by application of STEP7 software. This system integrates the merits of PLC and PC and possess high reliability, simple maintainance, expansibility, convenience ot re-development. This study attempts to clarify the evolution of innovation models in the context of information and communication technology (ITC) development. The frameworks developed for understanding the process of innovation consist of several major patterns in chronological order. From the 1970s, the transition of innovation models corresponds well with the development of ICT. This correspondence is essentially due to time effects, space effects and dematerialization effects induced by the ICT. With the development and maturation of the digital multi-media technology, digital multi-media copyright protection has become the hot spots. It thoroughly studies and discusses the application of the digital watermarking in multi-media copyright protection. According to the general framework of the watermarking, it has put forward the new method for protecting the multimedia products such as digital video and the digital image. It proposed the scheme and methods for the digital copyright's application. The results shows the new methods is feasibility and higher efficiency. Nowadays the computer crime has increased year by year around world due to the rapid development of computer technology. Consequently computer forensics has aroused wide attentions from scientists and government officials. In order to collect digital evidences which are supposed to be present in courts and maintain the integrality of evidence chain, crime scene protection is treated to be the critical factor during the computer forensics. This paper provides the foundation approach for initial computer scene investigation, outlines collection, documentation and electronic evidence storage. As the automated control systems have been applied to various aspects of everyday life including industrial control, oil mining, building automation and traffic scheduling, the strong flexibility and the high real-time performance of modern SCADA (Supervisory Control and Data acquisition) systems, especially their core — real-time databases, are in urgent need. In this paper, a practical architecture of the distributed real-time main-memory database is proposed, with the help of which, a modern SCADA system would be flexible enough to configure differently for different application, while still easily meet the requirements of the rigid time constraints. The speech signal is a complicated function influenced by factors such as the speaker, environment, etc. The artificial neural network (ANN) model carries on speech recognition with characteristics such as self-adaptation self-organization and self-imagination, suitable for speech recognition. This paper mainly studies the improvement scheme of traditional BP neural network in speech recognition. By making use of the scheme after improving, it can simplify network structure, accelerate operation, and shorten the training time. Internet technology is applied in daily life more and more extensively, thus, the corresponding security problems relating with internet are more and more serious. The attack to the web is now mainly from service software nowadays instead of WWW system structure. In this article, web service software and its threat to the security environment of the host computer are discussed, and the correct researching method to the problems pointed out above are presented. Taking university digital library as a case, this paper first constructs the model of services selection centering on the multi-objective features of library knowledge services selection. Next, it proposes the solution principle of the model based on the Genetic Algorithm. At last, with the help of Matlab Genetic Algorithm toolbox, it analyses and researches an example. This model can be used for reference and guidance for solving the problems of multi-objective knowledge services selection. This paper presents a survey on the Hop-constrained Shortest Path (HSP) problem. And a modified algorithm is proposed by analyzing the features of the optimal solution of the HSP problem. We apply bidirectional breadth-first search strategy to this algorithm, and try to reduce the number of vertices and edges involved in the computational process so as to reduce computing time. And the experimental results show the effectiveness of the proposed algorithm for large-scale network with fewer hops (around 6). In this paper, The Dirichlet problem for a localized nonlinear equation u t 1’1 u m = a ( x ) u p (0, t )+ b ( x ) u q ( x , t ) is investigated. In the case of p > q 1Â¥ m , It is proved that the solutions have a global blow-up and the rate of blow-up is uniform in all compact subsets of the domain. The main results of this paper are the following: A sort of three-dimensional Hopf manifold is constructed by applications of linear matrix cyclic group action on K1hler manifold; A method which could be calculated the holomorphic automorphism groups of the three-dimensional Hopf manifold is provided by means of several complex holomorphic function and universal covering theory. Recently, there is an increasing concern about the research of the non-functional demand in the interactive system, and in many cases the emotional factors can decide other non-functional demands. Emotional factors must be considered in a successful interactive system as well as the traditional usability. This paper argues that the relationship between emotion and interactive design is mainly reflected in three aspects: layout and color in an interface; design and use metaphor; interactive method, and accordingly puts forward the corresponding principles of human-computer interaction design. Applied fuzzy inference theory to expert system is designed in the paper against the problems of grid fault uncertainties. Through information rationality of expert system judgment and reasoning faculty of fuzzy comprehensive judgment combined with fault information and uncertainty elements, used multilevel fuzzy comprehensive judgment's inference engine of the most reasonable fault situation .It is valuable in project application. Network Intrusion Detection System are increasingly showing its importance for network security. Snort is a powerful lightweight network intrusion detection system. The paper proposes Snort architeture based on NAP, with high real-time and high performance. In recent years, blog has gradually become a new form of mainstream media networks,it has become an important channel for people to obtain information.In paper, by analyzed the feature of the Blog, it proposed an opinionretrieval method based on the Blog, and developeda polarity detectionalgorithm based on Negative rule to improve the performance of polarity detection part. The experimental results prove the validity of the method,Itimproves the MAP values of the system. The development of network brings opportunities as well as challenges to ideological and political work. Under the network environment, how to explore the innovative models and improve the quality of ideological and political educators is the focus of the article. An algorithm for computing discrete singular points of an algebraic surface is proposed based on divide and conquer subdivision technique and interval arithmetic. The algorithm guarantee to find all discrete singular points of an algebraic surface with any degree in any given cuboid within any given precision that is allowed by machine precision limit. In this paper we present a multimodal biometric system based on ECG and Palmprint biometrics. In the proposed system we used MFCC approach in order to extract features of ECG biometric and PCA due to extract features of Palmprint. After feature extraction as illustrated by the portions given in this document. Influence of information technology on enterprises and the done development of this ground has caused that there have been software and information systems in the most enterprises having designed the base of enterprise activity on the basis of them. But most of the used application are designed and developed by different companies and have various technologies and platforms and in actually not designed for relation with each other. Interoperability between applications of the enterprise and integration between them have been in the most important needs of the enterprise and purpose developers application. With appearance of the Service Oriented Architecture (SOA) a new approach was created in the world of software which provides possibility of implementing Enterprise Application Integration (EAI) with removing the privious limitations and defects without depending on the used platform and technology. In this essay considered the methods based of the SOA for integrating the applications and also mechanisms of transferring legacy systems to the SOA is described. The network intrusion detection system is based on the mechanism capturing network packets. Libpcap is one of the most popular packet capture library of the Linux operating system. In this paper, the working mechanism of Libpcap based on the Linux platform is analyzed in detail. In addition, building the experiment environment to test the performance of the typical multi-core MIPS network processor platform and multi-core X86 processor platform in high-speed network environment when capturing packets by Libpcap, finally come to obtain and analyze results of the test. The propitious culture in the architectural ornaments of traditional China mostly presents by the form of patterns, and is one important part of the Chinese traditional decorative arts. It is being beautified the Chinese traditional architectures, is the radiant jewelry in the traditional construction, also is the outstanding inheritance of the national culture. The propitious patterns design has the unique artistic expressive force by its profound meaning. In this paper the production of the propitious idea, design category of the propitious patterns, and the characteristic of the propitious patterns are described and studied in detail. This paper presents a survey of evolutionary approach for Clustering and how Genetic Algorithm is applied to different problem domains in the field of Information Retrieval. The paper is original in two main aspects first it gives an overview of evolutionary approach for clustering and information retrieval and second it suggests a novel evolutionary approach which serves both the areas of Clustering and Information Retrieval by developing a single Genetic Algorithm. Conventional clustering algorithms are sensitive to the choice of cluster center. Such a partition is insufficient to represent many real situations. To improve the performance of clustering algorithm, Genetic Algorithms is applied to clustering algorithms. Genetic Algorithms are robust in searching a multidimensional space to find optimal solution. This paper tries to reflect the research profile of this area by focusing more on how Evolutionary Algorithms can effectively work in forming clusters and improving retrieval performance. New possibilities in information technology and new challenges, in the higher education concept and method of stimulation earlier in computer system change in higher education based on process. As a contribution to these activities, this paper attempts to virtual classroom in the process evaluation results in the past ten years, to outline a concept for the next research direction in the future. The authors cited, and consider the new requirements and the trend of the solution to the problem of higher education project for the center. The following the change of the concept and related new and implementation method are introduced in this paper. Finally, solve the problem of the higher education for the center for the changed style draw engineering. The paper reports a study on computer and web-based college English teaching model based on questionnaire data. The subjects involved in the study were 124 second grade college students from Northwestern Polytechnical University. It is found out that most students are satisfied with the new teaching model. At the same time, they think the new teaching model needs improving and they suggested ways to improve it. The SGA (Simple Genetic Algorithm) depends on many factors and the two most important ones are Crossover Probability and Mutation Probability. In a successful run of SGA, the average fitness of the population after mating is better than the initial average fitness i.e. f new > f init Where f new is average fitness after mating and f init is average fitness before mating. The average fitness is defined as the average of fitness of chromosomes in the mating pool. The chromosomes are implemented as bit strings (i.e. 1001). These bit strings are represented using integers.The performance of SGA is evaluated in this paper by varying the crossover probability and mutation probability. The results are compared with the usual SGA. In order to measure the height of exploding object at low-altitude, a location method based on computer vision is proposed. A camera, with its intrinsic parameters calibrated beforehand, is used to take a picture of the exploding light and two point patterns. The two point patterns are used to calibrate the extrinsic parameters of the camera. Centroid method is applied to extract the centre of exploding light and the patterns in the image. The distance from the exploding position to camera is measured on the time difference of arrival of the sound and light generated by the explosion. Then the exploding position is determined on monocular vision principle. Experiment results show that the method has good accuracy and it is simple and convenient. This paper sets forth on the development and evolution of the pattern designs in the Tang Dynasty. In addition, it expatiates on the necessary relationship between the pattern designs and the Chinese modern landscape designs, taking the modern landscape designs as its carrier. It explains at some length the pattern designs in the Tang Dynasty' application as well as influences on the modern landscape designs. This paper takes the pattern designs in the Tang Dynasty as the breakthrough point, and takes the landscape designs as the research area. In this way, it expounds on the intercommunity and the adoptability of arts. Taking factual theory as the reality basis, this paper makes a conclusion through the field research. Meaningful exploration on the application of the art of pattern designs in the Tang Dynasty into the modern landscape designs are set foot in. Machine Readable Dictionaries (MRDs) provide a convenient and efficient base for systems that process natural languages. The contents in MRDs are vast and semantically linked in many ways. As new words are introduced or if semantics of existing words are altered in natural languages it becomes necessary to update the MRDs as well, to facilitate the natural language processing systems working on them. An automated system for enhancement of MRDs is a tedious task keeping in mind the vast vocabulary and word base in natural languages. This paper addresses these issues and discusses the various parameters that can assist in automating the process of enhancing a given MRD for English language. The teachers, who are newly employed by higher vocational colleges, are a preparation force for these schools to attain developments and expansions in the future, and also are a main force to train the high quality application-oriented talents. In this paper, the author makes the need plan through the analysis on the characteristics of newly-employed teachers and talent cultivation of higher vocational colleges, and then puts forward the training models of professional skills of the new-employed teachers of higher vocational colleges based on the PDCA cycle. Almost 25% of the directors in a sample of 118 A-share companies in the Shanghai Stock Exchange IPO from 2003 to 2008 have government background. These bureaucrat directors have great influence in the state-owned listed companies. They usually play the role of government, reducing the board's professionality. Besides, they often put the political and social objectives upon the companies' profit target, making companies bear more social responsibility, such as increasing employment, etc. Although the bureaucrat directors also bring in government subsidies and protection for the listed companies, they still lead to lower accounting earnings in these listed companies. Teaching Reflection plays an important role in the teachers' improvement. With the right use of modern education technology and informational network tools when teachers doing teaching reflection, it can make well because this can break the limit of traditional teaching reflection. This paper mainly talks about the content of teaching reflection by using education technology. Network remote video pushes forward the rural health care, social security, agricultural production and education information service system vigorously, and it improves an important role. The use of online video, real-time Q, remote diagnostics and other means to enhance rural plant, pharmaceutical and other industries of information technology is conducive to agricultural development and rural health development in the pharmaceutical distribution market, the consumer interests are protected. The general problem of multiprocessor scheduling can be stated as scheduling a task graph onto a multiprocessor system to minimize the schedule length. In literature, many algorithms have been proposed for the problem, such as the list heuristic, evolutionary algorithm, combine the above two, and so on. But these algorithms not considered part of the tasks needed to be executed on more than one processor simultaneously, so the above algorithms cannot solve or solve not well to this class of scheduling problems. In view of this special class of multiprocessor scheduling, this paper will propose a reasonable genetic algorithm with rational designed encoding and genetic operations. From experiment, we will find the validity of the algorithm proposed in this paper for the multiprocessor scheduling problem in which some tasks need to be executed on more than one processor simultaneously. The china ancient thoughts of the Confuceanism, the Taoism and the Buddhism and their realationships of each other constitute the major parts of china traditional thoughts culture. As china traditional culture component part—china ancient sport of keeping in good health also has very important influence actually, In some words keep controling function. Although the thoughts of the Confucianism, Taoism and the Buddhism for keeping in good health has their characteristies and advantage and disadvantage,but the three thoughts are togethered has overall reflected china ancient sport of preserving one's health school having positive practice meaning and role of individual value for today. In this paper, by carrying out an analysis on the new changes of the library reader services and integrating the current conditions of the libraries of the higher learning schools under the current new economic situation, the author conducts a discussion on how to develop and innovate the library reader services, with the ultimate purpose of promoting them to adapt to the needs of the new situation. Yang-Laplace transforms is an alternative approach to nonlinear fractional equations with local fractional derivative and local fractional integral. This paper presents a new wave equation with local fractional derivative. Finally, by using the Yang-Laplace transforms, its solution to nonlinear fractional wave equation is investigated in detail. Software testing is considered as a significant process through software development life cycle that can be managed, measured and improved continuously. Test Improvement is often referred to as the continuous improvement of the quality, and the efficiency of the testing process. This approached raised on the basis that an improved test process leads to an improved quality of the product. ISTQB test suite is a well-known recent endeavor describes the process and included activities, furthermore, it introduces few test process improvement models. In the previous paper [1], we presented a new method to improve the ISTQB test process by mapping CTP and TPI NEXT models. In this paper we aim that to evaluate ISTQB test process with TMMI model to determine current maturity level and it's weakness points. WebGIS has become one of the primary research directions in GIS. It is an efficient approach for the socialization of GIS. So it is important to research the structure and realization of WebGIS which is interoperable, transplantable, expansible and fit for various platforms. After analyzing and comparing the WebGIS system structure development and its main realization technologies, a realization technology based on J2EE is proposed. Once the traditional Chinese graphics are mentioned, it is natural for Chinese people to think of the essence of the traditional Chinese graphics which are the decoration patterns on the potteries and porcelains, jade articles, bronze ware, lacquer ware, tile carving, wood carving, gold and silver ware and wall painting, etc. These graphics possess the unique characteristics not only in China and also in the cultural history of the world, and have their own systems naturally. Besides, they are the symbol and pride of the traditional Chinese culture beyond all doubts. The traditional Chinese graphics were refined and developed by the previous skillful craftsmen from the natural life, and are able to mirror the high-quality artistic works from the palaces to the folk world. In addition, their national meanings, decorative patterns modeling, aesthetic principles, picture compositions, colors and others are the indispensable artistic cultivation lessons. In this paper, the author mainly gives a discussion about the application of the traditional Chinese graphics in the modern logo designs. Therefore, this paper is of practical and guiding significance to some extent. To shield the heterogeneity of home network for network convergence, it is important to provide architecture and QoS scheme of home network. We propose the universal network convergence architecture based on home gateway, to support interconnection between home network and external network. And we propose the dynamic QoS policy generation to shield heterogeneity of home network. Among the conventional algorithms of colorization, color transfer algorithm is the most common one. However, the traversal matching of each pixel is inevitable in the case of target color image. Though existing some improved methods of color correlation based, they make little sense on large resolution images and grayscale video rendering. This paper focuses on the use of CUDA, GPU general parallel computing platform, which is rapidly developed in recent years, accelerating colorization and adopting Secondary Coloring method to eliminate the effects of noise. The experimental results imply better acceleration. The scheduling problem is a typical time table problem in educational administration. For such a NP complete problems, when the genetic algorithm solves this problem, it has precociousness phenomenon and quickly converges not to the global optimal solution but to the local optimal solution. Therefore, we use the advantage of local search method and partial matching crossover operation to solve TTP problem with the genetic algorithm combining search algorithm. We do a lot of experiments and evaluate the performance of the improved genetic algorithm. The experiment results show that genetic search algorithm is a more superior algorithm to apply to the TTP problem. Just like building a house, learning music needs to lay solid foundation. The purpose of the piano teacher to teach playing piano is tell the students how to feel the beauty of music. Virtualization technology has provided customer with a more flexible, scalable and highly available infrastructure. Actually, the virtualization platform itself is heterogeneous, this leads major virtualization platforms lacking of interoperability, increasing the complexity of resource management, scheduling and load balancing. This article proposes a dynamic resource scheduling framework with heterogeneous virtualization platform supported to handle such issues. Based on Computational Fluid Dynamics (CFD) technique, the numerical simulation of T-hydrofoil was studied. The flow around the 2D hydrofoil was simulated by the modified RNG k-1 two-equation turbulence model. The lift coefficient, drag coefficient, lift-drag ratio and pitching moment coefficient of common hydrofoil and hydroflap on different working conditions were calculated and compared with experimental values after comprehensive analysis. The variation law of hydrodynamic coefficients with attack angle and flap angle were concluded by computing results, which provided basis in the application of trimaran. Higher education is an important special talent, cultural development of the science and technology, perfect modernization. It has two modes: higher education mode and the public welfare-public welfare model. The-public welfare pattern makes direct benefits, also have the opportunity cost of heavy losses, including education equality, education quality drop, expand unemployment, etc. Opportunity cost is the mode and aims at the higher education mode better election. A methodology of noise elimination in a gray image was tested and different parameters were investigated in order to estimate the noise level in a gray image. The estimated mean noise was calculated for variant values of the parameters and it was shown that only the number of orientation to use can affect the mean noise value, also it was shown that images with power to 2 size can optimize the noise processing. Information quality is one of the important indices in measuring quality of an individual in the era of information economy. This paper starts with an questionnaire survey conducted against campus college students, discusses the influence on students' information quality exerted by students' source conditions such as residence category, gender and parents' level of education, then puts forward some countermeasures based on these statistical analyses, intending to offer beneficial references for deeper research and practice. This paper presents the general methods of malware analysis on Symbian smartphone platform. The technical analysis undergoes in three phases: unpack the installation file, reverse engineering statically and trace dynamically (debugging). This paper gives a case study of a sample in the wild to prove the correctness and convenience of presented methods. It summarizes the behaviors of malware observed in our investigation. The result shows our methods for analysis is suitable and practical currently. The methods we presented have been used in real cases in forensic practice. Apache is the most widely used HTTP server in the world. Requests per second, transfer rate, time per request is the widely used indices in benchmarking HTTP server. This paper used benchmark test program ab which is widely used compared the performances of Apache between the multi-core network processor OCTEON5860 and XEON E5506. The results show that the performance of OCTEON 5860 is better than XEON E5506. Finally, through analyzing the advantage of network processor OCTEON5860 explained the benchmarking result. Reverse logistics has been brought to the forefront of corporate agenda not only due to environmental concerns and the recent environmental regulations, but also because of its profound financial ramifications. Depending on the specific strategy that each enterprise follows, reverse logistics may constitute a profit center. The importance of reverse logistics to the overall profitability of manufacturers and brand owners is steadily increasing as companies learn how to better decrease returns and extract value from returned parts. Closed-loop supply-chain channels are distribution systems that include activities supporting both the forward flow of goods from the manufacturer to the consumer as well as the reverse flow from the consumer to the manufacturer. In this paper, we identify the reverse logistics supply-chain channels, identify problems that companies face when they handle product returns along these channels and present the critical role that information technology and collaboration can play to mitigate many of the problems and deficiencies. It is imperative that firms operating in the reverse supply-chain channels collaborate to integrate and share information in a timely fashion. In this paper we discussed on the benefits, issues of reverse supply chain management and also focus on the impact of IT on reverse supply chain management. Tablet relies primarily on multi-touch operation control. The current operation mode is lack of asymmetric hands considering human factor. This article is based on cognitive science and human engineering which have made the research on the interactive division of operations and raises asymmetric hands operation in application of multi-point touch computers. Supporting multi-point touch and hand gesture recognition system will further enrich the user's interaction and provide more human interaction platform. In this paper we describe a solution for conversion of direct speech to indirect speech using finite state machine [FSM] parser, which uses skip list as a data structure for syntactic analysis. FSM operates in a bottom up fashion by assuming that the sentence will follow the form identified in the grammar. It looks for words occurring based on the grammar and on reaching the final state a proper sentence for the grammar is identified. Skip list provide the full functionality of a balanced tree where parts of speech are stored in separate nodes that may fail at any time i.e. skip the nodes if not satisfy the grammar rules. Establishing reasonable measures for the management of science and technology innovation, not only can reduce equipment loss, improve equipment degree work efficiency, make use of each function of equipment, make the optimization of coal mining technology in underground development aspects, accelerate the progress of the mining, optimize the coal quantity, do improve cogent accomplish high yield and high efficiency, create profits for the enterprise and also can arouse the enthusiasm of the knowledgeable employees, promote the culture construction of the enterprise, and improve the social image of enterprise with tangible and intangible profits for enterprise. In this paper, efficiency of Support Vector Machine (SVM) and Artificial Neural Network (ANN) is analyzed using unbalanced dataset. The dataset analyzed in this study is obtained from COIL Challenge'2000 and it is highly unbalanced with 94% good customers' data and 6% bad or fraud customers' data. We employed balancing techniques and SMOTE to bring the balance in the data and analysis is carried out. We employed (1) Under-sampling, (2) Over-sampling and (3) Synthetic Minority Oversampling Technique (SMOTE) for balancing the dataset. Since identifying fraudulent cases is paramount from the business perspective, management accords higher priority on sensitivity only. Therefore considering sensitivity alone, we observed that SVM outperformed with original unbalanced data. It is also observed that NN performed better with balanced data compared to it performance using unbalanced data. Internet of Things (IOT) is known as the most influential technological revolution in this century, which is treated to change the world. Thus it is of great strategic, social and economic significance to conduct research about it, while the core of that is Common Platform of the Internet of Things (CPIT). This paper explains CPIT from the aspect of framework and hierarchy, while it concentrates on the researches regarding the sensor common management, data unification and common data interface, environment supporting, services providing and so on. Besides that, this paper provides the XML implementation to the key part of CPIT as well. Digital campus construction involves the analysis, classification, and integration of existing raw data. This article describes the process of data pruning using ID3 algorithm, for the purpose of eliminating redundant attributes in the data and avoiding bias due to excess values in the integration process. It offers practical implications in data integration for colleges and universities who are designing their digital campuses. To avoid the constraint of wires during data acquisition, a wireless data acquisition system based on MATLAB and MCU is designed. Firstly, MCU, wireless serial communication module and other hardware are selected for the system, and the connection and interface for the hardware is designed. Secondly, the software of wireless communication is programmed based on MATLAB. Finally, an acoustic signal data acquisition experiment is performed to test the system, and experiment result verifies the feasibility of the system. Web publishing for SCADA system is not new. Traditional way for web publishing uses polling mode to refresh data. This method works well in most situations, but it can not meet the SCADA system for real-time data update requirements. The solutions is plugins, but the plugins have its own problems, such as security, platform, and requires too more system resources consume to use in resource-limited devices. To improve above issues, this paper attempts to present a new way for data publishing with Comet. Our solution includes a frame of SCADA system web publishing and event triggering mode used in web communication. with development of IOT (Internet of Things), a new architecture of home network is required. In the architecture, semantic description of services and devices is introduced. And hardware architecture of residential gateway is for the home network architecture based on the multi-core processor. At last software architecture of residential gateway is put forward. This paper presents the solution of economic dispatch (ED) problem of generating units with multiple fuel options based on the Lagrange multiplier theory (LMT). LMT is a conventional and efficient theory used to solve the optimal generation dispatch problem with only one fuel option for each generating unit. Finally, a simple and efficient method has developed based on formulating conventional Lagrange function to solve ED problem with multiple fuel options in this paper. The proposed approach has been examined and tested with the numerical results of ED problems with ten generating units with two or three fuel options. The test results compared to other methods and show the effectiveness of proposed approach for solving ED problems. This paper applies Robust Optimization method to optimize the public transport hub planning process. The Shortest-path Algorithm is firstly introduced to improve the initial solution and neighborhood structure. And the Robust Optimization method is applied to the problem of selecting the hub stations in the public transport network to help the decision making process. Furthermore, 8 hub stations are selected among 200 stations with the method application. The computation result shows its good usability in public transport planning. Consequently, the method can be used to instruct the public transport network in cities. In this paper, we propose a novel two-phase hybrid differential evolution (DE) algorithm with a variable neighborhood search method in order to enhance the exploitation ability of the algorithm. The algorithm is developed to solve a new NP-hard bi-objective parallel machine scheduling problem with earliness-tardiness and workload balancing as two objective functions. Due to the priority of the former, this paper attempts to apply a hierarchical approach for DE. Because of the discrete nature of scheduling problems, a random-key solution representation is used to encode solutions. The solutions provided by the proposed algorithm for 200 test problems with various sizes, outperform one of the state-of-the-art evolutionary algorithm, the two-phase genetic algorithm. In this paper an Artificial Bee Colony (ABC) Algorithm is employed for simultaneous coordinated tuning of two power system stabilizers (PSSs) to damp the power system inter-area oscillations. ABC is a population-based optimization algorithm inspired by the foraging behavior of bee colony and proven its superior capabilities, such as faster convergence and better global minimum achievement. For this, two conventional PSSs are designed in which a lead-lag structure is considered for each PSS and its parameters are tuned using ABC. A 2-area 4-machine system is considered as test system. To show the effectiveness of the designed PSSs, the study power system is tested by applying a three phase fault at a bus. Simulation studies show that the designed PSSs have good capability in damping the power systems low frequency oscillations. Computers have become an essential part of our lives. We use computer controlled equipment or computer software to complete our tasks easily. Computer can be divided into two parts. The first part, computer hardware, does the physical work while second part, computer software, tells the hardware what to do and how to do it. If you were to think of a computer as a living being, then the hardware would be the body that does things like seeing with eyes, lifting objects, and filling the lungs with air; the software would be the intelligence, interpreting the images that come through the eyes, telling the arms how to lift objects, and forcing the body to fill the lungs with air. Computer software or software is the collection of computer programs and related data that provide the instructions telling a computer what to do. Computer programmer using a computer programming language or coding and generate the computer software according to user requirement. In this paper, we investigate a supplier selection problem composed of single manufacturer and multiple suppliers under stochastic demand condition and quantity discount policy. The objective of this problem is to select the most economical set of suppliers and to allocate the ordering quantity among the selected suppliers to minimize total costs including selection, purchase, holding and shortage costs. Since the considered problem is NP-hard, this paper presents a novel hybrid algorithm (hybrid GA_VNS) that combines genetic algorithm (GA) with variable neighborhood search (VNS) to find near optimal solutions. This algorithm merges the explorative nature of GA with the exploitative nature of VNS to enhance the effectiveness of the algorithm. The performance of the hybrid GA_VNS is verified with comparing its results with the existing GA in the literature with 60 instances. Clustering analysis of data from DNA microarray hybridization studies is essential for identifying biologically relevant groups of genes. Partitional clustering methods such as K-means or self-organizing maps assign each gene to a single cluster. However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes.Gene expressions are expected to vary not only in terms of expression amplitudes, but also in terms of time progression since biological processes may unfold with different rates in response to different experimental conditions or within different organisms and individuals. Any distance (Euclidean, Manhattan, 1¦) which aligns the i'th point on one expression with the i'th point on the other will produce a poor similarity score. In this paper we use DTW distance to attain expression's similarity. The global exponential stability of a class of infinite-dimension stochastic interconnected large-scale systems with time delay was analyzed based on stochastic box theory, by constructing a vector Lyapunov function. A criterion was concluded for global exponential stability of the systems. t is independent of the delays and convenient of the computation, so it is easy for application. Based on the fuzzy control theory, this paper designs the roller press fuzzy control system through the analysis on Expert control experience and operator's operating. And then automatic system could be designed, which was used by industrial DCS system. The blind increase in the CMOS scaling technology has brought us to a stage where it has reached its saturation point. In here, after laying the basis of this work by having a look at the technology trend, a rising problem is addressed that is faced in manufacturing an MPSOC. Than the discussion is switched at reconfigurable computing architecture and it is extended till run-time reconfigurable computing to lead us to the point that how this scheme can reduces the defect rate problem of MPSOC manufactures. Furthermore, the work concludes at proposing a run time reconfiguring technology for MPSOCs as a replacement technology to reduce defect rates and enhance reliability through fault tolerance. The point emphasized than is that why not the leading market vendors switch towards this technology instead of suffering from all the high defect rates in their fabrication. This paper is not only a research review and proposal of new technology but also another step in the efforts for laying basis of reconfigurable computing as a future of computing technologies in context with problem which modern technology is facing today. Every human being should have the opportunity to make a better life for themselves. Unfortunately, many children in the world today grow up without this chance, because they are denied their basic right to even attend primary school. Various reasons like ,the lack of infrastructure, unavailabilty of proper learning environment, social barriers etc develops such curcumstancs which the children cannot bypass. This has led to illetracy thus promoting poverty. It becomes an unanswerable question that, what system should be adopted to give education in such circumstances?. One answer that comes to mind is EDUPORT. It is a complete classroom system that can be installed anywhere and education can be given in any corner of the world. This paper proposes a new classification algorithm named the Attribute Value Dependant classifier (AVD). This AVD classifier mainly focuses on identifying the relationship between the attribute values in the training dataset and the class label values. The ‘Attribute Value Dependant’ is the value which determines the extent to which each attribute value has its impact in deciding the class label is identified; and the training model is built based on these values. The attribute values in the test dataset are compared against the ‘Attribute Value Dependant’ values and based on this comparison the test dataset is classified. Since individual attribute value dependency on the class label is found, the irrelevant and inconsistent data in the training dataset are ignored during the classification and consequently the classification accuracy is improved. The performance of the AVD classifier has been compared with seven traditional classifiers and has been proved to produce better results. Today, IT is an important part of human life and does things more efficiently with Lower costs, less time and More Quality. The purpose of this study the effectiveness of IT courses on employee performance Islamic Azad University-IAU (Qaemshahr Branch, IRAN). Statistical population of this descriptive study is 498people and the sample size based on Krejcie and Morgan table was 217. Because of different objectives and indexes related to performance effectiveness, we used Multiple Attribute Decision Making with TOPSIS method for data analysis in which distance of indexes from positive and negative ideal points were evaluated. The results show that in managers group relatively improving abilities, occupational knowledge and objective realization had the highest impact and planning and decision making had the lowest impact. In Staff's group relatively improving occupational knowledge, improving quality, skills level and abilities had the highest impact and reducing costs, typing letters, occupational motivation, planning, and access to scientific resources and organizing had the lowest impact. In comparison of these indexes and their impact on managers and staff, we can say IT course's implementation was effective on IAU workers and gender and organizational posts had no impact on IT training effectiveness. When Running Linux on a multi-core processor, all of the network processing is processed by the operating system and the processing efficiency is very poor. To solve this problem, we describe a Multi-core Network Processing System (MNPS) in this paper. The MNPS divides the cores of a multi-core processor into two groups. One group runs MNPS-Linux, which is a modified Linux only retaining the same socket interface to the user applications. The other group runs MNPS-Stack, which processes the network stack without operating system and directly operates the hardware resources. Because of the offloading of network processing and no interrupt in MNPS-Linux and the directly operating the hardware resources and no operating system in MNPS-Stack, MNPS is very efficient. We can see from the result of the experiment that MNPS can get high performance but consumes less CPU resource. Since 1999, the city residents' consumption level and consumption structure in Guangzhou have big development, paying more attention to improve the quality of consumption. This article uses extended linear expenditure system model (ELES) and from the angles of marginal propensity to consume, basic consumption demand, income elasticity and price elasticity to analysis on city residents' consumption structure in Guangzhou and to understand the consuming rules of Guangzhou city residents, thereby providing policy suggestions for Guangzhou government to expand domestic demand, adjust the industrial structure, optimize and upgrade city residents' consumption structure. Before the Intelligent Science is born, people have endowed the Robots with the Artificial Intelligence. Due to the infinite possibilities of reality, the Artificial Intelligence has showed its limitations, people can only achieve the fuzzy control and simulating control on Robots. To face the infinite possibilities of reality as well as to achieve the precise control, one can only fall back on the Intelligent Science, the foundations of Intelligent Science are the Chinese Alphabetic Passwords and the Consciousness Passwords. People adjust the hand forms through the Chinese Alphabets, look for the Consciousness Passwords through the hand forms, these patterns can solve the precise control and the infinite possibilities of reality, people can achieve the Man - Robot dialogue. A high speed data processing system has been designed based on NIOS II reconfigurable soft IP cores. The mainly task of the system is to process data at high speed meanwhile to ensure the correctness of data. In this condition, user-defined SRAM logic controller combine complex flash operate mode has been designed to deal with plenty of data at high speed take the advantage of the reconfigurable characteristic of soft IP cores. System signal bit is 16, update speed is 10MHz and signal enable period is 15.3ms. SRAM using pingpang change structure processing data. By generating SRAM hardware interrupt changing Avalon bus control right and adding user-defined information such as head, time stamp ,data length and so on to ensure the correctness of data. System resource usage condition and power consumption also mentioned in detail. Wideband input voltage designed adapted to remote system control requirement. Through long time use, system has high reliability and stability. This method refers to the analysis of handwritten image to extract the characteristics of the image. As a part of the preprocessing stage the image is checked for noise removal, skew correction and slant removal. After preprocessing stage the text line is detected and word wise character wise segmentation is performed. The integer to integer wavelet transform is applied to the segmented image to extract the characteristics of the handwritten image. The high frequency part of the wavelet coefficients denotes the image details, the features deduced from wavelet coefficients can be used to retrieve the texture image and this method is not sensitive to luminance, these virtues cannot be found in tradition. In this paper, we introduce our methods and techniques to build the Vietnamese query processing component of our architecture of natural language based bus routes searching system. To construct this component, we have to resolve the syntactic analysis and semantic representation of Vietnamese questions. We have built appropriate syntactic rules to analyze various types of Vietnamese questions which we hope our system can process in this bus routes searching application. A typical model and appropriate related-mechanisms have also been established to process the semantics of Vietnamese questions syntactically analyzed by the system. This Vietnamese query processing component has integrated and tested in a complete bus routes searching system. XML has become the de facto standard for data representation and data communication over the World Wide Web. Due to the self describing nature of XML, it is accepted World Wide as a data exchange. But the same self describing ability makes it verbose and thus introduces redundancy in the document. This large document size also

This proceeding records the fully refereed papers presented at the 3rd international conference in Iasi, Romania, June 3–5, 2011. The main conference themes and tracks are all aspects of Electronics Computer Technology & Network and Computer Science. The main goal of this event is to provide international scientific forums for exchange of new ideas in a number of fields that interact in-depth through discussions with their peers from around the world. Both inward research: core areas of Electronics Computer Technology & Network and Computer Science, and outward research: multi-disciplinary, inter-disciplinary, and applications, were covered. This front matter contains the preface and table of contents. Click on PDF icon to view complete front matter. The protocol Secure Sockets Layer uses a combination of symmetrical and symmetrical encryptions. As we know, encryption with symmetrical keys is more rapid than the one with public keys, the latter offering, however, a much better method of authentication. The protocol Secure Sockets Layer-handshake allows the authentication client-server and the cooperation between parties for the creation of symmetrical keys used for encryption and decryption. This work proposes the replacement of classical techniques of client-server authentication by a quantum one, which is not vulnerable to the cybernetic attacks, and which solves the problem of Secure Sockets Layer protocol security. Assuring a correct authentication determines giving up the long row of authentication certifications used in the classical case in order to remove the existent suspicions before starting the communication process. The increase in network lifetime is one of the important challenges because the lifetime of Wireless Sensor Networks is limited by the energy (battery) of the nodes. Clustering is an effective topology control approach in sensor networks. The nodes close to each other have more overlap; they sense the same data from environment and cause a waste of energy by generating repetitive data. In this paper, a cluster based routing protocol is introduced, in the proposed protocol, in each round a certain number of nodes are specified; the nodes which have at least one neighboring node at a distance less than the threshold. Then, among them the nodes with less energy and greater overlap with their neighbors have been chosen to go to sleep mode, Also, in each round the nodes having more energy are selected as cluster head. On the basis of the simulation results by MATLAB, the proposed protocol increases the network lifetime, balances the load among sensor nodes further, and increases the network coverage. Based Dirty paper coding (DPC) is shown to achieve the capacity of multiple-input multiple-output (MIMO) Gaussian broadcast channels (BCs). In circuit data scenarios, users demand to get service at fixed desire rate. Finding the optimal covariance matrices and order of users for maximizing user capacity requires high complexity computation. To deal with this problem, many researchers use fixed order of users and get subpar performance. In this paper we present an iterative user selection scheme that aims to maximize user capacity. The main feature of the proposed scheme is that it does not impose a fixed order on the users. Users to be served are chosen iteratively considering influence from the chosen ones. Simulation results show that the proposed scheme achieves better performance than similar simple schemes. In addition, a compromise between performance and complexity can be made by a candidate user set concept. Cardinality of the candidate user set is fixed and users in the set are dynamically adjusted. Based on ADAMS, the rigid and flexible models of space-swing mechanism for the Superpave Gyratory Compactor are developed. The analysis and simulation shows the length of cranks, the initial phase of cranks and some assembling accuracy of points are very sensitive for the compaction angle of reaction frame. Bigger rigidity also gives some help to stabilize the change of the compaction angles. During the image tampering, contrast enhancement operation is often used to highlight some information, weaken or remove some unwanted information in images. However, this operation simultaneously leaves specific fingerprints in the image's pixel value histogram. This paper presents a wavelet analysis method to detect tampering image. We firstly convert the RGB color space into YCbCr color space, and extract the Y monochrome channel image; secondly, the normalized energy is calculated in the wavelet details sub-bands after wavelet transform of image's pixel value histogram of the component; finally, the altered image will be identified according to the normalized energy. The contrast experiment results about wavelet transform and Fourier transform indicate that the former is better than the latter in both false positive rates and time complexity. In addition, the proposed wavelet analysis approach can be applied to detect local contrast enhanced image, too. The results of the experiment show there is an obvious distinction between tampered and unaltered sub-blocks divided. The research of multi-objective optimization, how to find the Pareto optimum solution effectively and efficiently, has become very popular in recent years. And the logistics distribution problem is a very active domain that has been discussed by so many researchers. Though various algorithms have been applied to such kind optimization problem, the effectiveness still needs to be improved. In this paper, we analyzed the logistics distribution routing optimization problem, built its mathematical model, and used the multi-objective particle swarm optimization algorithm to solve the problem. Finally the simulation result demonstrated that the MOPSO algorithm performed better in quality and efficiency of searching the optimum path than other optimization algorithms. This research shows work in progress in comparing the genomes of two related organisms, namely the two North American strains of Histoplasma Capsulatum, in an effort to understand why one of them (G217B) is more infectious then the other (Wu24). For this we employ bioinformatics analysis tools along with Matlab and Perl programs. The results shown here indicate that the two strains have many genes in common (70%). Also othologs, paralogs, and gene families are reported. Further, corresponding contigs having common genes are found. Investigations on genetic variants associated with complex diseases are important for enhancements in diagnosis and treatments. SNPs (Single Nucleotide Polymorphisms), which comprise most of the millions of changes in human genome, are promising tools for disease-gene association studies. On the other hand, these studies are limited by cost of genotyping tremendous number of SNPs. Therefore, it is essential to identify a subset of SNPs that represents rest of the SNPs. As subset of SNPs is identified, data set should be searched as well as possible. In this study, a new method called CLONTagger was introduced, where Support Vector Machine (SVM) was used as SNP prediction method, whereas Clonal Selection Algorithm (CLONALG) was used as tag SNP selection method. The suggested method was compared with current tag SNP selection algorithms in literature using different datasets. Experimental results demonstrated that the suggested method could identify tag SNPs with better prediction accuracy than other methods from literature. Protein-protein interactions are critical in coordinating various cellular processes. They help understanding protein function and drug design. Extracting protein features from amino acid sequences is important in order to study protein-protein interactions. Various feature extraction approaches for proteins have been introduced up to the present. PseAAC is one of the most used protein feature extractor. In this work we purpose a new approach to calculate amino acid composition values. The purpose of our method is to adjust the weights of the composition values during feature extraction process. It means that bigger composition values will contribute more to prediction function than smaller ones. Our experimental results showed that our method outperformed PseAAC. This research proposes a segmentation algorithm for detecting nuclei and other regions of interests in biological tissues such as kidney and liver cells. The algorithm maximizes the edge coincidence between the edge obtained by Canny method and the edge resulted from the k-means clustering. The algorithm's effectiveness is illustrated on two images for which segmentation of four components is required: nuclei, red blood cell, tubules/sinusoids, and cytoplasm. In this paper we propose a complete high level segmentation algorithm of video flows into scenes. In the first phase we adopt a temporal segmentation method that identifies transitions with an accuracy of more then 95% in recall and 90% in precision rates at reduced computational time. In a second stage, a leap keyframe extraction method is presented that generates static summaries, at 23 % faster rate than the reference method for equivalent performances. The method generates static video summaries that capture all informational content of shots by allocating a dynamic number of frames for each shot influenced by the visual content variation. Finally, the detected keyframes feed a shot clustering algorithm which integrates a set of temporal constraints that exploit the scene properties in which either the setting is fixed or the action is continuous. Video scenes are obtained with an average precision and recall rates of 88%. In this paper we propose an enhanced 3D object planar parameterization method. After presenting a comprehensive and critical overview of the state of the art, we introduce a new barycentric mapping algorithm, based on the length ratio preservation. The proposed approach shows superior performances with respect to all state of the art techniques by reducing both area and length distortion with more than 77% and 55% respectively. Moreover, the computational complexity is equivalent with the faster technique implemented so far. A major advantage of our method, concerns the bijectivity property, which holds in all cases, and ensures valid and shape preserving embeddings for arbitrary open and triangular 3D meshes, regardless their complexity. In order to remain competitive in an environment where rapid changes occur in the global markets, business models, regulations and requirements, an organization must have an effective, functional and flexible information technology infrastructure, which will offer stability for the business and interoperability processes for customers, partners and suppliers. In the present context, where information is seen as a strategic resource of the organization, systems' integration is a step towards development and efficiency. Control structures with robust and/or nonlinearity compensator components represent one of the most successful solutions for the real-time control of the nonlinear processes. The paper proposes a structure and the correspondent original methodology of designing and physically implementation based on feedforward - feedback hybrid command. The applicability of the structure is proved using a real-time structure with an RST control algorithm. In the end, its software implementation and the obtained results are also shown. Distributed shared memory combines the shared memory programming model with physically distributed memory machines. In this paper we present our approach in implementing a software distributed shared memory system that runs on a cluster and provides access to a single address space. It's architecture is based on a modular design where every module performs a specific task: communication over the network, caching or local memory operations. Pthreads and MPI implementation details are provided along with performance results for local and remote memory operations with and without caching. Traditional business English teaching has been unable to meet the demands for talents in contemporary society. Its drawbacks make the application of computer network technology a new trend in the development of business English courses. Unique advantages of computer network technology, enriched contents, various forms, and inherent characteristics of autonomy, interaction and personalization for business English teaching open new ideas for reforming business English teaching. This paper constructs the specific modes of business English teaching under the environment of computer networks and explores the problems that exist in multimedia computer-assisted business English teaching as well. In order to address problems related to geographical distribution of application instances, data distribution has been a hot topic for years. Existing solutions are data-oriented (created by DBMS providers) and, in most cases, proven to be not quite suitable for realtime data replication. In this short paper we will present one practical case of multiple, geographically distributed application instances, using their own local databases, while real-time synchronization over a highly unreliable and expensive network is needed. The novelty of the solution described in this paper consists in transferring the replication responsibility from database level to the application logic level (business services) using a message oriented model. More precisely, each application request is implemented as a message that will be actually replicated to the other application instances. The most important issue to be solved has been found to be the global uniqueness of the business objects' identifiers. As Web applications environments standards, protocols, and development technologies become more mature, such environments develop into more dominant and more appealing tools to software application engineers and creators. Performance was always left to be handled by the advances made in the field of hardware, either in processing components like semiconductors, or in communication hardware protocols. Few moves have been taken in the direction of performance from software perspective. Most web application environments have been built on top of the current standard backbone architecture of web environments. In this paper, we are questioning the benefits of basic building blocks and whether they are designed and implemented to provide optimal performance. Better performance can be obtained with some customized changes to its building blocks. As web environments are very widely used by millions of users and client applications, it is our goal to make such architectural changes in the most delicate transparent way so that already existing applications will not suffer any compatibility problems, yet achieving a gain in performance. To achieve the flexibility and reusability of design and the excellent balance between performance and consumption, design and realize IP Compiler for DDS core based on Triangular approximation ROM compress technique. Finally it also shows the test results of the IP Compiler. It is verified by practice that the DDS circuits produced by the complier run steadily and perform excellently in most of the digital transmitters. This paper brings in Multi-source data fusion to solve the limitation of single sensor in the detecting of Forest-fire Harm Degree, and then analyses the basic theory. It sets up the forecast model of Forest-fire Harm Degree by using the BP Neural Networks and fuzzy theory and analyses the influence of temperature, humidity, rainfall, wind speed and sunlight. Through the simulation experiment it proves that the model has a high forecast precision. Virtual Reality (VR) is an innovative domain that has known exponential development in the last years. One major issue still remaining unresolved is navigation inside Virtual Environments (VEs). Following this direction the authors propose a bidirectional active treadmill based system correlated with a VE model, to provide a complete tool for VR navigation. The treadmill based interface combined with a noninvasive optical tracking method, allows a natural and smooth locomotion, in an undisturbed fashion, on a limitedsurface area. In order to establish the adequate control of the system during locomotion, two control methods were implemented and tested during a VE task. The system's architecture, testing method, test results and the author's discussion are also reported. The final part concludes with the authors' perspectives and development issues to still be researched. In this paper is presented a framework for off-line co-located mobile robot path planning using augmented reality technology. The system allows the user to control a virtual model of a robot co-located in the real environment, generates robot trajectories and simulates robot actions before the real robot performs the task. In the experiments conducted within this research a good synchronization was achieved between the path followed by the real and the virtual robot. This approach proves to be a powerful tool that offers advantages to the classical methods. Robots have a continuous increasing role in today's society as they have stepped in the human environment in order to better fulfill the more demanding and complex tasks. Ubiquitous technologies can enhance interaction between human and robot in order to achieve a more natural interaction. In this paper a framework for off-line programming of an industrial robot using ubiquitous technologies is presented. The system allows controlling a virtual model of an industrial robot in an immersive CAVE-like projection system, configuring robot trajectories and simulating the robot actions before the real robot performs the task. Human-robot interaction (HRI) is a highly researched topic in robotics, especially in assistive robotics systems. Disabled people represent a special category of persons that require special attention. Electrooculography (EOG) is a method for communication with these persons. In this paper is evaluated an interface for teleoperation of a mobile robot by means of EOG signals. Eye saccades are used for sending movement commands to the robot. The obtained results prove the effectiveness of the evaluated interaction method. This paper mainly explores how oversampling and feedback can be employed in high-resolution (Σ-Δ) modulators to extend the signal bandwidth into the range of megahertz, where oversampling ratio is constrained. A 2-1 cascaded multi-bit architecture suitable for broad-band applications is presented, and a linearization technique referred to as partitioned data weighted averaging (DWA) is introduced to suppress in-band digital-to-analog converter (DAC) errors. All blocks implement in the popular MATLAB/SIMULINK environment. The proposed set of blocks also takes into account most of non-ideal factors on sigma-delta modulator. As shown in the experimental results, for a 1 MHz signal bandwidth and −3dBFS input signal, the MASH 2-1 4-bit sigma-delta modulator can achieve 52.5 dB SNDR (signal to noise-and-distortion rate) at a 24Msample/s Nyquist conversion rate with an oversampling ratio of 16. A low-distortion 2-2-1 cascaded sigma-delta modulator for wide-band applications is presented. The topology includes three stages: the first and second stage is formed by second order low-distortion multi-bit architecture, while the following stage is realized by first order structure. This kind of architecture can greatly reduce the non-linear effects by using low-distortion architecture, and suppress the in-band noise, so it can reduce the over sampling ratio(OSR) effectively. The 2-2-1 cascaded sigma-delta modulator employing 4-b quantizers in very stage makes all quantization noise sources negligible at oversampling ratio(OSR) of 8. Behavioral simulation takes into account most of the non-idealities and experimental results show that for a 12.5 MHz signal bandwidth and 200MHz oversampling frequency, the modulator achieves a peak SNDR of 88.1 dB and an effective resolution of 14.34 bits with OSR of 8. The simulation also shows that it has well over loaded condition and power saving characters. This kind of topology reveals a good efficiency in the wide-band applications. In this paper, we survey the normalized subband adaptive filter (NSAF) structure and some improved algorithms proposed recently. These improved algorithms are mainly to avoid the conflicts between fast convergence rate and small misalignment or low computation complexity occurred in conventional NSAF. Finally, we compare the performance between NSAF and its improved versions through simulations. In this paper, we propose a new subband adaptive filter (SAF) structure and derive a new adaptive filter coefficients algorithm according to the principle of minimal disturbance. The proposed new structure is based on the two-stage subband decomposition, which can generalize old SAF structures, and therefore lead a novel insight into SAF structure. We also present the Complexity analysis. Compared to the old structure with one-stage decomposition, the new structure exhibits faster convergence rate in similar complexity. Simulation results validate the efficacy of the new proposed structure. Wireless Mesh Networks (WMNs) have attracted significant interests in recent years because of the flexibility and reduced costs. Routing protocols for WMNs is one of the most important factor and the prevalent research topics. According to the objectives of performance optimization, they can be divided into six categories: Hop-Count Based Routing, Link-Level QoS Routing, End-to-End QoS Routing, Reliability-Aware Routing, Stability-Aware Routing and Scalable Routing. This paper focuses on four kinds of the classification, giving the basic train of thought and example protocols. We will analyze the performance and compare their difference. A lot of work should be done to provide efficient routing protocols for the development of WMNs. A new DOA estimation algorithm in coherent source is proposed. The proposed method has a low RMSE performance compared to the conventional MEVT and RECONSTRUCT. Specifically for near angles and correlated signal, this new method had better performance. To verify the theoretical analysis, computer simulations are implemented. The coupling metric validated in this paper identifies Hidden coupling that is used to reduce the redundant code, and to measure the reliability of a program. Redundant code may prove to be a source of error and reduction of reliability, other than the overhead of maintaining and storing extra lines of code. The metric was applied on projects developed in .NET platform. It was found that on removing redundant code about 10–14% reduction of lines of code was achieved. Moreover, projects with redundant code were found to be prone to error. This paper presents a framework for ICT integration based on the Delphi approach. The goal is to construct an assessment and a monitoring framework that can be used by schools in the process of ICT integration. Experts consisting of ICT in education stakeholders participated anonymously in the Delphi process. A framework was drawn based on the consensus reached. The framework was pilot tested in one division participated by a total of twelve (12) schools covering both elementary and high school levels and public and private schools. Each school was ranked according to its ICT integration score and patterns were analyzed. The highest ranking school scored 46.99%. The division scored only 32.75% of the ideal. Concrete development paths are to be drawn up for each school and for the division which will be used as a model for national implementation. Though cognitive radio (CR) technology has been presented as one useful technology to enhance the spectrum efficiency, co-channel interference from the cognitive user (CU) to primary user (PU) can not be ignored. In order to obtain the maximal throughput, PUs should find out a new technique to derive good performance. In this paper, we present precoding schemes for the downlink of a MIMO system with the coexistence between a set of primary users and a cognitive user. The effective Zero-Forcing Beamforming (ZFB) algorithm is proposed to maximize the sum rate of PUs and satisfy the co-channel interference constraint from the CU to PUs, the total transmitted power constraint for primary access point (PAP) as well as the Signal to Interference and Noise Ratio of the CU is bigger than a given threshold γ . Simulation results show that our suboptimal algorithm is able to achieve high sum rate throughput with low complexity. Mobile Agent Technology with a lot of benefits and dynamicity is suitable for many fields, especially in e-commerce. In this paper, a variation in Centralized Key Server Infrastructure for e-commerce applications based on mobile agent is proposed. This variation saves the turnaround time1 of mobile agents, which they spend on waiting at the agent platform while platform is accessing the public key of mobile agent from key server. This variation is suitable for those applications where response time is the most critical parameter. We have simulated different scenarios using OMNeT++. The results with the proposed approach show a significant improvement in turnaround time of a mobile agent. Technological advances gave phenomenal growth to the implementation of 24 × 7 network convergence technologies, internet and its application in any organization be it government, academia, enterprise or personal finances. There is a need to protect the confidentiality, integrity and availability of data, network assets and services from associated vulnerabilities and threats. This paper aims at proposing a secure, reliable network infrastructure model which is critical to support growth, enable efficient operations and improve effective communication with customer, and partners. The proposed multilevel defense model is based on best practices, strategies, security policies cut out in accordance to the individual need of the organization. The effective management of network elements such as routers, firewalls, the placement of the firewalls, use of protocols and their monitoring through SNMP protocol can proactively detect any malicious activities or intrusion and can warn the system. Honeypots are used as first line of defense. CGM is an industry standard of POSC (Petrotechnical Open Standards Consortium), a widely used graphic format in petroleum exploration and production. According to the modern development principles for component technology, an approach to develop the parsing and customizing platform for CGM format with VS.NET and Carnac.NET is presented. This provides a flexible component based toolkit to parse CGM in integrated applications for Web services. Through the research on the existing data mining and association rules algorithms, for the deficiencies of the current association rule mining algorithm Apriori, this paper presents an improved Apriori association rule mining algorithm. The improved algorithm can reduce the number of generated candidate item sets and database scans through cutting of the frequent item set, thus greatly improving the efficiency of mining association rules. Through the research on the existing wireless sensor network (WSN) and its security technologies, this paper presents a design of the WSN-based secure routing algorithm. This design uses the existing routing algorithm as chief source, adding the security guidance strategy, introducing the location key information, to enhance the security performance of WSN routing. The improved routing algorithm makes the WSN routing achieve better anti-attack in the case of little overhead increase, therefore has high practical value. Current mobile context-aware applications for pervasive environments have been designed to consume information from computational nodes or devices in their surroundings or environments. As the hardware industry continues making much smaller, compact and cheap hardware, the vision of having plenty of very small powerful digital networking nodes in, for e.g., the living room or bedroom, is not so far. Designingsoftware that can make optimal use of all these computational nodes when needed is still challenging; since software will not only consume information from these nodes but parts of the software can be hosted on these different nodes. In this paper we propose the BubbleCodes Framework which is a generic application partitioning and retraction framework for next generation context-aware applications that will have the capabilities to partition and retract themselves on multiple computational nodes in a pervasive environment. Many commercial banks take operational risk and market risk into account when calculating capital adequacy ratio. This paper mainly elaborates on the application of EVT in the measurement of operational risks in financial institutions. There are roughly two ways to proceed with the EVT analysis on extreme operational loss events, the first of which is based on the point process, which is called POT, where it chooses a threshold and ignore when the events happened. According to the domestic financial institutions, the author suggests that at the early stage they should (1) build reliable OR data base, (2) design sound operational risk indicators, and (3) calculate and provide sufficient economic capital to defense the OR. This paper studies the relationship between energy consumption and economic growth of three northeastern provinces using ARDL model. And results show that there is a short-term and long-term unidirectional causality between economic growth and energy consumption in all three northeastern provinces; Jilin province shows the strongest correlation between energy consumption and economic growth, but its economic growth has the lowest dependence on energy consumption in all three provinces. This paper concludes that the short-term dependence on energy consumption in economic growth should not be ignored. In economics and finance, the Value-at-Risk (VaR) is a measurement of the maximum loss not exceeded with a given probability over a specified time. The VaR is an important measurement, as it gives a financial institution with confidence the maximum loss it can incur over time. In this paper, we briefly appraise general VaR measures. Subsequently, we introduce the idea of using the market volatility to make the VaR estimate, more responsive and efficient to the changes in the financial market. In this work, assuming as a model of price dynamic the Multifractional Processes with Random Exponent (MPRE), we analyze the behaviour of simulated time series in terms of autocorrelation. We show how, properly choosing the random exponent of MPRE, it is possible to capture the slow decay of autocorrelation of squared returns by preserving the absence of correlation in returns. The empirical analysis spotlights that a probable link between the previous two stylized facts and the fair behaviour of MPRE in their replication seems to be the continuity of the random exponent. In this paper, we examine the effects of split share structure in China on accounting conservatism. Using 5762 firm-years data about listed firms in China stock exchanges from 2001 to 2005, we find that the percentage of non-tradable share and the largest shareholder ownership have significantly negative effect on accounting conservatism. Demand from non-tradable shareholder is less than that from tradable shareholders in China. The small and medium-sized enterprise promotes the national economy development, constructs the market economy main body, the promotion social stability the foundation strength. Especially current, was guaranteeing that the national economy moderate increase, the alleviation employment pressure, realizes aspects and so on rely on science and education to rejuvenate the nation, optimize structure, is playing more and more vital role. Therefore, the correct instruction state-owned Small business reforms, supports each kind of small and medium-sized enterprise development vigorously, has become the current urgent strategic mission. But because the industry gathers the degree to be somewhat low, industrial colony quantity are few, independent innovation ability to be weak and so on question existences, has affected the industrial colony effect display and the colony risk control. Therefore, the transform outmoded habit and custom, the promotion industry colony forms target-oriented; Strengthens the innovation system construction, sharpens the independent innovation ability; The guidance enterprise marries forms an alliance, the promotion industry group develops; Will speed up the financing system construction and so on will be the key point which the industrial colony will construct. The unique geographical position of Gan Jiang Yuan, which has a significant value for researching, make it become the core region and key areas of the water conservation and ecological protection in Poyang Lake Ecological Economic Zone. Using papery terrain map, DEM data of the researching region was created. Based on texture information of the 3D surface from ETM+ image, then image and DEM data were overlapped to create three-dimensional terrain modeling and visualization of Gan Jiang Yuan Provincial Nature Reserve and its Application. The circular chromatic number of a graph is a natural generalization of the chromatic number. Circular chromatic number contains more information about the structure of a graph than chromatic number does. In this paper we obtain the circular chromatic number and circular list chromatic number of special graphs such as generalized circle, C n m , and their r -corona graphs. It is also show that there are all star-extremal graphs. The issue of coloring is very important in the graph theory. Fractional coloring as generalized coloring has used in many fields of computer science. This paper compute the fractional total chromatic number of generalized θ-graph using its definition and given lemma. Also, we obtain the fractional total chromatic number of r-corona graph for generalized θ-graph. Xunhua-Guide area is located in the middle-east part of the northeast Tibetan Plateau, and its relief is characterized by step-shaped low-relief at different elevation. In this paper, we argue the optimum filter window size of local relief which is 450m×450m, and discuss the geomorphological characteristics of Xunhua-Guide district based on numerical analysis of a digital elevation model (DEM), such as mean elevation, summit and base, as well as local relief and mean slope, from a high quality digital elevation model data. The largest relief is localized along the plateau's mountain rim, and mainly associated with active faults. It is characterized by low values of local relief which are related to sediment-floored flats and the deeply incised valleys prevailing in the low elevations and planation surface in the high elevations. The geomorphological features in Xunhua-Guide area indicate that the northeastern Tibetan Plateau under went a growing process of thrust uplift and the foreland basin vertical aggradation from the Oligocene to the early Pleistocene and regional tectonic uplift and river deep incisions after middle Pleistocene. Determination of the effect of the physical and mechanic properties that the aggregates have on concrete strength is only possible with the tests conducted. These studies take a long time and mostly are not economic. Therefore, different methods formed by utilizing the experimental studies done before are used to determine the strength characteristics. Results obtained from the model formed with the strength properties of concrete made by setting off from the physical characteristics that the largest component aggregate forming the concrete have and the results obtained with Linear Regression are compared in this study. Concretes complying with TS 706 standards have been prepared by keeping all components other than the aggregate forming the concrete constant and the 7 and 28 days compressive strengths of these concretes have been measured. The values determined experimentally have been estimated by developing models in Artificial Neural Networks and Linear Regression methods. 20 variables including crushed sand, Specific Weight of fine aggregate and coarse aggregate, Water Absorption, Dry Unit Weight, Bulk Density, Tight Unit Weight, Los Angeles Abrasion Strength, Fineness Modulus, and Flatness Modules have been used at the input stratum and 7 and 28 days compressive strengths have been used at the output stratum. It has been observed at the comparisons that the training and test results in the models can be estimated very close to test results. This paper presents an algorithm for a novel implementation of morphing 3D objects representing different facial expressions of the same head model, using masks. Specific selections of the face are morphed towards one specified target, whereas other selections of the same object are morphed after other targets. This way, novel facial expressions could be fastly processed, saving loads of the 3D modelers' time. Our algorithm also brings about a way to smooth out the unnatural aspect that appears on the model (after morphing) at the borders of the morphed selections, by partially applying the morphing transformation on a transition area surrounding the selection. Linear or non-linear functions are used to model the influence of morphing on this area. As a result, natural and lifelike new facial expressions of the model are saved with minimal human intervention (based on a set of manually modeled facial expressions). Most of all, we also present an algorithm that automatically calculates the transition area by determining the influence of the morphed selection on each row of vertex neighbors of each vertex on the selection border, thus even more reducing human intervention and improving the results. The test 3D head-model and its set of different facial expressions that were used as a basis for research in this paper were created (from concept scratch to actual 3D modeling) by the author of this paper. They served as a good work material for testing the efficiency of our algorithm. The implementation was made in C++, using OpenGL. Stochastic symplectic integrators arising from the generating function approach of constructing symplectic numerical methods for a linear stochastic oscillator with multiplicative noise are investigated. Numerical tests show efficiency and superiority of these integrators in comparison with non-symplectic numerical methods. Resorting to various writing techniques, the composer Cristian Misievici elaborates a particularly complex composition where modernity becomes a tool devoted to expression and where these two elements naturally intertwine to outline several musical pages conveying a sonorous landscape imbued with Romanian ethos. Symmetry, raised up to the rank of principle, becomes a compositional concept as well as a writing technique, being applied to almost all language elements. This study aims at organizing discontinuity based on a certain periodicity of “voiding the fullness” within a rhythmic flow made up of equal durations with a pulsation value. The main working method lies on numerical combinatorial devices (permutations) from the larger chapter of set theory. Analyzing in detail the musical structure could be helpful, but not enough to understand the profound sense of the music. Mathematics and arithmetic involve intuition and imagination, but have to be entirely precise. In the mean time, music is more original while it beaks the rules and principles. The composers are creating exceptions all the time. In The Art of Fugue , Bach reveals a magnificent mathematic thinking and musical intuition, at the same time. Mozart's opera The Marriage of Figaro is the result of both musical inspiration and mathematical intuition. Animated theatre is an art around which there is still much debate and prejudice. Its labelling as „minor art” is due to ignorance, misunderstanding and an unjustified misconceptions of those who express very strong opinions on this issue. Actually, the art of marionette theatre is governed by laws, techniques and specific poetics, which are well-established and influenced by both performance and visual arts, but also by the need for metaphor and technical rigour. Our study stems from the Essay on Marionette Theatre by Heinrich von Kleist. The present study starts from the technique of developing rhythm by added values to deduce a principle of selective asymmetrical augmentation within several rhythmical series of a bichronous type. Due to the structural peculiarities which occur within the series as a result of the transformations to which they are subjected, this study of rhythm may well be regarded as an investigation in the area of the “aksak”. The working method is mainly based on certain elements of numeric combinations. Iannis Xenakis, composer, mathematician, engineer and architect, born into a Greek family residing in Romania (b.1922, Brăila — d.2001, Paris), skillfully combined his knowledge of various fields, which led to a novel artistic creation where arts and mathematics are blended together. Starting from mathematical calculus Xenakis achieved important architectural and compositional creations among which impressive multimedia events are included. Xenakis's contribution to the achievement of the first multimedia project, the Philips Pavilion and Poème Èlectronique , was truly remarkable as it consisted of building the architectonic structure on one hand and composing a section in the audio part on the other hand, for both of which mathematical calculus was used. The B.A.C.H pattern presents generative qualities that are syntagmatically and paradigmatically articulated in micro and macrostructural symmetries, translation and mirror symmetries (including palindromes). B.A.C.H has 2880 variants = 10 (the B.A.C.H motif + 9 variants that are obtained by modifying the central minor third) × 12 (transpositions) × 24 (permutations). Standardization of music performance assessment improves the objectivity of the evaluative process in music performance. By calculating the interjudge reliability and by analyzing the adjudicators' performance ratings variability, we have discovered a significant impact of performance presentation format (audio versus audiovisual) and of marking schemes (global versus segmented) over the standardization level. Results have shown that segmented marking assessments of audiovisual music performance determine a higher consensus between adjudicators and reduce ratings variability. In this paper we analyze Greek composer's Fani Kosona's piece Structural Instability for solo piano (2007), initially by using strict musical techniques and consequently considering the mathematical basis in which the inspiration of this work lies, namely the concept of structural stability-instability. Commencing by the analysis of this particular piece, we aim to demonstrate that the mathematical background and the associated constructivist logic hidden behind a musical piece do not necessarily act as more restrictive factors to the composers' inspiration and freedom than other, pure musical criteria do, nor do they undermine its artistic value. In the same time, the reception of the work from the listener can be fully integrated and constructive independently of the knowledge of the underlying mathematical norms. The works of Tiberiu Olah, deeply rooted in the archaic layer of Romanian folklore, reveals rhythmic, melodic, timbral and expressive structures built on a predetermining mathematical thinking. The cycle of symphonic poems dedicated to the sculptor Constantin Brancuşi (Endless column, Table of silence) as well as the works Constellation of man and Events 1907 use articulate mathematical structures by the variety of acoustic parameters, both at a micro and at a macro-structural level. We will refer to a series of mathematical notions, which can also be regarded as mathematic models or correspondences of some composition strategies from O. Messiaen's symphony entitled Turangalîla . The involved mathematic notions are: cartesian product of functions, compound functions, periodical functions, partial sum of arithmetic sequences. For school to offer the chance to study in a logical and appropriate way the elements of the musical language, the innovation in the teaching act is needed. To eliminate the stereotypes which have shown during the time inefficiency beyond the aesthetic effect, the musical language must be logically understood, and for this, the using of even more information and acquired skills at other disciplines is needed. Here is that the mathematics is one from the most needed. The organized frame of the musical activities, in which pupils receive and interpret music, according with their possibilities of understanding and giving back, bring them closer, consciously, to their beauties, shapes them, harmonize them, balance them, helping them to fit in society, perceiving it as a functional universe. Aims: the objective of this paper is to show the links between numbers, geometrical figures and musical composition. Methods: the aims are achieved by research into historical ways of thinking about numbers, geometrical figures and the symbols which can be associated with them; by reference to the author's own experience in these associations; and by illustration on the basis of the author's compositions. Result: the paper demonstrates that it is possible to create music on the basis of associations between numbers, geometrical figures and the corresponding symbols. The automation is a new creative concept and the automated achievement is the apogee of a process in which the artist will put together a corpus of architectural elements through a dynamic model which will ensure an independent and ephemeral existence. In this context, the artist creates a perpetual reconstruction center, assuming the risk in which the work is dissolved into a flow of signs. The aim of this realization is to demonstrate that a graphic designer creates contexts, interfaces and sign systems that invite people to sustained interactions. They lead to parallel creations by using an astonishing amount of experience. The most used methods are: the digital art experiments belonging to the first artists who related the mathematical calculation with the harmony of the image and the mathematical and compositional rules application in order to create web pages. One of the results of applying these methods is the manipulating of the switching the spectator position with the actor position. Therefore, the purpose of the artist is to create contexts, interfaces and systems that invite to a progressive interaction. They lead to parallel creations using a rich and meaningful experience. In fact, all the internet users are influenced to switch the spectator position with the actor position, to pass from the consumer status to the provider status, from audience to production. The line is the basic graphic element used to define geometrical shapes. Straight, broken or curved, the line represents the reference for the marks or product's macro geometry or micro geometry. The designer uses this geometric element to create shapes, textures and finishing's. The objective of the paper is to highlight the role of the line as a main geometric and graphic element in communication of information about the aesthetic, constructive, technological or functional aspect of the benchmark or of the product. Theoretical and practical researches taken from the graphical analysis of some products on the market or from original proposal of products concepts highlight the role of the line in design process. The notion of rhythm is used in the language of many areas like philosophy and sciences (mathematics, astronomy, physics). In the social area is used in an emotional- simulative way such as “this activity has to have more rhythm” or “we have to give more rhythm to this action”. In the sport's area the notion of rhythm is frequently used regarding speed :”you have to give more rhythm to this movement”. Starting from the reality of understanding the geometric simplicity of classic visual universe, the use of mathematic language calls for a new concept, transdisciplinarity, able to overcome any difficulty of communication and grasp of contemporary visual arts, from abstract art to the kinetic and digital, computer-assisted art. Entered into Dan Voiculescu's chronological catalogue among the last finalized titles (July, 2009), Fantasia e Fuga sulle pedale per organo requires a simultaneous analytical reading, both from the perspective of the Baroque and modernity, being built upon a vectorial algebra of the music intervals employed. The stylistic bivalence of the entire piece is also reflected in the type of grammars used in modeling this novel opus; while the author applies a traditional grammar for the form shaping, by designing the discourse according to an early Baroque formula, he resorts to a generative grammar, typical for 20 th century music, for the elaboration of the content. The two levels of the text — the Baroque and the modern - overlap in a harmonious fusion and prove that the author rarely departs from an adherence to strict contrapuntal principles. The stylistic cross product is obtained by shaping the topography of the piece using the interval algorithms as a key parameter. Among the concepts the musical thinking of the XXth century are based on, there are principles, like symmetry, which derive from the proportional thinking specific to mathematics. The study depicts the way in which the composer Liviu Glodeanu exploited symmetry to design his own modal range, which he turned into a system, whose elements are tightly interconnected in the musical work Invenţiuni pentru suflători şi percuţie op. 14 ( Inventions for Wind Instrumentalists and Percussion Players Opus 14 ). The study points out how symmetry can be applied to the basic, five intonation element modes, as well as to the reunion modes by means of the set theory. The association between the science of mathematics and the musical art yield abstract connections in the conceptual layouts of the instrumental player. The creative thinking is dependent upon the prior interpretative layout of the musical work. The constants and variables generating abstract equations of the complex sound system all depend on the sounds and the tones which make up the musical sound phenomenon, thus facilitating the understanding of the complementarity between music and mathematics based on the concepts centered on the ineffable explained to the humanity with the help of science. Ancient Greece's architectural ensembles were organized according

Robust Adaptive Control for Fractional-Order Systems, with Disturbance and Saturation provides the reader with a good understanding on how to achieve tracking control and synchronization control of fractional-order nonlinear systems with system uncertainties, external disturbance, and input saturation. Although some texts have touched upon control of fractional-order systems, the issues of input saturation and disturbances have rarely been considered together. This book offers chapter coverage of fractional calculus and fractional-order systems; fractional-order PID controller and fractional-order disturbance observer; design of fractional-order controllers for nonlinear chaotic systems and some applications; sliding mode control for fractional-order nonlinear systems based on disturbance observer; disturbance observer based neural control for an uncertain fractional-order rotational mechanical system; adaptive neural tracking control for uncertain fractional-order chaotic systems subject to input saturation and disturbance; stabilization control of continuous-time fractional positive systems based on disturbance observer; sliding mode synchronization control for fractional-order chaotic systems with disturbance; and more. Based on the approximation ability of the neural network (NN), the adaptive neural control schemes are reported for uncertain fractional-order nonlinear systems Covers the disturbance estimation techniques that have been developed to alleviate the restriction faced by traditional feedforward control and reject the effect of external disturbances for uncertain fractional-order nonlinear systems By combining the NN with the disturbance observer, the disturbance observer based adaptive neural control schemes have been studied for uncertain fractional-order nonlinear systems with unknown disturbances Considers, together, the issue of input saturation and the disturbance for the control of fractional-order nonlinear systems in the present of system uncertainty, external disturbance, and input saturation Robust Adaptive Control for Fractional-Order Systems, with Disturbance and Saturation can be used as a reference for the academic research on fractional-order nonlinear systems or used in Ph.D. study of control theory and engineering. This front matter contains the contents, preface, series preface, symbols and acronyms, and is available for free viewing by clicking on the PDF below. eBook keywords: adaptive control, control systems, fractional-order, nonlinear systems, fractional integral, fractional derivatives, neural control, sliding-mode synchronization, external disturbance, input saturation, control theory. Over the past decades, fractional calculus has attracted increasing interest from researchers, and has been widely applied in fields in engineering and physics, such as system control, electromechanics, and signal processing. Since the mathematical model of a real plant can be accurately described via the fractional-order differential method, many systems can be expressed as fractional differential equations, for example, fractional-order economic systems, fractional-order biological population models, fractional-order financial systems, and fractional-order chaotic and hyperchaotic systems.With the development of fractional calculus, problems of control and synchronization control for fractional-order systems have been extensively investigated. So far, some important control schemes have been reported for fractional-order systems as follows. In this section, several important functions of fractional calculus, the definition of the fractional integral, three main fractional derivatives, and some important lemmas are introduced, which will be used throughout the book. Over the past decades, some important results on fractional-order controllers have been proposed for various systems. Podlubny introduced the concept of a fractional-order PI λ D μ controller, including a fractional-order integrator and a fractional-order differentiator. A well-known fractional-order controller was presented by Oustaloup et al. Li et al. proposed a novel fractional-order controller, based on Lyapunov stability theory; fractional-order chaotic and hyperchaotic systems were controlled by the proposed fractional-order controller. A novel chaotic system without equilibrium was proposed, and a fractional-order controller was designed to control the chaotic system without equilibrium, by Shao and Chen. Fractional-order controllers are effective in controlled systems, as has been proved in the mentioned works. Furthermore, FODOs have been widely studied for the control of fractional-order systems. Shao et al. studied FODO-based adaptive sliding-mode synchronization control for a class of fractional-order chaotic systems with unknown bounded disturbances. A robust adaptive neural control was proposed for a fractional-order rotational mechanical system in the presence of system uncertainties and external disturbances by Shao et al. Shao et al. investigated a FODO-based sliding-mode control scheme for a class of fractional-order nonlinear systems with external disturbances. The problem of stabilization control was studied for a class of continuous-time fractional systems subject to external constant disturbances based on a disturbance observer by Shao et al. Shao et al. proposed a FODO-based adaptive neural tracking control scheme for uncertain fractional-order chaotic systems subject to unknown disturbance and input saturation. According to these discussions, the anti-disturbance ability of control systems can be improved by employing the disturbance observer in the robust control for the uncertain nonlinear system with external disturbance. In this chapter, we mainly introduce a fractional-order PI λ D μ controller and a frequency-domain FODO. In this section, a novel chaotic system will be proposed by only considering the straight-line position x r and the pitch angle θ p of the two-wheeled self-balancing robot of Googol Technology. A mathematical model related to the two-wheeled self-balancing robot of Googol Technology was established by Son and Anh. According to the Caputo definition of the fractional derivative (2.17), a class of fractional-order nonlinear systems subjected to external disturbances and control inputs is considered. On the basis of the Caputo definition of the fractional derivative (2.17), we consider the following fractional-order rotational mechanical system with a centrifugal governor in the following form. According to the Caputo definition of the fractional derivative (2.17), the following uncertain FOCS in the presence of input saturation and unknown external disturbance is described as follows. R n denotes the n -dimensional real space. N ┬ denotes the transpose of a matrix N . A matrix N 0 ∈ R n × n is called a Metzler matrix if its off-diagonal elements are non-negative. A matrix N 1 ∈ R n × n can be seen as a non-negative matrix if all its elements are non-negative, e.g., N 1 ≥ 0. A vector Φ can be seen as a non-negative vector if all its elements are non-negative, e.g., Φ ≥ 0. It is said to be positive if all its components are positive (Φ > 0). Furthermore, it is said to be negative if all its components are negative (Φ < 0). On the basis of the Caputo definition of the fractional derivative (2.17), the FOCS will be introduced. According to the Caputo definition of the fractional derivative (2.17), the fractional-order nonlinear system will be described. According to the Caputo fractional derivative (2.17), the following nonlinear FOCS is considered. Based on the Caputo definition of the fractional derivative (2.17), we consider a class of fractional-order chaotic systems with unknown constant disturbance in the form of. This back matter contains the appendices, references, and index

Volume 18: Smart Systems Engineering—Computational Intelligence in Architecting Engineering Systems This proceedings is from the eighteenth meeting since the founding of the ANNIE Conferences in 1991. The conference was held in St. Louis, MO, USA, and attracted 140 papers internationally. Each paper was peer reviewed and revised before being included in this book. This front matter include the table of contents and preface In large distributed systems, it is often difficult for components to learn behavior that is beneficial to the full system, based on their limited worldview. The key culprit in this process is the mismatch between the traditionally slow learning process of the agents and the relatively rapid changes to the environment. In this paper, we present a theoretical result that significantly improves the learning speed of the agents by allowing the agent to receive rewards based on Actions Not Taken (ANT). This increase in speed is based on the agent receiving a counterfactual reward that estimates the reward an agent would have received had it taken a particular action. We then show results that demonstrate the applicability of this method in the congestion problem known as the El Farol Bar Problem. Furthermore, because these counterfactual rewards are partially based on the actions of the other agents in the system, the improvements become more pronounced as the system size increases. This paper addresses Micro Aerial Vehicle (MAV) control by leveraging neuro-evolutionary techniques that accommodate a higher number of control surfaces. Applying classical control methods to MAVs is a difficult process due to the complexity of the control laws with fast and highly non-linear dynamics. These methods are mostly based on models that are difficult to obtain for dynamic and stochastic environments. Instead, we focus on segmenting the different control surfaces to allow more flexibility to the neuro-evolutionary based controller. Precise control is then achieved by neuro-evolutionary techniques that have been successfully applied in many domains with similar dynamics. The results show that MAV performances are improved both in terms of reduced deflection angles and reduced drag (up to 4%) over a simplified model in two sets of experiments with different objective functions. This paper explores the pairing between sensors and controllers to allow autonomous navigation in unknown environments. Addressing this problem by directly using all available sensor information in a controller (e.g. a neural network) is tempting, but problematic. If the sensor provides too little useful information, the controller selection and training will be both difficult and unlikely to lead to good system behavior. If on the other hand, the sensor provides too much information, the controller will be overwhelmed and lead to unnecessarily complex and brittle control laws. Ideally, the sensors should provide as much or as little information as is likely to be needed and used by the controller. In this work, we focus on this particular problem and analyze how different sensor suites can be designed and paired with controllers to provide optimum information for successful navigation. We explore ultrasonic and thermal sensors, and pair them with feed forward neural networks. The results show that neural networks trained via supervised methods provide good sensor interpretation (e.g., less than 11% testing error), but that for the simple controller used, the pairing of two sensor types increases overall error rather than reduce it, highlighting the difficulty in sensor∕controller matching. In many robotic exploration missions, robots have to learn specific policies that allow them to: (i) select high level goals (e.g., identify specific points of interest (POIs)), (ii) navigate (reach those POIs), (iii) and adapt to their environment (e.g., modify their behavior based on changing environmental conditions). Furthermore, those policies must be robust, scalable, and account for the physical limitations of the robots (e.g., limited battery power and computational power). In this paper we evaluate reactive and learning navigation algorithms for exploration robots that must avoid obstacles or reach specific points of interest (e.g., heat sources). Our results show that neuro-evolutionary algorithms with well designed evaluation functions can produce up to 50% better behavior than reactive algorithms in complex domains where the robot goals are to select paths that lead to seek specific POIs, while avoiding obstacles. Graph Based Evolutionary Algorithms (GBEAs) are a novel modification to the local mating rules of an evolutionary algorithm that allow for the control of diversity loss by restricting mating choices. Graph structures are used to impose an artificial geography on the solution set to mimic geographical boundaries and other mating restrictions found in nature. Previous work has shown that by using graphs of a lower degree, diversity in the population decreases at a slower rate, allowing for the formation of more diverse set of good building blocks. This research also indicated that graph degree is not the only factor affecting diversity preservation; different graphs with the same degree hinted at other factors that could influence information flow. In this paper, we investigate the effect of broadening the number of candidate graphs by introducing two new sets of graphs, one constructed from regular sub-graphs and one set constructed using geographic data from six locations in the United States. It was found that the use of sub-graphs connected to a central hub can promote the development of necessary building blocks and increasing performance for certain problems. In addition, it was shown that graphs with a moderate to high level of diversity preservation are analogous to some geographic features in nature, providing a method to validate graphs used in epidemiological studies. This paper introduces an innovative approach to architecture design and optimization, which is inspired by the evolutionary processes of natural species. The objective is to reduce the architecting search space with structured architectural models that can handle ambiguity at different stages of the conceptual design. A key aspect of architecture development is to select a proper set of design primitives so that the problem can be formulated effectively and solved using tools available. Inspired by the famous heuristic of systems engineering that the greatest leverage in architecting is at the interfaces, an interface-based architecture design approach was developed that facilitates both the graph representations of system architectures and the applications of evolutionary algorithms. The basic idea is to choose an appropriate interface for each functional component from possible design space so that the overall system can be integrated in a way that optimizes the performance measures of interest. The interface design then drives the overall architecture design. This paper illustrates this method using the example of on-board intelligent transportation systems. This paper describes the application of the Barabasi-Albert model of a small-world network to genetic algorithms. These networks have two types of connections. Most connections are “local”, connecting only to immediate neighbors. The other type is “long-range”, connecting randomly to distant individuals. For the genetic algorithm, we place a population of chromosomes in such a network. Crossover (mating) only occurs between connected individuals. The locality encourages diversity similar to that seen by other authors using spatially restricted mating. On the other hand, the long-range connections allow superior characteristics to spread relatively rapidly through the entire population. We control the rapidity of this spread by the frequency of long-range connections. We have implemented this technique using the Barabasi-Albert model for small-world networks. The most important characteristic of this model is that it generates scale-free graphs. We have evaluated this technique on some engineering design problems which are typical of those encountered at General Dynamics — NN Shipbuilding, the largest shipbuilder in the US. We compare the Barabasi-Albert model with a different small-world model (Watts-Strogatz) that does not have the scale-free characteristic. We also compare it with the conventional genetic algorithm and we show its superiority under many conditions. The mammalian immune systems show vast adaptivity. The adaptivity is characterized by responsiveness and diversity. The responsiveness is arisen from the response network of the immune systems and the diversity is produced from the rearrangement of the genes related to the immune systems. Recently, many artificial immune algorithms have been devised inspiring with the natural immune systems. This paper proposes a new scheme of artificial immune algorithm, named Rearrangement Immune Algorithm (RIA), in which the rearrangement of the immune system is explicitly utilized combining with the evolution of the gene library using a Genetic Algorithm (GA). We show the performance of the RIA via applying an HP protein folding problem. Recent advances in a multi-agent system are standing on the basis how to treat several agents from a viewpoint of the agent approach. This paper proposes a new concept “Smart Control for Collective Agents” and a new methodology “Adaptive Strategic Mechanism for Collective Agents” from a viewpoint of adaptation in natural. Then, they are applied to a various kind of collective agents' problems. The smart control means that the collective agents explore their proper strategy through the adaptation under dynamic and ill-known environments, and that each agent makes an autonomous decision under the explored strategy as if he∕she has intelligence. Based on the smart control, some behavior patterns for the collective agents emerge and they are controlled to be adaptable for the environments. The collective agents can often be considered as a mobile multi-robot in a robotics field. However, the proposed concept and methodology are applicable to other engineering field such as an information network, a social behavior, and so on. In order to verify the proposed concept and methodology concretely, several examples are shown. This paper describes a distributed agent-based paradigm for hybrid (soft and hard) computation in information (data) fusion. The computations are the outcome of deterministic, nondeterministic or stochastic interaction among the agents, in an environment where information arises from database and multiple sensors. These interactions are like chemical reactions and the evolution of the multiset of agents can mimic the data fusion in a complex sensory system to achieve a required outcome. Since the reaction rules are inherently parallel, any number of actions can be performed cooperatively or competitively among the subsets of the agents. We also describe how scale-free and small world networks arise in the connectivity structure of agents during the information fusion and can result in swarming. We describe a multi agent-based paradigm which integrates the salient features of several agent models. The integrated multi agent paradigm can be realised as a distributed transaction-based model for negotiation and planning. It supports complex interaction mechanisms which are required in distributed virtual environment and distributed simulation technology for complex systems. These collaborative (cooperative) multi-agents will support distributed simulation applications including financial, military and government systems. The multi-agent architecture will be developed using Java based tools and distributed databases. An agent-based programming paradigm is described for the evolution of bio-inspired complex systems, e.g., genetic, and active walker (swarm and ant intelligence) models. Since the reaction rules are inherently parallel, any number of actions can be performed cooperatively or competitively among the subsets of the agents, so that the system reaches an equilibrium (or an emergent) state. We consider how this paradigm can be implemented through agent architectures - Adaptive agent and the Java-based Cougaar. In high dimensional feedback-controlled systems, the rate of information generation is too low for a given integration time-step. The low level of information generation is because of the slow system evolution with the optimum integration step size. This causes longer processing time and larger buffer capacity requirement for complexity analysis. Thus, for these systems, immediate solutions are not good candidate for sampling and mapping to binary sequences. To overcome this problem and eliminate the need for large buffer size, in this paper we introduce a method that instead of using real-time dynamic solutions, advance solutions are selected. This means, if trajectories traced and sampled with advance time, then system dynamics provides adequate information from phase space attractors. In this paper we address the following question. How much can information complexity be increased via a chaotic encryption and convolutional coding? To address this, the algorithmic complexity of data sequences generated from a cascade of one-stage chaotic cryptosystem and a one-stage convolutionally encoding mechanism is examined. An algorithm that evaluates the efficiency and performance of this mechanism for a secure digital communication is designed. Special attention was paid to the algorithmic complexity of computing information for an entire class of rate-1∕2 encoders. Numerical evidence indicates algorithmic complexity associated with the chaotic-encrypted convolutionally-encoded data increases along with the increase of the error correcting capacity of the decoder. The pace of development and automation urge the need of robots controlling much of the work which used to be done mainly by humans. The modern technology has emphasized on the need to move a robot in an environment which is dynamically changing. An example of such an application is the use of robots in industry to carry tools and other materials from one place to other. Since many robots would be working together, we need to ensure a collision free navigation plan for each of the robots. In this paper we find out the nearly most optimal path of the robot using A * algorithm at each instant of time. The algorithm ensures that under any circumstance, there would not be any collision of the robot with any of the dynamically changing obstacles. The mobile robot navigation control has huge industrial application. It is used by the industry to send robots for surveys, data acquisition, doing specific work etc. The collision free movement of robot in a moving obstacle environment can be used to move robot in a world of robots. Hence it takes us closer to a fully robot control production∕service system, where robots do all the work without external help. The algorithm takes its input as a grid. This grid may be formed by scanning the surroundings. The positions of obstacles are known in this grid. We assume that the robot can make a limited number of moves, restricted to moving forward a unit step or turning (clockwise or anticlockwise) a unit direction. The A * algorithm calculates the most efficient next move. When this algorithm was simulated, we saw the robot traveling without collision and reaching the destination. The path traced by the robot was very efficient and short even when robot was placed in a highly chaotic environment. Hence this algorithm can be used for efficient navigation control for robots. The field of multi-robot systems is sometimes called swarm robotics when the systems consist of many simple autonomous robots. However, each robot is usually assumed to have no learning mechanism for adapting to an embedded changing environment. Therefore, collective behavior is expected to emerge in the system only through interactions among the robots. This implies that they cannot be coordinated as a group. In this study, an evolutionary robotics approach is applied empirically to a multi-robot system to realize autonomous task allocation behavior as a kind of intelligent swarm robotics. Although artificial evolution has proven to be a promising approach to coordinate the controller of an autonomous robot, its effectiveness in developing beneficial collective behavior in a multi-robot system has not been verified. Several computer simulations are conducted in order to examine how artificial evolution contributes to conduct autonomous task allocation in a multi-robot system. In this paper, active learning with kernel machines, including Support Vector Machines and the p-Center Machine, is applied to the problem of tornado detection. This method is used to discriminate which storm-scale circulations yield tornadoes based on the radar derived Mesocyclone Detection Algorithm (MDA) and near-storm environment (NSE) attributes. The main objective of active learning is to choose instances or data points that are important to be labeled and included in the training set since labeling the instances in tornado data is considered costly and time consuming. We compare active learning with passive learning where the next instances to be included to the training set are randomly selected. The preliminary results show that active learning can achieve good performance and significantly reduce the training set size. Estimation of contaminant transport parameters in porous media is often constrained by the inability to measure pore-scale phenomena. Use of x-ray computed tomography (CT) may provide a tool to measure fluid transport at the pore-scale to facilitate estimation of transport parameters. The objective of this study was to use x-ray CT methods to measure transport of an iodide tracer in porous media and estimate porosity, solute pore-water velocity and solute dispersivity. CT-measured breakthrough curve experiments were conducted in columns of glass beads ranging from 1.4 to 8.0 mm in diameter with four sizes. Iodide breakthrough experiments were conducted using a medical CT scanner with a voxel size 0.5 by 0.5 mm by 2.0 mm thick. Based on the breakthrough curve for each pixel, the porosity, solute pore-water velocity and solute dispersivity distributions were determined. Frequency distributions of porosity within the core samples, excluding values equal to zero and one, were found to be uniform. The frequencies of porosity equal to zero and one increased as the log of glass bead diameter increased. Dispersivity frequency distributions for three glass bead sizes needed transformations using a 0.25 power to normalize the distributions. The study illustrates that this method of analysis is potentially useful for evaluating solute transport on a macropore-scale for porous materials. The heterogeneous nature of porous media presents serious challenges in accurately predicting solute transport through earth materials. Spatial analysis techniques such as geostatistics provide a quantitative tool to evaluate soil pore heterogeneity at a variety of scales. Since the CT method can provide spatially detailed data for solute transport parameters such as pore-water velocity and dispersivity, these detailed data may be evaluated using geostatistical analysis tools. The objective of this study was to determine the macropore-scale spatial semivariograms of CT-measured porosity, pore-water velocity, and dispersivity in cores. CT-measured breakthrough curve experiments were conducted in columns of glass beads (1.4 to 8.0 mm diam.). The exponential semivariogram model provided the best fit for the semivariograms of CT-measured porosity, pore-water velocity, and dispersivity for the cores. These three solute transport parameters were found to be autocorrelated with varying ranges of autocorrelation. Range of spatial autocorrelation for porosity, pore-water velocity and dispersivity was found to be a linear function of bead diameter (r values > 0.89). Ranges were found to be approximately 55% of the bead diameter size. This study illustrates the ability to utilize spatial semivariograms for quantifying the autocorrelation of CT-measured transport properties, information which is very useful in transport models. Significant difficulty in providing preferential treatments to transit vehicles along urban arterials is that buses often travel outside general traffic progression patterns (due to boarding and alighting passengers) thus creating conflicts between green time needs of general traffic and those of transit traffic. Simultaneous priority requests also complicate the green time allocation decisions, and so does the variability in boarding and alighting times. Genetic Algorithms (GA) and Artificial Neural Networks (ANN) are combined in this research to implement efficient transit priority within real-time coordinated network. An ANN model first predicts the amount of time lost to dwelling activity at bus stops. A GA then optimizes signal timings. Microscopic traffic simulation is used to evaluate the proposed procedure. The results show the ability of the proposed model to improve traffic network performance within a coordinated system compared to the current practices where transit signal priority (TSP) is implemented within fixed-time signal systems using the mean value of boarding∕alighting times. Studies of fluid flow in annular pipes have been popular in the petroleum engineering research. Most of the work has concentrated on CFD (Computational Fluid Dynamics) simulations, analytical and empirical models. In this study a neural network and evolutionary programming approach is developed to model the behavior of fluid flow in eccentric pipes. The model uses the fluid rheological parameters, density, mass flow rate, eccentricity, inner and outer pipe diameters, and predicts the pressure drop (ΔP) in the pipe in the flow direction. The evolutionary programming model uses basic mathematical operators, logarithm and sine functions. The results are compared with some experimental data obtained in literature and some Matlab CFD simulations. Preliminary studies indicate the neural network model performed better than the other models, evolutionary programming model can predict comparable pressure drop results, but not as effectively as the other models. Accurate predictions of contaminant transport in porous media are vital to assist in minimizing impairment of water resources. Fractal analysis of transport parameters may assist in quantifying soil heterogeneity at a variety of scales which will help in identifying possible water quality impairments and remedial procedures. Computed tomography (CT) methods can determine transport parameters, such as pore-water velocity and dispersivity, and provide detailed data sets at a finer resolution for fractal analysis. The objective of this study was to evaluate whether CT-measured solute transport parameters are fractal; and if so, determine the fractal dimension and lacunarity of pore-water velocity and dispersivity parameters. CT-measured breakthrough curve experiments were conducted in columns of glass beads (1.4 to 8.0 mm diam.). CT-measured porosity, pore-water velocity, and dispersivity were found to be fractal. Fractal dimensions of these parameters decreased with the logarithm of glass bead diameter. Results of the study indicated that both fractal dimension and lacunarity are required to discriminate spatial distributions of the solute transport parameters among different porous media. If fractal dimensions are the same for different fractal sets, lacunarity analysis may reveal different spatial patterns or fractal structures for such fractal sets. Conventional methods of subsurface assessment for remediation or monitoring purposes often involve field sampling and laboratory analyses of soil and water samples for specific contaminants species. Even though these procedures are well established and produce reliable results, they have a number of disadvantages. Among others, they are not measured in real time, and they are sometimes destructive because excavations are needed to obtain soil samples. Furthermore, the sampling and testing processes can be quite laborious and expensive. Various investigations have been carried out to develop alternative, nondestructive methods for such routine measurements. The application of artificial neural networks (ANN) in environmental site characterization has proved to be an effective modeling method for the prediction of migration paths of environmental contaminants. However, the uses of ANN modeling for the migration of explosives-related contaminants (in particular perchlorate) in water and soil, have not been widely reported in the literature. For this reason, this study will explore the potential use of neural network modeling for predicting the amount and distribution of perchlorate at military installations. Accurate analysis of scan images of natural geologic and earth systems is essential when evaluating pore size distributions in porous media for better prediction of contaminant and gas transport. The recent development of an adaptive structural element for use as a grayscale morphological operator in image analysis may prove useful for evaluating soil and geologic materials. The objective of this study was to illustrate the application of an adaptive grayscale morphological operator in evaluating four synthetic images representing differential ranges in pore radii and a set of computed tomography scan images from three management treatments affecting pore size distributions in soil. The morphological operator performs the erosion and dilation of image data and the surface area is estimated as a function of changing resolution of the operator. The rate of change of the surface area was used to estimate the multi-fractal dimension (signature) of the synthetic images as a function of changing resolution. Results show the benefits of this technique as a new analytical image analysis tool for evaluating size and distribution of particles. The upper signature differentiated pore size distributions for the three management treatments as a function of soil depth and was highly correlated with independently estimated porosity values. This tool can be used to evaluate size and spatial distributions of particles or pores within an image. Additional applications of this method include quantifying and analyzing image features from scans of soil and geologic materials. In this paper, a new Vehicle Routing Problem is introduced where driving time and working time restrictions are imposed on the problem. First, a mathematical model and a genetic algorithm-based solution technique are proposed and later they are compared. Two new operators (route-sensitive crossover and route-sensitive mutation) are also proposed to solve this particular problem. The results show that GA can find the optimal solution with a high frequency for small problems. As the problem size grows, it becomes difficult to solve the math model since the number of decision variables and the constraints grow fast. In those situations, GA continues to be a good choice since it can provide feasible solutions (and hopefully at least some optimal) relatively fast. The ocean surface wind vector field is a key element for accurate short term weather forecasting. Those forecasts are needed to issue timely weather warnings to avoid major catastrophes. In recent years, considerable effort has been expended to measure and forecast ocean surface wind speed using data provided by satellites. Analyses based on these massive data sets should be based on a subset of the full retrieved data to make the process efficient for use with on-line algorithms. This work builds upon successful application of support vector regression (SVR) and Voronoi tessellation to extract a data subset composed of support vectors. A pipeline method is developed to manage an on-line stream of the above mentioned data. Experiments show that the subsets reconstruct the wind vector field with high accuracy. Furthermore, the time required to generate the subset, using the pipeline, is ≈9% of that for thinning the whole data set. In this paper we present an analysis of various climate data sets by utilizing a discrete wavelet transform spectral decomposition. The spectral decomposition allows for feature extraction from the data which identifies teleconnection signals between the systems at various spectral frequencies. Feature extraction through spectral decomposition provides a means for understanding the likely time course response of individual systems to climate changes. Additionally, the spectral decomposition can yield insight into the time course response of climate changes propagating through various systems studied. By studying the spectral relationships, teleconnections between systems can be identified. The discrete wavelet transform allows for more information to be extracted from the data than a Fourier transform, by capturing both a map of the frequency content of the data, through examining it at different scales, as well as the temporal content of the data, by yielding the times at which these frequencies occur. Our overall research is focused on quantifying the uncertainty in climate model predictions of the effects of global warming on various systems. Understanding the frequency content and time course response of systems provides valuable information in identifying the evolution of signals through the data. The objective of this work is to implement a new hybrid feature selection system comprised of a genetic algorithm (GA) and a support vector machine program termed SVM perf . We have used this system to perform feature reduction of a colorectal cancer microarray dataset generated by the Moffitt Cancer Center. Using variance pruning as a coarse feature selection process with the GA-SVM perf wrapper, the method provided an A z (performance measure) value of .97 with only 7 features after 30 generations. Using a combination of variance pruning, t-tests and the GA-SVM perf wrapper, the method provided an A z value of 1 with only 6 features. These results show tremendous improvement over other linear techniques that were used to do feature reduction. This implies that the technique used in this paper is best suited for feature reduction since it can find patterns that separate different classification cases with high success. We have designed an automated process comprised of three basic components: coarse feature reduction and classification, and ∕ or fine feature measurement and selection, and then classification. Specifically, these three steps are: (1) coarse feature reduction using a combination of variance pruning and the Student's t test, where the resulting features are classified by a combination of logistics regression, the Wald test in combination with standard statistical testing using p values as a guide, (2) fine feature selection using the reduced feature set as input to a wrapper method consisting of a modified GA process, configured for this specific application, where the fitness function results are developed by support vector machines, and (3) the classification (and ∕ or diagnostic) process, which consists of training and validating specified support vector machines and a kernelized partial least squares (K-PLS) process as well as use of the evolutionary programming support vector machines (EP-SVM). This paper focuses only on the first component of course feature reduction process only using colorectal microarray gene expression data. Data mining is the method of analyzing data from various perspectives and summarizing it into useful information. Clustering is one of the prominent and efficient ways to use it as the data mining technique. Most of the clustering algorithms will usually employ distance metric based similarity measure to find the clusters such that the data points in the same cluster are similar; usually these algorithms use only discrete- valued databases. Instead this paper presents a conceptual clustering algorithm which can be employed on the categorical attributes as well as Boolean attributes. The use of the distance metric based similarity measure is not an appropriate method to be employed on the categorical attributes. So we proposed a new approach called HAC (Hierarchy of Concepts and Attributes), which can be used to measure the similarity between a set of data points. For a database table with the categorical attributes, our findings indicate that this HAC method will not only generates good quality clusters but also exhibits good scalability properties and it also organizes the data so as to maximize the inference capability[3]. Syndromic Surveillance is used for the early detection of disease outbreaks. Back Propagation has been demonstrated to be an accurate, robust, and scalable detection technique for disease outbreaks in over the counter pharmaceutical sales. The purpose of this study is to determine whether Support Vector Machines are comparable to Back Propagation in performing Syndromic Surveillance. Back Propagation and Support Vector Machines are used to detect outbreaks based on emergency department and Telehealth data. A data simulation methodology has been used to produce sufficient quantities of realistic data to perform this study. The results demonstrated that Support Vector Machines with a polynomial kernel are more successful to Back Propagation for detecting disease outbreaks based on data from emergency department in terms of false detections; however, they are comparable in terms of the detection time. In addition, Support Vector Machines with a polynomial kernel are comparable to Back Propagation for detecting outbreaks based on data from Telehealth in terms of false detections and the detection time. Problems involving complex adaptive systems (CASs) require complex adaptive solutions. In this work a new statistical mixture of experts architecture is presented as a solution to the general CAS problem. The new architecture is based on the general regression neural network (GRNN) foundation. This new mixture of experts solution is validated using a diagnostic mammography dataset. The outputs from various complex adaptive decision methodologies are used as inputs for GRNN based mixture of experts architecture. The work shows that this new solution outperforms the individual component models in making diagnostic benign-malignant predictions, which validates the solution. Researchers in the medical field are in constant search for innovative techniques to understand, explore, and test the function of biological mechanisms. Understanding the function of the mechanism could yield to developing effective drugs to treat diseases in the mechanism. An example of such mechanism is the renal system. Since in-vivo investigation of the mechanism is usually impractical or prohibited, we propose implementing a technique based on developing a mathematical model for the function of the mechanism. The model is simulated on the computer using Hardware Description Language (HDL) CAD packages. The simulation is synthesized on a compact electronic chip such as Field Programmable Gate Arrays (FPGAs). The chip, when correctly synthesized, will mimic the mechanism and will allow researchers to test and investigate the function of the mechanism. The chip, since it is compact, can be attached to the skin of the subject and monitor selected hormones through sensors. We have presented at ANNIE 2007 [1] the implementation of such technique on a very simplified renal system. In this paper we expand the work that has been done in 2007 by incorporating more hormones that play a role in the renal systems, specifically the anti diuretic hormone (ADH). The primary function of the heart is to supply blood and nutrients to the body. The regular beating of the heart moves the blood throughout the body. Each heartbeat is controlled by electrical impulses traveling through the heart. In the normal heart these electrical impulses occur in regular intervals. When something goes wrong with the heart's electrical system, the heart does not beat regularly. The irregular beating results in a rhythm disorder, or arrhythmia. ECG is a record of electrical impulses which precede the heart contractions. A single sinus (normal) cycle of the ECG, corresponding to one heart beat, is traditionally labeled with the letters P,Q,R,S and T which correspond to P-wave, PQ interval, QRS complex, QT interval, ST interval and T-wave. Heart arrhythmias result from any disturbance in the rate, regularity, and site of origin or conduction of the cardiac electric impulse. Premature ventricular contraction (PVC), left bundle brunch block (LBBB), and right bundle branch block (RBBB) are the three cardiac arrhythmias which can lead to or indicate the risk of heart failure. Our research is focused on constructing model parameters in order to generate different morphologies for the PQRST-complex. By prescribing specific characteristics of the heart rate dynamics such as the mean and standard deviation of the heart rate, spectral properties etc, we built a database which will be used for calculating the effectiveness of different techniques for noise and artifacts removal as well as for designing a pattern classifier able to recognize the above cardiac arrhythmias. Facial expressions and mood identification are important from the stand point of terror deterrence. Facial image based mood detection techniques may provide a fast and practical approach for noninvasive mood detection. The purpose of the present study was to develop a technique for facial image based expression classification using committee neural networks. Several parameters were extracted and used to train several neural networks. The best performing five networks were recruited into a committee. The neural network committee was evaluated using data obtained from subjects not used in training. The committee neural networks correctly identified the mood in 96.4% of the cases. The unique parameters identified in the present study along with committee neural networks present a powerful tool for facial image based mood detection. Exon prediction, including the use of complex multilayer neural networks, is an emerging field that has impacts in medicine, drug development, and law enforcement (Asyali, et al. 2006). However, few research projects have considered simple neural networks for human exon prediction. It is anticipated that the simplicity of two-layer neural networks can greatly reduce the complexity of existing exon prediction algorithms. A data set was compiled based on quantitative data collected on TATA boxes, TG-dinucleotides, CpG island qualities, poly-A tails, and codon bias. Results show that the proposed method hasprediction accuracy greater than 63% and a false positive rate less than 25% for all but one network. These results are an improvement from previous neural network gene prediction studies (Uberbacher and Mural, 1991). A simple Gaussian classifier, the nearest mean classifier (NMC), and principal components analysis (PCA) were used to explore the structure of the gene data set. The PCA results indicate that CpG islands have little effect on the existence of exons. This provides evidence supporting the lack of correlation between CpG islands and coding regions, a previously ambiguous relationship. In this paper, we show that a biped robot can walk dynamically using a simple control technique inspired from human locomotion. We introduce four critical angles that affect robot speed and step length. Our control approach consists in tuning the PID parameters of each joint in each walking phase for introducing active compliance and then to increase stability of the walk. This method could be easily implemented in real time because it needs acceptable calculation time. We validated the control approach to a dynamic simulation of our 14DOF biped called ROBIAN. A comparison with human walking is presented and discussed. We prove that we can maintain robot stability and walk cycle's repetition without referencing a predefined trajectory or detecting the center of pressure. Results show that the walk of the biped is very similar to human one. A power consumption analysis confirms that our approach could be implemented on the real robot ROBIAN. This paper proposes an efficient method for the classification of placental development with normal tissues. The proposed method consists of selection of tissues, feature extraction using discrete wavelet transform and classification of the tissue by the multi layer perceptron MLP and radial basis function RBF. The method is tested for placental images acquired by ultrasound techniques; resulting in 95% success rate. The proposed method showed a good classification rate. The method will be useful for detection of the anomalies those concerning premature birth and intra-uterine growth retardation. We extend a previously developed computational model for the simulation of multicellular tissue growth using a discrete approach based on cellular automata. Our objective is to investigate the tissue growth rates and population dynamics of different populations of migrating and proliferating mammalian cells. The model extension is applied in the context of a wound-healing environment where it is assumed that nutrient and growth factor concentrations remain constant in space and time. We report simulation results describing cell collision and aggregation for two cell populations each having its own division and motion characteristics based on experimental data. Both heterotypic and homotypic cell-cell interactions play important roles in wound healing. The temporal evolution of the frequency of cell collision and aggregation and their relations to other variables that quantify the dynamics of cell populations can be predicted by this model for different cell heterogeneity ratios and cell population speeds. Expressed Sequence Tags (ESTs) are short nucleotide subsequences of expressed genes, which can be rapidly generated in large quantities. With improving sequencing technology, the number of ESTs available in open-access databases is exponentially increasing. A method of gene family identification that makes use of this data can be a valuable tool in genome analysis. We have previously demonstrated such a technique which uses negative selection patterns (NSP) between family members to screen out potential paralogs from contigs assembled from ESTs (Frank et al., 2006; Frank et al., 2008). This strategy is now fully automated and tested on 10 gene families in Arabidopsis thaliana to see how the resulting putative paralogs compare with the actual gene sequences in this fully sequenced genome. The automation correctly identifies specific member genes in these families using only EST data. These results suggest that this automated strategy can identify many gene families in species where they are as yet undiscovered. Photo-plethysmography (PPG) is frequently used in research on microcirculation of blood. It is a non-invasive procedure and takes minimal time to be carried out. Usually PPG time series are analyzed by conventional linear methods, mainly Fourier analysis. These methods may not be optimal for the investigation of nonlinear effects of the heart circulation system like vasomotion, autoregulation, thermoregulation, breathing, heartbeat and vessels. The wavelet analysis of the PPG time series is a specific, sensitive nonlinear method for the in vivo identification of heart circulation patterns and human health status. This nonlinear analysis of PPG signals provides additional information which cannot be detected using conventional approaches. The wavelet analysis has been used to study healthy subjects and to characterize the health status of patients with a functional cutaneous microangiopathy which was associated with diabetic neuropathy. The non-invasive in vivo method is based on the radiation of monochromatic light through an area of skin on the finger. A Photometrical Measurement Device (PMD) has been developed. The PMD is suitable for non-invasive continuous on-line monitoring of one or more biologic constituent values and blood circulation patterns. In this paper, we formulate an optimal cross section design (OCD) problem of lunette eye of full trailer for a constrained allowable normal stress with section modulus as a nonlinear integer programming (NIP) problem and solve it directly by keeping the constraints based on an improved genetic algorithm (GA). We discuss the efficency between the proposed method and the traditional method. In this paper, we describe an implementation of a hybrid GA∕IA algorithm (HGA) which combines a Genetic Algorithm (GA) with the Immune Algorithm (IA) for solving multiobjective nonlinear integer programming problems. This proposed method can find better quality Pareto solutions. Moreover, we apply the HGA for solving the optimal design problem of the system reliability as a numerical example of the multiobjective nonlinear integer programming problem. We compare the proposed method with the simple genetic algorithm to verify its effectiveness. In this paper, we propose a hybrid Evolutionary Algorithm (EA) for the communication network design. The purpose is to improve Quality of Service (QoS) and provide network reliability. We formulate the problem with minimizing a communication cost as a kind of performance measures for communication network's QoS, at the same time, we also considering the network reliability. We investigate the different encoding, crossover and mutation operators on the performance of EAs to communication network problems. Based on the performance analysis of these encoding methods in EAs, we improve a new hybrid EA approach, in which initialization depends on an underlying random spanning-tree algorithm. Numerical experiments with various scales of communication network problems show the effectiveness and the efficiency of our approach by comparing with the recent researches. The Assembly Line Balancing (ALB) problem is a well-known manufacturing optimization problem, which determines the assignment of various tasks to an ordered sequence of stations. As Genetic Algorithms (GAs) have established themselves as a useful optimization technique in the manufacturing field, the application of GAs to ALB problem has expanded a lot. This paper describes a Generalized Pareto-based Scale-independent Fitness Function Genetic Algorithm (gp-siffGA) for solving ALB problem with Worker Allocation (ALB-wa) to minimize the cycle time, the variation of workload and the total cost under the constraint of precedence relationships at the same time. The results indicated that the proposed approach improved the quality of solutions more than the other existing GA approaches. In this research, an algorithm is applied for a multiobjective network design problem. It is known that Dijkstra method can solve single-objective network design problem in polynomial time. However, this method is hard to solve a multiobjective problem. We suppose that obtaining Pareto-optimal solutions is important, for example, in the case of application to a navigation system. Driver can select the most desirable route from the Pareto-optimal solutions. Some criteria of route search are assumed, for example, time, distance, and total expenses. We define three objective network design problem. To solve this problem which has multiple criteria, we apply a multiobjective genetic algorithm, aiming at simplification of parameter tuning and efficiency improvement of maintaining diversity. The priority-based encoding method will be used to represent chromosome. We will use this algorithm to calculate a Pareto-optimal or near Pareto-optimal solutions. Numerical experiments with simple network design problem will show the feasibility of our approach. Nowadays, many enterprises are using Voice over Internet Protocol (VoIP). The Quality of Service (QoS) of VoIP packet is very important for the real-time service and the quality of voice. For improving the QoS of VoIP, the scheduling problem for real-time packets on router is one of most challenging problem which is also proved to be NP-hard problem. In this paper, we consider a Real-time Transport Protocol (RTP) packet's sequence processing for voice quality. To solve this problem, we propose scheduling algorithm for the router's packet scheduling by a hybrid Genetic Algorithm (hGA). The objective of the packet scheduling model is to minimize the delay. We compare Modified Deficit Round Robin (MDRR)'s strict priority mode, alternate priority mode, Proportion-based GA and hGA. Numerical experiments with several algorithms show the effectiveness and efficiency of our proposed approach. In a re-entrant flow shop scheduling problem some methods are proposed to get a better TAT (turn around time) with genetic local search methods. One is an operation which searches for a solution that shifts the start timing in limited areas of each lot. Another is an operation which searches for a solution that shifts left and chooses the machine which starts earliest. The proposed methods are more valid than the other local search methods, such as swap, move, swap-2 neighborhood. In the past decade, genetic algorithms have been used in a variety of fields to find an optimal solution of the problem with several objectives. In this paper, we will deal with a human resource allocation problem with three conflicting objectives, i.e., minimizing the total costs of the staff, balancing the usage of the full-time staff, and maximizing the motivation of the staff. In human resource management, the allocation of human resources is usually done by human resource managers considering the efficiency of the staff costs and the services. However, the staffs' individual needs and their working environment should be satisfied as much as possible at the same time. In order to solve this multiobjective problem, hybrid multistage decision-based genetic algorithm will be introduced with fuzzy logic controller, which is used for parameter fine-tuning of genetic algorithm. As a result, this paper will show an optimum one-day staff schedule satisfying all three objectives. This paper consider a reverse logistics network problem (rLNP) with two objectives i.e. minimizing total cost of transportation as well as purchase and, simultaneously, minimizing cost of inventory that is must be reduced which is concerned with relationship between the demands of products and the quantity of provided products from processing center. For applying an evolutionary approach for this rLNP, priority-based encoding method and adaptive weight approach (AWA) are proposed. The effectiveness of proposed approach is evaluated through numerical experiments

Proceedings of the 2011 International Conference on Mechanical Engineering and Technology (ICMET 2011) held in London, UK, November 24–25, 2011. ICMET 2011 is a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results and development activities in Mechanical Engineering and Technology, and related interdisciplinary subjects. Those who attended the conference were engineers, scientists, managers of various companies and professors of universities from about 24 different countries and regions. This proceedings covers the subject areas of Mechanical Engineering and Technology, and also covers interdisciplinary subject areas of Computer Science and Technology. This front matter contains the preface, organizing committee and table of contents. Click on the PDF icon to view the complete front matter. Numerical calculation method is applied in thermal analysis area with the development of the computer technology. Solid-Fluid whole conjugated heat transfer method can take the mutual influence both the fluid flow and the heat transfer into account. Much more accurate and reasonable temperature fields results can be obtained, which provides the required conditions for the heat stress calculation. The engine model is simplified reasonably and meshed in this paper. Then the whole conjugated heat transfer method is applied to calculate the gasoline engine temperature field. The analysis is carried out on the temperature field, velocity field and heat transfer coefficient results. The results show that the design scheme of the water jacket model meets the cooling need of the new engine. Comparing the calculated results with the experimental ones, great differences are found in local hot regions. More researches on the phenomena and the rules of the boiling heat transfer on the local hot regions in the water jacket of the gasoline engine will be brought out. This paper discussed the problems of design complexity and modeling difficulty for the large wind turbine blades. According to Wilson theory and BEM theory, Matlab was used to calculate chord length, torsional angle and coordinate transformation. The coordinates were outputted automatically. The result obtained from the program was transmitted directly into Pro/E, and the 3D modeling of large wind turbine blades was achieved. This method accomplishes the programming design and the parameterized modeling, thus enhances the efficiency of the design and precision of modeling. An algorithm for environment modeling of mobile service robots based on the binocular stereo vision is presented. Three classical algorithms for environment modeling are emulated and compared. The structure of mobile service robots based on the stereo vision is divided into four sections: perception, modeling, planning, and action. The binocular camera is used to gather information of environment in the section of visual perception. Scale-invariant feature transform is used to collect pairs of stable feature points which are matched in one pair of pictures, and then three dimensional information of feature point will be obtained by using disparity to measure distance. The algorithms of environment modeling describe circumstance with the three dimensional information of environment feature points and match the current pictures being gained to the last pictures. The algorithms of environment modeling can guide the mobile service robots to avoid obstacles and get to the destination safely and reliably through path planning and vision navigation. This paper achieves different mapping methods through simulation experiment and gains the effect of map's use in robot vision navigation and obstacle avoidance experiment. Based on basic principles, operational requirements and key parameters of Seed Rope Direct Sowing Machine(SRDSM), the machine was designed and developed. The structural design of the anti-blocking device, sowing device, opening device, banking device, compacting device and assembly of the seed rope direct sowing machine, have been finished with the assistance of UG. The manufacture and testing of the prototype were carried out. Field test results showed: the machine has good maneuverability and high working efficiency, sowing effect is to meet the operational requirements, and effectively solved the problems of the easy plugging of opener and adjusting difficulty of the numbers of seed in every hole. It provide reference for the research and development of such equipments. This paper analyses several well-known class-cohesion measures in depth and points out their defects. Above all, it states that a class exists in the context of a software system and cannot be isolated because of the existence of interactions between it and the environment. It should be considered that external factors and other classes are capable of affecting the cohesion-measure result for a class. Therefore, we propose a new weighted-LCOM approach to measure class cohesion. Several commonly used measures and the new weighted measure are applied in some experiments to obtain cohesion results, and we prove the superiority, accuracy, and validity of the new measure by comparing these experimental results. The new method represents a new concept for evaluating class cohesion. This study presents a systematic method for concurrently developing the product variety. The proposed method integrates three approaches successively. First, the quality function deployment approach identifies the external driven factors of design variation. Second, the quantified design structure matrix technique is proposed to identify the internal interactions and build the hierarchy of components interactions within a product. Third, the morphology analysis approach is applied to visualize the concepts of the developing product through creating design solutions for every component and module. This approach represents the design priority and related design constrains using a structural graph for helping designers to create design solutions in a product design for variety. A case study is employed to illustrate this method and the result validates the feasibility and effectiveness. An efficient simple mechanical method is introduced to manufacture homogenous carbon nanosheets, having a thickness of the order of nanometer, high shape asymmetry, and a well preserved crystalline order. This mechanical method is based on the grinding of carbon powder under low energy pure shear milling, using liquid nitrogen as lubricant, to ease milling process. Homogenous carbon nanosheets with nanometer thick were synthesized using an efficient method as proved by SEM micrographs. Aiming at the questions of the standardized design of Movement Authority in high-speed train control system, this paper proposed a model of Movement Authority based on the generation of Movement Authority principle of RBC in the CTCS-3 Train Control System. We model the generation process of Movement Authority under the RBC handover mode, which can be achieved dynamic simulation by CPN tools. Finally we can verify the correctness of the principle Movement Authority generate and analyze its performance. This design for the Movement Authority Module provides a standardized method of software design and verification, and then can ensure the RBC control trains normally. Illumination control system is the base and precondition for image measurement because the measuring precision depends largely on high quality image data. The architecture of lamphouse and illumination scheme affect the image quality and edge extracting effect directly. This paper designed an illumination architecture which includes a back light and three direct ring front light lamp houses. A self-adaptive illumination control system based on genetic algorithm was put forward in order to acquire the best quality image of the object. The optimal illumination control parameters aimed at different objects to be measured could be found with the help of intelligent illumination control system. The expert system based on the category of objects to measure was built to accelerate the searching process for optimal control parameters. Experiments show that the proposed strategy can improve the performance of illumination control system greatly. In this paper, a 2DOF parallel proprioceptive mechanism for vehicle driving simulator with 3-leg is proposed. The proposed mechanism, which can realize pitch, roll and vibration motion of vehicle driving simulator, includes the bottom fixed platform, two servo electrical cylinder, one supporting pillar, the top platform and some joints. The kinematic characteristics of the 2DOF are analyzed and some analytic formulae are derived for solving inverse displacement and forward displacement. The analytic results are verified by its simulation mechanism to be consistent with the calculated ones. The proposed mechanism has very simple structure and low development cost, and is easy to regulate position and attitude of vehicle driving simulator. A combination boom mechanism for corn sprayer has been developed in this paper. The new-designed boom mechanism included horizontal boom, vertical boom, flexible connection, branch boom and stir wings. With the combination of the theories and methods of spray distribution uniformity, effective spray droplets coverage, and image processing in MATLAB, the length of the vertical boom and fixed angle of the branch boom were determined as 1200mm and 20°, and the spray scale of combination boom in the vertical plane was 1150mm. Using this combination boom mechanism, the corn plants met an all-direction spray, not only the upper part, but also the middle-lower part of the corn plants were sprayed, and the reverse side of the leaves of plants ould meet more spray droplets, so better spray results was achieved. Introduction of the design method to achieve semi-physical simulation system on the basis of the hydraulic test platform and EASY5 hydraulic system simulation model. Using EASY5 and MATLAB / SIMULIINK co-simulation model, Real-time simulation control was achieved by calling the Windows API Multimedia Timers in MATLAB/SIMULINK to overcome the realtime weaknesses of EASY5; TCP / IP Network Communication was used for data exchange between Simulator and Control machine; man-machine interface of simulator was designed with Visual Basic, to achieve experimental initialization the hardware in the loop simulation system and start the simulation. It can be seen from the test results that the semi-physical simulation system work well. It is an effective way that getting as much room as possible in a dispenser to carry more goods and increasing the scattering efficiency of the dispenser to raise its dispensing performance. According to the applied need of a radial scattering dispenser, a mechanical device which acquires driving force caused by torsion spring to change the relative position between parts of dispenser is designed. Its working performance is calculated and analyzed. LNG (Liquid Natural Gas) is also known as the 1œgreen fuel1 due to its high value of energy density and environmentally friendly behavior. LNG imports have grown in many countries at a remarkably high rate. On the other hand, technological innovation related to LNG facilities have continued, responding to modern regasification needs, like reduction in power consumption in this process. In order to improve the regasification process, it is possible to couple a vapor compression refrigeration cycle with a LNG regasification system. Energy saving is not the only benefit achieved. By using a green refrigerant, such as ammonia, the stratospheric ozone layer is protected. It is shown that the exergy analysis plays a key role in the optimization of the considered system. By assessing exergy destructions it is possible to determine the first component to be improved. Using computer software 1œSolid Works1 for generate the geometric form of the seal's rings and 1œANSYS-9 WORKBENCH1 program for the FEM analysis to calculate mechanical stresses and thermal loadings of a mechanical seals as a part of the centrifugal pumps working in an oil refinery. The goal of this analysis is to improve the design of the seal. The analysis was performed for the mechanical seals of the 100P3A and 100P3R pumps of an oil refinery. Two 1œscenarios1 was considered; each them is an 1œengineering1 simulation. To define the simulations we considered as known: the type of material and the material properties; the behavior of the contact surface of rings; the types and the magnitude of the loadings on the ring. As a variable are considered the geometric shape of the rings and loadings. Type of the material of sliding rings: silicon carbide/graphite. For the Scenario No.1, the two sliding rings of the mechanical packing resist to compression stress in the normal running conditions (work in the presence of auxiliary liquid). The two sliding rings resists even in the damage conditions (in the absence of the auxiliary liquid), like we can see in the Scenario No.2. The equivalent stress (Von Misses) had a maximum value in the silicon carbide ring for the both scenarios. The maximum strain (deformation) is in the graphite ring, in the both scenarios and it is 1,3 times greater in the scenario No. 2 (damage running conditions). Orthogonal turn-milling is mainly used in machining big parts. In this paper, we analyzed the cutting force of orthogonal turn-milling in machining micro-miniature parts. Basing on a trochoidal tooth trace we used the cutting force model of helical edge in the analysis. From the geometry of turn-milling we obtained the analytical expressions of cutting thickness, cutting width and other parameters. Thus we could calculate the cutting force with common cutting parameters. In order to verify the results, we also carried out cutting experiments. Compare the two results and we find there is error. Referring to the previous study we assume the error come from the cutting force of end edge. Therefore we draw the conclusion that the cutting force of end edge contributes the most to turn-milling cutting force. In order to reduce labor costs and germs pollution in plant tissue culture industry, an automated system for cutting and transplanting tissue culture seedlings in breeding differentiation period was developed. The system consists of a mechanical part, an image processing part and a control part. The mechanical part performs cutting and transplanting seedlings. The image processing part detects the position of every seedling root in one bottle and the position of every node on one seedling. The control part controls the motion of the mechanical part. In laboratory, the automated system was tested. The result shows that the success rate of the root detection is more than 92% and the average detection time is 266ms, and the success rate of the node detection is approximately 91% and the average detection time is 562ms, and the success rate of taking seedlings is 86.5% and cutting nodes is 89.5%. This paper introduces a drilling experiment table for laboratory use. This table can simulate drilling process and realize hydraulic feeding, rotating, and clamping rock sample. It can also realize stepless speed regulation for rotating system, and control drilling pressure accurately. The host power head can move in two-dimensional space. It forms a sectorial working face, therefore, it can drill at any position of rock sample. A multi-drilling parameters automatic measuring system which developed with configuration software has been also devised. The system can real-timely measure drilling pressure, rotational speed, depth of drill and drilling speed, etc. All the parameters and the real-time curves can be displayed on monitor. A database of the parameters can be built. And drilling reports can be generated. The article focuses at technology development of the combined process of vertical asymmetric rolling and plastic bending. Experimental research showed serious drawbacks in the rolling technology caused by the growth of dynamic loads arising at the moment of plate contact with the bending roller. For solving the problem it was proposed to make the roller position motile to allow its movement along the required trajectory. The application of the motile roller helps to reduce dangerous torque differentiation at working rolls by the value of 1,5–2,5 compared with the rigidly fixed roller. The most effective bending roller trajectory is a second-order curve that is convex parabola. This paper describes the system behaviour so that the system can be managed using adaptation based on characteristic patterns. The aim of the paper is to develop and apply an approach based on artificial neural networks to identify successful patterns for the purpose of follow-up adaptation of the system. The manufacturing, as one of the main links between resource consumption and environmental emissions, is poorly documented in terms of carbon footprint. There lacks a holistic concept to calculate the CO2 emissions emitted in product producing and to recognize the reduction opportunities. On this account this paper proposes a systematic approach to calculation of the emissions with using a hybrid emission analysis model. The paper shifts the perspective of lifecycle assessment (LCA) from the conventional entire product life cycle emphasis to the manufacturing phase. This approach permits identification of opportunities for reducing CO2 emissions at the process level and driving the manufacturing system towards low carbon. The Monomer vertical shelter tankers have been widely used because of their well-hiddenness and economy since 1980s. But the tankers were so narrow and poorly ventilated, that the oil gas in the tanks is hard to diffuse. The concentrative oil gas will cause fire and explosion which forms the high-risk area of oil warehouse. Documentary studies[1][2][3] prove that the airflow in the narrow space of oil tank is 1œ turbulence1. Numerical simulation of airflow for tankers was carried out on condition of natural and mechanical ventilation, using the computational fluid dynamics (CFD) code CFX5.7 based on k -1turbulence models. Regularities of distribution of oil gas in the tankers was compared and analyzed, and the improvement of reducing the concentration of oil gas was proposed. When stranded-wire helical springs are impacted, the movement of every spring coil will become very complicated owing to various factors, such as the mass, inertia and resonance of spring, the internal friction of steel wires, also the relative slipping during different steel wires of strandedwire helical springs. Base on that, a non-contact and multi-channel detection device of dynamic parameters of stranded-wire helical springs is proposed, which involves the design of mechanical structure, the lectotype and installation of sensors, the hardware and software module of signal acquisition and analysis. This device, combining a novel algorithmic of data processing special for springs, can be used to measure the relationships between displacement and time, velocity and time, acceleration and time for every spring coil. The results show that when stranded-wire helical springs are impacted, all spring coils will vibrate, also this movement will transmit to the fixed end in the form of longitudinal wave and reflect there; the relationship between displacement and axial length of spring coils point is non-linear, the same situation for the relation between velocity and spring coils' position; additionally, in the beginning of impact there is a large deformation in the active end, whereas on the contrary, little deformation in the fixed end while on the other hand there is a large deformation in the fixed end when the wave reaches there and reflects. Therefore, in practical design work of stranded-wire helical springs, it is necessary to analyze the impact response of springs in order to avoid the phenomenon of excessive deformation of some spring coils by selecting reasonable parameters. Microbial carbonate precipitation (MCP) is a process increasingly studied with the goal to exploit it to adapt mechanical soil properties for desired land uses. Fundamental understanding of key processes in MCP is needed in order to obtain a controllable full-scale application. Besides experimental investigations, mathematical modeling can help by creating a logical framework in which experiments can be interpreted and, if developed enough, predictions can be made. In this study we developed a numerical model that takes into account the various processes governing MCP at micro-scale (mm). Processes investigated include fluid flow, solute transport, crystal growth and deposition, and the clogging of pore spaces. These processes take place at a pore scale and have their effects on overall system properties. Although lab-scale experiments have proven helpful in elucidating the basic mechanisms that govern bacterial transport, crystal growth, deposition and detachment in porous media, the presence of physical-chemical and biological heterogeneities in several physical and engineered micro-systems make them extremely difficult and complex to represent experimentally. To investigate these processes at pore scale, a model is developed in which the porous medium is represented as an idealized twodimensional structure. An aqueous influent containing urea and calcium chloride flows by through the porous medium. Solutes are transported by convection and diffusion. Bacteria present on grain surfaces hydrolyze urea, forming ammonium and carbonate ions. Microbial carbonate precipitation occurs in the presence of calcium ions, eventually leading to calcium carbonate crystal formation. The model calculates the growth of a layer of crystals on the grain surface, leading to a narrowing of the pore channels with a concomitant increase in pressure drop and average fluid velocity over the 2-D structure. The results show that this simplified model can be used to identify phenomena that occur in physical experiments and have an effect on the larger scale. Creep and temperature-dependent creep, characteristic of one component polyurethane adhesives for wet and green structural wood glueing such as in glulam are two different parameters. Testing of the best standards-approved commercial polyurethane adhesive for this purpose shows that while ambient temperature creep is limited this is not the case for temperature-dependent creep. The commercial adhesive formulation characteristics that minimize or enhance ambient temperature and temperature-dependent creep are identified. In the paper the effectiveness of neighborhood structures in local search algorithms for flexible job shop scheduling problem on makespan is discussed. For the analysis of the effectiveness neighborhoods N1-N4, NS and NL with GRASP algorithm were used. Experiments with different neighborhoods of the algorithm have been considered and compared. The presented neighborhoods have been tested, and illustrated with examples for serial and serial - parallel routes. Giant magnetostrictive high power transducers usually work under a high intensity and frequency magnetic field. Hysteresis losses and eddy current losses are very heavy. At the same time, giant magnetostrictive materials (GGM) is sensitive to temperature. Therefore heat generation and temperature distribution is very important for the transducer's design. In this paper a high power ultrasonic transducer was designed. The magnetization behavior of GGM in the transducer was characterized by the modified Jiles-Atherton hysteresis model which considers eddy current losses and anomalous losses. Model parameters were determined from the least square fit between experimental values and model values. Various losses were calculated. Temperature distribution of the transducer was calculated with finite element method. Calculation results and experimental results show a good agreement. This paper presents a policy for visualization of large terrains in real-time. Our approach introduces an efficient terrain data structure based on hybrid quadtree, which combines static full resolution and dynamic variable resolution quadtree to organize the whole terrain scene and reduce the level of detail at need. Another feature is taking advantage of GPU to achieve view-frustum culling and terrain blocks updating. We also discuss some system-level aspects such as multithreaded asynchronous implementation of the proposed algorithm, video-memory allocation control, camera position prediction, etc. The presented approach shows a maximal speed increment of 38% for high-quality terrain rendering compare with other similar solutions. Based on wavelet transform has good time-frequency analysis character, wavelet de-noising principle and methods are introduced. Collecting acceleration response of tank when tank car is in pitch condition, using wavelet to de-noising and decompose vibration signals, extracting the low-frequency part and for its Hilbert envelope, and then, obtaining the power spectrum. The paper analyzes how liquid sloshing inside the tank impacts vibration of the car-body when the vehicle obtains an excitation. The results show that: wavelet analysis can better filter interference signal, the existence of the liquid in tank will increase vibration of the car-body, which is adverse to vehicle dynamic performance. Firstly, the model of the leaf spring, which supports the rear driving axle of minibus, was established by using three-link leaf spring model method. In multi-body dynamic simulation software ADAMS, this spring model was employed to calculate its stiffness and guiding characteristics. Then the software, SOLIDWORKS, was integrated to establish the model, including the combined stiff and flexible parts from the gearbox output shaft to the half axle of the driving axle and the rear suspension. With this model, Kinematics and dynamics analysis were performed. The effects of equivalent shaft angle on the vibration characteristics of various important components of the system were also investigated. The results show that when the angles between cross axes in the two universal joints are not equal it causes severe vibration in the important components among the driving shaft-driving axle system. The simulation with high reliability provides a dynamic ride vehicle model for follow-up study. According to the function requirements of CAD system of heat transfer equipment design in thermodynamic fields, data contained in a CAD system and its subsystems of shell-and-tube heat exchanger were analyzed synthetically, and the layout and design of system database were carried out. The framework of system database was presented, and the function and application of databases in the system including physical parameters, engineering materials, geometrical parameters of parts and drawings were discussed. The design and practice of database offer reference for design and application of database in other machinery CAD systems. The particle inconsistency problem significantly influences the calculation accuracy in the smoothed particle hydrodynamics (SPH) method. In the present study, we investigate primarily the influence of the particle inconsistency on the first derivative of field functions and discuss the behavior of several methods of dealing with this problem. In addition, we propose a new approach by which to compensate for this problem, especially for functions having a non-zero second derivative, that is less computational demanding, as compared to the finite particle method (FPM). The performance of the new approach is verified by a series of numerical study in one and two dimensional problems. In this study, a structure of a thin and flexible tactile sensor using pressure conductive rubber is presented. The sensor can cover specific three-dimensional surface, has a total of 36 elements and can measure the pressure in the range 0-600 kPa, approximately. In order to compare the performance of the voltage feedback methods and the zero potential method, which presented in the literature are applied to weaken the crosstalk effect in a resistive array, some simple circuits are structured based on these methods, respectively. Then the effect of some circuit parameters on measurement errors of each circuit is simulated and analyzed and the performance of the circuits to weaken the crosstalk effect is compared. According to the simulation results, the performance of the circuit based on the voltage feedback non-scanned-sampling-electrode method is the best than any others. Therefore, a tactile signal acquiring and processing circuit based on this method is design. At last, experimental results that the crosstalk affects the measurement errors of this circuit are given. Image registration for supper resolution reconstruction plays a paramount part in video-based criminal investigation and judicia1 forensics wherein the re1ated video materials taken from public surveillance system, mobile phones, and so forth are generally very poor in quality, and thus most of the popular super resolution image reconstruction methods fail to obtain satisfactory results In image registration, we defined a new type of control point called dominant point to capture the local variation property of an image. The order relationship between the sorting dominant point sequences, respectively extracted from the reference image and the target image, matches the two images, and at the same time, their location relationship is adopted in projection kernel regression, a new representation for function approximation in KBHS, for coordinate mapping function approximation. To reduce the computational time and cost of running computer-based simulation experiments, metamodels are becoming more and more popular for replacing the simulation codes for design and optimization. In this paper, a gene expression programming (GEP) based kriging method is proposed. In this method, the GEP algorithm is used to create regression functions in kriging metamodels. An asymmetric function is taken as an illustrative example to prove the validity and effectiveness of the proposed method. Compared to the GEP and original kriging methods, the proposed method can achieve more accurate approximation of a high-dimensional design space. The GEP based kriging method can not only improve the prediction performance of the original kriging method if strong trends exist in the original function relationships, but also deal with the approximation of the high-dimensional design space, where GEP shows poor performance. This paper is a part of the study on boom-type roadheader' s directional excavation, providing a theoretical basis for the accuracy of directional excavation. The author has analyzed the characteristics of work environment and developed the strategy of automatic compensation for pose deviation according to four basic pose parameters, on the basis of the key technologies on automatic cutting control and the key technologies on body pose parameters' detection. In this way, the problem caused by pose deviation can be solved, and then, the 16 situations of pose deviation combined by four basic pose parameters can be solved as well. Based on the development of the General-utility design of human-machine interaction (HMI for short) interface, and after the detailed analysis on the idea and technical characteristics of HMI interface, this paper studies the feasibility of the Generalutility design of HMI, according to which it comes up with a design model, it also emphatically elaborates HMI interface's principles and its technical supports. Moreover, the development tendency of General-utility design is properly prospected based on the living design examples at the end of paper. This paper introduces folk toys' value as materialized, realizable carrier of folk game culture from the aspect of folk game culture's development and inheritance. It further suggests that territorial toy design is the effective way and innovative mode of folk game culture's development and inheritance of modern nations and is the way of realizing sustainable development of non-material cultural heritage's protection. It takes the case of Chang yang district and emphatically elaborates territorial toy design's functions in the development and inheritance of folk game culture; it also thinks about the development of territorial toy design. Based on finite element simulation software Dynaform, the influence of process parameters such as blank-holder force (BHF), liquid pressure, gap between die and punch, and friction coefficient on the weld-line movement in hydro-forming deep drawing of square cup using tailor-welded blanks (TWBs) with different thickness has been simulated and investigated. The results show that when Q b 1Â¥ Q h in hydro-forming deep drawing, the effect of the pressure difference between thin and thick blank on the weld-line movement is not so much, while the bottom weld-line movement is reduced effectively by controlling the height of equivalent drawbead during pre- bulging, and the weld-line movement of the sidewall is decreased significantly by increasing the liquid pressure in the die cavity. At the same time, forming limit depth can be improved by increasing the gaps between die and punch. The results of this investigation have the practical significance to guide hydro-forming of tailor-welded blanks. In order to guarantee consistency of workpiece manufactured, grinding the transition surface is an important issue for manufacturing indxable insert. In this study, the paper analyzed systematically indexable-insert for cutting tools designation (ISO 1832-2004), and made use of parametric design method to analyze the geometric features of indexable insert. What is more, on the basis of grinding principles and the point-vector method, the mathematic models of typical transition surfaces of inserts-insert with wiper and chamfer, and insert with nose radius were established. The mathematic models derived are most important part in writing the software which is used to generate automatically programs for manufacturing indexable insert .The idea was that using small planes describe the transition surface of insert, and then a general relationship between those planes and workpiece coordinate system could be established based on the point-vector method. Finally, the simulation examples were done by CAD/CAM to check the correctness of the models. The method presented could be extended to study more complicated transition surface of insert. The identification of flame stability plays a vital role in the industrial production of plants. This paper presents a novel approach to the identification of the flame combustion stability. The various features that can reflect the characteristics of flame signal are extracted from the time and frequency domains of the signal. Based on the principal component analysis (PCA), the five features extracted are compressed into two features, which is very convenient to carry out the pattern identification following. The back-propagation neural network (BP neural network), as a good method of pattern identification, is applied to train the samplings. The results obtained demonstrate that the approach combining principal component analysis and BP neural network is very suitable for the identification of the flame combustion stability. combustion stability. The flow, heat, VOCs and humidity transfer in a cavity partially filled with thin porous medium were concerned in this paper. Two-domain model was founded by considering stress jump conditions at the interface, Brinkman-Forchheimer extended Darcy equation for flow in the porous medium and Navier-Stokes equation for flow in the clear fluid region. Finite element method was used to solve the governing equations with weak constraint condition at the interface. This paper was focused on the influence of Darcy number and stress jump conditions on flow, heat, VOCs and humidity transfer in the composite cavity. The numerical results showed that heat and humidity transfer would be enhanced with increase of Darcy number and stress jump coefficient. And the stress jump coefficient with different Darcy number would induce a specific behavior of VOCs transfer in the enclosure. This study aimed to investigate the effects of grain refinement on forming and brazing characteristics of three-layer 4343/3003/4343 aluminum clad sheets. The clad sheets with 0.7 mm thickness were fabricated by hot roll bonding process. Al-10Ti master alloy was used for grain refining of 3003 Al-Mn core alloy. The Ti inoculation level was changed up to 0.1%. The forming characteristic of the clad sheets was strongly dependent on the recrystallization microstructure feature according to Ti inoculation level and stress relief annealing condition. 0.011¼0.1%Ti inoculation treatment significantly improved the biaxial formability of the clad sheets at room temperature by 2 times or more. Ti solute dissolution of a significant level, 0.06%, from the core layer into the clad layer effectively refined 1-Al cells and eutectic Si particles of the resolidified filler layer, resulting in bonding strength increment of the brazed clad sheets. The sagging resistance was improved with increasing Ti inoculation level, because the core strengthening effect due to Ti solute and its intermetallic compound was bigger than the weakening effect due to erosion phenomenon. In case of material testing, the result of a measurement is only an approximation to the value of the measurand and is only complete when it is accompanied of the uncertainty. Computing the reported test result is straightforward; however, computing the uncertainty associated with the test result requires more consideration. The uncertainty evaluation process will encompass a number of influences quantities that affect the result obtained for the measurand In order to quantify the uncertainty we will have to consider all the factors that could influence the results. Material testing measurement process is always doubtful about the value of quantity to be measured which provides the basis for safe working of mechanical components during their operations therefore, Therefore Measurement professionals need to be explain to their clients the value of their work including its limitations. In this paper a methodology is developed for determining the result of measurement concerning the area of material testing and their respective uncertainties. Such methodology, which has a possible systematic application, is associated with guarantee of metrological reliability to the results of measurement in material testing, as well as the possibility of implementation in industrial laboratories, and in the Testing Laboratory Network. With this a mathematical model is developed by using regression analysis to explain the impact of various parameters on the measurement uncertainty and quality of material testing. This paper presents a low-cost solution to compute the attitudes of a tunnel boring machine (TBM) during microtunneling. Given the traditional method, three rotation angles of yaw, pitch and roll can be computed by the coordinates of three observation points on TBM. The improved modeling compensates shortcomings of the traditonal technique. The optimization method is proposed to decide better layout of the three observation points. And then, for concept reducing error due to measurement asynchronism of observation points during tunneling, Kalman filter algorithm is given to predict the coordination of observation points. Finally, Monte Calro simulation shows that the performance of this method is better than those traditional methods. The simulation experiment and measurement experiment both successfully demonstrated the proposed algorithm in terms of:(1) that Kalman filter algorithm reduced the error of attitude measurement;(2) the inhibiting effect of measurement error caused by random noise. This paper to study the difference between direct selling and pyramid schemes start with links to explain the relation ship marketing, database marketing, direct marketing based on customer relations theory and promote consumption an d growth of economic relations. Gomperts model predicts the introduction of the product life cycle and sales relations hips, the final instance through the analysis of the Amway Corporation to provide a balance of direct production cycle worthy example. Brain signals via scalp Electroencephalography (EEG) can be used by patients with severe motor impairments to communicate with their environment. This can be done by brain—computer interface (BCI) system. This work is based upon utilizing the brain signals of a human-being for the extraction of rhythmic activity from one or two channel noninvasively recorded signal using IEEE standard 1057 algorithm and the classification (using SVM ) of important information which can be used to get the control of a robot's navigation without physical strain. The procedure includes acquisition and analysis of brain signals via EEG equipment, development of a classification system using SVM techniques. The popular proportional fairness scheduler (PF) is very suitable for trade-off between system throughput and fairness, but we found a fatal problem when applying it for broadband networks with heterogeneous traffic. Because the PF scheduler only considers the average throughput, it will favor users with low data rate. This paper proposes a generalized PF scheduler which considers the profit instead of the average throughput. Simulation results show that the proposed scheduler can provide better fairness and transient behavior. The present paper develops a Concensus-Based Decentralized expectation-Maximization (CB-DEM) algorithm to estimate the parameters of a mixture density model for use in distributed flow and speed modeling tasks performed with traffic data collected at spatially deployed traffic loop detector (traffic sensors) in a certain freeway network. This algorithm uses traffic measurements including volume, occupancy and mean speed which gathered by some inductive loop detectors. These traffic detectors (traffic sensors) located in certain distances in the freeway network such that they establish a Distributed Sensor Network (DSN). The convincing simulation results for a set field traffic data from the Metro Freeway Network provided by Regional Traffic Management Center (RTMC), a part of Minnesota Department of Transportation (MnDOT) are presented. In this paper, the anti-pounding dampers were installed in a high-pier bridge's pounding locations (expansion joints) in longitudinal and transverse directions, under multi-excitation considering the traveling wave effect, the comparative analysis of the seismic response of the high-pier bridge between with and without the anti-collision damper which is set on pounding location were carried out. The anti-collision damper can be effective in preventing collisions between deck beams and between deck beam and block, and the displacements of the bridge piers is limited, internal forces of piers' bottoms greatly reduced, then to reduce the damage to piers, which will help to improve the overall seismic performance. But setting collision damper would also adversely affect the high-pier bridge, can increase the possibility of damage to the deck beams and uncertainty of some bearings' reaction. The experimental research was made on superficial layers laid-down through electrical sparking on the steel carbon OL 37 probes, the used electrode being made from a corrosion resistant material (Aluminum). The experiments where for the superficial treatment through impulse electrical discharges, made with the ELITRON 22A equipment, using an Al electrode of some parallelepiped probes with the surfaces of 0,00127512 m2, from steel carbon OL 37 brand, the probes plane surfaces where previously prepared. Preparing the surfaces presumes a thorough treatment and degrease with a powerful solvent. The treatment through electrical discharges where made manually, the active electrode is under a 60° angle with the treated surface. The probes on which the superficial treatment was made through impulse electrical discharges where individually weighted on the analytic balance at different time intervals, determining the corrosion process speed. The fine determining of the topography surfaces exposed to the action of the corrosive environment was made using the atomic force microscopy (AFM). For a comparative analysis of the effect of the corrosive environment on the superficial treated probes and on the untreated ones, a series of determinations have targeted the analysis of the surfaces of a probe subjected to the corrosive action of the environment, in the same conditions as the superficial treated probes but without the protection of the surfaces of the probe. The lack of the superficial layer permitted the corrosive environment a massive and pronounced attack on the probes material. The images on the original probe, resulted from the atomic force microscopy (AFM), indicate that after the action of the corrosive environment, shows unevenness, with material loss, which can be noted on the whole surface of the probe. In certain higher portions of the probes material, as a result of different phases from the structure, it was 1œconsumed1 less intense. The purpose of this research was to create a methodology for adopting the structure of a naval propulsion plant, by an estimate of noise. To choose the best way to approach, first of all, it was performed a study on a simple physical model which consists of a flat plate structure in U. In order to perform the static energy analysis it is formulated a set of equations of power flow for this structure. Vibro-acustic shipboard pollution is a very important issue for all classification societies prestigious as it may negatively affect both resistance vessel structure (shell and bone) influence the safety equipment on board and work and health staff on board. In accordance with the rules of classification societies, vibro-acoustic levels on board must not exceed specific maximum values allowed. The structure of Printing machine is complex, different parts have the same frequency signal in running, so it is very difficult to obtain the fault and status signal. In this paper we present a new method to monitor printing machine condition based on printing image texture. First we collect GATF images from different printing, then use gray level co-occurrence matrices (GLCM) to extract feature from GATF pictures, the features are classified by BP neural network methods, it can reflect part of printing machine condition. S7 communication can be used for Industrial Ethernet, PROFIBUS or MPI network. In this paper, Achieved by PLCSIM between two S7-400PLC based on TCP / IP, S7 communication, Describes the configuration of an S7 communication and programming. For two or more communications between the PLC simulation, PLCSIM the same. PLCSIM also supports MPIbased S7-400 S7 communication and S7-400 DP-based simulation of the S7 communication. The S7 communication network configuration and programming is basically the same, and it can provide some reference value for the analogous project. The design idea of PLC in combination with Touch-screen applying to the reinforced network forming machines welding control system is introduced in the paper. The hardware composition and System working principle are detailed described. The result of operation shows that the control system features flexible Operation, reliable work and convenient maintenance. The Cam-linkage mechanism has been widely used in many print and package machines. This paper proposes a method to simulate the movement of Cam-linkage mechanism using the SIMLINK software. The modules of velocity simulation, acceleration simulation and displacement simulation are designed, and the software of the simulation system is compiled. The kinetic analysis of the Intermittent Rotary Sheet Transfer Mechanism is also simulated by the software. The result of simulation meets the reality. The simulation system is convenient and the accuracy is very high. A large number of tedious deviations of analytic equations and the solution for equations are avoided, such that the intensity of the work is decreased and the efficiency of work is improved. A method to implement the on-machine measurement (OMM) with the touch-trigger probe, also called switching probes is advanced in this paper. Some of the advantages and disadvantages for touch-trigger probe are discussed. An objective function is proposed in this paper to evaluate the minimum zone cylindricity error. The error model is optimized by Genetic Algorithm (GA). The mathematical model may work out the minimum zone solution of cylindricity error with arbitrary position in space, and there are no special requirements in choosing measurement points. A case has been given to prove that the OMM system is useful for online inspection compared with Coordinate Measurement Machine (CMM). The approach can also be extended for solving other form and position errors. Nowadays, various researches about eco-friendly vehicles such as hybrid electric vehicle, fuel cell vehicle and electric vehicle have been actively carried out. Since most of these green cars have electric motors, the regenerative energy technology can be used to improve the fuel economy and the energy efficiency of vehicles. The regenerative brake is an energy recovery mechanism which slows a vehicle by converting its kinetic energy into electric energy, which can be either used immediately or stored until needed. This technology plays a significant role in achieving the high energy usage. However, there are some technical problems in driving safety and ride comfort of the vehicles. In this paper, the Hardware-in-the-loop Simulation (HILS) of Electro-hydraulic Brake (EHB) is performed to analyze the characteristics of the regenerative braking system for fuel cell electric vehicle. The performance simulator of the fuel cell vehicle is developed and transient response characteristics of the regenerative braking system are analyzed in the various driving situations. Recently driven by the increase in resource depletion problem and environmental pollution problem, there are active on-going developments of vehicles using motor as power source like hybrid vehicle, electric vehicle, fuel cell vehicle. Regarding such motor-powered vehicles, various researches are in progress for the enhancement of vehicle efficiency, and one essential technique to enhance vehicle fuel efficiency is the regenerative braking that uses the kinetic energy which is consumed as friction upon braking as power source by storing it in energy storage device like battery and ultra capacitor

This proceeding records the fully refereed papers presented at the 3rd International Conference on Computer Engineering and Technology in Kuala Lumpur, Malaysia from 17 to 19 June, 2011. This conference brings together scientists, scholars, engineers and students from the universities around the world and presentatives from industry, to present ongoing research activities, and hence to foster research relations between academia and industry. This front matter contains the preface, list of the organizing committee and table of contents. Click on the PDF icon to view the complete front matter. Requirement Determination (RD) is a communication-intensive activity, at minimum involving analysts, developers, business stakeholders and end users. Effective communication typically demands skilled requirements analysts, effective practices for requirements definition and management and tools to assist with these critical activities. The many human interfaces involved with requirements can lead to a variety of communication problems, including miscommunication between users and analysts, misunderstandings between analysts and developers, all of which add time and cost to software projects. This paper describes some of the key requirements issues that affect nearly every software and systems development project. Off-shore oil and petrochemical industry as high-risk industries, chemical products involved in the production and storage, marine construction and services, production operations and other risks, all types of emergencies that may occur at any time, safety production supervision is very difficult, arduous task of accident prevention. From the perspective of information technology on CNOOC deal with the accident emergency response to the incident response measures studied, with CNOOC existing network resources and the actual work proposed functional requirements of the emergency command system and thought, the use of a unified information system platform for the organization and command to respond to emergencies and improve emergency response capability to ensure that the work of emergency command prompt, efficient and orderly manner. Sigma-Delta Modulation (SDM) is a method for encoding high resolution signals into lower resolution signals using pulse-density modulation. This technique has found increasing use in modern electronic components such as analog-to-digital and digital-to-analog converters, frequency synthesizers, switched-mode power supplies and motor controls. One of the earliest and most widespread uses of SDM is in data conversion. An analog-to-digital converter (ADC) or digital-to-analog converter (DAC) circuit which implements this technique can relatively easily achieve very high resolutions using low-cost complementary metal-oxide-semiconductor (CMOS) processes, such as the processes used to produce digital integrated circuits. In this paper, a field programmable gate array (FPGA)-based prototype of first order Sigma-Delta modulator is presented. VHDL language is used to design and simulate the prototype. The implementation is performed using Xilinx Spartan-3 FPGA. The algorithms and implementation steps used are discussed in details. This study shows that although FPGA does not offer optimized hardware implementation compared to application-specific integrated circuit (ASIC), it allows short design time and enable verification of algorithm in hardware quickly. The subject of this research is the problem encountered in the localization of randomly distributed reactors in wireless reactor networks, a topic which has gained importance recently. In reactor networks, virtual or real-time localization of reactors is used in military and security applications, as well as in Geographic Routing algorithms. No constantly located reactors exist in this study; this is ‘Anchor Free Localization’ (AFL) [1]. By using the Flooding Routing method, every reactor, with its own ID, transports the signals and IDs that it receives periodically from its neighbors to the gateway. By means of the enhanced algorithm, we are able to obtain the most realistic network topology in the gateway. When brakeing on mue-split road, vehicle will run away off its orbit as the result of different brake force between both sides. Anti-lock Brake System(short of “ABS”) can not make brake intensity and directional stability optimized at the same time. To solve this problem, this paper proposes a Steering Stability Control strategy, which mainly utilizes Electric Power Steering(short of “EPS”) system to provide the vehicle with additional counter-steering torque in order to offset the unbalanced yaw torque on the vehicle, so that the vehicle could maintain its directionality instead of deviating from direct path. By means of co-simulation with ABS control, the SSC control method proposed in this paper has been validated. The rising popularity of social games worldwide has resulted in a growing importance for evaluation of Human Computer Interaction (HCI). Unlike most studies, this research study focuses on adopting a user-centric approach in order to assess the level of user engagement in social games. By combining two proven HCI evaluation methods, a comprehensive approach towards evaluating HCI user level engagement is developed. One method focuses on the game-gamer interaction whilst the other focuses on the gamer solely. As a result, an in-depth understanding of the gamer is achieved and can be better assessed. An individual discussion of each method is presented before both methods are combined to achieve a synergy in HCI evaluation. This combined method could ultimately serve as advancement to the quality of HCI evaluation. In the Internet, nodes are identified using IP addresses that depend on their topological location. IPv4/IPv6 translation technology involves address mapping between IPv6 and IPv4 nodes and the methods used to translate protocols, where nodes are in their respective IP version of network. This paper presents an IPv4 to IPv6 transition mechanism which attempts to provide transparent routing for end-nodes in IP V6 realm trying to communicate to end-nodes in IP V4 realm and vice versa. This is achieved using a combination of MAC address mapping and protocol translation. In order to study the energy-saving optimal control strategy for the two trains in a following operation under a moving autoblock system, an energy-saving control model is created. The main aims of the model are energy consumption and time error besides the safety. Based on this model, the static and dynamic speed restraints are put forward. Combined with the genetic algorithm (GA) and external punishment function, this problem is solved effectively. Real number coding and the strategy of ramps divided into three parts are adopted to shorten the length of chromosomes and improve the speed of the convergence. The simulation result shows that this method can reduce the total energy consumption of the two trains effectively based on the safety and punctuality. This article describes a technique which can be used to recognize isolated Farsi characters by normalizing them for orientation and size, finding the regions and categorizing by their alphabetical features. The system is rapid and able to recognize about 630 characters per second. The system not only identifies a character but also gives a measure of how close characters are to each other. Understanding the movement pattern of mosquitoes is necessary in malaria research, especially in network modeling, which is based on the fact that the interactions between mosquitoes and human hosts (through blood sucking bites) sustain malaria transmissions. Flight attributes such as direction of flight, length of flight, determinants of flights, among others will affect the overall dynamics of the human-mosquito network. This paper reviews related works on mosquito flight behavior, gives brief treatment on how this is applied in mosquito traps technology, and as well as outlines the overall implications of mosquito flight patterns to network-based modeling. This work is part of an ongoing research project on network based modeling approach to malaria research with particular interest on the prediction of the public places that act as vector reservoirs. In this paper, we introduce two algorithms for self-embedding an image into itself as a means for protecting the image content. After self-embedding, it is possible to recover portions of the image that have been cropped out, replaced, damaged, or otherwise tampered. The algorithms is based on transforming small 8×8 blocks using a DCT, quantizing the coefficients, and carefully encoding them in the least significant bits of other distant squares. This method provides a very high quality of reconstruction but it is very fragile. Inference techniques are used to make logical conclusions based upon given facts. Several techniques are used for inferencing like Inference with Rules, Inference with Frames, Case Based Reasoning, and Model Based Reasoning. No well defined formula exists for selecting a specified inference technique for a given situation. This is because every inference technique has its own advantages and drawbacks. In this paper, the authors have proposed a solution for selecting the inference technique according to the situation and domain. Moreover, the authors proposed a metric that may be used to select inference technique. Ensuring the security to enterprise network by singular security technology like firewall or IDS is not so much effective as it should be. Especially for the enterprises where the number of policies are not always fixed or varies over the time period. Because in this case handling all the policies according to their priorities of their strictness is not always possible by isolated safe guard. Therefore we have developed the INSPIRE (Integrated Network Security Policies in Routers for Enterprises) Framework to integrate all the network security policies for such enterprise by mapping the finite state machine with router nodes in such a way that coming data traffic from unsecured network will only required to face the policies which are needed to check and verify with the help of optimal number of router nodes. INSPIRE follows a very deterministic approach and also gives the better flexibility to extend the functionalities by integrating the security policies in distributed environment using optimal number of router nodes. We have also tried to justify INSPIRE Framework not only through mathematical proofs but even by giving the practical view. Taking eight routers for policies P1 ,P2 ,P3 ,P4 ,P'1 ,P'2 ,P'3 & P'4 it is seen that the Finite State Automata(FSA) based INSPIRE Framework is as effective as expected. One of the biggest advantage of INSPIRE Framework is its automation of taking decision and simplicity in configuration tasks. Web of things evolved from Internet of things. Lot of research has been done in designing architecture for Web of things. Two main architectures are Smart gateway based architecture and embedded Web Server based architecture. These architectures address some of the basic and essential issues relating to Service Oriented Architecture for WoT. We propose a better refined architecture for above mentioned two architectures which can be potentially used to prevent security threats like DoS attacks on embedded devices attached to the web and increase its performance .Our architecture provides a way for caching responses from device and thereby increasing its efficiency and performance and yielding quick response times. When two or more components are assembled linearly, the assembly variation will be the sum of the component tolerances. To achieve high-precision assembly, the components have to be manufactured with close tolerances. But, it will increase the product cost. If the assembly variation is to be less than the sum of the component tolerances, selective assembly is the only solution. In selective assembly, the components' dimensional distributions are divided into equal number of selective groups and the appropriate selective groups are assembled interchangeably. In this paper, the best combination of selective groups for a linear assembly, which consists of three components having similar dimensional distributions, is obtained using particle swarm optimization (PSO). The combination obtained has resulted in minimum assembly variation. The assembly variation obtained by interchangeable assembly is 36 µm. By implementing the proposed method, the assembly variation is reduced from 36 µm to 7 µm. Radiography is a technique that acts as a quality control for many products. Poor quality of radiographic image becomes an obstacle for interpreter to give accurate evaluation. The problem of noise existence and low image resolution makes the radiographic analysis more difficult. Image enhancement can be applied to reduce this problem for better image visualization. Therefore, a study was carried out to enhance the quality of radiographic image on porosity with different voltage and current to capture the image. In this paper, a set of digital radiographic weld flaws on porosity image was applied with multiple smoothing techniques such as median, average and gaussian low pass filters to remove noise. Then, the combination of top hat and bottom hat morphological techniques was used as contrast enhancement. The performance of enhanced image was evaluated quantitatively using SNR and PSNR. The experimental results indicate some improvements in the quality of radiographic image in which the defect is more clearly seen as compared to the original image. The proposed technique shows that the lowest voltage and current used can give the best image quality based on SNR and PSNR and hence can reduce the energy. Cycle embedding is an important issue in interconnection networks. Embedding cycles of different sizes into a network are beneficial to the efficient execution of parallel programs. The hypercube is a popular network because of its attractive properties. Given an n -dimensional hypercube Q n and let e be any edge of Q n . In this paper, we discuss the number of simple k -cycles in Q n , which pass through the edge e for k = 4 , 6 , and 8 . ERP system includes a complete set of applications including order processing, human resource management, manufacturing, finance, accounting, and customer relationship management. Several ERP vendors have made their products available to educational institutions with very attractive pricing options. The objective of the research paper is to study the scope of ERP implementation and develop a methodology for the integration of the higher education. In the present study the data is gathered through an exhaustive questionnaire and analysis is made using the suitable statistical techniques and hypothesis is tested using the chie-square test. Data Warehousing is an approach in which data from multiple heterogeneous and distributed operational systems (OLTP) are extracted, transformed and loaded into a central repository for the purpose of decision making. Since such database stores huge amounts of historical data, it is necessary to devise methods by which complex OLAP queries can be answered as fast as possible. OLAP is an approach which facilitates analytical queries accessing multidimensional databases. Using materialized views as pre-computed results for time-consuming queries is a common method for speeding up analytical queries. However, some constraints do not allow the systems to save all possible views. Therefore, one of the crucial decisions that data warehouse designers need to make is in the selection of the right set of views to be materialized. This paper focuses on solving the multi-objective view selection problem using a Vector Evaluated Genetic Algorithm (VEGA) approach subject to disk space constraint. In this paper, we investigated the efficiency of delayed strokes like dots on lexicon reduction and also increasing the recognition accuracy in online Farsi handwriting. Many Farsi letters in a word have peripheral and delayed strokes. Two filters relying on the delayed strokes were proposed to reduce the lexicon. These filters were based on location of the delayed strokes and their sequence. The proposed lexicon reduction was implemented on TMU dataset containing 1000 handwritten Farsi subwords. Experimental results yielded the speedup factor of 3 as well as 15% improvement in the recognition rate. Automatic facial expression recognition because of its applications in many areas such as human and robot interactions, clinical psychology, psychiatry, neurology, pain assessment and lie detection, become one of the principal investigation subjects in image processing. In several last decades, considerable studies were done. Most of these studies were based on 2D static images or 2D video sequences and only in recent years, researches were attended to use of 3D images. We based our research subject on 3D methods Because of these method abilities to overcome facial expressions recognition problems. In this paper we propose a method for discriminate smile and open mouth from neutral face. We extract features by using Maximum Curvatures and Linear Discriminate Analysis and then use RBF neural network for classifying. At the end, we test our proposal method with some non-frontal view 3D images from FRAV3D database and achieve a 91.3% average recognition rate. Scaling and power reduction trends in present technology causes sub threshold leakage currents to become an increasingly large component of total power dissipation. This paper presents Multi-threshold voltage technique for reducing standby power dissipation while still maintaining high performance in static and dynamic combinational logic blocks. Here 1-bit CMOS full adder taken as an example and implemented using MTCMOS technology and compared for the power and delay parameters using Cadence Virtuoso UMC 0.18µm. Further layout and RC parametric extraction has also been done using physical verification tool. Mining Negative Association Rules is of great importance, and it helps in taking crucial management decisions. In this paper we basically focus on finding negative rules of the form X → ¬Y and ¬X → Y. To achieve this we build a one pass parallel FP-Tree, which has all the ingredients to efficiently mine negative rules. This parallelism comes from the fact that there exists taxonomy among items in the database. This assumption matches most real world situations, where mining is applied. Hence this work is practical and can be implemented efficiently as a useful mining technique. This work focuses on Market Basket data analysis and efficiently mines only the interesting rules. The finite element method originated from the need for solving complex electromagnetic problems in electrical engineering. Skin depth is one of the important issues in microwave engineering. Many software to solve skin depth problems used finite element method Such as Matlab, Comsol and etc. But Results from different software, is not accordance with each other. In this paper, the diffusion equation using the software Comsol, and Matlab Pdetool with finite element method has been studied. Simulation shows that, the results of the software Matlab Pdetool, with the physical laws do not match, and not trusted. At present, videos from the Web are always lack of effective description for retrieval and recommendation. Automatically generating the description of the videos from the Web is a hard task. In this paper, we propose a method which utilizes the titles of videos and Latent Dirichlet Allocation (LDA), a hidden topic model, to generate pseudo-descriptions for videos. In our method, we first evaluate video titles' expression ability. The title which has enough information to outline the video it belongs to will be send to the trained LDA to get its topic distributions. Using the topic distributions and word-topic distributions gotten from the LDA, we get the most likely words that belong to the video as its pseudo-description. In experiments, 62305 Chinese automotive video titles are crawled from web for testing our method. The generated descriptions of videos are evaluated manually. The result shows that the pseudo-descriptions can describe the videos to some extent, and this method provides a promising way for automatically generating descriptions of the Web videos. IPv6 becomes the core technology of the future network gradually, coming with the increasingly prominent network management problems in daily life. In this paper, we design a management model for IPv6 network, based on Authentication, Authorization and Accounting. It supports IPv4 and IPv6 dual stack accessing, and can manage mobile users by unique identity. Using FreeRADIUS, an open source software, the system implements real-time authentication, authorization and accounting on users, integrates with resources from Internet Service Providers, forms extensive management logs, and provides solutions for dynamic network management to Internet Service Providers. This paper proposes a fast SVM learning method for mobile image recognition based on bags-of-words (BoW) algorithm. Different from PC-based image recognition, mobile users usually have high real-time requirements for the return of recognition results. Considering this, this paper proposes a fast support vector machine (SVM) learning method for each image category to perform mobile image recognition. The proposed learning method speeds up the training process by exploring the distributional properties of the training samples, in another words, it utilizes the relative distance of the training samples to the SVM hyperplane to remove some meaningless samples and further cluster the remaining data into various clusters and uses the centroid to represent each cluster. Through this, the huge training data will be greatly reduced and SVM learning will be greatly speeded up. Experimental results on the scene-15 dataset show that the proposed method is very effective compared with state-of-art works. Neighbourhood Preserving Embedding (NPE) is a manifold based dimensionality reduction technique in face recognition, which is able to discover the underlying informative facial structures. In this paper, we propose an enhanced version of NPE, namely Regularized NPE (RNPE) by regulating the NPE space for gaining better recognition performance. In RNPE, the eigenspace of the within-class scatter matrix is decomposed into three subspaces and the eigenfeatures of the subspaces will be regularized according to an eigenspectrum weighting model, respectively. Then, NPE is performed on the regularized features for dimensionality reduction. The proposed method obtains better recognition rate and is experimentally verified in PIE and FRGC databases. The daily stock turning point detection problems are investigated in this study. The Support Vector Regression model has been applied in various forecasting applications and proved to be with stable performances. In this research, SVR has been used to predict the trading signal since it could handle overall information effectively even under the complex environment of stock price variations. The trading signals from the historic database is derived from the application of piecewise linear representation of stock price. Therefore, the temporary bottoms and peaks of stock price within the studied period are identified by PLR. TS fuzzy rules were applied to calculate the dynamic threshold which intersects the trading signal and provides the trading points. The fuzzy rules were trained and obtained from the trading signals generated by PLR during the training period. A collaborative trading model of SVR and TS fuzzy rule is used to detect the trading points for various stocks of Taiwanese and America under different trend tendencies. The experimental results show our system is more profitable and can be implemented in real time trading system. A rapid and accurate diagnosis in patients with acute myocardial infarction is vital, since expeditious reperfusion therapy can improve prognosis in most patients. Myocardial infarction occurred when the blood supply to part of the heart was interrupted. In ECG monitoring, ST segment means the change of electric potential in the period which from the end of ventricular depolarization to the origin of repolarization, therefore, in myocardial infarction, ST segment change is the only criterion by which a doctor can determine if myocardial ischemia has occurred in the heart. This study combines the advantages of polynomial approximation and principal component analysis. Polynomial approximation can describe the morphology of ST segment change by coefficients and principal component analysis can generate the significant features for classification. The accuracy achieves 98.07% and the proposed approach is stable for the 12-lead ECG collected from PTB database. In recent years, industrial manufacturing usually faces the tradeoff of multi-objective decision problems. Many researchers have become more aware of the efficiency of heuristics for solving multi-objective problems. In this paper, we improve the previous SPGA approach proposed by Chang et al. [19] and present a Sub-population Genetic Algorithm II (SPGA2). SPGA2 takes advantage of the Tchebycheff Decomposition and effective Pareto Fronts and Reference Points generated during the evolutionary process to enhance the performance of the proposed approach. Our experimental results show that SPGA2 is able to improve the performance of SPGA in solving Parallel Machine Scheduling Problems. In Permutation Flow-shop Scheduling problems solving, Genetic Algorithm (GA) had been regarded as a meta-heuristic for approximation in combinatorial optimization. However, the standard Genetic Algorithm has suffered from slow convergence and trapped into local optimum when meeting the problems with higher complexities. In this research, we introduce a new heuristic by using the concept of Ant Colony Optimization (ACO) to extract patterns from the chromosomes generated in previous generations. The proposed heuristic is composed of two phases: 1. the blocks mining phase using ACO approach to establish a set of non-overlap block archive and the rest of cities in set S, and 2. a block recombination phase which will combine the set of blocks with the rest of jobs to form an artificial chromosome (AC). The goal of blocks mining is to obtain a set of genes which contain dependencies among gene relationships. These blocks without overlapping of genes can be further merged to form a new chromosome and the quality of the new chromosome can be greatly improved. The artificial chromosomes generated then will be injected into the GA process to speed up the convergence. From the result of experiments, the proposed puzzle-based ACGA or p -ACGA is validated significantly outperforms than other approaches on Permutation Flow shop Scheduling Problems. Removal of baseline wander is an important preprocessing step before manually or automatically interpreting Electrocardiography (ECG) records. However, baseline wander is usually mingled with the low-frequency part of ECG, which makes it difficult to fully remove baseline wander while preserving the original clinic information. To solve this problem, a real-time approach based on Discrete Cosine Transform (DCT) is presented in this paper. Experimental results on both simulated ECG and real ECG records of PTB database show that the proposed algorithm achieves better performance in terms of preserving the original clinic information than those of well-know wavelet-based methods. The huge bandwidth consumption of Peer-to-peer (P2P) applications pose challenges to network researches. P2P traffic pattern differs from traditional internet traffic patterns in terms of network resource utilization and the number of flow connections per session. In a P2P overlay network, while each peer downloads digital content, it is also simultaneously uploading the content to other peers, thus contributing to high outbound traffic. Although some previous researches focused on the processing aspect of P2P traffic, but a few researches have looked at it from the analytical modeling point of view. In this paper, we develop a P2P analytical model that characterizes and quantifies factors contributing to the aggressiveness of P2P applications. Our model shows that a high link utilization can be achieved at the expense of network congestion. From our results, a fixed peer rate and a limited peer flow connections are the preliminary steps for P2P-friendly network architecture. A new scheme of SNR-depending Sphere Decoding (SSD), which is based on an improved method of sphere decoding (KCL), for MIMO Network Coding (MIMO_NC) system is presented in this paper. The method can provide faster decoding speed while maintaining good precision. In SSD method, we set a coefficient k adaptive to the changing SNR. Thus, we have different reducing rate of the radius according to different SNR values. The simulation results show the effectiveness of this improved method. Under this scheme, the decoding procedure of MIMO_NC system can be ten times faster with small degradation in the performance. Four variants of Particle Swarm Optimization (PSO) are proposed to solve the obstacle avoidance control problem of redundant robots. The study involved simulating the performance of a 5 degree-of-freedom (DOF) robot manipulator in an environment with static obstacle. The robot manipulator is required to move from one position to a desired goal position with minimum error while avoiding collision with obstacles in the workspace. The four variants of PSO are namely PSO-W, PSO-C, qPSO-W and qPSO-C where the latter two are hybrid version of the first two algorithms. The hybrid PSO is created by incorporating quadratic approximation operator (QA) alongside with velocity update routine in updating particles' position. The computational result reveals that PSO-W yields better performance in terms of convergence speed and accuracy. Load balancing algorithms on Video on Demand systems very significantly on considering different requests which may differ in structure as I/O intensive or CPU/Memory intensive, due to which the performance of the algorithm varies. However, statistically a large number of tasks are I/O intensive rather than CPU or memory intensive. CPU requirements of the system are minimum. The goal of this proposed algorithm is to balance loads evenly across the entire cluster factoring in the CPU as well as I/O requirements, while at the same time trying to achieve an optimum completion time for each task. An assumption is made to not consider pre-emptive migration of tasks. A transaction in our model can be defined as the time difference in the acceptance and fulfillment of requirements of a task by the system. Task requirements in general for a video-on-demand system are video files stored on the server end on a secondary storage device which is to be streamed continuously to the request initiator. The proposed algorithm called CPU-Memory-I/O Load Balancing (CMIOLB) is compared to a couple of other scheduling and allocation policies. We have mathematically shown that the proposed algorithm performs better than the other policies. In this study, PV powered drip irrigation system was controlled and monitored remotely with soil moisture sensors. A centrifugal pump with brushless DC motor has been utilized for the purpose of transferring of water to drip irrigation system. Energy requirement of centrifugal pump system has been met from solar panels and batteries. Voltage and current of batteries, motor and solar panels were monitored with software developed by authors with C# language in Visual Studio.Net 2008 editor. However volumetric water content of soil was monitored with software and controlled solenoid valves depending on data of sensors. Each unit has PV powered wireless module and antenna for communicate main server. The software allows monitoring and controlling remote PC through internet. Designed system has been applied for dwarf cherry tree of 1000 pieces planted to an area of 8 decares in Zile District of Tokat Province of Turkey. This designed and implemented site-specific irrigation was aim to monitor and control soil moisture remotely, prevent excessive water usage with non-regularity irrigation, moisture stress of trees, erosion and salification, provided less growth of weeds and decreased the amount of water utilized by these weeds. One of the major difficulties in business and economics is to manage data accurately. Currently, approaches in stock forecasting have been rough set theory, time series and artificial neural networks. One of the most popular types of neural network has been the back propagation Neural Network. However, there are still problems with these models and there is a hidden layer. New models-Partially Connected Neural Evolutionary model (PARCONE) can correct this flaw. Parcone for the discovery of the more hidden knowledge stored within the historic time series data are needed in order to deal with the timely trading problem, i.e., buy, hold or sell within a time constraint. This paper presents a parallel implementation of a new permutation generation method. This permutation generation method is based on the starter sets for listing all the n ! permutations. The sequential algorithm is developed and parallelized for parallel computing by integrating with Message Passing Interface (MPI) libraries. The performance of the parallel algorithms is presented to demonstrate the validation of the works. The triple-band inset feed rectangular microstrip antenna for Worldwide interoperability for Microwave Access (WiMAX) application is proposed, fabricated and measured. In order to obtain the desired triple-band, the two slots are embedded in one of the radiating edges of the rectangular patch to excite the extra resonant frequencies. The placement and length of the slots are made to achieve good impedance matching at all three resonant frequencies. The antenna is optimized by ANSOFT HFSS and a prototype is fabricated according to the optimized parameters values. The simulated and measured results show that the antenna is of the triple-band characteristic for WiMAX applications. This paper presents an ongoing project that determines how much children in Yemen appreciate digital storytelling. The study is initiated in response to the importance of knowledge in the digital age. Specifically, this study is part of encouragements towards the implementation of eLearning, in which self-paced and active learning is supported. This paper starts with the issues of current state of the art of knowledge dissemination in electronic form. The activities involved are explained as part of the methodologies. Also, data have been collected through qualitative approaches. Finally some discussions follow and conclude the paper. It was found that the children appreciate the digital storytelling very much. Web interactive multimedia system, an information and communication system, is introduced and its attributes are outlined. The system consists of several features such as chat, audio, video, polling, whiteboard and desktop sharing and provides students with the opportunity of real time collaboration. When used in a university blended learning environment, it enables immediate feedback between participants across physical space. In this paper, a secure BSS-based cryptosystem has been proposed for encryption of images. Conventional BSS-based encryption scheme is not secure especially against differential attack. The main reason is due to the fixed key which is applied to encrypt all images. Here we have exploited the AES key expansion to produce a different key for transmitting each confidential image. Our simulations and also calculations based on correlation coefficient confirm that the proposed algorithm has effectively enhanced the level of security. The paper addresses the adaptive multi-user resource allocation for a distributed multi-carrier DS-CDMA network. The real packet throughput, which turns out to be noncovex and nondifferentiable, is considered to measure the system performance. A new non-cooperative power control game is proposed in which each user seeks to optimally choose the transmit power, subchannels and modulation size in order to minimize its own transmit power subject to the transmit power constraint and quality-of-service (QoS) requirement. As the peculiar status of food distribution center in grain logistics supply chain, we optimize distribution routes, so as to get the minimum cost. In order to meet the requirement that the frequency of delivery is an integer, a math model is builded, which is established integer programming that based on linear programming and MATLAB. An example is given which manifest that the proposed method is effective and can find the optional solution quickly. The Karhunen-loeve transform expresses image data in terms of number of eigen vectors depending upon the dimension of an image. In color images, there is a large data redundancy available. Thus there is a scope for redundancy minimization and subsequent image data compression. This paper presents a technique to estimate the optimum number of the eigen vectors required for reconstructing the original image without a visible compromise on image quality. The MSE and PSNR are used as benchmarking parameters for reconstruction while 2% loss of energy is considered as threshold for the reconstruction as human visual system can not respond less than 2% loss of energy incident on human retina. This experiment was carried out on many real life images and it has been observed that around 20% eigen vectors of the total vectors are enough to reconstruct original image with more than 40db PSNR in most of the database images. The technique is found to reduce the number of eigen vectors required for reconstruction with 40 db PSNR, to less than 50% in case of most of the real life color images and specially for video scenes where there is a minimal difference between the successive frames of a video scene. Job sequencing problem is to find sequence of jobs in such way that when execute it should give maximum profit. New Job Sequencing algorithm covers the aspect of simplification. Previous algorithm [1] designed for Job Sequencing is very complex, hard to understand and hard to implement. New Job Sequencing algorithm Removes Disadvantage of standard algorithm. It is taking same time complexity and space complexity as that of standard algorithm. A modified printed circular shaped monopole antenna with tapered base has been proposed and optimized for UWB applications. The antenna structure is composed of a circular patch with tapered base and a partial ground plane with a quarter-circle edges on top of two sides. The result shows that the antenna achieves an impedance bandwidth ( V S W R ≤ 2 ) of 118.82 % (2.75 to 10.8 GHz) and ( V S W R ≤ 2.6 ) of 151.65% (2.75 to 20 GHz). A stable radiation pattern makes the proposed antenna suitable for being used in wireless communication. Detailed of the proposed antenna design is presented and discussed. Data mining technology has been used widely for business, banking, and telecommunication purposes. Lately it is not uncommon this technology used for other fields. This paper outline the novel knowledge discovery process model known as hybrid model designed purposely for educational environment. This hybrid model consists of six steps; understanding of educational domain problem, understanding educational data, educational data pre-processing, educational data mining, evaluation of the discovered knowledge and use of the discovered knowledge. The outcome of this paper shows the new method of discovering new knowledge from educational data. Corner detection is an important process before control points detection. It is to ensure the accurateness of detected control points. Since there is a lot of corner detection methods developed time by time, this paper studied three most competent methods and compared them. Efficiency of corner detector can be evaluated using its criteria, which also discussed in this paper. The result may guide to the best corner detector for outline image. Pronunciation variation is a major obstacle in improving the performance of Arabic automatic speech recognition (ASR) systems. This phenomenon alters the pronunciation spelling of words beyond their listed forms in the phonetic dictionary, leading to a number of out of vocabulary (OOV) word forms. This paper presents a direct data-driven approach to model pronunciation variations, in which the pronunciation variants are distilled from the training speech. The proposed method is based on adding the pronunciation variants to the ASR pronunciation dictionary as well as to the language model. We started with a baseline Arabic speech recognition system using Carnegie Mellon University (CMU) Sphinx3 speech recognition engine. The baseline is based on a 5.4 hour speech corpus of Modern Standard Arabic (MSA) broadcast news, with a phonetic dictionary of 14,234 canonical pronunciations. The baseline system achieves a WER of 13.39%. The proposed method identifies the variations in the phonetic transcription of the spoken words. The phonemic variants of words are then filtered and added with distinctive letter spellings in an expanded phonetic dictionary. In our experiment, 554 variants were added to the basic phonetic dictionary as new words. The artificially added words are used together with their sentences in the language model as well. Our results show that while the expanded dictionary alone did not add appreciable improvements, the WER is reduced by 2.04 % when the variants are considered within the language model. Lightweight fault localization compares program spectra in passing runs and failing runs, and computes the likelihood of program entities containing faults. Aspect-Oriented Programming (AOP) is applied in this paper to monitor program execution and capture program semantics-method call relationships. Edge-weighted method call graph (EWMCG) which represents successful program behavior is produced through analyzing passing spectra. And EWMCG representing failing program behavior is produced through analyzing failing spectra. Based on the idea that the greater the edge call probability difference is, the higher the edge suspiciousness is, we rank edges according to suspiciousness. Preliminary experimental results show that, compared with traditional instrumenting way to collect program spectra, AOP can reduce more than tens of times of overhead. Empirical studies prove that our fault localization has the potential to be helpful in localizing faults. Programmers only need to examine 5.92%∼46.6% of code using our approach. This research aims at reducing power loss in transformer, which is concerned as an enormous effect on the economics of electrical network operating. Hence changing transformer tap is proved to be an effective way to modify performance of transformer itself. A method is proposed for selecting a right tap, which is based on the optimization principles of active power loss minimization and reactive power loss minimization. The results shown that the proposed method possesses the excellent effect on energy saving and power losses reducing. In the last part of this paper, an example is given to verify the feasibility calculation of energy saving. This paper will look into the utilization of electromyogram (EMG) signal for control of a robotic gripper. EMG signal is acquired from flexor carpi ulnaris and flexor carpi radialis of the forearm. These are the muscles that responsible for wrist flexion and extension that brought to opening and closing of the hand. To link this with the control of robotic gripper, the EMG signal from the muscles will first be classified into two distinct groups which represents ‘hand open’ and ‘hand close’ gesture. In this study, EMG data corresponds to hand opening and closing was recorded from five subjects. Feature of EMG signal were extracted using mean absolute value (MAV) method. The feature vector is then classified into the two distinct movement using Support Vector Machine (SVM). Write operation or the addition of storaging nodes and the exit will affect the consistency of the datacopy. How to select the best copy from multiple copies of data to best maximize the speed of accessing data resources is also a key issue of maintaining datacopy. This paper has summarized State of the field and has proposed datacopy selection strategy based on gray prediction after analyzing the basis of selecting copies. The simulation results show that it has a good effect in cloud storage. Replicas consistency strategies is an important aspect of ensuring the data is available. After Analyzing and summarizing relevant academic research, this paper has proposed the replicas consistency strategies based on optimization data copy chain, has created the replicas chain and maintained the replicas chain, and has analyzed the process of maintaining replicas chain. The simulation results show that the strategy can effectively reduce network redundancy and can timely update all replicas data of target data. This system main use Internet technology and GPRS communication, through based on MapInfo urban municipal administration geography information management pattern chord video information gathering route of transmission, Used the embedded intelligent control method, the success has designed based on the Internet, the GPRS urban street light illumination long-distance intelligent control system, Used the integration monitor terminal to carry on the network, used the dynamic analysis technology to the lighting attachment uninterrupted monitoring, integrated the advanced network turning on technology, Uses the stratification structure construction super supervisory system. This system in the Jiangsu Province Yixingshi wetland park practical application, realizes effectively to street light's long-distance monitoring. In this paper is presented position and velocity control simulation of a double-sided, 6/4 poled, 3 phased, 8 A, 24V, 250 W and 250 N pull force Linear Switched Reluctance Motor (LSRM) at elevator door load. Reference velocity is variable depended to position and time. The velocity of translator was controlled versus to position by Fuzzy Logic Control (FLC) and PI control techniques. Velocity of translator separately compared the simulation results PI and FLC techniques. While the door decelerating with FLC, velocity error is more than PI control. But, this is more useful than PI control. Because door closes is more little time than PI. According to the characteristics of push-mode supply chain, its operating mechanisms is analyzed and the dynamics model of it was established . Then the simulation analysis of systemic behavior of push-mode supply chain was conducted under the circumstances of disturbance of market. At the same time, the simulation of ordering cycle and target inventory's influence to the behavior of push-mode supply chain was run. The results indicate that: for push-mode supply chain, the delivery ratio of it can be increased only through adjusting order cycle time, not through changing target inventory. Policy description languages (PDL) are the basis of policy-driven exception handling for Service-based processes. Due to the lack of existing policy languages representing capacities for exception handling, this paper presents WS-Policy4SPEH, a new PDL for exception handling in Service-based processes. Based on the Web Services Policy Framework, this language extended the specifications of effects in ECA rules; defined a variety of action patterns that support in details the exception handling and flexibly specified the return modes and the exception propagation after exception handling. The paper adopted XML as a meta-language for specifying WS-Policy4SPEH, with a reasonable scalability. This paper presents self-localization module for mobile robot that travels around indoor environments. Our module uses the only one sensor, a single camera looking up the ceiling. There is no efficient enough SLAM (Simultaneous Localization And Mapping) algorithm working on embedded system. The initial difficulty of vision based SLAM is computational complexity to acquire reliable feature on their algorithm. To reduce the computational complexity, we use the ceiling segmentation to extract line features of ceiling area. Line features are extracted from the boundaries between the ceiling and walls. Extended Kalman Filter is used to estimate the pose of a robot and build the ceiling map with line features. The experiment is practiced in our indoor test bed and the proposed algorithm is proved by the experimental results. The lagging behind of tourism planning and tourism information management seriously delays the tourism development in China. Setting up the tourism planning and management information system is beneficial to the comprehensive managing and programming of tourist areas. Based on the discussion of tourism planning and management information system development modes, the paper puts forward the overall structure and main functions of the system, which determines the design method for tourist area data base, realizing the connection between the spatial data base and relational data base and graphic display of informational data. Combining with the Component based geographic information system Map Objects, functions like information search, statistics and analysis, basic graphs operation, spatial analysis of tourist area are designed on the VB platform. It also analyzes key technology of data bases connection and special map drawing and describes the kernel codes. After commissioning, the system is running normally, which can be widely used in planning and managing a variety of tourism resources. Searching on the World Wide Web is the second most frequent operation on the Web after e-mail [1]. Page ranking relates to searching through a group of web pages or other similar cross referenced resources. A Link Analysis Ranking algorithm proceeds to extracting the hyperlinks between the collection of Web pages and produces a weight for each Web page. This paper describes HITS algorithm and techniques developed for reducing the query time cost of HITS ranking algorithm. The aim of this paper is to develop a flexible methodology to analyze the effectiveness of different variables on various dependent variables which all are times series. This survey shows how to use a time series regression on one of the most important and primary index (page views per visit) on Google analytic and in conjunction it shows how to use the most suitable data to gain a more accurate result. There are too many data available

This proceedings is from the nineteenth meeting since the founding of the ANNIE Conferences in 1991. The conference was held in St. Louis, MO, USA, and attracted over 100 papers internationally. Each paper was peer reviewed and revised before being included in this book. This front matter contains the table of contents Performance sensitivity resulting from system integration is a subject commonly left untreated in the system architecting and early systems engineering phases. Ambiguity in the physical architecture often leads system designers to ignore this emergent behavior even though it can greatly alter the intended system performance. New methods of probing integration sensitivity are being researched. These methods employ computationally intensive methods to produce a set of performance predictions based on design variable iterations. There are two shortcomings with this approach. First, the computational intensity of the process limits the capacity to explore a large number of iterations. Second, a concise and computationally simple method is needed to encode this data and present it to system designers. In this paper, an artificial neural network is proposed to address both of these issues. The multilayer perceptron neural network architecture is developed based on a limited available data set. The results obtained are promising to support RF system development. In this paper we explore the chaos synchronization in a coupled non-homogeneous oscillating system. This is characterized by the loss of exponential instability in the traverse direction through system interaction. Additionally, the dependence of the synchronization properties of the system with respect to the intensity of the coupling constant is examined and discussed. In this paper, we develop algorithms for calculation of fractal measures and characteristic exponents for modeling of a complex systems evolution represented through digitized chaotic signals. Using temporal localization along phase trajectories of a chaotic attractor reconstructed from nonlinear time series, we achieve the essential reduction of required computer resources that allows the nonlinear analysis algorithms to be realized even for higher-dimensional cases. The numerical simulations confirm reliability of the developed algorithms and its high efficiency. Virtual sensors are mathematical models that predict the readings of a sensor in a location currently without an operational sensor. Virtual sensors can be used to compensate for a failed sensor or as a framework for supporting mathematical decomposition of a model of a complex system. This study applies a novel genetic programming representation called a function stack to the problem of virtual sensor induction in a simple thermal system. Real-valued function stacks are introduced in this study. The thermal system modeled is a heat exchanger. Function stacks are found to be able to efficiently find compact and accurate models for each often sensors using the data from the other sensors. This study serves as proof-of-concept for using function stacks as a modeling technology for virtual sensors. Creating new knowledge through analysis of massive data sets brings about a profound positive impact on society. Data streams are created from a multitude of sources (e.g., sensors, models) and then are compiled into heterogeneous sets of information. The users of these data may be modelers who have specific requirements to update numerical models dynamically, through assimilation techniques. Assimilation is problematic because linear techniques, such as Kalman filters, are applied to nonlinear dynamics. We propose an innovative approach to ameliorate these problems and provide scalable algorithms whose computational complexity is much lower than with traditional methods. Our research uses support vector machines and other kernel methods for data mining (e.g., data thinning) to accomplish these tasks. Computational results on a free fall model were highly encouraging. In this paper, we expose a weakness of a secret key cipher based on pseudorandom number generation, which was previously described as high quality and passing various statistical tests (entropy, FIPS 140-2 annex C, Marsaglia tests). Random number generation is operated by one-dimensional, non-uniform cellular automata with rules of radius 2. We show that specific configurations of rule assignments generate suites with zero entropy. We propose a systematic construction that leads to such assignments, and compute the size of the weak key space. Finally, solutions to remedy this problem are envisioned and the possibility to discover additional issues is discussed. This work utilizes a novel Self-Organizing Map, called ParaSOM, that is an advancement of the traditional SOM. The ParaSOM is different from existing architectures in that it processes the entire input space in parallel. It also utilizes a feature called a cover region , in which individual neurons “cover” whole regions of the input space, and not just a single vector. The effectiveness of the cover region is represented by its cover value . Neurons in the ParaSOM network have an age attribute. This attribute is used in a fashion similar to the Fritzke networks, from which it is borrowed. The age is a counter, indicating how long a neuron has existed in the vicinity of either sufficiently dense or sparse inputs. In dense input, the age is incremented after each epoch; in sparse input, the age is decremented. The architecture also incorporates a growth component. When a neuron is situated in an area that is dense with inputs for a sufficient period of time, as determined by the age threshold, it is understood that the neuron is well placed, and that this region is a good place to add another neuron. Conversely, neurons existing in sufficiently sparse input areas can be removed from the network. These features, along with others, allow the ParaSOM to execute epochs at a faster rate than other architectures, as well as converge in fewer epochs, and provide better metrics for input space coverage. Recent events highlight the need for tools to anticipate threats posed by terrorists. Assessing these threats requires combining information from disparate data sources such as analytic models, simulations, historical data, sensor networks, and user judgments. These disparate data can be combined in a coherent, analytically defensible, and understandable manner using a Bayesian belief network (BBN). In this paper, we develop a BBN threat anticipatory model based on a deceptive reasoning algorithm using a network engineering process that treats the probability distributions of the BBN nodes within the broader context of the system development process. Beginning in 2010, the U.S. will require that all cargo loaded in passenger aircraft be inspected. This will require more efficient processing of cargo and will have a significant impact on the inspection protocols and business practices of government agencies and the airlines. In this paper, we conduct performance evaluation study for an aviation security cargo inspection queuing system for material flow and accountability. The overall performance of the aviation security cargo inspection system is computed, analyzed, and optimized for the different system dynamics. Various performance measures are considered such as system capacity, residual capacity, and throughput. These metrics are performance indicators of the system's ability to service current needs and response capacity to additional requests. The increased physical understanding resulting from execution of the queuing model utilizing these vetted performance measures will reduce the overall cost and shipping delays associated with the new inspection requirements. This paper proposes a self-organized kernel fuzzy clustering method based on the idea of self-organized dissimilarity between two objects, while considering the degree of sharing of common properties of the pair of objects for the obtained fuzzy clusters. Moreover, we propose a method for evaluation of an adaptable number of clusters using an idea of measuring the degree of agreement between the target similarity data and the restored similarity which consists of the result of the self-organized kernel fuzzy clustering model. We describe in this paper a new evolutionary method for the optimization of a modular neural network for multimodal biometry The proposed evolutionary method produces the best architecture of the modular neural network (number of modules, layers and neurons) and fuzzy inference systems (memberships functions and rules) as fuzzy integration methods. The integration of responses in the modular neural network is performed by using type-1 and type-2 fuzzy inference systems. The performance of a spread spectrum code division multiple access system depends on the correlation properties of the employed spreading codes. In order to suppress the multiple access interference among the competitive users of the channel it is desirable that, the cross-correlation values between spreading sequences should be as low as possible, and to achieve proper synchronization and to suppress inter-symbol interference the auto-correlation of every sequence should be as peaky as possible. In addition to these two requirements the spread spectrum multiple access communication requires large number of sequences to increase the channel capacity. In this paper we propose Barker like ternary sequences with ortho-normal odd-shift property, and are optimized using combinatorial optimization technique such as Hamming scan. The load-bearing capacity of pavement structures is a fundamental structural performance metric of transportation infrastructure networks in the context of safe and efficient movement of people and goods from one place to another. Non-destructive test (NDT) methods are typically employed to routinely evaluate the structural condition of pavement structures, their lifespan and the appropriate maintenance activities to be carried out. This involves computing the Young's modulus of each layer of the pavement structure through inverse analysis of acquired NDT data. Over the past two decades, soft computing techniques such as Artificial Neural Networks (ANNs), Genetic Algorithms (GAs), and Fuzzy Logic Approach (FLA) have been applied in numerous civil engineering fields for pattern recognition, function approximation, etc. This paper proposes the use of an Adaptive-Network-based Fuzzy Inference System (ANFIS) combined with Finite Element Modeling (FEM) for inverse analysis of multi-layered flexible pavement structures subjected to dynamic loading. Using the proposed approach, it will be possible for pavement engineers to characterize the non-linear, stress-dependent modulus of the pavement layers based on the NDT data in real time, identify the pavement defects, and better determine the appropriate rehabilitation strategy. The on-site earthquake early warning system (EEWS), as part of the total solution of seismic hazard mitigation, was under development to provide a series of time related parameters such as the magnitude of the earthquake, the time until strong shaking begins, and the seismic intensity of the shaking (peak ground acceleration). Interaction of different types of earthquake ground motion and variations in the elastic property of geological media throughout the propagation path result in a highly nonlinear function. We use neural networks to model these nonlinearities and develop learning techniques for the analysis of earthquake seismic signal. This warning system is designed to analyze the first-arrival from the three components of the earthquake signals in as little as 3 sec after first ground motion is felt at the sensors at a rate of 50 samples per second. Then the EEWS instantaneously provide a profile consists of a magnitude related estimates of damage parameters, such as time until peak ground acceleration (PGA) and maximum seismic intensity. The neural network based system is trained using seismogram data from more than 1000 earthquakes recorded in Taiwan. The proposed EEWS can be integrated with distributed networks for site-specific applications. By producing accurate and informative warnings, the system has the potential to significantly minimize the hazards caused by catastrophe earthquake ground motion. Advances in the application of X-ray computed tomography (CT) for evaluation of soil porosity have added a new research tool for investigating porosity features. Objectives of this study were to evaluate CT scan porosity images using fractal dimension and lacunarity and to relate these fractal properties to bulk core properties of soil saturated hydraulic conductivity and macroporosity. Forty intact samples taken at four depths were scanned at 7 mm distances throughout each core to provide eight scans per sample. CT-measured density from samples equilibrated to three soil water potentials was found to be fractal at a scale from 0.2 to 76 mm. Fractal lacunarity of CT-measured density was found to be a quadratic function of soil depth while fractal dimension was not correlated with depth. Fractal lacunarity of CT-measured density was significantly correlated with log-transformed saturated hydraulic conductivity (r = 0.66) and macroporosity (r = 0.74). Lacunarity was found to be more sensitive than fractal dimension in differentiating effects of soil depth. This study illustrates how X-ray CT images from soil cores can be evaluated using fractal analysis techniques to obtain parameters which correlate with core-scale soil physical properties. Many civil engineering problems, due to uncertain problem definitions are not suitable for conventional computer applications. Many such problems are now being tackled using Artificial Neural Network (ANN or NN) which operate analogous to that of biological nervous system. The catastrophic damage to life and property due to wind storms is experienced in many parts of the world including India, which has a long coast line. Also the demand for taller, lighter and more slender structures continues to increase, so does the importance of designing for wind-induced building motion. This has encouraged structural engineers to study the effect of wind induced oscillation on tall buildings. Therefore it is necessary to review computing techniques which are currently in use to determine the wind forces for along wind direction. This paper presents the use of ANN for determination of along wind response oftall buildings for wind loads as IS:875 (Part-3)-1987. This paper explores the feasibility of applying support vector regression (SVR) kernel-based supervised learning method to develop hot mix asphalt (HMA) dynamic modulus ( | E * | ) predictive models. SVR-based prediction models were developed using the latest comprehensive | E * | database that is available to the researchers. The SVR model predictions were compared with the existing regression-based prediction model which is employed in the Mechanistic-Empirical Pavement Design Guide (MEPDG). The SVR based | E * | models show better prediction accuracy compared to the existing regression models. The determination of optimal function and parameters for SVR algorithm is recommended to improve the prediction performance of SVR based | E * | models. Predicting travel time along arterials is a complex dynamic problem. Most complexity derives from traffic interruptions at signalized intersections, viewed as decision points with significant uncertainty. Accurate but costly and unsustainable prediction can be obtained using sensors and probe vehicles. This research presents a more sustainable approach that draws on advanced computational paradigms and easily available data, to predict travel time along urban arterials. The notion of state-space of roadway traffic and state-space neural networks (SSNN) are used to predict travel times both under time-invariant turn (TIVT) and time-variant turn (TVT) shares using basic traffic data easily collectable with current field hardware. X-ray computed tomography (CT) has been used to evaluate differences in structure for soils. Soil development under different ecological regions has been found to significantly alter soil structural properties. Objectives of this study were to evaluate CT scan porosity images using fractal dimension and lacunarity for Russian soils developed under meadow, forest and a forest-meadow transition zone. Thirty intact samples taken at two depths were scanned at 7 mm distances throughout each core to provide nine scans per sample. For moist soil samples (−10 kPa potential), the fractal dimension and lacunarity were statistically different ( P < 0.05 ) among ecosystem treatments. However for dry soil samples (<−3 MPa), only the fractal dimension was statistically different among treatments. Results of the study indicate that fractal dimension significantly ( P < 0.05 ) decreased with soil depth for both water potentials but lacunarity was not significantly affected by depth. Saturated hydraulic conductivity was found to be correlated with CT-measured macroporosity ( r = 0.69 ) and the slope of the lacunarity curve ( r = −0.53 ). Fractal analysis of CT images from soils offers a potential tool for evaluating soil macroporosity changes under different ecosystems. ANN with a back-propagation learning algorithm was developed to model the data importance at the Massachusetts Military Reservation site. In various testing trials, thirty-three back-propagation ANN models were developed, which excluded or included certain groundwater monitoring wells. These models were then used to investigate the minimum number of groundwater wells necessary to characterize the Demo 1 site accurately. The explosion of available sequence data necessitates the development of sophisticated machine learning tools with which to analyze them. This study investigates the effects of applying a model which simulates the evolution of a ring species to the training of side effect machines. A comparison is done between side effect machines evolved in the ring structure and side effect machines evolved using a standard evolutionary algorithm based on tournament selection. The side effect machines in this study also shift from a training model based on k-means clustering to one based on a k-nearest neighbor model. A parameter study was performed to investigate the impact of the division of training data into examples for nearest neighbor assessment and training cases. The parameter study demonstrated that parameter setting is important in the baseline runs but had little impact in the ring-optimization runs. The ring optimization technique was also found to exhibit substantially better and also more reliable training performance. The Sierpinski representation for real optimization problems permits the rapid location of diverse sets of optima. In this study we demonstrate the ability of the Multiple Optima Sierpinski Searcher(MOSS) to located nested features within a complex two-dimensional system. The Mandelbrot set is used as the target complex two-dimensional system. Minibrots (smaller instances of the Mandelbrot set) serve as the target feature. Search of the two-dimensional Mandelbrot set is expanded to a three-dimensional search problem by adding a scale parameter to the usual pair of Cartesian coordinates. A parameter setting study is performed and the MOSS algorithm is used to enumerate minibrots, including nested minibrots, demonstrating the ability of the system to located nested features within a complex system. This study builds on previous work that classifies evolutionary computation problems via graph-based taxonomic techniques. A new collection of graphs that permit the measurement of small population effects are employed as well as a new distance measure that incorporates information on the variability of problem hardness into the taxonomic process. The new set of graphs and improved distance measure on problems are tested on a diverse set of string-based optimization problems including two new types of problems: fragmentation and K-max. The familiar SAW, one-max, and royal road problems are also included. It is found that problem difficulty, although explicitly removed from the information used to classify the problems, is nevertheless detected by the taxonomic technique. The problems appearing in earlier studies are shown to retain their diversity of behavior, confirming that the improvements to the problem classification system did not degrade a valuable feature of the earlier system. This paper applies two techniques, hybridization and small population effects, to the problem of logic function induction. It also uses an efficient representation for genetic programming called a function stack. Function stacks are a directed acyclic graph representation used in place of the more common tree-structured representation. This study is the second exploring an algorithm for evolutionary computation called the blender algorithm which performs hybridization of many small populations. The blender algorithm is tested on the 3 and 4 variable parity problems. Confirming and sharpening earlier results on the use of small population sizes for the parity problem, it is demonstrated that subpopulation size and intervals between population mixing steps are critical parameters. The blender algorithm is found to perform well on the parity problem. Neighbor joining algorithms are a type of hierarchical clustering algorithm commonly used to construct “family trees” that form a visualization of how data are related to one another. This type of algorithm is fast but known not to be robust to the addition or deletion of single data points. This study uses an evolutionary algorithm to find sets of data for which the algorithm is maximally and minimally stable. A new distance measure between trees is introduced and used to design a fitness function that measures the stability of a neighbor joining algorithm on a data set. This yields a novel bootstrap test for the stability of a data set relative to any given neighbor joining algorithm. It is found that typical data is highly unstable, suggesting that neighbor-joining algorithms should only be used on data where it is natural to suspect an underlying hierarchical structure to data, such as gene sequences of related organisms. Grid robots have proven to be an effective modeling tool for artificial life research, providing a platform to evaluate methods of machine learning. Some of the most interesting behaviors found in artificial life problems are the co-evolutionary effects caused by two different virtual species interacting with each other. This paper further examines this phenomenon by applying an artificial geography on two evolving species of virtual robots using evolutionary algorithms for controllers. Graph Based Evolutionary Algorithms were applied to three versions of a simple controller for “painter” robots. The results of this study showed that even though the virtual robot behavior changed, the preferred graph is consistent with the best performing graphs for a simple string problem. This verifies that the class of grid robot problems can occupy multiple regions of a taxonomy of evolutionary computation problems and allows for a baseline for future grid robot experimentation. Graph Based Evolutionary Algorithms have been shown to provide taxonomical information on a variety of computational intelligence problems. This technique allows for differentiation between different problems, but it has not been used to examine the differences due to multiple representations of the same problem. This paper further investigates the use of Graph Based Evolutionary Algorithms to provide information about the effects of representation on evolutionary algorithm problems. This information can enable a priori selection of a method that provides better performance when applied to a problem with a similar representation and/or solution search space. This paper examines five optimization problems using three different representations: binary, gray coding, and real value. The impact of these representations is explored using their performance on graphs as taxonomical characters. This paper introduces MAS4EVO, a new multi-agent organizational model supporting the design and hybridization of evolutionary algorithms (EAs) including co-evolutionary genetic algorithms (CGAs). Representing EAs as an organizational multi-agent system allows dealing with simplicity, autonomy, modularity and robustness. It permits to explicit their characteristics in terms of topology, interaction and adaptation. MAS4EVO provides a complete framework for designing EAs, including a dedicated organizational model based on four specifications (structural, functional, dialogic and normative), allowing to fully describing EAs characteristics. MAS4EVO's utilization is demonstrated by the design of a cooperative and a competitive CGA. Their application using MAS4EVO's implementation, called DAFO (Distributed Agent Framework for Optimization) is illustrated on an emergent topology control problem in mobile hybrid ad hoc networks called injection network problem. Multiagent-based simulation using activation-inhibition, and positive feedback is useful to study the evolution of group-swarming. The group-swarming approach can help us to understand the pattern formation, both micro (local) and macro (global), that result in bacterial colonies, human-animal trails, crowd patterns, phylogenetic trees, and other biological patterns. The group-swarming approach (of randomly communicating with other groups to revise belief based on new information available), by preferential linking locally in a group and globally among different groups, mimics the process of epochal evolution and innovation advocated by Crutchfield, in which the groups assemble partial solutions that are metastable and eventually reach equilibrium. The individual groups correspond to sub-basins of approximately iso-fitness and are strongly or weakly connected to other sub-basins thus mapping genotype-to phenotype and phenotype to fitness. Substitution boxes (S-boxes) are important elements of many block ciphers. Classical S-boxes are usually represented by specially designed static tables, which are used today in current cryptographic standards, such as Data Encryption Standard (DES) [3] or Advanced Encryption Standard (AES) [4], but in the result of developing methods of cryptanalysis they do not ensure enough safety of ciphers. In this paper we propose a methodology to design new more sophisticated 6×4 S-boxes functionally equivalent to ones used in DES. We provide an exhaustive experimental analysis of the proposed Cellular Automata-based (CA-based) S-boxes in terms of non-linearity, autocorrelation, balance and strict avalanche criterion, and compare results with ones related to DES S-boxes. We show that the proposed CA-based S-boxes have cryptographic properties comparable or better than the classical S-box tables. The interesting feature of the proposed S-boxes is a dynamic flexible structure, fully functionally realized by Cellular Automata (CA). A dynamical structure of CA-based S-boxes provides a possibility to use them as dynamic S-boxes, what opens new perspectives in cryptography. Long term memory stores critical data for long periods of time. In this paper we show that the addition of long term memory grants agents playing the iterated prisoner's dilemma (IPD) a substantial competitive advantage. This paper extends previous work [1] in which IPD players utilized a limited subset of previous game actions to drive game-play. We introduce a novel representation of strategies for the IPD which consist of a pair of finite state machines - one which records long term memory into a set of scalar variables, and a second which drives actions based on the memory data. Control agents act in much the same way but do not have access to long term memories. In this paper we introduce a novel swarm intelligence approach, based in the artificial bee colony optimization algorithm (ABC), now designed specifically to solve constrained numerical optimization problems: The scout-behavior modified artificial bee colony (SM-ABC) algorithm. In SM-ABC, the behavior of the scout bee is modified as to get the capability to exploit the vicinity of the current best solution (food source). Also, the way to control the tolerance for equality constraints is altered. SM-ABC looks to improve the capabilities of ABC to find good solutions in problems with a high dimensionality and active constraints. The performance of SM-ABC is tested in 13 well-known benchmark problems found in the literature. A comparison is performed between the published results of the original ABC algorithm and SM-ABC. Finally, a performance comparison against algorithms from the state-of-the-art in bio-inspired constrained optimization is shown. The results suggest that SMABC is a promising heuristic to solve numerical constrained optimization problems. This paper evaluates different strategies for solving the problem of emission source localization in an environment monitored by a distributed wireless sensor network. Typical application scenarios in which this problem could arise include emergency response and military surveillance. A nonlinear least squares method is developed to model the problem of estimation of the emission source location and the intensity at the source. Three solution approaches are considered to solve the problem, namely, a least squares solver (LSQ), particle swarm optimization (PSO), and differential evolution (DE). On the estimation error performance metric, in most cases the LSQ and PSO solutions achieve about equally good quality results, better than that of the DE solution. On execution time performance, however, the PSO algorithm is found to consistently outperform LSQ, by up to a factor of 20. This is an important criterion for selection of algorithms for embedded applications such as in sensor networks. Finally, the paper remarks on further acceleration of the PSO solution using distributed processing and hardware techniques. This paper proposes a Sudoku puzzle solver using swarm intelligence (SI). Sudoku is an NP-Complete problem where the complexity increases greatly with puzzle size. Several algorithmic and heuristic approaches have been implemented to solve different levels of popular 9 × 9 grid puzzles. This study proposes the usage of swarm intelligence by simulating an artificial ant colony for efficiently solving Sudoku puzzles of varying sizes. Using an SI approach, a number of challenges are addressed, including development of effective heuristic functions, good communication approaches among ants, prevention of memory waste, and the escape from local optimums. The experiments show that the performance of our SI Sudoku solver outperforms existing ones. Also, this solver is not highly sensitive to different difficulty levels, and has the ability to always find a solution, if available, for large grid size puzzles (e.g., 100 × 100 grid). In this paper, we formulate an optimal weight design (OWD) problem of the double box culvert for a constrained allowable shearing stress of the sidewall, top wall and bottom wall by the slope-deflection method and solve it directly by keeping the constraints based on an improved genetic algorithm (GA). We discuss the efficiency between the proposed method and the traditional method. The Open Shortest Path First (OSPF) is a dynamic routing protocol in Internet Protocol (IP) networks. Specifically, it is a link-state routing protocol and falls into the group of interior gateway protocols, operating within an Autonomous System (AS). In this paper, we deal with OSPF area design problem which is also proved to be an NPhard optimization problem. The primary aim of this paper is to design an OSPF area while considering the objective of minimizing the cost of OSPF area. First, the OSPF area considered in this study is divided into 3 levels. The 1st is the backbone level which contains main office and the 2nd is the Area Border Router (ABR) level. Lastly, the 3 rd level is branch office area. Later, to solve this 3 leveled OSPF area model, a Priority-based Genetic Algorithm (priGA) is proposed. Finally, to show the applicability and the efficiency of the proposed approach, numerical experiments are performed. A large number of studies has applied a metaheuristic approach to a variety of combinatorial problems. One of the areas where many researchers have used metaheuristic approach is the human resource allocation problem in the tourism industry. In the tourism industry, minimizing costs for tour guides is one of the most important issues. However, there are many constraints to consider when applying a metaheuristic approach to solving this problem. The purpose of this study is to consider cost minimization of tour guides. While minimizing costs, tour guide language skills, tour knowledge, and intercity transportation costs related to the places where the assigned tour starts should be considered. Moreover, tourist language needs are often ignored in a real-world tour guide allocation. So, tourist language preferences should be satisfied as much as possible. Since dealing with many constraints can be difficult when applying optimum-seeking approaches, this study will apply a well-known metaheuristic approach, genetic algorithm, for solving a three-dimensional (tour, tour guide, and tourist) tour guide allocation problem. As a result, this study shows an optimum tour guide schedule satisfying tourist preferences for type of tour and languages by using multistage decision-based genetic algorithm. Through the Quay Crane (QC) scheduling process, planners need to find the sequence of ship clusters that each QC will serve and the time schedule for the service, while satisfying various constraints among ship clusters. This paper studies this QC scheduling problem considering interference between QCs, which will cause waste waiting time for QC utilities. We propose a multi-objective genetic algorithm to minimize the turn around time of the container ships and to balance the workloads among Yard Cranes (YCs) at the same time for this NP-complete combinatorial problem. Numerical experiments using practical data is performed to test the performance of the multi-objective genetic algorithm suggested in this study. Transportation planning (TP) is a well-known basic network model that can be generally defined as a problem to minimize a total delivery cost. However the concept of inventory is not included in a traditional TP model. These restrictions on this model profoundly affect the use of the TP model in the real world. In this paper, we formulate the two-stage transportation problem with inventory and exclusionary side constraints (esc-2ITP). In this model, one year is divided into several terms and the annual demands of delivery centers are satisfied for each term. This model includes the additional constraint in which simultaneous shipments between some plants are prohibited. In order to solve the problem, we propose an effective genetic algorithms (GA) method called the Boltzmann random key-based GA (Brk-GA). This paper describes a job-shop scheduling problem (JSP) of processing product subject to no delay time job and minimizing the holding cost. These are two objective models of the minimum delivery delay time and minimum holding cost. In this paper, we describe the model of the goal programming method which has the delivery time and the holding cost (JSPDH) by genetic algorithms (GA). The effectiveness of the proposed method is clarified by numerical experiments using benchmark problems for job-shop scheduling. The multi-objective route selection problem (m-RSP) is a hot research topic in the car navigation system (CNS) for ITS (Intelligent Transportation System). In this paper, we propose a two-stage genetic algorithm (tsGA) to solve it. The purpose of the proposed approach is to create enough Pareto-optimal routes with good distribution for the car driver depending on his/her preference. In the first stage of the proposed solution approach, the accurate route searching ability of Dijkstra algorithm and the exploration ability of Genetic algorithm (GA) are effectively combined together to find enough Pareto solutions that are the initial population of the second stage. In the second stage, we adopt route-based genetic algorithm to calculate more Pareto solutions. Solutions provided by the proposed approach are compared with the current research to show the effectiveness and practicability of the solution approach proposed. In recent years, rescheduling attracted considerable attention, motivated by both important practical issues and interesting research problems. In this paper we discuss a multi-objective rescheduling problem. A set of original jobs has been scheduled to minimize a given cost objective, and then several sets of new jobs arrive unexpectedly. The objective in the original schedule still needs to be minimized over all of the jobs. However, this will change the original schedule, reducing customer satisfaction and creating havoc with the original resource allocations. Thus, the tradeoff between the scheduling cost and the disruption cost must be considered in detail. We also propose a multi-objective evolutionary approach for solving this rescheduling problem. We use new representation method in the proposed algorithm. Advanced genetic operators adapted to the specific chromosome structure and the characteristics of the rescheduling problem are developed. Some practical test instances will demonstrate the effectiveness and efficiency of the proposed algorithm. The main characteristic of the problem is that it considers a synchronized environment. A scheduling problem is handled in a manufacturing system that is using uniform time bucket approach for synchronization. There are three main aspects of the problem. The first aspect is the allocation of manpower. The manpower levels are determined in order to maximize production rate. Then, cell loading issue is addressed for multiple cells. Finally, a product sequence is generated for each cell in order to minimize the number of periods where available manpower is exceeded. Genetic Algorithm (GA) is proposed to solve the problem. Two main approaches are developed and along with different cell loading strategies. Minimizing similarity among products during cell loading led to better product sequences in each cell. This research focuses on an algorithm that enables a robot to navigate through any unknown terrain autonomously without undergoing a collision with any obstacle. A foundation to the whole research has been given by the Idiotypic Algorithm and the dynamic equation of the vertebrate immune system proposed by Jerne. The dynamic equation chooses a winning antibody for any antigen based on its affinity toward the given antigen. A new concept called random antibody selection has been incorporated in the existing idiotypic algorithm. Unlike previous researches on the same subject, where a predefined set of antibodies are already available for the robot to choose from, the robot is not provided with all the perfect solutions. Based on the affinity of a few randomly selected antibodies, the winning antibody is chosen. In this case, the antigen is not necessarily a perfect match to neutralize the effects of the antigen, thereby making the algorithm more realistic. To prove the functionality of this new concept, a number of virtual environments were created with randomly placed obstacles and the path followed by the robot was simulated. It can be seen that the random antibody selection process functions efficiently. By adjusting a few parameters such as the diameter of the robot, or the multiplier value for the voltage supply to the wheels of the robot, the program generated for this research can be implemented on any robot of any size to function in environments of any size. We present an adaptation of the bacterial foraging optimization algorithm (inspired on bacteria moving in their environment looking for high-nutrient areas) to solve engineering design problems. This proposal simplifies the original algorithm, proposed for unconstrained optimization, as to adapt it to solve constrained problems in numerical search spaces. The modifications look to decrease the number of parameters used in the algorithm, adding a constraint-handling mechanism and improving the communication capabilities among bacteria. The approach is tested on some well-known engineering design problems and its performance is compared against state-of-the-art algorithms. Based on the obtained results, some conclusions are established and the future work is defined. Premature ventricular contraction (PVC), left bundle brunch block (LBBB), and right bundle branch block (RBBB) are the three cardiac arrhythmias which can lead to or indicate the risk of heart failure. The goal of this research is to suggest an alternative way to diagnosing any potential of arrhythmia even when no specific arrhythmia features are observed. We propose new approaches in locating the arrhythmia features: Attractive Random Walk Distribution (aRWD) and Attractive Gaussian Walk Distribution (aGWD). We call the process of extracting the normal neighbor rhythm (NNR) from electrocardiogram (ECG) data with aGWD and aRWD WALKING. The extracted NNR is analyzed with simple data point competition (SDC) technique. The morphology of NNR is then recorded in tables with exponential fraction scale. Information processing in the brain results from the spread and interaction of electrical and chemical signals within and among neurons. The equations that describe brain dynamics generally do not have analytical solutions. The recent expansion in the use of simulation tools in the field of neuroscience has been encouraged by the rapid growth of quantitative observations that both stimulate and constrain the formulation of new hypotheses of neuronal function. In our research we use the NEURON simulation environment as it is capable of efficient discrete event simulations of networks of spiking neurons, as well as hybrid simulations of nets whose elements include both artificial neurons and neuron models with membrane currents governed by voltage-gated ionic conductances. We studied the kinetics of sodium and potassium channels and how the respective currents are affected by different drugs. In 2008, there were over 100,000 newly reported cases of colon cancer, and 40,000 cases of rectal cancer in the United States. In order to minimize the number of deaths from these diseases, researchers have been striving to find a set of genes that can accurately characterize the correct prognosis for colorectal cancer. Working with a gene expression microarray dataset of about 55,000 genes, collected from 122 colorectal cancer patients, this research developed technology to identify an optimal set of features through several methods of feature selection. These methods included coarse feature reduction, fine feature selection, and classification using a Genetic Algorithm / Support Vector Machine (GA/SVM) hybrid. However, microarray data with dimensions such as these are feature-rich and case-poor, which can lead to dangers of overfitting. This research was successful in developing a feature reduction method that was able to suggest a set of genes with potential ties to colorectal cancer, provoking further investigation into this relationship. For the ANNIE 2008 conference we developed and preliminarily tested an alternative approach to the popular ensemble mixture used for solving complex adaptive system (CAS) problems (ref. 1), which we have termed the oracle. This approach does not use heuristic or “ad-hoc” methods to combine the results of the separate component models, but uses a quantitative error measure for the model output combinations. We believe the system has the advantage of being simpler to use than a standard mixture-of-experts approach. In this paper we extend the previous work to accommodate multiple input vectors per sample. Our objective is to build a two-view intelligent complex adaptive decision mechanism (CADM) for use in either mammography screening or diagnostic situations. Microarrays, which allow for the measurement of thousands of gene expression levels in parallel, have created a wealth of data not previously available to biologists along with new computational challenges. Microarray studies are characterized by a low sample number and high feature space with many features irrelevant to the problem being studied. This makes feature selection a necessary pre-processing step for many analyses, particularly classification. A Genetic Algorithm and Artificial Neural Network wrapper approach is implemented to find the highest scoring set of features for an ANN classifier. Each generation relies on the performance of a set of features trained on an ANN for fitness evaluation. A publically-available leukemia microarray data set (Golub et al., 1999), consisting of 25 AML and 47 ALL Leukemia samples, each with 7129 features, is used to evaluate this approach. Results show an increased performance of selected features over the classifier from Golub et al. 1999. The spherical self-organizing feature map (SSOFM) has previously been implemented for data visualization, three-dimensional (3D) freeform surface reconstruction, shape morphing and registration. This paper extends its application to cranial anthropometry. Current cephalometric evaluation techniques involve identifying cranial landmarks and establishing parameters of relative alignment between anatomical structures. These techniques are mostly two-dimensional while available 3D techniques manipulate a dense cloud of points or surface models acquired directly from CT scans. The proposed method adapted a previously developed SSOFM-morphing technique to create low-density tessellations of pre- and post-operative CT scans, both having identical nodal topologies. Cranial landmarks were identified and pre- and postoperative tessellated forms were compared to examine post-surgical cranial growth in craniosynostosis. It further proposes a framework for tissue characterization in forensic facial reconstruction. Both applications use the inherent nodal correspondence established during the shape metamorphosis operation. The paper demonstrates proof-of-concept of the technique and its potential in craniofacial reconstructive surgeries. In this paper we describe a Modular Neural Network (MNN) with fuzzy integration for face, fingerprint and voice recognition. The proposed MNN architecture defined in this paper consists of three modules; face, fingerprint and voice. Each of the mentioned modules is divided again into three sub-modules. The same information is used as input to train the sub modules. Once we have trained and tested the MNN modules, we proceed to integrate these modules with a fuzzy integrator. In this paper we demonstrate that using MNNs for face, fingerprint and voice recognition integrated with a fuzzy integrator is a good option to solve pattern recognition problems. Face recognition is an attractive biometric approach due to the ease in which photographs of the human face can be acquired and processed. The non-intrusive ability of surveillance equipment permits face recognition applications to be used in a myriad of environments. Despite decades of impressive research, face recognition still struggles with variations in illumination, pose and expression as well as spoofing challenges. In order to improve effectiveness, face recognition is often combined with other biometric modalities. An alternative to multimodal biometrics may lie in the exploitation of the hyperspectral imagery and the processing of contextual layers of information contained within these images. The use of context in a hierarchal and fused manner can lead to a more selective gallery. This approach is novel for hyperspectral face recognition and is expected to show improved efficiency, performance and robustness over classical recognition methodologies. In this work, more accurate facial expression recognition system is developed by proposing an enhanced algorithm in facial feature tracking and a novel feature extraction method. In this system, the selected facial feature points are tracked automatically from, the first frame to the last, using an enhanced cross correlation algorithm with adaptive window search. Based on action units, an appropriate feature selection differentiates between the expressions according to their temporal information. The use of principle component analysis reduces the less important information of feature matrix and accelerates the system's performance. The extracted feature matrix is then given to the K-nearest neighbor classifier with free parameter of K to classify the face expressions within the six basic emotions. The correct classification rate of this system is increased to 95.6%. This paper introduces a novel technique for estimating the age of a person from a digital image of the face. The age estimating technique proposed combines Active Appearance Models (AAMs) and machine learning methods, i.e. Artificial Neural Network (ANN) and Support Vector Regression (SVR), to improve the accuracy of human age estimation over the current state-of-the-art algorithms. In this method, characteristics of the face are codified into feature vectors by the use of a multi-factored Principle Components Analysis (PCA) as utilized by AAMs. The feature vectors are provided as input to the ANN for a binary group classification: youth and adult. A unique age estimation function is derived for each group using SVR of the feature vector. The proposed approach yields significant improvement in overall mean-absolute error (MAE), mean-absolute error per decade of life (MAE/D), and the Percent Error Cumulative Score (CS) against the baseline data corpus. Moments have been widely used for creating invariant features for image classification and object recognition problems. In this study, different moments that are extracted from a database of 1200 images are used for object classification. The images are obtained from 10 different objects, each of which had 120 images that are rotated in different angles with different lighting conditions. For performance analysis, geometric invariant moments, Zernike moments, Pseudo- Zernike moments, Tchebichef moments and statistical features of the objects are extracted from each image. 800 of the images (80 images from each object) were used in training and the remaining 400 images (40 images from each object) were used for performance testing. In the classification step Nearest Neighbor (NN) and Bayesian classifiers are used. The results from each moment are compared. Overall

Sponsored by the International Association of Computer Science and Information Technology (IACSIT) and the Singapore Institute of Electronics (SIE). MIMT 2010 aims at bringing together the researchers, scientists, engineers, and scholar students in all areas of Mechanical, Industrial, and Manufacturing Technologies, and provides an international forum for the dissemination of original research results, new ideas and practical development experiences which concentrate on both theory and practices. The conference focuses on the frontier topics in Mechanical, Industrial, and Manufacturing Technologies subjects. This front matter contains the table of contents The thickness of material is an important parameter between the state of plane stress and plane strain, and the fracture toughness value in two states is very different. For the facture toughness test, the minimum specimen thickness is set in many national standards. And the fracture toughness value in plane strain state is usually adopted as the material toughness, which is far from the actual material toughness curve. In actual project, mechanical member thickness is usual the middle thickness between the state of plane stress and plane strain. So the calculation results aren't in accordance with the test results. First, thickness effect on fracture toughness and plastic zone size is analyzed. Then using the relation of plastic zone size and thickness in fracture toughness test, the limited thickness of the plane stress state and plane strain state is decided. Based on the limited thickness and linear relation, the fracture toughness formula of arbitrary material thickness is put forward. And the plastic zone size of arbitrary material thickness is also presented using linear interpolations. It is well known that human body contains considerable kinetic energy when in motion, so it is ideal to exploit such kinetic energy to power portable electronics. This paper proposed a novel generator, with reasonable dimension and affordable weight, to harvest human body's kinetic energy and convert it to electricity for mobile electronic devices. The generator uses an eccentric rotor, made of permanent magnets, to ‘catch’ the human body's motion and to produce changing magnetic field, where the wire coils as the stator will generate current due to the electromagnetic effect. As a typical application, the generator can be worn on the wrist as the watch, in which case simulation results show that the generator, 40mm in diameter and 50g in weight, can produce 30mW during normal walking. When an operator first detects unusual and/or infrequent signals in an automation system over prolonged periods of time, however, the system seems to be ok. The operator need not do any thing, but must keep a certain level of attention to detect more serious signals for confirming the problems of the system. The ability to detect and track the following signals after the initial unusual signal is referred to as the extended vigilance. The purpose of this study was to develop a quantitative model for measuring the extended vigilance by fuzzy logic, which extends two-valued logic (“Yes” or “No” to determine hit or miss, correct rejection or false alarm) to multi-valued logic by membership functions of fuzzy sets. Then a fuzzy logical alarm system was developed for improving performance of extended vigilance in automation Supervisory task. The experimental results showed that the effect of the system is good for improving performance of extended vigilance. Discussion on optimized cost compensation and relevant incentives system has been carried out in this paper aiming at promoting private investment in public projects. Parameters have been optimized based on contracting and incentive theory, leading to the conclusion that dissymmetric information may weaken the strength and effect of incentive contracting, while the government profit gaining will debase the stimulation in turning fixed prices contracting to cost-price contracting. Feed structure of the NC rotary table was analyzed firstly. The dual worm-gear transmission mechanism was then employed to eliminate the clearance. The transfer function of the servo system was presented. According to the LuGre friction model, the nonlinear fuzzy sliding mode control was presented for the servo system to compensate the friction nonlinearity. Through fuzzy adjusting the switching gain, the sliding mode control compensation system achieved less buffeting characteristics. At last the proposed error compensation approach was employed to control the rotary axis of a NC rotary table. The result shows the effectiveness of method, which has a very important significance to improve the motion precision of the NC rotary table. A new two-factor method based on the probability and the fuzzy sets theory is used for the analysis of the dynamic response of fuzzy-random truss under the stationary stochastic excitation, in which the structural parameters are considered as fuzzy-random variables and the excitation adopted is a stationary random process ground acceleration in horizontal direction. After the fuzzy-random correlation function matrix of structural displacement response in time domain and the fuzzy-random mean square values of structural dynamic response in frequency domain are developed by using the two-factor method, fuzzy numerical characteristics of structural dynamic responses are finally derived. The effects of the uncertainty of the structural parameters on dynamic response are illustrated via an engineering example. Recently, Ultrasonic is used in welding precision part manufacturing. Ultra sonic vibration applies mechanical vibration to the welding parts. Using power supply that transmits 50Hz or 60Hz current to 20kHz or 40kHz Ultrasonic current, Transducer that changes electric energy to mechanical vibration energy, Booster that controls the amplitude of the transducer, Horn that transmits electric energ to the welding part and welds it. Transducer, Booster, Horn is needed to be designed and manufactured accurately because the shape, length, mass and etc effects the output frequency and vibration mode. Especially, Horn needs to be designed to have a wanted amplification which is made by generation a resonance for efficient Ultrasonic energy transmission. In the case of dissonance of natural frequency of Transducer, Horn, Booster, the Ultrasonic vibration, which is necessary for process, won't be transferred to the output of the Horn. So the resonance design of the Tool Horn is important. In this research, we ideally designed the Ultrasonic metal welding Horn by FEM analysis. In this paper, the authors have investigated the effects components commonality and uncertainty - namely lead time and machine breakdown, in a multi-stage dependent demand environment. The throughput of the finished products and production cycle time are examined for different experimental scenarios with reference to an existing manufacturing setting. The situations of the production lines are analyzed in WITNESS. Simulation models are developed, and these are verified and validated with the collected historical data. It is observed that inclusion of common components in the manufacturing system is generally beneficial over the non-commonality environment, especially i) in uncertain situations, ii) for long procurement lead time of components and iii) when the number of parts increase in the system. Impacts of machine breakdown on system outcomes are higher than that of the lead time variation. The combination of uncertain factors has more impact on outcomes compared to the individual factor. A simple knock detection method for spark ignition engines is proposed in this paper. The signal acquisition is done by an accelerometer screwed on the engine block. The statistics characteristics of the vibration signals are analyzed, and then a knock detection method based on kurtosis is proposed. The method can detect knock with low intensity while short data serial is used. In order to solve the problem of roller drawing efficiency for producing dyeing printing equipment enterprises, this paper proposed roll fast-mapping system. This system made the secondary development for AutoCAD, using VC + +6.0 as development platform, ObjectARX as the development tools. In this paper, authors first carried out analysis and research for features of roll, established the classification method of roll and the way of determining characteristic values. On this basis, proposed feature-driven mapping technology, and finally gived the system menu customized approach achieved the program fast-mapping, shortened the drawing cycle, improved drawing efficiency, increased the competitiveness of dyeing printing equipment production enterprises. Layer Steel Fiber Reinforced Rubber Concrete is a new type of pavement material. Base on optimized concrete mix design, the flexural tensile performance of Layer Steel Fiber Reinforced rubber concrete was studied. Detailed discussion was performed in the Flexural tensile properties compared with ordinary concrete, rubber concrete, layer steel fiber reinforced concrete. The enhanced toughness of pavement structure was analyzed using the experimental constitutive curve of this new pavement material. The results can be helpful for further study and practical application. A new type of mobile system used to get asymmetrical rotation for lunar rover was presented. The mobile system was mainly constructed by a double-half-revolution mechanism, which was composed of a first swiveling arm, a second swiveling arm and two striding rods. Static force model of the mechanics of this configuration was described. According to the kinematic analysis, the pose of the rover can be calculated. With the pose of the rover calculated, the normal forces between the wheel-legs and ground were simulated. From this simulation it's possible to determine whether the rover will slide, tip over or maintain its balance. Simulation results showed that the normal forces were affected by applying specific frictional coefficient. Enthalpy-difference method has been utilized in this paper to test and analyze Seasonal Energy Efficiency Ratio (SEER) of normal model air conditioner and two-compressor model air conditioner with same refrigeration ability. According to test data, and combining the weather data of 6 cities, the energy efficiency of each product has been gotten in this paper. It shows that the average energy saving rate and average cost saving rate of these six cities of two-compressor air conditioner of these six cities is 22.12% and 6.29%, respectively, when compared with air conditioner with constant rotate speed. The objective of this investigation was to provide a detailed evaluation of the heat affected zone properties of a high-strength pipeline steel. The X80 high-strength low-alloy microalloyed steel was supplied as a hot rolled plate with accelerated cooling. The four-wire tandem submerged arc welding process with different heat input was used to generate welded joints. The microstructure of the heat affected zone depended on heat input values. M/A constituent appeared in the microstructure of HAZ region for all of the specimens along the prior-austenite grain boundaries and between bainitic ferrite laths. Charpy impact specimens were notched in four locations: FL (fusion line), FL+1mm, FL+2mm and FL+3mm. The Charpy absorbed energy of specimens was assessed using Charpy impact testing at −50°C In recent times, enterprises are facing a time competition concurrence. Any enterprise which in the shortest possible time can deliver products which meet customers requirements can win many competitive advantages. Three dimensional concurrent engineering is an operation management method based on time competition. It expands concurrent engineering to the supply chain design and improves the operating performances. When elaborating the tradition house of quality there are some defects which occur. This paper proposes a quality functional deployment of three dimensional concurrent engineering by introducing an extended quality functional deployment. Through an extend house of quality, this research transforms customer requirements into product design, the process design and the supply chain design and reduces the time from new product design to product market. It then combines the Extend Quality Function Deployment with the three dimensional concurrent engineering in order to resolve the defects met when elaborating the tradition house of quality. This way, this research helps to satisfy the customer requirements, to improve product quality, to shorten the development cycle of product, to enhance customer response speed and to increase the competition capability of enterprises. We present aero engine multidisciplinary collaborative design and simulation technology based on Product Master Model to solve the multidisciplinary coupling problem in the development process. This paper mainly studies the modeling technique of Product Master Model. The research proposes the generalized and special definition of Product Master Model and studies its logical organization, its included geometric and non-geometric information and its modeling approach based on feature. It then examines the methodology and process by which develop a modeling tool based on UG/OPEN API to construct the Product Master Mode of blisk. The case illustrates the validity and feasibility of the modeling technique finally. This paper considers the hybrid flow-shop scheduling problem with multiprocessor tasks which has proven to be NP-hard problem. Due to complexity of the problem, we addressed a restricted simulated annealing (RSA) in which a deduced predecessor-successor relationship of jobs is constructed as a neighborhood search engine. The information of the deduced predecessor-successor relationship of jobs was dynamically updated in the process of SA. The RSA algorithm is experimented on the benchmark instances and compared with existing algorithms in the literature. The computational results show that the RSA algorithm yields very high quality solutions on the same benchmark instances, especially for large problems. The vibration signal from the initial fault of rolling element bearing is characterized by short time impacts, which is weak in energy and buried in the surrounding noise. This feature makes traditional envelope analysis method often disturbed in application. In this paper, a scheme is introduced, which uses autoregressive model preprocessing the failure data and thereby relatively enhances the transient impact in the failure signal. Subsequently, the self-adapting complex Morlet wavelets envelope analysis method based on maximizing kurtosis criterion is done, then, a good transient impact is extracted from the preprocessed signal. This approach avoids the deficiency of traditional envelope needing to set centre frequency and envelope bandwidth manually. Experiments verify the feasibility and effectiveness of the introduced scheme. In this paper, a new approach based on independent component analysis (ICA) to against interference while being in the envelope analysis of rolling element bearing is proposed. It can remove the disturbance from the mixed vibration signals according to the difference of vibration sources. Brief introductions about the theories of ICA and envelope analysis are also presented. The test results verified the validity of the proposed approach. The power plants are classified by the type of fuel and the type of operating condition. The most of the gas turbine power plants are usually operated under DSS (Daily Start-up and Shutdown) mode. To find out the root causes of the turbine failure, the study and inspection were performed in the plant. Based on the analysis, there are some serious damages on gas turbines generator rotor windings. The basic causes of the damage are thermal growth and abrasion. The damages occurred from squared type winding, retaining ring insulation difference, and short-turn. We use the ABAQUS program to analysis the problem for the damage and show how to improve. Reinforcement learning is an important method of machine learning. This paper using the graph theory to express varieties of knowledge points, which their's relationship is expressed by the graph of topological graph. Applied the Technology of association rule Recommendation to deal with the relationship between these knowledge points, give the corresponding of the recommendation work flow chart. In the paper data tables used to store the knowledge points, the algorithm to demonstrate the technical of association rule Recommendation feasibility and rationality. This paper is based on the two recommendations: the Content-based Recommendation and the Collaborative Filtering Recommendation into a hybrid recommendation. The paper combined with the two algorithms recommendations characteristics, given the basic flow chart of hybrid filter. The experimental date used to analyze and evaluate the beneficiation of the hybrid recommendation. Finally, the mean absolute error to illustrate the recommendation method is reasonable. Made the information of the system E-Learning is better to recommend. Ultrasonic energy is used in plastics welding, metal welding, drilling and lots of processing fields. Because of the recent miniaturization and light weighting of electronic parts and mechanic parts, these days we need a better welding method, which is the Ultrasonic metal welding. Which is a more accurate, more minimized welding method than before. Ultrasonic metal welding machine consist of a Power Supply that changes a 50 ∼ 60Hz electrical power to a 20,000hz ∼ 40,000hz electrical energy, a Transducer that changes electric energy to mechanical vibration energy, a Booster that reduce or amplifies the amplitude of the Transducer, a Horn that welds workpieces by transmitting vibration energy. The Transducer, Booster, Horn has to be designed and made very accurately because the shape, length, mass and etc effects the resonant frequencies and vibration mode. In this research, to design the Transducer and the Horn, we decided the size by the vibration equation, calculated and analyzed the natural frequency by the modal analysis and harmonic analysis. Using Ansys that is analysis program. In allusion to the automation of the art of assembling some shafts and pins of hubcap gear-boxes by pressing, a special industrial robot controller based on PROFI-BUS is introduced in this paper. Based on the introduction of the process of assembling shafts and pins of hubcap gear-boxes by pressing, the paper describes the structure and the characteristics of the robot. Further, the paper emphatically analyses the controller based on PROFI-BUS, including the design ideas and the characteristics of the hardware and the software. The property of the bottom measurement and the calculate method of bottom subside is simply introduced. As for the problems about measurement exiting in verification regulation of vertical metal tank capacity, a new putting-into-type liquid level meter method is presented, based on analysis of several resolvable methods. The method can measure exactly point deformation values of the tank bottom and improve the verification precision. An innovative, non polluting hybrid rotary prime mover is proposed for automotive transportation and stationary power plants. This is speculated to be run by compressed air and electromagnetism powered by a stationary battery which is charged by SPVC (Solar Photo Voltaic Cell) and onboard wind turbines. The working principle of the engine and the energy balance are also presented. Future work and innovations are also envisaged. This paper deals with the optimization of the cutting variables which are cutting speed (V c ), feed rate (f), pressure (P) and flow rate (Q) of high pressure coolant (HPC) to obtain improved machining performances in turning AISI-4320 steel by uncoated carbide insert. An experimental study along with predictive models of cutting temperature (θ), chip reduction co-efficient (ξ) and surface roughness (R a ) has been carried out under response surface methodology (RSM). Multi-objective optimization has been carried out based on genetic algorithm (GA). Two conflicting objectives, minimizing cutting temperature and cutting force are simultaneously optimized against the constraint of surface roughness being less than 3 µm. The results show that θ, ξ and R a can be well estimated through the models. Optimizing the models also returns a pareto optimality chart which returns optimized cutting variables. The Working principle of VAWT (vertical axis wind turbine) and calculation method of wind energy utilization efficiency were interpreted. Partial integration method was used to analyze and calculate the relationship between the power of three-leaf structural VAWT and the size of the blades structure, which provides an effective method of fundamental analysis for its structural design. To resolve the issues of wind tracing and constant rotation speed control, an embedded control system based on PIC16F877A MCU was designed. Using angle sensors, temperature sensors, speed sensors, wind speed sensors and battery power monitoring system and so forth, achieves the global control for this VAWT. 4C theory is presented in the context of the demand, and the pursuit of customer satisfaction stands top priority. Compared with the theory of 4P and product-oriented, customer-oriented theory of 4C has been great progress and development, 4C strategy widely used by corporate marketing strategies. With the continuous deepening of the practice, the importance of value highlight day by day, prompting companies to develop marketing Countermeasures 4C and it must be onto a new level. On this basis, this paper proposes a view that using 4C marketing countermeasures create perceived value for the customer, and it takes machinery manufacturing industry as an object to build empirical structural equation model and to verify and obtain a conclusion that there is a significant positive correlation on marketing countermeasures to the perceived value's upgrading under driven factors- gap and customer satisfaction. The rapid development of technology makes the disparity between the machinery industries increasingly apparent. The theory of the current marketing opportunities with the core of differentiation is not enough to help machinery industry grasp the chance of marketing. This paper understand perceived value using the core of disparity, and propose the theoretical framework of marketing opportunities based on the perceived value, combining the marketing opportunities, perceived disparity, satisfaction and perceived value effectively, and then verified the relation through the empirical relationship between them, improve the theoretical framework, point out the new direction for the machinery industry to seek marketing opportunities. Differentiated benefits is the essence of prodduct, with the demand-led industrial economy going into recession, it is facing challenges about product positioning formed by satisfying demand. In this paper, based on the current marketing theory and practice, analysized the product value and differentiated benefits in-depth, re-built the positioning of the product differentiated benefits model, the model indicated the relationship among the product value, the differentiated benefits and the satisfaction, and then tested the reasonable of this model by structural equation modeling. The dynamic balancing optimization of the slider-crank mechanism in vertical sheer is very complicated. If the other function indexes is satisfied, it became the goal of optimum to make the working device high speed, high efficiency and smooth operation. The virtual prototype of vertical sheer is built using software ADAMS, and the matching blocks of vertical sheer are parameterized. Through optimization, the optimal angle and mass are gotten, which solve effectively the operating problem of the vertical sheer, such as motor overheat, lower rotation speed, and unstable running, realize the high speed and high efficiency. The analytical method of solving conventionally dynamic balancing of slider-crank mechanism is also introduced at the same time. Through comparing two methods, the method based on ADAMS is more accurate, more efficient. Quality is no longer a target, but a process. Almost all establishments famous for quality have not yet achieved perfection. With advances in Industrial Engineering, quality is no longer a domain of the well stocked but has become a necessity for every industrial unit to prevail. This paper aims to ease its understanding and help organizations handicapped in terms of size and manpower implement overall quality in a simple, easy and effective way. This paper is to act as a handbook for those aiming to increase the productivity, visibility and profitability of their respective set - ups. The paper deals with highlighting 5 key areas where the implementation of quality yields a rapid increase in the overall quality index of the company. The uniqueness of this approach is that it is appropriate for all industries and services. Laser rapid manufacturing is a state-of-the-art technology, which is the combination of rapid prototyping and laser cladding. This technology introduces a substantially complicated manufacturing process in that too many factors linked together influence this procedure. Accordingly, the relative experiments and analyses need to be performed for ascertaining the influence law of these factors on the process, which is the key to optimize this forming process and improve the quality of as-deposited metal parts. Among these factors, the substrate preheating temperature is an important one that affects the evolution of microstructure by changing the temperature gradient. Consequently, it is necessary to master the influence law of preheating temperature on composition segregation and microstructure morphology. Based on the experiments, the proper process system of substrate preheating can be concluded in terms of the relative material, which is the key to fabricate high-quality and low-defect nickel-based metal parts. The present work deals with experimental investigation in the effect of MQL jet on various work material and cutting tool with respect to different responses. The results include significant reduction in temperature, force, dimensional deviation, surface roughness and tool wear rate by MQL. So, it can be concluded that considering all responses MQL for medium carbon steel shows better reduction when using uncoated carbide SNMM insert and on the other hand for the case of uncoated carbide SNMG insert MQL for alloy steel AISI 4320 is most effective. Elastomers, in particular rubbers, are used in a wide variety of products ranging from rubber hoses, isolation bearings, and shock absorbers to tires. Rubber has good properties and is thermal and electrical resistant. We used carbon nanotube in rubber and modeled this composite with ABAQUS software. Because of hyperelastic behavior of rubber we had to use a strain energy function for nanocomposites modeling. We tested a sample of rubber and gained uniaxial, biaxial and planar test data and then used this data to get a good strain energy function. Mooney-Rivlin form, Neo-Hookean form, Ogden form, Polynomial form, reduced polynomial form, Van der Waals form and etc, are some methods to get strain function energy. Modulus of elasticity and Poisson ratio and some other mechanical properties gained for a representative volume element (RVE) of composite in this work. We also considered rubber as an elastic material and gained mechanical properties of composite and then compared result for elastic and hyperelastic rubber matrix together This paper describes a study of three-dimensional vibration characteristics of functionally graded super-elliptical plates with different boundary conditions. The analysis is based on the three-dimensional small-strain, linear and elasticity theory. The Ritz method is applied to derive the frequency equation. The triplicate Chebyshev polynomial series form the backbones of the admissible functions, as modified by a characteristic boundary function to ensure the satisfaction of geometric boundary conditions of the plate. The accuracy of these results is verified by appropriate convergence studies and checked with the available literature as well as the 3-D theory. This paper proposes a method of enabling direct teaching and playback, data simplification employing Douglas-Peucker algorithm (DPA), and the repulsive direction vector for reducing the errors between the reference and teaching data. This upcoming technique associated with human-robot cooperation is introduced as a concept of an automated robotic polishing system. By virtue of this robotic challenge, dependency on labor-saving efforts put automation in the cutting edge of devices for surface finishing processes such as polishing. Realizing the proposed algorithm, the optimal teaching point generation algorithm for the robotic polishing process is presented through the experiments. The paper focuses on a spatial rotation three Degree of Freedom (DOF) 4-SPS-S parallel robot mechanism, which has four SPS Active Legs and one passive constraining leg. The geometric model of the robot mechanism is introduced, and then velocity mapping equation and Jacobian matrix for the mechanism are developed. Based on principle of virtual work and sub-structure synthesis method, stiffness analysis model is established for the mechanism. Through orthogonal transformation of the stiffness matrix and diagonalizing the stiffness matrix, the mechanism's main stiffness indexes on 6 directions and directions along which max or mini stiffness occur are derived, and the distribution of main stiffness values of various directions over the entire workspace is disclosed. This paper provides theoretical foundations for engineering design and application for this class of parallel robot mechanism. The screw theory is adopted for the kinematic performance analysis of a fully-symmetrical 5-5R parallel mechanism firstly. Then the limb singularity analysis by using reciprocal screw theory is presented. Two cases of limb singular configurations are found for this parallel mechanism. When three parallel axes of rotating joints are coplanar or the plane determined by two intersecting axes is perpendicular to the base plane, the limb singular configurations will occur. The determination of singular configurations is critical to understanding a parallel manipulator's kinematics and can be important in the implementation of controller for manipulator. It has come to light that man-caused factor is the first cause of all kinds of coal mine accidents. The relationship between the mining accidents and the personnel factors and the requirements of the safety qualities for the mine personnel was discussed. First, this system employed psychological and behavioral technology and the method to establish psychological and behavioral evaluation index of perception, cognition, individuality adaptability of coal mine safety personnel to coal mine safety work according as basic requirements for indispensable psychological level. Then, several sensitive, correlative and reliable criteria were selected, and at the same time, forecast indexes to prevent man-caused accident related with the criterions were selected too. Second, performances of personnel followed by defining criteria and pretest index were measured. At last, the applicability of psychological pretest indexes was studied. Two kinds of psychological measurements, five kinds of sensory and cognitive capacity measurements and three kinds of duty evaluation tables was constituted and adopted in this research. It is believed that basic psychological tests and indexes of pretests adopted in this research are fairly good on validity and may become important basis for selecting personnel in coal mine on psychology. An experimental investigation of the forming limit diagram (FLD) for law carbon steel (DIN1623-St 13). The main objective of this work was to determine the forming limit diagram for low carbon (DIN1623-St 13 CD) using (tensile strength and deep drawing test). This diagram is found by practical experiments done on two cases of different test are studied. The first case “tensile specimens group” where a pattern of circle grids is stamped on. Then tensile test is done to them. After that, the change happened in circles was measured and therefore major and minor strains were calculated. The effect of various thicknesses on forming limit diagram is studied. The second case” deep drawing specimens” a pattern of square grids was stamped on them. After applying the deep drawing, the same steps are taken to determine the forming limit diagram. The premise of Apriori algorithm is that the frequency and significance of each item in the database are equal or similar, but in the actual practice of fault diagnosis it's not the case. This paper improved it on the basis of Apriori algorithm, utilizing multiple minimum supports to solve the mining of non-frequent item in equipment fault diagnosis; meanwhile a CCWMMS Algorithm based on “credit component values” is proposed, which focus on the item's inconsistent degree of significance in the actual application. This paper also proved this algorithm's exactness and validity in fault diagnosis by actual examples. Collaborative optimization (CO) is a hierarchical decomposition strategy in multidisciplinary design optimization (MDO) for the design of large-scale complex coupled engineering systems. In CO approach, an original design problem is decomposed into system-level and subsystem-level design problems, and interdisciplinary compatibility constraints (ICC) are defined for the complex coupled relationships between all the individual subsystems. However, confronted with the problems that system objective functions partially rely on local design variables and local state variables in some subsystems, CO can't guarantee the consistency between these local variables and corresponding system design variables. Additionally, ICC can be violated easily by the large fluctuation caused by a small variation of some design variables with big values. This paper concentrates on the ICC in CO, makes some modifications on them and proposes an enhanced collaborative optimization (ECO) methodology. With the ECO strategy, we successfully solve the classical gear reducer design problem in the MDO integration software called iSIGHT. The better results show that ECO is effective and valuable. Combustion and emission characteristics comparison experiments between the diesel-biodiesel mixture fuel and diesel-biodiesel-aethylether mixture fuel are done on a single cylinder diesel engine. Ignition delay period, combustion pressure, heat release ratio, combustion temperature and emissions of the two fuels are analyzed. Results indicate: at 1800rpm, compared with B30, ignition delay period ofB25+M5 increases; peak pressure, peak pressure increase ratio, peak heat release ratio and peak combustion temperature of B25+M5 increase; CO, HC and smoke emissions decrease 39.7%, 17.2% and 50.6% respectively; NO x emission increases 11.6%. Results prove: addment of aethylether can obviously improve the combustion course of diesel-biodiesel mixture fuel and can effectively decrease the smoke emission. Compared to other AHSS, dual phase (DP) steel is used most widely in today's automobile industry for its high strength and good crash performance. However. DP weld's interfacial fracture mode will decrease its weld quality as well as weldability obviously. This paper uses the advantage of servo gun to study the effect of welding process variables on interfacial fracture degree and find out an optimized welding parameter using orthogonal experimental design method to minimize the occurrence of interfacial fracture of DP welds and improve its weldability. This paper will first describe the Linear Quadratic Regulator (LQR) and Fuzzy logic controller when the Proportional-Integral-Derivative (PID) controllers are inactive for procedures that have large delay time (LDT) in transfer stage. Therefore in those states, LQR and Fuzzy controllers perform better than the PID controllers. The constrained LQR is optimal and stabilizing. The solution algorithm is guaranteed to terminate in finite time with a computational cost that has a reasonable upper bound compared to the minimal cost for computing the optimal solution. The system determines the amount of fuel required from a fuzzy algorithm to arrive at the desired temperature. The parameters of the fuzzy control paradigm were a collection of rules and fuzzy-set membership functions. The output of the Fuzzy controller is defuzzified by two different methods; Middle of Maximum (MOM) and Supremum of Maximum (SOM). Eventually, LQR and Fuzzy logic controllers have been designed for a thermal system, which circulates hot air to keep the temperature of a chamber constant and finally the results are analyzed and compared. Establish the precise cost model is one of the most important content of Life Cycle Cost (LCC). In order to find out the important factors in the modeling of LCC, and reduce the correlativity between the factors that affect the cost model, the method of improved Partial Least Squares (PLS) regression with Rough Set was proposed to enhance the calculation precision of the LCC modeling. The attributes of the data were reduced, redundant information were deleted, and then to PLS regression. The deficiency of the PLS regression were improved by this method. Compared with the method of PLS regression, the precision of improved PLS regression model with Rough Set was higher and its application was quite comprehensive. The role of turbochargers is becoming increasingly important as a tool to improve engine fuel economy and reduce engine emissions. As such, compressor and turbine seals must be robustly designed as they can be a significant contributor to emissions and a cause of poor reliability. This paper presents a design guideline that explores the function of the seals, the factors that affect the performance of the seals as well as a number of design tools that can assist the design engineer in properly designing compressor and turbine seals such that they will work well with a minimum amount of development. Based on the thermal elasto-plastic finite element method, the influence of the tool orthogonal rake on cutting forces, workpiece temperature and plastic strain during the orthogonal metal cutting process is studied in this paper. The results show that the cutting forces, the cutting temperature, and the cutting deformation all decrease with increasing the tool orthogonal rake. The effects of usage and time will cause fatigue cracks and corrosion damage to initiate and grow, compromising structural integrity of the served aircraft. To develop an effective inspection and maintenance-scheduling program that takes advantage of life extension technologies, the concept of aging aircraft structure sustainment engineering served in corrosive environment was proposed in this article. The whole algorithm of the sustainment engineering was described and the included situations of repairs, corrosion damage and widespread fatigue damage on aircraft structures were presented, and the effect of the three situations to aging aircraft structure safety was discussed. At last, a numerical example was given to investigate the effect of corrosion and widespread fatigue damage to structural life. The structure life affected by corrosion damage and widespread fatigue damage can be reduced 1.25–2.75 times compared to a non-corroded structure. In actual job shop processing, work pieces are submitted discretely; setup time exists between different processes; and process could be performed in alternative machines. Due dates obey time window distribution. For this type job shop scheduling, aiming at maximizing minimum customer satisfaction and minimizing sum of static and dynamic cost, fuzzy job shop scheduling model with alternative machines is proposed and the algorithm designing is presented. Also, a simulation of 10 machines, 6 work pieces and 6 processes is demonstrated to validate this method, which is an efficient approach for fuzzy multi-objective scheduling with multiple constraints. Machine condition prognosis is a method to predicting machine condition deterioration, based on which condition based maintenance can be effectively scheduled to prevent unexpected machine breakdown, injuries of human, and costs due to the loss of productivity. The noise present in the measured condition variables may adversely affect the prognostic results. Reported work to address this problem includes removing the effects of noise from the observations of condition variables before prediction and modeling actual observations in a statistical way, which is, however, usually not user-friendly. In this work, support vector machine (SVM) is used directly for machine condition prognosis. As SVM is a parametric method, it has potential to achieve good denosing and predicting results simultaneously by appropriately adjusting its model parameters. An optimization model is developed for selecting the parameters, which is solved by adopting genetic algorithms. Two-phase flows, because of providing more heat transfer rate compared with single-phase flows, has drawn attention of many researchers. Two-phase flows commonly include flow regimes of different heat transfer coefficient, among those, annular flow regime usually experience maximum heat transfer coefficient. Flow management in this regime is usually a great deal because of probability of dry-out occurrence. Dry-out phenomenon considerably reduces heat transfer rate. Therefore, attempts should be made to prevent this phenomenon, to obtain as great heat transfer as possible. Entrainment is of parameters that highly affect probability of dry-out occurrence and its location. Entrainment in turn involves with some ripples of different frequencies that commonly form as a result of Kelvin-Helmholtz instabilities at liquid-steam interface in annular two phase flows. These ripples often grow to waves. Interfacial waves are the most significant potential of entrainment mass transfer. Most of two-phase flow simulations, simply neglect the effect of boundary waves. Such a simplifying assumption results in a considerable error in estimation of heat and mass transfer. In the present study, a theoretical approach is applied to simulate interfacial waves, in order to consider effects of these waves on heat and mass transfer phenomenon. In this regard, a ratio of evaporation contribution of mass transfer to entrainment contribution, due to existence of interfacial waves, is defined and computed to find whether it is rational to neglect these waves or not. The entrainment physiques and fundamental are studied through geometrical investigation of interfacial waves and the forces act on the waves. A general correlation for calculating entrainment is proposed based on the physical concept of entrainment phenomenon. The correlation is then confirmed to be consistent with empirical correlations. C-Mold software was applied to the analysis of injection molding of the LCD cover so as to solve the main problems of warpage and injection unbalance of the product. According to the results of filling analysis, problems have been found out and the mold design has been improved. The described case showed the capability of CAE to find the reasons that cause warpage, duration of cooling period, sink mark, blush, color variation and shrinkage directly or indirectly. Thus, CAE analysis has a wide application prospects in injection molding. Using the similar material and simulating test sample joints by prepared vitriol sheet, the sacle effect on compressive strength of five kinds of fractal distribution joints rock mass is studied by test and numerical simulation, in which the uniaxial compressive strength of the small-scale test sample is obtained form the test, and the the unaxial compressive strength of the large-scale test sample obtained by computer simulation by testing conditions. On the base of analyzing the strength change with the scale or the joints distribution dimension, the planar empirical equation is put forward. It is concluded that the rock ductility law increasing with the number augument of rock masses joints is deduced, however, the damage process and way are controlled by the joints distribution. Radiation ovens have drawn a great consideration due to their low energy consumption, safe use and the better curing process in comparison with other kinds of ovens. Providing proper thermal conditions for the curing body in the oven environment is of great importance. Engaging with variable parameters, designing radiation ovens are more complicated relative to other kinds. In the present study a numerical approach of finite surface element method for optimal designing of radiation ovens are proposed. Temperature of heaters at the oven ceiling is the design parameter. Quasi -Newtonian approach is applied for determination of heaters' temperature to achieve an acceptable curing process.Definition of the objective function is completely discussed and effects of two significant concepts of equivalent isentropic time and temperature on objective function behavior are comprehensively studied. Applying equivalent isentropic temperature concept, result in long-lasting convexity treatment of the objective function. Paint cure process is assessed through paint cure window criterion. In this study we investigate how to generate free-form surface design using partial differential equations (PDE). The extension of Bloor and Wilson PDE based approach is considered. The method views surface generation as a boundary value problem and produces free-form surfaces as the solution to elliptic PDE. Intrinsic parameter controls the geometry of the surface through the boundary conditions on the solution of the PDE. Thus, we show the representation using illustrative examples. This paper is about the mechanical analysis of the driving parts of piezoelectric vibration feeder. It analyzed the driving parts of piezoelectric vibration feeder making use of the ANSYS software, extracted the intrinsic frequency and stress analysis diagram and then calculated the amplitude-frequency characteristic curve. It studied the relationship between the resonance spring and system resonance frequency, identified the resonance frequency range of the vibratory hopper, and provided theory arguments for better automatic control. As the key technology of magnesium alloy application, a set of double-chamber gas protection system has been designed ground on process expert database. In view of the different needs of flux and concentration for the cover gas under different furnace system states, this PLC control system based on the process expert database meets the requirements of gas protection control system effectively. The automatic judgment of furnace system states and intelligent adjustment of control parameters have been achieved by control system. And the double-chamber gas protection control system can carry out the independent control of cover gas led into melting room and holding room. Then the flux and mixing ratio of cover gas can be precisely controlled to meet the requirements of effective protection when the magnesium alloy melting system under different states. At the same time, the effect of gas protection can be obtained through using the minimum dosage of cover gas, and the negative effects on the environment can be decreased extremely. Simulation was conducted based on the characteristics of continuity of temperature change, which was shown that in different conditions this control system could obtain the requirements of cover gas control flexibly and effectively, which are set by the process expert database. Hybrid SPR has been developed into a new branch of sheet materials joining technique. In this paper, the free transverse vibration characteristics of single lap-jointed cantilevered hybrid SPR joint are investigated in detail. The focus of the analysis is to reveal the influence on the transverse natural frequencies and mode shapes of the hybrid SPR joint of different characteristics of adhesives. Numerical examples show that the transverse natural frequencies increase significantly as the Young's modulus of the adhesives increase, but almost no change corresponding to the change in Poisson's ratio. The mode shapes show that there are different deformations in the jointed section of the hybrid SPR joints. These different deformations may cause different natural frequency values and different stress distributions. McPherson Suspension is researched with multi-body dynamics and Suspension Kinematics theory. When the rear rubber bushing stiffness of lower control arm is changed, the suspension performance is analyzed and discussed in the vertical bounce, roll bounce, brake force and drive force. The conclusion is drawn that stiffness of rear rubber bushing in all directions has no effect on the suspension performance in the vertical bounce and roll bounce. In the brake force and drive force radical stiffness of rear rubber bushing has heavy effect on the suspension performance and axial and torsion stiffness of rear rubber bushing has a little effect on the suspension performance. In this study, ductile iron was produced by the sandwich method using induction furnace installed at local commercial foundry. A comparative study of the effects of nickel varying from nil to 3.0 wt % was made. Tensile samples were machined from Y Block castings. Tensile test was performed to find out the effect of nickel on tensile strength of ductile iron having different compositions of nickel. One melt was made without nickel while three melts were made with the addition of 1.0 wt%, 2.0 wt % and 3.0 wt % nickel respectively. Effect of austempering heat treatment was also studied to find out the effect of nickel on tensile strength. The samples were austenitized at 90 oC for one hour and austempered at 270 oC and 370 oC. It was found that with the increase of nickel in ductile iron, the tensile strength continued to increase up to 3.0 wt. % with and without nickel addition in both austempering temperatures. The highest tensile strength was obtained with 3.0 wt % nickel. Lean production has been regarded as the third production paradigm after craft-ship production and mass production. Because it incorporates craft-ship production's high quality and mass production' low quality, making enterprises more easily adapted to customer's demand which is characterized as high variety and low volume, so lean production

Proceedings of the ANNIE Conference, November 2010, St. Louis, Missouri. The newest volume in this series presents refereed papers in the following categories and their applications in the engineering domain: Neural Networks; Complex Networks; Evolutionary Programming; Data Mining; Fuzzy Logic; Adaptive Control; Pattern Recognition; Smart Engineering System Design. These papers are intended to provide a forum for researchers in the field to exchange ideas on smart engineering system design. This front matter contains the table of contents and preface The computer manufacturing enterprise system (CMES) emerges and evolves from enterprises' dynamic interactions under the dynamic environment. In this paper we propose that a CMES is not simply a system, but rather a complex adaptive system (CAS). A formulism is constructed to use agent-based simulation (ABS) that allows analysis and design of CMEs, and examination of how CMEs communicate and interact, located and distributed in the CME ecosystem. As systems become more complex, probability of potential system failures and unexampled events increase. In order to move towards the design of resilient systems, there is a need for methodology that links the studies of failure mechanisms to system lifecycle. Prognostic Health Management (PHM) links system engineering processes with diagnostic analysis. This paper outlines a process framework for embedding PHM during architecting of system-of-systems. This paper considers the problem of tracking space objects and propagating their orbital trajectories for declaring potential collision events and assessing corresponding collision probabilities. The design of the complex collision alert system for space situational awareness needs to consider the space object motion uncertainty, the possible earth blockage between the space borne observer and the object being tracked, and any intentional orbital changes that may lead to a collision to any existing resident space object. We apply a nonlinear filtering technique to estimate the orbital state of the space object and a Monte Carlo method to assess the collision probability of any potential encounter. We also develop a collision alert model using realistic encounter scenarios of geostationary objects being observed by low-earth orbit satellites. We quantify the performance of the collision alert system in terms of detection probability, false alarm probability, and average delay from the onset time of an object maneuver resulting in a collision path. Managing complexity using model based systems engineering methods has been an area of increasing research. Models created represent the characteristics of system being developed. Comparisons between models that provide solutions to a common problem are traditionally done using measures of effectiveness and scoring matrices. These techniques are effective in selecting the right solution, but are limited by their dependency on the underling requirements. Change in these requirements leaves a cascading effect on the solution space in the design process. A measure of a solution's susceptibility to these changes in requirements is essential to evaluate the fitness of the model configuration used. Such a measure when combined with other effectiveness scores for a solution would provide a holistic view for judicious decision making. In this paper, we propose a metric to measure the susceptibility of the solution models based on the component interdependency and changing requirements in the development process. Requirements Dependency Factor (RDF) is proposed as a new requirements specification and evaluation metric to assess the quality of requirements. This method ranks requirements on the basis of complexity, risk, and change impact if changed during the life cycle. It is argued that most of all existing requirements specification attributes are qualitative in nature. Current metrics often focus on examining whether requirements are correctly elicited. RDF, however, supplies information about the risk of the project, which can be calculated directly from a set of requirements. The Darpa Urban Challenge project is used to illustrate the calculation and interpretation of RDF. The problem with the existing data modeling techniques is high level of irrelevance in documents retrieved due to the difficulty of understanding human intensions. Our research aims to achieve higher level of relevant document retrieval compared to the existing methods. The difficulty of document retrieval process often stems from the complexity in recognizing a sentence in a given context because of polysemy words. In this paper we describe a noble approach to a data retrieval process based on HAC (Hierarchy of Attributes and Concepts) through which semantic hierarchy relationship can be analyzed for retrieval criteria. The primary aim of this search engine is to understand the human intensions by handling the polysemy words and to retrieve the most relevant results for the user based on identified intentions. The proposed approach is based on our belief that knowledge and information has to be organized in a manner that is intuitive to the user. Further, it is shown to be superior to other existing methods in that it shows high precision rate in retrieving the results. In this paper, we propose Visual Data Analytics (VDA) system as a tool for semantic reasoning based on ontology, through which the Hierarchy of Attributes and Concepts (HAC) can be graphically represented. The VDA is designed to represents attributes, concepts, and their relationships visually and conceptually. In this way, users can quickly search and identify the existence of attributes, concepts and their relationships for semantic reasoning. This system allows users to see and understand concept clusters visually as an effective concept modeling tool. Furthermore, this VDA system allows users to dynamically update the concept models in a selected domain by permitting the deletion and addition of the attributes or concepts to support the dynamic representation of relations between the attributes and concepts. The VDA is applied in a preventive health care domain to demonstrate its effectiveness. Integrating self-organization into control models for wireless sensor networks (WSNs) allows a system to adopt in real-time to maintain the required quality of service in highly dynamic environments. In this paper, the topological structure of a WSN is altered based on time-driven and data-driven events in order to maintain bandwidth, redundancy, and communication speed subject to constraints such as power usage. However, most control models are based on either a time-driven or a data-driven approach which limits the self-organization ability. Unknown data-driven events cause uncertainty in node states leading to variability in outcome. Reducing variability involves enriching the knowledge about node states. From this perspective, an Agent-based Simulation (ABS) provides a strong modeling scheme to examine the system's emergent behavior under different set of rules. In particular, we extract concepts from complex and biological system models. This theoretical framework offers a new direction towards finding solutions for WSN control. Most reinforcement learning algorithms are of the model-free type in which the transition probabilities are not computed and the agent seeks to make decisions without building the transition probability model. We focus on the model-based, also called model-building , algorithms that attempt to build the model along with optimization of the decision-making process. Model-based algorithms have certain advantages over model-free algorithms in that their behavior is more stable and robust . Another aspect of robustness and stability of the algorithm has to do with the variability in the value of the performance measure returned by the algorithm. We will present a new model-building algorithm that builds the transition probability model simultaneously with the value function and a new variance-penalizing algorithm that exhibits robustness with respect to the performance measure. Routing data from sensor nodes to designated mobile data sinks is a common and challenging task in a wide spectrum of Wireless Sensor Network (WSN) applications and thus becoming an active research area. In this paper, a reinforcement-learning based adaptive routing scheme implemented through Adaptive Critic Design (ACD) is proposed. In this scheme, sensor nodes discover and improve the routes at the time of packets transmission. Decision is made dynamically at each sensor node based on various constraints and environmental conditions considered and multi-objective optimization performed. Extensive simulations using synthetic network topologies and sink traces are conducted to test the performance of the proposed routing algorithm with the guidance of Design of Experiments (DoE). The results show the proposed scheme is highly robust and adaptive to a variety of situations. Support Vector Machines (SVMs) and other kernel methods can be applied to the monitoring of multivariate processes. Notably, kernel methods are designed to be robust to common probabilistic assumptions which is a lacking characteristic of conventional control charts. The aim of this work is to show the applications of SVMs to multivariate processes with unknown distribution and correlated characteristics. Experimental results with data sets from the UCI repository of machine learning databases showed remarkable potential. This paper studies the effect of covariance regularization for high dimensional data for classification. This is done primarily by fitting a mixture of Gaussians where the covariance matrix is regularized to each class. Three data sets from various domains are used to suggest the results are applicable to any domain where covariance regularization is required. The regularization needs of the data when pre-processed using two dimensionality reduction techniques, the popular principal component analysis (PCA) and the up-and-coming random projection, are also compared. Observations include that using a large amount of covariance regularization consistently provides classification accuracy as good if not better than using little or no covariance regularization as well as the state-of-the-art classification algorithms across all training set sizes and all but the lowest dimensionalities and that pre-processing using random projection gives results equal to or better than PCA. The results also indicate that random projection could be considered a regularization method per se. Recently a number of research groups presented transistor-based designs exhibiting behavior similar to biological synapses, facilitating creation of a tangible artificial neuron. Hardware neural networks would possess great advantages in information processing tasks that are inherently parallel, such as image processing, require learning, such as handwriting recognition, or in an environment where the processing unit might be susceptible to physical damage. A number of different possibilities for realization of hardware neural networks currently exist. This paper presents analysis of performance degradation of various architectures of artificial neural networks when subjected to neural damage. An analysis of un-optimized and optimized, feed-forward and recurrent networks, trained with uncorrelated and correlated data sets is conducted. A comparison of networks with single, dual, triple, and quadruple hidden layers is quantified. The main finding is that for damage occurring to cells in hidden layer(s) the architecture that sustains the least damage is that of a single hidden layer. However, when the damage is administered to input layer then the opposite, that is arranging cells in multiple hidden layers, offers the most resilience to the damage. Additionally, recurrent networks offer improved resilience to damage compared to feed-forward networks. Data assimilation is a vital step in numerical modeling, particularly in the atmospheric sciences and oceanography. It allows for problems with uneven spatial and temporal data distribution and redundancy to be addressed such that models can ingest information. Conventional methods for assimilation include Kalman filters and variational approaches. They have increased in sophistication to better fit their application requirements and circumvent their implementation issues. Nevertheless, these approaches are incapable of overcoming fully their unrealistic assumptions, particularly linearity, normality, Markovian processes, knowledge of underlying mathematical models and zero error covariances. This paper introduces a family of learning algorithms inspired by support vector machines capable of assisting or replacing the aforementioned traditional methods in assimilating data and making forecasts, without the assumptions of the conventional methods. The application of these algorithms to the processing of the states of a Lorenz 96 model show improvements in speed, efficiency and accuracy in recovering unperturbed state trajectories. The Communications system based in satellite networks and the development of hybrid networks that combine the use of satellite with optical links are being widely studied these days. The main objective is propose a methodology for performance analysis in Multi-Service Satellite Network but can be adapted to more complex networks as Next Generation Networks (NGN). This analysis provides the differentiation between the measurements: system, network and services. With its special features that distinguish them from each other, they will be described throughout the paper and finally we presents real values of study case applying this methodology to the network with 420 active V-SATS that delivery services as: VoIP, data, video and operational measurements used by the oil industry. One of the most important functions of wireless sensor networks is to provide trusted data to a querying host. The existence of compromised nodes or malfunctioning nodes would degrade the trustworthiness of aggregated data. In this paper, we consider clustered sensor networks, in which a normal sensor node can communicate directly with its cluster head. We present an AdaBoost algorithm based approach to detecting abnormal nodes. In our approach, every node is characterized by a series of statistical features which are completely different from the features used by any boosting algorithm in the intrusion detection of wired networks. Finally, we conduct a test-bed experimental study in which behaviors of compromised nodes are simulated. The results of our experiment demonstrate that our proposed approach can effectively detect compromised nodes and significantly reduce the false positive ratio. Classifieds searches on smartphones have great potential to provide more relevant results, higher flexibility and better usability compared to their desktop counterparts. In this paper, we present a new framework for mobile classifies searches with a collection of efficient and effective methods for utilizing geolocation information, creating integrated, coherent results from multiple sources, and incorporating third party social network services. The framework provides support to a rich variety of classified searches on smartphones. Based on this framework, we have developed a location-aware classifieds search iPhone application, NearBuy, which enables users to quickly locate prospective real estate and apartment listings by geolocations. The iPhone application displays results gathered and combined from multiple online sources on an intuitive and easy-to-use map. Additional location-based features enable users to easily explore related information such as neighborhood statistics and photos. Moreover, within a few taps, users are able to browse the website of data source, get direction from his/her location to the real estate and apartment, email and even make a phone call to sellers or landlords directly from the application. NearBuy has received great reviews from the iPhone App community since its release in April 2009. This paper examines the effects on the Quality of Service (QoS) performance, (i.e., received packet throughput, End-End (E2E) delay, packet delivery rate, and routing overhead) for wireless Mobile Adhoc Networks (MANETs) based on design factor selections, such as number of nodes, data rate, and choice of routing algorithm, et al. This paper describes models representing real-world scenarios, such as emergency first responders, where selected nodes arrive, communicate, and move, randomly. Network simulations, trace analysis, and statistical analysis software were used for this research. A design of experiments (DoE) method, i.e., fractional factorials, illustrated which combination of design factors influenced QoS performance more than others. The results showcased that grid size, not evidenced in prior research, and number of nodes played the most significant roles. To reduce the variation evidenced herein and attain a level of optimization, the Six-Sigma (6σ) approach and others will be investigated in a follow-on effort. In this paper we studied the algorithmic complexity behavior of a class of evolutionary systems generated from the Fibonacci system as a base generator. These classes of second generation Fibonacci systems demonstrate interesting features similar to parent systems from complexity perspectives. These properties are derived analytically and presented in numerical simulations. This paper studied a vehicle routing problem with time windows and stochastic travel and service time. A simulation-based optimization framework is originally developed so that the significance of different stochastic parameters as well as distribution functions can be tested simultaneously in a single model. Genetic algorithm with route-sensitive crossover and route-sensitive mutation is applied to minimize the total delivery cost in a deterministic fashion, while Arena simulation models are used for performance analysis of stochastic parameters. Finally, some test instances with certain stochastic components and various distribution functions are established to investigate the performance of simulation models, then computational results are reported. This paper reports an empirical investigation into the effect of different annealing (cooling) schedules on the performance of the simulated annealing algorithm for (i) proton exchange membrane fuel cell stack design optimization, and (ii) parabolic function minimization. The performance metric is the solution quality of the optimal or near-optimal solution obtained at a predetermined number of function evaluations. Five different annealing schemes are considered: linear, exponential, geometric, Cauchy, and Boltzmann. Computational results show that the exponential and geometric schedules outperform the three other schedules on both the problems. One-tailed t-tests are used to study the statistical significance of the results. The results reported in this paper are better than the solutions for PEMFC stack design published by Mohamed and Jenkins in Journal of Power Sources 131 (2004). In this paper, we formulate an optimal weight design (OWD) problem of the single box culvert for a constrained allowable shearing stress of the sidewall, top wall and bottom wall by the slope-deflection method and solve it directly by keeping the constraints based on an improved genetic algorithm (GA). We discuss the efficiency between the proposed method and the traditional method. This paper describes a Competitive Co-evolutionary Algorithm with electric charge model to solve Tsumego . The following three procedures achieve an effective evolutionary process. 1- The Go stones used in Tsumego are assumed to be electric charges. 2- In any specific arrangement of Go stones on the board in Tsumego , the electrical potential distribution of each intersection (where a stone is placed) on the board has a specific calculation. 3- Based on the electrical potential distribution (or variation of electric potential), intersections that do not reach a specific threshold level are excluded. (Intersections on the board are considered to be genes in the chromosomes of the evolution object. Therefore, the length of the chromosomes shortens according to number of excluded intersections.) Thus, the search domain and the calculation cost decreases. In addition, the numeric features calculated from the array of Go stones have been analyzed to develop more efficient methods. This manuscript examines permitting multiple populations of evolvable regressors to compete to be the best model for the largest number of data points. Competition between populations enables a natural process of specialization that implicitly partitions the data. This partitioning technique uses function-stack based regressors and has the ability to discover the natural number of clusters in a data set via a process of sub-population collapse. Computer Go has been recognized as an unconquered challenge to the Artificial Intelligence and Computational Intelligence societies since 1997 when Garry Kasparov, the human Chess champion, was defeated by the IBM supercomputer Deep Blue. Computer Go is considered more than just an unsolved problem; it also serves as an excellent test bed for novel applications to practical problems because of its clear-cut objective and the vast amount of sub-problems that allow for tests of practicality. We propose novel recursive and non-recursive approaches to count the size of groups of connected stones on a Go board. The simple and elegant recursive approach always answers the correct group size. Inspired by the former's tree traversal mechanism, the non-recursive approach guarantees to return the correct answers in an autonomous and scalable manner. In swarm robotics, sometimes more targets result in less tagging due to interference. We investigated several static metrics and their relationship to tagging performance in a swarm robotic cellular automata simulation. The performance metric measures the percentage of targets tagged within a fixed number of steps. The independent metrics measure initial tagging potential, target interference potential, and the robot density. The first metric is the normalized sum of the Manhattan distances between each robot and each target and is meant to capture the potential for tagging early in the simulation that can heavily impact performance. The second metric measures the potential negative impact of target interference on robots, which has the effect of slowing or even trapping robots, distracting them from untagged targets. Finally, the third metric is the global robot density in the world and actually has a positive influence on tagging performance up to the point of saturation. The values of these metrics are taken form the initial world states. We discuss the metrics and simulation and our results show how the three independent metrics in combination predict the dependent metric. This paper deals with unsupervised genetic algorithm based clustering in multidimensional parameter spaces for the non-linear Duffing dynamic system. Numerical integration of the governing differential equations provides the basis for the development of Poincaré maps which is used for automatic feature extraction and data clustering in the parameter space to distinguish regions of periodic behavior from chaotic regions. An elitist genetic algorithm is used to search the parameter space to optimize a combination of oscillator parameters. The Service-oriented Evolutionary Computation Architecture (SoECA) defines a standard of Evolutionary Computations (ECs), and provides a software tool for the researches and real-world applications. We can perform the rapid development for most of EC algorithms by this SoECA. Network modeling is basically a fundamental issue in various fields, including applied mathematics, computer science, engineering, management, and operations research. Network models provide a useful way for modeling various real world problems and are extensively used in many different types of systems: manufacturing and logistics etc. In this paper, we propose a network modeling technique to formulate the complex scheduling problems of APS, and focus how to model the scheduling problems to mathematical formulation. Then we connect SoECA as an optimization tool for solving the scheduling problems. The SoECA will help improve the EC's availability in the variable practical scheduling in APS. Traditional formulations on reliability optimization problems have assumed that the coefficients of models are known as fixed quantities and reliability optimization is treated as deterministic optimization problems. Because that the optimal design of system reliability is resolved in the same stage of overall system design, model coefficients are highly uncertainty and imprecision during design phase and it is usually very difficult to determine the precise values for them. However, these coefficients can be roughly given as the intervals of confidence. In this paper, we formulated reliability optimization problem as nonlinear goal programming with interval coefficients and develop a genetic algorithm to solve it. The key point is how to evaluate each solution with interval data. We give a new definition on deviation variables, which take interval relation into account. Numerical example is given to demonstrate the efficiency of the proposed approach. This project investigates the use of Graph-Based Evolutionary Algorithms in generating diverse solutions for the traveling salesman problem. The traveling salesman problems have a number of applications in science and engineering. Using Graph-Based Evolutionary Algorithms to generate a set of diverse solutions to this problem will provide an opportunity to explore how resiliency can be added to applications such as supply chain management problems. A dissimilarity measure based on transpositions is used to compute the diversity of the solutions. It was found that the number of diverse solutions generated by multiple algorithm runs increases with the rate of information shared within the algorithm. In ant colony optimization methods, the central pheromone trails data structure τ can be thought of as representing the collective wisdom of the population. In each iteration, after each ant generates its candidate solution based on τ and η (a problem-dependent heuristic function), the τ structure is then updated to integrate the experience gained from the solutions constructed into the collective wisdom of the group. First, each entry of the τ data structure is reduced by a fraction ρ, where ρ is an evaporation rate constant, and then some entries of τ are reinforced based on the solutions constructed. We propose a variation in which instead of ρ being constant, each entry of τ is reduced by a Gaussian random number N (ρ m , ρ s ). We evaluate our proposed variation in the context of MAXMIN Ant System and a 1,173-city instance of the traveling salesman problem, and find that our variation improves solution quality. There is a transportation problem as one of typical problems of combinatorial optimization problems. We aim to obtain the semi-optimal solution which was extended to the actual transportation problem with low cost and short time using a genetic algorithm (GA). In this paper, we compared three methods. At first, transportation costs and time respectively solve single objective transportation problem for optimal solutions. Next, the transportation time changes to the transportation costs, that is, multi-objective transportation problem requested the solution as a single objective transportation problem. In the last, the Pareto solution method is used, and combined with the other two results. This paper seeks to determine the feasibility of using fuzzy concepts in conjunction with genetic algorithms in order to solve multi-objective multi-scheduler decision making problems. The domain chosen is the area of single machine scheduling. An experimentation is carried out with different fitness function type and secondary operators considering different scheduler profiles. Preliminary results show both have an effect on the schedule proposed by the system. Many applications involve highly coupled attributes that can range broadly in values. The Kakuro puzzle, an NP-Complete problem, mimics the situation but in a form of numerical combinations. It is expected that an efficient solver can assist in several technological needs, such as finding the optimal data storage utilization, circuit wiring and multiprocessor scheduling. The existing solver is algorithmic-based using lookup tables and exercising recursions. They are good for small size puzzles whose entries have few possible combinations. This motivates the search of alternative methods. In this paper, a swarm intelligent learning strategy is proposed. A set of artificial agents obey rules and follow heuristics to communicate with each other without lookup. The iteratively gained knowledge guides the agents toward the solution. Experiments show the advantage of learning in handling abundant value combinations. Cellular Automata (CAs) are dynamical systems in which space and time are discrete, where each cell obeys the same rule and has a finite number of states. The Cellular Automata model is both general and simple. Generality relates to two things: (1) the model can perform universal computation and (2) the basic units are formed out of a general interaction and not because of a specialized function. The Cellular Automata model is one of the simplest and most general models available for observing and computing complex systems. In this paper we provide an in-depth snapshot of CA, its components that make up the system, rules that the cells follow to bring about dynamic behavior, the classification of CA based on their behavior towards certain rules, and we will also provide an analogy between CAs and Differential Equations as CAs are an extension to Partial Differential Equations. Due to the number of page limitations, topics covered in this paper are summarized. Interested readers are encouraged to refer to the references at the end of this paper. Many real world problems face multiple constraints in the environment, in which some of the partitions have more defined constraints than others. Those with less restriction possess flexibility, but make identification of the global solution difficult due to a bigger search space. The Heyawake puzzle game is a good representative of such, proven to be a NP-complete problem. Each puzzle is composed of rooms that contain cells. The game is to fill up certain cells to satisfy a set of correlated rules. However, the major challenge comes from a freedom that the number of filled cells in a room may not be pre-defined but arbitrary. This freedom introduces complexity. In this paper, a heuristic learning solver, which applies the ant colony swarm intelligence technique, is developed to tackle the high computation complexity of Heyawake. A two-phase processing approach is employed to address firm values first and then account for the uncertainties next. Our experiments show that the method yields good performance on puzzles with more fixed restriction in rooms but can suffer from a computation overhead for many rooms with less restriction. Certain types of problems are extremely difficult to solve through the use of standard computational algorithms and require the employment of alternative methods such as artificial intelligence techniques, which aim to generate a close approximate solution rather than a definite best solution. This paper concentrates on the application of these techniques to the road pixel identification problem using spectral band analysis of satellite data. In particular, a standard back-propagation neural network and a neural network using weights evolved from a genetic algorithm are used to attempt to solve the road pixel identification problem. This paper also compares the performance of the two previously mentioned techniques. This paper attempts to determine which of the two techniques is more suitable for learning the weights of the feed forward neural network as it applies to the road pixel identification problem. Information processing in the brain results from the spread and interaction of electrical and chemical signals within and among neurons. The equations that describe brain dynamics generally do not have analytical solutions. The recent expansion in the use of simulation tools in the field of neuroscience has been encouraged by the rapid growth of quantitative observations that both stimulate and constrain the formulation of new hypotheses of neuronal function. We use the NEURON simulation environment as it provides a powerful and flexible environment for implementing biologically realistic models of electrical and chemical signaling in neurons and networks of neurons. In this research we focus on synaptic potentials interaction as well as on the influence of excitatory and inhibitory neurotransmitters on the conductance changes. We concentrate our attention on influence of gamma (γ)-aminobutyric acid (GABA) as many mental disorders are thought to be due to disturbances in postsynaptic inhibition. Since diagnostic errors can lead to severe consequences for a patient, medical schools are searching for advanced methodologies to teach and asses diagnostic reasoning. Computer software or actors portraying patients are used to present the symptoms of a disease to the students, and the students' approach in diagnosing that disease are recorded. An expert analyzes that record to classify each approach as being correct or incorrect and then recommends appropriate training for each student. With the goal of automating this classification process, neural network-based supervised algorithms are tested in this investigation. The task here is to reliably classify the diagnosis skills of 200 third-year medical students in diagnosing a back pain case. Each student could acquire information from a set of 22 questions, physical examinations and diagnostic tests to diagnose the disease. The potential of using less than 22 features are also investigated. Classification results provided by neural networks are compared with that provided by two conventional statistical classifiers. Significant interest exists in establishing radiologic imaging as a valid biomarker for assessing the response of cancer to a variety of treatments. This preliminary research study has demonstrated that Statistical Learning Theory algorithms, properly used in a clinical setting, have the potential to address questions and criticisms associated with both Response Evaluation Criteria in Solid Tumors and World Health Organization scoring methods. We also propose that tumor heterogeneity, shape, etc. obtained from computer tomography and/or Magnetic Resonance Imaging scans be added to the Statistical Learning Theory feature vector for processing. This paper describes an ongoing research effort to identify gene sets that predict the survival of colorectal cancer patients based on gene expression data. Since the dataset includes 395 genes (after initial feature reduction) and 122 patients, the issue of over fitting must be addressed. A genetic algorithm (GA) specifically designed for feature set selection is used in combination with a support vector machine (SVM). By evaluating groups of genes as opposed to individual genes, complementary sets are obtained. To combat over fitting, the original measurements are perturbed by noise using variances appropriate to each measurement and an overall gain that is adjusted until only a “modest” number of gene sets are repeatedly discovered. Through these adjustments we seek the strongest signal in the data set. The goal is the discovery of clinically useful diagnostic patterns or the rejection of a data set if the strongest signal is not biologically relevant. Initial simulations have shown signs of reproducibility, consistency, and relevance of identified (individual) genes. Protein secondary structure prediction has been a well studied research problem in bioinformatics for years. In previous papers, we presented a rule-based data mining method called RT-RICO (Relaxed Threshold Rule Induction from Coverings) that addressed this problem. Our method surpassed the accuracy, or Q3 score, that had been reported for other computational methods for protein secondary structure prediction using the standard datasets, RS126 and CB396. The success of our rule-based method supported the belief that there are meaningful statistical relationships between any secondary structure position and its neighboring amino acids. However, because of the vast amount of rules generated by RT-RICO, potentially useful information within a rule set was difficult to identify. Herein we discuss the results of examining those RTRICO rules using an existing association rule visualization tool, modified to account for the non-Boolean characterization of protein secondary structure. Application of fuzzy sets within the field of decision making improves the efficiency of interactive systems, and it has, for the most part, consisted of “fuzzifications” of the classical theories of decision making. While decision making under condition of risk and uncertainty has been modeled by probabilistic decision theories and by the game theories, fuzzy decision theories attempt to deal with the fuzziness inherent in imprecise determination of preferences, constrains, and goals. Imprecision and uncertainty play a large role in the field of medicine, life and social sciences. In this paper we propose topology and learning algorithm of neuro-fuzzy system for generation and correction of objects' membership function and respective generalized patterns. The results have been used in medical diagnostics system for determination of influence of chosen set of features (symptoms) over different classes (diseases). The purpose of this paper is to compare early prediction of survival in patients following treatment for metastatic non-small cell lung cancer (NSCLC) using a support vector machine (SVM) paradigm, compared with standard logistic regression (LR). Retrospective blinded independent review by two board certified radiologist body imagers (observers 1 and 2) of the baseline and first post treatment CT scan in 26 patients with stages IIIB and IV NSCLC, consecutively identified from a phase 2 drug trial evaluating gemcitabine in combination with irinotecan, was performed. We show the Support Vector Machine (SVM) paradigm obtained results which consistently outperformed the standard Logistics Regression (LR) approach currently in clinical use. That is because of the highly non-linear nature of the problem, which led to the LR processing resulting in AUCs which were comparable to random guessing (AUC < 0.50) for the majority of experiments individually or as a combination of both board certified radiologists. Finally, the impact is that the proposed research and resultant algorithms will provide a computer aided risk assessment methodology and software packages which could be eventually used in the clinical environment to minimize the errors defined above. Consequently, cancer treatment could be administered more cost effectively by the eventual widespread use of these complex adaptive systems. This paper introduces a new method for ECG classification based on Hidden Markov Tree (HMT) model implemented on Hidden Toolkit platform. The proposed method is capable of distinguishing 8 arrhythmia classes extracted from QT database while varying each time the states and the Gaussian numbers per state of the HMT model. For morphological descriptors (MD) associated with RR intervals, every heart beat is characterized by 10-elements vector and 2-elements vector referring to pre-RR and post-RR. For Higher Order Cumulants descriptors (HOC) associated with RR intervals, every heart beat is characterized by 15-elements vector, and also pre-RR and post-RR. The quality of the classifier was assessed in terms of 4 statistical indicators: sensitivity (SE), specificity (SP), false positive rate (FPR) and false negative rate (FNR). These indices obtained with (MD) associated with RR intervals for our recognition system were a (SE) of 94,95%, a (SP) about 98,65%, a (FPR) value 1,34% and a FNR value 4,82%. By using (HOC) descriptors associated with RR intervals, we obtained a (SE) of 97,22%, a (SP) about 99,12%, a (FPR) value 0,86% and a FNR value 2,77%. In this paper we present a study to automatically iterate through a database containing hundreds of MRI image slices and classify them as containing a tumor or as healthy. Performing this classification manually is prone to error, costly, time consuming, irreproducible and non-scalable. Our technique uses the midsagittal axis to determine whether an asymmetry is present amongst the two hemispheres. This is done using a deformation process followed by a novel morphological erosion operation to conclude the presence of a tumor. Our dataset contains simulated T1-weighted axial slices derived from 3D volumes. These volumes were obtained from BrainWeb and augmented with tumors by the Utah Center for Neuro Image Analysis. Our results indicate an accuracy rate of roughly 90% for the 277 slices tested. These promising results demonstrate that our technique can be applied to large datasets to detect the presence of tumors. Furthermore, our process can be extended to localize these tumors and apply data mining procedures for quantitative analysis. In this paper, an unsupervised approach based on evolving vector quantization (EVQ) is presented for enhancing dermatology images for skin lesion segmentation. Vector quantization (VQ) as a famous compression technique has been widely used in image signal compression and speech signal compression. The EVQ algorithm extends the Linde, Buzo, and Gray (LBG) vector quantization method with particle swarm optimization to cluster the pixels inside the image based on merging similar gray value pixels. The proposed enhancement technique is evaluated using 100 dermoscopy skin lesion images for skin lesion segmentation. The EVQ algorithm is applied to the individual color planes, red, green, and blue, respectively. Segmentation results using these three planes are compared and scored based on manual borders obtained from three dermatologists. In addition, differential equation-based particle swarm optimization is implemented and their results are compared with the standard PSO. Genetic Programming (GP) is a systematic, domain-independent evolutionary computation technique that stochastically evolves populations of computer programs to perform a user-defined task. Similar to Genetic Algorithms (GA) which evolves a population of individuals to better ones, GP iteratively transforms a population of computer programs into a new generation of programs by applying biologically inspired operations such as crossover, mutation, etc. In this paper, a population of Hot-Mix Asphalt (HMA) dynamic modulus stiffness prediction models is genetically evolved to better ones by applying the principles of genetic programming. The HMA dynamic modulus (|E*|), one of the stiffness measures, is the primary HMA material property input in the new Mechanistic Empirical Pavement Design Guide (MEPDG) developed under National Cooperative Highway Research Program (NCHRP) 1-37A (2004) for the American State Highway and Transportation Officials (AASHTO). It is shown that the evolved HMA model through GP is reasonably compact and contains both linear terms and low-order non-linear transformations of input variables for simplification. This paper presents a technique for detecting and tracking multiple vehicles using a single camera. The algorithm utilizes an improved median-based method for calculating a background image. Background image subtraction and region growing are used for moving-object identification. A neural network is used for function approximation, to aid object detection in the background-subtracted image. Velocity prediction enhanced by a local similarity-based algorithm is used for tracking multiple vehicles in video. In this work, utilization of two maps that specify the frequency of vehicle occurrence and the expected vehicle size at image locations is proposed. In particular, the processing window size is adapted depending on the expected vehicle size. X-ray computed tomography (CT) has been introduced as a method to measure fluid transport at the macropore scale to estimate transport parameters. The objective of this study was to use x-ray CT methods to measure transport of an iodide tracer in soil cores and estimate distributions of solute pore-water velocity and dispersivity. CT-measured breakthrough curve experiments were conducted for eight undisturbed soil cores removed from the surface horizon of a Sarpy loamy sand (Typic Udispamment). Breakthrough experiments with KI were conducted using an x-ray CT scanner. Based on breakthrough curves for each pixel, solute pore-water velocity and dispersivity distributions were determined. CT-measured velocity values were slightly lower (6%) than effluent-estimated values. Frequency distributions of pore-water velocity within the intact core samples were found to be normal except one which was bi-modal. CT-measured dispersivity values were 21% lower than effluent-estimated values, attributed to the additional dispersion occurring through the column end-plate. Dispersivity frequency distributions for the intact soil cores all needed transformations; one needed a 0.25 power transformation to normalize the distribution while the others needed a 0.10 power transformation. This study illustrates that the CT method is useful for evaluating solute transport on a macropore scale for porous materials. The heterogeneous nature of porous media presents serious challenges in accurately predicting solute transport through earth materials. Spatial analysis techniques such as geostatistics provide a quantitative tool to evaluate soil pore heterogeneity at a variety of scales. The objective of this study was to determine the macropore-scale spatial variograms of CT-measured pore-water velocity and dispersivity in intact soil cores. CT-measured breakthrough curve experiments were conducted through eight intact soil cores removed from the surface horizon of a Sarpy loamy sand (Typic Udispamment). Breakthrough experiments with KI were conducted using a medical x-ray CT scanner. Based on the breakthrough curve for each pixel, solute pore-water velocity and dispersivity distributions were determined. The exponential variogram model provided the best fit for the variograms of CT-measured pore-water velocity and dispersivity for the cores. The range of autocorrelation for pore-water velocity was found to be 1.4 to 10 mm and dispersivity to be 0.85 to 3.5 mm. The dispersivity autocorrelation range was found to be approximately 65% of the pore-water velocity range. This study illustrates the ability to utilize spatial variograms for quantifying the autocorrelation of CT-measured transport properties, information which may be useful in transport models. Accurate predictions of contaminant transport in porous media are vital to assist in minimizing impairment of water resources. Fractal analysis of transport parameters may assist in quantifying soil heterogeneity at a variety of scales which will help in identifying possible water quality impairments and remedial procedures. The objective of this study was to evaluate whether computed tomography (CT)-measured solute transport parameters are fractal, and if so, determine the fractal dimension and lacunarity of pore-water velocity and dispersivity parameters. CT-measured breakthrough curve experiments were conducted through eight intact soil cores removed from the surface horizon of a Sarpy loamy sand (Typic Udispamment). Breakthrough experiments with KI were conducted using a medical x-ray CT scanner. Based on the breakthrough curve for each pixel, solute pore-water velocity and dispersivity distributions were determined. CT-measured pore-water velocity and dispersivity were found to be fractal. Fractal dimensions of pore-water velocity ranged from 2.16 to 2.43 and for dispersivity from 2.38 to 2.66. Results indicated that both fractal dimension and lacunarity are required to discriminate spatial distributions of the solute transport parameters among samples. If fractal dimensions are the same for different fractal sets, lacunarity analysis may reveal different spatial patterns or fractal structures for such fractal sets. Neural Networks (NNets) are used to model the impact of on-street parking (OSP) conditions on the functionality of arterials as measured by travel time. A microscopically simulated network is used to generate synthetic travel time data under different parking activity and traffic flow levels. A back-propagation NNet is trained to predict the travel time under different conditions. For low traffic flow and low OSP levels the NNet is able to predict travel time with practically good accuracy but without the explicit consideration of the complex traffic flow issues induced by the interaction between traffic flow and on-street parking. At lower ranges of flow and parking maneuvers the NNet predictions were accurate but less so at higher levels. Besides accuracy, the NNet models appear robust enough to cope well with the cyclic variations in arterial operations. As interaction between variables--and its influence on travel time—peaked, other secondary variables became more prominent and started influencing travel time significantly. Other variables, or interaction among variables, may need to be explicitly taken into account. To properly characterize the permeability response of PCC pavement structures, Kansas Department of Transportation (KDOT) generally runs the Rapid Chloride Permeability test (RCPT) to determine the resistance of concrete to penetration of chloride ions. RCPT typically measures the number of coulombs passing through concrete samples over a period of six hours at a concrete age of 7, 28, and 56 days. In this study, back-propagation Artificial Neural Network (ANN)- and Regression-based permeability response prediction models for Rapid Chloride are developed by using the database provided by KDOT in order to reduce the duration of the testing period. Backprop ANN learning technique proved to be an efficient methodology to produce relatively accurate permeability prediction models. Comparison of the prediction accuracy of the developed models proved that ANN models have outperformed their counterpart regression models. Developed ANN-Based permeability prediction models are effective and applicable in characterizing the permeability response of concrete

The ICACTE 2009 was organized to gather members of the international community of Computer Theory and Engineering scientists so that researchers from around the world could present their leading-edge work, expanding our community's knowledge and insight into the significant challenges currently being addressed in that research. This front matter contains the table of contents This research aimed to design an intelligent S/W agent to represent the sign languages to educate the deaf student as special needs individuals according to the international criteria of tutoring computer software as an intelligent tutoring system. Semi-experimental method and a comparative study between two types of representing sign language (digital video or 3d animation) are shown to determine the most appropriate methods for raising the learning rate of the deaf students. The designed application limited to the unit taught is “The nutrition systems” from the Science curriculum, Second year, Al Amal Schools, at Egypt. The research results revealed that there are significant statistical differences between the averages of the degrees of the two experimental groups in achievement, attributed to the difference type of displaying the sign language (Digital Video or 3d animations) for behalf of the group used the digital video and the Intelligent S/W agent. Reconfigurable computing is the next generation approach to compute the algorithms with as much high speed as that of application specific integrated circuits along with the as much flexibility as that of programmable processors. The reconfigurable instruction set processors being most prominent execution platforms for reconfigurable computing have been evolved through many design alternatives. The evolution has explored that the execution performance of a typical reconfigurable processor is greatly dependant on the basic design of its configuration unit. Configuration updation of reconfigurable processor is the dynamically controlled by this unit and hence this unit plays a vital role in the performance enhancement of reconfigurable processor. In this research paper an efficient configuration unit design has been presented which has the capability of loading the most optimal configurations by making the maximum reusability of the existing configuration streams. The simulated results have shown that proposed configuration unit always demonstrates most optimal configuration overhead for reconfigurable processors and hence can be used in high speed reconfigurable instruction set processors. Biomedical signal recordings are affected by different kinds of noise that make their interpretation difficult. In this paper, we present a comparative study of some wavelet functions in the denoising of phonocardiogram (PCG) signals. In particular, we consider the Daubechies of order 4, 6, 8, 10 and 15, Coiflets of order 3, 4, 5 and finally Symlets 10 (sym 10). The performance of these wavelets is based on the measurement of the signal-to-noise Ratio (SNR) of the denoised signal as well as the Mean Square Error (MSE) between the original noisy signal and its denoised counterpart. The results indicate that Daubechies of order 10 (db10) outperform other wavelet functions and, consequently, are potential candidates in the characterization of abnormal PCG signal. Image reconstruction is the art of obtaining a three dimensional scene from 2D images.. Approaches for image reconstruction are, Shape from shading, Shape from texture, Shape from motion, and Shape from stereo. In Shape from stereo or the Stereo Image Reconstruction only two images are used to reconstruct the scene. The most difficult problem in Stereo image reconstruction is the correspondence problem. Matching each pixel is a complex process results in many mismatches and inaccurate three dimensional scene. We have done matching in two levels, the first level is Feature based matching, the second level is Area-based matching. We have joined the two levels to obtain a more accurate pixel by pixel correspondence. We also obtained an adaptive search range and window size for each pixel to reduce the mismatches. Our procedure introduced high accuracy results and more dense 3D scene. Traditional data collection protocols suffer “hot spot” problem heavily in area around the sink node. Recently proposed schemes using mobile sinks try to balance the load with the cost of sink mobility. However, most approaches are based on unit disk graph (UDG) model, which is inaccurate in physical world. We propose an UDG-free solution for data collection with mobile sinks using dominating set and traveling salesman problem (TSP) techniques. A distributed algorithm for dominating set construction is presented, and the result set is used in approximate TSP algorithm to generate a moving path. Our solution not only reduces communication overhead, but also balances the load distribution. This paper presents visualizations of the basic ideas about the multi-objective transportation problem, our purpose is to provide the user with an impressive visual illustrations of the genetic algorithm method of solving the multi-objective transportation problem using Java. This paper presents investigations into the development of feed-forward control schemes for anti-swaying control of a rotary crane system. A nonlinear rotary crane system is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. An unshaped square-pulse torque input is used to determine the characteristic parameters of the system for design and evaluation of the feed-forward control techniques. Feed-forward control schemes based on input shaping and filtering techniques are to be examined. The proposed techniques are designed based on the properties of the system for anti-sway control. The responses of the rotary crane system to the shaped inputs are analyzed in time and frequency domains. Performances of the control schemes are examined in terms of sway angle reduction and time response specifications. Finally, a comparative assessment of the proposed control techniques is presented and discussed. Learning systems are very effective tools for discovering knowledge from databases. Most symbolic learning systems face difficulties when discovering knowledge from large databases. Adapting the learning systems to cope with large databases is the traditional solution to overcome these limitations. This paper evaluates a new methodology for partitioning the representation space. The method selects an irrelevant attribute, determined by a utility function, to partition the representation space. Since irrelevant attributes are not needed to describe concepts learned from the original data, the knowledge discovered from all subspaces should be independent of such an attribute. If the representation space is partitioned by a relevant attribute, the knowledge discovered from all subspaces are combined simply using information about that attribute. The method is analyzed using C5 learning system, or See5. One of the major drawbacks of multi-carrier systems is the high peak-to-average power ratio (PAPR) of the transmitted signals. In this paper, the proposed novel low-complexity selective mapping (SLM) and partial transmit sequences (PTS) schemes are applicable to interleaved orthogonal frequency division multiple access (OFDMA) uplink systems for PAPR reduction. The basic idea is to explore the special structure of interleaved OFDMA, so as to reduce the complexity of PAPR reduction. Current PAPR reduction techniques can be combined with the proposed structure, SLM and PTS are combined for instance. Simulation results show that compared with traditional techniques, the proposed technique can gain the same PAPR reduction but with considerable complexity reduction. The new SLM interleaved OFDMA scheme reduces the computational complexity, while it shows almost the same performance of PAPR reduction as that of the conventional SLM interleaved OFDMA scheme, the new PTS proposed can reduce the complexity too. This method needs side information in the receptor. In this paper, based on the concept of domain decomposition, we construct a class of new alternating group explicit iterative method for fifth order dispersive equations. The method has the intrinsic property of parallelism. Results of numerical experiments show the method is more effective than the known SOR iterative method. In Content-Based Image Retrieval (CBIR), indexing techniques based on global features that relate color and texture are commonly used to represent a description of images. However this approach is unable to capture local information of parts of the image that contain different characteristics. Therefore, some necessary local features of image may be might do not taking in account. This research introduces the new methods in which using the force histograms and radial density to capture some invariant local features. The results show that the force histograms and radial density use to solve the problem caused by variations in scaling, rotation, and translation. Furthermore this technique provides that efficient features to retrieve the sought image where difference pattern of objects may affect the retrieval accuracy. This paper proposes a comparative study of different noise removel techniques and wavelet analysis for image denoising. The performance of these techniques was investigated using an image test Lena and real-life images obtained by the Scanning Electron Microscope (SEM) with a set of predefined noise levels. The performance of these techniques was carried out with respect to two quantitative measures: Peak signal-to-noise ration (PSNR), and mean Square Error (MSE). Experimental results on Lena image and image of SEM are compared with various denoising techniques such as mean filtering; median filtering, Wiener filtering and discrete wavelet transform (DWT) analysis in conjunction with neighbour threshold. The results of the comparative study show that this method presents the best performance among all denoising techniques. The atomic force microscope (AFM) is considered a powerful tool used for imaging at nanometer scale. The microscope tip has to go back and forth in a raster scanning motion over a substrate carrying the sample at slow rate to get enough accurate image of the sample. Many algorithms are designed to solve such problem by steering the tip along the surface of the sample. In the present work, a control algorithm is designed to steer the tip along the desired sample surface only. The scanning process is carried out simply, rabidly, and acquiring high resolution. The proposed algorithm depends only on the data coming from the vertical sensing device. The algorithm is tested for different samples and it is found to be ideal in imaging string-like objects, such as carbon nanotubes, nanowires, and DNA strands. The algorithm performance is accurate, reliable, and resolution is now a controlled parameter. With the widely applied of P2P technology recent year, its illegitimate use on unauthorized sharing of copyrighted files is increasingly rampant. In order to track down these illegal activities, monitoring P2P tasks precisely is needed. To address this issue, we present a method for monitoring the specific content of BtiTorrent file sharing. The method is able to monitor BitTorrent stream according to specific content, no mater the torrent file of the content is possessed or not. Asynchronous transfer mode (ATM) has been adopted as the switching and transport infrastructure for the future broadband integrated services digital network (B-ISDN). The extension of broadband services to the wireless environment is being driven mainly by the proliferation of multimedia portable computers, personal digital assistants, and personal information assistants. Although there are various competing technologies that may provide these services, such as 3G cellular networks and WLAN, wireless ATM has the advantage of offering end-to-end multimedia capabilities with guaranteed quality of service (QoS). The wireless medium has several unique properties which make the design of WATM networks more challenging than the wired one. The most important challenge is the MAC protocol and the Scheduling algorithms that is used to traffic regulation based on traffic characteristics. Student project allocations models (SPA) in which lecturers have preferences over students or projects have been studied in [8, 9]. This paper presents a visualization of a new general student project allocation model in which the lecturers have preference over pairs. The purpose is to provide the user with visual illustrations of student-project allocation algorithm with Preference over Pairs. The visualization is implemented in Java for the fact that it is a web-oriented language. A mobile platform is a huge opportunity for future commercial transactions. This platform should be equipped with a proper middleware, and then traditional commercial applications could be redefined for this new platform. We proposed an architecture style to fill the gap, and excess the development of commercial applications on mobile phones. There are more than 1000 languages and 14 scripts used by 112 million people in India. All of these scripts divide the document in three parts: Text block, Image block, and Table block. In 21 st century, there is a need, obvious reasons, to convert these old printed documents in digital form. Converting them manually is a huge and difficult task. Further it is prone to human errors. Another automated technique is to use Optical character recognition (OCR) system to convert the entire printed document image into editable document. In this paper, an effort has been made to develop OCR technique which converts the printed document into editable document. Firstly a scanned document is preprocessed for noise and skew correction. It is then followed by text-non text classification. Then text line detection has to be performed in the text area. There is no method available which can detect the text line if the image contains the multicolumn text area. In this paper the main contribution is to detect the blocks and detect the text lines in these detected blocks. The technique which can extract the text lines in image document is presented here. After extraction of text lines, word segmentation, character segmentation, and template matching can be performed. EC_ERP is proposed in this paper for integration of E-Business and ERP. The necessity and feasibility analysis of E-Business and ERP integration in terms of market competition, problems in ERP implementation, software development etc. are provided; Strategy is given for implementing ERP in Chinese enterprises; 4-stage EC_ERP implementation process is presented based on the 4-stage ERP implementation theory proposed by Markus and Tanis. In this paper, based on the nine point implicit difference scheme we present a class of alternating group explicit (AGE) iterative method of order four accurate for poisson equations. Also convergence analysis is given. The method has the property of intrinsic parallelism and group explicit computation. In order to verify the AGE method we give several numerical examples. Comparison of the AGE iterative method with nine point implicit scheme show that the method is of nearly the same accuracy with the nine point implicit scheme, and the AGE method can shorten the running time clearly. The Inadequacies of classical design process in developing load compatible-lightweight components have compelled the designers to exploit CAE (computer aided engineering) structural optimization tools effectively early at design stage. Currently, the contemporary design process has entered to a realm where CAE based optimization; simulations and analysis are indispensable for designing the optimal configurations of novel products. In this research, nonparametric three-dimensional structural topology optimization is investigated to find the novel load-compatible configuration design of an operating structure of civil aircraft by exploiting TOSCA and ANSYS software. Analytical load calculations pertinent to the operating and ground conditions are estimated and applied by considering the orientation of structural assembly members and build-in supports offered in the main structure. A smoothened topological optimized model is then imported in CATIA software to extract the CAD viable design. A methodology is also devised to modify the layout of topological optimized voids with splines and fillets, to construct manufacturalbe features and avoid stress concentrations. The resulting novel design is then analyzed and validated against stipulated loads, constraints and other requirements. Aerial image classification is a method to classify and identify the objects on digital maps. Color, edge, shape, and texture have been extracted in order to classify objects on the aerial images. These feature attributes can be obtained directly from aerial images. However the complexity of data and number of rule based may be over information, which it can be reduced by the data mining techniques. In this research, we focus on the use of Fuzzy Logic for pattern classification. The attribute classifications have followed by the design and the implementation of its corresponding tool (Fuzzy Miner) . Finally, the context of Fuzzy Miner is identified and to classify for its improvement are formulated. Extensive tests are performed to demonstrate the performance of Fuzzy Miner and compared with a performance Fuzzy C-Mean classifier. The results showed that, Fuzzy Miner has the best outcomes while Fuzzy C-Mean has the second rank outcomes. One of the most important challenges of Bayesian networks is training an optimal network based on existing training samples. We propose two Learning Automata-based methods for training parameters and structure of the network. Parameter training method is an incremental method which performs training and testing simultaneously and has lower computational cost than enumerative or search based parameter training methods. The structure training method uses a guided search scheme and avoids getting stuck in local maxima. This outputs a network that improves classification accuracy. We could also use both these methods together to train the network. Results indicated that this combinational method further improved classification accuracy while still kept computational cost rational. The exploration of lunar satellite, “No.l Chang e” is simulated with the orbit design by using Matlab GUI and virtual reality design tool. The scene can be chosen by selecting different observation angles. In the mean time, image capturing, processing and transmitting are also simulated. It is the long distance that signal has to pass thus suffers a tremendous attenuation during the deep space transmission. The image will get serious noise which makes the picture blurry. Therefore, we should take the link budget very carefully, including the influence of the atmosphere, to make sure that the image quality is acceptable. On the other hand, some image processing algorithms are also considered. On account of the interferential problem of milling the helicoid, the helical groove's profile are different from the milling cutter's cutting edge that result in difficulty in tool edge design; and the chip flutes of cutting tools have crucial effect in cutting capability and the machining quality, It need improve design precision of milling cutter so that meet the machining precision demand of spiral flute, especially under the different cutting parameters circumstances. Using BP neural network's nonlinear mapped characteristic to simulate discrete coordinates of cutting edge so that obtain the purpose of high precision designing cutting tools' profile. Therefore, a nonlinear model, which is established between the reamer's spiral finite and the milling cutter's profile by BP neural network. According to spiral flute profile, BP neural network simulate the cutting edge of under different helicoid parameter with the Levenberg-Marquardt back-propagation algorithm, the simulating experimental result has proved that using neural network to design milling cutter's profile can satisfy the actual need and can simulate the tool edge under different machining parameter. Following the direction of higher vocational education reform, based on the reform practice at Baoding Vocational College of Technology, we proposed “3-tower diagram” reverse educing method to develop highly skilled personnel training plan. The method characters and procedure are briefly described and detailed implementation is given by an example of developing computer application major vocation personnel training plan. This paper describes an adaptive middleware platform, consisting of the interface model, framework model and perception model, which respectively build on components-based, reflection and event-driven technologies. The interface model encapsulates reusable implementation code, and makes it interact with its environment through well-defined interfaces. The framework model classifies component, and makes component statically or its corresponding object dynamically evolvable. The perception model based on event-driven asynchronous push model opens component object's inner states to outer world. Finally, this paper presents an application example of the implementation of GUI system on our platform. In the paper, the computer control system of self-learning expert for industrial powder injection production is introduced which has been successfully applied. And the working principle and design method of computer hardware and software is discussed. Moreover, the whole process of continuous real-time measurement and closed-loop control for powder injection amount and feed rate of fed-batch part is introduced. In this paper, we present a four order unconditionally stable implicit scheme for 2D hyperbolic equations. Based on the scheme and the concept of decomposition a class of parallel alternating group explicit (AGE) iterative method is derived, and convergence analysis is given. In order to verify the AGE iterative method, we give an example at the end of the paper. A corporate network consists of many individual network security components. Firewall, active directory, and IDS are some examples of these components. Each network security component has its own high level security policy which is translated into low level security mechanisms. There is a wide gap between high level and low level representation of security policy making enforcement of high level security policy faces some essential difficulties. Consistency, verification, and maintenance are the major ones of these difficulties. One approach to overcome these difficulties is to present security policy in an intermediate level and then automate the translation of the intermediate level security policy into low level security mechanisms. Extended Organization Based Access control (EOrBAC) model is valuable step towards introducing this intermediate level. One of the major advantages of EOrBAC is its ability to model most network security components. This paper extends the work of EOrBAC by applying its concept on active directory network security component. Also, an EOrBAC based network security management toolkit is developed to realize this approach. Urban water supply quantity forecasting belongs to non-linear system problem. To forecast urban water supply quantity exactly, support vector machine optimized by genetic algorithm (GA-SVM) is proposed. Genetic algorithm (GA) is used to determine training parameters of support vector machine in GA-SVM. The experimental results indicate that the proposed GA-SVM model can achieve great accuracy in urban water supply quantity forecasting. Spatial exploration projects become more and more complex, involving several different communication nodes posing various communication challenges. To deal with communication challenges in Mars, an interplanetary overlay Network is proposed to establish a communication infrastructure among planets, natural and artificial satellites, and various mission elements such as spacecrafts and rovers. Mars surface nodes in such network have limited resources in terms of storage, energy, processing power. To this end, the paper proposes a resource-aware routing in Interplanetary Surface Network (IPRAR). Performance results are promising. This paper introduces the multicast communication model based on TCP/IP protocol, explicates the support for IP multicast by Winsock 2, designs and realizes the activity image IP multicast system in the local area network environment. In this paper, we present a new time-frequency voice modification concept of speech signal for listeners with hearing impairment. The proposed method, named FBSOLA, for Filter Bank Synchronous Overlap and Addition, explore the SOLA algorithm used for Time-Scale-Modification of speech signal in order to establish a new time-frequency modification method using the M subbands obtained by a Filter Bank analysis-synthesis. We have used the Cosine Modulated Pseudo-QMF Banks. This combined technique allows the modification of both temporal rhythm and spectral envelope of speech signal. A practical solution for perfect reconstruction using the Cosine Modulated Pseudo-QMF Bank is proposed in this paper. The result is a fairly inexpensive (small amount of computation), flexible algorithm that performs a large variety of modifications in order to improve the speech intelligibility for hearing impaired listeners. A software system of the proposed technique is implemented in order to perform complex high quality modifications of speech signal. Experimental results show that the speech signal can be successfully modified to different time-scale/ frequency-magnitudes with high quality. An enterprise would get into a disaster state if they take the liberty to develop software without a good risk measurement. Therefore, the measure is very significant no matter for theoretic or practice. However, the measurement is quite difficult because there are many risk factors in process of software development. And, how much is the holistic risk of a project? Balanced the profit gained from the project and the risk, whether is worth to develop it or not? The questions are always scabrous for the corporations and scholars researched in software engineering field. In this paper, we made creatively a definition of risk fusion, and demonstrated the rationality of risk fusion measurement by using information entropy, and developed a model of risk fusion measurement of software development based on information entropy, and answered the former problems, and also provided a model case. The model can be used to measure the risk fusion, which have been proved in practice, and can be used as basis for risk decision-making. Project-oriented teaching methods were proposed in developing an Engineering Hydrology in a learning content management system, in which a digital learning environment was used to manage, organize and implement course materials, teaching, and evaluation. The system will be applied in training water information technology professionals. The system adopted information technology and curriculum integration, which enable student to complete the training, learn necessary knowledge, and to build up the ability to achieve the designated goals. Accurate forecasting of reservoir's water flow dispatching is very significant to reservoir's optimum dispatching. In order to realize accurate forecasting results of reservoir's water flow dispatching, RBF neural network optimized by genetic algorithm (GA-RBFNN) is proposed in the paper. Genetic algorithm is well suited for searching global optimal values in complex search space. Thus, genetic algorithm is used to dynamically optimize the training parameters of RBFNN. Based on the comparison with the forecast result from BP neural network, the proposed GA-RBFNN model has higher forecasting accuracy. The process and characteristics of the instructional design of adult mobile learning resources are studied in this paper. We first analyzed the characteristics of adult mobile learning resources, and studied each step in the designing process, considering the characteristics of adult mobility. Then we referred to international digital learning resources standards and criteria, considering the characteristics of mobile equipment and adult learners, and we built a resources designing model suitable for adult mobile learning. In the end, we gave some advices to the resource- designers. The target of this contribution is presentation of non standard ways of backup database creation in Oracle. First way is the creation of physical standby database by PL/SQL script, which consists of creation standby initialization files, hot backup copy of primary database data files to standby location and startup of new standby database in Data Guard configuration. Alternative way uses cold backup of primary database and offline copy of backup data files to standby locality. A concept of database backup creations for specific problem, where using of implemented tools in Oracle is unnecessary, is also presented. At that manner are used PL/SQL tools only, without using supplementary services. A set of time- and frequency-domain mixed indexes considering both guidance loop overall performance and hardware constraint was presented. However, the autopilot response using the index exhibited slowly. A general autopilot design procedure synthesized optimal control and frequency-domain constraint was thus proposed. Wherein, the weights selection was transformed into an optimization problem. A four-loop topology was examined to deal with the special case of low-frequency actuator. The analysis and simulation results show that relaxing the static stability of a missile is only benefit to improve missile steady performance. Though a static unstable missile can be stabilized, the finite resource of actuator is the crucial limited factor dominating autopilot function. Sensing coverage and expanding lifetime are important issues for wireless sensor networks. The nodes scheduling for energy-efficiency coverage problem is NP-complete. We considered the problem for the wireless sensor networks with heterogeneous sensing ranges. It typically belongs to a multi-objective optimal model. We present an energy-efficient coverage optimization algorithmbased on Micro-GA multi-objective optimization algorithm (MGAMOO) to solve it. The novel strategy aims to search a Pareto non-dominated front to give a strong support to the selection of optimal active nodes set. To be practical, we have obtained a protocol, HEECO. Numerical simulation experiments were carried out to demonstrate the performance of the proposed algorithm and protocol. Compared with other former protocols, our method shows better qualities in the effects of deployed nodes and amount of active nodes. In view of the early prediction of mine fires, a new method had been studied. The parameters, the coal's spontaneous combustion tendency, the concentration of some gases, were comprehensively analyzed according to different mine condition, which could be used to predict mine fires. The fire prediction model was set up based on neural network optimized by Levenberg-Marquardt algorithm. This was benefit to speed up the convergence rate and improve forecasting rate of identification. Simulation results show that the rate of correct prediction was further improved. This algorithm propound a new way on fire information identification which achieves the most early prediction and the accurate identification of non-fire information before the fire happens. In order to strengthen the data consistency of asynchronous replication protocol, this paper presents an asynchronous replication protocol under fixed space-consistency (ARPFS). ARPFS can achieve fixed data consistency between the primary and backup systems by adjusting the response time of completing write requests dynamically. It is proved by experiments that ARPFS affords a performance between synchronous protocol and asynchronous protocol. It is useful to construct a practical replication system base on fixed data consistency. In the typical implementation of the SHA-1 algorithm, resource constrain makes it meet the limit in the low cost FPGA. The huge need of Slice challenges the use of it. In this paper, we present a spectrum of approaches to implement SHA-1. They are not only taking full advantage of the embedded block RAM and distribute RAM in the FPGA, but also the algorithm optimization to balance the logic block consumption and the speed. We aim to provide different implementation to satisfy the FPGA of different classes in various embedded applications. The paper presents an algorithm for path planning and cooperating two mobile robots, for doing all possible tasks by one mobile robot by using two mobile robots, with cooperation mobile robots in a dynamic environment with obstacles and without any collision between them. Path planning for two mobile robots by using artificial potential field (APF) for reach the same target. Two mobile robots in an environment have neighboring area for collision avoidance. Using two mobile robots for doing tasks will cause increasing speed and decreasing time. The algorithm can be extended for three or more robots. Aiming at the simulation problem of 3D flexible cable in equipment operation simulation training platform, the cable model is classified as two types which are named as constant length model and changeable length model. Then two different simulation methods are put forward according to their respective 3D shape characteristics. Firstly, the catenary method is adopted to describe the constant length model considering the gravity it deserved and the curve equation is deduced to be the final math model. Secondly, the changeable length model is equal to draw a 3D line according two given 3D coordinate points and cylinder with certain radius around the line can be drawn with calling OpenGL API. The rendering effect of each model is presented to prove the simulation feasibility. Finally, the realization mechanism called OpenGL call-back function combining with Vega is brought forward. It shows greatest traits on cable simulation in similar virtual reality system. A coupling model which is based on the Chaos phase space reconstruct and the radial basis function neural network and its utility for rainfall prediction is developed. In general, the precipitation time series, while the time of precipitation processes from beginning to end, has a non-linear feature, which usually can be expressed through a monthly rainfall. Therefore, a new coupling model based on the Chaos theory is produced in this study. In according with the new model monthly rainfall time delay and embedding dimension was computed by autocorrelation function, saturated related dimension and CAO methods, respectively. Furthermore, phase space reconstruction is achieved after the time delay and embedding dimension are counted. Afterwards, the RBF neural networks based on chaotic time series were proposed. In this study, monthly average precipitation of Jianyang city of Sichuan Province, in southeast China, was carried out from 1951 to 2008 to investigate the Chaos phenomenon and simulation. The calculating results show that, the time delay for this time series is 3, the embedding dimension is 9 and the saturated correlation dimension exists. The RBF neural networks coupling with chaotic simulation results show that the proposed model has effective prediction outcome and high prediction precision for the simulated chaotic time sequence, as well as the final absolute error comes to 1.09e-l 1 and the relative errors are lower than 5% except several minimum data. In addition, this coupling model would be used to estimate an annual precipitation and adjust the pattern of planting and guarantee the harvest in agriculture, etc. A hybrid algorithm for global optimization of multivariate polynomial with bound constraints was proposed. The algorithm combines numerical, interval and symbolic methods. Interval methods can obtain small intervals and are guaranteed to contain the global optimum in the presence of rounding errors. Almost all interval-based global optimization methods use interval Newton method to verify existence and uniqueness of a solution to the problem. However, existence and uniqueness verification of a solution to a problem will not succeed when the Jacobi matrix is singular at some point in the region. To overcome the interval methods' shortcomings, we propose to use the symbolic method proposed by Pedersen et al. to improve the system's efficiency and to guarantee the interval methods' integrity. The hybrid method can solve problems that separately none of traditional methods is unable to solve. Furthermore, all the methods in our algorithm have nice properties for parallelization. So the performance of the system can be improved further. Nowadays, frozen foods are well-known among Malaysia society. This is due to the modern lifestyles which require short food preparing times without neglecting the food nutritious. In supporting this requirement, the manipulation of vending machine is identified as a tool to promote modern and healthy living style, besides to simplify the cooking process. This paper describes the effort on designing conceptual model for a proposed steaming food vending machine simulator. Conceptual modelling is the most crucial part in developing simulation model; since in this part, the developer need to identify the variables; recognize the desired simulation flows and transform the deliverables into visualized form which can be understood by all parties related to the project. In this study, the process of three main states (user selection state, freezer state and steaming state) has been modelled using process approach, which emphasized on the process flow or control logic to construct the model for steamed buns vending machine application. Replication system belongs to highly reliable software; therefore, the reliability of itself is particularly important. This paper discusses the error brought about by the breakdown of primary-backup replication system. Then, an error handling method for primary-backup replication protocol (LVR) is presented in this paper aiming at handling this error and improving the reliability. LVR can maintain the data consistency by reconstructing write requests and updating them to backup. Analysis and experiment have revealed that LVR performs highly efficiently and it can be widely used in primary-backup replication protocols. The increasing product diversity and sophistication have demanded an integrated system which can integrate subsystems of an enterprise. The purpose of this research work is to efficiently use all resources available in a manufacturing enterprise by developing a fully integrated system. The proposed system uses the electronic data processing methods together with new database techniques. A framework based on single source of product data (SSPD) system is established to completely integrate the different subsystem of production line. The SSPD framework describe the product data generation, transmission and processing of a production line. The SSPD system validation is carried out by implementing the system in an aerospace enterprise. Before implementing the system the step wise integration and function test was performed and documented. To overcome the disadvantages of the electrostatic target characteristic signal predictors based on Adaline and Elman neural network, such as big error and slow speed, a prediction model based on a four-layer fuzzy neural network (FNN) was proposed for electrostatic target detection. In this model, the membership functions were Gauss functions and the back propagation (BP) algorithm was applied to train the network parameters. The simulation results show that the performance of FNN prediction model is superior to that of Adaline and Elman neural network. It is characterized by smaller error, smaller calculation amount and faster speed which are crucial in real-time system. The proposed prediction method can provide an effective way to compensate the delay of circuits and improve the real-time of the electrostatic detection system. In this paper we present an extension to the Honey Bee Foraging PSO (HBF-PSO) algorithm. This algorithm is modeled after the food foraging behavior of the honey bees and performs a collective foraging for fitness in promising neighborhoods in combination with individual scouting searches in other areas. The strength of the algorithm lies in its continuous monitoring of the whole scouting and foraging process with dynamic relocation of the bees if more promising regions are found. The algorithm has the potential to be useful for optimization problems of multi-modal nature. The extension we propose allows HBF-PSO to automatically adjust the neighborhood size during execution which results in improved performance. The details of the algorithm are presented followed by experimental results on some commonly used multi-modal benchmark test functions. We present a comparison of both versions of HBF-PSO with NichePSO and SPSO. According to ballistic characteristics, bomb-parachute system was simplified and calculation model of trajectory stability was established. Based on the model, effect of related factors and sensitive degree of these factors on trajectory stability was analyzed and compared. The results indicate that equatorial damping coefficient, equatorial rotational inertia and drag coefficient of parachute are key influence factors of trajectory stability. In addition, extending flight distance before parachute opening can speed up convergence rate of attack angle and the trajectory stability will be better correspondingly. The results could provide references not only for the research of optimal design of bomb-parachute system, but also the further analysis of trajectory stability. This paper presents an energy-efficient scheduling algorithm with accrual utility in battery-powered embedded systems. We propose our Two-Step Energy-Efficient Algorithm (TSEEA), which comprises two parts: a static algorithm, which runs offline and achieves the static execution frequencies of all tasks under conservative conditions; and a dynamic one, which strives to reclaim slack time and effectively tunes execution frequency of candidate task in a timely manner. Compared with other algorithms, our algorithm can fully exploit a supply of limited energy to yield more utility. The experiments validate our analytical results and demonstrate that the proposed algorithm outperforms other existing algorithms with respect to utility. Now the existing wave directional spectrum estimation methods have their respective advantages on calculation accuracy and computing time. The paper presents a hybrid algorithm, which gets initial solution by using MLM, and then does second optimization by using a new designed parametrical algorithm based on a wave direction spreading model. The new parametrical algorithm presented here sets up nonlinear equations by using the equal relationship between measured cross spectrum and theoretical cross spectrum, and then gets solution by using nonlinear least squares algorithm. Simulation shows that the hybrid algorithm above has very high computation accuracy, short computing time, and strong anti-noise ability. Process migration which can improve the efficiency in the implementation of task is the key technology in grid. In the current grid environment, a large-scale application program is often broken down into a number of tasks that contain much relation. In order to improve the efficiency, the task needs to be migrated after submitting to the grid. This paper proposes a task selection strategy about migration which is based on fuzzy migration cost, and according to the relation among the tasks, it realizes the selection algorithm about the destination nodes. The experimental results show that the strategy improves the implementation efficiency of associated tasks obviously. In order to supply a reliable and low-cost method for testing excavator's controllers and evaluating the performance of strategies, an excavator real-time simulation system has been developed. The hardware-in-the-loop system, including dynamic model of the arms, dynamic model of the main hydraulic system and an 3D real-time display subsystem, is presented in this paper. The simulation results are also described at the end of the paper. To resolve the problem of the quality detection of cold-rolled strips online,, an approach for defects detection using the method of digital filter with the theory of artificial immune is put forward. The structure of the cold-rolled strips system and the principle of this method are stated detailed. The experiment results in one steelworks show this method can meet the demands of the quality detection of cold-rolled strips and can be used to implement the online quality detection of cold-rolled strips. Taking Chinese Shandong Province for example, Grey Incidence Analysis was utilized to do an empirical research on the relationships between industrial structure and economic development. The results showed that: (i) because of the influence from the original situations of indicator sequences, the absolute degrees of grey incidence about three industries were basically equivalent, which was in line with hypothesis 1 and hypothesis 2; (ii) from the relative degrees of grey incidence and synthetic degrees of grey incidence about three industries, there were such relationships as follows: relative (synthetic) degree of grey incidence about secondary industry > relative (synthetic) degree of grey incidence about primary industry > relative (synthetic) degree of grey incidence about secondary industry > relative (synthetic) degree of grey incidence about tertiary industry; and (iii) from the perspective of the application of grey incidence analysis, it is necessary to pay more attention to the original situation influence of time sequences to computing results. Prefetching is a common technique of tolerating the memory latency. However, it rapidly increases the communications traffic between the upper-level storage and the lower-level. Based on the analysis of access patterns of the SPEC benchmarks, we propose a novel push structure, in which the L2 cache can actively push instructions and data to the L1 cache at a proper time without the request from the L1 cache. By using a cycle-accurate simulator running SPEC benchmarks, the experimenting results showed that our push structure can significantly reduce the access to the L2 cache by 34.6%. Therefore, our push structure can effectively reduce the communications traffic between the L1 and the L2 cache. Our push structure also averagely increases the IPC by 6.6%. A target tracking algorithm based on particle swarm optimization (PSO) is proposed. Due to a premature convergence with PSO in multimodal problems, an improved PSO, i.e. hierarchic particle swarm optimization (HPSO), is proposed and utilized to track target. To maintain high diversity of particle swarm, dynamic propagation is utilized to generate new particles in tracking process. In addition, parameters in PSO are adaptively adjustment in iteration process, leading to a favorable performance in tracking applications. Experiment results demonstrate the proposed algorithm is accurate and effective. Animating virtual crowds with a large number of autonomous agents are effective to enhance realism in virtual reality applications. In this paper we present some preliminary results concerning a real-time visualization methods for large crowds reside in virtual environments. Making good use of LOD, we adopt three resolution models as detailed, less detailed geometry and imposter to represent virtual agent. At the same time we divide virtual crowd into crowd, group, and agent. Then we continue to divide agent into leader- agent and general-agent. We only have to certain which model should be adopted for leader-agent in one group not for every agent for less time complexity. We demonstrate our methods through the manifest the large number of human crowd in the virtual environment. We do to curb noise and improve image quality, you must first pre-processing of images, that is, smooth images. The purpose of image smoothing is to improve the image of the visual effects and improve image clarity in order to become more conducive to the computer image processing and analysis of various characteristics. We use a classic cellular automata “Game of Life,” conducted a study about image smoothing based on game of life to image that a cell for each pixel, using a radius of 1 neighbors of Moore type. We transform the image of the different rules, the use of two-dimensional cellular automaton model area of the smoothed image. We experimentally demonstrate that the smoothing method with the median filter to the normalized mean square error and peak signal to noise ratio comparison method revealed that the more obvious advantages. The aim of this study is to develop a prototype of web based machinery maintenance scheduling system. Maintenance is an important task in remaining the system functionality and to extend the life time of an asset. However, a weak maintenance management and practice may leads to the major system failure which involved high maintenance cost. This paper describes an initial attempt of developing e-maintenance application - Web Based Machinery Maintenance Scheduler System (MMS). MMS is developed to manage the maintenance scheduling of all machines operated in Mechanical Engineering Laboratory. Based on the study, the prototype is able to generate maintenance scheduling for each machines based on the machine maintenance specification, record the data for the emergency maintenance case and generate the monthly maintenance report. The detail outcomes and the results from the study are discussed in this paper. This paper proposed an image steganalysis scheme based on the statistic moments of 2-D histogram in frequency domain. The difference is calculated in three directions, horizontal, vertical and diagonal towards adjacent pixels to obtain three-directional differential images for a natural image. Then the features for steganalysis are extracted from the 2-D DFT of the 2-D histogram of image itself and its differential images. Support vector machine (SVM) with RBF kernel is applied as classifier to distinguish between stego images and cover images. We test the performance of our proposed steganalysis method over spread spectrum (SS) data hiding method, LSB method and QIM data hiding method. The experiment