In the early days of aerospace turbomachines, the value of curved vanes for higher efficiency was appreciated while designing aeroengine superchargers during WWI1. Consequently, the first design trade-off was between mechanical stress (i.e., the impeller diameter) and efficiency. In particular, a straight vane produces a higher pressure head compared to a backward curved vane. Furthermore, as the impeller RPM and diameter (i.e., the impeller tip speed) increase, the straight vane produces lower bending stresses vis-à-vis the curved vane that tries to “straighten” itself.

No matter how sophisticated an authentication system has been devised, human is often considered as the weakest link in the security chain. Security problems can stem from bad interactions between humans and systems. Eye movement is a natural interaction modality. The application of eye tracking technology in authentication offers a promising and feasible solution to the tradeoff between the usability and the security of an authentication system. This paper presents a comprehensive study on existing Eye Movement Based Authentication (EMBA) methodologies and systems, and briefly outlines the technical and methodological aspects of EMBA systems. We decompose the EMBA technique into three fundamental aspects: (1) eye movement input modality, (2) eye movement interaction mechanism, and (3) eye movement pattern recognition. The features and functions of the EMBA modules are further analyzed. Emphasis is given on the interrelationship among the modules and their general impacts on the formation and function of the EMBA framework. The paper attempts to provide a systemic treatment on the state of the art technology and also to outline some potential future development directions in eye movement based interaction and security systems.

Most traditional intrusion detection systems attempt to achieve a low error rate. Actually, different mistakes will lead to different losses. The standard classifier based on minimizing the error rate is quite unreasonable and unable to obtain a good classification and prediction results. Cost-sensitive mechanism by introducing proposed to minimize the overall cost of the misclassification. With K-nearest neighbors and Bayesian decision theory, the algorithm is improved to avoid the complicated calculation process. The experimental result demonstrate that we can trade off between false negative and false positive by cost matrix, which can minimize false negative and while constraining false positive at a low level so as to minimize the total misclassification cost.

In the recent years, digital image and video have emerged as the new techniques for the creation, distribution and storage of information. Latest developments in multimedia technologies facilitate the capture and storage of video data with comparatively low-cost computers. Moreover, the novel possibilities provided by the information highways have resulted in the widespread availability of large amount of video data. Nevertheless these data are highly futile unless appropriate search methodologies are employed. Contemporary users are dissatisfied with the video retrieval systems that offer analogue VCR functionality. Content-based search and retrieval of video data has turned out to be a demanding and significant issue. Video encompasses multiple types of audio and visual information those are hard to extract, combine or trade-off in common video information retrieval. In this paper, we address the specific aspect of inferring our approach for content-based video retrieval from a collection of videos. In particular, we introduce a new video data model that supports the integrated use of different approaches. Initially the system splits a video into a sequence of elementary shots, extracts a few representative frames from each shot and computes frame descriptors based on color, Edge and motion features. The extracted features of all the elementary video shots are stored in feature library. In our system, the videos are retrieved based on a query clip. For a query video clip, the color, edge and motion features are extracted and compared against the features in the feature library. The comparison is performed with the aid of Kullback- Leibler distance similarity measure. Afterwards, similar videos are retrieved from the collection of videos based on the calculated Kullback- Leibler distance.

The tradeoff between molecular complexity and accuracy of results continues to be a tug of war in computational material science. One of the challenges in computational nano materials science is the ability to parallelize the tools used, so as to facilitate the solution of more computationally extensive and complex problems with better accuracy. Though using more computationally powerful computers would enable solving larger problems, however real scalability is inherent to the underlying code used to implement the algorithms, and sometimes the algorithms themselves. Ab initio calculations are essential in identifying the properties of new nano materials. We investigate the performance scalability of Abinit1,2 in Band Structure calculations on a massively parallel architecture. We introduce a typical tool flow used for the computations involved. We study the scalability of the underlying tools while performing band structure calculations for C60 and EDOT molecules. We gained initial understanding of the factors affecting scalability for the molecules under consideration and we give some recommendations on how to address the possible issues that affect them.

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.

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.

RAMCAP Plus SM represents the most current stage of the continuing development of Risk Analysis and Management for Critical Asset Protection (RAMCAP SM 1 ). The development was initiated in response to the recommendation of a 2002 White House conference of more than one hundred senior executives from the private sector concerning the protection of the Nation's critical infrastructure. The executives' highest priority was an objective, consistent and efficient method for assessing and reducing infrastructure risks in terms directly comparable among the assets of a given sector and across sectors. The RAMCAP process allowed rational allocation of finite resources to protect the most important and vulnerable infrastructure assets. At the same time, the executives recognized that no universal process would fit the wide range of industries defined as critical infrastructures without some tailoring to fit the respective industries. To achieve the necessary consistency and comparability while recognizing the differences among industries, the RAMCAP approach was conceived as having two levels: a high-level and general method, periodically updated in a publication such as this, and as a series of Sector-Specific Guidance (SSG) documents, expressly tailored to the technologies, issues and cultures of the respective sectors and subsectors. The SSGs - and adaptations of other tools - would be “RAMCAP-consistent” if they met explicit criteria derived from the then-current approach. This assured that the results of applying SSGs would be directly comparable, regardless of the industry to which they were applied. The RAMCAP Plus process consists of seven steps (defined later in this publication) that are practical and robust rather than esoteric or overly theoretical. The goal is an efficient, straightforward process that can be carried out by on-site professionals within a week or less, with a modicum of special training. This design requirement dictates many of the specific trade-offs within in the RAMCAP Plus process.

In the allocation of resources to system safety, there are two dominant approaches in the literature and practice: (i) multiobjective tradeoff analysis involving metrics of risk, performance, and cost; and (ii) cost-benefit analysis involving the monetization of benefits and risk reductions and costs. Multiobjective tradeoff analysis offers an advantage of bringing relevant evidence to the decision makers, who is thoroughly engaged in the evaluation of allocation alternatives. In addition, multiobjective tradeoff analysis is able to address a plurality of perspectives on the allocation problem. However the amount of information needing to be understood by the decision makers can be overwhelming, particularly when the decision space is combinatorial. Cost-benefit analysis offers an advantage of fiscal accountability in large safety programs, in that all benefits and risk reductions are monetized according to a set of standard assumptions. In addition, cost-benefit analysis effectively codifies the values of a safety program for uniform and consistent application across levels and divisions of an organization. However, it can be difficult to agree on the relevant perspectives of for example who pays and who benefits and furthermore to agree on the functional forms and parameters of the benefit and cost functions. We recognize the need for safety program managers to achieve the combined advantages and minimize the disadvantages of the several approaches. In this paper, we review recently developed methods to integrate multiobjective tradeoff analysis to cost-benefit analysis in the allocation of resources to system safety. We describe a framework of multiobjective combinatorial optimization that is supported by alternatives forms of the cost and benefit functions using interval analysis to address uncertainty of the function parameters. We describe that the integrated methods combine some advantages of bringing relevant evidence to the decision makers while supporting the fiscal accountability of the safety program. The methods illuminate a prevalent tradeoff between addressing the intensity of hazards and the exposures to the hazards. Impact analysis of the functional forms and interval analysis of uncertainty enable the methods to proceed without precise knowledge or agreement on key elements of cost and benefit functions. On a graphic representing the tradeoff analysis of risk, performance, and cost, we identify three zones of the plausibility of the benefit-to-cost ratio of particular allocations exceeding a needed threshold of the benefit-to-cost ratio: (1) certain to exceed the threshold, (2) plausible to exceed the threshold, and (3) impossible to exceed the threshold. There are applications of the methods to the allocation of safety-enhancing devices in transportation systems and to the allocation of biological, chemical, and radiological warning sensors around a region. We describe needs for future effort to improve the integration of multiobjective tradeoff analysis with cost-benefit analysis for decision making in safety programs. The paper will be of interest to program managers, reliability engineers, quality and safety professionals, and risk analysts who are charged with the allocation of limited investments and other resources to many and diverse kinds of technologies and projects in large safety programs.

The decision-based design community has made impressive progress over the past 20 years. The theory has become better founded. Industrial test-bed applications have grown more sophisticated. The successes and failures of methodologies in the field have informed the research agenda. Our interdisciplinary approach has evolved from that of a dilettante to that of a highly skilled systems analyst—one with a deep understanding of the integration of one or more technical specialties. The most fundamental contribution has been to bring the same mathematical rigor to design decision-making that has long been employed in traditional design analysis, particularly in the areas of preference modeling, design evaluation and trade-offs under uncertainty. The engineering design community is now keenly aware that decision-making is integral to the design process, rather than an afterthought relegated to others. It is an important element in nearly all phases of design, from defining the problem, synthesizing alternatives, evaluating what is acceptable and what is not, identifying which design elements to work on first, specifying what information is needed and by whom, selecting which alternatives are worth pursuing further and finally configuring the optimal design. Later chapters in this book will reveal the liveliness of ongoing debates about the pros and cons of alternative DBD approaches. While these debates can be quite interesting, don't let them detract from the central message of this book. In truth, the single greatest contribution of DBD has been to help designers recognize that decision-making has always been integral to the design process; only now we think much more carefully about how to make decisions.

The good name of Mr. George Antaki, P.E. was summoned in Chapter 1 when steam hammer was under discussion. As I closed out my planning for this book, I ran across a neat little package concerning pipe (and duct and equipment) insulation which was excerpted from Mr. Antaki's book of ASME Professional Development Series lectures. It consists of the following reprinted pages. It may help clarify some of the qualitative confusion factors a consulting plant or A/E engineer may face when insulation material tradeoffs are made. As always, be sure to also obtain the specific quantitative conductivity versus density data from the material's responsible vendor or manufacturer.

There are trade-offs between electrical performance, cost, and temperature, so it doesn't pay to be TOO cool. Lesson : Junction temperature operating limits .