الصفحة 1
الصفحة 1
Network and Parallel Computing ; IFIP International Conference, NPC 2008, Shanghai, China, October 18-20, 2008. Proceedings
This book constitutes the refereed proceedings of the IFIP International Conference on Network and Parallel Computing, NPC 2008, held in Shanghai, China in October 2008.The 32 revised full papers presented were carefully selected from over 140 submissions. The papers are organized in topical sections on network technologies; network applications; network and parallel architectures; parallel and distributed software.
Multi-Agent and Multi-Agent-Based Simulation ; Joint Workshop MABS 2004
The aim of the workshop was to provide a forum for work in both appli- tions of multi-agent-based simulation and the technical challenges of simulating large multi-agent systems (MAS). There has been considerable recent progress in modelling and analyzing multi-agent systems, and in techniques that apply MAS models to complex real-world systems such as social systems and organi- tions. Simulation is an increasingly important strand that weaves together this work. In high-risk, high-cost situations, simulations provide critical cost/benefit leverage, and make possible explorations that cannot be carried out in situ: – Multi-agent approaches to simulating complex systems are keytools in interdisciplinary studies of social systems. Agent-based social simulation (ABSS) research simulates and synthesizes social behavior in order to understand real social systems with properties of self-organization, scalability, robustness, and openness. – In the MAS community, simulation has been applied to awide range of MAS research and design problems, from models of complex individual agents - ploying sophisticated internal mechanisms to models of large-scale societies of relatively simple agents which focus more on the interactions between agents.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part I
This paper presents a method for classification of medical images, using machine learning and deformation-based morphometry. A morphological representation of the anatomy of interest is first obtained using highdimensional template warping, from which regions that display strong correlations between morphological measurements and the classification (clinical) variable are extracted using a watershed segmentation, taking into account the regional smoothness of the correlation map which is estimated by a crossvalidation strategy in order to achieve robustness to outliers. A Support Vector Machine-Recursive Feature Elimination (SVM-RFE) technique is then used to rank computed features from the extracted regions, according to their effect on the leave-one-out error bound. Finally, SVM classification is applied using the best set of features, and it is tested using leave-one-out. The results from a group of 61 brain images of female normal controls and schizophrenia patients demonstrate not only high classification accuracy (91.8%) and steep ROC curves, but also exceptional stability with respect to the number of selected features and the SVM kernel size
Formal Modeling and Analysis of Timed Systems ; Vol.4202 ; 4th International Conference, FORMATS 2006, Paris, France, September 25-27, 2006, Proceedings
The aim of FORMATS is to promote the study of fundamental and practical aspects of timed systems, and to bring together researchers from di?erent d- ciplines that share interests in modelling and analysis of timed systems. In this volume, there are articles on: – Foundations and Semantics: contributions to the theoretical foundations of timed systems and timed formal languages as well as comparison between di?erentmodelsusedbydi?erentcommunities(timedautomata,timedPetri nets, timed MSCs, hybrid automata, timed process algebra, timed temporal logics, timed abstract state machines, as well as probabilistic models). – Methods and Tools: techniques, algorithms, data structures, and software toolsforanalyzingtimedsystemsandresolvingtemporalconstraints(mod- checking, simulation, robustness analysis, scheduling, etc).
Evolvable Machines : Theory & Practice
Methods for the artificial evolution of active components, such as programs and hardware, are rapidly developing branches of adaptive computation and adaptive engineering. "Evolvable Machines" reports innovative and significant progress in automatic and evolutionary methodology applied to machine design. This book presents theoretical as well as practical chapters concentrating on Evolvable Robots, Evolvable Hardware Synthesis, as well as Evolvable Design.
Embedded systems design : The ARTIST roadmap for research and development
Embedded systems now include a very large proportion of the advanced products designed in the world, spanning transport (avionics, space, automotive, trains), electrical and electronic appliances (cameras, toys, televisions, home appliances, audio systems, and cellular phones), process control (energy production and distribution, factory automation and optimization), telecommunications (satellites, mobile phones and telecom networks), and security (e-commerce, smart cards), etc. The extensive and increasing use of embedded systems and their integration in everyday products marks a significant evolution in information science and technology. We expect that within a short timeframe embedded systems will be a part of nearly all equipment designed or manufactured in Europe, the USA, and Asia. There is now a strategic shift in emphasis for embedded systems designers: from simply achieving feasibility, to achieving optimality. Optimal design of embedded systems means targeting a given market segment at the lowest cost and delivery time possible. Optimality implies seamless integration with the physical and electronic environment while respecting real-world constraints such as hard deadlines, reliability, availability, robustness, power consumption, and cost. In our view, optimality can only be achieved through the emergence of embedded systems as a discipline in its own right.
Digital watermarking ; Vol. 3304 ; 3rd International Workshop, IWDW 2004, Seoul, Korea, October 30 - November 1, 2004, revised selected papers
We are happy to present to you the proceedings of the 3rd International Workshop on Digital Watermarking, IWDW 2004. Since its modern reappearance in the academic community in the early 1990s, great progress has been made in understanding both the capabilities and the weaknesses of digital watermarking. On the theoretical side, we all are now well aware of the fact that digital watermarking is best viewed as a form of communication using side information. In the case of digital watermarking the side information in question is the document to be watermarked. This insight has led to a better understanding of the limits of the capacity and robustness of digital watermarking algorithms. It has also led to new and improved watermarking algorithms, both in terms of capacity and imperceptibility. Similarly, the role of human perception, and models thereof, has been greatly enhanced in the study and design of digital watermarking algorithms and systems. On the practical side, applications of watermarking are not yet abundant. The original euphoria on the role of digital watermarking in copy protection and copyright protection has not resulted in widespread use in practical systems. With hindsight, a number of reasons can be given for this lack of practical applications.
Demystifying Internet of Things Security : Successful IoT Device/Edge and Platform Security Deployment
The IoT presents unique challenges in implementing security and Intel has both CPU and Isolated Security Engine capabilities to simplify it. This book explores the challenges to secure these devices to make them immune to different threats originating from within and outside the network. The requirements and robustness rules to protect the assets vary greatly and there is no single blanket solution approach to implement security.
Deep neural networks and data for automated driving : robustness, uncertainty quantification, and insights towards safety
Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety? This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.
Control Theory Tutorial : Basic Concepts Illustrated by Software Examples
Introduces the basic principles of control theory in a concise self-study guide. It complements the classic texts by emphasizing the simple conceptual unity of the subject. A novice can quickly see how and why the different parts fit together. The concepts build slowly and naturally one after another, until the reader soon has a view of the whole. Each concept is illustrated by detailed examples and graphics. The full software code for each example is available, providing the basis for experimenting with various assumptions, learning how to write programs for control analysis, and setting the stage for future research projects. The topics focus on robustness, design trade-offs, and optimality. Most of the book develops classical linear theory. The last part of the book considers robustness with respect to nonlinearity and explicitly nonlinear extensions, as well as advanced topics such as adaptive control and model predictive control.
Computer Vision Metrics : Survey, Taxonomy, and Analysis
Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more.
A Testers Guide to .NET Programming
A Tester's Guide to .NET Programming focuses solely on applied programming techniques for testers. You will learn how to write simple automated tests, enabling you to test tools and utilities. You will also learn about the important concepts driving modern programming today, like multitier applications and object-oriented programming. More businesses are adopting .NET technologies, and this book will equip you to assess software robustness and performance. Whether you're an experienced programmer who's unfamiliar with testing concepts, or you're an experienced tester versed in VB .NET and C#, the included real-world tips and example code will help you start your projects.
