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This book combines the research activities of the authors, both of whom are researchers at Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation), and presents their findings from the last 15 years. Their work uses air transport as its focal point, within the realm of mathematical optimization, looking at real life problems and theoretical models in tandem, and the challenges that accompany studying both approaches. The authors’ research is linked with the attempt to reduce air space congestion in Western Europe, USA and, increasingly, Asia. They do this through studying stochastic optimization (particularly artificial evolution), the sectorization of airspace, route distribution and takeoff slots, and by modeling airspace congestion. Finally, the authors discuss their short, medium and long term research goals. They hope that their work, although related to air transport, will be applied to other fields, such is the transferable nature of mathematical optimization. At the same time, they intend to use other areas of research, such as approximation and statistics to complement their continued inquiry in their own field. Contents 1. Introduction. Part 1. Optimization and Artificial Evolution 2. Optimization: State of the Art. 3. Genetic Algorithms and Improvements. 4. A new concept for Genetic Algorithms based on Order Statistics. Part 2. Applications to Air Traffic Control 5. Air Traffic Control. 6. Contributions to Airspace Sectorization. 7. Contribution to Traffic Assignment. 8. Airspace Congestion Metrics. 9. Conclusion and Future Perspectives. About the Authors Daniel Delahaye works for Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation) in France. Stéphane Puechmorel works for Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation) in France.

The first single-source reference covering the state of the art in grid and utility computing economy research This book presents the first integrated, single-source reference on market-oriented grid and utility computing. Divided into four main parts—and with contributions from a panel of experts in the field—it systematically and carefully explores: Foundations—presents the fundamental concepts of market-oriented computing and the issues and challenges in allocating resources in a decentralized computing environment. Business models—covers business models for service providers and brokers supporting different types of distributed applications, as well as business rules-based models for managing virtual organizations and accounting operations and services in grid computing environments. Policies and agreements—introduces policies, agreements, and specifications for the negotiation and establishment of contracts between providers and consumers. It also covers different approaches for resource allocation based on service-level agreements (SLAs) and management of risks associated with SLA violations. Resource allocation and scheduling mechanisms—covers economic models, such as commodity models, reciprocation, auctions, and game theory, and middleware technologies, such as Nimrod/G and Gridbus, for market-oriented grid computing and utility-oriented resource allocation. This book expertly captures the state of the art in the field while also identifying potential research directions and technologies that will facilitate the creation of global commercial grid and utility computing systems. It is an indispensable reference for systems architects, practitioners, developers, new researchers, and graduate students.

The topic of this book is proportionate-type normalized least mean squares (PtNLMS) adaptive filtering algorithms, which attempt to estimate an unknown impulse response by adaptively giving gains proportionate to an estimate of the impulse response and the current measured error. These algorithms offer low computational complexity and fast convergence times for sparse impulse responses in network and acoustic echo cancellation applications. New PtNLMS algorithms are developed by choosing gains that optimize user-defined criteria, such as mean square error, at all times. PtNLMS algorithms are extended from real-valued signals to complex-valued signals. The computational complexity of the presented algorithms is examined. Contents 1. Introduction to PtNLMS Algorithms 2. LMS Analysis Techniques 3. PtNLMS Analysis Techniques 4. Algorithms Designed Based on Minimization of User Defined Criteria 5. Probability Density of WD for PtLMS Algorithms 6. Adaptive Step-size PtNLMS Algorithms 7. Complex PtNLMS Algorithms 8. Computational Complexity for PtNLMS Algorithms About the Authors Kevin Wagner has been a physicist with the Radar Division of the Naval Research Laboratory, Washington, DC, USA since 2001. His research interests are in the area of adaptive signal processing and non-convex optimization. Milos Doroslovacki has been with the Department of Electrical and Computer Engineering at George Washington University, USA since 1995, where he is now an Associate Professor. His main research interests are in the fields of adaptive signal processing, communication signals and systems, discrete-time signal and system theory, and wavelets and their applications.

Explores and identifies the main issues, concepts, principles and evolution of software testing, including software quality engineering and testing concepts, test data generation, test deployment analysis, and software test management This book examines the principles, concepts, and processes that are fundamental to the software testing function. This book is divided into five broad parts. Part I introduces software testing in the broader context of software engineering and explores the qualities that testing aims to achieve or ascertain, as well as the lifecycle of software testing. Part II covers mathematical foundations of software testing, which include software specification, program correctness and verification, concepts of software dependability, and a software testing taxonomy. Part III discusses test data generation, specifically, functional criteria and structural criteria. Test oracle design, test driver design, and test outcome analysis is covered in Part IV. Finally, Part V surveys managerial aspects of software testing, including software metrics, software testing tools, and software product line testing. Presents software testing, not as an isolated technique, but as part of an integrated discipline of software verification and validation Proposes program testing and program correctness verification within the same mathematical model, making it possible to deploy the two techniques in concert, by virtue of the law of diminishing returns Defines the concept of a software fault, and the related concept of relative correctness, and shows how relative correctness can be used to characterize monotonic fault removal Presents the activity of software testing as a goal oriented activity, and explores how the conduct of the test depends on the selected goal Covers all phases of the software testing lifecycle, including test data generation, test oracle design, test driver design, and test outcome analysis Software Testing: Concepts and Operations is a great resource for software quality and software engineering students because it presents them with fundamentals that help them to prepare for their ever evolving discipline.

Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful ? data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.

This book lays out the concepts necessary to understand how a computer works. For reasons of clarity, the authors have deliberately chosen examples that apply to machines from all eras, without having to water down the contents of the book. This choice helps to show how techniques, concepts and performances have evolved since the first computers. The book is divided into five parts. The first four, which are of increasing difficulty, are the core of the book: “Elements of a Basic Architecture”, “Programming Model and Operation”, “Memory Hierarchy”, “Parallelism and Performance Enhancement”. The final part provides hints and solutions to the exercises in the book as well as appendices. The reader may approach each part independently based on their prior knowledge and goals.

A comprehensive guide to computer assisted exercises Readers can turn to this indispensable reference guide for comprehensive and lucid coverage of the operational, technical, and organizational knowledge needed to harness successful and constructive computer assisted exercises (CAX) and war games. It is geared also toward large civilian organizations that are looking to teach and test their strategies and procedures without the added cost of manpower. Divided into two clear parts, the book covers: Fundamentals and Theory—conflict and warfare; probability and statistics; simulation; distributed simulation; and experimentation and analysis Combat Modeling, Computer Assisted Exercises, and Practice—CAX architectures; CAX process; combat modeling; CAX support tools; communications/information system issues, technical risks, and risk miti-gation; and exercise centers and facilities Computer Assisted Exercises and Training: A Reference Guide is indispensable reading for research engineers, computer scientists, software engineers working with modeling and simulation, homeland security specialists, staff in simulation training centers, military strategists and commanders, and many others. It also serves as a valuable textbook for modeling and simulation courses at the upper-undergraduate and graduate levels.

The energy consumption issue in distributed computing systems raises various monetary, environmental and system performance concerns. Electricity consumption in the US doubled from 2000 to 2005. From a financial and environmental standpoint, reducing the consumption of electricity is important, yet these reforms must not lead to performance degradation of the computing systems. These contradicting constraints create a suite of complex problems that need to be resolved in order to lead to 'greener' distributed computing systems. This book brings together a group of outstanding researchers that investigate the different facets of green and energy efficient distributed computing. Key features: One of the first books of its kind Features latest research findings on emerging topics by well-known scientists Valuable research for grad students, postdocs, and researchers Research will greatly feed into other technologies and application domains

Many approaches to creating Software Product Lines have emerged that are based on Model-Driven Engineering. This book introduces both Software Product Lines and Model-Driven Engineering, which have separate success stories in industry, and focuses on the practical combination of them. It describes the challenges and benefits of merging these two software development trends and provides the reader with a novel approach and practical mechanisms to improve software development productivity. The book is aimed at engineers and students who wish to understand and apply software product lines and model-driven engineering in their activities today. The concepts and methods are illustrated with two product line examples: the classic smart-home systems and a collection manager information system.

NEW LANGUAGE VISUALIZES PROGRAM ABSTRACTIONS CLEARLY AND PRECISELY Popular software modelling notations visualize implementation minutiae but fail to scale, to capture design abstractions, and to deliver effective tool support. Tailored to overcome these limitations, Codecharts can elegantly model roadmaps and blueprints for Java, C++, and C# programs of any size clearly, precisely, and at any level of abstraction. More practically, significant productivity gains for programmers using tools supporting Codecharts have been demonstrated in controlled experiments. Hundreds of figures and examples in this book illustrate how Codecharts are used to: Visualize the building-blocks of object-oriented design Create bird's-eye roadmaps of large programs with minimal symbols and no clutter Model blueprints of patterns, frameworks, and other design decisions Be exactly sure what diagrams claim about programs and reason rigorously about them Tools supporting Codecharts are also shown here to: Recover design from plain Java and visualize the program's roadmap Verify conformance to design decision with a click of a button This classroom-tested book includes two main parts: Practice (Part I) offers experienced programmers, software designers and software engineering students practical tools for representing and communicating object-oriented design. It demonstrates how to model programs, patterns, libraries, and frameworks using examples from JDK, Java 3D, JUnit, JDOM, Enterprise JavaBeans, and the Composite, Iterator, Factory Method, Abstract Factory, and Proxy design patterns. Theory (Part II) offers a mathematical foundation for Codecharts to graduate students and researchers studying software design, modelling, specification, and verification. It defines a formal semantics and a satisfies relation for design verification, and uses them to reason about the relations between patterns and programs (e.g., «java.awt implements Composite» and «Factory Method is an abstraction of Iterator»).

Groundbreaking, long-ranging research in this emergent field that enables solutions to complex biological problems Computational systems biology is an emerging discipline that is evolving quickly due to recent advances in biology such as genome sequencing, high-throughput technologies, and the recent development of sophisticated computational methodologies. Elements of Computational Systems Biology is a comprehensive reference covering the computational frameworks and techniques needed to help research scientists and professionals in computer science, biology, chemistry, pharmaceutical science, and physics solve complex biological problems. Written by leading experts in the field, this practical resource gives detailed descriptions of core subjects, including biological network modeling, analysis, and inference; presents a measured introduction to foundational topics like genomics; and describes state-of-the-art software tools for systems biology. Offers a coordinated integrated systems view of defining and applying computational and mathematical tools and methods to solving problems in systems biology Chapters provide a multidisciplinary approach and range from analysis, modeling, prediction, reasoning, inference, and exploration of biological systems to the implications of computational systems biology on drug design and medicine Helps reduce the gap between mathematics and biology by presenting chapters on mathematical models of biological systems Establishes solutions in computer science, biology, chemistry, and physics by presenting an in-depth description of computational methodologies for systems biology Elements of Computational Systems Biology is intended for academic/industry researchers and scientists in computer science, biology, mathematics, chemistry, physics, biotechnology, and pharmaceutical science. It is also accessible to undergraduate and graduate students in machine learning, data mining, bioinformatics, computational biology, and systems biology courses.

The first book to introduce computer architecture for security and provide the tools to implement secure computer systems This book provides the fundamentals of computer architecture for security. It covers a wide range of computer hardware, system software and data concepts from a security perspective. It is essential for computer science and security professionals to understand both hardware and software security solutions to survive in the workplace. Examination of memory, CPU architecture and system implementation Discussion of computer buses and a dual-port bus interface Examples cover a board spectrum of hardware and software systems Design and implementation of a patent-pending secure computer system Includes the latest patent-pending technologies in architecture security Placement of computers in a security fulfilled network environment Co-authored by the inventor of the modern Computed Tomography (CT) scanner Provides website for lecture notes, security tools and latest updates