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Innovations in Defence Support Systems -3

Author: Paolo Remagnino

Publisher: Springer Science & Business Media

Published: 2011-03-04

Total Pages: 223

ISBN-13: 3642182771

This book is a continuation of our previous volumes on Innovations in Defence Support Systems. This book includes a sample of recent advances in intelligent monitoring. The contributions include: · Data fusion in modern surveillance · Distributed intelligent surveillance systems modeling for performance evaluation · Incremental learning on trajectory clustering · Pedestrian speed profiles from video sequence · System-wide tracking of individuals · A scalable approach based on normality components for intelligent surveillance · Distributed camera overlap estimation · Multi-robot team for environmental monitoring The book is directed to the security experts, engineers, scientists, students and professors who are interested in intelligent monitoring.

Innovations in Defence Support Systems – 1

Author: Anthony Finn

Publisher: Springer Science & Business Media

Published: 2010-07-15

Total Pages: 203

ISBN-13: 3642140831

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Innovations in the area of Defence Support Systems are multi-disciplinary, cover a broad range of technologies, and could not possibly be covered within a single volume. This research book presents a sample of research as below: • On the Transition of Innovation and Technology in Defence • Inserting Innovations In-service • Classification of Battlefield Ground Vehicles based on the Acoustic Emissions • Convoy Movement Problem – An Optimization Perspective • Machine Vision Algorithms for Autonomous Aerial Refueling for UAVs using the USAF Refueling Boom Method • Motion Optimization Scheme for Cooperative Mobile Robots • An Automated Decision System for Landmine Detection and Classification The book is directed to the application engineers, research students, professors, decision makers and scientists & engineers working in defence and related areas.

Innovations in Defence Support Systems - 2

Author: Lakhmi C Jain

Publisher: Springer

Published: 2011-02-05

Total Pages: 297

ISBN-13: 3642177646

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Innovations in Defence Support Systems - 2 presents a sample of the state-of-art research on defence support systems. The focus of the volume is on the design and optimization of socio-technical systems and their performance in defence contexts. Conceptual and methodological considerations for the development of such systems and criteria likely to be useful in their evaluation are discussed, along with their conceptual underpinnings in total system performance analysis.

Innovative Computing Methods and their Applications to Engineering Problems

Author: Nadia Nedjah

Publisher: Springer

Published: 2011-05-26

Total Pages: 166

ISBN-13: 3642209580

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The design of most modern engineering systems entails the consideration of a good trade-off between the several targets requirements to be satisfied along the system life such as high reliability, low redundancy and low operational costs. These aspects are often in conflict with one another, hence a compromise solution has to be sought. Innovative computing techniques, such as genetic algorithms, swarm intelligence, differential evolution, multi-objective evolutionary optimization, just to name few, are of great help in founding effective and reliable solution for many engineering problems. Each chapter of this book attempts to using an innovative computing technique to elegantly solve a different engineering problem.

Reasoning in Event-Based Distributed Systems

Author: Sven Helmer

Publisher: Springer Science & Business Media

Published: 2011-06-17

Total Pages: 318

ISBN-13: 364219723X

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With the rapid expansion of the Internet over the last 20 years, event-based distributed systems are playing an increasingly important role in a broad range of application domains, including enterprise management, environmental monitoring, information dissemination, finance, pervasive systems, autonomic computing, collaborative working and learning, and geo-spatial systems. Many different architectures, languages and technologies are being used for implementing event-based distributed systems, and much of the development has been undertaken independently by different communities. However, a common factor is an ever-increasing complexity. Users and developers expect that such systems are able not only to handle large volumes of simple events but also to detect complex patterns of events that may be spatially distributed and may span significant periods of time. Intelligent and logic-based approaches provide sound foundations for addressing many of the research challenges faced and this book covers a broad range of recent advances, contributed by leading experts in the field. It presents a comprehensive view of reasoning in event-based distributed systems, bringing together reviews of the state-of-the art, new research contributions, and an extensive set of references. It will serve as a valuable resource for students, faculty and researchers as well as industry practitioners responsible for new systems development.

Bio-Inspired Self-Organizing Robotic Systems

Author: Yan Meng

Publisher: Springer

Published: 2011-05-11

Total Pages: 273

ISBN-13: 364220760X

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Self-organizing approaches inspired from biological systems, such as social insects, genetic, molecular and cellular systems under morphogenesis, and human mental development, has enjoyed great success in advanced robotic systems that need to work in dynamic and changing environments. Compared with classical control methods for robotic systems, the major advantages of bio-inspired self-organizing robotic systems include robustness, self-repair and self-healing in the presence of system failures and/or malfunctions, high adaptability to environmental changes, and autonomous self-organization and self-reconfiguration without a centralized control. “Bio-inspired Self-organizing Robotic Systems” provides a valuable reference for scientists, practitioners and research students working on developing control algorithms for self-organizing engineered collective systems, such as swarm robotic systems, self-reconfigurable modular robots, smart material based robotic devices, unmanned aerial vehicles, and satellite constellations.

Meta-Learning in Computational Intelligence

Author: Norbert Jankowski

Publisher: Springer

Published: 2011-06-10

Total Pages: 362

ISBN-13: 3642209807

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Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.

New Horizons in Evolutionary Robotics

Author: Stéphane Doncieux

Publisher: Springer Science & Business Media

Published: 2011-02-17

Total Pages: 228

ISBN-13: 3642182712

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Evolutionary Algorithms (EAs) now provide mature optimization tools that have successfully been applied to many problems, from designing antennas to complete robots, and provided many human-competitive results. In robotics, the integration of EAs within the engineer’s toolbox made tremendous progress in the last 20 years and proposes new methods to address challenging problems in various setups: modular robotics, swarm robotics, robotics with non-conventional mechanics (e.g. high redundancy, dynamic motion, multi-modality), etc. This book takes its roots in the workshop on "New Horizons in Evolutionary Design of Robots" that brought together researchers from Computer Science and Robotics during the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2009) in Saint Louis (USA). This book features extended contributions from the workshop, thus providing various examples of current problems and applications, with a special emphasis on the link between Computer Science and Robotics. It also provides a comprehensive and up-to-date introduction to Evolutionary Robotics after 20 years of maturation as well as thoughts and considerations from several major actors in the field. This book offers a comprehensive introduction to the current trends and challenges in Evolutionary Robotics for the next decade.

Computational Optimization, Methods and Algorithms

Author: Slawomir Koziel

Publisher: Springer Science & Business Media

Published: 2011-06-17

Total Pages: 292

ISBN-13: 3642208584

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Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for optimality is challenging, either because of the high computational cost of evaluating objectives and constraints, or because of the nonlinearity, multimodality, discontinuity and uncertainty of the problem functions in the real-world systems. Another complication is that most problems are often NP-hard, that is, the solution time for finding the optimum increases exponentially with the problem size. The development of efficient algorithms and specialized techniques that address these difficulties is of primary importance for contemporary engineering, science and industry. This book consists of 12 self-contained chapters, contributed from worldwide experts who are working in these exciting areas. The book strives to review and discuss the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization. It also covers well-chosen, real-world applications in science, engineering and industry. Main topics include derivative-free optimization, multi-objective evolutionary algorithms, surrogate-based methods, maximum simulated likelihood estimation, support vector machines, and metaheuristic algorithms. Application case studies include aerodynamic shape optimization, microwave engineering, black-box optimization, classification, economics, inventory optimization and structural optimization. This graduate level book can serve as an excellent reference for lecturers, researchers and students in computational science, engineering and industry.

Mining and Control of Network Traffic by Computational Intelligence

Author: Federico Montesino Pouzols

Publisher: Springer Science & Business Media

Published: 2011-02-10

Total Pages: 322

ISBN-13: 3642180833

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As other complex systems in social and natural sciences as well as in engineering, the Internet is hard to understand from a technical point of view. Packet switched networks defy analytical modeling. The Internet is an outstanding and challenging case because of its fast development, unparalleled heterogeneity and the inherent lack of measurement and monitoring mechanisms in its core conception. This monograph deals with applications of computational intelligence methods, with an emphasis on fuzzy techniques, to a number of current issues in measurement, analysis and control of traffic in the Internet. First, the core building blocks of Internet Science and other related networking aspects are introduced. Then, data mining and control problems are addressed. In the first class two issues are considered: predictive modeling of traffic load as well as summarization of traffic flow measurements. The second class, control, includes active queue management schemes for Internet routers as well as window based end-to-end rate and congestion control. The practical hardware implementation of some of the fuzzy inference systems proposed here is also addressed. While some theoretical developments are described, we favor extensive evaluation of models using real-world data by simulation and experiments.