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An Introduction to Parallel and Vector Scientific Computation
In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as the authors cover traditional topics in a first course in scientific computing. Building on the fundamentals of floating point representation and numerical error, a thorough treatment of numerical linear algebra and eigenvector/eigenvalue problems is provided. By studying how these algorithms parallelize, the reader is able to explore parallelism inherent in other computations, such as Monte Carlo methods.
Algorithmic Foundations of Robotics XIV
This proceedings book helps bring insights from this array of technical sub-topics together, as advanced robot algorithms draw on the combined expertise of many fields—including control theory, computational geometry and topology, geometrical and physical modeling, reasoning under uncertainty, probabilistic algorithms, game theory, and theoretical computer science. Intelligent robots and autonomous systems depend on algorithms that efficiently realize functionalities ranging from perception to decision making, from motion planning to control. The works collected in this SPAR book represent the state of the art in algorithmic robotics. They originate from papers accepted to the 14th Interna...
Marine Robot Autonomy
Autonomy for Marine Robots provides a timely and insightful overview of intelligent autonomy in marine robots. A brief history of this emerging field is provided, along with a discussion of the challenges unique to the underwater environment and their impact on the level of intelligent autonomy required. Topics covered at length examine advanced frameworks, path-planning, fault tolerance, machine learning, and cooperation as relevant to marine robots that need intelligent autonomy.
Algorithmic Foundations of Robotics IX
Robotics is at the cusp of dramatic transformation. Increasingly complex robots with unprecedented autonomy are finding new applications, from medical surgery, to construction, to home services. Against this background, the algorithmic foundations of robotics are becoming more crucial than ever, in order to build robots that are fast, safe, reliable, and adaptive. Algorithms enable robots to perceive, plan, control, and learn. The design and analysis of robot algorithms raise new fundamental questions that span computer science, electrical engineering, mechanical engineering, and mathematics. These algorithms are also finding applications beyond robotics, for example, in modeling molecular m...
Oxford Textbook of Suicidology and Suicide Prevention
Part of the authoritative Oxford Textbooks in Psychiatry series, the new edition of the Oxford Textbook of Suicidology and Suicide Prevention remains a key text in the field of suicidology, fully updated with new chapters devoted to major psychiatric disorders and their relation to suicide.
Field and Service Robotics
FSR, the International Conference on Field and Service Robotics, is a robotics Symposium which has established over the past ten years the latest research and practical results towards the use of field and service robotics in the community with particular focus on proven technology. The first meeting was held in Canberra, Australia, in 1997. Since then the meeting has been held every two years in the pattern Asia, America, Europe. Field robots are non-factory robots, typically mobile, that operate in complex and dynamic environments; on the ground (of earth or planets), under the ground, underwater, in the air or in space. Service robots are those that work closely with humans to help them w...
Factor Graphs for Robot Perception
Reviews the use of factor graphs for the modeling and solving of large-scale inference problems in robotics. Factor graphs are introduced as an economical representation within which to formulate the different inference problems, setting the stage for the subsequent sections on practical methods to solve them.
The Oxford Handbook of Nonsuicidal Self-Injury
The Oxford Handbook of Nonsuicidal Self-Injury is a compendium of up-to-date research and knowledge of topics germane to the field of nonsuicidal self-injury (NSSI). Edited by renowned scholars Elizabeth E. Lloyd-Richardson, Imke Baetens, and Janis L. Whitlock, the handbook brings together cutting-edge research from a group of internationally distinguished scholars. It covers a wide array of topics including epidemiology, function, neurophysiological processes, lived experience, and intervention and prevention approaches. This comprehensive text will serve as a go-to guide for scholars, clinicians, and anyone with interest in understanding, treating, and preventing self-injury.
Information-Driven Planning and Control
A unified framework for developing planning and control algorithms for active sensing, with examples of applications for specific sensor technologies. Active sensor systems, increasingly deployed in such applications as unmanned vehicles, mobile robots, and environmental monitoring, are characterized by a high degree of autonomy, reconfigurability, and redundancy. This book is the first to offer a unified framework for the development of planning and control algorithms for active sensing, with examples of applications for a range of specific sensor technologies. The methods presented can be characterized as information-driven because their goal is to optimize the value of information, rather than to optimize traditional guidance and navigation objectives.
