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This book provides state-of-the-art scientific and engineering research findings and developments in the area of service robotics and associated support technologies around the theme of human-centric robotics. The book contains peer reviewed articles presented at the CLAWAR 2017 conference. The book contains a strong stream of papers on robotic locomotion strategies and wearable robotics for assistance and rehabilitation. There is also a strong collection of papers on non-destructive inspection, underwater and UAV robotics to meet the growing emerging needs in various sectors of the society. Robot designs based on biological inspirations are also strongly featured.
Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities—and provides co-design and co-optimization methodologies for building hardware neural networks that can learn. Presenting a complete picture from high-level algorithm to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers many fundamentals and essentials in neural networks (e.g., deep learning), as well as hardware implementation of neural networks. The book begins with an overview of neural networks. It then discusses algorithms for utilizing and training rate-based artificial neural networks. Next comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specialized hardware, from digital accelerator to analog accelerator. A design example on building energy-efficient accelerator for adaptive dynamic programming with neural networks is also presented. An examination of fundamental concepts and popular learning algorithms for spiking neural networks follows that, along with a look at the hardware for spiking neural networks. Then comes a chapter offering readers three design examples (two of which are based on conventional CMOS, and one on emerging nanotechnology) to implement the learning algorithm found in the previous chapter. The book concludes with an outlook on the future of neural network hardware. Includes cross-layer survey of hardware accelerators for neuromorphic algorithms Covers the co-design of architecture and algorithms with emerging devices for much-improved computing efficiency Focuses on the co-design of algorithms and hardware, which is especially critical for using emerging devices, such as traditional memristors or diffusive memristors, for neuromorphic computing Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design is an ideal resource for researchers, scientists, software engineers, and hardware engineers dealing with the ever-increasing requirement on power consumption and response time. It is also excellent for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities.
Designed to conform to the ISO/IEC standard 14143, the Common Software Measurement International Consortium (COSMIC) Function Point method has become the major estimation technique based on international standards for building software-intensive systems. COSMIC Function Points: Theory and Advanced Practices supplies a cutting-edge look at current a
The manufacturing industry will reap significant benefits from encouraging the development of digital manufacturing science and technology. Digital Manufacturing Science uses theorems, illustrations and tables to introduce the definition, theory architecture, main content, and key technologies of digital manufacturing science. Readers will be able to develop an in-depth understanding of the emergence and the development, the theoretical background, and the techniques and methods of digital manufacturing science. Furthermore, they will also be able to use the basic theories and key technologies described in Digital Manufacturing Science to solve practical engineering problems in modern manufacturing processes. Digital Manufacturing Science is aimed at advanced undergraduate and postgraduate students, academic researchers and researchers in the manufacturing industry. It allows readers to integrate the theories and technologies described with their own research works, and to propose new ideas and new methods to improve the theory and application of digital manufacturing science.
Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking.
RuleML 2003 was the second international workshop on rules and rule markup languages for the Semantic Web, held in conjunction with the International Semantic Web Conference (ISWC). The aim of the RuleML workshop series is to stimulate research on all issues related to web rule languages and to provide an annual forum for presenting and discussing new research results. The Semantic Web is a major world-wide endeavor to advance the Web by enriching its multimedia document content with propositional information that can be processed by inference-enabled Web applications. Rules and rule markup languages, such as RuleML, will play an important role in the success of the Semantic Web. Rules will act as a means to draw inferences, to express constraints,tospecifypoliciesforreactingtoevents,totransformdata,etc.Rule markup languages will allow us to enrich Web ontologies by adding de?nitions of derived concepts, to publish rules on the Web, to exchange rules between di?erent systems and tools, etc. RuleML 2003 built on the success of RuleML 2002, which was held in c- junction with ISWC 2002, Sardinia, Italy. The proceedings of RuleML 2002 can be found at http://www.ceur-ws.org/Vol-60/. Special highlights of the RuleML 2003 workshop were the two invited pres- tationsgivenbyPeterChenon“Rules,XML,andtheERModel”andbyHarold Boley on “Object-Oriented RuleML: User-Level Roles, URI-Grounded Clauses, and Order-Sorted Terms”. This proceedings volume also contains an invited - per by Francois ̧ Bry and Sebastian Scha?ert on “An Entailment Relation for Reasoning on the Web”.
This book presents high-quality research papers presented at the 3rd International Conference on Intelligent Computing and Advances in Communication (ICAC 2020) organized by Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India, in November 2020. This book brings out the new advances and research results in the fields of theoretical, experimental, and applied signal and image processing, soft computing, networking, and antenna research. Moreover, it provides a comprehensive and systematic reference on the range of alternative conversion processes and technologies.
This book is a collection of high-quality research articles. The book includes topics specific to the emerging areas of control for robotic systems, wireless communication, and development of embedded systems for robotic applications. The book integrates three important aspects of automation, namely (i) communication, (ii) control, and (iii) embedded design for robotic applications. This book is unique as it provides a unified framework for analysis, design, and deployment of the robotic applications across various engineering and non-engineering disciplines including the three primary aspects mentioned above. Furthermore, the emerging research and development work pertaining to the deployment of intelligent, nonlinear, and embedded control for robotic system for non-standard operating environment due to the widespread application of robotics technology for societal benefit is also a focal point of the book.
Metaheuristic algorithms are present in various applications for different domains. Recently, researchers have conducted studies on the effectiveness of these algorithms in providing optimal solutions to complicated problems. Advancements in Applied Metaheuristic Computing is a crucial reference source for the latest empirical research on methods and approaches that include metaheuristics for further system improvements, and it offers outcomes of employing optimization algorithms. Featuring coverage on a broad range of topics such as manufacturing, genetic programming, and medical imaging, this publication is ideal for researchers, academicians, advanced-level students, and technology developers seeking current research on the use of optimization algorithms in several applications.