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Advanced soft electronics in biomedical engineering : materials, manufactures, and applications

Presents the latest advances in soft electronics in biomedical engineering and its potential applications in various biomedical fields. Provide comprehensive coverage of how soft electronics are used in diagnostics and monitoring, medical therapy, neural engineering, and wearable and implantable systems. In particular, some emerging research areas such as advanced soft robotics, fiber sensing technologies, and power optimization strategies are explored. In addition, the book highlights international standardization activities in wearable technologies and implantable bioelectronics.

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Machine-learning-assisted intelligent processing and optimization of complex systems

Focuses on the most recent developments in intelligent optimization methods and their applications in various test cases. The reprint covers various topics, including distributed multiagent modeling, metaheuristic algorithms, multisource data fusion, mobile computing and mobile sensing, machine learning-based intelligent processing for modeling complex manufacturing systems, and data-driven intelligent modeling

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Machine Learning Techniques and Analytics for Cloud Security

covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions

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Machine learning in healthcare : Fundamentals and recent applications

Discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises.

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Machine Learning for Cyber Physical Systems : Selected papers from the International Conference ML4CPS 2020

Presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020.

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Machine learning and deep learning in medical data analytics and healthcare applications

Introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.

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Biomimetic neural learning for intelligent robots : Intelligent systems, cognitive robotics, and neuroscience

This book presents research performed as part of the EU project on biomimeticmultimodal learning in a mirror neuron-based robot (MirrorBot) and contribu-tions presented at the International AI-Workshop on NeuroBotics. The over-all aim of the book is to present a broad spectrum of current research intobiomimetic neural learning for intelligent autonomous robots. In this book we show the development of newtechniques using cell assemblies, associative neural networks, and Hebbian-typelearning in order to associate vision, language and motor concepts. We havedeveloped biomimetic multimodal learning and language instruction in a robotto investigate the task of searching for objects. As well as the research performedin this area for the MirrorBot project, the second part of this book incorporatessignificant contributions from other research in the field of biomimetic robotics.This second part of the book concentrates on the progress made in neuroscienceinspired robotic learning approaches (in short: NeuroBotics). We hope that this book stimulates and encourages new research in this in-teresting and dynamic area.

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Autonomy oriented computing : From problem solving to complex systems modeling

Autonomy Oriented Computing explores the important theoretical and practical issues in AOC, by analyzing methodologies and presenting experimental case studies. The book serves as a comprehensive reference source for researchers, scientists, engineers, and professionals in all fields concerned with this promising new development in computer science. It can also be used as a main or supplementary text in graduate and undergraduate programs across a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing and Computer Vision, Programming Paradigms, Computational Biology, and many others. The first part of the book, Fundamentals, describes the basic concepts and characteristics of an AOC system, and then it enumerates the critical design and engineering issues faced in AOC system development. The second part of the book, AOC in Depth, provides a detailed analysis of methodologies and case studies to evaluate the use of AOC in problem solving and complex system modeling. The final chapter reviews the essential features of the AOC paradigm and outlines a number of possibilities for future research and development.

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Autonomes fahren : Technische, rechtliche und gesellschaftliche aspekte = Autonomous driving : Technical, legal and social aspects

This book provides answers to a wide range of these and other questions. Experts from Germany and the USA describe central topics related to the automation of vehicles on public roads from an engineering and social science perspective. They show which "decisions" are required of an autonomous vehicle or which "ethics" must be programmed. The authors discuss expectations and concerns that characterize the individual and societal acceptance of autonomous driving. An increased safety potential through autonomous vehicles is compared to the challenges and solution approaches that play a role in securing the safety concept. In addition, they explain what possibilities for change and opportunities arise for our mobility and the reorganization of traffic, not least for freight traffic. The book thus offers an up-to-date, comprehensive and scientifically sound examination of the topic of "autonomous driving".

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Assistive technologies, robotics, and automated machines in the health domain

The field of healthcare is constantly evolving and advancing with new technologies and innovations. Among these, assistive technologies, robotics, and automated machines are rapidly gaining ground as powerful tools to improve the quality of care and enhance patient outcomes. From wearable devices that monitor vital signs to surgical robots that assist in complex procedures, these technologies have the potential to revolutionize the way we deliver healthcare. The development and the integration of assistive technologies, care robots, and automated machines are strategic both as single components, when paired together, and when interconnected in the health domain.This reprint explores the latest developments in assistive technologies, robotics, and automated machines in the health domain, providing a comprehensive overview of their applications and potential impact. The reprint is for the benefit of healthcare professionals, researchers, engineers, and students interested in these rapidly evolving fields.

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Artificial life models in software

Artificial Life Models in Software presents software tools, environments and realities dealing with creation, imitation and analysis of artefactual, virtual and living forms, written by those who personally design and produce software, hardware and art installations in artificial life, simulated complex systems and virtual worlds. This timely volume offers a nearly exhaustive overview and original analysis of major non-profit artificial life software packages. The carefully selected topics include: · simulation of real and imaginary life forms and their evolution · self-organization · emergent behaviours · swarm intelligence · evolutionary robotics · agent-based simulations · adaptive, complex and biologically inspired ecosystems · creative computer art There has long been a need within the academic and research community for an informal introduction and guidance to modern software tools for modelling and simulation of life-like phenomena – Artificial Life Models in Software fills this gap and provides invaluable information to both professional and amateur readers, offering detailed reviews of contemporary software for artificial life.

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Artificial intelligence in higher education : A practical approach

Highlights the broad field of artificial intelligence applications in education, regarding any type of artificial intelligence that is correlated with education. It discusses learning methodologies, intelligent tutoring systems, intelligent student guidance and assessments, intelligent education chatbots, and artificial tutors and presents the practicality and applicability implications of AI in education. The book offers new and current research along with case studies showing the latest techniques and educational activities. Will find interest with academicians which includes teachers, students of various disciplines, higher education policymakers who believe in transforming the education industry, research scholars who are pursuing their Ph.D. or Post Doc. in the field of Education Technology, Education, and Learning, etc. and those working in the area of Education Technology and Artificial Intelligence such as industry professionals in education management and e-learning companies

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Artificial Intelligence : Applications and innovations

It's about the science of artificial intelligence (AI). AI is the study of the design of intelligent computational agents. This book provides a valuable resource for researchers, scientists, professionals, academicians and students dealing with the new challenges and advances in the areas of AI and innovations. This book also covers a wide range of applications of machine learning such as fire detection, structural health and pollution monitoring and control. Provides insight into prospective research and application areas related to industry and technology / Discusses industry- based inputs on success stories of technology adoption / Discusses technology applications from a research perspective in the field of AI / Provides a hands- on approach and case studies for readers of the book to practice and assimilate learning

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Artificial intelligence : A modern approach ; global ed.

Explores the full breadth and depth of the field of artificial intelligence (AI). The 4th edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multi agent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI

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Application of computational electromagnetics techniques and artificial intelligence in the engineering

Introduces the latest developments in electromagnetic computing and artificial intelligence technology. Artificial intelligence technology can be applied to the modeling, analysis, and optimization design of microwave equipment, solving the routing problem of self-organizing networks in small unmanned aerial vehicle systems, calculating the radiation characteristics of antenna arrays on large electrical platforms, analyzing the impact of electromagnetic wave coupling on electronic devices, simulating the field distribution characteristics of electronic devices, and so on. With the help of artificial intelligence, designers can more conveniently, quickly, and accurately solve engineering problems.

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Anticipatory Behavior in Adaptive Learning Systems : From Brains to Individual and Social Behavior

Anticipatory behavior in adaptive learning systems is steadily gaining the - terest of scientists, although many researchers still do not explicitly consider the actual anticipatory capabilities of their systems.The introductory chapter of this volume therefore does not only provide an overview of the contributions included in this volume but also proposes a taxonomy of how anticipatory mechanisms can improve adaptive behavior and learning in cognitive systems. During the workshop it became clear that ant- ipations are involved in various cognitive processes that range from individual anticipatory mechanisms to social anticipatory behavior.

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Ant Colony Optimization and Swarm Intelligence ; 6th International Conference, ANTS 2008, Brussels, Belgium, September 22-24, 2008. Proceedings

This book constitutes the refereed proceedings of the 6th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008.

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AI in learning : Designing the future

AI (artificial intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning.

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AI For Emerging Verticals : Human-robot computing, sensing and networking

Artificial intelligence (AI) and machine learning (ML) will play a major role. By adopting AI software and services, businesses can create predictive strategies, enhance their capabilities, better interact with customers, and streamline their business processes. Explores novel concepts and cutting-edge research and developments towards designing these fully automated advanced digital systems. Fostered by technological advances in artificial intelligence and machine learning, such systems potentially have a wide range of applications in robotics, human computing, sensing and networking. The chapters focus on models and theoretical approaches to guarantee automation in large multi-scale implementations of AI and ML systems; protocol designs to ensure AI systems meet key requirements for future services such as latency; and optimisation algorithms to leverage the trusted distributed and efficient complex architectures.

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Advances in UAV detection, classification and tracking

Explores the latest techniques and advancements in unmanned aerial vehicle (UAV) detection, classification, and tracking. As UAV technology continues to evolve and become more accessible, there is a growing need for effective methods to detect, identify, and track these devices in various scenarios. This reprint provides a thorough overview of the state-of-the-art approaches for UAV detection, classification, and tracking, covering both theoretical and practical aspects.The reprint begins by introducing the basics of UAVs and their various applications, followed by a detailed overview of the challenges associated with UAV detection, classification, and tracking. The authors then present the latest techniques and algorithms used in the field, including machine-learning-based approaches, computer vision techniques, and sensor fusion techniques. The reprint also covers the challenges of real-world applications, such as dealing with occlusions, sensor noise, and environmental factors.

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