Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy.
In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering.
This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source.
Автор: Millington Название: Artificial Intelligence for Games,Third Edition ISBN: 1138483974 ISBN-13(EAN): 9781138483972 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Artificial Intelligence is an integral part of every video game. This book helps propfessionals keep up with the constantly evolving technological advances in the fast growing game industry and equips students with up-to-date infortmation they need to jumpstart their careers.
Автор: Bohr, Adam Название: Artificial Intelligence In Healthcare ISBN: 0128184388 ISBN-13(EAN): 9780128184387 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Artificial Intelligence in Healthcare Data is more than a comprehensive introduction to artificial intelligence and machine learning. The book is split into two sections with an introduction to current healthcare data challenges that is followed by specific applications and case studies. The editors explore how AI is used as a tool in the analysis of healthcare data, specifically focusing on machine learning, deep learning, natural language processing. data privacy, cybersecurity and the ethics. Other sections explore how AI tools can help to interrogate data across a range of healthcare applications, including AI driven wearables and sensors and AI assisted surgery.
This book will be useful for researchers, graduate students and practitioners in computer science, data science, bioinformatics, health informatics, biomedical engineering and clinical engineering.
Автор: Millington, Ian, Funge, John Название: Artificial Intelligence for Games ISBN: 0123747317 ISBN-13(EAN): 9780123747310 Издательство: Taylor&Francis Рейтинг: Цена: 10870.00 р. Наличие на складе: Поставка под заказ.
Описание: Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional experience to the problem of improving the quality of AI in games. He describes numerous examples from real games and explores the underlying ideas through detailed case studies. He goes further to introduce many techniques little used by developers today. The book's associated web site contains a library of C++ source code and demonstration programs, and a complete commercial source code library of AI algorithms and techniques.<br><br>"Artificial Intelligence for Games - 2nd edition" will be highly useful to academics teaching courses on game AI, in that it includes exercises with each chapter. It will also include new and expanded coverage of the following: AI-oriented gameplay; Behavior driven AI; Casual games (puzzle games). <br><br>* The first comprehensive, professional tutorial and reference to implement true AI in games written by an engineer with extensive industry experience.<br>* Walks through the entire development process from beginning to end.<br>* Includes examples from over 100 real games, 10 in-depth case studies, and web site with sample code.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Автор: West Darrell M. Название: The Future of Work: Robots, Ai, and Automation ISBN: 0815737866 ISBN-13(EAN): 9780815737865 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 2911.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Looking for ways to handle the transition to a digital economy. Robots, artificial intelligence, and driverless cars are no longer things of the distant future. They are with us today and will become increasingly common in coming years, along with virtual reality and digital personal assistants. As these tools advance deeper into everyday use, they raise the question—how will they transform society, the economy, and politics? If companies need fewer workers due to automation and robotics, what happens to those who once held those jobs and don't have the skills for new jobs? And since many social benefits are delivered through jobs, how are people outside the workforce for a lengthy period of time going to earn a living and get health care and social benefits? Looking past today's headlines, political scientist and cultural observer Darrell M. West argues that society needs to rethink the concept of jobs, reconfigure the social contract, move toward a system of lifetime learning, and develop a new kind of politics that can deal with economic dislocations. With the U.S. governance system in shambles because of political polarization and hyper-partisanship, dealing creatively with the transition to a fully digital economy will vex political leaders and complicate the adoption of remedies that could ease the transition pain. It is imperative that we make major adjustments in how we think about work and the social contract in order to prevent society from spiraling out of control. This book presents a number of proposals to help people deal with the transition from an industrial to a digital economy. We must broaden the concept of employment to include volunteering and parenting and pay greater attention to the opportunities for leisure time. New forms of identity will be possible when the "job" no longer defines people's sense of personal meaning, and they engage in a broader range of activities. Workers will need help throughout their lifetimes to acquire new skills and develop new job capabilities. Political reforms will be necessary to reduce polarization and restore civility so there can be open and healthy debate about where responsibility lies for economic well-being. This book is an important contribution to a discussion about tomorrow—one that needs to take place today.
Автор: Dinerstein, Ana Cecilia Pitts, Frederick Harry Название: World beyond work? automation basic inco ISBN: 1787691462 ISBN-13(EAN): 9781787691469 Издательство: Emerald Рейтинг: Цена: 3657.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book mounts a forceful critique of fashionable thinking on the possibility of a post-work, post-capitalist society achieved through automation, a basic income and the reduction of working hours to zero, suggesting this popular utopia is nothing of the sort.
Showcases the latest trends in new virtual/augmented reality healthcare and medical applications and provides an overview of the economic, psychological, educational and organizational impacts of these new applications and how we work, teach, learn and provide care.
With the current advances in technology innovation, the field of medicine and healthcare is rapidly expanding and, as a result, many different areas of human health diagnostics, treatment and care are emerging. Wireless technology is getting faster and 5G mobile technology allows the Internet of Medical Things (IoMT) to greatly improve patient care and more effectively prevent illness from developing.
This book provides an overview and review of the current and anticipated changes in medicine and healthcare due to new technologies and faster communication between users and devices.
The groundbreaking book presents state-of-the-art chapters on many subjects including:
A review of the implications of Virtual Reality (VR) and Augmented Reality (AR) healthcare applications
A review of current augmenting dental care
An overview of typical human-computer interaction (HCI) that can help inform the development of user interface designs and novel ways to evaluate human behavior to responses in VR and other new technologies
A review of telemedicine technologies
Building empathy in young children using augmented reality
AI technologies for mobile health of stroke monitoring & rehabilitation robotics control
Mobile doctor brain AI App
An artificial intelligence mobile cloud computing tool
Development of a robotic teaching aid for disabled children
Training system design of lower limb rehabilitation robot based on virtual reality
Описание: With this practical book, author Lomit Patel shows you how to use AI and automation to provide an operational layer atop those acquisition solutions to deliver amazing results for your company.
Автор: Fa–Long Luo Название: Machine Learning for Future Wireless Communications ISBN: 1119562252 ISBN-13(EAN): 9781119562252 Издательство: Wiley Рейтинг: Цена: 18683.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A comprehensive review to the theory, application and research of machine learning for future wireless communications
In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities.
Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author - a noted expert on the topic - covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource:
Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks
Covers a range of topics from architecture and optimization to adaptive resource allocations
Reviews state-of-the-art machine learning based solutions for network coverage
Includes an overview of the applications of machine learning algorithms in future wireless networks
Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing
Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
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