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Proceedings of the 12th International Symposium on Computer Science in Sport (IACSS 2019)
This book provides an overview of current activities in the fascinating area between computer science and sports, presenting the state of the art in utilising the latest developments in computer science to support sports coaches and athletes. It covers a broad range of topics reflecting the diversity of this interdisciplinary field, including concepts in informatics like expert systems, modelling, simulation, machine learning, robotics, and sensor integration. Further, it describes applications of computer science in sports, such as alpine skiing, badminton, football, rowing, and table tennis, as well as interesting applications areas of sport like dementia, physiology, training, and space flights. The appeals to informaticians interested in the application field of sports as well as for sports scientists and practitioners looking for advanced methods in their particular sport.
Advances in Artificial Systems for Medicine and Education V
This book broadly covers a scope of the latest advances for the development of artificial intelligence systems and their applications in various fields from medicine and technology to education. The proceedings comprise refereed papers presented at the Fifth International Conference of Artificial Intelligence, Medical Engineering, and Education (AIMEE2021), which took place at the Mechanical Engineering Institute of the Russian Academy of Sciences, Moscow, Russia, on 1–3 October 2021. Given the rapid development of artificial intelligence systems, the book emphasizes the need for the intensification of training of a growing number of relevant specialists, in particular, in medical engineer...
AI for Sports
It seems that artificial intelligence (AI) is always just five years away, but it never arrives. Recently, however. developments have made the practical utility of game theory a genuine reality. Will sport provide the petri dish in which AI will prove itself? What do domain specialists like managers and coaches want to know that they can’t currently find out, and can AI provide the answer? What competitive advantages might AI provide for recruitment, performance and tactics, health and fitness, pedagogy, broadcasting, eSports, gambling and stadium design in the future? Written by leading experts in both sports management and AI, AI for Sports begins to answer these and many other questions on the future of AI for sports.
Social Movements, Cultural Memory and Digital Media
This collected volume is the first to study the interface between contemporary social movements, cultural memory and digital media. Establishing the digital memory work practices of social movements as an important area of research, it reveals how activists use digital media to lay claim to, circulate and curate cultural memories. Interdisciplinary in scope, its contributors address mobilizations of mediated remembrance in the USA, Germany, Sweden, Italy, India, Argentina, the UK and Russia.
Ecological Informatics
Ecological Informatics promotes interdisciplinary research between ecology and computer science on elucidation of principles of information processing in ecosystems, ecological sustainability by informed decision making, and bio-inspired computation. The 2nd edition of the book consolidates the scope, concepts, and techniques of this newly emerging discipline by a new preface and additional chapters on cellular automata, qualitative reasoning, hybrid evolutionary algorithms and artificial neural networks. It illustrates numerous applications of Ecological Informatics for aquatic and terrestrial ecosystems, image recognition at micro- and macro-scale as well as computer hardware design. Case studies focus on applications of artificial neural networks, evolutionary computation, cellular automata, adaptive agents, fuzzy logic as well as qualitative reasoning. The 2nd edition of the book includes an index with novel evolutionary algorithms for the discovery of multiple nonlinear functions and rule sets as well as parameter optimisation in complex ecological data.
