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This book reviews the state of the art of big data analysis, artificial intelligence, and smart environments. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science, artificial intelligence, and smart environments inspire novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. This book reviews the state of the art of big data analysis, artificial intelligence, and smart environments. It includes issues that pertain to signal processing, probability models, machine learning, data mining, database, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. The papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart city in particular.The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers, and industrial researchers, as well as anyone interested in big data analysis and artificial intelligence.

This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems – theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.

This book constitutes the refereed proceedings of the 11th International Conference on Social Robotics, ICSR 2019, held in Madrid, Spain, in November 2019.The 69 full papers presented were carefully reviewed and selected from 92 submissions. The theme of the 2018 conference is: Friendly Robotics.The papers focus on the following topics: perceptions and expectations of social robots; cognition and social values for social robots; verbal interaction with social robots; social cues and design of social robots; emotional and expressive interaction with social robots; collaborative SR and SR at the workplace; game approaches and applications to HRI; applications in health domain; robots at home and at public spaces; robots in education; technical innovations in social robotics; and privacy and safety of the social robots.

This book constitutes the refereed proceedings of the 12th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2017, held in Beijing, China June 30 – July 1, 2017. The 26 papers presented were carefully reviewed and selected from 78 submissions. They provide a forum for sharing progresses in the areas of image processing technology; image analysis and understanding; computer vision and pattern recognition; big data mining, computer graphics and VR; as well as image technology applications

As information technologies (IT) become specialized and fragmented, it is easy to lose sight that many topics in IT have common threads and because of this, advances in one sub-discipline may transmit to another. The presentation of results between di?erent sub-disciplines of IT encourages this interchange for the advancement of IT as a whole. Of particular interest is the hybrid approach or combining ideas from one discipline with those of another to achieve a result that is more signi?cant than the sum of the individual parts. Through this hybrid philosophy, a new or common principle can be discovered which has the propensity to propagate throughout this multifaceted discipline. This volume comprises the selection of extended versions of papers that were presentedintheirshortenedformatthe2006InternationalConferenceonHybrid InformationTechnology(http://www.sersc.org/ICHIT2006/).Sixty-four papers out of the 235 that were published in ICHIT 2006 electronic proceedings were deemed suitable for inclusion in this volume, in a selection that was guided by technical quality and relevance to the balance of topics in hybrid information technology. The conference re?ected a change in the thinking of scientists and practitioners,whonowtendtojointheire?ortswithinmultidisciplinaryprojects. As a consequence, the readers may observe that many papers might conceivably be classi?ed into more than one chapter, given their interdisciplinary scope. The contributions in this monograph are clustered into six chapters: Data Analysis, Modeling, and Learning (11 papers); Imaging, Speech, and Complex Data (11 papers); Applications of Arti?cial Intelligence (11 papers); Hybrid, Smart, and UbiquitousSystems(11papers);HardwareandSoftwareEngineering(9papers); as well as Networking andTelecommunications (11 papers).