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This research monograph is highly contextual in the present era of spatial/spatio-temporal data explosion. The monograph is primarily prepared for graduate students of Computer Science, who wish to employ probabilistic graphical models, especially Bayesian networks (BNs), for applied research on spatial/spatio-temporal data.

To catch up, many application areas have begun relying on data science, i.e., on techniques for extracting models from data, such as data mining, machine learning, and innovative statistics.

This book provides insights into research in the field of artificial intelligence in combination with robotics technologies.

The novel coronavirus disease 2019 (COVID-19) pandemic has posed a major threat to human life and health. This book is beneficial for interdisciplinary students, researchers, and professionals to understand COVID-19 and how computational intelligence can be used for the purpose of surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease. The book contains different aspects of COVID-19 that includes fundamental knowledge, epidemic forecast models, surveillance and tracking systems, IoT- and IoMT-based integrated systems for COVID-19, social network analysis systems for COVID-19, radiological images (CT, X-ray) based diagnosis system, and computational intelligence and in silico drug design and drug repurposing methods against COVID-19 patients. The contributing authors of this volume are experts in their fields and they are from various reputed universities and institutions across the world. This volume is a valuable and comprehensive resource forcomputer and data scientists, epidemiologists, radiologists, doctors, clinicians, pharmaceutical professionals, along with graduate and research students of interdisciplinary and multidisciplinary sciences.

The novel coronavirus disease 2019 (COVID-19) pandemic has posed a major threat to human life and health. This book is beneficial for interdisciplinary students, researchers, and professionals to understand COVID-19 and how computational intelligence can be used for the purpose of surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease. The book contains different aspects of COVID-19 that includes fundamental knowledge, epidemic forecast models, surveillance and tracking systems, IoT- and IoMT-based integrated systems for COVID-19, social network analysis systems for COVID-19, radiological images (CT, X-ray) based diagnosis system, and computational intelligence and in silico drug design and drug repurposing methods against COVID-19 patients. The contributing authors of this volume are experts in their fields and they are from various reputed universities and institutions across the world. This volume is a valuable and comprehensive resource forcomputer and data scientists, epidemiologists, radiologists, doctors, clinicians, pharmaceutical professionals, along with graduate and research students of interdisciplinary and multidisciplinary sciences.

To catch up, many application areas have begun relying on data science, i.e., on techniques for extracting models from data, such as data mining, machine learning, and innovative statistics.

This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis.

This book is a new contribution aiming to give some last research findings in the field of optimization and computing. The challenge with this work is to gather the main contribution in three fields, optimization technique for production decision, general development for optimization and computing method and wider spread applications.

This book provides stepwise discussion, exhaustive literature review, detailed analysis and discussion, rigorous experimentation results (using several analytics tools), and an application-oriented approach that can be demonstrated with respect to data analytics using artificial intelligence to make systems stronger (i.e., impossible to breach).

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications.

This book proposes a number of promising models and methods for adaptive segmentation, swarm partition, permissible segmentation, and transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and fuzzy systems for information retrieval.

This comprehensive book is primarily intended for researchers, engineers, mathematicians and computer security specialists who are interested in multimedia security, steganography, encryption, and related research fields.

This book builds on decades of research and provides contemporary theoretical foundations for practical applications to intelligent technologies and advances in artificial intelligence (AI). Reflecting the growing realization that computational models of human reasoning and interactions can be improved by integrating heterogeneous information resources and AI techniques, its ultimate goal is to promote integrated computational approaches to intelligent computerized systems. The book covers a range of interrelated topics, in particular, computational reasoning, language, syntax, semantics, memory, and context information. The respective chapters use and develop logically oriented methods and techniques, and the topics selected are from those areas of logic that contribute to AI and provide its mathematical foundations.The intended readership includes researchers working in the areas of traditional logical foundations, and onnew approaches to intelligent computational systems.

This book includes original research findings in the field of memetic algorithms for image processing applications.

With the proliferation of technology, science became a medium used to create and interpret heritage in a way that redefines human achievements.

This book discusses the challenges facing current research in knowledge discovery and data mining posed by the huge volumes of complex data now gathered in various real-world applications (e.g., business process monitoring, cybersecurity, medicine, language processing, and remote sensing).

This book provides step-by-step explanations of successful implementations and practical applications of machine learning. deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning);

This book discusses heuristic methods - methods lacking a solid theoretical justification - which are ubiquitous in numerous application areas, and explains techniques that can make heuristic methods more reliable.

This book discusses various aspects of Industry 4.0 from the perspective of information system evolution. The interdisciplinary book addresses a number of topics related to modern information technologies, and presents innovative concepts, methods, models and tools for the development of information systems to support Industry 4.0.

Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models.

Mainly focusing on processing uncertainty, this book presents state-of-the-art techniques and demonstrates their use in applications to econometrics and other areas. Measurement uncertainty is usually described using probabilistic techniques, while uncertainty in expert estimates is often described using fuzzy techniques.

This book is useful to understand and write alongside non-human agents, examine the impact of algorithms and AI on writing, and accommodate relationships with autonomous agents. This book prepares researchers, students, practitioners, and citizens to work with AI writers, virtual humans, and social robots.