Multimodal Analytics For Next Generation Big Data Technologies And Applications

This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications. The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.

This book presents soft computing techniques and applications used in healthcare systems, along with the latest advancements. Written as a guide for assessing the roles that these techniques play, the book also highlights implementation strategies, lists problem-solving solutions, and paves the way for future research endeavors in smart and next-generation healthcare systems. This book provides applications of soft computing techniques related to healthcare systems and can be used as a reference guide for assessing the roles that various techniques, such as machine learning, fuzzy logic, and statical mathematics, play in the advancements of smart healthcare systems. The book presents the basics as well as the advanced concepts to help beginners, as well as industry professionals, get up to speed on the latest developments in healthcare systems. The book examines descriptive, predictive, and social network techniques and discusses analytical tools and the important role they play in finding solutions to problems in healthcare systems. A framework of robust and novel healthcare techniques is highlighted, as well as implementation strategies and a setup for future research endeavors. Healthcare Systems Using Soft Computing Techniques is a valuable resource for researchers and postgraduate students in healthcare systems engineering, computer science, information technology, and applied mathematics. The book introduces beginners to—and at the same time brings industry professionals up to speed with—the important role soft computing techniques play in smart healthcare systems.

This book is a collection of papers in the research area of big data, cloud computing, cybersecurity, machine learning, deep learning, e-learning, Internet of Things, reinforcement learning, information system, social media and natural language processing. This book includes papers presented at the 5th International Conference on Big Data Cloud and Internet of Things, BDIoT 2021 during March 17–18, 2021, at ENSIAS, Mohammed V University in Rabat, Morocco.

This two-volume set LNCS 13185 and 13186 constitutes the refereed proceedings of the 44th European Conference on IR Research, ECIR 2022, held in April 2022, due to the COVID-19 pandemic. The 35 full papers presented together with 11 reproducibility papers, 13 CLEF lab descriptions papers, 12 doctoral consortium papers, 5 workshop abstracts, and 4 tutorials abstracts were carefully reviewed and selected from 395 submissions.

The Rise of Smart Cities: Advanced Structural Sensing and Monitoring Systems provides engineers and researchers with a guide to the latest breakthroughs in the deployment of smart sensing and monitoring technologies. The book introduces readers to the latest innovations in the area of smart infrastructure-enabling technologies and howthey can be integrated into the planning and design of smart cities. With this book in hand, readers will find a valuable reference in terms of civil infrastructure health monitoring, advanced sensor network architectures, smart sensing materials, multifunctional material and structures, crowdsourced/social sensing, remote sensing and aerial sensing, and advanced computation in sensornetworks. Reviews the latest development in smart structural health monitoring (SHM) systems Introduces all major algorithms, with a focus on practical implementation Includes real-world applications and case studies Opens up a new horizon for robust structural sensing methods and their applications in smart cities

This seven-volume set LNCS 14054-14060 constitutes the proceedings of the 25th International Conference, HCI International 2023, in Copenhagen, Denmark, in July 2023. For the HCCII 2023 proceedings, a total of 1578 papers and 396 posters was carefully reviewed and selected from 7472 submissions. Additionally, 267 papers and 133 posters are included in the volumes of the proceedings published after the conference, as “Late Breaking Work”. These papers were organized in the following topical sections: HCI Design and User Experience; Cognitive Engineering and Augmented Cognition; Cultural Issues in Design; Technologies for the Aging Population; Accessibility and Design for All; Designing for Health and Wellbeing; Information Design, Visualization, Decision-making and Collaboration; Social Media, Creative Industries and Cultural Digital Experiences; Digital Human Modeling, Ergonomics and Safety; HCI in Automated Vehicles and Intelligent Transportation; Sustainable Green Smart Cities and Smart Industry; eXtended Reality Interactions; Gaming and Gamification Experiences; Interacting with Artificial Intelligence; Security, Privacy, Trust and Ethics; Learning Technologies and Learning Experiences; eCommerce, Digital Marketing and eFinance.

With AI advancements eliciting imminent changes to our transport systems, this enlightening Handbook presents essential research on this evolution of the transportation sector. It focuses on not only urban planning, but relevant themes in law and ethics to form a unified resource on the practicality of AI use.

This book covers the latest advances in Big Data technologies and provides the readers with a comprehensive review of the state-of-the-art in Big Data processing, analysis, analytics, and other related topics. It presents new models, algorithms, software solutions and methodologies, covering the full data cycle, from data gathering to their visualization and interaction, and includes a set of case studies and best practices. New research issues, challenges and opportunities shaping the future agenda in the field of Big Data are also identified and presented throughout the book, which is intended for researchers, scholars, advanced students, software developers and practitioners working at the forefront in their field.