The rise of internet and social media usage in the past couple of decades has presented a very useful tool for many different industries and fields to utilize. With much of the world’s population writing their opinions on various products and services in public online forums, industries can collect this data through various computational tools and methods. These tools and methods, however, are still being perfected in both collection and implementation. Sentiment analysis can be used for many different industries and for many different purposes, which could better business performance and even society. The Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines discusses the tools, methodologies, applications, and implementation of sentiment analysis across various disciplines and industries such as the pharmaceutical industry, government, and the tourism industry. It further presents emerging technologies and developments within the field of sentiment analysis and opinion mining. Covering topics such as electronic word of mouth (eWOM), public security, and user similarity, this major reference work is a comprehensive resource for computer scientists, IT professionals, AI scientists, business leaders and managers, marketers, advertising agencies, public administrators, government officials, university administrators, libraries, students and faculty of higher education, researchers, and academicians.

As social robots and the artificial intelligence (AI) that powers them become more advanced, they will likely take on more social and work roles. There is a variety of ways social robots can be engaged in human life, and they can leave an impact in terms of ease of use, productivity, and human support. The interactivity and receptivity of social robots can encourage humans to form social relationships with them. But now robots are intended to perform socially intelligent and interactive services like reception, guidance, emotional companionship, and more, which makes social human-robot interaction essential to help improve aspects of quality of life as well as to improve the efficiency of human care services. AI-Enabled Social Robotics in Human Care Services addresses recent advances in the latest technologies, new research results, and developments in the area of social robotics and AI and the latest developments in the field and future directions that can be beneficial to human society and human care services. Covering topics such as agriculture waste management systems, elder care, and facial emotion recognition, this premier reference source is an essential resource for AI professionals, computer scientists, robotics engineers, human care professionals, students and educators of higher education, librarians, researchers, and academicians.

This book is intended to survey the Internet of Behavior (IoB). The book begins with the benefits and potential pitfalls of IoB. Today, IoB has huge potential in every sector of the world. There are numerous applications for IoB which benefit users as well as the business market in order to enhance the user experience. In this book, the benefits of IoB and its negative constraints are discussed in detail. It is a high time that IoB is to take its crown and ruled the world. The work of IoB is critical in keeping our data secure because it can currently identify all humans who attempt to steal someone’s data. Moreover, the business uses of IoB are in high demand. By leveraging promising technical improvements and advances in machine learning algorithms, IoB enables capture, analysis, comprehension, and response for all types of human behavior in a technique that enables the tracking and interpretation of the behavior. IoB can be very useful wherever the behavior, preferences, interests, and location of people need to be examined. On the other hand, an analytical study on consumers’ social and behavioral psychology and their influence on online purchasing is much needed. With the help of visualization tools such as Tableau and detailed reporting on selection patterns, the impact of social media on decision making and the relationship between personality and purchasing power in various age groups is found. The presented study lists major decision-making psychometric factors and highlights critical factors affecting online purchases. The role of IoB is to shape customer service through the use of artificial intelligence, cloud computing, data, smart analytics, machine learning, and other volatile technologies. The attractive components of this book are discussions of dynamic routing mechanisms to reduce energy consumption in software-defined networks; deep insight into Internet of Things (IoT) and IoB security and privacy concerns – applications and future challenges; sentiment analysis and feature reduction using an arboreal monkey compression algorithm with a deep modified neural network classifier; cybersecurity concerns for IoB; and identification of nutrients and microbial contamination in fruits and vegetables using a technology using the Internet of Behavior. There is no doubt that this book covers numerous interesting themes and details on the Internet of Behavior.

Deep learning and reinforcement learning are some of the most important and exciting research fields today. With the emergence of new network structures and algorithms such as convolutional neural networks, recurrent neural networks, and self-attention models, these technologies have gained widespread attention and applications in fields such as natural language processing, medical image analysis, and Internet of Things (IoT) device recognition. This book, Deep Learning and Reinforcement Learning examines the latest research achievements of these technologies and provides a reference for researchers, engineers, students, and other interested readers. It helps readers understand the opportunities and challenges faced by deep learning and reinforcement learning and how to address them, thus improving the research and application capabilities of these technologies in related fields.

This nine-volume set LNCS 14104 – 14112 constitutes the refereed workshop proceedings of the 23rd International Conference on Computational Science and Its Applications, ICCSA 2023, held at Athens, Greece, during July 3–6, 2023. The 350 full papers and 29 short papers and 2 PHD showcase papers included in this volume were carefully reviewed and selected from a total of 876 submissions. These nine-volumes includes the proceedings of the following workshops: Advances in Artificial Intelligence Learning Technologies: Blended Learning, STEM, Computational Thinking and Coding (AAILT 2023); Advanced Processes of Mathematics and Computing Models in Complex Computational Systems (ACMC 2023); Artificial Intelligence supported Medical data examination (AIM 2023); Advanced and Innovative web Apps (AIWA 2023); Assessing Urban Sustainability (ASUS 2023); Advanced Data Science Techniques with applications in Industry and Environmental Sustainability (ATELIERS 2023); Advances in Web Based Learning (AWBL 2023); Blockchain and Distributed Ledgers: Technologies and Applications (BDLTA 2023); Bio and Neuro inspired Computing and Applications (BIONCA 2023); Choices and Actions for Human Scale Cities: Decision Support Systems (CAHSC-DSS 2023); and Computational and Applied Mathematics (CAM 2023).

The term ‘intelligent environment’ (IE) refers to a physical space that is enhanced by digital technologies. Such environments are designed to improve the quality of life of the people who live or work in them, and are equipped with technologies such as sensing systems and artificial intelligence which can detect changes in the environment, anticipate user requirements, and provide personalized services and experiences to users. This book presents presents papers from Workshops held during the first two days of IE2023, the 19th International Conference on Intelligent Environments, held in Mauritius between 27 and 30 June 2023, with an online participation available for those who could not travel to the island. The papers are grouped under the headings of the various workshops: the 12th International Workshop on the Reliability of Intelligent Environments (WoRIE’23); the 3rd International Workshop on Artificial Intelligence and Machine Learning for Emerging Topics (ALLEGET’23); the 3rd International Workshop on Self-Learning in Intelligent Environments (SeLIE’23); the 2nd International Workshop on Edge AI for Smart Agriculture (EAISA’23); and the 12th International Workshop on Intelligent Environments Supporting Healthcare and Well-being (WISHWell’2023), and represent a diverse array of cutting-edge research reflective of this exciting area of study. The book offers an overview of the latest and most exciting developments in intelligent-environments research, and will be of interest to all those working in the field.

This book focuses on the main advancements made in the economics and social sciences field through the use of grey systems theory. As a result, it addresses both the state of the art and the applications of grey systems theory in economics and social sciences. The book is structured in eight main chapters, covering the following topics: the state of the art in the grey systems theory research in economics and social sciences, which includes a bibliometric analysis, a selection of the most well-cited papers in the field, and a selection of applications in which the grey systems theory is used in the areas of suppliers selection, risk assessment, public opinion assessment, linear programming, complex projects management, social media analysis, and natural language processing Each chapter gives an overview of a particular economic or social sciences topic, providing an explanation on the main terms and methods used for solving the problem, including the notations, terminology, and the needed steps to solve it. A practical application is presented in most of the chapters, while in the others, a series of case studies are presented from the literature and discussed in depth in terms of methods used and advantages brought by each of these methods. The last chapter discusses the hybridization cases in which the grey systems theory has been or can be successfully used along with other artificial intelligence methods and techniques for a more advanced analysis in the economics and social sciences field. The reasoning and the explanations used in the book are easy to understand for the interested persons who are not familiar to the field and want to learn more related on how the grey systems theory can be applied to economics and social sciences. As for the experts in this field, this book can be a good referral point for developing new areas of research by combining the advantages of the grey systems theory with other theories within the field.

In the evolving landscape of Web3, the use of advanced machine learning, artificial intelligence, and cybersecurity transforms industries through theoretical exploration and practical application. The integration of advanced machine learning and AI techniques promises enhanced security protocols, predictive analytics, and adaptive defenses against the increasing number of cyber threats. However, these technological improvements also raise questions regarding privacy, transparency, and the ethical implications of AI-driven security measures. Advanced Machine Learning, AI, and Cybersecurity in Web3: Theoretical Knowledge and Practical Application explores theories and applications of improved technological techniques in Web 3.0. It addresses the challenges inherent to decentralization while harnessing the benefits offered by advances, thereby paving the way for a safer and more advanced digital era. Covering topics such as fraud detection, cryptocurrency, and data management, this book is a useful resource for computer engineers, financial institutions, security and IT professionals, business owners, researchers, scientists, and academicians.