Artificial intelligent systems, which offer great improvement in healthcare sector assisted by machine learning, wireless communications, data analytics, cognitive computing, and mobile computing provide more intelligent and convenient solutions and services. With the help of the advanced techniques, now a days it is possible to understand human body and to handle & process the health data anytime and anywhere. It is a smart healthcare system which includes patient, hospital management, doctors, monitoring, diagnosis, decision making modules, disease prevention to meet the challenges and problems arises in healthcare industry. Furthermore, the advanced healthcare systems need to upgrade with new capabilities to provide human with more intelligent and professional healthcare services to further improve the quality of service and user experience. To explore recent advances and disseminate state-of-the-art techniques related to intelligent healthcare services and applications. This edited book involved in designing systems that will permit the societal acceptance of ambient intelligence including signal processing, imaging, computing, instrumentation, artificial intelligence, internet of health things, data analytics, disease detection, telemedicine, and their applications. As the book includes recent trends in research issues and applications, the contents will be beneficial to Professors, researchers, and engineers. This book will provide support and aid to the researchers involved in designing latest advancements in communication and intelligent systems that will permit the societal acceptance of ambient intelligence. This book presents the latest research being conducted on diverse topics in intelligence technologies with the goal of advancing knowledge and applications healthcare sector and to present the latest snapshot of the ongoing research as well as to shed further light on future directions in this space. The aim of publishing the book is to serve for educators, researchers, and developers working in recent advances and upcoming technologies utilizing computational sciences.

A guide to AI's thorniest implications that asks: How shall we navigate our brave new world? We are at a monumental turning point in human history. AI is taking intelligence in new directions. The strongest human competitors in chess, go, and Jeopardy! have been beaten by AIs, and AI is getting more sophisticated by the day. Further, AI research is going inside the human brain itself, attempting to augment human minds. It may even create greater-than-human-level intelligence, leading to a new generation of artificial minds-Minds 2.0. Susan Schneider, a philosopher, argues that these undertakings must not be attempted without a richer understanding of the nature of the mind. An insufficient grasp of the underlying philosophical issues could undermine the use of AI and brain enhancement technology, bringing about the demise or suffering of conscious beings. Examining the philosophical questions lying beneath the algorithms, Schneider takes on AI's thorniest implications.

Quantum Inspired Computational Intelligence: Research and Applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and robust intelligent systems. Conventional computational intelligence-or soft computing-is conjoined with quantum computing to achieve this objective. The models covered can be applied to any endeavor which handles complex and meaningful information.

Blockchain is a technology that tends to be misunderstood by managers that need to make technology acquisition decisions. This book will provide readers with a basic understanding of blockchain and distributed ledger technology (DLT), the technologies that underpin it, and the technologies DLT is built upon. The book is purposefully not a book on how to code or explore other technical aspects of blockchain (other than the fundamentals). Rather, it provides managers with the basic understanding of the architectures and consensus algorithms, how they work, the design trade-offs of each architecture type, and what problems and use cases the core characteristics of DLT are best suited to solve providing business managers with the core information they need to ask the right questions of vendors when making business value assessments and acquisition decisions.

Autonomic networking aims to solve the mounting problems created by increasingly complex networks, by enabling devices and service-providers to decide, preferably without human intervention, what to do at any given moment, and ultimately to create self-managing networks that can interface with each other, adapting their behavior to provide the best service to the end-user in all situations. This book gives both an understanding and an assessment of the principles, methods and architectures in autonomous network management, as well as lessons learned from, the ongoing initiatives in the field. It includes contributions from industry groups at Orange Labs, Motorola, Ericsson, the ANA EU Project and leading universities. These groups all provide chapters examining the international research projects to which they are contributing, such as the EU Autonomic Network Architecture Project and Ambient Networks EU Project, reviewing current developments and demonstrating how autonomic management principles are used to define new architectures, models, protocols, and mechanisms for future network equipment.

Although the field of intelligent systems has grown rapidly in recent years, there has been a need for a book that supplies a timely and accessible understanding of this important technology. Filling this need, Case Studies in Intelligent Computing: Achievements and Trends provides an up-to-date introduction to intelligent systems. This edited book captures the state of the art in intelligent computing research through case studies that examine recent developments, developmental tools, programming, and approaches related to artificial intelligence (AI). The case studies illustrate successful machine learning and AI-based applications across various industries, including: A non-invasive and instant disease detection technique based upon machine vision through the image scanning of the eyes of subjects with conjunctivitis and jaundice Semantic orientation-based approaches for sentiment analysis An efficient and autonomous method for distinguishing application protocols through the use of a dynamic protocol classification system Nonwavelet and wavelet image denoising methods using fuzzy logic Using remote sensing inputs based on swarm intelligence for strategic decision making in modern warfare Rainfall-runoff modeling using a wavelet-based artificial neural network (WANN) model Illustrating the challenges currently facing practitioners, the book presents powerful solutions recently proposed by leading researchers. The examination of the various case studies will help you develop the practical understanding required to participate in the advancement of intelligent computing applications. The book will help budding researchers understand how and where intelligent computing can be applied. It will also help more established researchers update their skills and fine-tune their approach to intelligent computing.

In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: "Introduction and Background on Control Theory", "Adaptive Control and Neuroscience", "Adaptive Learning Algorithms", "Cyber-Physical Systems and Cooperative Control", "Applications". The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists. This book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems, including Electrical Engineers, Computer Science Engineers, Mechanical Engineers, Aerospace/Automotive Engineers, and Industrial Engineers. It could be used as a text or reference for advanced courses in complex control systems. * Collection of chapters from several well-known professors and researchers that will showcase their recent work * Presents different state-of-the-art control approaches and theory for complex systems * Gives algorithms that take into consideration the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams * Real system examples and figures throughout, make ideas concrete

INTELLIGENT DECISION SUPPORT SYSTEMS FOR SMART CITY APPLICATIONS This book provides smart city frameworks to address new difficulties by adding new features and allowing the city environment to react to collected data and information to increase the efficiency and sustainability of services for inhabitants. Making a smart city is an emerging strategy to mitigate the problems generated by urban population growth and rapid urbanization. This book aims to provide a better understanding of the concept of smart cities and the application of an intelligent decision support system. Based on the analysis of existing information there are eight critical factors of smart city initiatives: management and organization, technology, governance, policy context, people and communities, economy, built infrastructure, and natural environment. This book will focus on the application of the decision support system in managing these eight crucial aspects of smart cities. The intent in writing this book was also to provide a source that covers the stage-by-stage integration of the four key areas involving planning, physical infrastructure, ICT infrastructure, and deploying the smart solutions necessary for city transformation. With this as the motivation, "Decision Support Systems for Smart City Applications" provides the application of an intelligent decision support system for effectively and efficiently managing the transformation process, which can aid various supply chain stakeholders, academic researchers, and related professionals in building smart cities. Various chapters of this book are expected to support practicing managers during the implementation of smart solutions for city transformation. Audience This book is aimed at both academics and practitioners alike in the fields of intelligent computing, decision support systems, the manufacturing industry, supply chain managers, stakeholders, policymakers, and other technical and administrative personnel.

Robotics for Cell Manipulation and Characterization provides fundamental principles underpinning robotic cell manipulation and characterization, state-of-the-art technical advances in micro/nano robotics, new discoveries of cell biology enabled by robotic systems, and their applications in clinical diagnosis and treatment. This book covers several areas, including robotics, control, computer vision, biomedical engineering and life sciences using understandable figures and tables to enhance readers' comprehension and pinpoint challenges and opportunities for biological and biomedical research.

This book serves as the first guideline of the integrative approach, optimal for our new and young generations. Recent technology advancements in computer vision, IoT sensors, and analytics open the door to highly impactful innovations and applications as a result of effective and efficient integration of those. Such integration has brought to scientists and engineers a new approach -the integrative approach. This offers far more rapid development and scalable architecting when comparing to the traditional hardcore developmental approach. Featuring biomedical and healthcare challenges including COVID-19, we present a collection of carefully selective cases with significant added- values as a result of integrations, e.g., sensing with AI, analytics with different data sources, and comprehensive monitoring with many different sensors, while sustaining its readability.

This book brings together intelligence systems and the Internet of Things, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI and IoT to develop future strategies and to achieve sustainability goals. EAMMIS 2021 was organized by the Bridges Foundation in cooperation with the Istanbul Medeniyet University, Istanbul, Turkey, on March 19-20, 2021. EAMMIS 2021 theme was Artificial Intelligence Systems and the Internet of Things in the digital era. The papers presented at the conference provide a holistic view of AI education, MIS, cybersecurity, blockchain, Internet of Ideas (IoI), and knowledge management.

This book addresses some of the challenges suffered by the well-known and robust sliding-mode control paradigm. The authors show how the fusion of fuzzy systems with sliding-mode controllers can alleviate some of these problems and promote applicability. Fuzzy systems used as soft switches eliminate high-frequency signal oscillations and can substantially lower the noise sensitivity of sliding-mode controllers. The amount of a priori knowledge required concerning the nominal structure and parameters of a nonlinear system is also shown to be much reduced by exploiting the general function-approximation property of fuzzy systems so as to use them as identifiers. The main features of this book include: * a review of various existing structures of sliding-mode fuzzy control; * a guide to the fundamental mathematics of sliding-mode fuzzy controllers and their stability analysis; * state-of-the-art procedures for the design of a sliding-mode fuzzy controller; * source codes including MATLAB (R) and Simulink (R) codes illustrating the simulation of these controllers, particularly the adaptive controllers; * a short bibliography for each chapter for readers interested in learning more on a particular subject; and * illustrative examples and simulation results to support the main claims made in the text. Academic researchers and graduate students interested in the control of nonlinear systems and particularly those working in sliding-mode controller design will find this book a valuable source of comparative information on existing controllers and ideas for the development of new ones.

This book contains expanded versions of research papers presented at the international sessions of Annual Conference of the Japanese Society for Artificial Intelligence (JSAI), which was held online in June 2020. The JSAI annual conferences are considered key events for our organization, and the international sessions held at these conferences play a key role for the society in its efforts to share Japan's research on artificial intelligence with other countries. In recent years, AI research has proved of great interest to business people. The event draws both more and more presenters and attendees every year, including people of diverse backgrounds such as law and the social sciences, in additional to artificial intelligence. We are extremely pleased to publish this collection of papers as the research results of our international sessions.

This book addresses the adoption of intelligent algorithms for resolving challenges in different aspects of the society such as sport, cyber-security, COVID-19 pandemic, advertising, driving, smart environment-sensors, blockchain, cloud computing, and health. In addition, the book also covers machine learning fundamentals such as feature selection. The book presents practical simulation results and different illustrations in different chapters for easy understanding of concepts and approaches. The types of contributions in the book are as follows: original research, survey, and theoretical insight that describe advancement in the adoption of technique for resolving the broad range of challenges. Researchers, undergraduates, postgraduates, and industry experts will find the book as a valuable resource that bridges theory and practice.

AMBIENT INTELLIGENCE AND INTERNET OF THINGS The book explores long-term implementation techniques and research paths of ambient intelligence and the Internet of Things that meet the design and application requirements of a variety of modern and real-time applications. Working environments based on the emerging technologies of ambient intelligence (AmI) and the Internet of Things (IoT) are available for current and future use in the diverse field of applications. The AmI and IoT paradigms aim to help people achieve their daily goals by augmenting physical environments using networks of distributed devices, including sensors, actuators, and computational resources. Because AmI-IoT is the convergence of numerous technologies and associated research fields, it takes significant effort to integrate them to make our lives easier. It is asserted that Am I can successfully analyze the vast amounts of contextual data obtained from such embedded sensors by employing a variety of artificial intelligence (AI) techniques and that it will transparently and proactively change the environment to conform to the requirements of the user. Over time, the long-term research goals and implementation strategies could meet the design and application needs of a wide range of modern and real-time applications. The 13 chapters in Ambient Intelligence and Internet of Things: Convergent Technologies provide a comprehensive knowledge of the fundamental structure of innovative cutting-edge AmI and IoT technologies as well as practical applications. Audience The book will appeal to researchers, industry engineers, and students in artificial and ambient intelligence, the Internet of Things, intelligent systems, electronics and communication, electronics instrumentations, and computer science.

This book gathers selected research papers presented at the International Conference on Communication and Intelligent Systems (ICCIS 2020), organized jointly by Birla Institute of Applied Sciences, Uttarakhand, and Soft Computing Research Society during 26-27 December 2020. This book presents a collection of state-of-the-art research work involving cutting-edge technologies for communication and intelligent systems. Over the past few years, advances in artificial intelligence and machine learning have sparked new research efforts around the globe, which explore novel ways of developing intelligent systems and smart communication technologies. The book presents single- and multi-disciplinary research on these themes in order to make the latest results available in a single, readily accessible source.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra. This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

This book is a reflection of the modern scientific view of current and future problems and prospects of industry development: equipment and technologies. It combines the results of advanced researches of industry development: equipment and technologies in the field of various sciences - both technical and humanitarian, the synthesis of which allowed forming a holistic meta-scientific concept of industry development: equipment and technologies. The book consists of two parts. The first part reflects technical problems and ways of industry development: equipment and technologies. It examines the promising technologies for modern industrial development, the technogenic factors of neo-industrialization in the context of digital economy, strategic guidelines for the industry development: equipment and technologies from the standpoint of sustainable development, as well as integration mechanisms for the industry development: equipment and technologies, and scientific support for their activation. In the second part, organizational and managerial problems and ways of industry development: equipment and technologies are disclosed. The industry development: equipment and technologies were studied: a view from the standpoint of economics and management, legal barriers to the industry development: equipment: and technologies and the prospects for overcoming them, the impact of globalization on the industry development: equipment: and technologies and recommendations for managing internationalization, as well as social issues of industry development: equipment and technologies in the aspect of human resource's training and management. The book combines the best works presented at the International Research and Practice Conference" Actual Problems and Ways of Industry Development: Equipment and Technologies", organized by the Komsomolsk-on-Amur State University and the Institute of Scientific Communications and held in Komsomolsk-on-Amur (Russia) September 28-October 1, 2020. The target audience of the book is academic scientists studying issues of industry development: equipment and technologies, as well as industrial enterprises and government regulators of industry development: equipment and technologies.

The main topic of this book is the recent development of on-board advanced driver-assistance systems (ADAS), which we can already tell will eventually contribute to the autonomous and connected vehicles of tomorrow. With the development of automated mobility, it becomes necessary to design a series of modules which, from the data produced by on-board or remote information sources, will enable the construction of a completely automated driving system. These modules are perception, decision and action. State-of-the-art AI techniques and their potential applications in the field of autonomous vehicles are described. Perception systems, focusing on visual sensors, the decision module and the prototyping, testing and evaluation of ADAS systems are all presented for effective implementation on autonomous and connected vehicles. This book also addresses cooperative systems, such as pedestrian detection, as well as the legal issues in the use of autonomous vehicles in open environments.

This proceedings book helps bring insights from this array of technical sub-topics together, as advanced robot algorithms draw on the combined expertise of many fields-including control theory, computational geometry and topology, geometrical and physical modeling, reasoning under uncertainty, probabilistic algorithms, game theory, and theoretical computer science. Intelligent robots and autonomous systems depend on algorithms that efficiently realize functionalities ranging from perception to decision making, from motion planning to control. The works collected in this SPAR book represent the state of the art in algorithmic robotics. They originate from papers accepted to the 14th International Workshop on the Algorithmic Foundations of Robotics (WAFR), traditionally a biannual, single-track meeting of leading researchers in the field of robotics. WAFR has always served as a premiere venue for the publication of some of robotics' most important, fundamental, and lasting algorithmic contributions, ensuring the rapid circulation of new ideas. Though an in-person meeting was planned for June 15-17, 2020, in Oulu, Finland, the event ended up being canceled owing to the infeasibility of international travel during the global COVID-19 crisis.

If the intelligence of artificial systems were to surpass that of humans, humanity would face significant risks. The time has come to consider these issues, and this consideration must include progress in artificial intelligence (AI) as much as insights from AI theory. Featuring contributions from leading experts and thinkers in artificial intelligence, Risks of Artificial Intelligence is the first volume of collected chapters dedicated to examining the risks of AI. The book evaluates predictions of the future of AI, proposes ways to ensure that AI systems will be beneficial to humans, and then critically evaluates such proposals. The book covers the latest research on the risks and future impacts of AI. It starts with an introduction to the problem of risk and the future of artificial intelligence, followed by a discussion (Armstrong/Sokala/OhEigeartaigh) on how predictions of its future have fared to date. Omohundro makes the point that even an innocuous artificial agent can easily turn into a serious threat for humans. T. Goertzel explains how to succeed in the design of artificial agents. But will these be a threat for humanity, or a useful tool? Ways to assure beneficial outcomes through 'machine ethics' and 'utility functions' are discussed by Brundage and Yampolskiy. B. Goertzel and Potapov/Rodionov propose 'learning' and 'empathy' as paths towards safer AI while Kornai explains how the impact of AI may be bounded. Sandberg explains the implications of human-like AI via the technique of brain emulation. Dewey discusses strategies to deal with the 'fast takeoff' of artificial intelligence and, finally, Bishop explains why there is no need to worry because computers will remain in a state of 'artificial stupidity'. Sharing insights from leading thinkers in artificial intelligence, this book provides you with an expert-level perspective of what is on the horizon for AI, whether it will be a threat for humanity, and how we might counteract this threat.

Many users of the Internet are aware of bots: automated programs that work behind the scenes to come up with search suggestions, check the weather, filter emails, or clean up Wikipedia entries. More recently, a new software robot has been making its presence felt in social media sites such as Facebook and Twitter - the socialbot. However, unlike other bots, socialbots are built to appear human. While a weatherbot will tell you if it's sunny and a spambot will incessantly peddle Viagra, socialbots will ask you questions, have conversations, like your posts, retweet you, and become your friend. All the while, if they're well-programmed, you won't know that you're tweeting and friending with a robot. Who benefits from the use of software robots? Who loses? Does a bot deserve rights? Who pulls the strings of these bots? Who has the right to know what about them? What does it mean to be intelligent? What does it mean to be a friend? Socialbots and Their Friends: Digital Media and the Automation of Sociality is one of the first academic collections to critically consider the socialbot and tackle these pressing questions.

This book includes selected papers presented at the 4th International Conference on Data Engineering and Communication Technology (ICDECT 2020), held at Kakatiya Institute of Technology & Science, Warangal, India, during 25-26 September 2020. It features advanced, multidisciplinary research towards the design of smart computing, information systems and electronic systems. It also focuses on various innovation paradigms in system knowledge, intelligence and sustainability which can be applied to provide viable solutions to diverse problems related to society, the environment and industry.

Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs

This book includes papers presented at the International Conference "Educational Robotics in the Maker Era - EDUROBOTICS 2020", Online, February 2021. The contributions cover a variety of topics useful for teacher education and for designing learning by making activities for children and youth, with an emphasis on modern low-cost technologies (including block-based programming environments, Do-It-Yourself electronics, 3D printed artifacts, the use of intelligent distributed systems, the IoT technology, and gamification) in formal and informal education settings. This collection of contributions (17 chapters and 2 short papers) provides researchers and practitioners the latest advances in educational robotics in a broader sense focusing on science, technology, engineering, arts, and mathematics (STEAM) education. Teachers and educators at any school level can find insights and inspirations into how educational robotics can promote technological interest and 21st-century skills: creativity, critical thinking, team working, and problem-solving with special emphasis on new emerging making technologies.