Machine Learning is evolving computation and its application like never before. It is now widely recognized that machine learning is playing a similar role as electricity played in modernizing the world. From simple high school science projects to large-scale radio astronomy, machine learning has revolutionized it all. However, a few of the applications stand out as transforming the world and opening up a new era. The book intends to showcase applications of machine learning that are leading us to the next generation of computing and living standards. The book portrays the application of machine learning to cutting-edge technologies that are playing a prominent role in improving the quality of life and the progress of civilization. The focus of the book is not just machine learning, but its application to specific domains that are resulting in substantial progress of civilization. It is ideal for scientists and researchers, academic and corporate libraries, students, lecturers and teachers, and practitioners and professionals.

In the world of mathematics and computer science, technological advancements are constantly being researched and applied to ongoing issues. Setbacks in social networking, engineering, and automation are themes that affect everyday life, and researchers have been looking for new techniques in which to solve these challenges. Graph theory is a widely studied topic that is now being applied to real-life problems. Advanced Applications of Graph Theory in Modern Society is an essential reference source that discusses recent developments on graph theory, as well as its representation in social networks, artificial neural networks, and many complex networks. The book aims to study results that are useful in the fields of robotics and machine learning and will examine different engineering issues that are closely related to fuzzy graph theory. Featuring research on topics such as artificial neural systems and robotics, this book is ideally designed for mathematicians, research scholars, practitioners, professionals, engineers, and students seeking an innovative overview of graphic theory.

Artificial neural network research is one of the new directions for new generation computers. Current research suggests that open box artificial higher order neural networks (HONNs) play an important role in this new direction. HONNs will challenge traditional artificial neural network products and change the research methodology that people are currently using in control and recognition areas for the control signal generating, pattern recognition, nonlinear recognition, classification, and prediction. Since HONNs are open box models, they can be easily accepted and used by individuals working in information science, information technology, management, economics, and business fields. Emerging Capabilities and Applications of Artificial Higher Order Neural Networks contains innovative research on how to use HONNs in control and recognition areas and explains why HONNs can approximate any nonlinear data to any degree of accuracy, their ease of use, and how they can have better nonlinear data recognition accuracy than SAS nonlinear procedures. Featuring coverage on a broad range of topics such as nonlinear regression, pattern recognition, and data prediction, this book is ideally designed for data analysists, IT specialists, engineers, researchers, academics, students, and professionals working in the fields of economics, business, modeling, simulation, control, recognition, computer science, and engineering research.

This provocative book investigates the relationship between law and artificial intelligence (AI) governance, and the need for new and innovative approaches to regulating AI and big data in ways that go beyond market concerns alone and look to sustainability and social good. Taking a multidisciplinary approach, the contributors demonstrate the interplay between various research methods, and policy motivations, to show that law-based regulation and governance of AI is vital to efforts at ensuring justice, trust in administrative and contractual processes, and inclusive social cohesion in our increasingly technologically-driven societies. The book provides valuable insights on the new challenges posed by a rapid reliance on AI and big data, from data protection regimes around sensitive personal data, to blockchain and smart contracts, platform data reuse, IP rights and limitations, and many other crucial concerns for law's interventions. The book also engages with concerns about the 'surveillance society', for example regarding contact tracing technology used during the Covid-19 pandemic. The analytical approach provided will make this an excellent resource for scholars and educators, legal practitioners (from constitutional law to contract law) and policy makers within regulation and governance. The empirical case studies will also be of great interest to scholars of technology law and public policy. The regulatory community will find this collection offers an influential case for law's relevance in giving institutional enforceability to ethics and principled design.

Emerging technologies continue to affect a variety of industries, making processes more effective and efficient. However, they also impact society by promoting opportunities to encourage social change and socioeconomic advancement. Blockchain is one that is already influencing third world countries and disrupting the globe. Blockchain Technology for Global Social Change is an essential research publication that provides insight into advancements being made in blockchain and some potential applications of the technology that can improve the lives of individuals in emerging markets. This publication covers a range of topics such as digital government, health systems, and urbanization and is ideal for policymakers, academicians, researchers, sociologists, government officials, economists, and financial experts seeking current and relevant research on evolving blockchain technologies.

Artificial intelligence has become an invaluable tool in modern society and can be utilized across fields such as healthcare, travel, education, and construction. There are numerous benefits for companies, industries, and governments when adopting this technology into their daily operations as it continues to evolve to support the needs of society. Further study on the challenges and strategies of implementation is required in order to ensure the technology is employed to its full potential. Artificial Intelligence for Societal Development and Global Well-Being considers the various uses, best practices, and success factors of artificial intelligence across fields and industries and discusses critical ways in which the technology must be developed further for the good of society. Covering a range of topics such as smart devices, artificial neural networks, and natural intelligence, this reference work is crucial for scientists, librarians, business owners, government officials, entrepreneurs, scholars, researchers, practitioners, instructors, and students.

In this book, translated into English for the first time, Lelio Demichelis takes on a modern perspective of the concept/process of alienation. This concept-much more profound and widespread today than first described and denounced by Marx-has largely been forgotten and erased. Using the characters of Narcissus, Pygmalion and Prometheus, the author reinterprets and updates Marx, Nietzsche, Anders, Foucault and, in particular, critical theory and the Frankfurt School views on an administered society (where everything is automated and engineered, manifest today in algorithms, AI, machine learning and social networking) showing that, in a world where old and new forms of alienation come together, man is increasingly led to delegate (i.e. alienate) sovereignty, freedom, responsibility and the awareness of being alive.

This book presents and discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks. The rapid growth of server, desktop, and embedded applications based on deep learning has brought about a renaissance in interest in neural networks, with applications including image and speech processing, data analytics, robotics, healthcare monitoring, and IoT solutions. Efficient implementation of neural networks to support complex deep learning-based applications is a complex challenge for embedded and mobile computing platforms with limited computational/storage resources and a tight power budget. Even for cloud-scale systems it is critical to select the right hardware configuration based on the neural network complexity and system constraints in order to increase power- and performance-efficiency. Hardware Architectures for Deep Learning provides an overview of this new field, from principles to applications, for researchers, postgraduate students and engineers who work on learning-based services and hardware platforms.

Decision-making is a frequent problem in today's financial, business, and industrial world. Thus, fuzzy expert systems are increasingly being used to solve decision-making problems by attempting to solve a part or whole of a practical problem. These expert systems have proven that they can solve problems in various domains where human expertise is required, including the field of agriculture. Fuzzy Expert Systems and Applications in Agricultural Diagnosis is a crucial source that examines the use of fuzzy expert systems for prediction and problem solving in the agricultural industry. Featuring research on topics such as nutrition management, sustainable agriculture, and defuzzification, this book is ideally designed for farmers, researchers, scientists, academics, students, policymakers, and development practitioners seeking the latest research in technological tools that support crop disease diagnosis.

The world we live in presents plenty of tricky, impactful, and hard-tomake decisions to be taken. Sometimes the available options are ample, at other times they are apparently binary, either way, they often confront us with dilemmas, paradoxes, and even denial of values.In the dawn of the age of intelligence, when robots are gradually taking over most decision-making from humans, this book sheds a bit of light on decision rationale. It delves into the limits of these decision processes (for both humans and machines), and it does so by providing a new perspective that is somehow opposed to orthodox economics. All Economics reflections in this book are underlined and linked to Artificial Intelligence.The authors hope that this comprehensive and modern analysis, firmly grounded in the opinions of various groundbreaking Nobel laureate economists, may be helpful to a broad audience interested in how decisions may lead us all to flourishing societies. That is, societies in which economic blunders (caused by over simplification of problems and super estimation of tools) are reduced substantially.

Negnevitsky shows students how to build intelligent systems drawing on techniques from knowledge-based systems, neural networks, fuzzy systems, evolutionary computation and now also intelligent agents. The principles behind these techniques are explained without resorting to complex mathematics, showing how the various techniques are implemented, when they are useful and when they are not. No particular programming language is assumed and the book does not tie itself to any of the software tools available. However, available tools and their uses are described, and program examples are given in Java. The lack of assumed prior knowledge makes this book ideal for any introductory courses in artificial intelligence or intelligent systems design, while the contemporary coverage means more advanced students will benefit by discovering the latest state-of-the-art techniques, particularly in intelligent agents and knowledge discovery.

This volume provides an extensive overview of the Ethics of Artificial Intelligence for the Sustainable Development Goals. The authors are experts contributing with perspectives from different fields. The comprehensive collection of chapters illustrates the pressing governance problems related to using AI for the SDGs, and case studies describing how AI is advancing and can advance the achievement of the Goals. Students, scholars, and practitioners working on AI for SDGs, the ethical governance of AI, sustainability, and the fourth revolution can find this book a helpful reference.