Books in Artificial intelligence expert systems and knowledge based systems

Interdependent Human-Machine Teams

1st Edition
December 5, 2024
William Lawless + 3 more
English
Paperback
9 7 8 0 4 4 3 2 9 2 4 6 0
eBook
9 7 8 0 4 4 3 2 9 2 4 7 7

Interdependent Human-Machine Teams: The Path to Autonomy examines the foundations, metrics, and applications of human-machine systems, the legal ramifications of autonomy, trust by the public, and trust by the users and AI systems of their users, integrating concepts from various disciplines such as AI, machine learning, social sciences, quantum mechanics, and systems engineering. In this book, world-class researchers, engineers, ethicists, and social scientists discuss what machines, humans, and systems should discuss with each other, to policymakers, and to the public.It establishes the meaning and operation of “shared contexts” between humans and machines, policy makers, and the public and explores how human-machine systems affect targeted audiences (researchers, machines, robots, users, regulators, etc.) and society, as well as future ecosystems composed of humans, machines, and systems.

Empowering IoT with Big Data Analytics

1st Edition
November 16, 2024
Mohamed Adel Serhani + 2 more
English
Paperback
9 7 8 0 4 4 3 2 1 6 4 0 4
eBook
9 7 8 0 4 4 3 2 1 6 4 1 1

Empowering IoT with Big Data Analytics provides comprehensive coverage of major topics, tools, and techniques related to empowering IoT with big data technologies and big data analytics solutions, thus allowing for better processing, analysis, protection, distribution, and visualization of data for the benefit of IoT applications and second, a better deployment of IoT applications on the ground. This book covers big data in the IoT era, its application domains, current state-of-the-art in big data and IoT technologies, standards, platforms, and solutions. This book provides a holistic view of the big data value-chain for IoT, including storage, processing, protection, distribution, analytics, and visualization.Big data is a multi-disciplinary topic involving handling intensive, continuous, and heterogeneous data retrieved from different sources including sensors, social media, and embedded systems. The emergence of Internet of Things (IoT) and its application to many domains has led to the generation of huge amounts of both structured and unstructured data often referred to as big data.

Data Analytics for Intelligent Transportation Systems

2nd Edition
November 2, 2024
Mashrur Chowdhury + 2 more
English
Paperback
9 7 8 0 4 4 3 1 3 8 7 8 2
eBook
9 7 8 0 4 4 3 1 3 8 7 9 9

Data Analytics for Intelligent Transportation Systems, Second Edition provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Other sections provide extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies.All fundamentals/concept... presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. In addition, they will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning.

Responsible Artificial Intelligence Re-engineering the Global Public Health Ecosystem

1st Edition
June 7, 2024
Dominique J Monlezun
English
Paperback
9 7 8 0 4 4 3 2 1 5 9 7 1
eBook
9 7 8 0 4 4 3 2 1 5 9 6 4

Responsible Artificial Intelligence Re-engineering the Global Public Health Ecosystem: A Humanity Worth Saving is the first comprehensive book showing how trustworthy AI can revolutionize decolonized global public health. It explains how it works as an ecosystem and how it can be fixed to equitably empower us all to solve the defining crises of our era, from poverty to pandemics, climate to conflicts, debt to divisions. It is written from the first-hand perspective of the world’s first triple doctorate trained physician-data scientist and ethicist who has cared for more than 10,000 patients and authored 5 AI textbooks and more than 400 scientific and ethics papers. This essential resource integrates science, political economics, and ethics to unite our unique cultures, belief systems, institutions, and governments. In doing so, it is meant to give humanity a fighting chance against shared existential threats through cooperation and managed strategic competition for integral sustainable development.Taking seriously diverse voices, perspectives, and insights from the Global North and the Global South, this book uses concrete examples backed up by clear explanations to elucidate the current failures, emerging successes, and societal trends of global public health. It shows how a small number of powerful governments and corporations—amid digitalization, deglobalization, and demographic shifts—dominate global health, and how we can re-engineer a better future for it both societally and technologically. The book spans health breakthroughs in federated data architectures, machine learning, deep learning, swarm learning, quantum computing, blockchain, agile data governance and solidarity, value blocks (of democracies and autocracies), adaptive value supply chains, social networks, pandemics, health financing, universal health coverage, public–private partnerships, healthcare system design, precision agriculture, clean energy, human security, and multicultural global ethics. This book therefore is meant to provide a clear, coherent, and actionable guide equipping students, practitioners, researchers, policymakers, and leaders in digital technology, public health, healthcare, health policy, public policy, political economics, and ethics to generate the solutions that will define humanity’s next era—while recovering what that humanity means, and why it is worth saving.

Securing Next-Generation Connected Healthcare Systems

1st Edition
May 14, 2024
Deepak Gupta + 1 more
English
Paperback
9 7 8 0 4 4 3 1 3 9 5 1 2
eBook
9 7 8 0 4 4 3 1 3 9 5 2 9

Securing Next-Generation Connected Healthcare Systems: Artificial Intelligence Technologies focuses on the crucial aspects of IoT security in a connected environment, which will not only benefit from cutting-edge methodological approaches but also assist in the rapid scalability and improvement of these systems. This book shows how to utilize technologies like blockchain and its integration with IoT for communication, data security, and trust management. It introduces the security aspect of next generation technologies for healthcare, covering a wide range of security and computing methodologies.Resear... data scientists, students, and professionals interested in the application of artificial intelligence in healthcare management, data security of connected healthcare systems and related fields, specifically on data intensive secured systems and computing environments, will finds this to be a welcomed resource.

A Handbook of Artificial Intelligence in Drug Delivery

1st Edition
March 27, 2023
Anil K. Philip + 3 more
English
Paperback
9 7 8 0 3 2 3 8 9 9 2 5 3
eBook
9 7 8 0 3 2 3 9 0 3 7 3 8

A Handbook of Artificial Intelligence in Drug Delivery explores the use of Artificial Intelligence (AI) in drug delivery strategies. The book covers pharmaceutical AI and drug discovery challenges, Artificial Intelligence tools for drug research, AI enabled intelligent drug delivery systems and next generation novel therapeutics, broad utility of AI for designing novel micro/nanosystems for drug delivery, AI driven personalized medicine and Gene therapy, 3D Organ printing and tissue engineering, Advanced nanosystems based on AI principles (nanorobots, nanomachines), opportunities and challenges using artificial intelligence in ADME/Tox in drug development, commercialization and regulatory perspectives, ethics in AI, and more. This book will be useful to academic and industrial researchers interested in drug delivery, chemical biology, computational chemistry, medicinal chemistry and bioinformatics. The massive time and costs investments in drug research and development necessitate application of more innovative techniques and smart strategies.

Machine Learning

2nd Edition
March 1, 2023
Marco Gori + 2 more
English
Paperback
9 7 8 0 3 2 3 8 9 8 5 9 1
eBook
9 7 8 0 3 2 3 9 8 4 6 9 0

Machine Learning: A Constraint-Based Approach, Second Edition provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that include neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. It draws a path towards deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, such as in fuzzy systems. Special attention is given to deep learning, which nicely fits the constrained-based approach followed in this book.The book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, including many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included.

AI Computing Systems

1st Edition
October 12, 2022
Yunji Chen + 5 more
English
Paperback
9 7 8 0 3 2 3 9 5 3 9 9 3
eBook
9 7 8 0 3 2 3 9 5 3 9 8 6

AI Computing Systems: An Application Driven Perspective adopts the principle of "application-driven, full-stack penetration" and uses the specific intelligent application of "image style migration" to provide students with a sound starting place to learn. This approach enables readers to obtain a full view of the AI computing system. A complete intelligent computing system involves many aspects such as processing chip, system structure, programming environment, software, etc., making it a difficult topic to master in a short time.

Artificial Intelligence and Industry 4.0

1st Edition
August 14, 2022
Aboul Ella Hassanien + 2 more
English
Paperback
9 7 8 0 3 2 3 8 8 4 6 8 6
eBook
9 7 8 0 3 2 3 9 0 6 3 9 5

Artificial Intelligence and Industry 4.0 explores recent advancements in blockchain technology and artificial intelligence (AI) as well as their crucial impacts on realizing Industry 4.0 goals. The book explores AI applications in industry including Internet of Things (IoT) and Industrial Internet of Things (IIoT) technology. Chapters explore how AI (machine learning, smart cities, healthcare, Society 5.0, etc.) have numerous potential applications in the Industry 4.0 era. This book is a useful resource for researchers and graduate students in computer science researching and developing AI and the IIoT.

Data Mining

4th Edition
July 2, 2022
Jiawei Han + 2 more
English
Paperback
9 7 8 0 1 2 8 1 1 7 6 0 6
eBook
9 7 8 0 1 2 8 1 1 7 6 1 3

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data, or KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducing concepts and methods for mining frequent patterns, associations, and correlations for large data sets; data classificcation and model construction; cluster analysis; and outlier detection. Concepts and methods for deep learning are systematically introduced as one chapter. Finally, the book covers the trends, applications, and research frontiers in data mining.

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health