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Artificial Intelligence for .NET: Building Smart Applications with Microsoft Cognitive Services APIs

by Nishith Pathak

Get introduced to the world of artificial intelligence with this accessible and practical guide. Build applications that make intelligent use of language and user interaction to better compete in today's marketplace. Discover how your application can deeply understand and interpret content on the web or a user's machine, intelligently react to direct user interaction through speech or text, or make smart recommendations on products or services that are tailored to each individual user. With Microsoft Cognitive Services, you can do all this and more utilizing a set of easy-to-use APIs that can be consumed on the desktop, web, or mobile devices. Developers normally think of AI implementation as a tough task involving writing complex algorithms. This book aims to remove the anxiety by creating a cognitive application with a few lines of code. There is a wide range of Cognitive Services APIs available. This book focuses on some of the most useful and powerful ways that your application can make intelligent use of language. Artificial Intelligence for . NET: Speech, Language, and Search will show you how you can start building amazing capabilities into your applications today. What You'll Learn Understand the underpinnings of artificial intelligence through practical examples and scenarios Get started building an AI-based application in Visual Studio Build a text-based conversational interface for direct user interaction Use the Cognitive Services Speech API to recognize and interpret speech Look at different models of language, including natural language processing, and how to apply them in your Visual Studio application Reuse Bing search capabilities to better understand a user's intention Work with recommendation engines and integrate them into your apps Who This Book Is For Developers working on a range of platforms, from . NET and Windows to mobile devices. Examples are given in C#. No prior experience with AI techniques or theory is required.

Artificial Intelligence for Neuroscience and Emotional Systems: 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4–7, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14674)

by Hojjat Adeli José Manuel Ferrández Vicente Mikel Val Calvo

The two volume set LNCS 14674 and 14675 constitutes the proceedings of the 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, which took place in Olhâo, Portugal, during June 4–7, 2024. The 99 full papers presented in these proceedings were carefully reviewed and selected from 193 submissions. They were organized in topical sections as follows: Part I: Machine learning in neuroscience; artificial intelligence in neurophysiology; neuromotor and cognitive disorders; intelligent systems for assessment, treatment, and assistance in early stages of Alzheimer's disease and other dementias; socio-cognitive, affective and physiological computing; affective computing and context awareness in ambientintelliigence; learning tools to lecture; Part II: Machine learning in computer vision and robotics; bio-inspired computing approaches; social and civil engineering through human AI translations; smart renewable energies: advancing AI algorithms in the renewable energy industry; bioinspired applications.

Artificial Intelligence for Personalized Medicine: Promoting Healthy Living and Longevity (Studies in Computational Intelligence #1106)

by Arash Shaban-Nejad Martin Michalowski Simone Bianco

This book aims to highlight the latest achievements in the use of AI in personalized medicine and healthcare delivery. The edited book contains selected papers presented at the 2023 Health Intelligence workshop, co-located with the Thirty-Seven Association for the Advancement of Artificial Intelligence (AAAI) conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. This book provides information for researchers, students, industry professionals, clinicians, and public health agencies interested in the applications of AI in medicine and public health.

Artificial Intelligence for Renewable Energy and Climate Change

by Pandian Vasant Gerhard-Wilhelm Weber Joshua Thomas José Antonio Marmolejo-Saucedo Roman Rodriguez-Aguilar

ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY AND CLIMATE CHANGE Written and edited by a global team of experts in the field, this groundbreaking new volume presents the concepts and fundamentals of using artificial intelligence in renewable energy and climate change, while also covering the practical applications that can be utilized across multiple disciplines and industries, for the engineer, the student, and other professionals and scientists. Renewable energy and climate change are two of the most important and difficult issues facing the world today. The state of the art in these areas is changing rapidly, with new techniques and theories coming online seemingly every day. It is important for scientists, engineers, and other professionals working in these areas to stay abreast of developments, advances, and practical applications, and this volume is an outstanding reference and tool for this purpose. The paradigm in renewable energy and climate change shifts constantly. In today’s international and competitive environment, lean and green practices are important determinants to increase performance. Corresponding production philosophies and techniques help companies diminish lead times and costs of manufacturing, improve delivery on time and quality, and at the same time become more ecological by reducing material use and waste, and by recycling and reusing. Those lean and green activities enhance productivity, lower carbon footprint and improve consumer satisfaction, which in reverse makes firms competitive and sustainable. This practical, new groundbreaking volume: Features coverage on a wide range of topics such as classical and nature-inspired optimization and optimal control, hybrid and stochastic systems Is ideally designed for engineers, scientists, industrialist, academicians, researchers, computer and information technologists, sustainable developers, managers, environmentalists, government leaders, research officers, policy makers, business leaders and students Is useful as a practical tool for practitioners in the fields of sustainable and renewable energy sustainability Includes wide coverage of how artificial intelligence can be used to impact the struggle against global warming and climate change

Artificial Intelligence for Renewable Energy Systems (Artificial Intelligence and Soft Computing for Industrial Transformation)

by Ajay Kumar Vyas S. Balamurugan Kamal Kant Hiran Harsh S. Dhiman

ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.

Artificial Intelligence for Risk Mitigation in the Financial Industry

by Narayan C. Debnath Archana Patel Purvi Pokhariyal Shweta Anand Ambrish Kumar Mishra

Artificial Intelligence for Risk Mitigation in the Financial Industry This book extensively explores the implementation of AI in the risk mitigation process and provides information for auditing, banking, and financial sectors on how to reduce risk and enhance effective reliability. The applications of the financial industry incorporate vast volumes of structured and unstructured data to gain insight into the financial and non-financial performance of companies. As a result of exponentially increasing data, auditors and management professionals need to enhance processing capabilities while maintaining the effectiveness and reliability of the risk mitigation process. The risk mitigation and audit procedures are processes involving the progression of activities to “transform inputs into output.” As AI systems continue to grow mainstream, it is difficult to imagine an aspect of risk mitigation in the financial industry that will not require AI-related assurance or AI-assisted advisory services. AI can be used as a strong tool in many ways, like the prevention of fraud, money laundering, and cybercrime, detection of risks and probability of NPAs at early stages, sound lending, etc. Audience This is an introductory book that provides insights into the advantages of risk mitigation by the adoption of AI in the financial industry. The subject is not only restricted to individuals like researchers, auditors, and management professionals, but also includes decision-making authorities like the government. This book is a valuable guide to the utilization of AI for risk mitigation and will serve as an important standalone reference for years to come.

Artificial Intelligence for Robotics: Build intelligent robots that perform human tasks using AI techniques

by Francis X. Govers

Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making in robots Book Description Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence. What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot's intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics.

Artificial Intelligence for Robotics and Autonomous Systems Applications (Studies in Computational Intelligence #1093)

by Ahmad Taher Azar Anis Koubaa

This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics.Artificial intelligence is being integrated into robots in order to develop advanced robotics capable of performing multiple tasks and learning new things with a better perception of the environment, allowing robots to perform critical tasks with human-like vision to detect or recognize various objects. Intelligent robots have been successfully constructed using machine learning and deep learning AI technology. Robotics performance is improving as higher quality, and more precise machine learning processes are used to train computer vision models to recognize different things and carry out operations correctly with the desired outcome.We believe that the increasing demands and challenges offered by real-world robotic applications encourage academic research in both artificial intelligence and robotics. The goal of this book is to bring together scientists, specialists, and engineers from around the world to present and share their most recent research findings and new ideas on artificial intelligence in robotics.

Artificial Intelligence for Science and Engineering Applications

by Shahab D. Mohaghegh

Artificial Intelligence (AI) is defined as the simulation of human intelligence through the mimicking of the human brain for analysis, modeling, and decision‑making. Science and engineering problem solving requires modeling of physical phenomena, and humans approach the solution of scientific and engineering problems differently from other problems. Artificial Intelligence for Science and Engineering Applications addresses the unique differences in how AI should be developed and used in science and engineering. Through the inclusion of definitions and detailed examples, this book describes the actual and realistic requirements as well as what characteristics must be avoided for correct and successful science and engineering applications of AI.This book:• Offers a brief history of AI and covers science and engineering applications• Explores the modeling of physical phenomena using AI• Discusses explainable AI (XAI) applications• Covers the ethics of AI in science and engineering• Features real‑world case studiesOffering a probing view into the unique nature of scientific and engineering exploration, this book will be of interest to generalists and experts looking to expand their understanding of how AI can better tackle and advance technology and developments in scientific and engineering disciplines.

Artificial Intelligence for Scientific Discoveries: Extracting Physical Concepts from Experimental Data Using Deep Learning

by Raban Iten

Will research soon be done by artificial intelligence, thereby making human researchers superfluous? This book explains modern approaches to discovering physical concepts with machine learning and elucidates their strengths and limitations. The automation of the creation of experimental setups and physical models, as well as model testing are discussed. The focus of the book is the automation of an important step of the model creation, namely finding a minimal number of natural parameters that contain sufficient information to make predictions about the considered system. The basic idea of this approach is to employ a deep learning architecture, SciNet, to model a simplified version of a physicist's reasoning process. SciNet finds the relevant physical parameters, like the mass of a particle, from experimental data and makes predictions based on the parameters found. The author demonstrates how to extract conceptual information from such parameters, e.g., Copernicus' conclusion that the solar system is heliocentric.

Artificial Intelligence for Smart Healthcare (EAI/Springer Innovations in Communication and Computing)

by Parul Agarwal Kavita Khanna Ahmed A. Elngar Ahmed J. Obaid Zdzislaw Polkowski

This book provides information on interdependencies of medicine and telecommunications engineering and how the two must rely on each other to effectively function in this era. The book discusses new techniques for medical service improvisation such as clear-cut views on medical technologies. The authors provide chapters on communication essentiality in healthcare, processing of medical amenities using medical images, the importance of data and information technology in medicine, and machine learning and artificial intelligence in healthcare. Authors include researchers, academics, and professionals in the field.

Artificial Intelligence for Smart Manufacturing: Methods, Applications, and Challenges (Springer Series in Reliability Engineering)

by Kim Phuc Tran

This book provides readers with a comprehensive overview of the latest developments in the field of smart manufacturing, exploring theoretical research, technological advancements, and practical applications of AI approaches. With Industry 4.0 paving the way for intelligent systems and innovative technologies to enhance productivity and quality, the transition to Industry 5.0 has introduced a new concept known as augmented intelligence (AuI), combining artificial intelligence (AI) with human intelligence (HI).As the demand for smart manufacturing continues to grow, this book serves as a valuable resource for professionals and practitioners looking to stay up-to-date with the latest advancements in Industry 5.0. Covering a range of important topics such as product design, predictive maintenance, quality control, digital twin, wearable technology, quantum, and machine learning, the book also features insightful case studies that demonstrate the practical application of these tools in real-world scenarios.Overall, this book provides a comprehensive and up-to-date account of the latest advancements in smart manufacturing, offering readers a valuable resource for navigating the challenges and opportunities presented by Industry 5.0.

Artificial Intelligence for Societal Issues (Intelligent Systems Reference Library #231)

by Anupam Biswas Vijay Bhaskar Semwal Durgesh Singh

Artificial intelligence (AI) has the potential to provide innovative solutions to various societal issues and real-world social challenges. AI is useful in combating some of the seemingly unsolvable social crises facing the world today. Be it disaster awareness and management or demand forecasting, or healthcare informatics or disease outbreaks like COVID-19, the AI plays a pivotal role everywhere. AI has the potential to address some of the societal issues that indirectly pose challenges like cybercrime, agriculture, education, economy, and health. The book covers several applications of AI as solutions to different societal issues, which include economic empowerment, smart education system, COVID-19 detection & management, emotion detection, fraudulent transactions, applications in agriculture and health informatics, etc. The book will be helpful for the academicians and researchers working with various areas of societal issues, data science, artificial intelligence, and machine learning.

Artificial Intelligence for Solar Photovoltaic Systems: Approaches, Methodologies, and Technologies (Explainable AI (XAI) for Engineering Applications)

by Bhavnesh Kumar

This book provides a clear explanation of how to apply artificial intelligence (AI) to solve the challenges in solar photovoltaic technology. It introduces readers to new AI-based approaches and technologies that help manage and operate solar photovoltaic systems effectively. It also motivates readers to find new AI-based solutions for these challenges by providing a comprehensive collection of findings on AI techniques.It covers important topics including solar irradiance variability, solar power forecasting, solar irradiance forecasting, maximum power point tracking, hybrid algorithms, swarm optimization, evolutionary optimization, sensor-based sun- tracking systems, single-axis and dual-axis sun-tracking systems, smart metering, frequency regulation using AI, emerging multilevel inverter topologies, and voltage and reactive power control using AI.This book is useful for senior undergraduate students, graduate students, and academic researchers in areas such as electrical engineering, electronics and communication engineering, computer science, and renewable energy.

Artificial Intelligence for Space: Trends, Applications, and Perspectives

by Matteo Madi Olga Sokolova

The new age space value chain is a complex interconnected system with diverse actors, which involves cross-sector and cross-border collaborations. This book helps to enrich the knowledge of Artificial Intelligence (AI) across the value chain in the space-related domains. Advancements of AI and Machine Learning have impactfully supported the space sector transformation as it is shown in the book. "This book embarks on a journey through the fascinating realm of AI in space, exploring its profound implications, emerging trends, and transformative potential." Prof. mult. Dr.med. Dr.rer.nat. Oliver UllrichDirector Innovation Cluster Space and Aviaton (UZH Space Hub), University of Zurich, Switzerland Aimed at space engineers, risk analysts, policy makers, technical experts and non-specialists, this book demonstrates insights into the implementation of AI in the space sector, alongside its limitations and use-case examples. It covers diverse AI-related topics applicable to space technologies or space big data such as AI-based technologies for improving Earth Observation big data, AI for space robotics exploration, AI for astrophysics, AI for emerging in-orbit servicing market, and AI for space tourism safety improvement. Key Features: Provides an interdisciplinary approach, with chapter contributions from expert teams working in the governmental or private space sectors, with valuable contributions from computer scientists and legal experts; Presents insights into AI implementation and how to unlock AI technologies in the field; Up to date with the latest developments and cutting-edge applications Matteo Madi, Ph.D., is an entrepreneur, innovator, business developer and space-tech specialist with many years of experiences in the Swiss and International public and private sectors. He is the founder of Sirin Orbital Systems AG, a Swiss innovative company based in Zurich, focused on the development and commercialization of advanced enabling technologies for the needs of emerging space market and future sustainable space exploration. It also creates innovative solutions for the use of space technologies and satellite-based services for terrestrial applications. Olga Sokolova, Ph.D., is a risk analyst proficient in critical infrastructure risk assessment to natural and technical hazards. She has been engaged in development and analysis of structural risk-management tools towards sustainable future and has a record in raising social awareness of spaceborne risks and opportunities brought to the society by the "New Space" industry developments. Along with Dr. M. Madi, Dr. O. Sokolova is the Co-Editor of the book entitled, "Space Debris Peril: Pathways to Opportunities", published by CRC Press: Taylor and Francis in November 2020 (ISBN 9780367469450).

Artificial Intelligence for Sustainability: Innovations in Business and Financial Services

by Thomas Walker Stefan Wendt Sherif Goubran Tyler Schwartz

In light of the climate crisis, businesses are expected to embrace sustainability to reduce their negative impacts on the environment and society, while at the same time strengthening their organisations’ positive impacts. Managing this alongside the traditional requirements of business requires careful handling, and it is small wonder that some are heralding the advantages posed by artificial intelligence (AI) as the missing piece of the puzzle. This edited book aims to present a balanced discussion of the benefits and costs of using AI for the natural environment and society, including an analysis of its potential to help meet the UN’s Agenda 2030 and the Sustainable Development Goals. Researchers, practitioners, regulators, and entrepreneurs at the forefront of sustainable AI solutions share insights into the different sustainable applications of AI and highlight how these new developments may affect and contribute to our fight against climate change and address further environmental and social challenges. This volume will be of great interest to scholars and students of digital business and new technologies, sustainability, and strategy.

Artificial Intelligence for Sustainable Applications (Artificial Intelligence and Soft Computing for Industrial Transformation)

by K. Umamaheswari B. Vinoth Kumar S. K. Somasundaram

ARTIFICAL INTELLIGENCE for SUSTAINABLE APPLICATIONS The objective of this book is to leverage the significance of artificial intelligence in achieving sustainable solutions using interdisciplinary research through innovative ideas. With the advent of recent technologies, the demand for Information and Communication Technology (ICT)-based applications such as artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), health care, data analytics, augmented reality/virtual reality, cyber-physical systems, and future generation networks, has increased drastically. In recent years, artificial intelligence has played a more significant role in everyday activities. While AI creates opportunities, it also presents greater challenges in the sustainable development of engineering applications. Therefore, the association between AI and sustainable applications is an essential field of research. Moreover, the applications of sustainable products have come a long way in the past few decades, driven by social and environmental awareness, and abundant modernization in the pertinent field. New research efforts are inevitable in the ongoing design of sustainable applications, which makes the study of communication between them a promising field to explore. This book highlights the recent advances in AI and its allied technologies with a special focus on sustainable applications. It covers theoretical background, a hands-on approach, and real-time use cases with experimental and analytical results. Audience AI researchers as well as engineers in information technology and computer science.

Artificial Intelligence for Sustainable Development (EAI/Springer Innovations in Communication and Computing)

by Anandakumar Haldorai Babitha Lincy R Suriya Murugan Minu Balakrishnan

This book delves into the synergy between AI and sustainability. This comprehensive guide illuminates the latest trends and cutting-edge techniques, offering invaluable insights for researchers, practitioners, and policymakers interested in the cross-section of AI and sustainability. The authors illustrate how AI-driven innovations are revolutionizing environmental conservation, urban planning, healthcare, and more. The book also considers the ethical considerations and governance frameworks crucial to harnessing AI's potential for global benefit. Whether a seasoned expert or a curious newcomer, this book empowers readers to navigate the dynamic landscape of AI and sustainability, paving the way for a more eco-conscious and equitable world.

Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications (Studies in Computational Intelligence #912)

by Aboul Ella Hassanien Roheet Bhatnagar Ashraf Darwish

This book highlights the latest advances in the field of artificial intelligence and related technologies, with a special focus on sustainable development and environmentally friendly artificial intelligence applications. Discussing theory, applications and research, it covers all aspects of artificial intelligence in the context of sustainable development.

Artificial Intelligence for Sustainable Energy: Select Proceedings of the International Conference, GEn-CITy 2023 (Lecture Notes in Electrical Engineering #1142)

by Jimson Mathew Lenin Gopal Filbert H. Juwono

This book presents select proceedings of the International Conference on Green Energy, Computing, and Intelligent Technology (GEn-CITy 2023) held at the University of Southampton Malaysia in July 2023. This book primarily covers clean energy and intelligent technologies for a sustainable future. This book serves as a forum for engineers, researchers, and specialists from academia, research centers, and industry worldwide to discuss and present the latest developments and applications related to the challenges of securing green and clean energy sources for the 21st century to protect the environment.

Artificial Intelligence for Sustainable Finance and Sustainable Technology: Proceedings of ICGER 2021 (Lecture Notes in Networks and Systems #423)

by Abdalmuttaleb M. A. Musleh Al-Sartawi

This book shows latest research on artificial intelligence for sustainable technology. ICGER 2021 was organized by the Accounting, Finance and Banking Department at Ahlia University, Bahrain, and was conducted on the 15th and 16th of September. The strategic partners included the University of Jordan, the Bahrain Economists Society, the Association of Chartered Certified Accountants: ACCA, Al-Barka Banking Group and the International Computer Auditing Education Association: ICAEA . The theme of the ICGER 2021 centered around artificial intelligence for sustainable finance and sustainable technology. Accordingly, the papers presented at the conference provided a holistic view of sustainable finance, sustainability, AI, financial technology, cybersecurity, blockchain, CSR, and governance. This book, unlike ever before, brings together intelligence applications of new technologies and the sustainability requirements in the era of the digital economy, 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 applications and financial technologies to develop future strategies and to achieve sustainable development goals.

Artificial Intelligence for the Internet of Health Things (Biomedical and Robotics Healthcare)

by K. Shankar Eswaran Perumal Deepak Gupta

This book discusses research in Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in design, implementation, and optimization of challenging healthcare solutions. This book features a wide range of topics such as AI techniques, IoT, cloud, wearables, and secured data transmission. Written for a broad audience, this book will be useful for clinicians, health professionals, engineers, technology developers, IT consultants, researchers, and students interested in the AI-based healthcare applications. Provides a deeper understanding of key AI algorithms and their use and implementation within the wider healthcare sector Explores different disease diagnosis models using machine learning, deep learning, healthcare data analysis, including machine learning, and data mining and soft computing algorithms Discusses detailed IoT, wearables, and cloud-based disease diagnosis model for intelligent systems and healthcare Reviews different applications and challenges across the design, implementation, and management of intelligent systems and healthcare data networks Introduces a new applications and case studies across all areas of AI in healthcare data K. Shankar (Member, IEEE) is a Postdoctoral Fellow of the Department of Computer Applications, Alagappa University, Karaikudi, India. Eswaran Perumal is an Assistant Professor of the Department of Computer Applications, Alagappa University, Karaikudi, India. Dr. Deepak Gupta is an Assistant Professor of the Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.

Artificial Intelligence Frontiers in Statistics: Al and Statistics III

by David J. Hand

This book presents a summary of recent work on the interface between artificial intelligence and statistics. It does this through a series of papers by different authors working in different areas of this interface. These papers are a selected and referenced subset of papers presented at the 3rd Interntional Workshop on Artificial Intelligence and Statistics, Florida, January 1991.

Artificial Intelligence, Game Theory and Mechanism Design in Politics

by Tshilidzi Marwala

This book explores how AI and mechanism design can provide a new framework for international politics. The international political system is all manners in which countries, governments and people relate. Mechanism design in international politics relates to identifying rules that define relationships between people and countries that achieve a particular outcome, e.g., peace or more trade or democracy or economic development. Artificial intelligence is technique of making machines intelligent. This book explores mechanism design and artificial intelligence in international politics and applies these technologies to politics, economy and society. This book will be of interest to scholars of international relations, politics, sustainable development, and artificial intelligence.

Artificial Intelligence Governance and the Blockchain Revolution (Artificial Intelligence and the Rule of Law)

by Qiqi Gao Jiteng Zhang

This is the first professional academic work in China to discuss artificial intelligence and blockchain together. Artificial intelligence is a productivity revolution, and its development has a significant and profound impact on global changes. However, at the same time, its development also brings a series of challenges to human society, such as privacy, security, and fairness issues. Therefore, the significance of blockchain is even more prominent. Blockchain is a revolution in production relations, which will propose important solutions to the challenges of privacy, security, and fairness that arise after the development of artificial intelligence. The book not only discusses the problems currently faced by the development of artificial intelligence, as well as the new opportunities and challenges that artificial intelligence brings to future global governance, but also explains the further development direction of the intelligent revolution from the perspective of blockchain.

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