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Artificial Intelligence and Competition: Economic and Legal Perspectives in the Digital Age (Contributions to Economics)

by Georgios I. Zekos

This book examines the impact of artificial intelligence on competition and antitrust in today's global digital economy. It scrutinizes the economic and legal ramifications of Artificial Intelligence (AI), addressing the challenges it presents to competition and the law.Beginning with an analysis of AI's developments across various economic sectors, the book highlights the need for updated legislation. It focuses on the digital economy, emphasizing digital platforms' role in shaping competition. Econometric investigations and a novel index assess competition's influence on foreign direct investment and multinational enterprises. Comparing competition practices across jurisdictions like the EU, US, Germany, and China, the book uncovers commonalities and differences in competition law principles. It also explores various theories on competition and competition law, seeking convergence or divergence.This book is an essential resource for scholars, legal professionals, policymakers, and anyone seeking a better understanding of how AI is reshaping competition and antitrust in the digital age.

Artificial Intelligence and Computer Vision (Studies in Computational Intelligence #672)

by Huimin Lu Yujie Li

This edited book presents essential findings in the research fields of artificial intelligence and computer vision, with a primary focus on new research ideas and results for mathematical problems involved in computer vision systems. The book provides an international forum for researchers to summarize the most recent developments and ideas in the field, with a special emphasis on the technical and observational results obtained in the past few years.

Artificial Intelligence and Conservation (Artificial Intelligence for Social Good)

by Fei Fang Milind Tambe Bistra Dilkina Andrew J. Plumptre

With the increasing public interest in artificial intelligence (AI), there is also increasing interest in learning about the benefits that AI can deliver to society. This book focuses on research advances in AI that benefit the conservation of wildlife, forests, coral reefs, rivers, and other natural resources. It presents how the joint efforts of researchers in computer science, ecology, economics, and psychology help address the goals of the United Nations' 2030 Agenda for Sustainable Development. Written at a level accessible to conservation professionals and AI researchers, the book offers both an overview of the field and an in-depth view of how AI is being used to understand patterns in wildlife poaching and enhance patrol efforts in response, covering research advances, field tests and real-world deployments. The book also features efforts in other major conservation directions, including protecting natural resources, ecosystem monitoring, and bio-invasion management through the use of game theory, machine learning, and optimization.

Artificial Intelligence and COVID Effect on Accounting (Accounting, Finance, Sustainability, Governance & Fraud: Theory and Application)

by Bahaaeddin Alareeni Allam Hamdan

This book considers the effects of COVID-19 on accounting, particularly with regard to the role of artificial intelligence in accounting in the post-pandemic business environment. The contributions in the book consider a variety of sectors that have been affected by the pandemic, such as the stock market, forensic accounting, Bitcoin, as well as the economic and educational responses to the pandemic and the aftermath felt by both developing and developed countries. This book will be a valuable read for academics, students and practitioners of accounting who are keen to explore the future of the field in light of the pandemic.

Artificial Intelligence and Credit Risk: The Use of Alternative Data and Methods in Internal Credit Rating

by Rossella Locatelli Giovanni Pepe Fabio Salis

This book focuses on the alternative techniques and data leveraged for credit risk, describing and analysing the array of methodological approaches for the usage of techniques and/or alternative data for regulatory and managerial rating models. During the last decade the increase in computational capacity, the consolidation of new methodologies to elaborate data and the availability of new information related to individuals and organizations, aided by the widespread usage of internet, set the stage for the development and application of artificial intelligence techniques in enterprises in general and financial institutions in particular. In the banking world, its application is even more relevant, thanks to the use of larger and larger data sets for credit risk modelling. The evaluation of credit risk has largely been based on client data modelling; such techniques (linear regression, logistic regression, decision trees, etc.) and data sets (financial, behavioural, sociologic, geographic, sectoral, etc.) are referred to as “traditional” and have been the de facto standards in the banking industry. The incoming challenge for credit risk managers is now to find ways to leverage the new AI toolbox on new (unconventional) data to enhance the models’ predictive power, without neglecting problems due to results’ interpretability while recognizing ethical dilemmas. Contributors are university researchers, risk managers operating in banks and other financial intermediaries and consultants. The topic is a major one for the financial industry, and this is one of the first works offering relevant case studies alongside practical problems and solutions.

Artificial Intelligence and Cyber Security in Industry 4.0 (Advanced Technologies and Societal Change)

by Velliangiri Sarveshwaran Joy Iong-Zong Chen Danilo Pelusi

This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications. ​

Artificial Intelligence and Cybersecurity: Advances and Innovations (Green Engineering and Technology)

by Ishaani Priyadarshini and Rohit Sharma

Artificial intelligence and cybersecurity are two emerging fields that have made phenomenal contributions toward technological advancement. As cyber-attacks increase, there is a need to identify threats and thwart attacks. This book incorporates recent developments that artificial intelligence brings to the cybersecurity world. Artificial Intelligence and Cybersecurity: Advances and Innovations provides advanced system implementation for Smart Cities using artificial intelligence. It addresses the complete functional framework workflow and explores basic and high-level concepts. The book is based on the latest technologies covering major challenges, issues and advances, and discusses intelligent data management and automated systems. This edited book provides a premier interdisciplinary platform for researchers, practitioners and educators. It presents and discusses the most recent innovations, trends and concerns as well as practical challenges and solutions adopted in the fields of artificial intelligence and cybersecurity.

Artificial Intelligence and Cybersecurity: Theory and Applications

by Tuomo Sipola Tero Kokkonen Mika Karjalainen

This book discusses artificial intelligence (AI) and cybersecurity from multiple points of view. The diverse chapters reveal modern trends and challenges related to the use of artificial intelligence when considering privacy, cyber-attacks and defense as well as applications from malware detection to radio signal intelligence.The chapters are contributed by an international team of renown researchers and professionals in the field of AI and cybersecurity.During the last few decades the rise of modern AI solutions that surpass humans in specific tasks has occurred. Moreover, these new technologies provide new methods of automating cybersecurity tasks. In addition to the privacy, ethics and cybersecurity concerns, the readers learn several new cutting edge applications of AI technologies.Researchers working in AI and cybersecurity as well as advanced level students studying computer science and electrical engineering with a focus on AI and Cybersecurity will find this book useful as a reference. Professionals working within these related fields will also want to purchase this book as a reference.

Artificial Intelligence and Data Analytics for Energy Exploration and Production

by Fred Aminzadeh Cenk Temizel Yasin Hajizadeh

ARTIFICAL INTELLIGENCE AND DATA ANALYTICS FOR ENERGY EXPLORATION AND PRODUCTION This groundbreaking new book is written by some of the foremost authorities on the application of data science and artificial intelligence techniques in exploration and production in the energy industry, covering the most comprehensive and updated new processes, concepts, and practical applications in the field. The book provides an in-depth treatment of the foundations of Artificial Intelligence (AI) Machine Learning, and Data Analytics (DA). It also includes many of AI-DA applications in oil and gas reservoirs exploration, development, and production. The book covers the basic technical details on many tools used in “smart oil fields”. This includes topics such as pattern recognition, neural networks, fuzzy logic, evolutionary computing, expert systems, artificial intelligence machine learning, human-computer interface, natural language processing, data analytics and next-generation visualization. While theoretical details will be kept to the minimum, these topics are introduced from oil and gas applications viewpoints. In this volume, many case histories from the recent applications of intelligent data to a number of different oil and gas problems are highlighted. The applications cover a wide spectrum of practical problems from exploration to drilling and field development to production optimization, artificial lift, and secondary recovery. Also, the authors demonstrate the effectiveness of intelligent data analysis methods in dealing with many oil and gas problems requiring combining machine and human intelligence as well as dealing with linguistic and imprecise data and rules.

Artificial Intelligence and Data Mining Approaches in Security Frameworks (Advances in Data Engineering and Machine Learning)

by Neeraj Bhargava Ritu Bhargava Pramod Singh Rathore Rashmi Agrawal

Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to Artificial Intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalize security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and Data Mining and several other computing technologies to deploy such system in an effective manner. This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice. This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library.

Artificial Intelligence and Data Mining for Mergers and Acquisitions

by Debasis Chanda

The goal of this book is to present a modeling framework for the Virtual Organization that is focused on process composition. This framework uses Predicate Calculus Knowledge Bases. Petri Net-based modeling is also discussed. In this context, a Data Mining model is proposed, using a fuzzy mathematical approach, aiming to discover knowledge. A Knowledge-Based framework has been proposed in order to present an all-inclusive knowledge store for static and dynamic properties. Toward this direction, a Knowledge Base is created, and inferences are arrived at. This book features an advisory tool for Mergers and Acquisitions of Organizations using the Fuzzy Data Mining Framework and highlights the novelty of a Knowledge-Based Service-Oriented Architecture approach and development of an Enterprise Architectural model using AI that serves a wide audience. Students of Strategic Management in business schools and postgraduate programs in technology institutes seeking application areas of AI and Data Mining, as well as business/technology professionals in organizations aiming to create value through Mergers and Acquisitions and elsewhere, will benefit from the reading of this book.

Artificial Intelligence and Data Mining in Healthcare

by Malek Masmoudi Bassem Jarboui Patrick Siarry

This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection.The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.

Artificial Intelligence and Data Science: First International Conference, ICAIDS 2021, Hyderabad, India, December 17–18, 2021, Revised Selected Papers (Communications in Computer and Information Science #1673)

by Ashwani Kumar Iztok Fister Jr. P. K. Gupta Johan Debayle Zuopeng Justin Zhang Mohammed Usman

This book constitutes selected papers presented at the First International Conference on Artificial Intelligence and Data Science, ICAIDS 2021, held in Hyderabad, India, in December 2021. The 43 papers presented in this volume were thoroughly reviewed and selected from the 195 submissions. They focus on topics of artificial intelligence for intelligent applications and data science for emerging technologies.

Artificial Intelligence and Data Science Based R&D Interventions: Proceedings of NERC 2022

by Ratnajit Bhattacharjee Debanga Raj Neog Konda Reddy Mopuri Santosh Kumar Vipparthi

This book title is a composition of multiple research efforts that are based on cutting-edge Artificial Intelligence (AI) techniques. Some of the signal processing problems are addressed with techniques from the broad areas of machine learning and deep learning.

Artificial Intelligence and Deep Learning for Computer Network: Management and Analysis (Chapman & Hall/Distributed Computing and Intelligent Data Analytics)

by Sangita Roy Rajat Subhra Chakraborty Jimson Mathew Arka Prokash Mazumdar Sudeshna Chakraborty

Artificial Intelligence and Deep Learning for Computer Network: Management and Analysis aims to systematically collect quality research spanning AI, ML, and deep learning (DL) applications to diverse sub-topics of computer networks, communications, and security, under a single cover. It also aspires to provide more insights on the applicability of the theoretical similitudes, otherwise a rarity in many such books. Features: A diverse collection of important and cutting-edge topics covered in a single volume. Several chapters on cybersecurity, an extremely active research area. Recent research results from leading researchers and some pointers to future advancements in methodology. Detailed experimental results obtained from standard data sets. This book serves as a valuable reference book for students, researchers, and practitioners who wish to study and get acquainted with the application of cutting-edge AI, ML, and DL techniques to network management and cyber security.

Artificial Intelligence and Digital Diplomacy: Challenges and Opportunities

by Fatima Roumate

This volume discusses digital diplomacy and artificial intelligence within the context of global governance and international security. Rapid digitalization has changed the way international actors interact, offering new opportunities for international and bilateral cooperation and reinforcing the role of the emergent actors within global governance. New phenomena linked to digitalization and artificial intelligence are emerging and this volume brings a multidisciplinary, mixed-methods approach to studying them. Written by globally recognized experts, each chapter presents a case study covering an emerging topic such as: international regulation of the web and digital diplomacy, the interplay of artificial intelligence and cyber diplomacy, social media and artificial intelligence as tools for digital diplomacy, the malicious use of artificial intelligence, cyber security, and data sovereignty. Incorporating both theory and practice, quantitative and qualitative analysis, this volume will be of interest to graduate students and researchers in international relations, diplomacy, security studies, and artificial intelligence, as well as diplomats and policymakers looking to understand the implications of digitalization and artificial intelligence in their fields.

Artificial Intelligence and Digital Systems Engineering (Analytics and Control)

by Adedeji B. Badiru

The resurgence of artificial intelligence has been fueled by the availability of the present generation of high-performance computational tools and techniques. This book is designed to provide introductory guidance to artificial intelligence, particularly from the perspective of digital systems engineering. Artificial Intelligence and Digital Systems Engineering provides a general introduction to the origin of AI and covers the wide application areas and software and hardware interfaces. It will prove to be instrumental in helping new users expand their knowledge horizon to the growing market of AI tools, as well as showing how AI is applicable to the development of games, simulation, and consumer products, particularly using artificial neural networks. This book is for the general reader, university students, and instructors of industrial, production, civil, mechanical, and manufacturing engineering. It will also be of interest to managers of technology, projects, business, plants, and operations.

Artificial Intelligence and Digitalization for Sustainable Development: 10th EAI International Conference, ICAST 2022, Bahir Dar, Ethiopia, November 4-6, 2022, Proceedings (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering #455)

by Bereket H. Woldegiorgis Kibret Mequanint Mekuanint A. Bitew Teketay B. Beza Abdulkerim M. Yibre

This proceedings, ICAST 2022, constitutes the refereed post-conference proceedings of the 10th International Conference on Advancement of Science and Technology, ICAST 2022, which took place in Bahir Dar, Ethiopia, in November 2022. The 17 revised full papers and one short paper were carefully reviewed and selected from 174 submissions. The papers present economic and technologic developments in modern societies related to important issues such digitization, energy transformation, impact on national economy, and its recent advancements.

Artificial Intelligence and Economic Sustainability in the Era of Industrial Revolution 5.0 (Studies in Systems, Decision and Control #528)

by Abdalmuttaleb M. A. Musleh Al-Sartawi Abdulnaser Ibrahim Nour

Industry 5.0 has been dubbed as the digital revolution with a soul. This book incorporates a wealth of research which integrates artificial intelligence (AI) with economic sustainability and Industry 5.0. It examines the human-centricity of the upcoming digital revolution and the role of sustainable technologies in enhancing the livelihoods of workers, individuals, communities, and eventually societies. It provides insight on important areas related to artificial intelligence, sustainable development, and society 5.0. The chapters present a wide range of topics including block cipher, entrepreneurship and AI, AI and stock trading decisions, digital transformation, knowledge management, chatbot engineering, cybersecurity, and smart metering system. This book is beneficial to scholars and academics who will find in it the knowledge of the support of AI and its contribution to economic sustainability, and solutions to enhance human-centricity and resilience.

Artificial Intelligence and Economic Theory: Skynet in the Market (Advanced Information and Knowledge Processing)

by Tshilidzi Marwala Evan Hurwitz

This book theoretically and practically updates major economic ideas such as demand and supply, rational choice and expectations, bounded rationality, behavioral economics, information asymmetry, pricing, efficient market hypothesis, game theory, mechanism design, portfolio theory, causality and financial engineering in the age of significant advances in man-machine systems. The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence concepts such as the swarming of birds, the working of the brain and the pathfinding of the ants. Artificial Intelligence and Economic Theory: Skynet in the Market analyses the impact of artificial intelligence on economic theories, a subject that has not been studied. It also introduces new economic theories and these are rational counterfactuals and rational opportunity costs. These ideas are applied to diverse areas such as modelling of the stock market, credit scoring, HIV and interstate conflict. Artificial intelligence ideas used in this book include neural networks, particle swarm optimization, simulated annealing, fuzzy logic and genetic algorithms. It, furthermore, explores ideas in causality including Granger as well as the Pearl causality models.

Artificial Intelligence and Economics: the Key to the Future (Lecture Notes in Networks and Systems #523)

by Domenico Marino Melchiorre Monaca

This book aims to deal with the main advances in the study of artificial intelligence, the digital and circular economy and innovation from a multidisciplinary perspective. Whoever governs the artificial intelligence will hold the keys to the world and the future. This consideration explains the growing role of artificial intelligence in our lives and the need to understand its mechanisms.This book presents original research articles addressing various aspects of artificial intelligence applied to economics, law, management, and optimization. The topics discussed include, economics, territorial policies, law, resource allocation strategies, information technology, and learning for inclusion.Combining the input of contributing professors and researchers from Italian and other foreign universities, the book is of interest to students, researchers, and practitioners, as well as members of the public in general, interested in the world of the artificial intelligence and economics.

Artificial Intelligence and Edge Computing for Sustainable Ocean Health (The Springer Series in Applied Machine Learning)

by Debashis De Diganta Sengupta Tien Anh Tran

Artificial Intelligence and Edge Computing for Sustainable Ocean Health explores the transformative role of AI and edge computing in preserving and enhancing ocean health. The growing influence of Artificial Intelligence (AI), along with the Internet of Things (IoT) in generating wide coverage of sensor networks, and Edge Computing (EC) has paved the way for investigation of underwater as well as massive marine data, thereby generating huge potential for credible research opportunities for these domains. This book’s journey begins with a broad overview of Artificial Intelligence for Sustainable Ocean Health, setting the foundation for understanding AI's potential in marine conservation. The subsequent chapter, Role of Artificial Intelligence and Technologies in Improving Ocean Health in Promoting Tourism, illustrates the synergy between technological advancements and sustainable tourism practices, demonstrating how AI can enhance the attractiveness and preservation of marine destinations. The identification, restoration, and monitoring of marine resources along with the utilization of technology continues in Utilization of Underwater Wireless Sensor Network through Supervising a Random Network Environment in the Ocean Environment has been extensively dealt with. The technical challenges of underwater imaging, essential for accurate data collection and analysis has been discussed. The importance of Explainable AI is discussed in chapters like Sustainable Development Goal 14: Explainable AI (XAI) for Ocean Health, Explainable AI (XAI) for Ocean Health: Exploring the Role of Explainable AI in Enhancing Ocean Health, and A Comprehensive Study of AI (XAI) for Ocean Health Monitoring, which emphasize transparency and trust in AI systems. Further, Revolutionizing Internet of Underwater Things with Federated Learning, Underwater Drone, Underwater Imagery with AI/ML and IoT in ROV Technology and Ocean Cleanup has been demonstrated using innovative approaches to addressing underwater challenges. The book also includes a Review on the Optics and Photonics in Environmental Sustainability, focusing on the role of optics in marine conservation. Security issues are tackled in Intelligent Hash Function Based Key-Exchange Scheme for Ocean Underwater Data Transmission, and the overarching potential of AI in marine resource management is discussed in Artificial Intelligence as Key-enabler for Safeguarding the Marine Resources.

Artificial Intelligence and Environmental Sustainability: Challenges and Solutions in the Era of Industry 4.0 (Algorithms for Intelligent Systems)

by Hui Lin Ong Ruey-An Doong Raouf Naguib Chee Peng Lim Atulya K. Nagar

The book discusses comprehensive and cutting-edge research and development endeavors, as well as innovative solutions, in implementing AI and related technologies to meet and undertake current and future challenges towards ensuring environmental sustainability. It explores the future research directions in the era of Industry 4.0. In the beginning, an overview of the utilization of Al for environmental sustainability is provided. The remaining chapters of the book cover the technological and application aspects of Al for environmental sustainability with illustrative examples. Finally, challenges with respect to deploying Al to solving environmental problems and the future trends are covered.

Artificial Intelligence and Evaluation: Emerging Technologies and Their Implications for Evaluation (Comparative Policy Evaluation)

by Steffen Bohni Nielsen, Francesco Mazzeo Rinaldi and Gustav Jakob Petersson

Artificial Intelligence and Evaluation: Emerging Technologies and Their Implications for Evaluation is a groundbreaking exploration of how the landscape of program evaluation will be redefined by artificial intelligence and other emerging digital technologies.In an era where digital technologies and artificial intelligence (AI) are rapidly evolving, this book presents a pivotal resource for evaluators navigating the transformative intersection of their practice and cutting-edge technology. Addressing the dual dimensions of how evaluations are conducted and what is evaluated, a roster of distinguished contributors illuminate the impact of AI on program evaluation methodologies. Offering a discerning overview of various digital technologies, their promises and perils, they carefully dissect the implications for evaluative processes and debate how evaluators must be equipped with the requisite skills to harness the full potential of AI tools. Further, the book includes a number of compelling use cases, demonstrating the tangible applications of AI in diverse evaluation scenarios. The use cases range from the application of GIS data to advanced text analytics. As such, this book provides evaluators with inspirational cases on how to apply AI in their practice as well as what pitfalls one must look out for.Artificial Intelligence and Evaluation is an indispensable guide for evaluators seeking to not only adapt to but thrive in the dynamic landscape of evaluation practices reshaped by the advent of artificial intelligence.The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

Artificial Intelligence and Evolutionary Algorithms in Engineering Systems: Proceedings of ICAEES 2014, Volume 1 (Advances in Intelligent Systems and Computing #324)

by Bijaya Ketan Panigrahi L. Padma Suresh Subhransu Sekhar Dash

The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

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