Kunstig intelligens

This book constitutes the proceedings of the 11th International Conference on Big Data and Artificial Intelligence, BDA 2023, held in Delhi, India, during December 7¿9, 2023. The17 full papers presented in this volume were carefully reviewed and selected from 67 submissions. The papers are organized in the following topical sections: ¿Keynote Lectures, Artificial Intelligence in Healthcare, Large Language Models, Data Analytics for Low Resource Domains, Artificial Intelligence for Innovative Applications and Potpourri.

Water, our planet's life force, faces multiple challenges in the 21st century, including surging global demand, shifting climate patterns, and the urgent need for sustainable management. Guidance, knowledge, and hope is sharply needed in academia and technology industries, and Innovations in Machine Learning and IoT for Water Management is a formidable resource to provide these necessities. This book delves into the dynamic synergy of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), ushering in a new era of water resource stewardship. This book embarks on a journey through the frontiers of AI and IoT, unveiling their transformative impact on water management. From the vantage point of satellite imagery analysis, it scrutinizes the Earth's vital signs, unlocking crucial insights into water resources. It chronicles the rise of AI-powered predictive analytics, a revolutionary force propelling precision water usage and conservation. This book explains how IoT can be an effective tool to increase intelligence of our water systems. The book meticulously navigates through domains as diverse as aquifer monitoring, hydropower generation optimization, and predictive analytics for water consumption. This book caters to a diverse audience, from water management experts and environmental scientists to data science aficionados and IoT enthusiasts. Engineers seeking to reimagine the future of water systems, technology enthusiasts eager to delve into AI's potential, and individuals impassioned by preserving water will all find a well-needed resource in these pages.

Navigating Emerging Tech EthicsCONVERSATIONAL CHAT INFORMATIVE BOOKBy ABEBE- BARD AI WOLDEMARIAM The rapid advancement of emerging technologies has brought about a plethora of ethical concerns, particularly in the realms of targeted surveillance and manipulation. This book delves into these critical issues, examining the potential harms and benefits of these technologies while exploring strategies for fostering ethical and responsible development.In this thought-provoking volume, Abebe-Bard AI Woldemariam provides a comprehensive overview of the ethical landscape surrounding emerging technologies. Drawing upon cutting-edge research and real-world case studies, the book explores the ethical implications of targeted surveillance, addressing issues such as privacy, autonomy, and discrimination. It also examines the potential for manipulation through social media, algorithms, and other forms of digital technology, considering the impact on individuals and society as a whole.Key Features:Explores the ethical implications of targeted surveillance and manipulation in the context of emerging technologies.Examines the potential harms and benefits of these technologies, considering the impact on individuals and society.Provides strategies for fostering ethical and responsible development of emerging technologies.Offers a comprehensive overview of the ethical landscape surrounding emerging technologies.Draws upon cutting-edge research and real-world case studies.Target Audience:Policymakers and regulators responsible for developing and overseeing emerging technologies.Researchers and scholars in the fields of technology ethics, law, and social sciences.Technology professionals concerned with the ethical implications of their work.Informed citizens interested in understanding the ethical challenges posed by emerging technologies.

Are you ready to revolutionize your fraternity or sorority recruitment? Michael Ayalon and Ben Gold have crafted an extraordinary guide that will take your Greek Life experience to the next level. In "Using AI to Grow Your Fraternity or Sorority," they provide you with a cutting-edge playbook that seamlessly integrates Artificial Intelligence (AI) into the heart of your organization. Are you ready to reshape the future of your fraternity or sorority? "Using AI to Grow Your Fraternity or Sorority" is your key to unlocking a new era of recruitment success. Get your copy today and embark on a journey of innovation, growth, and excellence in Fraternity and Sorority Life.

This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in introductory textbooks.  This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning.  

This book presents an extension of fuzzy set theory allowing for multi-polar information, discussing its impact on the theoretical and practical development of multi-criteria decision making. It reports on set of hybrid models developed by the authors, and show how they can be adapted, case by case, to the lack of certainty under a variety of criteria. Among them, hybrid models combining m-polar fuzzy sets with rough, soft and 2-tuple linguistic sets, and m-polar hesitant fuzzy sets and hesitant m-polar fuzzy are presented, together with some significant applications. In turn, outranking decision-making techniques such as m-polar fuzzy ELECTRE I, II, III and IV methods, as well as m-polar fuzzy PROMETHEE I and II methods, are developed. The efficiency of these decision-making procedures, as well as other possible extensions studied by the authors, is shown in some real-world applications. Overall, this book offers a guide on methodologies to deal with the multi-polarity and fuzziness of the real-world problems, simultaneously. By including algorithms and computer programming codes, it provides a practice-oriented reference guide to both researchers and professionals working at the interface between computational intelligence and decision making.

This book presents the proceedings of the International Conference on Managing Business through Web Analytics (ICMBWA 2021). The conference provides a global forum for sharing knowledge and results in theory, methodology, and applications of Web Analytics and their role in the formulation and the orientation of businesses' strategies. The aim of the conference is to provide a platform for researchers and practitioners from both academia and industry to meet and share their works in the field. Is an excellent resource for scholars, experts and industrial in the fields represented, as well as Ph.D. students seeking an entryway into current research in data analytics, Web analytics, machine learning algorithms, and their various applications within businesses. 

This book constitutes the refereed proceedings of the 15th International Symposium on Search-Based Software Engineering, SSBSE 2023, which took place in San Francisco, CA, USA, during December 8, 2023.The 7 full and 7 short papers included in this book were carefully reviewed and selected from 23 submissions. They focus on formulating various optimization problems in software engineering as search problems, addressing them with search techniques, intending to automate complex software engineering tasks.

Der vorliegende Band markiert einen initialen Schritt zur umfassenden Erörterung des Themenfelds ¿Vertrauen in KI¿ aus vielfältigen Blickwinkeln. Dabei wird eine Herangehensweise sowohl aus wirtschafts- und sozialwissenschaftlicher als auch aus informationstechnischer Perspektive gewählt, die zudem interdisziplinäre Aspekte einbezieht. Insgesamt präsentiert der Band fünfzehn Beiträge von 25 renommierten Autorinnen und Autoren, die ihre Expertise aus vierzehn unterschiedlichen Einrichtungen einbringen. Ziel dieser Debatten ist es, Lernende, Lehrende, Forschende sowie Entscheidungsträgerinnen und -träger aus Politik und Wirtschaft dazu zu befähigen, auf Basis von Fakten eine fundierte Meinung zu bilden. Auf dieser Grundlage sollen sie in der Lage sein, gut durchdachte persönliche Entscheidungen im Umgang mit KI zu treffen.

Dieses Lehrbuch betrachtet Data Management als interdisziplinäres Konzept mit Fokus auf den Zielen datengetriebener Unternehmen. Im Zentrum steht die interaktive Entwicklung eines Unternehmensdatenmodells für ein virtuelles Unternehmen mit Unterstützung eines online Learning Games unter Einbeziehung der Aufgaben, Ziele und Grundsätze des Data Managements, typischer Data-Management-Komponenten und Frameworks wie Datenmodellierung und Design, Metadaten Management, Data Architecture, und Data Governance, und verknüpft diese mit datengetriebenen Anwendungen wie Business Warehousing, Big Data, In-Memory Data Management, und Machine Learning im Data Management Kontext.Das Buch dient als Lehrbuch für Studierende der Informatik, der Wirtschaft und der Wirtschaftsinformatik an Universitäten, Hochschulen und Fachschulen und zur industriellen Aus- und Weiterbildung.

How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee. A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning. In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons.

Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment not only supports the development of Intelligent & Connected Transportation, but also promotes the landing application of autonomous driving. Areas covered include the fusion target perception method based on vehicle vision and millimeter wave radar, cross-field of view object perception method, vehicle motion recognition method based on vehicle road fusion information, vehicle trajectory prediction method based on improved hybrid neural network and driving map construction driven by road perception fusion are introduced in this book. Benefiting from the development of computer technique, the advanced machine learning and artificial intelligence theories are used by this book to show readers the construction process of the Autonomous Driving Map.

This book constitutes the refereed proceedings of the 19th International Symposium on Algorithmics of Wireless Networks, ALGOWIN 2023, held in Amsterdam, The Netherlands, during September 7¿8, 2023.The 10 full papers included in this book were carefully reviewed and selected from 22 submissions. They were organized in topical sections as follows: design and analysis of algorithms, models of computation and experimental analysis.

This book constitutes the refereed proceedings of the 26th Brazilian Symposium on Formal Methods, SBMF 2023, held in Manaus, Brazil, during December 4-8, 2023.The 7 full papers and 2 short papers presented in this book were carefully reviewed and selected from 16 submissions.The papers are divided into the following topical sections: specification and modeling languages; testing; and verification and validation.

This book aims to gather high-quality research papers on developing theories, frameworks, architectures, and algorithms for solving complex challenges in smart healthcare applications for real industry use. It explores the recent theoretical and practical applications of metaheuristics and optimization in various smart healthcare contexts. The book also discusses the capability of optimization techniques to obtain optimal parameters in ML and DL technologies. It provides an open platform for academics and engineers to share their unique ideas and investigate the potential convergence of existing systems and advanced metaheuristic algorithms. The book's outcome will enable decision-makers and practitioners to select suitable optimization approaches for scheduling patients in crowded environments with minimized human errors.The healthcare system aims to improve the lives of disabled, elderly, sick individuals, and children. IoT-based systems simplify decision-making and task automation, offering an automated foundation. Nature-inspired metaheuristics and mining algorithms are crucial for healthcare applications, reducing costs, increasing efficiency, enabling accurate data analysis, and enhancing patient care. Metaheuristics improve algorithm performance and address challenges in data mining and ML, making them essential in healthcare research. Real-time IoT-based healthcare systems can be modeled using an IoT-based metaheuristic approach to generate optimal solutions.Metaheuristics are powerful technologies for optimization problems in healthcare systems. They balance exact methods, which guarantee optimal solutions but require significant computational resources, with fast but low-quality greedy methods. Metaheuristic algorithms find better solutions while minimizing computational time. The scientific community is increasingly interested in metaheuristics, incorporating techniques from AI, operations research, and soft computing. New metaheuristicsoffer efficient ways to address optimization problems and tackle unsolved challenges. They can be parameterized to control performance and adjust the trade-off between solution quality and resource utilization. Metaheuristics manage the trade-off between performance and solution quality, making them highly applicable to real-time applications with pragmatic objectives.

The book delivers an excellent professional development resource for educators and practitioners on the cutting-edge computational intelligence techniques and applications. It covers many areas and topics of computational intelligence techniques and applications proposed by computational intelligence experts and researchers and furthers the enhancement of the community outreach and engagement component of computational intelligence techniques and applications. Furthermore, it presents a rich collection of manuscripts in highly regarded computational intelligence techniques and applications topics that have been creatively compiled. Computers are capable of learning from data and observations and providing solutions to real-life complex problems, following the same reasoning approach of human experts in various fields. This book endows a rich collection of applications in widespread areas. Among the areas addressed in this book are Computational Intelligence Principles andTechniques; CI in Manufacturing, Engineering, and Industry; CI in Recognition and Processing; CI in Robotics and Automation; CI in Communications and Networking; CI in Traditional Vehicles, Electric Vehicles, and Autonomous Vehicles; CI in Smart Cities and Smart Energy Systems; and CI in Finance, Business, Economics, and Education. These areas span many topics including repetitive manufacturing, discrete manufacturing, process manufacturing, electronic systems, speech recognition, pattern recognition, signal processing, image processing, industrial monitoring, vision systems for automation and robotics, cooperative and network robotics, perception, planning, control, urban traffic networks control, vehicle-to-roadside communications, smart buildings, smart urbanism, smart infrastructure, smart connected communities, smart energy, security, arts, and music.

This book constitutes the proceedings of the 27th Annual Conference on Medical Image Understanding and Analysis, MIUA 2023, which took place in Aberdeen, UK, during July 19¿21, 2023.The 24 full papers presented in this book were carefully reviewed and selected from 42 submissions. They were organized in topical sections as follows: Image interpretation; radiomics, predictive models and quantitative imaging; image classification; and biomarker detection.

This book presents a variety of advanced statistical methods at a level suitable for advanced undergraduate and graduate students as well as for others interested in familiarizing themselves with these important subjects. It proceeds to illustrate these methods in the context of real-life applications in a variety of areas such as genetics, medicine, and environmental problems.The book begins in Part I by outlining various data types and by indicating how these are normally represented graphically and subsequently analyzed. In Part II, the basic tools in probability and statistics are introduced with special reference to symbolic data analysis. The most useful and relevant results pertinent to this book are retained. In Part III, the focus is on the tools of machine learning whereas in Part IV the computational aspects of BIG DATA are presented.This book would serve as a handy desk reference for statistical methods at the undergraduate and graduate level as well as be useful in courses which aim to provide an overview of modern statistics and its applications.

This book explores the employment of market mechanisms for data-interactive innovations. Based on the concept of innovators' marketplaces the book introduces a new concept of 'data jackets' to enable analysis of what kind of data exist, where they are located, and what kind of information they hold, even if the contents of data cannot be made publicly available.The book presents the concept of a marketplace for data in the case of data-interactive innovations. It introduces the marketplace as a platform for value-based exchange of data and - based on the idea of the innovators' marketplace - explains how data jackets can be utilized independently from the actual contents of the data. Specific chapters deepen the understanding of variables, constraints and intentions as constituent parts of data jackets, and the extension to variable quest, a process towards the design of data. A number of case studies showcases how the methods and processes presented can be employed in real-life contexts. Finally the authors present some extensions of the concept for web-based IMDJ and connections to business information system and an outlook.

This book comprises a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2021), held at Technical University of Sofia, Sofia, Bulgaria, during 08-10 July 2021. The book covers research papers in the field of N-dimensional multicomponent image processing, multidimensional image representation and super-resolution, 3D image processing and reconstruction, MD computer vision systems, multidimensional multimedia systems, neural networks for MD image processing, data-based MD image retrieval and knowledge data mining, watermarking, hiding and encryption of MD images, MD image processing in robot systems, tensor-based data processing, 3D and multi-view visualization, forensic analysis systems for MD images and many more.

This book constitutes the proceedings of the 18th International Conference, ICTERI 2023, held in Ivano-Frankivsk, Ukraine, during September 18¿22, 2023.The 21 full papers included in this volume were carefully reviewed and selected from 90 submissions. The volume focuses on research advances in ICT, business or academic applications of ICT, and design and deployment of ICT infrastructures.

As a new interpretable model, three-way decision has also received academic attention in machine learning. With respect to different hesitant fuzzy information, this book deeply discusses the deduction process of decision rules of three-way decision and generates interpretable knowledge with the risk semantics. It further explores the applications of three-way decision to support healthcare management. This book is used as a reference for engineers, technicians, and researchers who are working in the fields of management science, operation management, computer science, information management, fuzzy mathematics, business intelligence, and other fields. It also serves as a textbook for postgraduate and senior undergraduate students of the relevant professional institutions of higher learning.

This book discusses the role of mobile network data in urban informatics, particularly how mobile network data is utilized in the mobility context, where approaches, models, and systems are developed for understanding travel behavior. The objectives of this book are thus to evaluate the extent to which mobile network data reflects travel behavior and to develop guidelines on how to best use such data to understand and model travel behavior. To achieve these objectives, the book attempts to evaluate the strengths and weaknesses of this data source for urban informatics and its applicability to the development and implementation of travel behavior models through a series of the authors' research studies.Traditionally, survey-based information is used as an input for travel demand models that predict future travel behavior and transportation needs. A survey-based approach is however costly and time-consuming, and hence its information can be dated and limited to a particular region. Mobile network data thus emerges as a promising alternative data source that is massive in both cross-sectional and longitudinal perspectives, and one that provides both broader geographic coverage of travelers and longer-term travel behavior observation. The two most common types of travel demand model that have played an essential role in managing and planning for transportation systems are four-step models and activity-based models. The book's chapters are structured on the basis of these travel demand models in order to provide researchers and practitioners with an understanding of urban informatics and the important role that mobile network data plays in advancing the state of the art from the perspectives of travel behavior research.

This book introduces readers to the fundamentals of and recent advances in federated learning, focusing on reducing communication costs, improving computational efficiency, and enhancing the security level. Federated learning is a distributed machine learning paradigm which enables model training on a large body of decentralized data. Its goal is to make full use of data across organizations or devices while meeting regulatory, privacy, and security requirements. The book starts with a self-contained introduction to artificial neural networks, deep learning models, supervised learning algorithms, evolutionary algorithms, and evolutionary learning. Concise information is then presented on multi-party secure computation, differential privacy, and homomorphic encryption, followed by a detailed description of federated learning. In turn, the book addresses the latest advances in federate learning research, especially from the perspectives of communication efficiency, evolutionary learning, and privacy preservation.The book is particularly well suited for graduate students, academic researchers, and industrial practitioners in the field of machine learning and artificial intelligence. It can also be used as a self-learning resource for readers with a science or engineering background, or as a reference text for graduate courses.       

Manufacturing from Industry 4.0 to Industry 5.0: Advances and Applications unfolds establishing three main pillars: (i) it investigates the theoretical background of the current industrial practice within the framework of industry 4.0 by presenting its key definitions and backbone technologies; (ii) it discusses the methods and state-of-the-art developments employed in the ongoing digital transformation of companies worldwide to promote more resilient, sustainable, and human-centric smart manufacturing and production networks; and (iii) it outlines a strategic plan for the transition from industry 4.0 to industry 5.0. Written by an international group of expert scientists, this volume offers an overview of the most recent research in the field and provides actionable insights to benefit audiences in both academia and industry.

Handbook of Robotic Surgery serves as a primer covering the main areas of knowledge in robotic surgery. This comprehensive book provides essential information on all aspects related to robotic surgery, from the present up to the future. The discussion presented in sections ranges from the historical background of robotic surgery up to more recent and future technological innovations such as remote controls, surgically distant collaboration, simulators, modern surgical robotics, fluorescence-guided surgery, and virtual reality. The book also contains sections dedicated to the safety conditions in surgery and patient protection, which will be suitable for surgeons, health professionals, biomedical engineering professionals, healthcare administrators, and students. There are specific chapters for all areas in which robotic surgery has been used in daily clinical practice or is under development.