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Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky: 25th International Conference, AIED 2024, Recife, Brazil, July 8–12, 2024, Proceedings, Part II (Communications in Computer and Information Science #2151)
by Andrew M. Olney Irene-Angelica Chounta Zitao Liu Olga C. Santos Ig Ibert BittencourtThis volume constitutes poster papers and late breaking results presented during the 25th International Conference on Artificial Intelligence in Education, AIED 2024, which took place in Recife, Brazil, during July 8–12, 2024. The 18 full papers and 92 short papers were carefully reviewed and selected from 200 submissions. They are organized in topical sections as follows: Part One: Blue Sky, Industry, Innovation and Practitioner, WideAIED and Late-Breaking Results. Part Two: Late-Breaking Results, Doctoral Consortium, Workshops and Tutorials.
Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky: 25th International Conference, AIED 2024, Recife, Brazil, July 8–12, 2024, Proceedings, Part I (Communications in Computer and Information Science #2150)
by Olga C. Santos Ig Ibert Bittencourt Irene-Angelica Chounta Andrew M. Olney Zitao LiuThis volume constitutes poster papers and late breaking results presented during the 25th International Conference on Artificial Intelligence in Education, AIED 2024, which took place in Recife, Brazil, during July 8–12, 2024. The 18 full papers and 92 short papers were carefully reviewed and selected from 200 submissions. They are organized in topical sections as follows: Part One: Blue Sky, Industry, Innovation and Practitioner, WideAIED and Late-Breaking Results. Part Two: Late-Breaking Results, Doctoral Consortium, Workshops and Tutorials.
Artificial Intelligence in Education: The Power and Dangers of ChatGPT in the Classroom (Studies in Big Data #144)
by Amina Al-Marzouqi Said A. Salloum Mohammed Al-Saidat Ahmed Aburayya Babeet GuptaThis book aims to bring together a collection of innovative and cutting-edge research that addresses the various challenges in the application and theoretical aspects of ChatGPT in education. ChatGPT is a large language model developed by OpenAI that has the ability to generate human-like text based on a prompt. This has significant potential for use in the field of education, as it allows for the creation of personalized, interactive learning experiences, automating assessment and grading, and more. In e-learning, ChatGPT is used to provide instant feedback and support to students, as well as generate interactive conversations in the target language for language learning. It is also integrated with existing learning management systems and educational technology platforms to enhance their capabilities. In research, ChatGPT is used for natural language processing and sentiment analysis to gather insights on student learning experiences and educational outcomes. However, it is important to note that there are also ethical and privacy concerns that come with using language models like ChatGPT in education, such as data protection and the potential for bias. Overall, the use of ChatGPT in education has the potential to revolutionize the way we learn, teach, and access information. The book seeks to publish original manuscripts that cover a broad range of topics, from the development of new chatbot technologies and their integration into the classroom, to the examination of the ethical and pedagogical implications of these systems. By compiling the latest developments in the field and highlighting new areas for exploration, this book provides valuable insights and perspectives for researchers, educators, and practitioners working in the field of ChatGPT and education. The ultimate goal is to advance the understanding of ChatGPT and its role in education and to promote its effective and responsible use in the classroom and beyond.
Artificial Intelligence in Education Technologies: Proceedings of 2024 5th International Conference on Artificial Intelligence in Education Technology (Lecture Notes on Data Engineering and Communications Technologies #228)
by Tim Schlippe Eric C. K. Cheng Tianchong WangThis book is a collection of selected research papers presented at the 2024 5th International Conference on Artificial Intelligence in Education Technology (AIET 2024), held in Barcelona, Spain, on July 29 - 31, 2024. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems. It is a timely and up-to-date publication responsive to the rapid development of AI technologies, practices and their increasingly complex interplay with the education domain. It promotes the cross-fertilisation of knowledge and ideas from researchers in various fields to construct the interdisciplinary research area of AI in Education. These subject areas include computer science, cognitive science, education, learning sciences, educational technology, psychology, philosophy, sociology, anthropology and linguistics. The feature of this book will contribute from diverse perspectives to form a dynamic picture of AI in Education. It also includes various domain-specific areas for which AI and other education technology systems have been designed or used in an attempt to address challenges and transform educational practice. Education stands as a cornerstone for societal progress, and ensuring universal access to quality education is integral to achieving Goal 4 of the United Nations' Sustainable Development Goals (SDGs). The goal is to ensure inclusive and equitable quality education for all by 2030. This involves not only expanding access to education but also improving the quality of education to promote lifelong learning opportunities. AI has the potential to significantly contribute to the achievement of Goal 4. It is committed to exploring how AI may play a role in bringing more innovative practices, transforming education, and triggering an exponential leap towards the achievement of the Education 2030 Agenda. Providing broad coverage of recent technology-driven advances and addressing a number of learning-centric themes, the book is an informative and useful resource for researchers, practitioners, education leaders and policy-makers who are involved or interested in AI and education.
Artificial Intelligence in Financial Markets: Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics (New Developments in Quantitative Trading and Investment)
by Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous and Konstantinos TheofilatosAs technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
Artificial Intelligence in Healthcare: First International Conference, AIiH 2024, Swansea, UK, September 4–6, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14975)
by Marco Ceccarelli Xianghua Xie Iain Styles Gibin PowathilThe two-volume set LNCS 14975 + 14976 constitutes the proceedings of the First International Conference on Artificial Intelligence in Healthcare, AIiH 2024, which took place in Swansea, UK, in September 2024. The 47 full papers included in the proceedings were carefully reviewed and selected from 70 submissions. They were organized in the following topical sections: Part I: Personalised Healthcare and Medicine; AI driven early diagnosis and prevention; AI driven robotics for healthcare; AI in mental health; Part II: AI in proactive care and intervention; AI-aided medical imaging and analysis; Medical signal and image processing; Assisted living technology; Digital twinning, virtual pathology and oncology; Patient data, privacy and ethics.
Artificial Intelligence in Healthcare and Medicine
by Kayvan NajarianThis book provides a comprehensive overview of the recent developments in clinical decision support systems, precision health, and data science in medicine. The book targets clinical researchers and computational scientists seeking to understand the recent advances of artificial intelligence (AI) in health and medicine. Since AI and its applications are believed to have the potential to revolutionize healthcare and medicine, there is a clear need to explore and investigate the state-of-the-art advancements in the field. This book provides a detailed description of the advancements, challenges, and opportunities of using AI in medical and health applications. Over 10 case studies are included in the book that cover topics related to biomedical image processing, machine learning for healthcare, clinical decision support systems, visualization of high dimensional data, data security and privacy, bioinformatics, and biometrics. The book is intended for clinical researchers and computational scientists seeking to understand the recent advances of AI in health and medicine. Many universities may use the book as a secondary training text. Companies in the healthcare sector can greatly benefit from the case studies covered in the book. Moreover, this book also: Provides an overview of the recent developments in clinical decision support systems, precision health, and data science in medicine Examines the advancements, challenges, and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor. Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY, and the former Chair of Cyber Security, University of York. Enrique Domínguez is a professor in the Department of Computer Science at the University of Malaga and a member of the Biomedical Research Institute of Malaga. Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of the Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.
Artificial Intelligence in Material Science: Advances
by Mohamed Arezki MellalArtificial intelligence (AI) in the form of machine learning and nature-inspired optimization algorithms are vastly used in material science. These techniques improve many quality metrics, such as reliability and ergonomics.This book highlights the recent challenges in this field and helps readers to understand the subject and develop future works. It reviews the latest methods and applications of AI in material science. It covers a wide range of topics, including Material processing; Properties prediction; Conventional machining, such as turning, boring, grinding, and milling; non-conventional machining, such as electrical discharge machining, electrochemical machining, laser machining, plasma machining, ultrasonic machining, chemical machining, and water-jet machining; Machine tools, such as programming, design, and maintenance. AI techniques reviewed in the book include Machine learning, Fuzzy logic, Genetic algorithms, Particle swarm optimization, Cuckoo search, Grey wolf optimizer, and Ant colony optimization.
Artificial Intelligence in Mechatronics and Civil Engineering: Bridging the Gap (Emerging Trends in Mechatronics)
by Ehsan Momeni Danial Jahed Armaghani Aydin AziziRecent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering. The power of artificial intelligence and machine learning techniques in solving some examples of real-life problems in engineering is highlighted in this book. The implementation process to design the optimum intelligent models is discussed in this book.
Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings (Lecture Notes in Computer Science #10259)
by Annette ten Teije, Christian Popow, John H. Holmes and Lucia SacchiThis book constitutes the refereed proceedings of the 16th Conference on Artificial Intelligence in Medicine, AIME 2017, held in Vienna, Austria, in June 2017.The 21 revised full and 23 short papers presented were carefully reviewed and selected from 113 submissions. The papers are organized in the following topical sections: ontologies and knowledge representation; Bayesian methods; temporal methods; natural language processing; health care processes; and machine learning, and a section with demo papers.
Artificial Intelligence in Medicine: 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14844)
by Robert Moskovitch Joseph Finkelstein Enea ParimbelliThis two-volume set LNAI 14844-14845 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Medicine, AIME 2024, held in Salt Lake City, UT, USA, during July 9-12, 2024. The 54 full papers and 22 short papers presented in the book were carefully reviewed and selected from 335 submissions. The papers are grouped in the following topical sections: Part I: Predictive modelling and disease risk prediction; natural language processing; bioinformatics and omics; and wearable devices, sensors, and robotics. Part II: Medical imaging analysis; data integration and multimodal analysis; and explainable AI.
Artificial Intelligence in Medicine: 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part II (Lecture Notes in Computer Science #14845)
by Robert Moskovitch Joseph Finkelstein Enea ParimbelliThis two-volume set LNAI 14844-14845 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Medicine, AIME 2024, held in Salt Lake City, UT, USA, during July 9-12, 2024. The 54 full papers and 22 short papers presented in the book were carefully reviewed and selected from 335 submissions. The papers are grouped in the following topical sections: Part I: Predictive modelling and disease risk prediction; natural language processing; bioinformatics and omics; and wearable devices, sensors, and robotics. Part II: Medical imaging analysis; data integration and multimodal analysis; and explainable AI.
Artificial Intelligence in Medicine: 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26–29, 2019, Proceedings (Lecture Notes in Computer Science #11526)
by David Riaño Annette Ten Teije Szymon WilkThis book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.
Artificial Intelligence in Medicine: 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, Virtual Event, June 15–18, 2021, Proceedings (Lecture Notes in Computer Science #12721)
by Allan Tucker Pedro Henriques Abreu Jaime Cardoso Pedro Pereira Rodrigues David RiañoThis book constitutes the refereed proceedings of the 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, held as a virtual event, in June 2021. The 28 full papers presented together with 30 short papers were selected from 138 submissions. The papers are grouped in topical sections on image analysis; predictive modelling; temporal data analysis; unsupervised learning; planning and decision support; deep learning; natural language processing; and knowledge representation and rule mining.
Artificial Intelligence in Music, Sound, Art and Design: 13th International Conference, EvoMUSART 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings (Lecture Notes in Computer Science #14633)
by Colin Johnson Sérgio M. Rebelo Iria SantosThis book constitutes the refereed proceedings of the 13th International Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2024, held as part of EvoStar 2024, in Aberystwyth, UK, April 3–5, 2024. The 17 full papers and 8 short papers presented in this book were carefully reviewed and selected from 55 submissions. The main purpose of this conference proceedings was to bring together practitioners who are using Artificial Intelligence techniques for artistic tasks, providing the opportunity to promote, present, and discuss ongoing work in the area.
Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine: First International Workshop, AIPAD 2024 and First International Workshop, PILM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings (Lecture Notes in Computer Science #15197)
by Federica Proietto Salanitri Serestina Viriri Ulaş Bağcı Pallavi Tiwari Boqing Gong Concetto Spampinato Simone Palazzo Giovanni Bellitto Nancy Zlatintsi Panagiotis Filntisis Cecilia S. Lee Aaron Y. LeeThis volume constitutes the refereed proceedings of the First International Workshop on Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, AIPAD 2024 and the First International Workshop on Personalized Incremental Learning in Medicine, PILM 2024, held in conjunction with MICCAI 2024, in Marrakesh, Morocco, in October 2024. The 8 full papers included in these proceedings were carefully reviewed and selected from 9 submissions. They were organized in topical sections as follows: artificial intelligence in pancreatic disease detection and diagnosis; and personalized incremental learning in medicine.
Artificial Intelligence in Prescriptive Analytics: Innovations in Decision Analysis, Intelligent Optimization, and Data-Driven Decisions (Intelligent Systems Reference Library #260)
by Witold Pedrycz Gilberto Rivera Eduardo Fernández Gustavo Javier MeschinoConsidering the advances of the different approaches and applications in the last years, and even in the last months, this is a particular moment in history to transform every data-driven decision-making process with the power of Artificial Intelligence (AI). This book reveals, through concrete case studies and original application ideas, how cutting-edge AI techniques are revolutionizing industries such as finance, health care, and manufacturing. It invites us to discover how machine learning, decision analysis, and intelligent optimization are changing, directly or indirectly, almost all aspects of our daily lives. This comprehensive book offers practical insights and real-world applications for professionals, researchers, and students alike. It helps to learn how to apply AI for smarter, data-driven decisions in areas like supply chain management, risk assessment, and even personalized medicine. Be inspired by the chapters of this book and unlock the full potential of AI in your field!
Artificial Intelligence in Sport Performance Analysis
by Duarte Araújo Micael S Couceiro Ludovic Seifert Hugo Sarmento Keith DavidsTo understand the dynamic patterns of behaviours and interactions between athletes that characterize successful performance in different sports is an important challenge for all sport practitioners. This book guides the reader in understanding how an ecological dynamics framework for use of artificial intelligence (AI) can be implemented to interpret sport performance and the design of practice contexts. By examining how AI methodologies are utilized in team games, such as football, as well as in individual sports, such as golf and climbing, this book provides a better understanding of the kinematic and physiological indicators that might better capture athletic performance by looking at the current state-of-the-art AI approaches. Artificial Intelligence in Sport Performance Analysis provides an all-encompassing perspective in an innovative approach that signals practical applications for both academics and practitioners in the fields of coaching, sports analysis, and sport science, as well as related subjects such as engineering, computer and data science, and statistics.
Artificial Intelligence, Learning and Computation in Economics and Finance (Understanding Complex Systems)
by Ragupathy VenkatachalamThis book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, computer science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded.Theoretical and empirical studies featured in this book draw on a variety of approaches such as agent-based modeling, numerical simulations, computable economics, as well as employing tools from artificial intelligence and machine learning algorithms. The use of computational approaches to perform counterfactual thought experiments are also introduced, which help transcend the limits posed by traditional mathematical and statistical tools.The book also includes discussions on methodology, epistemology, history and issues concerning prediction, validation, and inference, all of which have become pertinent with the increasing use of computational approaches in economic analysis.
Artificial Intelligence Logic and Applications: 4th International Conference, AILA 2024, Lanzhou, China, August 10–11, 2024, Proceedings (Communications in Computer and Information Science #2248)
by Songmao Zhang Luis Soares BarbosaThis book constitutes the proceedings of the 4th International Conference on Artificial Intelligence Logic and Applications, AILA 2024, held in Lanzhou, China, during August 10–11, 2024. The 16 full papers and the 11 short papers included in this volume were carefully reviewed and selected from 45 submissions. The papers cover the following topics: AI logic foundation; AI logic reasoning; AI logic applications.
Artificial Intelligence Logic and Applications: The 2nd International Conference, AILA 2022, Shanghai, China, August 26–28, 2022, Proceedings (Communications in Computer and Information Science #1657)
by Songmao Zhang Yixiang ChenThis book constitutes refereed proceedings of the 2nd International Conference on Artificial Intelligence Logic and Applications 2022 held in Shanghai, China from August 26–28, 2022.The 20 full papers presented in this volume were carefully reviewed and selected from a total of 27 submissions. The papers in the volume are organised according to the following topical headings: program logic; fuzzy logic; applications; author index.
Artificial Intelligence Logic and Applications: The 3rd International Conference, AILA 2023, Changchun, China, August 5–6, 2023, Proceedings (Communications in Computer and Information Science #1917)
by Songmao Zhang Yonggang ZhangThis book constitutes the proceedings of the Third International Conference, AILA 2023, held in Changchun, China, during August 5–6, 2023. The 26 full papers and the 10 short papers included in this volume were carefully reviewed and selected from 56 submissions. This volume aims to provide novel ideas, original research achievements, and practical experiences in a broad range of artificial intelligence logic and applications.
Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications #186)
by Panos M. Pardalos Stamatina Th. Rassia Arsenios TsokasThis volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities.Special features include:New research on the design of city elements and smart systems with respect to new technologies and scientific thinkingDiscussions on the theoretical background that lead to smart cities for the futureNew technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environmentsThe book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.
Artificial Intelligence, Optimization, and Data Sciences in Sports (Springer Optimization and Its Applications #218)
by Maude J. Blondin Iztok Fister Jr. Panos M. PardalosThis book delves into the dynamic intersection of data science, data mining, machine learning, and optimization within sports. It compiles and presents the latest achievements in this vibrant and emerging research area, offering a comprehensive overview of how these technologies revolutionize sports analytics and performance. Topical coverage includes artificial intelligence in sports, automated machine learning for training sessions, computational social science, and deep learning applications. Readers will also explore cutting-edge concepts such as digital twins in sports and sports prediction through data analysis. This volume highlights theoretical advancements and practical case studies that demonstrate real-world applications. Ideal for researchers, practitioners, and students in fields related to sports science, data analytics, and machine learning, this book serves as a crucial resource for anyone looking to understand the transformative impact of technology on sports. Whether you are an academic scholar or a professional working in the industry, this collection offers valuable insights that bridge the gap between research and practical solutions.
Artificial Intelligence over Infrared Images for Medical Applications: Third International Conference, AIIIMA 2024, Virtual Event, November 9, 2024, Proceedings (Lecture Notes in Computer Science #15279)
by Siva Teja Kakileti Geetha Manjunath Robert G. Schwartz Eddie Y. K. NgThis book constitutes the refereed proceedings of the Third International Conference on Artificial Intelligence over Infrared Images for Medical Applications, AIIIMA 2024, held as a virtual event, on November 9, 2024. The 11 full papers presented in these proceedings were carefully reviewed and selected from 27 submissions. These papers focus on the application of Artificial Intelligence in medical infrared imaging for cancer screening, cancer diagnosis, cancer risk assessment, treatment monitoring, sports injury, diabetic foot ulcers detection, and pain management.