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Recent Advances and Applications of Fuzzy Metric Fixed Point Theory
by Dhananjay Gopal Juan Martinez MorenoThis book not only presents essential material to understand fuzzy metric fixed point theory, but also enables the readers to appreciate the recent advancements made in this direction. It contains seven chapters on different topics in fuzzy metric fixed point theory. These chapters cover a good range of interesting topics such as con- vergence problems in fuzzy metrics, fixed figure problems, and applications of fuzzy metrics. The main focus is to unpack a number of diverse aspects of fuzzy metric fixed point theory and its applications in an understandable way so that it could help and motivate young graduates to explore new avenues of research to extend this flourishing area in different directions. The discussion on fixed figure problems and fuzzy contractive fixed point theorems and their different generalizations invites active researchers in this field to develop a new branch of fixed point theory. Features: Explore the latest research and developments in fuzzy metric fixed point theory. Describes applications of fuzzy metrics to colour image processing. Covers new topics on fuzzy fixed figure problems. Filled with examples and open problems. This book serves as a reference book for scientific investigators who want to analyze a simple and direct presentation of the fundamentals of the theory of fuzzy metric fixed point and its applications. It may also be used as a textbook for postgraduate and research students who try to derive future research scope in this area.
Recent Advances and Applications of Fuzzy Metric Fixed Point Theory
by Dhananjay Gopal Juan Martinez MorenoThis book not only presents essential material to understand fuzzy metric fixed point theory, but also enables the readers to appreciate the recent advancements made in this direction. It contains seven chapters on different topics in fuzzy metric fixed point theory. These chapters cover a good range of interesting topics such as con- vergence problems in fuzzy metrics, fixed figure problems, and applications of fuzzy metrics. The main focus is to unpack a number of diverse aspects of fuzzy metric fixed point theory and its applications in an understandable way so that it could help and motivate young graduates to explore new avenues of research to extend this flourishing area in different directions. The discussion on fixed figure problems and fuzzy contractive fixed point theorems and their different generalizations invites active researchers in this field to develop a new branch of fixed point theory. Features: Explore the latest research and developments in fuzzy metric fixed point theory. Describes applications of fuzzy metrics to colour image processing. Covers new topics on fuzzy fixed figure problems. Filled with examples and open problems. This book serves as a reference book for scientific investigators who want to analyze a simple and direct presentation of the fundamentals of the theory of fuzzy metric fixed point and its applications. It may also be used as a textbook for postgraduate and research students who try to derive future research scope in this area.
Recent Developments in Algebra and Analysis: International Conference on Recent Developments in Mathematics, Dubai, 2022 – Volume 1 (Trends in Mathematics)
by Ho-Hon Leung R. Sivaraj Firuz KamalovThis volume collects the proceedings of the International Conference on Recent Developments in Mathematics (ICRDM), held at Canadian University Dubai, UAE, in August 2022. It is the first of two volumes, this first volume focuses on recent advances in algebra and analysis, and the second volume covers more applied topics. Each chapter identifies existing challenges in these theoretical areas, and highlights the importance of establishing new theorems and algorithms to address them. Recent Developments in Algebra and Analysis will appeal to a range of postgraduate students and researchers who are interested in exploring more on these areas and play an integral role in modern science.
Recent Developments of Fuzzy Matrix Theory and Applications
by Madhumangal PalThis book provides a comprehensive overview of the development of fuzzy matrix theory from its inception to its current state. It covers various types of fuzzy matrices, such as intuitionistic fuzzy matrices, interval-valued fuzzy matrices, interval-valued intuitionistic fuzzy matrices, bipolar fuzzy matrices, picture fuzzy matrices, neutrosophic fuzzy matrices, m-polar fuzzy matrices and similar one. Drawing primarily from the author's research work and collaborations, the book offers a state-of-the-art discussion of these topics. Theoretical concepts are illustrated with examples for clarity, accompanied by figures depicting fuzzy matrices and their variations. Suitable for both beginners and expert researchers, the book offers a wealth of material and includes numerous open problems at the end of almost all chapters to encourage further exploration and investigation.
Recent Trends in AI Enabled Technologies: First International Conference, ThinkAI 2023, Hyderabad, India, December 29, 2023, Revised Selected Papers (Communications in Computer and Information Science #2045)
by Gangamohan Paidi Suryakanth V Gangashetty Ashwini Kumar VarmaThis book constitutes the refereed proceedings of the First International Conference on Recent Trends in AI Enabled Technologies, ThinkAI 2023, which took place in Hyderabad, India, in December 2023. The 7 full papers presented in these proceedings were carefully reviewed and selected from 51 submissions. The conference focuses on on up to date topics and recent trends in artificial intelligence and related technologies.
Recent Trends in Intelligence Enabled Research: Selected Papers of Fifth Doctoral Symposium, DoSIER 2023 (Advances in Intelligent Systems and Computing #1457)
by Siddhartha Bhattacharyya Gautam Das Sourav De Leo MrsicThis book gathers extended versions of papers presented at DoSIER 2023 (Fifth Doctoral Symposium on Intelligence Enabled Research, held at Cooch Behar Government Engineering College, West Bengal, India, during December 20–21, 2023). The papers address the rapidly expanding research area of computational intelligence, which, no longer limited to specific computational fields, has since made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design, to name but a few. Presenting chapters written by experts active in these areas, the book offers a valuable reference guide for researchers and industrial practitioners alike and inspires future studies.
Reconfiguring Relations in the Empty Nest: Those Who Leave and Those Who Stay (Palgrave Macmillan Studies in Family and Intimate Life)
by Magdalena Żadkowska Marta Skowrońska Christophe Giraud Filip SchmidtThis edited volume traverses the spectrum of experiences that take place after children leave the family home and parents find themselves in the "empty nest" stage of life. Rather than focusing on measuring the intensity of empty nest syndrome or asking whether parents' marital satisfaction increases or decreases in this phase, the authors present rich qualitative data from across Poland and France to show that there is great variation in how families experience the empty nest, developing both a study on intimacy and love and on family solidarity. Throughout the book, themes of mixed emotions, nuanced attitudes, contradictions, and dissonance are explored while shedding light on "supporting actors" of the empty nest transition, such as family pets and material objects.
Regression Analysis By Example Using R (Wiley Series in Probability and Statistics)
by Ali S. Hadi Samprit ChatterjeeRegression Analysis By Example Using R A STRAIGHTFORWARD AND CONCISE DISCUSSION OF THE ESSENTIALS OF REGRESSION ANALYSIS In the newly revised sixth edition of Regression Analysis By Example Using R, distinguished statistician Dr Ali S. Hadi delivers an expanded and thoroughly updated discussion of exploratory data analysis using regression analysis in R. The book provides in-depth treatments of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. The author clearly demonstrates effective methods of regression analysis with examples that contain the types of data irregularities commonly encountered in the real world. This newest edition also offers a brand-new, easy to read chapter on the freely available statistical software package R. Readers will also find: Reorganized, expanded, and upgraded exercises at the end of each chapter with an emphasis on data analysis Updated data sets and examples throughout the book Complimentary access to a companion website that provides data sets in xlsx, csv, and txt format Perfect for upper-level undergraduate or beginning graduate students in statistics, mathematics, biostatistics, and computer science programs, Regression Analysis By Example Using R will also benefit readers who need a reference for quick updates on regression methods and applications.
Regression Analysis By Example Using R (Wiley Series in Probability and Statistics)
by Ali S. Hadi Samprit ChatterjeeRegression Analysis By Example Using R A STRAIGHTFORWARD AND CONCISE DISCUSSION OF THE ESSENTIALS OF REGRESSION ANALYSIS In the newly revised sixth edition of Regression Analysis By Example Using R, distinguished statistician Dr Ali S. Hadi delivers an expanded and thoroughly updated discussion of exploratory data analysis using regression analysis in R. The book provides in-depth treatments of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. The author clearly demonstrates effective methods of regression analysis with examples that contain the types of data irregularities commonly encountered in the real world. This newest edition also offers a brand-new, easy to read chapter on the freely available statistical software package R. Readers will also find: Reorganized, expanded, and upgraded exercises at the end of each chapter with an emphasis on data analysis Updated data sets and examples throughout the book Complimentary access to a companion website that provides data sets in xlsx, csv, and txt format Perfect for upper-level undergraduate or beginning graduate students in statistics, mathematics, biostatistics, and computer science programs, Regression Analysis By Example Using R will also benefit readers who need a reference for quick updates on regression methods and applications.
Reinforcement Learning: Aktuelle Ansätze verstehen – mit Beispielen in Java und Greenfoot
by Uwe LorenzIn uralten Spielen wie Schach oder Go können sich die brillantesten Spieler verbessern, indem sie die von einer Maschine produzierten Strategien studieren. Robotische Systeme üben ihre Bewegungen selbst. In Arcade Games erreichen lernfähige Agenten innerhalb weniger Stunden übermenschliches Niveau. Wie funktionieren diese spektakulären Algorithmen des bestärkenden Lernens? Mit gut verständlichen Erklärungen und übersichtlichen Beispielen in Java und Greenfoot können Sie sich die Prinzipien des bestärkenden Lernens aneignen und in eigenen intelligenten Agenten anwenden. Greenfoot (M.Kölling, King’s College London) und das Hamster-Modell (D.Bohles, Universität Oldenburg) sind einfache, aber auch mächtige didaktische Werkzeuge, die entwickelt wurden, um Grundkonzepte der Programmierung zu vermitteln. Wir werden Figuren wie den Java-Hamster zu lernfähigen Agenten machen, die eigenständig ihre Umgebung erkunden. Die zweite Auflage enthält neue Themen wie "Genetische Algorithmen" und "Künstliche Neugier" sowie Korrekturen und Überarbeitungen.
Reliability and Statistics in Transportation and Communication: Selected Papers from the 23rd International Multidisciplinary Conference on Reliability and Statistics in Transportation and Communication: Digital Twins - From Development to Application, RelStat-2023, October 19-21, 2023, Riga, Latvia (Lecture Notes in Networks and Systems #913)
by Igor Kabashkin Irina Yatskiv Olegas PrentkovskisThis book reports on cutting-edge theories and methods for analyzing complex systems, such as transportation and communication networks and discusses multi-disciplinary approaches to dependability problems encountered when dealing with complex systems in practice. The book presents the most relevant findings discussed at the 23rd International Multidisciplinary Conference on Reliability and Statistics in Transportation and Communication (RelStat 2023), which took place as a hybrid event on October 19 – 21, 2023, in/from Riga, Latvia. It spans a broad spectrum of advanced theories and methods, giving a special emphasis to the digitalization of transport systems, as well as smart, artificial intelligence, and digital twins applications.
Reliability Assessment of Tethered High-altitude Unmanned Telecommunication Platforms: k-out-of-n Reliability Models and Applications (Infosys Science Foundation Series)
by Vladimir M. Vishnevsky Dharmaraja Selvamuthu Vladimir Rykov Dmitry V. Kozyrev Nika Ivanova Achyutha KrishnamoorthyThis book provides a systematic presentation of the major results in the field of the theory of k-out-of-n systems obtained in recent years and their applications for the reliability assessment of high-altitude unmanned platforms. Mathematical models, methods, and algorithms, presented in the book, will make a significant contribution to the development of reliability theory and the theoretical foundations of unmanned UAV-based aerial communications networks in the framework of the concept of creating the 5G and beyond networks. The book gives a description of new mathematical methods and approaches (based on decomposable semi-regenerative processes, simulation and machine learning methods, and inventory models) to the study of the complex k-out-of-n systems, which makes it possible to carry out numerical calculations of reliability indicators. Organized into five chapters, each chapter begins with a summary of the main definitions andresults contained in the chapter. The content of this book is based on the original results developed by the authors, many of which appear for the first time in book form.
Reliability Engineering
by Youchao Sun Longbiao Li Dmytro TiniakovThis textbook covers the fundamentals of reliability theory and its application for engineering processes, especially for aircraft units and systems. Reliability basis was explained for the best understanding of reliability analysis application for engineering systems in aviation industry. Several approaches for the reliability analysis and their application with examples are presented. It also introduces main trends in the modern reliability theory development.This book will be interested for university students and early-career engineers of aviation industry majors.
Reliability Engineering: Data analytics, modeling, risk prediction
by Stefan BrackeThis textbook teaches methods of data analytics for technical reliability analyses and risk prognosis on the basis of probabilistics, statistics and modelling. The methods of Reliability Engineering are applied in the elementary phases of the product emergence process (concept and series development, production) as well as during the field use of technical products. This book contains a detailed outline of the basics of statistics, graphical visualisation and calculation methods. Numerous case studies are discussed, representing typical tasks of the engineer in reliability analysis during development/production as well as during the assessment of field damages. The target groups are thus both engineering students and practitioning engineers who deal with technical reliability in the context of the development and manufacturing of complex technical products as well as field data analyses. The presentation of the methods and procedures of Reliability Engineering follows the guideline "theory-guided - practice-oriented", so that this book can be used both as a reference work and as a textbook.
Rescuing Econometrics: From the Probability Approach to Probably Approximately Correct Learning (Routledge INEM Advances in Economic Methodology)
by Duo QinHaavelmo’s 1944 monograph, The Probability Approach in Econometrics, is widely acclaimed as the manifesto of econometrics. This book challenges Haavelmo’s probability approach, shows how its use is delivering defective and inefficient results, and argues for a paradigm shift in econometrics towards a full embrace of machine learning, with its attendant benefits. Machine learning has only come into existence over recent decades, whereas the universally accepted and current form of econometrics has developed over the past century. A comparison between the two is, however, striking. The practical achievements of machine learning significantly outshine those of econometrics, confirming the presence of widespread inefficiencies in current econometric research. The relative efficiency of machine learning is based on its theoretical foundation, and particularly on the notion of Probably Approximately Correct (PAC) learning. Careful examination reveals that PAC learning theory delivers the goals of applied economic modelling research far better than Haavelmo’s probability approach. Econometrics should therefore renounce its outdated foundation, and rebuild itself upon PAC learning theory so as to unleash its pent-up research potential. The book is catered for applied economists, econometricians, economists specialising in the history and methodology of economics, advanced students, philosophers of social sciences.
Rescuing Econometrics: From the Probability Approach to Probably Approximately Correct Learning (Routledge INEM Advances in Economic Methodology)
by Duo QinHaavelmo’s 1944 monograph, The Probability Approach in Econometrics, is widely acclaimed as the manifesto of econometrics. This book challenges Haavelmo’s probability approach, shows how its use is delivering defective and inefficient results, and argues for a paradigm shift in econometrics towards a full embrace of machine learning, with its attendant benefits. Machine learning has only come into existence over recent decades, whereas the universally accepted and current form of econometrics has developed over the past century. A comparison between the two is, however, striking. The practical achievements of machine learning significantly outshine those of econometrics, confirming the presence of widespread inefficiencies in current econometric research. The relative efficiency of machine learning is based on its theoretical foundation, and particularly on the notion of Probably Approximately Correct (PAC) learning. Careful examination reveals that PAC learning theory delivers the goals of applied economic modelling research far better than Haavelmo’s probability approach. Econometrics should therefore renounce its outdated foundation, and rebuild itself upon PAC learning theory so as to unleash its pent-up research potential. The book is catered for applied economists, econometricians, economists specialising in the history and methodology of economics, advanced students, philosophers of social sciences.
Research Challenges in Information Science: 18th International Conference, RCIS 2024, Guimarães, Portugal, May 14–17, 2024, Proceedings, Part I (Lecture Notes in Business Information Processing #513)
by João Araújo Jose Luis de la Vara Maribel Yasmina Santos Saïd AssarThis book constitutes the proceedings of the 18th International Conference on Research Challenges in Information Sciences, RCIS 2024, which took place in Guimarães, Portugal, during May 2024. The scope of RCIS is summarized by the thematic areas of information systems and their engineering; user-oriented approaches; data and information management; business process management; domain-specific information systems engineering; data science; information infrastructures, and reflective research and practice. The 25 full papers, 12 Forum and 5 Doctoral Consortium papers included in these proceedings were carefully reviewed and selected from 100 submissions. They were organized in topical sections as follows: Part I: Data and information management; conceptual modelling and ontologies; requirements and architecture; business process management; data and process science; security; sustainability; evaluation and experience studies Part II: Forum papers; doctoral consortium papers.
Research Challenges in Information Science: 18th International Conference, RCIS 2024, Guimarães, Portugal, May 14–17, 2024, Proceedings, Part II (Lecture Notes in Business Information Processing #514)
by João Araújo Jose Luis de la Vara Maribel Yasmina Santos Saïd AssarThis book constitutes the proceedings of the 18th International Conference on Research Challenges in Information Sciences, RCIS 2024, which took place in Guimarães, Portugal, during May 2024. The scope of RCIS is summarized by the thematic areas of information systems and their engineering; user-oriented approaches; data and information management; business process management; domain-specific information systems engineering; data science; information infrastructures, and reflective research and practice. The 25 full papers, 12 Forum and 5 Doctoral Consortium papers included in these proceedings were carefully reviewed and selected from 100 submissions. They were organized in topical sections as follows: Part I: Data and information management; conceptual modelling and ontologies; requirements and architecture; business process management; data and process science; security; sustainability; evaluation and experience studies Part II: Forum papers; doctoral consortium papers.
Research in History and Philosophy of Mathematics: The CSHPM 2022 Volume (Annals of the Canadian Society for History and Philosophy of Mathematics/ Société canadienne d’histoire et de philosophie des mathématiques)
by Maria Zack David WaszekThis volume contains 8 papers that have been collected by the Canadian Society for History and Philosophy of Mathematics. It showcases rigorously reviewed contemporary scholarship on an interesting variety of topics in the history and philosophy of mathematics.Some of the topics explored include:A way to rethink how logic is taught to philosophy students by using a rejuvenated version of the Aristotelian idea of an argument schemaA quantitative approach using data from Wikipedia to study collaboration between nineteenth-century British mathematiciansThe depiction and perception of Émilie Du Châtelet’s scientific contributions as viewed through the frontispieces designed for books written by or connected to herA study of the Cambridge Women’s Research Club, a place where British women were able to participate in scholarly scientific discourse in the middle of the twentieth centuryAn examination of the research and writing process of mathematicians by looking at their drafts and other preparatory notesA global history of al-Khwārāzmī’s Kitāb al-jabr wa-l-muqābala as obtained by tracing its reception through numerous translations and commentariesWritten by leading scholars in the field, these papers are accessible not only to mathematicians and students of the history and philosophy of mathematics, but also to anyone with a general interest in mathematics.
Research Methods and Statistics in Psychology
by Hugh CoolicanResearch Methods and Statistics in Psychology provides students with the most readable and comprehensive survey of research methods, statistical concepts and procedures in psychology today. Assuming no prior knowledge, this bestselling text takes you through every stage of your research project, giving advice on planning and conducting studies, analysing data and writing up reports, both quantitative and qualitative. It incorporates diversity and includes a large section on cross-cultural psychology methods and issues. The book continues its long tradition of integrating qualitative issues into methods chapters as well as providing two chapters dedicated to qualitative methods. It provides clear coverage of experimental, interviewing and observational methods; psychological testing; and statistical procedures which include nominal-level tests, ordinal and interval two-condition tests, simple and multi-factorial ANOVA designs, correlation, multiple regression, log linear analysis, factor analysis and, new with this edition, logistic regression. It features detailed and illustrated SPSS instructions for all these and other procedures, eliminating the need for an extra SPSS textbook. New edition features include: • Logistic regression. • Greater detail of online research methods. • Expanded coverage of report writing guidelines. • Concepts illustrated with up-to-date published research examples. • Instructor and Student Resource website signposted throughout the book to improve student usability. Each chapter contains a glossary, key terms and newly integrated exercises, ensuring that key concepts are understood. This book is extended and enhanced by a fully updated and refreshed Instructor and Student Resource website, which includes: • A collection of interactive multiple-choice questions with detailed feedback, providing the opportunity to test understanding at different levels. • Practical exercises that give students the opportunity to put their learning into practice. • Links to further reading and sources to expand knowledge. • Test banks for each chapter to save instructors time. Access the website at: www.routledge.com/cw/coolican.
Research Methods and Statistics in Psychology
by Hugh CoolicanResearch Methods and Statistics in Psychology provides students with the most readable and comprehensive survey of research methods, statistical concepts and procedures in psychology today. Assuming no prior knowledge, this bestselling text takes you through every stage of your research project, giving advice on planning and conducting studies, analysing data and writing up reports, both quantitative and qualitative. It incorporates diversity and includes a large section on cross-cultural psychology methods and issues. The book continues its long tradition of integrating qualitative issues into methods chapters as well as providing two chapters dedicated to qualitative methods. It provides clear coverage of experimental, interviewing and observational methods; psychological testing; and statistical procedures which include nominal-level tests, ordinal and interval two-condition tests, simple and multi-factorial ANOVA designs, correlation, multiple regression, log linear analysis, factor analysis and, new with this edition, logistic regression. It features detailed and illustrated SPSS instructions for all these and other procedures, eliminating the need for an extra SPSS textbook. New edition features include: • Logistic regression. • Greater detail of online research methods. • Expanded coverage of report writing guidelines. • Concepts illustrated with up-to-date published research examples. • Instructor and Student Resource website signposted throughout the book to improve student usability. Each chapter contains a glossary, key terms and newly integrated exercises, ensuring that key concepts are understood. This book is extended and enhanced by a fully updated and refreshed Instructor and Student Resource website, which includes: • A collection of interactive multiple-choice questions with detailed feedback, providing the opportunity to test understanding at different levels. • Practical exercises that give students the opportunity to put their learning into practice. • Links to further reading and sources to expand knowledge. • Test banks for each chapter to save instructors time. Access the website at: www.routledge.com/cw/coolican.
Research Software Engineering: A Guide to the Open Source Ecosystem (Chapman & Hall/CRC Data Science Series)
by Matthias BannertResearch Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.Key Features overview: breakdown of complex data science software stacks into core components applied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source software reader guidance: different entry points and rich references to deepen the understanding of selected aspects
Research Software Engineering: A Guide to the Open Source Ecosystem (Chapman & Hall/CRC Data Science Series)
by Matthias BannertResearch Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.Key Features overview: breakdown of complex data science software stacks into core components applied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source software reader guidance: different entry points and rich references to deepen the understanding of selected aspects
Researching Mathematical Modelling Education in Disruptive Times (International Perspectives on the Teaching and Learning of Mathematical Modelling)
by Gabriele Kaiser Hans-Stefan Siller Vince GeigerThis edited volume documents research on mathematical modelling education, before, during, and after the Covid 19 pandemic. Mathematical modelling is essential for understanding natural and human generated phenomena, and informs decision-making about events such as the pandemic, climate change, and other disruptive events. Communication to the public, often by the media, makes use of mathematical modelling to justify changes to public policy, as seen during the COVID-19 crisis. Consequently, mathematical modelling has assumed an increasingly prominent role in curricula internationally, providing opportunities to understand how it is used in current circumstances and to plan for the needs of future societies. This book focuses on research on mathematical modelling education and its implementation at school and tertiary level. Contributions to the book and point to directions for further innovation in mathematical modelling education. Authors of this volume are members of the International Community of Teachers of Mathematical Modelling, the peak research body for the teaching and learning of mathematical modelling.
Reshaping Power Dynamics Between Sustainable Growth and Technical Disruption: 6th International Conference on Economics and Social Sciences, ICESS 2023, Bucharest, Romania (Springer Proceedings in Business and Economics)
by Alina Mihaela Dima Sorin VâlceaThis book covers various topics related to economics and the social sciences, such as artificial intelligence, sustainability, ESG, and tax administration. The respective contributions provide insights and perspectives on the current challenges and opportunities in these fields, while also showcasing the latest research and innovations from scholars and practitioners around the world. The book is based on the papers presented at the 6th International Conference on Economics and Social Sciences, ICESS 2023, which was held in Bucharest, Romania.