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Presents interplays between numerical approximation and statistical inference as a pathway to simple solutions to fundamental problems.
Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.
A better understanding of the mechanisms leading a fluid system to exhibit turbulent behavior is one of the grand challenges of the physical and mathematical sciences. Over the last few decades, numerical bifurcation methods have been extended and applied to a number of flow problems to identify critical conditions for fluid instabilities to occur. This book provides a state-of-the-art account of these numerical methods, with much attention to modern linear systems solvers and generalized eigenvalue solvers. These methods also have a broad applicability in industrial, environmental and astrophysical flows. The book is a must-have reference for anyone working in scientific fields where fluid flow instabilities play a role. Exercises at the end of each chapter and Python code for the bifurcation analysis of canonical fluid flow problems provide practice material to get to grips with the methods and concepts presented in the book.
The world faces significant challenges as the population and consumption continue to grow while fossil fuels and other raw materials are depleted at everincreasing rates. Environmental consciousness and a penchant for thinking about material cycles have caught on with consumers. Therefore, the use of environmentally compatible materials and sustainable production methods are now desired. Materials and Technologies for a Green Environment discusses the major issues surrounding the production of energy through biofuels and waste management. It comprises seven chapters that cover various fields of interest to readers involved in environmental management and sustainability planning. The topics covered include renewable energy sources, thermoelectric generators, electric vehicles, biodiesel production from poultry waste, scramjet combustion engines, and sustainable architecture for green buildings. Given its scope, this book is a valuable resource for students, researchers and engineers in environmental science, mechanical engineering, and chemical engineering and sustainability studies
The book provides a pedagogic and comprehensive introduction to homogenization theory with a special focus on problems set for non-periodic media. The presentation encompasses both deterministic and probabilistic settings. It also mixes the most abstract aspects with some more practical aspects regarding the numerical approaches necessary to simulate such multiscale problems. Based on lecture courses of the authors, the book is suitable for graduate students of mathematics and engineering.
This advanced monograph is concerned with modern treatments of central problems in harmonic analysis. The main theme of the book is the interplay between ideas used to study the propagation of singularities for the wave equation and their counterparts in classical analysis. In particular, the author uses microlocal analysis to study problems involving maximal functions and Riesz means using the so-called half-wave operator. To keep the treatment self-contained, the author begins with a rapid review of Fourier analysis and also develops the necessary tools from microlocal analysis. This second edition includes two new chapters. The first presents Hörmander's propagation of singularities theorem and uses this to prove the Duistermaat-Guillemin theorem. The second concerns newer results related to the Kakeya conjecture, including the maximal Kakeya estimates obtained by Bourgain and Wolff.
The 47 full papers and 24 short papers included in this book were carefully reviewed and selected from 245 submissions. These articles cater to the most contemporary and happening topics in the fields of AI that range from Intelligent Recommendation Systems, Game Theory, Computer Vision, Reinforcement Learning, Social Networks, and Generative AI to Conversational and Large Language Models. They are organized into four areas of research: Theoretical contributions, Cognitive Computing models, Computational Intelligence based algorithms, and AI Applications.