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Elsevier

Books in Physical sciences and engineering

  • Quantum Theory, Decision Making and Social Dynamics

    • 1st Edition
    • Tofigh Allahviranloo + 3 more
    • English
    Quantum Theory, Decision Making, and Social Dynamics is a detailed exploration of the connection between quantum theory, decision-making, and social networks. As quantum theory expands into various fields, there is an increasing demand for accessible resources that clarify its principles and uses. This book aims to address that need by explaining the complex relationship between quantum theory and social dynamics, especially in decision-making contexts. It discusses the challenges of understanding and applying quantum theory in social settings and provides readers with the knowledge to leverage its potential in decision-making processes. The book is divided into eleven chapters, each focusing on a specific aspect of quantum theory and its applications. Chapter 1 introduces quantum theory, fuzzy logic, and social network analysis, highlighting key concepts like superposition, entanglement, and fuzzy influence within networks. Chapter 2 examines fuzzy sets, membership functions, and inference systems, with applications in devices, traffic management, and healthcare. Chapter 3 covers the mathematical framework of quantum mechanics and its philosophical paradoxes, connecting them to fuzzy logic models of uncertainty. Chapter 4 links social networks to quantum graphs, defining their topology, centrality, and entangled edges. Chapter 5 models social identity as a fuzzy quantum superposition, exploring identity collapse and coherence within networks. Chapter 6 relates quantum entanglement to social ties, proposing fuzzy–quantum graph models for interconnected systems. Chapter 7 analyses measures of irregularity in quantum graphs and applies these to financial networks. Chapter 8 integrates quantum cognition with fuzzy MCDM, employing various probability evaluation methods. Chapter 9 features case studies of fuzzy systems and their integration with quantum fuzzy graphs. Chapter 10 develops a quantum graph-based link prediction model for dynamic social networks. Chapter 11 concludes with a summary of the quantum–fuzzy framework, discussing its contributions, limitations, and future directions.

  • Boundary Value Problems and Partial Differential Equations

    • 7th Edition
    • David L. Powers + 3 more
    • English
    For over fifty years, Boundary Value Problems and Partial Differential Equations, Seventh Edition has provided advanced students an accessible and practical introduction to deriving, solving, and interpreting explicit solutions involving partial differential equations with boundary and initial conditions. Fully revised and now in its Seventh Edition, this valued text aims to be comprehensive without affecting the accessibility and convenience of the original. The resource’s main tool is Fourier analysis, but the work covers other techniques, including Laplace transform, Fourier transform, numerical methods, characteristics, and separation of variables, as well, to provide well-rounded coverage. Mathematical modeling techniques are illustrated in derivations, which are widely used in engineering and science. In particular, this includes the modeling of heat distribution, a vibrating string or beam under various boundary conditions and constraints. New to this edition, the text also now uniquely discusses the beam equation. Throughout the text, examples and exercises have been included, pulled from the literature based on popular problems from engineering and science. These include some "outside-the-box" exercises at the end of each chapter, which provide challenging and thought-provoking practice that can also be used to promote classroom discussion. Chapters also include Projects, problems that synthesize or dig more deeply into the material that are slightly more involved than standard book exercises, and which are intended to support team solutions. Additional materials, exercises, animations, and more are also accessible to students via links and in-text QR codes to support practice and subject mastery.

  • Bacterial Biogeochemistry

    The Ecophysiology of Mineral Cycling
    • 4th Edition
    • Gary M. King + 1 more
    • English
    Bacterial Biogeochemistry: The Ecophysiology of Mineral Cycling, Fourth Edition discusses the influence of bacterial activity on the chemical environment of the biosphere. Following the success of previous editions, this update focuses on bacterial metabolism and its relevance to the environment, including the decomposition of soil, food chains, nitrogen fixation, assimilation, and reduction of carbon nitrogen and sulfur, and microbial symbiosis. All chapters have been revised and brought up-to-date in light of the many advances and discoveries that have taken place during the last decade. The scope of the new edition has broadened to provide a review of the processes and phenomena that are relevant for global change feedback loops and advances in bacterial biogeochemical cycles.

  • Measure and Integration

    Concepts, Examples, and Applications
    • 1st Edition
    • Ahmed Ghatasheh + 2 more
    • English
    Measure and Integration: Examples, Concepts, and Applications instructs on core proofs, theorems, and approaches of real analysis as illustrated via compelling exercises and carefully crafted, practical examples. Following early chapters on core concepts and approaches of real analysis, the authors apply real analysis across integration on product spaces, radon functionals, bounded variation and lebesgue-stieltjes measures, convolutions, probability, and differential equations, among other topics. From chapter one onward, students are asked to apply concepts to reinforce understanding and gain applied experience in real analysis. In particular, exercises challenge students to use key proofs of major real analysis theorems to encourage independent thinking, problem-solving, and new areas of research powered by real analysis.

  • Learning-Driven Game Theory for AI

    Concepts, Models, and Applications
    • 1st Edition
    • Mehdi Salimi + 1 more
    • English
    Learning-Driven Game Theory for AI: Concepts, Models, and Applications offers in-depth coverage of recent methodological and conceptual advancements in various disciplines of Dynamic Games, namely differential and discrete-time dynamic games, evolutionary games, repeated and stochastic games, and their applications in a variety of fields, such as computer science, biology, economics, and management science. In this book, the authors bridge the gap between traditional game theory and its modern applications in artificial intelligence (AI) and related technological fields. The dynamic nature of contemporary problems in robotics, cybersecurity, machine learning, and multi-agent systems requires game-theoretic solutions that go beyond classical methods. The book delves into the rapidly growing intersection of pursuit differential games and AI, focusing on how these advanced game-theoretic models can be applied to modern AI systems, making it an indispensable resource for both academics and professionals. The book also provides a variety of applications demonstrating the practical integration of AI and game theory across various disciplines, such as autonomous systems, federated learning, and distributed decision-making frameworks. The book also explores the use of game theory in reinforcement learning, swarm intelligence, multi-agent coordination, and cybersecurity. These are critical areas where AI and dynamic games converge. Each chapter covers a different facet of dynamic games, offering readers a comprehensive yet focused exploration of topics such as differential and discrete-time games, evolutionary dynamics, and repeated and stochastic games. The absence of static games ensures a concentrated focus on the dynamic, evolving problems that are most relevant today.

  • Essentials of Big Data Analytics

    Applications in R and Python
    • 1st Edition
    • Pallavi Chavan + 2 more
    • English
    Essentials of Big Data Analytics: Applications in R and Python is a comprehensive guide that demystifies the complex world of big data analytics, blending theoretical concepts with hands-on practices using the Python and R programming languages and MapReduce framework. This book bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of big data. Essentials of Big Data Analytics is designed to provide a comprehensive resource for readers looking to deepen their understanding of Big Data analytics, particularly within a computer science, engineering, and data science context. By bridging theoretical concepts with practical applications, the book emphasizes hands-on learning through exercises and tutorials, specifically utilizing R and Python. Given the growing role of Big Data in industry and scientific research, this book serves as a timely resource to equip professionals with the skills needed to thrive in data-driven environments.

  • Air Pollution

    • 1st Edition
    • Volume 14
    • English
    This book offers a comprehensive overview of air pollution, exploring its sources, impacts, and the latest strategies for monitoring, control, and mitigation. Covering key topics such as atmospheric pollutants, health and environmental effects, regulatory frameworks, and innovative technologies, the book provides valuable insights for researchers, policymakers, and students interested in understanding and addressing the challenges of air quality management.

  • Engineering Generative AI-Based Software

    • 1st Edition
    • Miroslaw Staroń
    • English
    Engineering Generative-AI Based Software discusses both the process of developing this kind of AI-based software and its architectures, combining theory with practice. Sections review the most relevant models and technologies, detail software engineering practices for such systems, e.g., eliciting functional and non-functional requirements specific to generative AI, explore various architectural styles and tactics for such systems, including different programming platforms, and show how to create robust licensing models. Finally, readers learn how to manage data, both during training and when generating new data, and how to use generated data and user feedback to constantly evolve generative AI-based software.As generative AI software is gaining popularity thanks to such models as GPT-4 or Llama, this is a welcomed resource on the topics explored. With these systems becoming increasingly important, Software Engineering Professionals will need to know how to overcome challenges in incorporating GAI into the products and programs they develop.

  • Phosphonate Chemistry, Technology and Applications

    Industrial, Environmental, and Energy Applications
    • 1st Edition
    • Konstantinos D. Demadis
    • English
    Phosphonate Chemistry, Technology and Applications: Industrial, Environmental, and Energy Applications presents a comprehensive and interdisciplinary overview of phosphonate compounds, covering synthetic methods, metal phosphonate hybrid materials, and their diverse applications. Key topics include scale and corrosion inhibition, catalytic properties, magnetic and optical functionalities, biomedical uses, and advanced applications in energy, gas capture, imaging, electrocatalysis, and environmental remediation. The book consolidates the latest research from the past decade, offering a systematic, concise, and user-friendly reference that bridges organic, inorganic, and materials chemistry.This is an essential resource for researchers, professionals, and advanced students working across chemistry, materials science, environmental science, and chemical engineering. Its broad scope and practical focus make it the definitive guide for anyone involved in phosphonate-related research or industrial applications.

  • Development in Wastewater Treatment Research and Processes: Microbiome in Ecosystem

    A Sustainable Approach for Wastewater Treatment
    • 1st Edition
    • Maulin P. Shah + 1 more
    • English
    Microbiome in Ecosystem: A Sustainable Approach for Wastewater Treatment: Developments in Wastewater Treatment Research and Processes delves deeply into the pioneering use of microbiome for the sustainable treatment of waste water. The book examines the biochemical, physicochemical, and molecular pathways of microbes involved in waste water treatment processes, elucidating their indispensable contributions to environmental preservation and sustainable development. From the exploration of microbiome-generated nanoparticles to the discourse on bioengineering methodologies and the synthesis of bioactive metabolites and enzymes, the book provides a thorough analysis of state-of-the-art techniques and advancements in the field. The book reveals invaluable insights into the microbiome of diverse ecosystems, including their multifaceted functions, interactions, and the underlying molecular, genetic, and biochemical processes relevant to waste water treatment. Emphasizing global challenges and offering forward-looking perspectives, the book serves as an essential reference for students, researchers, scientists, and professionals across various disciplines such as biotechnology, microbiology, environmental science, and waste treatment engineering.

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