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Elsevier

Books in Computer science

The Computing collection presents a range of foundational and applied content across computer and data science, including fields such as Artificial Intelligence; Computational Modelling; Computer Networks, Computer Organization & Architecture, Computer Vision & Pattern Recognition, Data Management; Embedded Systems & Computer Engineering; HCI/User Interface Design; Information Security; Machine Learning; Network Security; Software Engineering.

  • Metaheuristic Optimization Algorithms

    Optimizers, Analysis, and Applications
    • 1st Edition
    • Laith Abualigah
    • English
    Metaheuristic Optimization Algorithms: Optimizers, Analysis, and Applications presents the most recent optimization algorithms and their applications across a wide range of scientific and engineering research fields. The book provides readers with a comprehensive overview of eighteen optimization algorithms to address this complex data, including Particle Swarm Optimization Algorithm, Arithmetic Optimization Algorithm, Whale Optimization Algorithm, and Marine Predators Algorithm, along with new and emerging methods such as Aquila Optimizer, Quantum Approximate Optimization Algorithm, Manta-Ray Foraging Optimization Algorithm, and Gradient Based Optimizer, among others. Each chapter includes an introduction to the modeling concepts used to create the algorithm that is followed by the mathematical and procedural structure of the algorithm, associated pseudocode, and real-world case studies.

  • Performance Enhancement and Control of Photovoltaic Systems

    • 1st Edition
    • Saad Motahhir + 1 more
    • English
    Performance Enhancement and Control of Photovoltaic Systems brings together the latest advances in photovoltaic control and integration, with various embedded technologies applied to standalone and grid connected systems in normal and abnormal operating conditions, with new approaches intended to overcome a number of critical limitations in using PV technology. The book begins by introducing modern photovoltaic (PV) systems, system integration, materials, and thermodynamic analysis for improved performance, before examining applications in industrial processes, artificial neural network technology, and economic analysis of PV systems.In-depth chapters then demonstrate the use of advanced control and optimization techniques, covering the use of new embedded technologies, through different applications such as MPPT controllers, solar trackers, cleaning systems, cooling systems, and monitoring systems. Applications of photovoltaic energy systems in distributed generation, microgrid, and smart grid systems will be considered.

  • Foundations of Quantum Programming

    • 2nd Edition
    • Mingsheng Ying
    • English
    Foundations of Quantum Programming, Second Edition provides a systematic exposition of the subject of quantum programming. Emphasis is placed on foundational concepts, methods, and techniques that can be widely used for various quantum programming models and languages. The book describes how programming methodologies developed for current computers can be extended for quantum computers, along with new programming methodologies that can effectively exploit the unique power of quantum computing. In addition, this resource introduces a chain of quantum programming models from sequential to parallel and distributed programming in the paradigm of superposition-of-dat... to the paradigm of superposition-of-pro... content presents a series of logical and mathematical tools for verification and analysis of quantum programs, including invariant generation, termination analysis, and abstract interpretation.

  • Artificial Intelligence and Machine Learning for Women’s Health Issues

    • 1st Edition
    • Meenu Gupta + 1 more
    • English
    Artificial Intelligence and Machine Learning for Women’s Health Issues discusses the applications, challenges, and solutions that machine learning can bring to women’s health challenges. The book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning which enhance the future healthcare system. This book's primary focus is on women’s health issues and machine learning's role in providing solutions to these challenges, providing novel ideas for feasible implementation. It also provides an early-stage analysis for early diagnosis of women’s health issues.

  • Theory of Structured Parallel Programming

    • 1st Edition
    • Yong Wang
    • English
    Theory of Structured Parallel Programming is a comprehensive guide to structured parallel programming corresponding to traditional structured sequential programming. The book provides readers with comprehensive coverage of theoretical foundations of structured parallel programming, including analyses of parallelism and concurrency, truly concurrent process algebras, building block-based structured parallel programming, modelling and verification of parallel programming language, modelling and verification of parallel programming patterns, as well as modeling and verification of distributed systems.There have been always two ways to approach parallel computing: one is the structured way, and the other is the graph-based (true concurrent) way. The structured way is often based on the interleaving semantics, such as process algebra CCS. Since the parallelism in interleaving semantics is not a fundamental computational pattern (the parallel operator can be replaced by alternative composition and sequential composition), the parallel operator often does not occur as an explicit operator, such as in the mainstream programming languages C, C++, Java, et al.

  • Intelligent Evolutionary Optimization

    • 1st Edition
    • Hua Xu + 1 more
    • English
    Intelligent Evolutionary Optimization introduces biologically-inspire... intelligent optimization algorithms to address complex optimization problems and provide practical solutions for tackling combinatorial optimization problems. The book explores efficient search and optimization methods in high-dimensional spaces, particularly for high-dimensional multi-objective optimization problems, offering practical guidance and effective solutions across various domains. Providing practical solutions, methods, and tools to tackle complex optimization problems and enhance modern optimization techniques, this book will be a valuable resource for professionals seeking to enhance their understanding and proficiency in intelligent evolutionary optimization.

  • Bio-Inspired Strategies for Modeling and Detection in Diabetes Mellitus Treatment

    • 1st Edition
    • Alma Y Alanis + 3 more
    • English
    Bio-Inspired Strategies for Modeling and Detection in Diabetes Mellitus Treatment focuses on bioinspired techniques such as modeling to generate control algorithms for the treatment of diabetes mellitus. The book addresses the identification of diabetes mellitus using a high-order recurrent neural network trained by an extended Kalman filter. The authors also describe the use of metaheuristic algorithms for the parametric identification of compartmental models of diabetes mellitus widely used in research works such as the Sorensen model and the Dallaman model. In addition, the book addresses the modeling of time series for the prediction of risk scenarios such as hyperglycaemia and hypoglycaemia using deep neural networks. The detection of diabetes mellitus in the early stages or when current diagnostic techniques cannot detect glucose intolerance or prediabetes is proposed, carried out by means of deep neural networks present in the literature. Readers will find leading-edge research in diabetes identification based on discrete high-order neural networks trained with an extended Kalman filter; parametric identification of compartmental models used to describe diabetes mellitus; modeling of data obtained by continuous glucose-monitoring sensors for the prediction of risk scenarios such as hyperglycaemia and hypoglycaemia; and screening for glucose intolerance using glucose-tolerance test data and deep neural networks. Application of the proposed approaches is illustrated via simulation and real-time implementations for modeling, prediction, and classification.

  • Ethics in Online AI-Based Systems

    Risks and Opportunities in Current Technological Trends
    • 1st Edition
    • Santi Caballé + 2 more
    • English
    Ethics in Online AI-Based Systems: Risks and Opportunities in Current Technological Trends creates a space to explore the ethical relevance that new technologies under development may have. Stimulating reflection and considerations with respect to the design, deployment, and use of technology helps readers guide current and future technological advancements from an ethically informed position to ensure that such advancements contribute towards solving current global and social challenges that we, as a society, have today. This will not only be useful for researchers and professional engineers, but also for educators, policy makers, and ethicists.Recent technological advancements have deeply transformed society and the way people interact with each other. Instantaneous communication platforms have allowed connections with other people, forming global communities and creating unprecedented opportunities in many sectors, making access to online resources more ubiquitous by reducing limitations imposed by geographical distance and temporal constrains. These technological developments bear ethically relevant consequences with their deployment, and legislations often lag behind such advancements. Because the appearance and deployment of these technologies happen much faster than legislative procedures, the way these technologies affect social interactions have profound ethical effects before any legislative regulation can be built in order to prevent and mitigate those effects.

  • Current Molecular Targets of Heterocyclic Compounds for Cancer Therapy

    • 1st Edition
    • Vivek Asati + 1 more
    • English
    Current Molecular Targets of Heterocyclic Compounds for Cancer Therapy discusses recently developed treatments based on molecular targets which are genetically altered in cancer cells and are essential for tumor development and survival. Considerable research effort has been devoted to the development of targeted drugs that inhibit the action of pathogenic kinases, and clinical studies performed so far have validated the positive effects of kinase inhibitors for cancer treatment. Each chapter discusses a molecular target, such as ALK2, ATR, CK, Src-Abl, EGFR, Fyn-Blk-Lyn, IGFs, and PAK1.The book's chapters are written by experts who actively work on the targets to help readers fully understand how they can be used. This is a valuable resource for cancer researchers, oncologists, graduate students and members of the biomedical field who are interested in the potential of novel cancer therapies based on molecular targets.

  • Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment

    • 1st Edition
    • Zhijun Chen
    • English
    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.

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