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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.

  • The Essential Criteria of Graph Databases

    • 1st Edition
    • Ricky Sun
    • English
    The Essential Criteria of Graph Databases collects several truly innovative graph applications in asset-liability and liquidity risk management to spark readers’ interest and further broaden the reach and applicable domains of graph systems. Although AI has incredible potential, it has three weak links: 1. Blackbox, lack of explainability, 2. Silos, slews of siloed systems across the AI ecosystem, 3. Low-performance, as most of ML/DL based AI systems are SLOW. Hence, fixing these problems paves the road to strong and effective AI.

  • Human-Computer Interaction

    An Empirical Research Perspective
    • 2nd Edition
    • I. Scott MacKenzie
    • English
    Human-Computer Interaction: An Empirical Research Perspective is the definitive guide to empirical research in HCI. The book begins with foundational topics, including historical context, the human factor, interaction elements, and the fundamentals of science and research. From there, the book progresses to the methods for conducting an experiment to evaluate a new computer interface or interaction technique. There are detailed discussions and how-to analyses on models of interaction, focusing on descriptive models and predictive models. Writing and publishing a research paper is explored with helpful tips for success.Throughout the book, readers will find hands-on exercises, checklists, and real-world examples. This is a must-have, comprehensive guide to empirical and experimental research in HCI – an essential addition to your HCI library.

  • Fractional Difference, Differential Equations, and Inclusions

    Analysis and Stability
    • 1st Edition
    • Saïd Abbas + 3 more
    • English
    Fractional Difference, Differential Equations, and Inclusions: Analysis and Stability is devoted to the existence and stability (Ulam-Hyers-Rassias stability and asymptotic stability) of solutions for several classes of functional fractional difference equations and inclusions. Covered equations include delay effects of finite, infinite, or state-dependent nature, and tools used to establish the existence results for the proposed problems include fixed point theorems, densifiability techniques, monotone iterative technique, notions of Ulam stability, attractivity and the measure of non-compactness, as well as the measure of weak noncompactness. The tools of fractional calculus are found to be of great utility in improving the mathematical modeling of many natural phenomena and processes occurring in the areas of engineering, social, natural, and biomedical sciences. All abstract results in the book are illustrated by examples in applied mathematics, engineering, biomedical, and other applied sciences.

  • Synthetic Data and Generative AI

    • 1st Edition
    • Vincent Granville
    • English
    Synthetic Data and Generative AI covers the foundations of machine learning with modern approaches to solving complex problems and the systematic generation and use of synthetic data. Emphasis is on scalability, automation, testing, optimizing, and interpretability (explainable AI). For instance, regression techniques – including logistic and Lasso – are presented as a single method without using advanced linear algebra. Confidence regions and prediction intervals are built using parametric bootstrap without statistical models or probability distributions. Models (including generative models and mixtures) are mostly used to create rich synthetic data to test and benchmark various methods.

  • Connectomic Medicine

    Guide to Brain AI in Treatment Decision Planning
    • 1st Edition
    • Michael E. Sughrue + 2 more
    • English
    Connectomic Medicine: A Guide to Brain AI in Treatment Decision Planning examines how to apply connectomics to clinical medicine, including discussions on techniques, applications, novel ideas, and in case examples that highlight the state-of-the-art. Written by pioneers, this volume serves as the foundation for all neuroscience clinicians/researche... venturing into the field of AI medicine, its realistic applications, and how to integrate AI connectomics into clinical practice. With widespread applications in neurology, neurosurgery and psychiatry, this book is appropriate for anyone interested in cerebral network anatomy, imaging techniques, and insights into this emerging field.

  • Handbook of Truly Concurrent Process Algebra

    • 1st Edition
    • Yong Wang
    • English
    Handbook of Truly Concurrent Process Algebra provides readers with a detailed and in-depth explanation of the algebra used for concurrent computing. This complete handbook is divided into five Parts: Algebraic Theory for Reversible Computing, Probabilistic Process Algebra for True Concurrency, Actors – A Process Algebra-Based Approach, Secure Process Algebra, and Verification of Patterns. The author demonstrates actor models which are captured using the following characteristics: Concurrency, Asynchrony, Uniqueness, Concentration, Communication Dependency, Abstraction, and Persistence. Every pattern is detailed according to a regular format to be understood and utilized easily, which includes introduction to a pattern and its verifications.Patter... of the vertical domains are also provided, including the domains of networked objects and resource management. To help readers develop and implement the software patterns scientifically, the pattern languages are also presented.

  • Practical Design and Applications of Medical Devices

    • 1st Edition
    • Dilber Uzun Ozsahin + 1 more
    • English
    Practical Design and Applications of Medical Devices focuses on devices which receive and transmit bioelectric signals, such as electrocardiograph, electrodes, blood flow, blood pressure, physiological effects and, in some cases, current flowing through the human body. This thorough guide for researchers and engineers in the field of biomedical and instrumentation engineering presents a streamlined medical strategy for designing these medical devices, sensors, and tools. It also promotes operational efficiency in the healthcare industry, with the goals of improving patient safety, lowering overall healthcare costs, broadening access to healthcare services, and improving accessibility.

  • Metaheuristics Algorithms for Medical Applications

    Methods and Applications
    • 1st Edition
    • Mohamed Abdel-Basset + 2 more
    • English
    Metaheuristics Algorithms for Medical Applications: Methods and Applications provides readers with the most complete reference for developing metaheuristics techniques with machine learning for solving biomedical problems. This book is organized to present a stepwise progression beginning with the basics of metaheuristics, leading into methods and practices, and concluding with advanced topics. The first section of this book presents the fundamental concepts of metaheuristics and machine learning and provides a comprehensive taxonomic view of metaheuristics methods according to a variety of criteria such as data type, scope, and method. The second section of this book explains how to apply metaheuristics techniques for solving large-scale biomedical problems, including analysis and validation under different strategies. The final portion of the book focuses on advanced topics in metaheuristics in four different applications. Readers will discover a variety of new methods, approaches, and techniques, as well as a wide range of applications demonstrating key concepts in metaheuristics for biomedical science. This book provides a leading-edge resource for researchers in a variety of scientific fields who are interested in metaheuristics, including mathematics, biomedical engineering, computer science, biological sciences, and clinicians in medical practice.

  • Multifunctional Nanocomposites for Targeted Drug Delivery in Cancer Therapy

    • 1st Edition
    • Awesh K. Yadav + 2 more
    • Awesh K. Yadav + 2 more
    • English
    Multifunctional Nanocomposites for Targeted Drug Delivery in Cancer Therapy explores the design, synthesis, and application of different multifunctional nanocomposites drug delivery system for cancer treatment. It encompasses initial chapters discussing introductory information about cancer, followed by chapters focusing on the detailed information about various novel drug delivery systems for treatment of several organ site cancers such as prostate, skin, breast, lung, liver, pancreas, stomach, colon, blood, mouth and throat. It is a valuable resource for cancer researchers, oncologists, graduate students, and members of biomedical research who need to understand more about novel nanotechnologies applied to cancer treatment.

  • Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems

    • 1st Edition
    • Yuekuan Zhou + 3 more
    • English
    Advances in Digitalization and Machine Learning for Integrated Building-Transportat... Energy Systems examines the combined impact of buildings and transportation systems on energy demand and use. With a strong focus on AI and machine learning approaches, the book comprehensively discusses each part of the energy lifecycle, considering source, grid, demand, storage, and usage. Opening with an introduction to smart buildings and intelligent transportation systems, the book presents the fundamentals of AI and its application in renewable energy sources, alongside the latest technological advances. Other topics presented include building occupants’ behavior and vehicle driving schedule with demand prediction and analysis, hybrid energy storages in buildings with AI, smart grid with energy digitalization, and prosumer-based P2P energy trading. The book concludes with discussions on blockchain technologies, IoT in smart grid operation, and the application of big data and cloud computing in integrated smart building-transportat... energy systems. This title provides critical information to students, researchers, and engineers wanting to understand, design, and implement flexible energy systems to meet the rising demand in electricity.

  • 5G/5G-Advanced

    The New Generation Wireless Access Technology
    • 3rd Edition
    • Erik Dahlman + 2 more
    • English
    5G Advanced: The Next Generation Wireless Access Technology, Third Edition follows the authors' highly celebrated books on 3G and 4G by providing a new level of insight into 5G NR. After an initial discussion of the background to 5G, including requirements, spectrum aspects and the standardization timeline, all technology features of the first phase of NR are described in detail. Included is a detailed description of the NR physical-layer structure and higher-layer protocols, RF and spectrum aspects and co-existence and interworking with LTE. This book provides a good understanding of NR and the different NR technology components, giving insight into why a certain solution was selected.

  • Colorectal Cancer

    Disease and Advanced Drug Delivery Strategies
    • 1st Edition
    • Bhupendra G. Prajapati + 2 more
    • English
    Colorectal Cancer: Disease and Advanced Drug Delivery Strategies examines the combined impact of basic clinical and medical treatments as well as recent advances in the field of colorectal cancer. With a strong focus towards colorectal cancer diagnosis, disease drug delivery, and diagnosis, the book also examines the Tumor microenvironment-res... and site-specific nanoparticles for cancer theragnostics. Sections provide the opportunity to understand and diagnose the disease, describes screening methods, and update on drugs, including nano- and immunotherapy. Content includes clinical trials in colorectal cancer research and disease models that help better direct researchers and clinicians on how to diagnose and treat colorectal cancer.

  • Biomarkers in Cancer Detection and Monitoring of Therapeutics

    Volume 1: Discovery and Technologies
    • 1st Edition
    • Ranbir Chander Sobti + 2 more
    • English
    Biomarkers in Cancer Detection and Monitoring of Therapeutics, Volume One, Discovery and Technologies discusses how molecular biomarkers are used to determine predisposition, facilitate detection, improve treatment and offer prevention guidelines for different cancer types. This first volume in the series focuses on techniques and approaches recently developed to assist in the decision of which biomarker to use for specific conditions. Topics covered include circulating tumor cells and circulating tumor DNA, exomes, tumor microenvironment, gene editing, artificial intelligence and robotics. In addition, the book discusses the development and applications of organoids and precision medicine.This book will be a valuable resource for cancer researchers, oncologists, graduate students and members of the biomedical field who are interested in the potential of biomarkers in cancer research.

  • Biomarkers in Cancer Detection and Monitoring of Therapeutics

    Volume 2: Diagnostic and Therapeutic Applications
    • 1st Edition
    • Ranbir Chander Sobti + 2 more
    • English
    Molecular Biomarkers in Cancer Detection and Monitoring of Therapeutics: Volume Two: Diagnostic and Therapeutic Applications discusses how molecular biomarkers are used to determine predisposition, facilitate detection, improve treatment and offer prevention guidelines for different cancers. It focuses on novel diagnostic techniques based on molecular biomarkers and their impact on treatment, covering different cancer types such as tumors in the nervous system, head and neck, oral and GI tractor, lung, breast, gastric system, leukemia and urogenital tract cancers. For each type, the book discusses the best diagnostic techniques and therapeutic approaches, thus helping readers easily identify the best solution for each case. This is a valuable resource for cancer researchers, oncologists, graduate students and other members of the biomedical field who are interested in the potential of biomarkers in cancer research.

  • Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images

    • 1st Edition
    • D. Jude Hemanth
    • English
    Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images comprehensively examines the wide range of AI-based mammogram analysis methods for medical applications. Beginning with an introductory overview of mammogram data analysis, the book covers the current technologies such as ultrasound, molecular breast imaging (MBI), magnetic resonance (MR), and Positron Emission mammography (PEM), as well as the recent advancements in 3D breast tomosynthesis and 4D mammogram. Deep learning models are presented in each chapter to show how they can assist in the efficient processing of breast images.The book also discusses hybrid intelligence approaches for early-stage detection and the use of machine learning classifiers for cancer detection, staging and density assessment in order to develop a proper treatment plan. This book will not only aid computer scientists and medical practitioners in developing a real-time AI based mammogram analysis system, but also addresses the issues and challenges with the current processing methods which are not conducive for real-time applications.

  • Picture Fuzzy Logic and Its Applications in Decision Making Problems

    • 1st Edition
    • Chiranjibe Jana + 3 more
    • English
    Picture Fuzzy Logic and Its Applications in Decision Making Problems provides methodological frameworks and the latest empirical research findings in the field of picture fuzzy operators and their applications in scientific research and real-world engineering problems. In this book, picture fuzzy sets are investigated, and different types of operators are defined to solve a number of important decision-making and optimization problems. The hybrid operator on picture fuzzy set based on the combination of picture fuzzy weighted averaging operators and picture fuzzy weighted geometric operators is developed and named Hybrid Picture Fuzzy Weighted Averaging Geometric (H-PFWAG) operator. In addition, another operator is developed for interval-valued picture fuzzy environment, which is named Hybrid Interval-Valued Picture Fuzzy Weighted Averaging Geometric (H-IVPFWAG) operator. These two operators are then demonstrated as solutions to Multiple-Attribute Decision-Making (MADM) problems. The picture fuzzy soft weighted aggregation operators (averaging and geometric) are defined, and these are applied to develop a multi-criteria group decision making system.

  • Embedded Systems

    ARM Programming and Optimization
    • 2nd Edition
    • Jason D. Bakos
    • English
    Embedded Systems: ARM Programming and Optimization, Second Edition combines an exploration of the ARM architecture with an examination of the facilities offered by the Linux operating system to explain how various features of program design can influence processor performance. The book demonstrates methods by which a programmer can optimize program code in a way that does not impact its behavior but instead improves its performance. Several applications, including image transformations, fractal generation, image convolution, computer vision tasks, and now machine learning are used to describe and demonstrate these methods. From this, the reader will gain insight into computer architecture and application design, as well as practical knowledge in embedded software design for modern embedded systems. The second edition has been expanded to include more topics of interest to upper level undergraduate courses in embedded systems.

  • Multi-Criteria Decision-Making for Renewable Energy

    Methods, Applications, and Challenges
    • 1st Edition
    • Mohamed Abdel-Basset + 3 more
    • English
    Multi-Criteria Decision-Making for Renewable Energy: Methods, Applications, and Challenges brings together the latest fuzzy and soft computing methods, models, and algorithms as applied to the field of renewable energy and supported by specific application examples and case studies. The book begins by approaching renewable energy sources, challenges and factors that affect their development, as well as green renewable energy sites and the utilization of fuzzy multi-criteria decision-making (MCDM) techniques in these broad contexts, as well as utilization in addressing the various environmental, economic, and social barriers to ensuring the sustainability of energy resources. Detailed chapters focus on the application of multi-criteria decision-making methods for planning, modeling and prioritization in specific areas of renewable energy, including solar energy, wind farms, solar-powered hydrogen production plants, biofuel production, energy storage, hydropower, and marine energy. Finally, future opportunities and research directions are explored.

  • Recent Advances in Nanocarriers for Pancreatic Cancer Therapy

    • 1st Edition
    • Prashant Kesharwani + 1 more
    • English
    Recent Advances in Nanocarriers for Pancreatic Cancer Therapy reviews thriving strategies concerning pancreatic cancer therapy, thoroughly describing the most recent developments in emerging modern drug delivery systems focused on, and derived from, nanotechnology. By providing a holistic understanding of the molecular pathways, conventional therapy and novel nanocarriers mediated drug delivery against pancreatic cancer, this work can be considered a complete package. The book offers a solution to the dissemination of data from a broad range of resources by providing an overview of the molecular pathways and conventional therapy of pancreatic cancer, the application of various nanocarriers, and more. This book equips scientists, clinicians and students to make rational treatment approaches based on nanomedicine for improving and extending the human life against pancreatic cancer.

  • Artificial Intelligence in the Age of Neural Networks and Brain Computing

    • 2nd Edition
    • Robert Kozma + 3 more
    • English
    Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters.

  • Energy Management in Homes and Residential Microgrids

    Short-Term Scheduling and Long-Term Planning
    • 1st Edition
    • Reza Hemmati
    • English
    Energy Management in Homes and Residential Microgrids: Short-Term Scheduling and Long-Term Planning provides an in-depth exploration of Home Energy Management Systems (HEMS), with a focus on practical applications for both short- and long-term models. Through this guide, readers will learn how to create efficient systems that facilitate the integration of renewable energy into the grid and simultaneously manage end-users' energy consumption. The short-term operation of Home Energy Management Systems is analyzed through various lenses, including renewable energy integration, energy storage integration, uncertainty in parameters, off-grid operation, outages and events, resilience, electric vehicle integration, and battery swapping strategy.The modelling of these topics is explained with step-by-step instructions, and the parameters and implications are thoroughly discussed. Additionally, the book offers insight into the long-term expansion planning for residential microgrids, providing a detailed examination of dynamic modeling, control, and stability of these small-scale energy systems. Throughout the book, simple and advanced examples are provided, and each example comes with numerical data, detailed formulation, modelling, and simulation.

  • Machine Learning for Biomedical Applications

    With Scikit-Learn and PyTorch
    • 1st Edition
    • Maria Deprez + 1 more
    • English
    Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch presents machine learning techniques most commonly used in a biomedical setting. Avoiding a theoretical perspective, it provides a practical and interactive way of learning where concepts are presented in short descriptions followed by simple examples using biomedical data. Interactive Python notebooks are provided with each chapter to complement the text and aid understanding. Sections cover uses in biomedical applications, practical Python coding skills, mathematical tools that underpin the field, core machine learning methods, deep learning concepts with examples in Keras, and much more. This accessible and interactive introduction to machine learning and data analysis skills is suitable for undergraduates and postgraduates in biomedical engineering, computer science, the biomedical sciences and clinicians.

  • Autonomous Mobile Robots

    Planning, Navigation and Simulation
    • 1st Edition
    • Rahul Kala
    • English
    Autonomous Mobile Robots: Planning, Navigation, and Simulation presents detailed coverage of the domain of robotics in motion planning and associated topics in navigation. This book covers numerous base planning methods from diverse schools of learning, including deliberative planning methods, reactive planning methods, task planning methods, fusion of different methods, and cognitive architectures. It is a good resource for doing initial project work in robotics, providing an overview, methods and simulation software in one resource. For more advanced readers, it presents a variety of planning algorithms to choose from, presenting the tradeoffs between the algorithms to ascertain a good choice. Finally, the book presents fusion mechanisms to design hybrid algorithms.

  • Resistance to Anti-CD20 Antibodies and Approaches for Their Reversal

    • 1st Edition
    • Volume 2
    • English
    Resistance to Anti-CD20 Antibodies and Approaches for Their Reversal presents in-depth content written by international experts in the study of resistance to anti-CD20 antibodies and approaches for their reversal. Anti-CD20 antibodies are used to achieve B cell depletion and are developed to treat B cell proliferative disorders, including non-Hodgkin’s lymphoma and chronic lymphocytic leukemia. In the past two decades, anti-CD20 antibodies have revolutionized the treatment of all B cell malignancies, however, there are patients that fail to respond to initial therapy or relapse sooner. This book explores new and existing avenues surrounding Anti-CD20 antibodies. In recent years, several next-generation anti-CD20 therapies have been developed but predicting and reversing resistance is still a challenging task. These areas are being actively studied as they represent a potential to improve anti-CD20 therapies and are discussed thoroughly in the book. It is a valuable resource for researchers, students and member of the biomedical and medical fields who want to learn more about resistance to anti-CD20 antibodies and their reversal.

  • Innovations in Artificial Intelligence and Human-Computer Interaction in the Digital Era

    • 1st Edition
    • Surbhi Bhatia Khan + 3 more
    • English
    Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches. Chapters explore how well AI can interact with users based on linguistics and user-centered design processes, especially with the advances of AI and the hype around many applications. Other sections investigate how HCI and AI can mutually benefit from a closer association and the how the AI community can improve their usage of HCI methods like “Wizard of Oz” prototyping and “Thinking aloud” protocols. Moreover, HCI can further augment human capabilities using new technologies. This book demonstrates how an interdisciplinary team of HCI and AI researchers can develop extraordinary applications, such as improved education systems, smart homes, smart healthcare and map Human Computer Interaction (HCI) for a multidisciplinary field that focuses on the design of computer technology and the interaction between users and computers in different domains.

  • Computational Intelligence Applications for Text and Sentiment Data Analysis

    • 1st Edition
    • Dipankar Das + 3 more
    • English
    Computational Intelligence Applications for Text and Sentiment Data Analysis explores the most recent advances in text information processing and data analysis technologies, specifically focusing on sentiment analysis from multifaceted data. The book investigates a wide range of challenges involved in the accurate analysis of online sentiments, including how to i) identify subjective information from text, i.e., exclusion of ‘neutral’ or ‘factual’ comments that do not carry sentiment information, ii) identify sentiment polarity, and iii) domain dependency. Spam and fake news detection, short abbreviation, sarcasm, word negation, and a lot of word ambiguity are also explored.Further chapters look at the difficult process of extracting sentiment from different multimodal information (audio, video and text), semantic concepts. In each chapter, the book's authors explore how computational intelligence (CI) techniques, such as deep learning, convolutional neural network, fuzzy and rough set, global optimizers, and hybrid machine learning techniques play an important role in solving the inherent problems of sentiment analysis applications.

  • Is Justice Real When “Reality” is Not?

    Constructing Ethical Digital Environments
    • 1st Edition
    • Katherine B. Forrest + 1 more
    • English
    Is Justice Real When “Reality” is Not?: Constructing Ethical Digital Environments examines how frameworks and concepts of justice should evolve in virtual worlds. Directed at researchers working in, or with an interest in virtual reality, as well as those interested in the fields of artificial intelligence and justice, this book covers research regarding impacts on human psychological states existing within alternative ethical frameworks. With chapters dedicated to behavioral impacts of virtual events, robotics and "unconscious", and human psychological states of role playing and existing, readers will be well-equipped to navigate the virtual worlds in which millions of people currently spend time.

  • pH Deregulation as the Eleventh Hallmark of Cancer

    • 1st Edition
    • Tomas Koltai + 6 more
    • English
    pH Deregulation as the Eleventh Hallmark of Cancer presents key concepts about pH deregulation in a concise and straight-forward manner. The book discusses topics such as pH regulation and metabolism, sodium hydrogen exchanger, monocarboxylate transporter, V-ATPase proton pump, carbonic anhydrases, and voltage gated sodium channels. In addition, it covers clinical and therapeutic implications and future perspectives. This is a valuable resource for researchers, oncologists, students and members of the biomedical and medical fields who want to learn more about the role of pH deregulation in cancer treatment. pH deregulation can improve the outcome of classical treatments without adding toxicity to them, and the book shows that treating the pH peculiarities of cancer is simple and can be performed with existing drugs. Based on the classification of tumor malignancy in ten hallmarks, the authors put pH deregulation at the spotlight and separated from metabolic reprogramming due to its impact on all other hallmarks, proposing it as an additional characteristic to evaluate and fight cancer.

  • High-Order Models in Semantic Image Segmentation

    • 1st Edition
    • Ismail Ben Ayed
    • English
    High-Order Models in Semantic Image Segmentation reviews recent developments in optimization-based methods for image segmentation, presenting several geometric and mathematical models that underlie a broad class of recent segmentation techniques. Focusing on impactful algorithms in the computer vision community in the last 10 years, the book includes sections on graph-theoretic and continuous relaxation techniques, which can compute globally optimal solutions for many problems. The book provides a practical and accessible introduction to these state-of -the-art segmentation techniques that is ideal for academics, industry researchers, and graduate students in computer vision, machine learning and medical imaging.

  • Handbook of Metaheuristic Algorithms

    From Fundamental Theories to Advanced Applications
    • 1st Edition
    • Chun-Wei Tsai + 1 more
    • English
    Handbook of Metaheuristic Algorithms: From Fundamental Theories to Advanced Applications provides a brief introduction to metaheuristic algorithms from the ground up, including basic ideas and advanced solutions. Although readers may be able to find source code for some metaheuristic algorithms on the Internet, the coding styles and explanations are generally quite different, and thus requiring expanded knowledge between theory and implementation. This book can also help students and researchers construct an integrated perspective of metaheuristic and unsupervised algorithms for artificial intelligence research in computer science and applied engineering domains. Metaheuristic algorithms can be considered the epitome of unsupervised learning algorithms for the optimization of engineering and artificial intelligence problems, including simulated annealing (SA), tabu search (TS), genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), differential evolution (DE), and others. Distinct from most supervised learning algorithms that need labeled data to learn and construct determination models, metaheuristic algorithms inherit characteristics of unsupervised learning algorithms used for solving complex engineering optimization problems without labeled data, just like self-learning, to find solutions to complex problems.

  • Artificial Intelligence in Healthcare and COVID-19

    • 1st Edition
    • Parag Chatterjee + 1 more
    • English
    Artificial Intelligence in Healthcare and COVID-19 showcases theoretical concepts and implementational and research perspectives surrounding AI. The book addresses both medical and technological visions, making it even more applied. With the advent of COVID-19, it is obvious that leading universities and medical schools must include these topics and case studies in their usual courses of health informatics to keep up with the pace of technological and medical advancements. This book will also serve professors teaching courses and industry practitioners and professionals working in the R&D team of leading medical and informatics companies who want to embrace AI and eHealth to fight COVID-19. Since AI in healthcare is a comparatively new field, there exists a vacuum of literature in this field, especially when applied to COVID-19. With the area of AI in COVID-19 being quite young, students and researchers usually face a struggle to rely on the few published papers (which are obviously too specific) or whitepapers by tech-giants (which are too wide).

  • Uncertainty in Data Envelopment Analysis

    Fuzzy and Belief Degree-Based Uncertainties
    • 1st Edition
    • Farhad Hosseinzadeh Lotfi + 4 more
    • English
    Classical data envelopment analysis (DEA) models use crisp data to measure the inputs and outputs of a given system. In cases such as manufacturing systems, production processes, service systems, etc., the inputs and outputs may be complex and difficult to measure with classical DEA models. Crisp input and output data are fundamentally indispensable in the conventional DEA models. If these models contain complex uncertain data, then they will become more important and practical for decision makers.Uncertainty in Data Envelopment Analysis introduces methods to investigate uncertain data in DEA models, providing a deeper look into two types of uncertain DEA methods, fuzzy DEA and belief degree-based uncertainty DEA, which are based on uncertain measures. These models aim to solve problems encountered by classical data analysis in cases where the inputs and outputs of systems and processes are volatile and complex, making measurement difficult.

  • Visualization, Visual Analytics and Virtual Reality in Medicine

    State-of-the-art Techniques and Applications
    • 1st Edition
    • Bernhard Preim + 3 more
    • English
    Visualization, Visual Analytics and Virtual Reality in Medicine: State-of-the-art Techniques and Applications describes important techniques and applications that show an understanding of actual user needs as well as technological possibilities. The book includes user research, for example, task and requirement analysis, visualization design and algorithmic ideas without going into the details of implementation. This reference will be suitable for researchers and students in visualization and visual analytics in medicine and healthcare, medical image analysis scientists and biomedical engineers in general. Visualization and visual analytics have become prevalent in public health and clinical medicine, medical flow visualization, multimodal medical visualization and virtual reality in medical education and rehabilitation. Relevant applications now include digital pathology, virtual anatomy and computer-assisted radiation treatment planning.

  • Multi-Criteria Decision-Making Sorting Methods

    Applications to Real-World Problems
    • 1st Edition
    • Luis Martinez Lopez + 3 more
    • English
    Multi Criteria Decision Making (MCDM) is a generic term for all methods that help people making decisions according to their preferences, in situations where there is more than one conflicting criterion. It is a branch of operational research dealing with finding optimal results in complex scenarios including various indicators, conflicting objectives and criteria. The approach of MCDM involves decision making concerning quantitative and qualitative factors.　　 The importance and success of MCDM are due to the fact that they have successfully dealt with different types of problematics for supporting decision makers such as choice, ranking and sorting, description.　　 Even though, each of the different problematics in MCDM is important, Multi-Criteria Decision-Making Sorting Methods will focus on sorting approaches across a wide range of interesting techniques and research disciplines. The applications which have been and can be solved by these techniques are more and more important in current real-world decision-making problems. Therefore, the book provides a clear overview of MCDM sorting methods and the different tools which can be used to solve real-world problems by revising such tools and characterizing them according to their performance and suitability for different types of problems. The book is aimed at a broad audience including computer scientists, engineers, geography and GIS experts, business and financial management experts, environment experts, and all those professional people interested in MCDM and its applications. The book may also be useful for teaching MCDM courses in fields such as industrial management, computer science, and applied mathematics, as new developments in multi-criteria decision making.

  • Reachable Sets of Dynamic Systems

    Uncertainty, Sensitivity, and Complex Dynamics
    • 1st Edition
    • Stanislaw Raczynski
    • English
    Reachable Sets of Dynamic Systems: Uncertainty, Sensitivity, and Complex Dynamics introduces differential inclusions, providing an overview as well as multiple examples of its interdisciplinary applications. The design of dynamic systems of any type is an important issue as is the influence of uncertainty in model parameters and model sensitivity. The possibility of calculating the reachable sets may be a powerful additional tool in such tasks. This book can help graduate students, researchers, and engineers working in the field of computer simulation and model building, in the calculation of reachable sets of dynamic models.

  • Robotics for Cell Manipulation and Characterization

    • 1st Edition
    • Changsheng Dai + 2 more
    • English
    Robotics for Cell Manipulation and Characterization provides fundamental principles underpinning robotic cell manipulation and characterization, state-of-the-art technical advances in micro/nano robotics, new discoveries of cell biology enabled by robotic systems, and their applications in clinical diagnosis and treatment. This book covers several areas, including robotics, control, computer vision, biomedical engineering and life sciences using understandable figures and tables to enhance readers’ comprehension and pinpoint challenges and opportunities for biological and biomedical research.

  • Biostatistics Manual for Health Research

    A Practical Guide to Data Analysis
    • 1st Edition
    • Nafis Faizi + 1 more
    • English
    **Selected for 2026 Doody's Core Titles in Biostatistics**Biost... Manual for Health Research: A Practical Guide to Data Analysis is a guide for researchers on how to apply biostatistics on different types of data. The book approaches biostatistics and its application from medical and health researcher’s point-of-view and has real and mostly published data for practice and understanding. The interpretation and meaning of the statistical results, reporting guidelines and mistakes are taught with real world examples. This is a valuable resource for biostaticians, students and researchers from medical and biomedical fields who need to learn how to apply statistical approaches to improve their research.

  • Nitric Oxide in Health and Disease

    Therapeutic Applications in Cancer and Inflammatory Disorders
    • 1st Edition
    • Lucia Morbidelli + 2 more
    • English
    Approx.326 pages

  • Up and Running with AutoCAD® 2024

    2D and 3D Drawing, Design and Modeling
    • 1st Edition
    • Elliot J. Gindis + 1 more
    • English
    Up and Running with AutoCAD® 2024: 2D and 3D Drawing, Design and Modeling presents a combination of step-by-step instructions, examples and insightful explanations. The book emphasizes core concepts and practical application of AutoCAD in engineering, architecture and design. Equally useful in instructor-led classroom training, self-study or as a professional reference, the book is written by a long-time AutoCAD professor and instructor with the user in mind.

  • A Handbook of Artificial Intelligence in Drug Delivery

    • 1st Edition
    • Anil K. Philip + 3 more
    • English
    A Handbook of Artificial Intelligence in Drug Delivery explores the use of Artificial Intelligence (AI) in drug delivery strategies. The book covers pharmaceutical AI and drug discovery challenges, Artificial Intelligence tools for drug research, AI enabled intelligent drug delivery systems and next generation novel therapeutics, broad utility of AI for designing novel micro/nanosystems for drug delivery, AI driven personalized medicine and Gene therapy, 3D Organ printing and tissue engineering, Advanced nanosystems based on AI principles (nanorobots, nanomachines), opportunities and challenges using artificial intelligence in ADME/Tox in drug development, commercialization and regulatory perspectives, ethics in AI, and more. This book will be useful to academic and industrial researchers interested in drug delivery, chemical biology, computational chemistry, medicinal chemistry and bioinformatics. The massive time and costs investments in drug research and development necessitate application of more innovative techniques and smart strategies.

  • Computational Methods in Drug Discovery and Repurposing for Cancer Therapy

    • 1st Edition
    • Ganji Purnachandra Nagaraju + 2 more
    • English
    Computational Methods in Drug Discovery and Repurposing for Cancer Therapy provides knowledge about ongoing research as well as computational approaches for drug discovery and repurposing for cancer therapy. The book also provides detailed descriptions about target molecules, pathways, and their inhibitors for easy understanding and applicability. The book discusses tools and techniques such as integrated bioinformatics approaches, systems biology tools, molecular docking, computational chemistry, artificial intelligence, machine learning, structure-based virtual screening, biomarkers, and transcriptome; those are discussed in the context of different cancer types, such as colon, pancreatic, glioblastoma, endometrial, and retinoblastoma, among others. This book is a valuable resource for researchers, students, and members of the biomedical and medical fields who want to learn more about the use of computational modeling to better tailor the treatment for cancer patients.

  • Machine Learning

    A Constraint-Based Approach
    • 2nd Edition
    • Marco Gori + 2 more
    • English
    Machine Learning: A Constraint-Based Approach, Second Edition provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that include neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. It draws a path towards deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, such as in fuzzy systems. Special attention is given to deep learning, which nicely fits the constrained-based approach followed in this book.The book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, including many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included.

  • Perspective of DNA Computing in Computer Science

    • 1st Edition
    • Volume 129
    • English
    DNA or Deoxyribonucleic Acid computing is an emerging branch of computing that uses DNA sequence, biochemistry, and hardware for encoding genetic information in computers. Here, information is represented by using the four genetic alphabets or DNA bases, namely A (Adenine), G (Guanine), C (Cytosine), and T (Thymine), instead of the binary representation (1 and 0) used by traditional computers. This is achieved because short DNA molecules of any arbitrary sequence of A, G, C, and T can be synthesized to order. DNA computing is mainly popular for three reasons: (i) speed (ii) minimal storage requirements, and (iii) minimal power requirements. There are many applications of DNA computing in the field of computer science. Nowadays, DNA computing is widely used in cryptography for achieving a strong security technique, so that unauthorized users are unable to retrieve the original data content. In DNA-based encryption, data are encrypted by using DNA bases (A, T, G, and C) instead of 0 and 1. As four DNA bases are used in the encryption process, DNA computing supports more randomness and makes it more complex for attackers or malicious users to hack the data. DNA computing is also used for data storage because a large number of data items can be stored inside the condensed volume. One gram of DNA holds approx DNA bases or approx 700 TB. However, it takes approx 233 hard disks to store the same data on 3 TB hard disks, and the weight of all these hard disks can be approx 151 kilos. In a cloud environment, the Data Owner (DO) stores their confidential encrypted data outside of their own domain, which attracts many attackers and hackers. DNA computing can be one of the best solutions to protect the data of a cloud server. Here, the DO can use DNA bases to encrypt the data by generating a long DNA sequence. Another application of DNA computing is in Wireless Sensor Network (WSN). Many researchers are trying to improve the security of WSN by using DNA computing. Here, DNA cryptography is used along with Secure Socket Layer (SSL) that supports a secure medium to exchange information. However, recent research shows some limitations of DNA computing. One of the critical issues is that DNA cryptography does not have a strong mathematical background like other cryptographic systems. This edited book is being planned to bring forth all the information of DNA computing. Along with the research gaps in the currently available books/literature, this edited book presents many applications of DNA computing in the fields of computer science. Moreover, research challenges and future work directions in DNA computing are also provided in this edited book.

  • Explainable Deep Learning AI

    Methods and Challenges
    • 1st Edition
    • Jenny Benois-Pineau + 3 more
    • English
    Explainable Deep Learning AI: Methods and Challenges presents the latest works of leading researchers in the XAI area, offering an overview of the XAI area, along with several novel technical methods and applications that address explainability challenges for deep learning AI systems. The book overviews XAI and then covers a number of specific technical works and approaches for deep learning, ranging from general XAI methods to specific XAI applications, and finally, with user-oriented evaluation approaches. It also explores the main categories of explainable AI – deep learning, which become the necessary condition in various applications of artificial intelligence. The groups of methods such as back-propagation and perturbation-based methods are explained, and the application to various kinds of data classification are presented.

  • Emerging Practices in Telehealth

    Best Practices in a Rapidly Changing Field
    • 1st Edition
    • Andrew M. Freeman + 1 more
    • English
    **Selected for 2026 Doody's Core Titles in Ambulatory**Emerging Practices in Telehealth: Best Practices in a Rapidly Changing Field is an introduction to telehealth basics, best practices and implementation methods. The book guides the reader from start to finish through the workflow implementation of telehealth technology, including EMRs, clinical workflows, RPM, billing systems, and patient experience. It also explores how telehealth can increase healthcare access and decrease disparities across the globe. Practicing clinicians, medical fellows, allied healthcare professionals, hospital administrators, and hospital IT professionals will all benefit from this practical guidebook.

  • Hamiltonian Monte Carlo Methods in Machine Learning

    • 1st Edition
    • Tshilidzi Marwala + 2 more
    • English
    Hamiltonian Monte Carlo Methods in Machine Learning introduces methods for optimal tuning of HMC parameters, along with an introduction of Shadow and Non-canonical HMC methods with improvements and speedup. Lastly, the authors address the critical issues of variance reduction for parameter estimates of numerous HMC based samplers. The book offers a comprehensive introduction to Hamiltonian Monte Carlo methods and provides a cutting-edge exposition of the current pathologies of HMC-based methods in both tuning, scaling and sampling complex real-world posteriors. These are mainly in the scaling of inference (e.g., Deep Neural Networks), tuning of performance-sensitiv... sampling parameters and high sample autocorrelation. Other sections provide numerous solutions to potential pitfalls, presenting advanced HMC methods with applications in renewable energy, finance and image classification for biomedical applications. Readers will get acquainted with both HMC sampling theory and algorithm implementation.

  • Intelligent Edge Computing for Cyber Physical Applications

    • 1st Edition
    • D. Jude Hemanth + 3 more
    • English
    Intelligent Edge Computing for Cyber Physical Applications introduces state-of-the-art research methodologies, tools and techniques, challenges, and solutions with further research opportunities in the area of edge-based cyber-physical systems. The book presents a comprehensive review of recent literature and analysis of different techniques for building edge-based CPS. In addition, it describes how edge-based CPS can be built to seamlessly interact with physical machines for optimal performance, covering various aspects of edge computing architectures for dynamic resource provisioning, mobile edge computing, energy saving scenarios, and different security issues. Sections feature practical use cases of edge-computing which will help readers understand the workings of edge-based systems in detail, taking into account the need to present intellectual challenges while appealing to a broad readership, including academic researchers, practicing engineers and managers, and graduate students.

  • Comprehensive Metaheuristics

    Algorithms and Applications
    • 1st Edition
    • Ali Mirjalili + 1 more
    • English
    Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-world applications across a variety of research fields. The book starts with fundamentals, mathematical prerequisites, and conceptual approaches to provide readers with a solid foundation. After presenting multi-objective optimization, constrained optimization, and problem formation for metaheuristics, world-renowned authors give readers in-depth understanding of the full spectrum of algorithms and techniques. Scientists, researchers, academicians, and practitioners who are interested in optimizing a process or procedure to achieve a goal will benefit from the case studies of real-world applications from different domains. The book takes a much-needed holistic approach, putting the most widely used metaheuristic algorithms together with an in-depth treatise on multi-disciplinary applications of metaheuristics. Each algorithm is thoroughly analyzed to observe its behavior, providing a detailed tutorial on how to solve problems using metaheuristics. New case studies and research problem statements are also discussed, which will help researchers in their application of the concepts.

  • Principles of Big Graph: In-depth Insight

    • 1st Edition
    • Volume 128
    • English
    Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field with this new volume presenting interesting chapters on a variety of topics, including CESDAM: Centered subgraph data matrix for large graph representation, Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications, An empirical investigation on Big Graph using deep learning, Analyzing correlation between quality and accuracy of graph clustering, geneBF: Filtering protein-coded gene graph data using bloom filter, Processing large graphs with an alternative representation, MapReduce based convolutional graph neural networks: A comprehensive review. Fast exact triangle counting in large graphs using SIMD acceleration, A comprehensive investigation on attack graphs, Qubit representation of a binary tree and its operations in quantum computation, Modified ML-KNN: Role of similarity measures and nearest neighbor configuration in multi label text classification on big social network graph data, Big graph based online learning through social networks, Community detection in large-scale real-world networks, Power rank: An interactive web page ranking algorithm, GA based energy efficient modelling of a wireless sensor network, The major challenges of big graph and their solutions: A review, and An investigation on socio-cyber crime graph.

  • Data Science, Analytics and Machine Learning with R

    • 1st Edition
    • Luiz Paulo Favero + 2 more
    • English
    Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear.

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