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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.

  • Machine Learning for Biomedical Applications

    With Scikit-Learn and PyTorch
    • 1st Edition
    • September 7, 2023
    • 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
    • September 1, 2023
    • 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
    • August 30, 2023
    • 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
    • July 22, 2023
    • 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
    • July 14, 2023
    • 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
    • July 6, 2023
    • 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
    • June 30, 2023
    • 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
    • June 22, 2023
    • 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
    • May 30, 2023
    • 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.

  • Uncertainty in Data Envelopment Analysis

    Fuzzy and Belief Degree-Based Uncertainties
    • 1st Edition
    • May 19, 2023
    • 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.

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