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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.

BooksJournals

    • Quantum Process Algebra

      • 1st Edition
      • March 6, 2025
      • Yong Wang
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 5 1 3 5
      • eBook
        9 7 8 0 4 4 3 2 7 5 1 4 2
      Quantum Process Algebra introduces readers to the algebraic properties and laws for quantum computing. The book provides readers with all aspects of algebraic theory for quantum computing, including the basis of semantics and axiomatization for quantum computing. With the assumption of a quantum system, readers will learn to solve the modeling of the three main components in a quantum system: the unitary operator, quantum measurement, and quantum entanglement, with full support of quantum and classical computing in closed systems. Next, the book establishes the relationship between probabilistic quantum bisimilarity and classical probabilistic bisimilarity, including strong probabilistic bisimilarity and weak probabilistic bisimilarity, which makes an axiomatization of quantum processes possible. With this framework, quantum and classical computing mixed processes are unified with the same structured operational semantics. Finally, the book establishes a series of axiomatizations of quantum process algebras. These process algebras support nearly all the main computation properties. Quantum and classical computing in closed quantum systems are unified with the same equational logic and the same structured operational semantics under the framework of ACP-like probabilistic process algebra. This unification means that the mathematics in the book can be used widely for verification of quantum and classical computing mixed systems, for example, most quantum communication protocols. ACP-like axiomatization also inherits the advantages of ACP, for example, and modularity means that it can be extended in an elegant way.

    • Blockchain and Digital Twin for Smart Hospitals

      • 1st Edition
      • February 1, 2025
      • Tuan Anh Nguyen
      • English
      • Paperback
        9 7 8 0 4 4 3 3 4 2 2 6 4
      • eBook
        9 7 8 0 4 4 3 3 4 2 2 7 1
      Blockchain and Digital Twins for Smart Healthcare describes the role of blockchain and digital twins in smart healthcare, covering the ecosystem of the Internet of Medical Things, how data can be gathered using a sensor network, which is securely stored, updated, and managed with blockchain for efficient and private medical data exchange. Medical data is collected real-time from devices and systems in smart hospitals: the internet of medical things. This data is integrated to provide insight from the analytics or machine learning software using digital twins. Security and transparency are brought through a combination of digital twin and blockchain technologies.

    • Accelerating Digital Transformation with the Cloud and the Internet of Things (IoT)

      • 1st Edition
      • January 20, 2025
      • Yacine Atif + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 2 2 1 7 7
      • eBook
        9 7 8 0 4 4 3 2 2 2 1 8 4
      Accelerating Digital Transformation with the Cloud and the Internet of Things (IoT) is a reference for IT engineers and decision-makers who may engage in IoT platform pilot projects. The resources covered in this book help establish plans for sustainable operations and management and assist with the long-term procurement of relevant IoT technologies. The aim of the book is to be exhaustive and holistic by pointing out numerous issues and related solution options that guide with daily challenges when deploying and running IoT platforms.The book is divided into three parts where each part includes relevant theoretical chapters and applied case studies. Part One focuses on architectural and federation options for the design and implementation of IoT platforms that foster strategic collaboration opportunities. Part Two addresses vertical security challenges across IoT platform layers. Finally, Part Three shows how IoT is driving the digital transformation wheel through existing and forthcoming case studies.

    • Dimensionality Reduction in Machine Learning

      • 1st Edition
      • February 4, 2025
      • Jamal Amani Rad + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 2 8 1 8 3
      • eBook
        9 7 8 0 4 4 3 3 2 8 1 9 0
      Dimensionality Reduction in Machine Learning covers both the mathematical and programming sides of dimension reduction algorithms, comparing them in various aspects. Part One provides an introduction to Machine Learning and the Data Life Cycle, with chapters covering the basic concepts of Machine Learning, essential mathematics for Machine Learning, and the methods and concepts of Feature Selection. Part Two covers Linear Methods for Dimension Reduction, with chapters on Principal Component Analysis and Linear Discriminant Analysis. Part Three covers Non-Linear Methods for Dimension Reduction, with chapters on Linear Local Embedding, Multi-dimensional Scaling, and t-distributed Stochastic Neighbor Embedding.Finally, Part Four covers Deep Learning Methods for Dimension Reduction, with chapters on Feature Extraction and Deep Learning, Autoencoders, and Dimensionality reduction in deep learning through group actions. With this stepwise structure and the applied code examples, readers become able to apply dimension reduction algorithms to different types of data, including tabular, text, and image data.

    • Medical Oncology Compendium

      • 1st Edition
      • April 16, 2025
      • Ramon Andrade B de Mello
      • English
      • Paperback
        9 7 8 0 4 4 3 1 5 6 0 9 0
      • eBook
        9 7 8 0 4 4 3 1 5 6 0 8 3
      Medical Oncology Compendium discusses several important topics in oncology with the help of leading experts worldwide who incorporate not only knowledge on recent developments in the field, but contextualize them within diverse socioeconomic environments to guarantee the applicability of the content in challenging scenarios. The book comprehensively discusses topics such as surgery, radiology, carcinogenesis, screening, assessment tools, evidence-based medicine, and precision oncology as applicable to different cancer types as non-small and small cell lung cancer, mesothelioma, breast cancer, gastric-rectal cancer, female specific cancers, prostate, skin and bone sarcomas.In addition, it discusses options to minimize oncology pain and palliative care. It is a valuable resource for oncologists, clinicians, researchers, healthcare workers and members of biomedical field who needs to understand more about diagnosis, treatment options and support for cancer patients.

    • Blockchain and Digital Twin for Smart Healthcare

      • 1st Edition
      • February 12, 2025
      • Tuan Anh Nguyen
      • English
      • Paperback
        9 7 8 0 4 4 3 3 0 3 0 0 5
      • eBook
        9 7 8 0 4 4 3 3 0 3 0 1 2
      The smart hospital framework involves three main layers: data, insight and access. Medical data is collected real-time from devices and systems in a smart hospitals: the internet of medical things. This data is integrated to provide insight from the analytics or machine learning software using digital twins. Security and transparency are brought through a combination of digital twin and blockchain technologies. Blockchain and Digital Twins for Smart Healthcare describes the role of blockchain and digital twins in smart healthcare. It describes the ecosystem of the Internet of Medical Things, how data can be gathered using a sensor network, which is securely stored, updated and managed with blockchain for efficient and private medical data exchange. The end goal is insight that provides faster, smarter decisions with more efficiency to improve care for the patient.

    • Quantum Computing for Healthcare Data

      • 1st Edition
      • January 17, 2025
      • Gayathri Nagasubramanian + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 2 9 7 2
      • eBook
        9 7 8 0 4 4 3 2 9 2 9 8 9
      Quantum Computing for Healthcare Data: Revolutionizing the Future of Medicine presents an advanced overview of the fundamentals of quantum computing, from the transition of traditional to quantum computing, to the challenges and opportunities encountered as various industries enter into the paradigm shift. The book investigates how quantum AI, quantum data processing, and quantum data analysis can best be integrated into healthcare data systems. The book also introduces a range of case studies which feature applications of quantum computing in connected medical devices, medical simulations, robotics, medical diagnosis, and drug discovery. The book will be a valuable resource for researchers, graduate students, and professional programmers and computer engineers working in the areas of healthcare data management and analytics, blockchain, IoT, and big data analytics.

    • Neural Network Algorithms and Their Engineering Applications

      • 1st Edition
      • January 9, 2025
      • Chao Huang + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 2 0 2 6
      • eBook
        9 7 8 0 4 4 3 2 9 2 0 3 3
      Neural Network Algorithms and Their Engineering Applications presents the relevant techniques used to improve the global search ability of neural network algorithms in solving complex engineering problems with multimodal properties. The book provides readers with a complete study of how to use artificial neural networks to design a population-based metaheuristic algorithm, which in turn promotes the application of artificial neural networks in the field of engineering optimization.The authors provide a deep discussion for the potential application of machine learning methods in improving the optimization performance of the neural network algorithm, helping readers understand how to use machine learning methods to design improved versions of the algorithm. Users will find a wealth of source code that covers all applied algorithms. Code applications enhance readers' understanding of methods covered and facilitate readers' ability to apply the algorithms to their own research and development projects.

    • Emerging Fuzzy Intelligent Systems for Smart Healthcare Management

      • 1st Edition
      • April 10, 2025
      • Shahzaib Ashraf + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 9 9 7 4
      • eBook
        9 7 8 0 4 4 3 3 3 9 9 8 1
      Emerging Fuzzy Intelligent Systems for Smart Healthcare Management: Applications of Disc q-Rung Orthopair Fuzzy Sets presents comprehensive methodological frameworks and the latest empirical research findings concerning disc q-rung orthopair fuzzy operators, with a specific focus on their applications in smart technologies for healthcare management. The book solves a crucial problem by offering readers an invaluable opportunity to conduct a comparative analysis, contrasting the proposed methods with their existing knowledge base. Disc q-Rung Orthopair sets, being the generalization of q-Rung Orthopair fuzzy sets, which are, in turn, the generalization of Pythagorean fuzzy sets, extend the capabilities of handling uncertainty beyond conventional fuzzy sets.The authors strive to narrow the knowledge gap by clarifying the practical applications of disc q-rung orthopair fuzzy logic. In addition, it explores an enhanced version of q-Rung Orthopair Fuzzy Sets, specifically focusing on Disc q-Rung Orthopair Fuzzy Sets, introducing various types of operators. These operators play a crucial role in solving decision-making and optimization problems. A notable contribution is the development of a hybrid operator, termed as the Disc q-Rung Orthopair Fuzzy Hybrid Weighted Averaging/Geometric (D-qROFHWA/G) operator.

    • Federated Learning for Medical Imaging

      • 1st Edition
      • March 17, 2025
      • Xiaoxiao Li + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 3 6 4 1 9
      • eBook
        9 7 8 0 4 4 3 2 3 6 4 2 6
      Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging.

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