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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.

11-20 of 2577 results in All results

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

  • 1st Edition
  • March 1, 2025
  • Yacine Atif + 1 more
  • Fatos Xhafa
  • 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.

Federated Learning for Medical Imaging

  • 1st Edition
  • March 1, 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.In addition, it 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 is a complete resource for computer scientists and engineers as well as clinicians and medical care policymakers wanting to learn about the application of federated learning to medical imaging.

Necrobotics for Healthcare Applications and Management

  • 1st Edition
  • March 1, 2025
  • Hemachandran Kannan + 4 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 4 8 3 2 - 0
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 4 8 3 3 - 7
Necrobotics for Healthcare Applications and Management delves into the emerging area of necrobotics and its implications for healthcare. Exploring the convergence of robotics, technology, and healthcare, the book presents leading-edge research, practical implementations, and ethical considerations. It bridges a significant gap in healthcare literature, furnishing a contemporary and comprehensive perspective on necrobotics. Highlighting its distinct applications, management nuances, and ethical dimensions in the domain of medical robotics, the book equips readers with an in-depth grasp of this evolving field. It offers insights into technological intricacies, practical utilization, and ethical guidelines. Through real-world case studies and exemplar practices, it vividly demonstrates successful necrobotics deployments while addressing integration challenges. The book facilitates adept navigation of necrobotics complexities, spur innovation, enhance patient outcomes, and contribute to healthcare evolution. Catering to the distinct information requisites and daily obstacles encountered by engineers, healthcare practitioners, and researchers, the book offers extensive insights into necrobotics technologies, real-life case studies, and ethical reflections. It stands as a valuable resource for individuals striving to harness necrobotics' potential for efficacious healthcare solutions.

Machine Learning

  • 3rd Edition
  • March 1, 2025
  • Sergios Theodoridis
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 9 2 3 8 - 5
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 9 2 3 9 - 2
Machine Learning: From the Classics to Deep Networks, Transformers and Diffusion Models, Third Edition starts with the basics, including least squares regression and maximum likelihood methods, Bayesian decision theory, logistic regression, and decision trees. It then progresses to more recent techniques, covering sparse modelling methods, learning in reproducing kernel Hilbert spaces and support vector machines. Bayesian learning is treated in detail with emphasis on the EM algorithm and its approximate variational versions with a focus on mixture modelling, regression and classification. Nonparametric Bayesian learning, including Gaussian, Chinese restaurant, and Indian buffet processes are also presented. Monte Carlo methods, particle filtering, probabilistic graphical models with emphasis on Bayesian networks and hidden Markov models are treated in detail. Dimensionality reduction and latent variables modelling are considered in depth. Neural networks and deep learning are thoroughly presented, starting from the perceptron rule and multilayer perceptrons and moving on to convolutional and recurrent neural networks, adversarial learning, capsule networks, deep belief networks, GANs, and VAEs. The book also covers the fundamentals on statistical parameter estimation and optimization algorithms.Focusing on the physical reasoning behind the mathematics, without sacrificing rigor, all methods and techniques are explained in depth, supported by examples and problems, providing an invaluable resource to the student and researcher for understanding and applying machine learning concepts.New to this editionThe new material includes an extended coverage of attention transformers, large language models, self-supervised learning and diffusion models.

Deep Learning in Action: Image and Video Processing for Practical Use

  • 1st Edition
  • March 1, 2025
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 3 0 0 7 8 - 3
  • eBook
    9 7 8 - 0 - 4 4 3 - 3 0 0 7 9 - 0
Artificial intelligence technology has entered an extraordinary phase of fast development and wide application. The techniques developed in traditional AI research areas, such as computer vision and object recognition, have found many innovative applications in an array of real-world settings. The general methodological contributions from AI, such as a variety of recently developed deep learning algorithms, have also been applied to a wide spectrum of fields such as surveillance applications, real-time processing, IoT devices, and health care systems. The state-of-the-art and deep learning models have wider applicability and are highly efficient. Deep Learning in Action: Image and Video Processing for Practical Use provides a comprehensive and accessible resource for both intermediate to advanced readers seeking to harness the power of deep learning in the domains of video and image processing. The book bridges the gap between theoretical concepts and practical implementation by emphasizing lightweight approaches, enabling readers to efficiently apply deep learning techniques to real-world scenarios. It focuses on resource-efficient methods, making it particularly relevant in contexts where computational constraints are a concern.

Artificial Neural Networks and Type-2 Fuzzy Set

  • 1st Edition
  • March 1, 2025
  • Snehashish Chakraverty
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 3 2 8 9 4 - 7
  • eBook
    9 7 8 - 0 - 4 4 3 - 3 2 8 9 5 - 4
Soft computing is an emerging discipline which aims to exploit tolerance for imprecision, approximate reasoning, and uncertainty to achieve robustness, tractability, and cost effectiveness for building intelligent machines. Soft computing methodologies include neural networks, fuzzy sets, genetic algorithms, Bayesian networks, and rough sets, among others. In this regard, neural networks are widely used for modeling dynamic solvers, classification of data, and prediction of solutions, whereas fuzzy sets provide a natural framework for dealing with uncertainty. Artificial Neural Networks and Type-2 Fuzzy Set: Elements of Soft Computing and Its Applications covers the fundamental concepts and the latest research on variants of Artificial Neural Networks (ANN), including scientific machine learning and Type-2 Fuzzy Set (T2FS). In addition, the book also covers different applications for solving real-world problems along with various examples and case studies. It may be noted that quite a bit of research has been done on ANN and Fuzzy Set theory/ Fuzzy logic. However, Artificial Neural Networks and Type-2 Fuzzy Set is the first book to cover the use of ANN and fuzzy set theory with regards to Type-2 Fuzzy Set in static and dynamic problems in one place. Artificial Neural Networks and Type-2 Fuzzy Sets are two of the most widely used computational intelligence techniques for solving complex problems in various domains. Both ANN and T2FS have unique characteristics that make them suitable for different types of problems. This book provides the reader with in-depth understanding of how to apply these computational intelligence techniques in various fields of science and engineering in general and static and dynamic problems in particular. Further, for validation purposes of the ANN and fuzzy models, the obtained solutions of each model in the book is compared with already existing solutions that have been obtained with numerical or analytical methods.

The UX Book

  • 3rd Edition
  • February 28, 2025
  • Rex Hartson + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 3 4 4 3 - 2
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 3 4 4 4 - 9
The UX Book: Agile Design for a Quality User Experience, Third Edition takes a practical, applied, hands-on approach to UX design that is based on the application of established and emerging best practices, principles, and proven methods to ensure a quality user

Fractional Modeling of Fluid Flow and Transport Phenomena

  • 1st Edition
  • February 3, 2025
  • Mohamed F. El-Amin
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 6 5 0 8 - 2
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 6 5 0 9 - 9
Fractional Modeling of Fluid Flow and Transport Phenomena focuses on mathematical and numerical aspects of fractional-order modeling in fluid flow and transport phenomena. The book covers fundamental concepts, advancements, and practical applications, including modeling developments, numerical solutions, and convergence analysis for both time and space fractional order models. Various types of flows are explored, such as single- and multi-phase flows in porous media, involving different fluid types like Newtonian, non-Newtonian, nanofluids, and ferrofluids. This book serves as a comprehensive reference on fractional-order modeling of fluid flow and transport phenomena, offering a single resource that is currently unavailable.Fractional-order modeling has gained traction in engineering and science, particularly in fluid dynamics and transport phenomena. However, its mathematical and numerical advancements have progressed relatively slowly compared to other aspects. Therefore, this book emphasizes the fractional-order modeling of fluid flow and transport phenomena to bridge this gap. Each chapter in the book delves into a specific topic closely related to the others, ensuring a cohesive and self-contained structure.

Soft Computing in Smart Manufacturing and Materials

  • 1st Edition
  • February 3, 2025
  • Sudan Jha + 4 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 9 9 2 7 - 8
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 9 9 2 8 - 5
Soft Computing in Smart Manufacturing and Materials explains the role of soft computing in the manufacturing industries. It presents the techniques, concepts and design principles behind smart soft computing, and describes how they can be applied in the development and manufacture of smart materials. It provides perspectives for design and commissioning of intelligent applications, including in health care, agriculture, and production assembly, and reviews the latest intelligent technologies and algorithms related to the methodologies of monitoring and mitigation of sustainable engineering.

Blockchain and Digital Twin for Smart Hospitals

  • 1st Edition
  • February 3, 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.