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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

    • Computational Intelligence Methods for Sentiment Analysis in Natural Language Processing Applications

      • 1st Edition
      • January 19, 2024
      • D. Jude Hemanth
      • English
      • Paperback
        9 7 8 0 4 4 3 2 2 0 0 9 8
      • eBook
        9 7 8 0 4 4 3 2 2 0 1 0 4
      Computational Intelligence for Sentiment Analysis in Natural Language Processing Applications provides a solution to this problem through detailed technical coverage of AI-based Sentiment Analysis methods for various applications. The book's authors provide readers with an in-depth look at the challenges and associated solutions, including case studies and real-world scenarios from across the globe. Development of scientific and enterprise applications are covered that will aid computer scientists in building practical/real-world AI-based Sentiment Analysis systems. With the vast increase in Big Data, computational intelligence approaches have become a necessity for Natural Language Processing and Sentiment Analysis in a wide range of decision-making application areas.

    • Federated Learning

      • 1st Edition
      • February 9, 2024
      • Lam M. Nguyen + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 9 0 3 7 7
      • eBook
        9 7 8 0 4 4 3 1 9 0 3 8 4
      Federated Learning: Theory and Practi ce provides a holisti c treatment to federated learning as a distributed learning system with various forms of decentralized data and features. Part I of the book begins with a broad overview of opti mizati on fundamentals and modeling challenges, covering various aspects of communicati on effi ciency, theoretical convergence, and security. Part II featuresemerging challenges stemming from many socially driven concerns of federated learning as a future public machine learning service. Part III concludes the book with a wide array of industrial applicati ons of federated learning, as well as ethical considerations, showcasing its immense potential for driving innovation while safeguarding sensitive data.Federated Learning: Theory and Practi ce provides a comprehensive and accessible introducti on to federated learning which is suitable for researchers and students in academia, and industrial practitioners who seek to leverage the latest advance in machine learning for their entrepreneurial endeavors.

    • A Practical Introduction to Virtual Reality

      • 1st Edition
      • October 7, 2024
      • Lori Rebenitsch + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 4 0 3 6 5
      • eBook
        9 7 8 0 4 4 3 1 4 0 3 7 2
      A Practical Introduction to Virtual Reality: From Concepts to Executables is written for the undergraduate computer science student taking a course in virtual reality. This tutorial-based text is organized so that by the end of the semester students will have created their first VR game, including sound and various interactions. The materials are written from the position of the student and the student’s professor as opposed to the professional with prior graphics experience.Beginning with an introductory chapter covering the ten universal basics necessary for VR coding, the book moves on to such topics as putting together a VR set-up, creating Heads Up displays, building scene trees, learning how to import 3D models and animations, lighting and audio, and more, until by the end of the book, students will have a final project game ready for beta testing and publishing!

    • Empowering IoT with Big Data Analytics

      • 1st Edition
      • November 16, 2024
      • Mohamed Adel Serhani + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 1 6 4 0 4
      • eBook
        9 7 8 0 4 4 3 2 1 6 4 1 1
      Empowering IoT with Big Data Analytics provides comprehensive coverage of major topics, tools, and techniques related to empowering IoT with big data technologies and big data analytics solutions, thus allowing for better processing, analysis, protection, distribution, and visualization of data for the benefit of IoT applications and second, a better deployment of IoT applications on the ground. This book covers big data in the IoT era, its application domains, current state-of-the-art in big data and IoT technologies, standards, platforms, and solutions. This book provides a holistic view of the big data value-chain for IoT, including storage, processing, protection, distribution, analytics, and visualization.Big data is a multi-disciplinary topic involving handling intensive, continuous, and heterogeneous data retrieved from different sources including sensors, social media, and embedded systems. The emergence of Internet of Things (IoT) and its application to many domains has led to the generation of huge amounts of both structured and unstructured data often referred to as big data.

    • Data Science in the Medical Field

      • 1st Edition
      • September 25, 2024
      • Seifedine Kadry + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 4 0 2 8 7
      • eBook
        9 7 8 0 4 4 3 2 4 0 2 9 4
      Data science has the potential to influence and improve fundamental services such as the healthcare sector. This book recognizes this fact by analyzing the potential uses of data science in healthcare. Every human body produces 2 TB of data each day. This information covers brain activity, stress level, heart rate, blood sugar level, and many other things. More sophisticated technology, such as data science, allows clinicians and researchers to handle such a massive volume of data to track the health of patients. The book focuses on the potential and the tools of data science to identify the signs of illness at an extremely early stage.

    • Caspases as Molecular Targets for Cancer Therapy

      • 1st Edition
      • August 10, 2024
      • Ankur Vaidya
      • English
      • Paperback
        9 7 8 0 4 4 3 1 5 6 4 4 1
      • eBook
        9 7 8 0 4 4 3 1 5 6 4 5 8
      Caspases as Molecular Targets for Cancer Therapy discusses the recent developments on targeted therapies for cancer using caspases. It describes the selection of specific caspases for cancer therapy with the current standard of care and highlights numerous assay techniques for caspase activities. This book discusses topics such as mutations within apoptosis gene, inflammatory caspases, tumor suppression, and the different caspase types and their role in anticancer activity. In addition, it discusses caspase activity assay procedure and future perspectives. It is a valuable resource for researchers, students, and members of biomedical and medical fields who want to learn more about novel anticancer targeted therapies.

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

      • 1st Edition
      • April 18, 2024
      • Alma Y Alanis + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 2 3 4 1 9
      • eBook
        9 7 8 0 4 4 3 2 2 3 4 0 2
      Bio-Inspired Strategies for Modeling and Detection in Diabetes Mellitus Treatment focuses on bioinspired techniques such as modeling to generate control algorithms for the treatment of diabetes mellitus. The book addresses the identification of diabetes mellitus using a high-order recurrent neural network trained by an extended Kalman filter. The authors also describe the use of metaheuristic algorithms for the parametric identification of compartmental models of diabetes mellitus widely used in research works such as the Sorensen model and the Dallaman model. In addition, the book addresses the modeling of time series for the prediction of risk scenarios such as hyperglycaemia and hypoglycaemia using deep neural networks. The detection of diabetes mellitus in the early stages or when current diagnostic techniques cannot detect glucose intolerance or prediabetes is proposed, carried out by means of deep neural networks present in the literature. Readers will find leading-edge research in diabetes identification based on discrete high-order neural networks trained with an extended Kalman filter; parametric identification of compartmental models used to describe diabetes mellitus; modeling of data obtained by continuous glucose-monitoring sensors for the prediction of risk scenarios such as hyperglycaemia and hypoglycaemia; and screening for glucose intolerance using glucose-tolerance test data and deep neural networks. Application of the proposed approaches is illustrated via simulation and real-time implementations for modeling, prediction, and classification.

    • Computational Knowledge Vision

      • 1st Edition
      • August 19, 2024
      • Wenbo Zheng + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 1 6 1 9 0
      • eBook
        9 7 8 0 4 4 3 2 1 6 1 8 3
      Computational Knowledge Vision: The First Footprints presents a novel, advanced framework which combines structuralized knowledge and visual models. In advanced image and visual perception studies, a visual model's understanding and reasoning ability often determines whether it works well in complex scenarios. This book presents state-of-the-art mainstream vision models for visual perception. As computer vision is one of the key gateways to artificial intelligence and a significant component of modern intelligent systems, this book delves into computer vision systems that are highly specialized and very limited in their ability to do visual reasoning and causal inference.Questions naturally arise in this arena, including (1) How can human knowledge be incorporated with visual models? (2) How does human knowledge promote the performance of visual models? To address these problems, this book proposes a new framework for computer vision–computational knowledge vision.

    • API Design for C++

      • 2nd Edition
      • May 23, 2024
      • Martin Reddy
      • English
      • Paperback
        9 7 8 0 4 4 3 2 2 2 1 9 1
      • eBook
        9 7 8 0 4 4 3 2 2 2 2 0 7
      API Design for C++, Second Edition provides a comprehensive discussion of Application Programming Interface (API) development, from initial design through implementation, testing, documentation, release, versioning, maintenance, and deprecation. It is the only book that teaches the strategies of C++ API development, including interface design, versioning, scripting, and plug-in extensibility. Drawing from the author's experience on large scale, collaborative software projects, the text offers practical techniques of API design that produce robust code for the long-term. It presents patterns and practices that provide real value to individual developers as well as organizations.The Second Edition includes all new material fully updated for the latest versions of C++, including a new chapter on concurrency and multithreading, as well as a new chapter discussing how Objective C++ and C++ code can co-exist and how a C++ API can be accessed from Swift programs. In addition, it explores often overlooked issues, both technical and non-technical, contributing to successful design decisions that produce high quality, robust, and long-lived APIs. It focuses on various API styles and patterns that will allow you to produce elegant and durable libraries. A discussion on testing strategies concentrates on automated API testing techniques rather than attempting to include end-user application testing techniques such as GUI testing, system testing, or manual testing.

    • Computational Intelligence in Sustainable Computing and Optimization

      • 1st Edition
      • October 8, 2024
      • Balamurugan Balusamy + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 3 7 2 4 9
      • eBook
        9 7 8 0 4 4 3 2 3 7 2 5 6
      Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, artificial intelligence, and computer science to optimize environmental resourcesComputation... intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable.

Related subjects

Applications

Artificial intelligence

Business intelligence

Computer systems organization

Computer vision and pattern recognition

Computing milieux

Data

Graphics cad hci

Hardware and architecture

Information systems

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Software

Theory and mathematics