Skip to main content
Elsevier
View Cart
My account

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

    • Internet of Things: Architectures for Enhanced Living Environments

      • 1st Edition
      • Volume 133
      • February 7, 2024
      • Goncalo Marques
      • English
      • Hardback
        9 7 8 0 3 2 3 9 1 0 8 9 7
      • eBook
        9 7 8 0 3 2 3 9 1 0 9 0 3
      Internet of Things: Architectures for Enhanced Living Environments, Volume 133 presents interesting chapters on a variety of timely topics, including Explainable Artificial Intelligence for Enhanced Living Environments: A Study on User Perspective, Human behavioral anomaly pattern mining within an IoT environment: an exploratory study, Indoor Activity Localization Technologies for Assisted Living: Opportunities, Challenges, and Future Directions, Smart Indoor Air Quality Monitoring for Enhanced Living Environments and Ambient Assisted Living, Usability evaluation for the IoT use in Enhanced Living Environments, Roadmap to the elderly enhanced living and care environments: applications and challenges on the Internet of Things domain, and much more.

    • Machine Learning for Low-Latency Communications

      • 1st Edition
      • October 10, 2024
      • Yong Zhou + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 2 0 7 3 9
      • eBook
        9 7 8 0 4 4 3 2 2 0 7 4 6
      Machine Learning for Low-Latency Communications presents the principles and practice of various deep learning methodologies for mitigating three critical latency components: access latency, transmission latency, and processing latency. In particular, the book develops learning to estimate methods via algorithm unrolling and multiarmed bandit for reducing access latency by enlarging the number of concurrent transmissions with the same pilot length. Task-oriented learning to compress methods based on information bottleneck are given to reduce the transmission latency via avoiding unnecessary data transmission.Lastly, three learning to optimize methods for processing latency reduction are given which leverage graph neural networks, multi-agent reinforcement learning, and domain knowledge. Low-latency communications attracts considerable attention from both academia and industry, given its potential to support various emerging applications such as industry automation, autonomous vehicles, augmented reality and telesurgery. Despite the great promise, achieving low-latency communications is critically challenging. Supporting massive connectivity incurs long access latency, while transmitting high-volume data leads to substantial transmission latency.

    • 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.

    • Metaheuristic Optimization Algorithms

      • 1st Edition
      • May 5, 2024
      • Laith Abualigah
      • English
      • Paperback
        9 7 8 0 4 4 3 1 3 9 2 5 3
      • eBook
        9 7 8 0 4 4 3 1 3 9 2 6 0
      Metaheuristic Optimization Algorithms: Optimizers, Analysis, and Applications presents the most recent optimization algorithms and their applications across a wide range of scientific and engineering research fields. The book provides readers with a comprehensive overview of eighteen optimization algorithms to address this complex data, including Particle Swarm Optimization Algorithm, Arithmetic Optimization Algorithm, Whale Optimization Algorithm, and Marine Predators Algorithm, along with new and emerging methods such as Aquila Optimizer, Quantum Approximate Optimization Algorithm, Manta-Ray Foraging Optimization Algorithm, and Gradient Based Optimizer, among others. Each chapter includes an introduction to the modeling concepts used to create the algorithm that is followed by the mathematical and procedural structure of the algorithm, associated pseudocode, and real-world case studies.

    • Data Science, Analytics and Machine Learning with R

      • 1st Edition
      • January 23, 2023
      • Luiz Paulo Favero + 2 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 4 2 7 1 1
      • eBook
        9 7 8 0 3 2 3 8 5 9 2 3 3
      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.

    • Visualization, Visual Analytics and Virtual Reality in Medicine

      • 1st Edition
      • May 15, 2023
      • Bernhard Preim + 3 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 2 9 6 2 0
      • eBook
        9 7 8 0 1 2 8 2 3 1 0 6 7
      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.

    • Biomarkers in Cancer Detection and Monitoring of Therapeutics

      • 1st Edition
      • November 16, 2023
      • Ranbir Chander Sobti + 2 more
      • English
      • Paperback
        9 7 8 0 3 2 3 9 5 1 1 4 2
      • eBook
        9 7 8 0 3 2 3 9 5 1 1 5 9
      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.

    • Handbook of Truly Concurrent Process Algebra

      • 1st Edition
      • December 1, 2023
      • 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.

    • Multi-Criteria Decision-Making for Renewable Energy

      • 1st Edition
      • October 24, 2023
      • Mohamed Abdel-Basset + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 3 3 7 8 7
      • eBook
        9 7 8 0 4 4 3 1 3 3 8 9 3
      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.

    • Perspective of DNA Computing in Computer Science

      • 1st Edition
      • Volume 129
      • February 21, 2023
      • English
      • Hardback
        9 7 8 0 3 2 3 8 5 5 4 6 4
      • eBook
        9 7 8 0 3 2 3 8 5 5 4 7 1
      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.

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

Internet and web technology

Software

Theory and mathematics