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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

    • Professional Penetration Testing

      • 3rd Edition
      • January 21, 2025
      • Thomas Wilhelm
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 4 7 8 8
      • eBook
        9 7 8 0 4 4 3 2 6 4 7 9 5
      Professional Penetration Testing: Creating and Learning in a Hacking Lab, Third Edition walks the reader through the entire process of setting up and running a pen test lab. Penetration testing—the act of testing a computer network to find security vulnerabilities before they are maliciously exploited—is a crucial component of information security in any organization. Chapters cover planning, metrics, and methodologies, the details of running a pen test, including identifying and verifying vulnerabilities, and archiving, reporting and management practices. The material presented will be useful to beginners through advanced practitioners.Here, author Thomas Wilhelm has delivered penetration testing training to countless security professionals, and now through the pages of this book, the reader can benefit from his years of experience as a professional penetration tester and educator. After reading this book, the reader will be able to create a personal penetration test lab that can deal with real-world vulnerability scenarios. "...this is a detailed and thorough examination of both the technicalities and the business of pen-testing, and an excellent starting point for anyone getting into the field." –Network Security

    • Computational Intelligence for Genomics Data

      • 1st Edition
      • January 21, 2025
      • Babita Pandey + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 0 0 8 0 6
      • eBook
        9 7 8 0 4 4 3 3 0 0 8 1 3
      Computational Intelligence for Genomics Data presents an overview of machine learning and deep learning techniques being developed for the analysis of genomic data and the development of disease prediction models. The book focuses on machine and deep learning techniques applied to dimensionality reduction, feature extraction, and expressive gene selection. It includes designs, algorithms, and simulations on MATLAB and Python for larger prediction models and explores the possibilities of software and hardware-based applications and devices for genomic disease prediction. With the inclusion of important case studies and examples, this book will be a helpful resource for researchers, graduate students, and professional engineers.

    • Applied Graph Data Science

      • 1st Edition
      • January 27, 2025
      • Pethuru Raj + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 6 5 4 3
      • eBook
        9 7 8 0 4 4 3 2 9 6 5 5 0
      Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with its practical research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques.

    • ChatGPT

      • 1st Edition
      • April 9, 2025
      • Ge Cheng
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 4 3 6 7
      • eBook
        9 7 8 0 4 4 3 2 7 4 3 7 4
      ChatGPT: Principles and Architecture bridges the knowledge gap between theoretical AI concepts and their practical applications. It equips industry professionals and researchers with a deeper understanding of large language models, enabling them to effectively leverage these technologies in their respective fields. In addition, it tackles the complexity of understanding large language models and their practical applications by demystifying underlying technologies and strategies used in developing ChatGPT and similar models. By combining theoretical knowledge with real-world examples, the book enables readers to grasp the nuances of AI technologies, thus paving the way for innovative applications and solutions in their professional domains.Sections focus on the principles, architecture, pretraining, transfer learning, and middleware programming techniques of ChatGPT, providing a useful resource for the research and academic communities. It is ideal for the needs of industry professionals, researchers, and students in the field of AI and computer science who face daily challenges in understanding and implementing complex large language model technologies.

    • Agent-Based Models with MATLAB

      • 1st Edition
      • January 20, 2025
      • Erik Cuevas + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 4 0 0 4 1
      • eBook
        9 7 8 0 4 4 3 2 4 0 0 5 8
      Agent-Based Models with MATLAB introduces Agent-Based Modeling (ABM), one of the most important methodologies for complex systems modeling. The book explores computational implementations and accompanying MATLAB software code as a means of inspiring readers to apply agent-based models to solve a diverse range of problems. It comes with a large amount of software code that accompanies the main text, and the modeling systems described in the book are implemented using MATLAB as the programming language. Despite the heavy mathematical components of Agent-Based Models and complex systems, it is possible to utilize these models without in-depth understanding of their mathematical fundamentals.This book enables computer scientists, mathematicians, researchers, and engineers to apply ABM in a wide range of research and engineering applications. It gradually advances from basic to more advanced methods while reinforcing complex systems through practical, hands-on applications of various computational models.

    • Federated Learning in Metaverse Healthcare

      • 1st Edition
      • September 19, 2025
      • Shubham Mahajan + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 7 8 9 5
      • eBook
        9 7 8 0 4 4 3 3 3 7 9 0 1
      Federated Learning in Metaverse Healthcare: Personalized Medicine and Wellness explores the integration of the metaverse with healthcare, offering immersive experiences and personalized care. The book introduces federated learning, emphasizing its advantages over traditional centralized machine learning in healthcare. It provides a historical context and discusses the technological advancements that led to the emergence of metaverse healthcare. Privacy-preserving methods crucial for protecting sensitive healthcare data within federated learning environments are also examined, underscoring the importance of secure communication protocols. Other important points include the transformation of healthcare delivery through virtual environments, remote consultations, and immersive experiences.The role of telemedicine in facilitating remote diagnostics and consultations via virtual platforms, and the applications of augmented reality wearables for real-time health monitoring and wellness tracking are detailed. Additionally, the book discusses federated learning's ability to deliver personalized treatment plans tailored to individual patient needs, its role in predictive modeling for disease risks and prevention, as well as virtual health coaches offering personalized guidance for wellness management. The challenges and ethical dilemmas of metaverse healthcare and federated learning, along with potential solutions, are also considered.

    • Artificial Neural Networks and Type-2 Fuzzy Set

      • 1st Edition
      • February 19, 2025
      • Snehashish Chakraverty + 2 more
      • 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.

    • Soft Computing in Smart Manufacturing and Materials

      • 1st Edition
      • January 20, 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.

    • Advances in Computational Methods and Modeling for Science and Engineering

      • 1st Edition
      • February 4, 2025
      • Hari M Srivastava + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 0 0 1 2 7
      • eBook
        9 7 8 0 4 4 3 3 0 0 1 3 4
      Advances in Computational Methods and Modelling in Science and Engineering explores the application of computational techniques and modeling approaches in science and engineering, providing practical knowledge and skills for tackling complex problems using numerical simulations and data analysis. This book addresses the need for a cohesive and up-to-date resource in the rapidly evolving field of computational methods. It consolidates diverse topics, serving as a one-stop guide for individuals seeking a comprehensive understanding of the subject matter. Sections focus on mathematical techniques that provide global solutions for models arising in engineering and scientific research applications by considering their long-term benefits.The mathematical treatment of these models is very helpful in understanding these models and their real-world applications. The methods and modeling techniques presented are useful for mathematicians, engineers, scientists, and researchers working on the mathematical treatment of models in a wide range of applications, including disciplines such as engineering, physics, chemistry, computer science, and applied mathematics.

    • Digital Twin and Blockchain for Sensor Networks in Smart Cities

      • 1st Edition
      • February 25, 2025
      • Tuan Anh Nguyen
      • English
      • Paperback
        9 7 8 0 4 4 3 3 0 0 7 6 9
      • eBook
        9 7 8 0 4 4 3 3 0 0 7 7 6
      Digital twin, blackchain, and wireless sensor networks can work together to improve services in the smart city. Big data derived from wireless sensor networks can be integrated to accommodate the exchange of real-time data between citizens, governments, and organizations. Blockchain can provide high security for large-scale communications and transactions between many stakeholders. Digital twin uses physical models and historical data to integrate big information under multidiscipline, multiphysical quantities, multiscale, and multiprobability conditions.Digital Twin and Blockchain for Sensor Networks in Smart Cities explores how digital twin and blockchain can be optimized to improve services. This book is divided into three parts. Part 1 focuses on the fundamental concepts of blockchain and digital twin for sensor networks in the smart cities, while Part 2 describes their applications for managing the regular operations and services. Part 3 deals with their applications for safe cities.

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