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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 5326 results in All results

Applied Graph Data Science

  • 1st Edition
  • February 1, 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 gives readers both the conceptual foundations and technical methods for applying these powerful techniques.

Computational Intelligence for Genomics Data

  • 1st Edition
  • February 1, 2025
  • 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 a comprehensive 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. The book includes the design, algorithms and simulations on MATLAB and Python for the larger prediction models. It also explores the possibilities of software and hardware-based applications and devices for genomic disease prediction models by providing case studies and multiple examples. This book will be a helpful resource for researchers, graduate students and professional engineers who are developing new data analysis techniques and prediction models for the analysis of genomics data.

Intelligent and Soft Computing

  • 1st Edition
  • February 1, 2025
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 3 0 0 9 0 - 5
  • eBook
    9 7 8 - 0 - 4 4 3 - 3 0 0 9 1 - 2
Intelligent and Soft Computing: Techniques and Applications brings together the most recent discoveries and technological advancements in both intelligent and soft computing. It illustrates the synergistic effect of cutting-edge developments in all areas of both fields to build intelligent software systems to solve a multitude of problems spanning both areas. The book offers an introduction to artificial intelligence as well as fuzzy logic concepts, systems, and methods. Additional sections focus on AI tools and applications, search and data mining, reasoning and evolution, as well as nature-inspired computing techniques. Applications and case studies are included in all chapters. Researchers, graduate students, and professionals working in these domains will find this to be a timely reference that provides insight on current and future developments of this emerging domain for decision support, management, information technology, and business applications.

Encyclopedia of Bioinformatics and Computational Biology

  • 2nd Edition
  • January 16, 2025
  • Shoba Ranganathan + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 3 2 3 - 9 5 5 0 2 - 7
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 5 5 0 3 - 4
Bioinformatics and Computational Biology (BCB) combine elements of computer science, information technology, mathematics, statistics, and biotechnology, providing the methodology and in silico solutions to mine biological data and processes, for knowledge discovery.In the era of molecular diagnostics, targeted drug design and Big Data for personalized medicine, computational methods for data analysis are essential tools for biochemistry, biology, biotechnology, pharmacology, biomedical and computer science, as well mathematics and statistics. New areas are emerging, and relatively isolated fields are becoming current hot research areas in BCB, such as Quantitative Biology, Computational Vaccinology, Epidemiology and Infection Diffusion, Synthetic Biology and Phenomics. The role of BCB in characterizing SARS-CoV-2 variants and facing the COVID-19 pandemic is just one example of how these tools can find us better prepared for such future events.This Encyclopedia comprises three sections, covering Theory, Topics and Applications. The theoretical methodology underpinning BCB are described in the Theory section; Topics covers traditional areas such as phylogeny, as well as more recent areas such as translational bioinformatics, cheminformatics and environmental informatics; Applications provides guidance for commonly asked "how to" questions.​​​​​​​Navigating the maze of confusing jargon and the plethora of software tools is often confronting for students and researchers alike. This comprehensive and unique resource provides up-to-date theory and application content to address molecular data analysis requirements, with precise definition of terminology, and lucid explanations by field experts.

Computer-Aided Diagnosis (CAD) Tools and Applications for 3D Medical Imaging

  • 1st Edition
  • Volume 136
  • January 10, 2025
  • Abhishek Gupta + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 3 2 3 - 9 8 8 5 7 - 5
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 8 8 5 8 - 2
Computer-Aided Diagnosis (CAD) Tools and Applications for 3D Medical Imaging, Volume 136 of the Advances in Computers series, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. Published since 1960, this series provides contributors with a medium to explore their subjects in greater depth and breadth than typical journal articles. This volume discusses various aspects of Computer-Aided Diagnosis.

RISC-V Microprocessor System-On-Chip Design

  • 1st Edition
  • January 1, 2025
  • David Harris + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 9 9 4 9 8 - 9
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 9 4 9 9 - 6
RISC-V Microprocessor System-On-Chip Design is intended for a graduate or undergraduate course in microprocessor design. The reader will learn to design and optimize microprocessors and use them in a system-on-chip, applying contemporary design and verification tools. Much of the book describes detailed designs and tradeoffs for the functional blocks in and around a processor. RISC-V Microprocessor System-On-Chip Design is written to be accessible to an advanced undergraduate audience with limited background and will explain concepts from operating systems, VLSI, and memory systems as necessary. High school mathematics is sufficient preparation for most of the book, although the floating point and division chapters will be primarily of interest to those with a curiosity about computer arithmetic. Like Harris and Harris’s Digital Design and Computer Architecture textbooks, this book will appeal to students with easy-to-read and complete explanations, sidebars, and occasional humor and cartoons. The book comes with an open-source implementation and will include end-of-chapter problems to extend the RISC-V processor in various ways. Ancilliary materials include a GitHub repository with complete open-source SystemVerilog code, validation code in C and assembly language, and code for benchmarking and booting Linux.

Programming Language Pragmatics

  • 5th Edition
  • January 1, 2025
  • Michael Scott + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 9 9 9 6 6 - 3
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 8 4 2 3 - 2
Programming Language Pragmatics is the most comprehensive programming language textbook available today, with nearly 1000 pages of content in the book, plus hundreds more pages of reference materials and ancillaries online. Michael Scott takes theperspective that language design and language implementation are tightly interconnected, and that neither can be fully understood in isolation. In an approachable, readable style, he discusses more than 50 languages in the context of understanding how code isinterpreted or compiled, providing an organizational framework for learning new languages, regardless of platform. This edition has been thoroughly updated to cover the most recent developments in programming language design and provides both a solid understanding of the most important issues driving software development today

Computer Architecture

  • 7th Edition
  • January 1, 2025
  • John L. Hennessy + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 5 4 0 6 - 5
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 5 4 0 7 - 2
Computer Architecture: A Quantitative Approach, has been considered essential reading by instructors, students and practitioners of computer design for nearly 30 years. The seventh edition of this classic textbook from John Hennessy and David Patterson, w

Multifunctional Nanoparticles for Cancer Therapeutic Applications

  • 1st Edition
  • January 1, 2025
  • Sabu Thomas + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 1 6 8 6 - 2
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 1 6 8 7 - 9
Multifunctional Nanoparticles for Cancer Therapeutic Applications: Design and Challenges describes the use of multifunctional nanoparticles for cancer treatment, highlighting their toxicological evaluation and opportunities for prospective clinical therapeutic development. Besides significant research and clinical success, cancer nanomedicines currently face challenges towards clinical translation and this book aims to shed a light on complex issues. Sections discuss synthetic strategies and functionalization of nanoparticles, routes of administration, biological barriers and how to overcome them, nanoparticles for cancer treatment available in the market, active targeting approach, non-viral gene-based therapy with multifunctional nanoparticles, and the use of nanoparticles in immunotherapy.In addition, the book covers image guided cancer therapy, stem cell targeted therapy, and toxicity. This is a valuable resource for cancer researchers, oncologists, clinicians, and members of the biomedical field who need to understand the potential of multifunctional nanoparticles in cancer drug delivery, diagnosis, and treatment.

Agent-Based Models with MATLAB

  • 1st Edition
  • January 1, 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
As the world becomes more complicated and linked, many of our research questions can no longer be answered using straightforward models. Agent-Based Models with MATLAB introduces one of the most important methodologies for complex systems modeling, called Agent-Based Modeling (ABM), using 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. Observing the implementation of a particular approach through code can be helpful for readers, even those with strong mathematical abilities, as it eliminates ambiguities and uncertainties, making the material easier to grasp and communicate. The book comes with a large amount of software code accompanying 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. For many readers, a more feasible goal is to grasp the concepts of these models through programming instead of mathematical formulations. Agent-Based Models with MATLAB enables computer scientists, mathematicians, researchers and engineers to apply ABM in a wide range of research and engineering applications. The book gradually advances from basic to more advanced methods, while reinforcing understanding of complex systems through practical, hands-on applications of various computational models.