Skip to main content

Morgan Kaufmann

  • Human-Computer Interaction

    An Empirical Research Perspective
    • 2nd Edition
    • I. Scott MacKenzie
    • English
    Human-Computer Interaction: An Empirical Research Perspective is the definitive guide to empirical research in HCI. The book begins with foundational topics, including historical context, the human factor, interaction elements, and the fundamentals of science and research. From there, the book progresses to the methods for conducting an experiment to evaluate a new computer interface or interaction technique. There are detailed discussions and how-to analyses on models of interaction, focusing on descriptive models and predictive models. Writing and publishing a research paper is explored with helpful tips for success.Throughout the book, readers will find hands-on exercises, checklists, and real-world examples. This is a must-have, comprehensive guide to empirical and experimental research in HCI – an essential addition to your HCI library.
  • Fractional Difference, Differential Equations, and Inclusions

    Analysis and Stability
    • 1st Edition
    • Saïd Abbas + 3 more
    • English
    Fractional Difference, Differential Equations, and Inclusions: Analysis and Stability is devoted to the existence and stability (Ulam-Hyers-Rassias stability and asymptotic stability) of solutions for several classes of functional fractional difference equations and inclusions. Covered equations include delay effects of finite, infinite, or state-dependent nature, and tools used to establish the existence results for the proposed problems include fixed point theorems, densifiability techniques, monotone iterative technique, notions of Ulam stability, attractivity and the measure of non-compactness, as well as the measure of weak noncompactness. The tools of fractional calculus are found to be of great utility in improving the mathematical modeling of many natural phenomena and processes occurring in the areas of engineering, social, natural, and biomedical sciences. All abstract results in the book are illustrated by examples in applied mathematics, engineering, biomedical, and other applied sciences.
  • Synthetic Data and Generative AI

    • 1st Edition
    • Vincent Granville
    • English
    Synthetic Data and Generative AI covers the foundations of machine learning with modern approaches to solving complex problems and the systematic generation and use of synthetic data. Emphasis is on scalability, automation, testing, optimizing, and interpretability (explainable AI). For instance, regression techniques – including logistic and Lasso – are presented as a single method without using advanced linear algebra. Confidence regions and prediction intervals are built using parametric bootstrap without statistical models or probability distributions. Models (including generative models and mixtures) are mostly used to create rich synthetic data to test and benchmark various methods.
  • Handbook of Truly Concurrent Process Algebra

    • 1st Edition
    • 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.
  • Embedded Systems

    ARM Programming and Optimization
    • 2nd Edition
    • Jason D. Bakos
    • English
    Embedded Systems: ARM Programming and Optimization, Second Edition combines an exploration of the ARM architecture with an examination of the facilities offered by the Linux operating system to explain how various features of program design can influence processor performance. The book demonstrates methods by which a programmer can optimize program code in a way that does not impact its behavior but instead improves its performance. Several applications, including image transformations, fractal generation, image convolution, computer vision tasks, and now machine learning are used to describe and demonstrate these methods. From this, the reader will gain insight into computer architecture and application design, as well as practical knowledge in embedded software design for modern embedded systems. The second edition has been expanded to include more topics of interest to upper level undergraduate courses in embedded systems.
  • Embedded System Design

    Methodologies and Issues
    • 1st Edition
    • Lawrence J. Henschen + 1 more
    • English
    Embedded Systems Design: Methodologies and Issues presents methodologies for designing these systems and discusses major issues, both present and future, that designers must consider in bringing products with embedded processing to market. The book starts from the first step after product proposal (behavioral modeling) and goes through the steps for modeling internal operations. Specific areas of focus include methods for designing safe, reliable, and robust embedded systems. Sections cover selection of processors and related hardware as well as issues involved in designing related software. Finally, the book present issues that will occur in systems designed for the Internet of Things. This book is for junior/senior/MS students in computer science, computer engineering, and electrical engineering who intend to take jobs in industry designing and implementing embedded systems and Internet of Things applications.
  • Formal Verification

    An Essential Toolkit for Modern VLSI Design
    • 2nd Edition
    • Erik Seligman + 2 more
    • English
    Formal Verification: An Essential Toolkit for Modern VLSI Design, Second Edition presents practical approaches for design and validation, with hands-on advice to help working engineers integrate these techniques into their work. Formal Verification (FV) enables a designer to directly analyze and mathematically explore the quality or other aspects of a Register Transfer Level (RTL) design without using simulations. This can reduce time spent validating designs and more quickly reach a final design for manufacturing. Building on a basic knowledge of SystemVerilog, this book demystifies FV and presents the practical applications that are bringing it into mainstream design and validation processes. Every chapter in the second edition has been updated to reflect evolving FV practices and advanced techniques. In addition, a new chapter, Formal Signoff on Real Projects, provides guidelines for implementing signoff quality FV, completely replacing some simulation tasks with significantly more productive FV methods. After reading this book, readers will be prepared to introduce FV in their organization to effectively deploy FV techniques that increase design and validation productivity.
  • Machine Learning

    A Constraint-Based Approach
    • 2nd Edition
    • Marco Gori + 2 more
    • English
    Machine Learning: A Constraint-Based Approach, Second Edition provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that include neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. It draws a path towards deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, such as in fuzzy systems. Special attention is given to deep learning, which nicely fits the constrained-based approach followed in this book.The book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, including many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included.
  • Network Algorithmics

    An Interdisciplinary Approach to Designing Fast Networked Devices
    • 2nd Edition
    • George Varghese + 1 more
    • English
    Network Algorithmics: An Interdisciplinary Approach to Designing Fast Networked Devices, Second Edition takes an interdisciplinary approach to applying principles for efficient implementation of network devices, offering solutions to the problem of network implementation bottlenecks. In designing a network device, there are dozens of decisions that affect the speed with which it will perform – sometimes for better, but sometimes for worse. The book provides a complete and coherent methodology for maximizing speed while meeting network design goals. The book is uniquely focused on the seamless integration of data structures, algorithms, operating systems and hardware/software co-designs for high-performance routers/switches and network end systems. Thoroughly updated based on courses taught by the authors over the past decade, the book lays out the bottlenecks most often encountered at four disparate levels of implementation: protocol, OS, hardware and architecture. It then develops fifteen principles key to breaking these bottlenecks, systematically applying them to bottlenecks found in end-nodes, interconnect devices and specialty functions located along the network. Later sections discuss the inherent challenges of modern cloud computing and data center networking.
  • AI Computing Systems

    An Application Driven Perspective
    • 1st Edition
    • Yunji Chen + 5 more
    • English
    AI Computing Systems: An Application Driven Perspective adopts the principle of "application-driven, full-stack penetration" and uses the specific intelligent application of "image style migration" to provide students with a sound starting place to learn. This approach enables readers to obtain a full view of the AI computing system. A complete intelligent computing system involves many aspects such as processing chip, system structure, programming environment, software, etc., making it a difficult topic to master in a short time.