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Morgan Kaufmann

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

    • 1st book:metaData.edition
    • Alma Y Alanis contributors.plusContributors
    • publicationLanguages:en
    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 Intelligence and Blockchain in Complex Systems

    System Security and Interdisciplinary Applications
    • 1st book:metaData.edition
    • Fadi Al-Turjman
    • publicationLanguages:en
    Computational Intelligence and Blockchain in Complex Systems: System Security and Interdisciplinary Applications provides readers with a guide to understanding the dynamics of AI, machine learning, and computational intelligence in blockchain, and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications. This book examines the role of computational intelligence and machine learning in the development of algorithms to deploy blockchain technology across a number of applications, including healthcare, insurance, smart grid, smart contracts, digital currency, precision agriculture, and supply chain. The authors cover the unique and developing intersection between cyber security and blockchain in modern networks, as well as in-depth studies on cybersecurity challenges and multidisciplinary methods in modern blockchain networks. Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods, especially the complex algorithms involved in blockchain security aspects for hashing, coding, and decoding. This book also provides readers with the most in-depth technical guide to the intersection of computational intelligence and blockchain, two of the most important technologies for the development of next-generation complex systems

  • Object-Oriented Analysis and Design for Information Systems

    Modeling with BPMN, OCL, IFML, and Python
    • 2nd book:metaData.edition
    • Raul Sidnei Wazlawick
    • publicationLanguages:en
    Object-Oriented Analysis and Design for Information Systems, Second Edition clearly explains real object-oriented programming in practice. Expert author Raul Sidnei Wazlawick explains concepts such as object responsibility, visibility, and the real need for delegation in detail. The object-oriented code generated by using these concepts in a systematic way is concise, organized and reusable.The patterns and solutions presented in this book are based in research and industrial applications. You will come away with clarity regarding processes and use cases and a clear understanding of how to expand a use case. Wazlawick clearly explains how to build meaningful sequence diagrams. Object-Oriented Analysis and Design for Information Systems illustrates how and why building a class model is not just placing classes into a diagram. You will learn the necessary organizational patterns so that your software architecture will be maintainable. The Second Edition includes all new content shifting the focus of the book to agile software development, including Scrum software project management, BPMN diagrams, user stories, and Python code examples.

  • Many-Sorted Algebras for Deep Learning and Quantum Technology

    • 1st book:metaData.edition
    • Charles R. Giardina
    • publicationLanguages:en
    Many-Sorted Algebras for Deep Learning and Quantum Technology presents a precise and rigorousdescription of basic concepts in quantum technologies and how they relate to deep learning and quantum theory. Current merging of quantum theory and deep learning techniques provides the need for a source that gives readers insights into the algebraic underpinnings of these disciplines. Although analytical, topological, probabilistic, as well as geometrical concepts are employed in many of these areas, algebra exhibits the principal thread; hence, this thread is exposed using many-sorted algebras. This book includes hundreds of well-designed examples that illustrate the intriguing concepts in quantum systems. Along with these examples are numerous visual displays. In particular, the polyadic graph shows the types or sorts of objects used in quantum or deep learning. It also illustrates all the inter and intra-sort operations needed in describing algebras. In brief, it provides the closure conditions. Throughout the book, all laws or equational identities needed in specifying an algebraic structure are precisely described.

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

    • 1st book:metaData.edition
    • D. Jude Hemanth
    • publicationLanguages:en
    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.

  • Human-Computer Interaction

    An Empirical Research Perspective
    • 2nd book:metaData.edition
    • I. Scott MacKenzie
    • publicationLanguages:en
    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 book:metaData.edition
    • Saïd Abbas contributors.plusContributors
    • publicationLanguages:en
    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 book:metaData.edition
    • Vincent Granville
    • publicationLanguages:en
    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 book:metaData.edition
    • Yong Wang
    • publicationLanguages:en
    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 book:metaData.edition
    • Jason D. Bakos
    • publicationLanguages:en
    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.

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