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Books in Mathematics

The Mathematics collection presents a range of foundational and advanced research content across applied and discrete mathematics, including fields such as Computational Mathematics; Differential Equations; Linear Algebra; Modelling & Simulation; Numerical Analysis; Probability & Statistics.

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21-30 of 2429 results in All results

Industrial Network Security

  • 3rd Edition
  • March 26, 2024
  • Eric D. Knapp
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 3 7 3 7 - 2
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 3 7 3 8 - 9
As the sophistication of cyber-attacks increases, understanding how to defend critical infrastructure systems—energy production, water, gas, and other vital systems—becomes more important, and heavily mandated. Industrial Network Security, Third Edition arms you with the knowledge you need to understand the vulnerabilities of these distributed supervisory and control systems.Author Eric Knapp examines the unique protocols and applications that are the foundation of Industrial Control Systems (ICS) and provides clear guidelines for their protection. This comprehensive reference gives you thorough understanding of the challenges facing critical infrastructures, new guidelines and security measures for infrastructure protection, knowledge of new and evolving security tools, and pointers on SCADA protocols and security implementation.

Data Fusion Techniques and Applications for Smart Healthcare

  • 1st Edition
  • March 12, 2024
  • Amit Kumar Singh + 1 more
  • English
  • Paperback
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  • eBook
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Data Fusion Techniques and Applications for Smart Healthcare covers cutting-edge research from both academia and industry, with a particular emphasis on recent advances in algorithms and applications that involve combining multiple sources of medical information. The book can be used as a reference for practicing engineers, scientists, and researchers, but it will also be useful for graduate students and practitioners from government and industry as well as healthcare technology professionals working on state-of-the-art information fusion solutions for healthcare applications.Medical data exists in several formats, from structured data and medical reports to 1D signals, 2D images, 3D volumes, or even higher dimensional data such as temporal 3D sequences. Healthcare experts can make auscultation reports in text format; electrocardiograms can be printed in time series format, X-rays saved as images; volume can be provided through angiography; temporal information by echocardiograms, and 4D information extracted through flow MRI.

Computation and Modeling for Fractional Order Systems

  • 1st Edition
  • February 20, 2024
  • Snehashish Chakraverty + 1 more
  • English
  • Paperback
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  • eBook
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Computation and Modeling for Fractional Order Systems provides readers with problem-solving techniques for obtaining exact and/or approximate solutions of governing equations arising in fractional dynamical systems presented using various analytical, semi-analytical, and numerical methods. Various analytical/semi-analytical/numerical methods are applied for solving real-life fractional order problems. The comprehensive descriptions of different recently developed fractional singular, non-singular, fractal-fractional, and discrete fractional operators, along with computationally efficient methods, are included for the reader to understand how these may be applied to real-world systems, and a wide variety of dynamical systems such as deterministic, stochastic, continuous, and discrete are addressed.Fractional calculus has gained increasing popularity and relevance over the last few decades, due to its well-established applications in various fields of science and engineering. It deals with the differential and integral operators with non-integral powers. Fractional differential equations are the pillar of various systems occurring in a wide range of science and engineering disciplines, namely physics, chemical engineering, mathematical biology, financial mathematics, structural mechanics, control theory, circuit analysis, and biomechanics, among others.

Artificial Intelligence and Machine Learning for Open-world Novelty

  • 1st Edition
  • Volume 134
  • February 19, 2024
  • Ganesh Chandra Deka + 1 more
  • English
  • Hardback
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  • eBook
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Artificial Intelligence and Machine Learning for Open-world Novelty, Volume 134 in the Advances in Computers series presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on AI and Machine Learning for Real-world problems, Graph Neural Network for learning complex problems, Adaptive Software platform architecture for Aerial Vehicle Safety Levels in real-world applications, OODA Loop for Learning Open-world Novelty Problems, Privacy-Aware Crowd Counting Methods for Real-World Environment, AI and Machine Learning for 3D Computer Vision Applications in Open-world, and PIM Hardware accelerators for real-world problems.Other sections cover Irregular Situations in Real-World Intelligent Systems, Offline Reinforcement Learning Methods for Real-world Problems, Addressing Uncertainty Challenges for Autonomous Driving in Real-World Environments, and more.

Modeling and Analysis of Longitudinal Data

  • 1st Edition
  • Volume 50
  • February 7, 2024
  • Arni S.R. Srinivasa Rao + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 3 - 1 3 6 5 1 - 1
  • eBook
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Longitudinal Data Analysis, Volume 50 in the Handbook of Statistics series covers how data consists of a series of repeated observations of the same subjects over an extended time frame and is thus useful for measuring change. Such studies and the data arise in a variety of fields, such as health sciences, genomic studies, experimental physics, sociology, sports and student enrollment in universities. For example, in health studies, intra-subject correlation of responses must be accounted for, covariates vary with time, and bias can arise if patients drop out of the study.

Actuaries' Survival Guide

  • 3rd Edition
  • February 2, 2024
  • Ping Wang + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 5 4 9 7 - 3
  • eBook
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Actuaries' Survival Guide: Navigating the Exams as Applications of Data Science, Third Edition explains what actuaries are, what they do, and where they do it. The book describes exciting combinations of ideas, techniques, and skills involved in their day-to-day work. This edition has been updated to reflect the rise of social networking and the internet, the progress toward a global knowledge-based economy, and the global expansion of the actuarial field that has occurred since the prior edition.

Applying Computational Intelligence for Social Good

  • 1st Edition
  • Volume 132
  • January 14, 2024
  • Preetha Evangeline David + 1 more
  • English
  • Hardback
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  • eBook
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Applying Computational Intelligence for Social Good: Track, Understand and Build a Better World, Volume 132 presents views on how Computational Intelligent and ICT technologies can be applied to ease or solve social problems by sharing examples of research results from studies of social anxiety, environmental issues, mobility of the disabled, and problems in social safety. Sample chapters in this release include Why is implementing Computational Intelligence for social good so challenging? Principles and its Application, Smart crisis management system for road accidents using Geo-Spacial Machine Learning Techniques, Residential Energy Management System (REMS) Using Machine Learning, Text-Based Personality Prediction using XLNet, and much more.

Introductory Differential Equations

  • 6th Edition
  • December 21, 2023
  • Martha L. Abell + 1 more
  • English
  • Paperback
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  • eBook
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Introductory Differential Equations, Sixth Edition provides the foundations to assist students in learning not only how to read and understand differential equations, but also how to read technical material in more advanced texts as they progress through their studies. The book's accessible explanations and many robust sample problems are appropriate for a first semester course in introductory ordinary differential equations (including Laplace transforms), for a second course in Fourier series and boundary value problems, and for students with no background on the subject.

Handbook of Truly Concurrent Process Algebra

  • 1st Edition
  • December 1, 2023
  • Yong Wang
  • English
  • Paperback
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  • eBook
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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.Patterns 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.

Fundamentals of Data Science

  • 1st Edition
  • November 17, 2023
  • Jugal K. Kalita + 2 more
  • English
  • Paperback
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  • eBook
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Fundamentals of Data Science: Theory and Practice presents basic and advanced concepts in data science along with real-life applications. The book provides students, researchers and professionals at different levels a good understanding of the concepts of data science, machine learning, data mining and analytics. Users will find the authors’ research experiences and achievements in data science applications, along with in-depth discussions on topics that are essential for data science projects, including pre-processing, that is carried out before applying predictive and descriptive data analysis tasks and proximity measures for numeric, categorical and mixed-type data. The book's authors include a systematic presentation of many predictive and descriptive learning algorithms, including recent developments that have successfully handled large datasets with high accuracy. In addition, a number of descriptive learning tasks are included.

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Mathematics and applied mathematics

Statistics and probability