Condition Monitoring Using Computational Intelligence Methods

These two books cover the most significant recent advances in oncological molecular imaging, from methods and preclinical research to clinical practice. The first book is divided into two sections. The first section focuses on standardized and emerging technologies, as well as probe designs for various imaging modalities, including advanced X-ray imaging, CT, MRI, SPECT, total body PET, ultrasound, optical imaging, optoacoustic imaging, and probes for these modalities. The section also covers artificial intelligence in radiomics. The second section focuses on preclinical applications, including advanced microscopy in animal imaging. The second book presents various clinical applications of molecular imaging and related imaging features. The first section of the second book discusses the crucial, emerging role of molecular imaging in planning and monitoring oncological therapies and future challenges and prospects in multimodality imaging. The second section discusses radiotherapy appro

This 5th edition of this popular graduate textbook, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. It includes numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The R package 'astsa' has had major updates and the text will reflect those updates. In general, the graphics have been improved. New topics include random number generation, modeling and fitting predator-prey interactions, more emphasis on structural models, testing for linearity, discussion of EM algorithm is more extensive, Bayesian analysis of state space models and MCMC is more extensive (including new scripts in astsa), particle methods are introduced, stochastic volatility coverage is expanded, changepoint detection is introduced (new topic).The

This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches.The book's authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents

Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers. The contributed chapters cover the use of Bayesian probabilistic modelling in a diverse set of applications, including improving pointing-based interfaces; efficient text entry using modern language models; advanced interface design using cutting-edge techniques in Bayesia

Understand multiphase flows using multidisciplinary knowledge in physical principles, modelling theories, and engineering practices. This essential text methodically introduces the important concepts, governing mechanisms, and state-of-the-art theories, using numerous real-world applications, examples, and problems. Covers all major types of multiphase flows, including gas-solid, gas-liquid (sprays or bubbling), liquid-solid, and gas-solid-liquid flows. Introduces the volume-time-averaged transport theorems and associated Lagrangian-trajectory modelling and Eulerian-Eulerian multi-fluid modelling. Explains typical computational techniques, measurement methods and four representative subjects of multiphase flow systems. Suitable as a reference for engineering students, researchers, and practitioners, this text explores and applies fundamental theories to the analysis of system performance using a case-based approach.

Single Molecule Science (SMS) has emerged from developing, using and combining technologies such as super-resolution microscopy, atomic force microscopy, and optical and magnetic tweezers, alongside sophisticated computational and modelling techniques. This comprehensive, edited volume brings together authoritative overviews of these methods from a biological perspective, and highlights how they can be used to observe and track individual molecules and monitor molecular interactions in living cells. Pioneers in this fast-moving field cover topics such as single molecule optical maps, nanomachines, and protein folding and dynamics. A particular emphasis is also given to mapping DNA molecules for diagnostic purposes, and the study of gene expression. With numerous illustrations, this book reveals how SMS has presented us with a new way of understanding life processes. A must-have for researchers and graduate students, as well as those working in industry, primarily in the areas of biophy

Tackling structural geology problems today requires a quantitative understanding of the underlying physical principles, and the ability to apply mathematical models to deformation processes within the Earth. Accessible yet rigorous, this unique textbook demonstrates how to approach structural geology quantitatively using calculus and mechanics, and prepares students to interface with professional geophysicists and engineers who appreciate and utilize the same tools and computational methods to solve multidisciplinary problems. Clearly explained methods are used throughout the book to quantify field data, set up mathematical models for the formation of structures, and compare model results to field observations. An extensive online package of coordinated laboratory exercises enables students to consolidate their learning and put it into practice by analyzing structural data and building insightful models. Designed for single-semester undergraduate courses, this pioneering text prepares

With the most comprehensive and up-to-date overview of structure-based drug discovery and using experimental and computational approaches, this book covers principles, methods, applications, and emerg

Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricu

This book provides a self-contained introduction to the simulation of flow and transport in porous media, written by a developer of numerical methods. The reader will learn how to implement reservoir simulation models and computational algorithms in a robust and efficient manner. The book contains a large number of numerical examples, all fully equipped with online code and data, allowing the reader to reproduce results, and use them as a starting point for their own work. All of the examples in the book are based on the MATLAB Reservoir Simulation Toolbox (MRST), an open-source toolbox popular popularity in both academic institutions and the petroleum industry. The book can also be seen as a user guide to the MRST software. It will prove invaluable for researchers, professionals and advanced students using reservoir simulation methods. This title is also available as Open Access on Cambridge Core.

The increased and widespread availability of large network data resources in recent years has resulted in a growing need for effective methods for their analysis. The challenge is to detect patterns that provide a better understanding of the data. However, this is not a straightforward task because of the size of the data sets and the computer power required for the analysis. The solution is to devise methods for approximately answering the questions posed, and these methods will vary depending on the data sets under scrutiny. This cutting-edge text introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, before discussing the thought processes and creativity involved in the analysis of large-scale biological and medical data sets, using a wide range of real-life examples. Bringing together leading experts, this text provides an ideal introduction to and insight into the interdisciplinary field of network da

Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you.Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems.In this book, you will:Use heuristics and design fitness functions.Build genetic algorithms.Make nature-inspired swarms with ants, bees and particles.Create Monte Carlo simulations.Investigate cellular automata.Find minima and maxima, using hill climbing and simulated annealing.Try selection methods,

Diagnosis and Fault Tolerance of Electrical Machines, Power Electronics and Drives describes techniques for fault analysis, diagnostics, condition monitoring methods, reconfiguration, remedial operati

This book reviews existing sensor technologies that are now being coupled with computational intelligence for the remote monitoring of physical activity and ex vivo biosignatures. In today’s frenetic

This highly informative book provides a comprehensive, up-to-date and practical reference for daily clinical practice in the management of patients affected by bone metastases. Written by renowned orthopedic surgeons and leading doctors in the respective fields of expertise, it offers a transversal review of the current medical and surgical treatments to allow a real interdisciplinary approach to the oncologic patient according to the highest current standards. The book illustrates all the fundamental medical treatments for metastatic bone diseases and provides an overview of pathology issues related to this condition. An entire section is devoted to main different methods of patients approach. It also provides guidance on all current surgical procedures and minimally invasive treatment techniques. Using a common language and recognizing the different osteoncologic competences, this work allows surgeons, oncologists, radiologists, pathologists and physiatricians to update their experti

The Riemann hypothesis (RH) is perhaps the most important outstanding problem in mathematics. This two-volume text presents the main known equivalents to RH using analytic and computational methods. The book is gentle on the reader with definitions repeated, proofs split into logical sections, and graphical descriptions of the relations between different results. It also includes extensive tables, supplementary computational tools, and open problems suitable for research. Accompanying software is free to download. These books will interest mathematicians who wish to update their knowledge, graduate and senior undergraduate students seeking accessible research problems in number theory, and others who want to explore and extend results computationally. Each volume can be read independently. Volume 1 presents classical and modern arithmetic equivalents to RH, with some analytic methods. Volume 2 covers equivalences with a strong analytic orientation, supported by an extensive set of appe

The Riemann hypothesis (RH) is perhaps the most important outstanding problem in mathematics. This two-volume text presents the main known equivalents to RH using analytic and computational methods. The book is gentle on the reader with definitions repeated, proofs split into logical sections, and graphical descriptions of the relations between different results. It also includes extensive tables, supplementary computational tools, and open problems suitable for research. Accompanying software is free to download. These books will interest mathematicians who wish to update their knowledge, graduate and senior undergraduate students seeking accessible research problems in number theory, and others who want to explore and extend results computationally. Each volume can be read independently. Volume 1 presents classical and modern arithmetic equivalents to RH, with some analytic methods. Volume 2 covers equivalences with a strong analytic orientation, supported by an extensive set of appe

This book reports on new theories and applications in the field of intelligent systems and computing. It covers computational and artificial intelligence methods, as well as advances in computer visio

Hugh Craig and Brett Greatley-Hirsch extend the computational analysis introduced in Shakespeare, Computers, and the Mystery of Authorship (edited by Hugh Craig and Arthur F. Kinney; Cambridge, 2009) beyond problems of authorship attribution to address broader issues of literary history. Using new methods to answer long-standing questions and challenge traditional assumptions about the underlying patterns and contrasts in the plays of Shakespeare and his contemporaries, Style, Computers, and Early Modern Drama sheds light on, for example, different linguistic usages between plays written in verse and prose, company styles and different character types. As a shift from a canonical survey to a corpus-based literary history founded on a statistical analysis of language, this book represents a fundamentally new approach to the study of English Renaissance literature and proposes a new model and rationale for future computational scholarship in early modern literary studies.

Based on a course taught by the author, this book combines the theoretical underpinnings of statistics with the practical analysis of Earth sciences data using MATLAB. The book is organized to introduce the underlying concepts, and then extends these to the data, covering methods that are most applicable to Earth sciences. Topics include classical parametric estimation and hypothesis testing, and more advanced least squares-based, nonparametric, and resampling estimators. Multivariate data analysis, not often encountered in introductory texts, is presented later in the book, and compositional data is treated at the end. Datasets and bespoke MATLAB scripts used in the book are available online, as well as additional datasets and suggested questions for use by instructors. Aimed at entering graduate students and practicing researchers in the Earth and ocean sciences, this book is ideal for those who want to learn how to analyse data using MATLAB in a statistically-rigorous manner.

This new and completely updated edition gives a detailed description of radiative transfer processes at a level accessible to advanced students. The volume gives the reader a basic understanding of global warming and enhanced levels of harmful ultraviolet radiation caused by ozone depletion. It teaches the basic physics of absorption, scattering and emission processes in turbid media, such as the atmosphere and ocean, using simple semi-classical models. The radiative transfer equation, including multiple scattering, is formulated and solved for several prototype problems, using both simple approximate and accurate numerical methods. In addition, the reader has access to a powerful, state-of-the-art computational code for simulating radiative transfer processes in coupled atmosphere-water systems including snow and ice. This computational code can be regarded as a powerful educational aid, but also as a research tool that can be applied to solve a variety of research problems in environ

This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems

Written using clear and accessible language, this text provides detailed coverage of the core mathematical concepts underpinning signal processing. All the core areas of mathematics are covered, including generalized inverses, singular value decomposition, function representation, and optimization, with detailed explanations of how basic concepts in these areas underpin the methods used to perform signal processing tasks. A particular emphasis is placed on the practical applications of signal processing, with numerous in-text practice questions and real-world examples illustrating key concepts, and MATLAB programs with accompanying graphical representations providing all the necessary computational background. This is an ideal text for graduate students taking courses in signal processing and mathematical methods, or those who want to establish a firm foundation in these areas before progressing to more advanced study.

The book reports on new theories and applications in the field of intelligent systems and computing. It covers computational and artificial intelligence methods, as well as advances in computer vision

In the chapters in Part I of this textbook the author introduces the fundamental ideas of artificial intelligence and computational intelligence. In Part II he explains key AI methods such as search,

This concise, plain-language guide for senior undergraduates and graduate students aims to develop intuition, practical skills and an understanding of the framework of numerical methods for the physical sciences and engineering. It provides accessible self-contained explanations of mathematical principles, avoiding intimidating formal proofs. Worked examples and targeted exercises enable the student to master the realities of using numerical techniques for common needs such as solution of ordinary and partial differential equations, fitting experimental data, and simulation using particle and Monte Carlo methods. Topics are carefully selected and structured to build understanding, and illustrate key principles such as: accuracy, stability, order of convergence, iterative refinement, and computational effort estimation. Enrichment sections and in-depth footnotes form a springboard to more advanced material and provide additional background. Whether used for self-study, or as the basis o

This concise, plain-language guide for senior undergraduates and graduate students aims to develop intuition, practical skills and an understanding of the framework of numerical methods for the physical sciences and engineering. It provides accessible self-contained explanations of mathematical principles, avoiding intimidating formal proofs. Worked examples and targeted exercises enable the student to master the realities of using numerical techniques for common needs such as solution of ordinary and partial differential equations, fitting experimental data, and simulation using particle and Monte Carlo methods. Topics are carefully selected and structured to build understanding, and illustrate key principles such as: accuracy, stability, order of convergence, iterative refinement, and computational effort estimation. Enrichment sections and in-depth footnotes form a springboard to more advanced material and provide additional background. Whether used for self-study, or as the basis o

How can Twitter data be used to study individual-level human behavior and social interaction on a global scale? This book introduces readers to the methods, opportunities, and challenges of using Twitter data to analyze phenomena ranging from the number of people infected by the flu, to national elections, to tomorrow's stock prices. Each chapter, written by leading domain experts in clear and accessible language, takes the reader to the forefront of the newly emerging field of computational social science. An introductory chapter on Twitter data analysis provides an overview of key tools and skills, and gives pointers on how to get started, while the case studies demonstrate shortcomings, limitations, and pitfalls of Twitter data as well as its advantages. The book will be an excellent resource for social science students and researchers wanting to explore the use of online data.

How can Twitter data be used to study individual-level human behavior and social interaction on a global scale? This book introduces readers to the methods, opportunities, and challenges of using Twitter data to analyze phenomena ranging from the number of people infected by the flu, to national elections, to tomorrow's stock prices. Each chapter, written by leading domain experts in clear and accessible language, takes the reader to the forefront of the newly emerging field of computational social science. An introductory chapter on Twitter data analysis provides an overview of key tools and skills, and gives pointers on how to get started, while the case studies demonstrate shortcomings, limitations, and pitfalls of Twitter data as well as its advantages. The book will be an excellent resource for social science students and researchers wanting to explore the use of online data.

Uniting classical and modern photonics approaches by presenting optical analyses as solutions of Maxwell's equations, this unique book enables students and practising engineers to fully understand the similarities and differences between the different methods. The book begins with a thorough discussion of plane wave analysis, which provides a clear understanding of optics without considering boundary condition or device configuration. It then goes on to cover diffraction analysis of many applications, including a rigorous analysis of TEM waves using Maxwell's equations with boundaries. Laser cavity modes and Gaussian beams are presented, modal analysis is covered, and approximation methods are discussed (including the perturbation technique, coupled mode analysis, and super mode analysis). With theory linked to practical examples throughout, it provides a clear understanding of the interplay between plane wave, diffraction and modal analysis, and how the different techniques can be app

This monograph presents computational techniques and numerical analysis to study conservation laws under uncertainty using the stochastic Galerkin formulation. With the continual growth of computer po

Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by nu

Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by nu

This text examines in detail mathematical and physical modeling, computational methods and systems for obtaining and analyzing biological structures, using pioneering research cases as examples. As su

Among all the numerical methods in seismology, the finite-difference (FD) technique provides the best balance of accuracy and computational efficiency. This book offers a comprehensive introduction to FD and its applications to earthquake motion. Using a systematic tutorial approach, the book requires only undergraduate degree-level mathematics and provides a user-friendly explanation of the relevant theory. It explains FD schemes for solving wave equations and elastodynamic equations of motion in heterogeneous media, and provides an introduction to the rheology of viscoelastic and elastoplastic media. It also presents an advanced FD time-domain method for efficient numerical simulations of earthquake ground motion in realistic complex models of local surface sedimentary structures. Accompanied by a suite of online resources to help put the theory into practice, this is a vital resource for professionals and academic researchers using numerical seismological techniques, and graduate st

Contrary to popular mythology, the designs of favorable products and successful systems do not appear suddenly, or magically. This second edition of Engineering Design demonstrates that symbolic representation and related problem-solving methods, offer significant opportunities to clarify and articulate concepts of design to lay a better framework for design research and design education. Artificial Intelligence (AI) provides a substantial body of material concerned with understanding and modeling cognitive processes. This book adopts the vocabulary and a paradigm of AI to enhance the presentation and explanation of design. It includes concepts from AI because of their explanatory power and their utility as possible ingredients of practical design activity. This second edition has been enriched by the inclusion of recent work on design reasoning, computational design, AI in design, and design cognition, with pointers to a wide cross section of the current literature.

Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems. The authors maintain a balance between mathematical analysis and practical design of intelligent agents. All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP. The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.

This book classifies the maximal subgroups of the almost simple finite classical groups in dimension up to 12; it also describes the maximal subgroups of the almost simple finite exceptional groups with socle one of Sz(q), G2(q), 2G2(q) or 3D4(q). Theoretical and computational tools are used throughout, with downloadable Magma code provided. The exposition contains a wealth of information on the structure and action of the geometric subgroups of classical groups, but the reader will also encounter methods for analysing the structure and maximality of almost simple subgroups of almost simple groups. Additionally, this book contains detailed information on using Magma to calculate with representations over number fields and finite fields. Featured within are previously unseen results and over 80 tables describing the maximal subgroups, making this volume an essential reference for researchers. It also functions as a graduate-level textbook on finite simple groups, computational group the

This new text surveys a series of fundamental problems in astrophysics, both analytically and computationally, for advanced students in physics and astrophysics. The contents are supported by more than 110 class-tested Mathematica® notebooks, allowing rigorous solutions to be explored in a visually engaging way. Topics covered include many classical and historically interesting problems, enabling students to appreciate the mathematical and scientific challenges that have been overcome in the subject's development. The text also shows the advantages and disadvantages of using analytical and computational methods. It will serve students, professionals and capable amateurs to master the quantitative details of modern astrophysics and the computational aspects of their research projects. Downloadable Mathematica® resources available at www.cambridge.org/koberlein.

Handbook of Neuroevolution Through Erlang presents both the theory behind, and the methodology of, developing a neuroevolutionary-based computational intelligence system using Erlang. With a foreword