Condition Monitoring Using Computational Intelligence Methods

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 second edition guides readers through experimental and computational techniques on the study of tissue morphogenesis, with a specific focus on techniques to image, manipulate, model and analyze tissue morphogenesis. Chapters focus on imagining analysis of tissue morphogenesis, culture models of tissue morphogenesis, manipulating cells and tissues in vivo, novel model systems to investigate issue morphogenesis and computational models. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Tissue Morphogenesis: Methods and Protocols serves as a primary resource for both fundamental and practical understanding of the techniques used to uncover the basis of tissue morphogenesis.

This book provides an in-depth roadmap for qualitative research methods and data analysis across disciplines using ATLAS.ti. It encompasses and rationalizes key qualitative research concepts and methods with innovative frameworks to enrich the reader’s understanding of qualitative research methods and data analysis. The book contains multiple real-world projects that assist readers in developing conceptual and theoretical knowledge, as well as gaining insights from fieldwork, visualizing data collection, analysis, and methodological interpretations.This easy to use book provides a pragmatic approach to qualitative methods, proficiency in capturing field observations, user-friendly steps to data analysis starting from transcription, preparation of data, reading and identification of quotations, coding, memoing, commenting, code groups, creating smart codes and groups using set, semantic, and proximity operators resulting in generating numerous insightful thematic reports in avariety of

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

This book presents methods for the summation of infinite and finite series and the related identities and inversion relations. The summation includes the column sums and row sums of lower triangular matrices. The convergence of the summation of infinite series is considered. The author's focus is on symbolic methods and the Riordan array approach. In addition, this book contains hundreds summation formulas and identities, which can be used as a handbook for people working in computer science, applied mathematics, and computational mathematics, particularly, combinatorics, computational discrete mathematics, and computational number theory. The exercises at the end of each chapter help deepen understanding.Much of the materials in this book has never appeared before in textbook form. This book can be used as a suitable textbook for advanced courses for high lever undergraduate and lower lever graduate students. It is also an introductory self-study book for re- searchers interested in t

THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSISBy focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

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.

Introduction to Intelligence: Institutions, Operations, and Analysis offers you a strategic, international, and comparative approach to covering intelligence organizations and domestic security issues. Written by multiple authors, each chapter draws on the author's professional and scholarly expertise in the subject matter. As a core text for an introductory survey course in intelligence, this text provides you with a comprehensive introduction to intelligence, including institutions and processes, collection, communications, and common analytic methods.

This book marries social work and artificial intelligence to provide an introductory guide for using AI for social good. Following an introductory chapter laying out approaches and ethical principles of using AI for social work interventions, the book describes in detail an intervention to increase the spread of HIV information by using algorithms to determine the key individuals in a social network of homeless youth. Other chapters present interdisciplinary collaborations between AI and social work students, including a chatbot for sexual health information and algorithms to determine who is at higher stress among persons with Type 2 Diabetes. For students, academic researchers, industry leaders, and practitioners, these real-life examples from the USC Center for Artificial Intelligence in Society demonstrate how social work and artificial intelligence can be used in tandem for the greater good.

Why a new approach is needed in the quest for general artificial intelligence.Since the inception of artificial intelligence, we have been warned about the imminent arrival of computational systems th

Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. Accompanying the mathematical derivations are full implementations of dozens of numerical methods in Python, as well as more than 250 end-of-chapter problems. Numerical methods and physics examples are clearly separated, allowing this introductory book to be later used as a reference; the penultimate section in each chapter is an in depth project, tackling physics problems which cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the

Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. Accompanying the mathematical derivations are full implementations of dozens of numerical methods in Python, as well as more than 250 end-of-chapter problems. Numerical methods and physics examples are clearly separated, allowing this introductory book to be later used as a reference; the penultimate section in each chapter is an in depth project, tackling physics problems which cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the

Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning methods for neuroscience. The methods are demonstrated through case studies of real problems to empower readers to build their own solutions. The book covers a wide variety of methods, including supervised classification with non-probabilistic models (nearest-neighbors, classification trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic regression and Bayesian network classifiers), meta-classifiers, multi-dimensional classifiers and feature subset selection methods. Other parts of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial statistics with po

This combines theory and practice for the design of earth lateral support for deep excavations in soil, along with design methods, basic and computational numerical methods. It is heavily illustrated

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem.First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare.

The exposure of two senior republicans as informers for British intelligence in 2005 led to a popular perception that the IRA had 'lost' the intelligence war and was pressurised into peace. In this first in-depth study across the entire conflict, Thomas Leahy re-evaluates the successes and failures of Britain's intelligence activities against the IRA, from the use of agents and informers to special-forces, surveillance and electronic intelligence. Using new interview material alongside memoirs and Irish and UK archival materials, he suggests that the IRA was not forced into peace by British intelligence. His work sheds new light on key questions in intelligence and security studies. How does British intelligence operate against paramilitaries? Is it effective? When should governments 'talk to terrorists'? And does regional variation explain the outcome of intelligence conflicts? This is a major contribution to the history of the conflict and of why peace emerged in Northern Ireland.

The exposure of two senior republicans as informers for British intelligence in 2005 led to a popular perception that the IRA had 'lost' the intelligence war and was pressurised into peace. In this first in-depth study across the entire conflict, Thomas Leahy re-evaluates the successes and failures of Britain's intelligence activities against the IRA, from the use of agents and informers to special-forces, surveillance and electronic intelligence. Using new interview material alongside memoirs and Irish and UK archival materials, he suggests that the IRA was not forced into peace by British intelligence. His work sheds new light on key questions in intelligence and security studies. How does British intelligence operate against paramilitaries? Is it effective? When should governments 'talk to terrorists'? And does regional variation explain the outcome of intelligence conflicts? This is a major contribution to the history of the conflict and of why peace emerged in Northern Ireland.

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.

Using IBM SPSS for Social Statistics and Research Methods supports the use of SPSS for social statistics and research methods classes and is an excellent companion to any undergraduate statistics

Meaningful use of advanced Bayesian methods requires a good understanding of the fundamentals. This engaging book explains the ideas that underpin the construction and analysis of Bayesian models, with particular focus on computational methods and schemes. The unique features of the text are the extensive discussion of available software packages combined with a brief but complete and mathematically rigorous introduction to Bayesian inference. The text introduces Monte Carlo methods, Markov chain Monte Carlo methods, and Bayesian software, with additional material on model validation and comparison, transdimensional MCMC, and conditionally Gaussian models. The inclusion of problems makes the book suitable as a textbook for a first graduate-level course in Bayesian computation with a focus on Monte Carlo methods. The extensive discussion of Bayesian software - R/R-INLA, OpenBUGS, JAGS, STAN, and BayesX - makes it useful also for researchers and graduate students from beyond statistics.

Meaningful use of advanced Bayesian methods requires a good understanding of the fundamentals. This engaging book explains the ideas that underpin the construction and analysis of Bayesian models, with particular focus on computational methods and schemes. The unique features of the text are the extensive discussion of available software packages combined with a brief but complete and mathematically rigorous introduction to Bayesian inference. The text introduces Monte Carlo methods, Markov chain Monte Carlo methods, and Bayesian software, with additional material on model validation and comparison, transdimensional MCMC, and conditionally Gaussian models. The inclusion of problems makes the book suitable as a textbook for a first graduate-level course in Bayesian computation with a focus on Monte Carlo methods. The extensive discussion of Bayesian software - R/R-INLA, OpenBUGS, JAGS, STAN, and BayesX - makes it useful also for researchers and graduate students from beyond statistics.

Focusing on students’ presentations and discussions in laboratory seminars, this book presents case studies on evidence-based education using artificial intelligence (AI) technologies. It proposes a s

Qualitative Comparative Analysis in Mixed Methods Research and Evaluation provides a user-friendly introduction for using Qualitative Comparative Analysis (QCA) as part of a mixed methods approach to

This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aime

This book addresses issues of monitoring populations of tigers, ungulate prey species and habitat occupancy, with relevance to similar assessments of large mammal species and general biodiversity. It

Mathematical Physics in Theoretical Chemistry deals with important topics in theoretical and computational chemistry. Topics covered include density functional theory, computational methods in biologi

The prediction of crystal structures from first principles has been one of the grand challenges for computational methods in chemistry and materials science. The goal of being able to reliably predict

This volume explores the latest available wet-lab techniques and computational methods to study in-cell small-molecule behavior and interactions with their targets. The chapters in this book discuss t

This volume explores recent techniques for the computational inference of gene regulatory networks (GRNs). The chapters in this book cover topics such as methods to infer GRNs from time-varying data;

This book marries social work and artificial intelligence to provide an introductory guide for using AI for social good. Following an introductory chapter laying out approaches and ethical principles of using AI for social work interventions, the book describes in detail an intervention to increase the spread of HIV information by using algorithms to determine the key individuals in a social network of homeless youth. Other chapters present interdisciplinary collaborations between AI and social work students, including a chatbot for sexual health information and algorithms to determine who is at higher stress among persons with Type 2 Diabetes. For students, academic researchers, industry leaders, and practitioners, these real-life examples from the USC Center for Artificial Intelligence in Society demonstrate how social work and artificial intelligence can be used in tandem for the greater good.

Cutting through the hype, a practical guide to using artificial intelligence for business benefits and competitive advantage.In The AI Advantage, Thomas Davenport offers a guide to using artificial in

Recent startling successes in machine intelligence using a technique called ‘deep learning’ seem to blur the line between human and machine as never before. Are computers on the cusp of be

Recent startling successes in machine intelligence using a technique called ‘deep learning’ seem to blur the line between human and machine as never before. Are computers on the cusp of be

Strengthen and inform your monitoring and assessment skills, with the freshly updated Electronic Fetal Monitoring: Concepts and Applications, 3rd Edition. Offering in-depth information on physiology,

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issue

Updated throughout for this new edition, Water Distribution System Monitoring describes the latest water quality monitoring approaches, techniques, and equipment that will assist water utilities stay

Updated throughout for this new edition, Water Distribution System Monitoring describes the latest water quality monitoring approaches, techniques, and equipment that will assist water utilities stay

This volume covers several aspects of rational drug design, such as synthesis of novel bioactive drugs; development and application of new methodologies; computational methods valuable for the establi

A comprehensive treatment of systems and software testing using state of the art methods and tools This book provides valuable insights into state of the art software testing methods and explains, wit

This book examines air pollution of a big city using multi-year and multi-season data from ground-based air monitoring stations and satellite sounding data, which provides more clear and detailed info