Functional Analysis Methods for Reliability Models

Configurational Comparative Methods paves the way for an innovative approach to empirical scientific work through a strategy that integrates key strengths of both qualitative (case-oriented) and quan

A number of methods currently exist for the analysis and design of slopes. This book provides a critical review of these and offers several more appropriate approaches for overcoming numerical converg

This is a fully up-dated and expanded practical guide to protein structure-function relationships and it represents the most comprehensive volume on PTM analysis available. This important area of res

Praise for the First Edition ". . . outstandingly appealing with regard to its style, contents, considerations of requirements of practice, choice of examples, and exercises."—Zentrablatt Math ". . .

This first book to cover exclusively and in detail the principles, tools and methods for determining the reliability of microelectromechanical materials, components and devices covers both component m

Modern Methods for Robust Regression offers a brief but in-depth treatment of various methods for detecting and properly handling influential cases in regression analysis. This volume, geared toward

Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post-graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts.

Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post-graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts.

Inferring the precise locations and splicing patterns of genes in DNA is a difficult but important task, with broad applications to biomedicine. The mathematical and statistical techniques that have been applied to this problem are surveyed and organized into a logical framework based on the theory of parsing. Both established approaches and methods at the forefront of current research are discussed. Numerous case studies of existing software systems are provided, in addition to detailed examples that work through the actual implementation of effective gene-predictors using hidden Markov models and other machine-learning techniques. Background material on probability theory, discrete mathematics, computer science, and molecular biology is provided, making the book accessible to students and researchers from across the life and computational sciences. This book is ideal for use in a first course in bioinformatics at graduate or advanced undergraduate level, and for anyone wanting to kee

Inferring the precise locations and splicing patterns of genes in DNA is a difficult but important task, with broad applications to biomedicine. The mathematical and statistical techniques that have been applied to this problem are surveyed and organized into a logical framework based on the theory of parsing. Both established approaches and methods at the forefront of current research are discussed. Numerous case studies of existing software systems are provided, in addition to detailed examples that work through the actual implementation of effective gene-predictors using hidden Markov models and other machine-learning techniques. Background material on probability theory, discrete mathematics, computer science, and molecular biology is provided, making the book accessible to students and researchers from across the life and computational sciences. This book is ideal for use in a first course in bioinformatics at graduate or advanced undergraduate level, and for anyone wanting to kee

Focussing on structural reliability methods, reliability-based optimization, structural system reliability and risk analysis, lifetime performance and various applications in civil engineering. Invalu

The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development of population models and the use of subjective judgement. The advantages of Bayesian methods, are also described here, for example, the incorporation of any relevant prior information and the ability to assess the evidence in favour of competing hypotheses. Free software is available as well as an accompanying web-site containing the data files and WinBUGS codes. Bayesian Methods for Ecology will appeal to academic researchers, upper undergraduate and graduate students of Ecology.

Pedagogical insights gained through 30 years of teaching applied mathematics led the author to write this set of student-oriented books. Topics such as complex analysis, matrix theory, vector and tens

In Adenovirus Methods and Protocols, William S. M. Wold has organized a collection of readily reproducible methods for conducting research with adenoviruses, the premier and most widely used model in

Dental Functional Morphology offers an alternative to the received wisdom that teeth merely crush, cut, shear or grind food and shows how teeth adapt to diet. Providing an analysis of tooth action based on an understanding of how food particles break, it shows how tooth form from the earliest mammals to modern-day humans can be understood using very basic considerations about fracture. It outlines the theoretical basis step by step, explaining the factors governing tooth shape and size and provides an allometric analysis that will revolutionize attitudes to the evolution of the human face and the impact of cooked foods on our dentition. In addition, the basis of the mechanics behind the fracture of different types of food, and methods of measurement are given in an easy-to-use appendix. It will be an important sourcebook for physical anthropologists, dental and food scientists, palaeontologists and those interested in feeding ecology.

As the analysis of social networks, or networks of interpersonal and social relationships among social groups, has become an increasingly important method of research in several of the social and behavioural sciences, the gathering of network data has outpaced the development of new methods for its analysis. Addressing the need for analytical tools, Philippa Pattison presents a number of algebraic models for the analysis of network data, explaining in the process the rationale for an algebraic approach. Models are developed for both complete networks, meaning those representing the social ties between all pairs of members in a given group, and local networks, meaning those structured around the social ties of one particular group member. Many applications are presented and the ways that these methods can address a number of important issues confronting network analysis are explained.

Optimal Reliability Design, first published in 2000, provides a detailed introduction to systems reliability and reliability optimization. Techniques for maximizing system reliability are described, focusing on component reliability enhancement and redundancy arrangement. The authors present several case studies and show how optimization techniques are applied in practice. They also pay particular attention to finding methods that give the optimal trade-off between reliability and cost. The book begins with a review of key background material, and a discussion of a range of optimization models. The authors go on to cover optimization tools, such as heuristics, discrete optimization, nonlinear programming, mixed integer programming, optimal arrangement, and metaheuristic algorithms. They also describe the computational implementation of these tools. Many numerical examples are included, and the book contains over 180 homework exercises. It is suitable as a textbook for graduate-level co

Focusing on the application of mathematics to chemical engineering, Applied Mathematical Methods for Chemical Engineers, Second Edition addresses the setup and verification of mathematical models usin

For the first time in book form, Analytical Methods for Markov Semigroups provides a comprehensive analysis on Markov semigroups both in spaces of bounded and continuous functions as well as in Lp spa

This handbook is a reference guide for selecting and carrying out numerous methods of soil analysis. It is written in accordance with analytical standards and quality control approaches. It covers a l

This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

This book deals with these parametric methods, first discussing those based on time series models, Capon’s method and its variants, and then estimators based on the notions of sub-spaces. Howeve

Reliability Optimization thru Component Condition Monitoring and Root Cause Analysis details the effective method of component condition monitoring for use as both a predictive maintenance and root c

Physical Analysis for Tribology presents a unified approach to the study of wear in mechanical systems. Written by a leading expert who has studied and taught the subject both in Britain and the USA, this book will be valuable to researchers and students with a wide range of experience in tribology. The book concentrates on the methods of physical analysis and the applications of these techniques. This is then illustrated by a discussion of specific tribosystems. The early chapters provide an introduction to physical analysis that is thorough and rigorous. This prepares the reader with all the knowledge necessary to understand the subsequent discussion of applications. Although the description of systems is not exhaustive, the treatment and the theory are universal and will therefore be relevant to individual case studies. The book will appeal to tribologists from a wide variety of disciplines and will be of interest to researchers in physics, chemistry, metallurgy and mechanical engin

The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed in their 2000 book. Without putting too much emphasis on software,

The authors describe here a framework in which the type notation of functional languages is extended to include a notation for binding times (that is run-time and compile-time) that distinguishes between them. Consequently the ability to specify code and verify program correctness can be improved. Two developments are needed, the first of which introduces the binding time distinction into the lambda calculus, in a manner analogous with the introduction of types into the untyped lambda calculus. Methods are also presented for introducing combinators for run-time. The second concerns the interpretation of the resulting language, which is known as the mixed lambda-calculus and combinatory logic. The notion of 'parametrized semantics' is used to describe code generation and abstract interpretation. The code generation is for a simple abstract machine designed for the purpose; it is close to the categorical abstract machine. The abstract interpretation focuses on a strictness analysis that

The Mumford-Shah functional was introduced in the 1980s as a tool for automatic image segmentation, but its study gave rise to many interesting questions of analysis and geometric measure theory. The

Here is a book for anyone who would like to become better acquainted with the modern tools of numerical analysis for several significant computational problems arising in finance. The authors review s

Written by world-renowned authorities, Functional Lung Imaging explores the use of state-of-the-art imaging modalities for the analysis of pulmonary function. It provides an up-to-date and global pers

Describes the procedures for collection of samples, sample preparation, and analysis of CWC-related chemicals. It deals with analytical procedures that can be followed in well-equipped off-site labora

Written by a pioneer in the development of quantitative reliability methods for aircraft systems analysis and design, this text encompasses the entire field of reliability engineering. It draws on sta

Dental Functional Morphology offers an alternative to the received wisdom that teeth merely crush, cut, shear or grind food and shows how teeth adapt to diet. Providing an analysis of tooth action based on an understanding of how food particles break, it shows how tooth form from the earliest mammals to modern-day humans can be understood using very basic considerations about fracture. It outlines the theoretical basis step by step, explaining the factors governing tooth shape and size and provides an allometric analysis that will revolutionize attitudes to the evolution of the human face and the impact of cooked foods on our dentition. In addition, the basis of the mechanics behind the fracture of different types of food, and methods of measurement are given in an easy-to-use appendix. It will be an important sourcebook for physical anthropologists, dental and food scientists, palaeontologists and those interested in feeding ecology.

Kline (psychology, Concordia U., Montreal) answers a recent American Psychological Association call for changes in how research data are analyzed in the field. Assuming only a basic background in soci

Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for

This new textbook provides a concise but comprehensive guide to quantitative research methods for undergraduate and postgraduate students in all of the social sciences, as well as established researc

This new textbook provides a concise but comprehensive guide to quantitative research methods for undergraduate and postgraduate students in all of the social sciences, as well as established research

Members of the RAND Frederick S. Pardee Center for Longer Range Global Policy and the Future Human Condition reveal its initial findings into incorporating factors 25 to 100 years in the future into d

This book presents the current state of the art in computational models for turbulent reacting flows, and analyzes carefully the strengths and weaknesses of the various techniques described. The focus is on formulation of practical models as opposed to numerical issues arising from their solution. A theoretical framework based on the one-point, one-time joint probability density function (PDF) is developed. It is shown that all commonly employed models for turbulent reacting flows can be formulated in terms of the joint PDF of the chemical species and enthalpy. Models based on direct closures for the chemical source term as well as transported PDF methods are covered in detail. An introduction to the theory of turbulent and turbulent scalar transport is provided for completeness. The book is aimed at chemical, mechanical, and aerospace engineers in academia and industry, as well as developers of computational fluid dynamics codes for reacting flows.

Focusing on the purely theoretical aspects of strongly correlated electrons, this volume brings together a variety of approaches to models of the Hubbard type - i.e., problems where both localized and