Methods of Nonlinear Analysis

This book describes effective methods for automatically analyzing a sentence, based on the syntactic and semantic characteristics of the elements that form it. To tackle ambiguities, the authors

"Designed for a one-semester course on the subject, this classroom-tested text presents fundamental concepts of numerical mathematics and explains how to implement and program numerical methods. Drawi

The Intelligent Systems Series comprises titles that present state-of-the-art knowledge and the latest advances in intelligent systems. Its scope includes theoretical studies, design methods, and real

Become a master of data analysis, modeling, and spreadsheet use with BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 5E! This quantitative methods text provides users with the tools to succeed

Partial Differential Equations: Topics in Fourier Analysis explains how to use the Fourier transform and heuristic methods to obtain significant insight into the solutions of standard PDE models. It s

Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D. Allison, is an accessible, data-based introduction to methods of survival analysis. Research

The second edition of Statistics and Data Analysis for Nursing , uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Readers ar

Mathematical analysis is key to the modeling and management of natural resources. By presenting required mathematical methods, classic dynamic models for non-renewable and renewable resources, and by exploring several contemporary problems, this text provides a foundation for advanced research. Topics include seminal models in fishery, forestry and non-renewable resource management, as well as an extensive collection of contemporary applications that include the optimal transition from fossil fuels to clean energy, the optimal timing of interventions to save endangered species, pest control and the optimal management of antibiotic resistance. Deterministic and stochastic models in both discrete and continuous time are covered. The book encourages students to pursue a deeper understanding of the analytics of resource problems and to deploy numerical methods when analytical results prove intractable. The combination of analysis, theory and applications will launch the next generation of

Mathematical analysis is key to the modeling and management of natural resources. By presenting required mathematical methods, classic dynamic models for non-renewable and renewable resources, and by exploring several contemporary problems, this text provides a foundation for advanced research. Topics include seminal models in fishery, forestry and non-renewable resource management, as well as an extensive collection of contemporary applications that include the optimal transition from fossil fuels to clean energy, the optimal timing of interventions to save endangered species, pest control and the optimal management of antibiotic resistance. Deterministic and stochastic models in both discrete and continuous time are covered. The book encourages students to pursue a deeper understanding of the analytics of resource problems and to deploy numerical methods when analytical results prove intractable. The combination of analysis, theory and applications will launch the next generation of

This volume provides an introduction for flood risk management practitioners, up-to-date methods for analysis of uncertainty and its use in risk-based decision making. It addresses decision making fo

This practical guide to survival data and its analysis for readers with a minimal background in statistics shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts as bias, confounding, independence, and interaction are presented in the context of survival analysis and also are basic components of a broad range of applications. These topics make up essentially a 'second-year', one-semester biostatistics course in

This practical guide to survival data and its analysis for readers with a minimal background in statistics shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts as bias, confounding, independence, and interaction are presented in the context of survival analysis and also are basic components of a broad range of applications. These topics make up essentially a 'second-year', one-semester biostatistics course in

Part of SAGE’s Mastering Business Research Methods, conceived and edited by Bill Lee, Mark N. K. Saunders and Vadake K. Narayanan and designed to support researchers by providing in-depth and practica

Part of SAGE’s Mastering Business Research Methods, conceived and edited by Bill Lee, Mark N. K. Saunders and Vadake K. Narayanan and designed to support researchers by providing in-depth and practica

Proving the adage that to be forewarned is to be forearmed, the contributors of these papers presented at the May 2008 conference explain how improvements in computational methods have allowed them to

A huge amount of fixed and paraffin-embedded tissue is stored in every hospital. This is very precious material that can be used for translational research and for diagnostics. The molecular methods e

One of the only texts available to cover not only how failure occurs but also examine methods developed to expose the reasons for failure, Metal Failures has long been considered the most definitive a

Analyzing language can be tricky but it provides a useful insight within social research. This book shows how to apply methods to written and spoken words, across a range of social sciences. Solving p

Analyzing language can be tricky but it provides a useful insight within social research. This book shows how to apply methods to written and spoken words, across a range of social sciences. Solving p

This textbook puts design at the center of introducing students to the course in mass and energy balances in chemical engineering. Employers and accreditations increasingly stress the importance of design in the engineering curriculum, and design-driven analysis will motivate students to dig deeply into the key concepts of the field. The second edition has been completely revised and updated. It introduces the central steps in design and three methods of analysis: mathematical modeling, graphical methods, and dimensional analysis. Students learn how to apply engineering skills, such as how to simplify calculations through assumptions and approximations; how to verify calculations, significant figures, spreadsheets, graphing (standard, semi-log and log-log); and how to use data maps, in the contexts of contemporary chemical processes such as the hydrogen economy, petrochemical and biochemical processes, polymers, semiconductors, and pharmaceuticals.

Aimed at graduates and researchers, and requiring only a basic knowledge of multi-variable calculus, this introduction to computer-based partial differential equation (PDE) modeling provides readers with the practical methods necessary to develop and use PDE mathematical models in biomedical engineering. Taking an applied approach, rather than using abstract mathematics, the reader is instructed through six biomedical example applications, each example characterized by step-by-step discussions of established numerical methods and implemented in reliable computer routines. Adopting this technique, the reader will understand how PDE models are formulated, implemented and tested. Supported by a set of rigorously tested general purpose PDE routines online, and with enhanced understanding through animations, this book will be ideal for anyone faced with interpreting large experimental data sets that need to be analyzed with PDE models in biomedical engineering.

Many applications in science and engineering require a digital model of a real physical object. Advanced scanning technology has made it possible to scan such objects and generate point samples on their boundaries. This book, first published in 2007, shows how to compute a digital model from this point sample. After developing the basics of sampling theory and its connections to various geometric and topological properties, the author describes a suite of algorithms that have been designed for the reconstruction problem, including algorithms for surface reconstruction from dense samples, from samples that are not adequately dense and from noisy samples. Voronoi- and Delaunay-based techniques, implicit surface-based methods and Morse theory-based methods are covered. Scientists and engineers working in drug design, medical imaging, CAD, GIS, and many other areas will benefit from this first book on the subject.

Many applications in science and engineering require a digital model of a real physical object. Advanced scanning technology has made it possible to scan such objects and generate point samples on their boundaries. This book, first published in 2007, shows how to compute a digital model from this point sample. After developing the basics of sampling theory and its connections to various geometric and topological properties, the author describes a suite of algorithms that have been designed for the reconstruction problem, including algorithms for surface reconstruction from dense samples, from samples that are not adequately dense and from noisy samples. Voronoi- and Delaunay-based techniques, implicit surface-based methods and Morse theory-based methods are covered. Scientists and engineers working in drug design, medical imaging, CAD, GIS, and many other areas will benefit from this first book on the subject.

The Biographia Literaria has long been recognised as one of the central prose texts of the Romantic period, both for its value as a piece of elevated prose writing and for the insights into poetry, criticism and the faculties of the mind that it offers. It seeks to reunify philosophical thought and aesthetic feeling in the belief that genuine knowledge emerges from only such a synthesis. Dr Wheeler's analysis proceeds from a number of points of view. The gradual growth of the Biographia Literaria is illuminated by notebooks and letters that show Coleridge wrestling with the work over a period of fifteen years. The aesthetic and metaphysical thought informing the Biographia is also discussed in order to elucidate the methods and purposes of the work, in which Coleridge's use of metaphor and irony constitutes both the structure and the point of engagement with the reader.

Attention to cultural variation has become an important source of insight in the social, behavioural, and health sciences. Mixed methods research provides an especially sensitive and powerful way to make systematic cross-cultural comparisons, in which qualitative approaches give a window onto cultural meaning and the phenomenological 'feel' of social life, and quantitative methods facilitate hypothesis testing and sophisticated modelling of social and behavioural phenomena. For researchers engaged in cross-cultural projects, this book offers a theory-based approach to integrating 'numbers' and 'text' based on discourse as the originary form of data collection, the method and framework of analysis, and the medium of publication. The book provides concise explanations, targeted examples, step-by-step instructions, and actual analyses of cross-cultural, quantitative survey data and qualitative interview data, with special attention to language(s) and translation as clues to the study of c

Aimed at graduate students in physics and mathematics, this book provides an introduction to recent developments in several active topics at the interface between algebra, geometry, topology and quantum field theory. The first part of the book begins with an account of important results in geometric topology. It investigates the differential equation aspects of quantum cohomology, before moving on to noncommutative geometry. This is followed by a further exploration of quantum field theory and gauge theory, describing AdS/CFT correspondence, and the functional renormalization group approach to quantum gravity. The second part covers a wide spectrum of topics on the borderline of mathematics and physics, ranging from orbifolds to quantum indistinguishability and involving a manifold of mathematical tools borrowed from geometry, algebra and analysis. Each chapter presents introductory material before moving on to more advanced results. The chapters are self-contained and can be read inde

The Earth and environmental sciences are becoming progressively more quantitative due to the increased use of mathematical models and new data analysis techniques. This accessible introduction presents an overview of the mathematical methods essential for understanding Earth processes, providing an invaluable resource for students and early career researchers who may have missed (or forgotten) the mathematics they need to succeed as scientists. Topics build gently from basic methods such as calculus to more advanced techniques including linear algebra and differential equations. The practical applications of the mathematical methods to a variety of topics are discussed, ranging from atmospheric science and oceanography to biogeochemistry and geophysics. Including over 530 exercises and end-of-chapter problems, as well as additional computer codes in Python and MATLAB®, this book supports readers in applying appropriate analytical or computational methods to solving real research questi

Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.

This practical book is designed for applied researchers who want to use mixed models with their data. It discusses the basic principles of mixed model analysis, including two-level and three-level structures, and covers continuous outcome variables, dichotomous outcome variables, and categorical and survival outcome variables. Emphasizing interpretation of results, the book develops the most important applications of mixed models, such as the study of group differences, longitudinal data analysis, multivariate mixed model analysis, IPD meta-analysis, and mixed model predictions. All examples are analyzed with STATA, and an extensive overview and comparison of alternative software packages is provided. All datasets used in the book are available for download, so readers can re-analyze the examples to gain a strong understanding of the methods. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other

This practical book is designed for applied researchers who want to use mixed models with their data. It discusses the basic principles of mixed model analysis, including two-level and three-level structures, and covers continuous outcome variables, dichotomous outcome variables, and categorical and survival outcome variables. Emphasizing interpretation of results, the book develops the most important applications of mixed models, such as the study of group differences, longitudinal data analysis, multivariate mixed model analysis, IPD meta-analysis, and mixed model predictions. All examples are analyzed with STATA, and an extensive overview and comparison of alternative software packages is provided. All datasets used in the book are available for download, so readers can re-analyze the examples to gain a strong understanding of the methods. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other

An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a website that provides all data sets, questions for each chapter and l

A valuable new edition of a standard referenceThe use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An In

The field of forensic DNA analysis has grown immensely in the past two decades and genotyping of biological samples is now routinely performed in human identification (HID) laboratories. Application areas include paternity testing, forensic casework, family lineage studies, identification of human remains, and DNA databasing. Forensic DNA Analysis: Current Practices and Emerging Technologies explores the fundamental principles and the application of technologies for each aspect of forensic DNA analysis. The book begins by discussing the value of DNA evidence and how to properly recognize, document, collect, and store it. The remaining chapters examine: The most widely adopted methods and the best practices for DNA isolation from forensic biological samples and human remainsStudies carried out on the use of both messenger RNA and small (micro) RNA profilingReal-time polymerase chain reaction (PCR) methods for quantification and assessment of human DNA prior to genotypingCapillary electr

Every chemist needs to know the fundamentals of the instrumental methods of analysis. This eighth edition of "Instrumental Methods of Analysis" provides the essential background for a one-semester upp