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Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration is an introduction to the field of Integrated Navigation Systems. It serves as an excellent reference for working engineers as well as textbook for beginners and students new to the area. The book is easy to read and understand with minimum background knowledge. The authors explain the derivations in great detail. The intermediate steps are thoroughly explained so that a beginner can easily follow the material. The book shows a step-by-step implementation of navigation algorithms and provides all the necessary details. It provides detailed illustrations for an easy comprehension.  The book also demonstrates real field experiments and in-vehicle road test results with professional discussions and analysis. This work is unique in discussing the different INS/GPS integration schemes in an easy to understand and straightforward way. Those schemes include loosely vs tightly coupled, open loop vs closed lo

Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration

Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models. Key features: * Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. * Provides a thorough introduction for research students. * Computational tools to deal with complex problems are illustrated along with real life case studies * Looks at inference, prediction and decision making. Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practition

Bayesian Analysis of Stochastic Process Models

Elliptically Contoured Models in Statistics and Portfolio Theory fully revises the first detailed introduction to the theory of matrix variate elliptically contoured distributions. There are two additional chapters, and all the original chapters of this classic text have been updated. Resources in this book will be valuable for researchers, practitioners, and graduate students in statistics and related fields of finance and engineering. Those interested in multivariate statistical analysis and its application to portfolio theory will find this text immediately useful. ​In multivariate statistical analysis, elliptical distributions have recently provided an alternative to the normal model. Elliptical distributions have also increased their popularity in finance because of the ability to model heavy tails usually observed in real data. Most of the work, however, is spread out in journals throughout the world and is not easily accessible to the investigators. A noteworthy function of this

Elliptically Contoured Models in Statistics and Portfolio Theory

The Education Endowment Foundation&apos;s Teaching and Learning Toolkit describes collaborative learning as an approach which &apos;involves pupils working together on activities or learning tasks&apos; and in such a way that enables &apos;everyone to participate on a collective task that has been clearly assigned&apos;. In the context of this book, Cooperative Learning relates to a number of such activities from simple memorising to more complex analysis and debating which are designed to boost learners&apos; interdependence, participation and interaction. Drawing upon both research-informed theory and real-world examples, Jakob Werdelin and Drew Howard present both an insightful introduction to Cooperative Learning as a practice and philosophy and a practical guide to classroom application. The authors share their expertise on how to amplify the effect of current pedagogical approaches and schemes of work, simplify performance management as an empowering tool for teachers and leaders

The Beginner's Guide to Cooperative Learning

This book provides a serious introduction to the subject of massspectrometry, providing the reader with the tools and informationto be well prepared to perform such demanding work in a real-lifelaboratory. This essential tool bridges several subjects and manydisciplines including pharmaceutical, environmental and biomedicalanalysis that are utilizing mass spectrometry: * Covers all aspects of the use of mass spectrometry forquantitation purposes * Written in textbook style to facilitate understanding of thistopic * Presents fundamentals and real-world examples in a'learning-though-doing' style

Trace Quantitative Analysis by Mass Spectrometry

This book provides a practical introduction to analyzing ecological data using real data sets. The first part gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modeling techniques), multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a reader’s own data analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.

Analyzing Ecological Data

Starting with a simple formulation accessible to all mathematicians, this second edition is designed to provide a thorough introduction to nonstandard analysis. Nonstandard analysis is now a well-developed, powerful instrument for solving open problems in almost all disciplines of mathematics; it is often used as a ‘secret weapon’ by those who know the technique. This book illuminates the subject with some of the most striking applications in analysis, topology, functional analysis, probability and stochastic analysis, as well as applications in economics and combinatorial number theory. The first chapter is designed to facilitate the beginner in learning this technique by starting with calculus and basic real analysis. The second chapter provides the reader with the most important tools of nonstandard analysis: the transfer principle, Keisler’s internal definition principle, the spill-over principle, and saturation. The remaining chapters of the book study different fields for applica

Nonstandard Analysis for the Working Mathematician

This book introduces readers to all the necessary components and knowledge to start being a vital part of the IoT revolution.  The author discusses how to create smart-IoT solutions to help solve a variety of real problems.  Coverage includes the most important aspects of IoT architecture, the various applications of IoT, and the enabling technologies for IoT. This book presents key IoT concepts and abstractions, while showcasing real case studies.  The discussion also includes an analysis of IoT strengths, weaknesses, opportunities and threats.  Readers will benefit from the in-depth introduction to internet of things concepts, along with discussion of IoT algorithms and architectures tradeoffs. Case studies include smart homes, smart agriculture, and smart automotive.

The Era of Internet of Things

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner.   Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters.  T

Pattern Recognition and Classification

ENbook.pl

Real analysis provides the fundamental underpinnings for calculus, arguably the most useful and influential mathematical idea ever invented. It is a core subject in any mathematics degree, and also one which many students find challenging. A Sequential Introduction to Real Analysis gives a fresh take on real analysis by formulating all the underlying concepts in terms of convergence of sequences. The result is a coherent, mathematically rigorous, but conceptually simple development of the standard theory of differential and integral calculus ideally suited to undergraduate students learning real analysis for the first time.This book can be used as the basis of an undergraduate real analysis course, or used as further reading material to give an alternative perspective within a conventional real analysis course.

A Sequential Introduction to Real Analysis | Speight J. Martin | Twarda | Twarda

This book presents an introduction to the key topics in Real Analysis and makes the subject easily understood by the learners. The book is primarily useful for students of mathematics and engineering studying the subject of Real Analysis. It includes many examples and exercises at the end of chapters. This book is very authentic for students, instructors, as well as those doing research in areas demanding a basic knowledge of Real Analysis. It describes several useful topics in Real Analysis such as sets and functions, completeness, ordered and field, neighborhoods, limit points of a set, open sets, closed sets, countable and uncountable sets, sequences of real numbers, limit, continuity and differentiability of real functions, uniform continuity, point-wise and uniform convergence of sequences and series of real functions, Riemann integration, improper integrals and metric spaces.

Introduction to the Basics of Real Analysis | Singh Harendra | Twarda | Twarda

pThis book provides an introduction to real analysis, a fundamental topic that is an essential requirement in the study of mathematics. It deals with the concepts of infinity and limits, which are the cornerstones in the development of calculus.p pBeginning with some basic proof techniques and the notions of sets and functions, the book rigorously constructs the real numbers and their related structures from the natural numbers. During this construction, the readers will encounter the notions of infinity, limits, real sequences, and real series. These concepts are then formalised and focused on as stand-alone objects. Finally, they are expanded to limits, sequences, and series of more general objects such as real-valued functions. Once the fundamental tools of the trade have been established, the readers are led into the classical study of calculus continuity, differentiation, and Riemann integration from first principles. The book concludes with an introduction to the study of measure

The Big Book of Real Analysis | Johar Syafiq | Twarda

Infinitesimal Analysis V1 Elementary Real Variables is a book written by William Benjamin Smith and first published in 1898. The book is a comprehensive introduction to the theory of infinitesimal analysis, with a focus on real variables. The text is divided into two parts, with the first part covering the basic concepts of calculus, such as limits, derivatives, and integrals. The second part of the book delves deeper into the theory of functions, including topics such as continuity, uniform convergence, and power series. Smith's writing style is clear and concise, making the book accessible to both beginners and advanced students of mathematics. The book is also notable for its historical significance, as it played a significant role in the development of the modern theory of calculus. Overall, Infinitesimal Analysis V1 Elementary Real Variables is a classic text that is still relevant today for anyone interested in the foundations of calculus and real analysis.This scarce antiquarian

Infinitesimal Analysis V1 | Smith William Benjamin | Twarda

pThis book presents an introduction into Robinson's nonstandard analysis, which is an application of model theory in analysis. Unlike some texts, it does not attempt to teach elementary calculus on the basis of nonstandard analysis, but points to some applications in more advanced analysis. These can hardly be obtained by standard methods such as a deeper investigation of Hahn-Banach limits or of finitely additive measures. The contents move from a discussion of the preliminaries to Nonstandard Models Nonstandard Real Analysis Enlargements and Saturated Models Functionals, Generalized Limits, and Additive Measures and finally Nonstandard Topology and Functional Analysis. The reader is not expected to have any background in model theory some background in analysis, topology, or functional analysis is useful - although the book is as much self-contained as possible and can be understood after a basic calculus course.p

Nonstandard Analysis | Vth Martin Andreas | Twarda | Twarda

A Primer of Real Functions is a mathematical textbook written by Ralph Philip Boas Jr. and published as part of the Carus Mathematical Monographs series. The book is aimed at students and mathematicians who are interested in studying real analysis and calculus. It covers a range of topics including limits, continuity, differentiability, integration, and sequences and series of functions. The book begins with an introduction to the real number system and the concept of limits, before moving on to topics such as continuity, differentiability, and integration. The author provides clear explanations of the concepts and theorems, and includes numerous examples and exercises to help readers understand and apply the material. The book is suitable for use as a textbook in undergraduate and graduate courses in real analysis and calculus, as well as for self-study by anyone interested in these topics.This scarce antiquarian book is a facsimile reprint of the old original and may contain some imp

A Primer Of Real Functions | Boas Jr Ralph Philip | Twarda

Alan McKee presents a student friendly introduction to the analysis of cultural texts. The book highlights the cultural differences in interpretation with an array of fascinating examples. bTextual Analysisb is written in an accessible style with several useful case studies. Each chapter also includes exercises for classroom8242 - biJane Stokes, London Metropolitan Universityp pbip p McKee is a gifted practitioner of the skills he would teach in this book, as well as a lively and engaging writer and one who has a real commitment to making his ideas available to a larger public8242 - biHenry Jenkins, Massachusetts Institute of Technologyp pp pbiThis book provides an indispensable basic introduction to textual analysis. McKee starts from the most basic philosophical foundations that underlie the practice and explains why texts are important and what they tell us about the world they represent.p pbp pTextual Analysis bguides students away from finding the  correct8242 interpretation of a 

Textual Analysis | McKee Alan | Twarda

pemThe Practice of Mathematics An Introduction to Proof Techniques and Number Systemsem is designed to help students prepare for higher-level mathematics courses through an introduction to the methods and practices of logic and proof. The book uses the development of set theory and the number systems as a framework for the introduction of the various proof techniques.br  br  As students study proof techniques, they learn about basic set theory, natural numbers, integers, rational numbers, and real numbers. Within each chapter, ideas critical to the number systems are expanded to motivate the study of more advanced topics. In this way, students are exposed to basic ideas and concepts in modern algebra, graph theory, combinatorics, real analysis, and topology.br  br  Additionally, the text serves as an introduction to mathematics as a profession, covering mathematical disciplines, professional activities, and mathematical software. It includes a large variety of exercises that range from

Practice of Mathematics | Johnston Clifford | Twarda

pMeta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. p The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis including when it should not be used. Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences

Handbook of Meta | Analysis in Ecology and Evolution | Koricheva Julia | Paperback | Twarda

pbThe Classic Introduction to Technical Analysis--Fully Updated and Revised!bp pThe most reliable method for forecasting trends and timing market turns, technical analysis is as close to a scientific trading approach as you can get--and it is particularly valuable in today's volatile markets. iThe Technical Analysis Coursei, Fourth Edition, provides the know-how you need to make this powerful tool part of your overall investing strategy.p pThrough a series of lessons and exams, you'll master the techniques used by the most successful technical analysts in the market today. Updated with hundreds of real market examples, iThe Technical Analysis Coursei provides the essential foundation for using time-tested technical analysis techniques to profit from the markets. You'll learn how to ul liIdentify profitable chart patterns, including reversals, consolidation formations, and gaps liUtilize key analytical tools, including trendlines and channels, support and resistance, relative strength a

The Technical Analysis Course, Fourth Edition | Meyers Thomas | Twarda

pThis book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis - supported by numerous real data examples and reusable R code - with a rigorous treatment of probability and statistical principles. pWhere contemporary undergraduate textbooks in probability theory or statistics often miss applications and an introductory treatment of modern methods bootstrapping, Bayes, etc., and where applied data analysis books often miss a rigorous theoretical treatment, this book provides an accessible but thorough introduction into data analysis, using statistical methods combining the two viewpoints. The book further focuses on methods for dealing with large data-sets and streaming-data and hence provides a single-course introduction of statistical methods for data science.brpp

Statistics for Data Scientists | Kaptein Maurits | Twarda

pThis book provides a practical introduction to analyzing ecological data using real data sets collected as part of postgraduate ecological studies or research projects. The first part gives a largely non-mathematical introduction to data exploration, univariate methods including GAM and mixed modeling techniques, multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies, mainly written together with biologists who attended courses given by the authors. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a reader's own data analysis. The case studies also show how to deal with certain levels of difficulty during the key process of selecting the correct or appropriate statistical technique. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.p

Analyzing Ecological Data | Zuur Alain | Paperback | Twarda

pstrongKey features strongpul liUnique in its combination of serving as an introduction to spatial statistics and to modeling agricultural and ecological data using Rli liProvides exercises in each chapter to facilitate the book's use as a course textbook or for self-studyli liAdds new material on generalized additive models, point pattern analysis, and new methods of Bayesian analysis of spatial data.li liIncludes a completely revised chapter on the analysis of spatiotemporal data featuring recently introduced software and methodsli li pUpdates its coverage of R software including newly introduced packagesp li ulpemSpatial Data Analysis in Ecology and Agriculture Using R, 2nd Editionem provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology, agriculture, and environmental science. Readers have praised the book's practical coverage of spatial statistics, real-world examples, and user-friendly approach in presentin

Spatial Data Analysis in Ecology and Agriculture Using R | Plant Richard E. | Twarda | Twarda

bA hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework.b pToday many information sources--including sensor networks, financial markets, social networks, and healthcare monitoring--are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA Massive Online Analysis, a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. pThe book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow

Machine Learning for Data Streams | Bifet Albert | Twarda

bA hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework.bpToday many information sources--including sensor networks, financial markets, social networks, and healthcare monitoring--are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA Massive Online Analysis, a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations.ppThe book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow,

pThe increased use of non-inferiority analysis has been accompanied by a proliferation of research on the design and analysis of non-inferiority studies. Using examples from real clinical trials, strongDesign and Analysis of Non-Inferiority Trialsstrong brings together this body of research and confronts the issues involved in the design of a non-inferiority trial. Each chapter begins with a non-technical introduction, making the text easily understood by those without prior knowledge of this type of trial. ppppstrongTopics covered include strongpppul ppp liA variety of issues of non-inferiority trials, including multiple comparisons, missing data, analysis population, the use of safety margins, the internal consistency of non-inferiority inference, the use of surrogate endpoints, trial monitoring, and equivalence trialsli pliSpecific issues and analysis methods when the data are binary, continuous, and time-to-eventli pliThe history of non-inferiority trials and the design and conduct

Design and Analysis of Non | Inferiority Trials | Rothmann Mark D. | Paperback | Twarda

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pHow can music withstand the death and destruction brought on by war Global conflicts of the 20th century fundamentally transformed not only national boundaries, power relations, and global economies, but also the arts and culture of every nation involved. An important, unacknowledged aspect of these conflicts is that they have unique musical soundtracks. iMusic in World War IIi explores how music and sound took on radically different dimensions in the United States and Europe before, during, and after World War II. Additionally, the collection examines the impact of radio and film as the disseminators of the war's musical soundtrack. Contributors contend that the European and American soundtrack of World War II was largely one of escapism rather than the lofty, solemn, heroic, and celebratory mode of war music in the past. Furthermore, they explore the variety of experiences of populations forced from their homes and interned in civilian and POW camps in Europe and the United States, 

Music in World War II | Potter Pamela M. | Twarda

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