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Abstract Algebra An Inquiry-Based Approach

Abstract Algebra An Inquiry-Based Approach

Abstract Algebra: An Inquiry-Based Approach Second Edition not only teaches abstract algebra but also provides a deeper understanding of what mathematics is how it is done and how mathematicians think. The second edition of this unique flexible approach builds on the success of the first edition. The authors offer an emphasis on active learning helping students learn algebra by gradually building both their intuition and their ability to write coherent proofs in context. The goals for this text include: Allowing the flexibility to begin the course with either groups or rings. Introducing the ideas behind definitions and theorems to help students develop intuition. Helping students understand how mathematics is done. Students will experiment through examples make conjectures and then refine or prove their conjectures. Assisting students in developing their abilities to effectively communicate mathematical ideas. Actively involving students in realizing each of these goals through in-class and out-of-class activities common in-class intellectual experiences and challenging problem sets. Changes in the Second Edition Streamlining of introductory material with a quicker transition to the material on rings and groups. New investigations on extensions of fields and Galois theory. New exercises added and some sections reworked for clarity. More online Special Topics investigations and additional Appendices including new appendices on other methods of proof and complex roots of unity. Encouraging students to do mathematics and be more than passive learners this text shows students the way mathematics is developed is often different than how it is presented; definitions theorems and proofs do not simply appear fully formed; mathematical ideas are highly interconnected; and in abstract algebra there is a considerable amount of intuition to be found. | Abstract Algebra An Inquiry-Based Approach

GBP 89.99
1

The New S Language

The New S Language

This book provides documentation for a new version of the S system released in 1988. The new S enhances the features that have made S popular: interactive computing flexible graphics data management and a large collection of functions. The new S features make possible new applications and higher-level programming including a single unified language user defined functions as first-class objects symbolic computations more accurate numerical calculations and a new approach to graphics. S now provides direct interfaces to the poowerful tool of the UNIX operating system and to algorithms implemented in Fortran and C. | The New S Language

GBP 325.00
1

Decision Support System and Automated Negotiations

Decision Support System and Automated Negotiations

Decision support systems are developed for integrated pest and disease management and nutrition management using open-source technologies as java android and low-cost hardware devices like Arduino micro controller. This text discusses the techniques to convert agricultural knowledge in the context of ontology and assist grape growers by providing this knowledge through decision support system. The key features of the book are: Presents the design & development of an ontology-based decision support system for integrated crop management. Discusses the techniques to convert agricultural knowledge in text to ontology. Focuses on an extensive study of various e-Negotiation protocols for automated negotiations Provides an architecture for predicting the opponent’s behaviour and various factors which affect the process of negotiation. The text is primarily written for graduate students professionals and academic researchers working in the fields of computer science and engineering agricultural science and information technology. | Decision Support System and Automated Negotiations

GBP 89.99
1

Probability and Statistics for Engineering and the Sciences with Modeling using R

Probability and Statistics for Engineering and the Sciences with Modeling using R

Probability and statistics courses are more popular than ever. Regardless of your major or your profession you will most likely use concepts from probability and statistics often in your career. The primary goal behind this book is offering the flexibility for instructors to build most undergraduate courses upon it. This book is designed for either a one-semester course in either introductory probability and statistics (not calculus-based) and/or a one-semester course in a calculus-based probability and statistics course. The book focuses on engineering examples and applications while also including social sciences and more examples. Depending on the chapter flows a course can be tailored for students at all levels and background. Over many years of teaching this course the authors created problems based on real data student projects and labs. Students have suggested these enhance their experience and learning. The authors hope to share projects and labs with other instructors and students to make the course more interesting for both. R is an excellent platform to use. This book uses R with real data sets. The labs can be used for group work in class or for self-directed study. These project labs have been class-tested for many years with good results and encourage students to apply the key concepts and use of technology to analyze and present results. | Probability and Statistics for Engineering and the Sciences with Modeling using R

GBP 89.99
1

Mixed Effects Models for Complex Data

Mixed Effects Models for Complex Data

Although standard mixed effects models are useful in a range of studies other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts missing data measurement errors censoring and outliers. For each class of mixed effects model the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data the book introduces linear mixed effects (LME) models generalized linear mixed models (GLMMs) nonlinear mixed effects (NLME) models and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values measurement errors censoring and outliers. Self-contained coverage of specific topicsSubsequent chapters delve more deeply into missing data problems covariate measurement errors and censored responses in mixed effects models. Focusing on incomplete data the book also covers survival and frailty models joint models of survival and longitudinal data robust methods for mixed effects models marginal generalized estimating equation (GEE) models for longitudinal or clustered data and Bayesian methods for mixed effects models. Background materialIn the appendix the author provides background information such as likelihood theory the Gibbs sampler rejection and importance sampling methods numerical integration methods optimization methods bootstrap and matrix algebra. Failure to properly address missing data measurement errors and other issues in statistical analyses can lead

GBP 59.99
1

Handbook of Empirical Economics and Finance

Handbook of Empirical Economics and Finance

Handbook of Empirical Economics and Finance explores the latest developments in the analysis and modeling of economic and financial data. Well-recognized econometric experts discuss the rapidly growing research in economics and finance and offer insight on the future direction of these fields. Focusing on micro models the first group of chapters describes the statistical issues involved in the analysis of econometric models with cross-sectional data often arising in microeconomics. The book then illustrates time series models that are extensively used in empirical macroeconomics and finance. The last set of chapters explores the types of panel data and spatial models that are becoming increasingly significant in analyzing complex economic behavior and policy evaluations. This handbook brings together both background material and new methodological and applied results that are extremely important to the current and future frontiers in empirical economics and finance. It emphasizes inferential issues that transpire in the analysis of cross-sectional time series and panel data-based empirical models in economics finance and related disciplines.

GBP 69.99
1

Spectral Theory and Nonlinear Functional Analysis

Spectral Theory and Nonlinear Functional Analysis

This Research Note addresses several pivotal problems in spectral theory and nonlinear functional analysis in connection with the analysis of the structure of the set of zeroes of a general class of nonlinear operators. It features the construction of an optimal algebraic/analytic invariant for calculating the Leray-Schauder degree new methods for solving nonlinear equations in Banach spaces and general properties of components of solutions sets presented with minimal use of topological tools. The author also gives several applications of the abstract theory to reaction diffusion equations and systems. The results presented cover a thirty-year period and include recent unpublished findings of the author and his coworkers. Appealing to a broad audience Spectral Theory and Nonlinear Functional Analysis contains many important contributions to linear algebra linear and nonlinear functional analysis and topology and opens the door for further advances.

GBP 175.00
1

Project-Based R Companion to Introductory Statistics

Project-Based R Companion to Introductory Statistics

Project-Based R Companion to Introductory Statistics is envisioned as a companion to a traditional statistics or biostatistics textbook with each chapter covering traditional topics such as descriptive statistics regression and hypothesis testing. However unlike a traditional textbook each chapter will present its material using a complete step-by-step analysis of a real publicly available dataset with an emphasis on the practical skills of testing assumptions data exploration and forming conclusions. The chapters in the main body of the book include a worked example showing the R code used at each step followed by a multi-part project for students to complete. These projects which could serve as alternatives to traditional discrete homework problems will illustrate how to put the pieces together and conduct a complete start-to-finish data analysis using the R statistical software package. At the end of the book there are several projects that require the use of multiple statistical techniques that could be used as a take-home final exam or final project for a class. Key features of the text: Organized in chapters focusing on the same topics found in typical introductory statistics textbooks (descriptive statistics regression two-way tables hypothesis testing for means and proportions etc. ) so instructors can easily pair this supplementary material with course plans Includes student projects for each chapter which can be assigned as laboratory exercises or homework assignments to supplement traditional homework Features real-world datasets from scientific publications in the fields of history pop culture business medicine and forensics for students to analyze Allows students to gain experience working through a variety of statistical analyses from start to finish The book is written at the undergraduate level to be used in an introductory statistical methods course or subject-specific research methods course such as biostatistics or research methods for psychology or business analytics. Author After a 10-year career as a research biostatistician in the Department of Ophthalmology and Visual Sciences at the University of Wisconsin-Madison Chelsea Myers teaches statistics and biostatistics at Rollins College and Valencia College in Central Florida. She has authored or co-authored more than 30 scientific papers and presentations and is the creator of the MCAT preparation website MCATMath. com.

GBP 48.99
1

Introductory Analysis An Inquiry Approach

Introductory Analysis An Inquiry Approach

Introductory Analysis: An Inquiry Approach aims to provide a self-contained inquiry-oriented approach to undergraduate-level real analysis. The presentation of the material in the book is intended to be inquiry-oriented' in that as each major topic is discussed details of the proofs are left to the student in a way that encourages an active approach to learning. The book is self-contained in two major ways: it includes scaffolding (i. e. brief guiding prompts marked as Key Steps in the Proof) for many of the theorems. Second it includes preliminary material that introduces students to the fundamental framework of logical reasoning and proof-writing techniques. Students will be able to use the guiding prompts (and refer to the preliminary work) to develop their proof-writing skills. FeaturesStructured in such a way that approximately one week of class can be devoted to each chapterSuitable as a primary text for undergraduates or as a supplementary text for some postgraduate coursesStrikes a unique balance between enquiry-based learning and more traditional approaches to teaching | Introductory Analysis An Inquiry Approach

GBP 44.99
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Handbook of Educational Measurement and Psychometrics Using R

Handbook of Educational Measurement and Psychometrics Using R

Currently there are many introductory textbooks on educational measurement and psychometrics as well as R. However there is no single book that covers important topics in measurement and psychometrics as well as their applications in R. The Handbook of Educational Measurement and Psychometrics Using R covers a variety of topics including classical test theory; generalizability theory; the factor analytic approach in measurement; unidimensional multidimensional and explanatory item response modeling; test equating; visualizing measurement models; measurement invariance; and differential item functioning. This handbook is intended for undergraduate and graduate students researchers and practitioners as a complementary book to a theory-based introductory or advanced textbook in measurement. Practitioners and researchers who are familiar with the measurement models but need to refresh their memory and learn how to apply the measurement models in R would find this handbook quite fulfilling. Students taking a course on measurement and psychometrics will find this handbook helpful in applying the methods they are learning in class. In addition instructors teaching educational measurement and psychometrics will find our handbook as a useful supplement for their course.

GBP 44.99
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Accelerated Life Models Modeling and Statistical Analysis

Accelerated Life Models Modeling and Statistical Analysis

The authors of this monograph have developed a large and important class of survival analysis models that generalize most of the existing models. In a unified systematic presentation this monograph fully details those models and explores areas of accelerated life testing usually only touched upon in the literature. Accelerated Life Models: Modeling and Statistical Analysis presents models methods of data collection and statistical analysis for failure-time regression data in accelerated life testing and for degradation data with explanatory variables. In addition to the classical results the authors devote considerable attention to models with time-varying explanatory variables and to methods of semiparametric estimation. They also examine the simultaneous analysis of degradation and failure-time data when the intensities of failure in different modes depend on the level of degradation and the values of explanatory variables. The authors avoid technical details by explaining the ideas and referring to resources where thorough analysis can be found. Whether used for teaching research or general reference Accelerated Life Models: Modeling and Statistical Analysis provides new and known models and modern methods of accelerated life data analysis. | Accelerated Life Models Modeling and Statistical Analysis

GBP 59.99
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Data Classification Algorithms and Applications

Data Classification Algorithms and Applications

Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition database data mining and machine learning. Addressing the work of these different communities in a unified way Data Classification: Algorithms and Applications explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains including text multimedia social network and biological data. This comprehensive book focuses on three primary aspects of data classification:Methods: The book first describes common techniques used for classification including probabilistic methods decision trees rule-based methods instance-based methods support vector machine methods and neural networks. Domains: The book then examines specific methods used for data domains such as multimedia text time-series network discrete sequence and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm. Variations: The book concludes with insight on variations of the classification process. It discusses ensembles rare-class learning distance function learning active learning visual learning transfer learning and semi-supervised learning as well as evaluation aspects of classifiers. | Data Classification Algorithms and Applications

GBP 44.99
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Matrix Theory From Generalized Inverses to Jordan Form

Matrix Theory From Generalized Inverses to Jordan Form

In 1990 the National Science Foundation recommended that every college mathematics curriculum should include a second course in linear algebra. In answer to this recommendation Matrix Theory: From Generalized Inverses to Jordan Form provides the material for a second semester of linear algebra that probes introductory linear algebra concepts while also exploring topics not typically covered in a sophomore-level class. Tailoring the material to advanced undergraduate and beginning graduate students the authors offer instructors flexibility in choosing topics from the book. The text first focuses on the central problem of linear algebra: solving systems of linear equations. It then discusses LU factorization derives Sylvester's rank formula introduces full-rank factorization and describes generalized inverses. After discussions on norms QR factorization and orthogonality the authors prove the important spectral theorem. They also highlight the primary decomposition theorem Schur's triangularization theorem singular value decomposition and the Jordan canonical form theorem. The book concludes with a chapter on multilinear algebra. With this classroom-tested text students can delve into elementary linear algebra ideas at a deeper level and prepare for further study in matrix theory and abstract algebra. | Matrix Theory From Generalized Inverses to Jordan Form

GBP 59.99
1

Analyzing Health Data in R for SAS Users

Analyzing Health Data in R for SAS Users

Analyzing Health Data in R for SAS Users is aimed at helping health data analysts who use SAS accomplish some of the same tasks in R. It is targeted to public health students and professionals who have a background in biostatistics and SAS software but are new to R. For professors it is useful as a textbook for a descriptive or regression modeling class as it uses a publicly-available dataset for examples and provides exercises at the end of each chapter. For students and public health professionals not only is it a gentle introduction to R but it can serve as a guide to developing the results for a research report using R software. Features:Gives examples in both SAS and RDemonstrates descriptive statistics as well as linear and logistic regressionProvides exercise questions and answers at the end of each chapterUses examples from the publicly available dataset Behavioral Risk Factor Surveillance System (BRFSS) 2014 dataGuides the reader on producing a health analysis that could be published as a research reportGives an example of hypothesis-driven data analysisProvides examples of plots with a color insert

GBP 44.99
1

Discovering Evolution Equations with Applications Volume 1-Deterministic Equations

Discovering Evolution Equations with Applications Volume 1-Deterministic Equations

Discovering Evolution Equations with Applications: Volume 1-Deterministic Equations provides an engaging accessible account of core theoretical results of evolution equations in a way that gradually builds intuition and culminates in exploring active research. It gives nonspecialists even those with minimal prior exposure to analysis the foundation to understand what evolution equations are and how to work with them in various areas of practice. After presenting the essentials of analysis the book discusses homogenous finite-dimensional ordinary differential equations. Subsequent chapters then focus on linear homogenous abstract nonhomogenous linear semi-linear functional Sobolev-type neutral delay and nonlinear evolution equations. The final two chapters explore research topics including nonlocal evolution equations. For each class of equations the author develops a core of theoretical results concerning the existence and uniqueness of solutions under various growth and compactness assumptions continuous dependence upon initial data and parameters convergence results regarding the initial data and elementary stability results. By taking an applications-oriented approach this self-contained conversational-style book motivates readers to fully grasp the mathematical details of studying evolution equations. It prepares newcomers to successfully navigate further research in the field. | Discovering Evolution Equations with Applications Volume 1-Deterministic Equations

GBP 74.99
1

Self-Similarity and Beyond Exact Solutions of Nonlinear Problems

Self-Similarity and Beyond Exact Solutions of Nonlinear Problems

Nonlinearity plays a major role in the understanding of most physical chemical biological and engineering sciences. Nonlinear problems fascinate scientists and engineers but often elude exact treatment. However elusive they may be the solutions do exist-if only one perseveres in seeking them out. Self-Similarity and Beyond presents a myriad of approaches to finding exact solutions for a diversity of nonlinear problems. These include group-theoretic methods the direct method of Clarkson and Kruskal traveling waves hodograph methods balancing arguments embedding special solutions into a more general class and the infinite series approach. The author's approach is entirely constructive. Numerical solutions either motivate the analysis or confirm it therefore they are treated alongside the analysis whenever possible. Many examples drawn from real physical situations-primarily fluid mechanics and nonlinear diffusion-illustrate and emphasize the central points presented. Accessible to a broad base of readers Self-Similarity and Beyond illuminates a variety of productive methods for meeting the challenges of nonlinearity. Researchers and graduate students in nonlinearity partial differential equations and fluid mechanics along with mathematical physicists and numerical analysts will re-discover the importance of exact solutions and find valuable additions to their mathematical toolkits. | Self-Similarity and Beyond Exact Solutions of Nonlinear Problems

GBP 56.99
1

Flexible Imputation of Missing Data Second Edition

Flexible Imputation of Missing Data Second Edition

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes like deletion or mean imputation only work under highly restrictive conditions which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data. | Flexible Imputation of Missing Data Second Edition

GBP 38.99
1

Field Guide to Compelling Analytics

Field Guide to Compelling Analytics

Field Guide to Compelling Analytics is written for Analytics Professionals (APs) who want to increase their probability of success in implementing analytical solutions. In the past soft skills such as presentation and persuasive writing techniques have been the extent of teaching junior APs how to effectively communicate the value of analytical products. However there are other aspects to success such as trust and experience that may play a more important role in convincing fellow APs clients advisors and leadership groups that their analytic solutions will work. This book introduces the formula ‘Analytics + Trust + Communication + Experience > Convince Them’ to illustrate an AP’s ability to convince a stakeholder. The ‘Convince Me’ stakeholders might be an analytics team member team lead decision-maker or senior leader that are either internal or external to the AP’s organization. Whoever they are this formula represents a concise digestible and above all practical means to increase the likelihood that you will be able to persuade them of the value of your analytical product. Features Includes insight questions to support class discussion Written in broadly non-mathematical terms designed to be accessible to any level of student or practicing AP to read understand and implement the concepts Each section introduces the ideas through real-life case studies

GBP 48.99
1

Metabolomics Practical Guide to Design and Analysis

Metabolomics Practical Guide to Design and Analysis

Metabolomics is the scientific study of the chemical processes in a living system environment and nutrition. It is a relatively new omics science but the potential applications are wide including medicine personalized medicine and intervention studies food and nutrition plants agriculture and environmental science. The topics presented and discussed in this book are based on the European Molecular Biology Organization (EMBO) practical courses in metabolomics bioinformatics taught to those working in the field from masters to postgraduate students PhDs postdoctoral and early PIs. The book covers the basics and fundamentals of data acquisition and analytical technologies but the primary focus is data handling and data analysis. The mentioning and usage of a particular data analysis tool has been avoided; rather the focus is on the concepts and principles of data processing and analysis. The material has been class-tested and includes lots of examples computing and exercises. Key Features:Provides an overview of qualitative /quantitative methods in metabolomicsOffers an introduction to the key concepts of metabolomics including experimental design and technologyCovers data handling processing analysis data standards and sharingContains lots of examples to illustrate the topicsIncludes contributions from some of the leading researchers in the field of metabolomics with extensive teaching experiences | Metabolomics Practical Guide to Design and Analysis

GBP 44.99
1

Discrete Mathematics with Ducks

Discrete Mathematics with Ducks

Discrete Mathematics with Ducks Second Edition is a gentle introduction for students who find the proofs and abstractions of mathematics challenging. At the same time it provides stimulating material that instructors can use for more advanced students. The first edition was widely well received with its whimsical writing style and numerous exercises and materials that engaged students at all levels. The new expanded edition continues to facilitate effective and active learning. It is designed to help students learn about discrete mathematics through problem-based activities. These are created to inspire students to understand mathematics by actively practicing and doing which helps students better retain what they’ve learned. As such each chapter contains a mixture of discovery-based activities projects expository text in-class exercises and homework problems. The author’s lively and friendly writing style is appealing to both instructors and students alike and encourages readers to learn. The book’s light-hearted approach to the subject is a guiding principle and helps students learn mathematical abstraction. Features:The book’s Try This! sections encourage students to construct components of discussed concepts theorems and proofsProvided sets of discovery problems and illustrative examples reinforce learningBonus sections can be used by instructors as part of their regular curriculum for projects or for further study

GBP 38.99
1

Introduction to Functional Equations

Introduction to Functional Equations

Introduction to Functional Equations grew out of a set of class notes from an introductory graduate level course at the University of Louisville. This introductory text communicates an elementary exposition of valued functional equations where the unknown functions take on real or complex values. In order to make the presentation as manageable as possible for students from a variety of disciplines the book chooses not to focus on functional equations where the unknown functions take on values on algebraic structures such as groups rings or fields. However each chapter includes sections highlighting various developments of the main equations treated in that chapter. For advanced students the book introduces functional equations in abstract domains like semigroups groups and Banach spaces. Functional equations covered include: Cauchy Functional Equations and Applications The Jensen Functional Equation Pexider's Functional Equation Quadratic Functional Equation D'Alembert Functional Equation Trigonometric Functional Equations Pompeiu Functional Equation Hosszu Functional Equation Davison Functional Equation Abel Functional Equation Mean Value Type Functional Equations Functional Equations for Distance Measures The innovation of solving functional equations lies in finding the right tricks for a particular equation. Accessible and rooted in current theory methods and research this book sharpens mathematical competency and prepares students of mathematics and engineering for further work in advanced functional equations.

GBP 69.99
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Multilevel Modeling Using R

Multilevel Modeling Using R

Like its bestselling predecessor Multilevel Modeling Using R Second Edition provides the reader with a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. New in the Second Edition: Features the use of lmer (instead of lme) and including the most up to date approaches for obtaining confidence intervals for the model parameters. Discusses measures of R2 (the squared multiple correlation coefficient) and overall model fit. Adds a chapter on nonparametric and robust approaches to estimating multilevel models including rank based heavy tailed distributions and the multilevel lasso. Includes a new chapter on multivariate multilevel models. Presents new sections on micro-macro models and multilevel generalized additive models. This thoroughly updated revision gives the reader state-of-the-art tools to launch their own investigations in multilevel modeling and gain insight into their research. About the Authors: W. Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at Ball State University. Jocelyn E. Bolin is a Professor in the Department of Educational Psychology at Ball State University. Ken Kelley is the Edward F. Sorin Society Professor of IT Analytics and Operations and the Associate Dean for Faculty and Research for the Mendoza College of Business at the University of Notre Dame.

GBP 56.99
1

The Cloud Computing Book The Future of Computing Explained

The Cloud Computing Book The Future of Computing Explained

This latest textbook from bestselling author Douglas E. Comer is a class-tested book providing a comprehensive introduction to cloud computing. Focusing on concepts and principles rather than commercial offerings by cloud providers and vendors The Cloud Computing Book: The Future of Computing Explained gives readers a complete picture of the advantages and growth of cloud computing cloud infrastructure virtualization automation and orchestration and cloud-native software design. The book explains real and virtual data center facilities including computation (e. g. servers hypervisors Virtual Machines and containers) networks (e. g. leaf-spine architecture VLANs and VxLAN) and storage mechanisms (e. g. SAN NAS and object storage). Chapters on automation and orchestration cover the conceptual organization of systems that automate software deployment and scaling. Chapters on cloud-native software cover parallelism microservices MapReduce controller-based designs and serverless computing. Although it focuses on concepts and principles the book uses popular technologies in examples including Docker containers and Kubernetes. Final chapters explain security in a cloud environment and the use of models to help control the complexity involved in designing software for the cloud. The text is suitable for a one-semester course for software engineers who want to understand cloud and for IT managers moving an organization’s computing to the cloud. | The Cloud Computing Book The Future of Computing Explained

GBP 44.99
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Automata and Computability A Programmer's Perspective

Automata and Computability A Programmer's Perspective

Automata and Computability is a class-tested textbook which provides a comprehensive and accessible introduction to the theory of automata and computation. The author uses illustrations engaging examples and historical remarks to make the material interesting and relevant for students. It incorporates modern/handy ideas such as derivative-based parsing and a Lambda reducer showing the universality of Lambda calculus. The book also shows how to sculpt automata by making the regular language conversion pipeline available through a simple command interface. A Jupyter notebook will accompany the book to feature code YouTube videos and other supplements to assist instructors and studentsFeatures Uses illustrations engaging examples and historical remarks to make the material accessible Incorporates modern/handy ideas such as derivative-based parsing and a Lambda reducer showing the universality of Lambda calculus Shows how to sculpt automata by making the regular language conversion pipeline available through simple command interface Uses a mini functional programming (FP) notation consisting of lambdas maps filters and set comprehension (supported in Python) to convey math through PL constructs that are succinct and resemble math Provides all concepts are encoded in a compact Functional Programming code that will tesselate with Latex markup and Jupyter widgets in a document that will accompany the books. Students can run code effortlessly. All the code can be accessed here. | Automata and Computability A Programmer's Perspective

GBP 39.99
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Approximate Analytical Methods for Solving Ordinary Differential Equations

Approximate Analytical Methods for Solving Ordinary Differential Equations

Approximate Analytical Methods for Solving Ordinary Differential Equations (ODEs) is the first book to present all of the available approximate methods for solving ODEs eliminating the need to wade through multiple books and articles. It covers both well-established techniques and recently developed procedures including the classical series solution method diverse perturbation methods pioneering asymptotic methods and the latest homotopy methods. The book is suitable not only for mathematicians and engineers but also for biologists physicists and economists. It gives a complete description of the methods without going deep into rigorous mathematical aspects. Detailed examples illustrate the application of the methods to solve real-world problems. The authors introduce the classical power series method for solving differential equations before moving on to asymptotic methods. They next show how perturbation methods are used to understand physical phenomena whose mathematical formulation involves a perturbation parameter and explain how the multiple-scale technique solves problems whose solution cannot be completely described on a single timescale. They then describe the Wentzel Kramers and Brillown (WKB) method that helps solve both problems that oscillate rapidly and problems that have a sudden change in the behavior of the solution function at a point in the interval. The book concludes with recent nonperturbation methods that provide solutions to a much wider class of problems and recent analytical methods based on the concept of homotopy of topology.

GBP 59.99
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