Today, certain computer software systems exist which surpass the computational ability of researchers when their mathematical techniques are applied to many areas of science and engineering. These computer systems can perform a large portion of the calculations seen in mathematical analysis. Despite this massive power, thousands of people use these systems as a routine resource for everyday calculations. These software programs are commonly called "Computer Algebra" systems. They have names such as MACSYMA, MAPLE, muMATH, REDUCE and SMP. They are receiving credit as a computational aid with in creasing regularity in articles in the scientific and engineering literature. When most people think about computers and scientific research these days, they imagine a machine grinding away, processing numbers arithmetically. It is not generally realized that, for a number of years, computers have been performing non-numeric computations. This means, for example, that one inputs an equa tion and obtains a closed form analytic answer. It is these Computer Algebra systems, their capabilities, and applications which are the subject of the papers in this volume."

Pro SharePoint 2013 Branding and Responsive Web Development is the definitive reference on the technologies, tools, and techniques needed for building responsive websites and applications with SharePoint 2013. The book focuses on solutions that provide the best browser experience for the myriad of devices, browsers, and screen orientations and resolutions. Web technology has changed considerably in the past few years. Microsoft has embraced the new generation of open standards represented by HTML5 and JavaScript, and these changes are represented in a fundamental shift in how SharePoint 2013 supports web content management and publishing. Authors Eric Overfield, Oscar Medina, Kanwal Khipple, and Rita Zhang join forces to dive into the new features and capabilities provided by SharePoint 2013 and combine them with the latest techniques in responsive web design and development to demonstrate how to build modern and progressive websites and applications. Pro SharePoint 2013 Branding and Responsive Web Development covers the following technologies: SharePoint 2013 Server Edition Office 365 SharePoint Online Expression Blend 2013 Napa Tools for Office and SharePoint Development Visual Studio 2012 HTML5 and CSS3 JavaScript, JQuery, JQuery UI, Modernizr, and the Bootstrap Framework SharePoint 2013 Client Object Model

Enterprise developers face several challenges when it comes to building serverless applications, such as integrating applications and building container images from source. With more than 60 practical recipes, this cookbook helps you solve these issues with Knative--the first serverless platform natively designed for Kubernetes. Each recipe contains detailed examples and exercises, along with a discussion of how and why it works. If you have a good understanding of serverless computing and Kubernetes core resources such as deployment, services, routes, and replicas, the recipes in this cookbook show you how to apply Knative in real enterprise application development. Authors Kamesh Sampath and Burr Sutter include chapters on autoscaling, build and eventing, observability, Knative on OpenShift, and more. With this cookbook, you'll learn how to: Efficiently build, deploy, and manage modern serverless workloads Apply Knative in real enterprise scenarios, including advanced eventing Monitor your Knative serverless applications effectively Integrate Knative with CI/CD principles, such as using pipelines for faster, more successful production deployments Deploy a rich ecosystem of enterprise integration patterns and connectors in Apache Camel K as Kubernetes and Knative components

A t the terminal seated, the answering tone: pond and temple bell. ODAY as in the past, statistical method is profoundly affected by T resources for numerical calculation and visual display. The main line of development of statistical methodology during the first half of this century was conditioned by, and attuned to, the mechanical desk calculator. Now statisticians may use electronic computers of various kinds in various modes, and the character of statistical science has changed accordingly. Some, but not all, modes of modern computation have a flexibility and immediacy reminiscent of the desk calculator. They preserve the virtues of the desk calculator, while immensely exceeding its scope. Prominent among these is the computer language and conversational computing system known by the initials APL. This book is addressed to statisticians. Its first aim is to interest them in using APL in their work-for statistical analysis of data, for numerical support of theoretical studies, for simulation of random processes. In Part A the language is described and illustrated with short examples of statistical calculations. Part B, presenting some more extended examples of statistical analysis of data, has also the further aim of suggesting the interplay of computing and theory that must surely henceforth be typical of the develop ment of statistical science."

S is a high-level language for manipulating, analysing and displaying

data. It forms the basis of two highly acclaimed and widely used data

analysis software systems, the commercial S-PLUS(r) and the Open

Source R. This book provides an in-depth guide to writing software in

the S language under either or both of those systems. It is intended

for readers who have some acquaintance with the S language and want to

know how to use it more effectively, for example to build re-usable

tools for streamlining routine data analysis or to implement new

statistical methods.

One of the outstanding strengths of the S language is the ease with

which it can be extended by users. S is a functional language, and

functions written by users are first-class objects treated in the same

way as functions provided by the system. S code is eminently readable

and so a good way to document precisely what algorithms were used, and

as much of the implementations are themselves written in S, they can be

studied as models and to understand their subtleties. The current

implementations also provide easy ways for S functions to call

compiled code written in C, Fortran and similar languages; this is

documented here in depth.

Increasingly S is being used for statistical or graphical analysis

within larger software systems or for whole vertical-market

applications. The interface facilities are most developed on

Windows(r) and these are covered with worked examples.

The authors have written the widely used Modern Applied Statistics

with S-PLUS, now in its third edition, and several software libraries

that enhance S-PLUS and R; these and the examples used in both books

are available on the Internet.

Dr. W.N. Venables is a senior Statistician with the CSIRO/CMIS

Environmetrics Project in Australia, having been at the Department of

Statistics, University of Adelaide for many years previously.

Professor B.D. Ripley holds the Chair of Applied Statistics at the

University of Oxford, and is the author of four other books on spatial

statistics, simulation, pattern recognition and neural networks. Both

authors are known and respected throughout the international S and R

communities, for their books, workshops, short courses, freely

available software and through their extensive contributions to the

S-news and R mailing lists.

Keith M. Ponting Speech Research Unit, DERA Malvern St. Andrew's Road, Great Malvern, Worcs. WR14 3PS, UK email: ponting

Nonlinear physics continues to be an area of dynamic modern research, with applications to physics, engineering, chemistry, mathematics, computer science, biology, medicine and economics. In this text extensive use is made of the Mathematica computer algebra system. No prior knowledge of Mathematica or programming is assumed. This book includes 33 experimental activities that are designed to deepen and broaden the reader's understanding of nonlinear physics. These activities are correlated with Part I, the theoretical framework of the text.

Rcpp is the glue that binds the power and versatility of R with the speed and efficiency of C++. With Rcpp, the transfer of data between R and C++ is nearly seamless, and high-performance statistical computing is finally accessible to most R users. Rcpp should be part of every statistician's toolbox. -- Michael Braun, MIT Sloan School of Management

"Seamless R and C++ integration with Rcpp" is simply a wonderful book. For anyone who uses C/C++ and R, it is an indispensable resource. The writing is outstanding. A huge bonus is the section on applications. This section covers the matrix packages Armadillo and Eigen and the GNU Scientific Library as well as RInside which enables you to use R inside C++. These applications are what most of us need to know to really do scientific programming with R and C++. I love this book. -- Robert McCulloch, University of Chicago Booth School of Business

Rcpp is now considered an essential package for anybody doing serious computational research using R. Dirk's book is an excellent companion and takes the reader from a gentle introduction to more advanced applications via numerous examples and efficiency enhancing gems. The book is packed with all you might have ever wanted to know about Rcpp, its cousins (RcppArmadillo, RcppEigen .etc.), modules, package development and sugar. Overall, this book is a must-have on your shelf. -- Sanjog Misra, UCLA Anderson School of Management

The Rcpp package represents a major leap forward for scientific computations with R. With very few lines of C++ code, one has R's data structures readily at hand for further computations in C++. Hence, high-level numerical programming can be made in C++ almost as easily as in R, but often with a substantial speed gain. Dirk is a crucial person in these developments, and his book takes the reader from the first fragile steps on to using the full Rcpp machinery. A very recommended book -- Soren Hojsgaard," "Department of Mathematical Sciences, Aalborg University, Denmark

"Seamless R and C ++ Integration with Rcpp" provides the first comprehensive introduction to Rcpp. Rcpp has become the most widely-used language extension for R, and is deployed by over one-hundred different CRAN and BioConductor packages. Rcpp permits users to pass scalars, vectors, matrices, list or entire R objects back and forth between R and C++ with ease. This brings the depth of the R analysis framework together with the power, speed, and efficiency of C++.

Dirk Eddelbuettel has been a contributor to CRAN for over a decade and maintains around twenty packages. He is the Debian/Ubuntu maintainer for R and other quantitative software, edits the CRAN Task Views for Finance and High-Performance Computing, is a co-founder of the annual R/Finance conference, and an editor of the Journal of Statistical Software. He holds a Ph.D. in Mathematical Economics from EHESS (Paris), and works in Chicago as a Senior Quantitative Analyst.

"

"Fast Compact Algorithms and Software for Spline Smoothing" investigates algorithmic alternatives for computing cubic smoothing splines when the amount of smoothing is determined automatically by minimizing the generalized cross-validation score. These algorithms are based on Cholesky factorization, QR factorization, or the fast Fourier transform. All algorithms are implemented in MATLAB and are compared based on speed, memory use, and accuracy. An overall best algorithm is identified, which allows very large data sets to be processed quickly on a personal computer.

Accessible to a general audience with some background in statistics and computing Many examples and extended case studies Illustrations using R and Rstudio A true blend of statistics and computer science -- not just a grab bag of topics from each

Grimmett, Geoffrey: Percolation and disordered systems.- Kesten, Harry: Aspects of first passage percolation. "

This edited survey book consists of 20 chapters showing application of Clifford algebra in quantum mechanics, field theory, spinor calculations, projective geometry, Hypercomplex algebra, function theory and crystallography. Many examples of computations performed with a variety of readily available software programs are presented in detail.

Accompanying the book, as with all TELOS sponsored publications, is an electronic component. In this case it is a DOS-Diskette produced by one of the coauthors, Paul Wellin. This diskette consists of "Mathematica "notebooks and packages which contain the codes for all examples and exercises in the book, as well as additional materials intended to extend many ideas covered in the text. It is of great value to teachers, students, and others using this book to learn how to effectively program with "Mathematica" .

This is the first book to show the capabilities of Microsoft Excel to teach biological and life sciences statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science problems. If understanding statistics isn't your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2007 for Biological and Life Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.

Mathematics plays an important role in many scientific and engineering disciplines. This book deals with the numerical solution of differential equations, a very important branch of mathematics. Our aim is to give a practical and theoretical account of how to solve a large variety of differential equations, comprising ordinary differential equations, initial value problems and boundary value problems, differential algebraic equations, partial differential equations and delay differential equations. The solution of differential equations using R is the main focus of this book. It is therefore intended for the practitioner, the student and the scientist, who wants to know how to use R for solving differential equations. However, it has been our goal that non-mathematicians should at least understand the basics of the methods, while obtaining entrance into the relevant literature that provides more mathematical background. Therefore, each chapter that deals with R examples is preceded by a chapter where the theory behind the numerical methods being used is introduced. In the sections that deal with the use of R for solving differential equations, we have taken examples from a variety of disciplines, including biology, chemistry, physics, pharmacokinetics. Many examples are well-known test examples, used frequently in the field of numerical analysis.

Algorithms for Computer Algebra is the first comprehensive textbook to be published on the topic of computational symbolic mathematics. The book first develops the foundational material from modern algebra that is required for subsequent topics. It then presents a thorough development of modern computational algorithms for such problems as multivariate polynomial arithmetic and greatest common divisor calculations, factorization of multivariate polynomials, symbolic solution of linear and polynomial systems of equations, and analytic integration of elementary functions. Numerous examples are integrated into the text as an aid to understanding the mathematical development. The algorithms developed for each topic are presented in a Pascal-like computer language. An extensive set of exercises is presented at the end of each chapter. Algorithms for Computer Algebra is suitable for use as a textbook for a course on algebraic algorithms at the third-year, fourth-year, or graduate level. Although the mathematical development uses concepts from modern algebra, the book is self-contained in the sense that a one-term undergraduate course introducing students to rings and fields is the only prerequisite assumed. The book also serves well as a supplementary textbook for a traditional modern algebra course, by presenting concrete applications to motivate the understanding of the theory of rings and fields.

This book deals with the performance analysis of closed queueing networks with general processing times and finite buffer spaces. It offers a detailed introduction to the problem and a comprehensive literature review. Two approaches to the performance of closed queueing networks are presented. One is an approximate decomposition approach, while the second is the first exact approach for finite-capacity networks with general processing times. In this Markov chain approach, queueing networks are analyzed by modeling the entire system as one Markov chain. As this approach is exact, it is well-suited both as a reference quantity for approximate procedures and as extension to other queueing networks. Moreover, for the first time, the exact distribution of the time between processing starts is provided.

Developments in both computer hardware and Perhaps the greatest impact has been felt by the software over the decades have fundamentally education community. Today, it is nearly changed the way people solve problems. impossible to find a college or university that has Technical professionals have greatly benefited not introduced mathematical computation in from new tools and techniques that have allowed some form, into the curriculum. Students now them to be more efficient, accurate, and creative have regular access to the amount of in their work. computational power that were available to a very exclusive set of researchers five years ago. This Maple V and the new generation of mathematical has produced tremendous pedagogical computation systems have the potential of challenges and opportunities. having the same kind of revolutionary impact as high-level general purpose programming Comparisons to the calculator revolution of the languages (e.g. FORTRAN, BASIC, C), 70's are inescapable. Calculators have application software (e.g. spreadsheets, extended the average person's ability to solve Computer Aided Design - CAD), and even common problems more efficiently, and calculators have had. Maple V has amplified our arguably, in better ways. Today, one needs at mathematical abilities: we can solve more least a calculator to deal with standard problems problems more accurately, and more often. In in life -budgets, mortgages, gas mileage, etc. specific disciplines, this amplification has taken For business people or professionals, the excitingly different forms.

Molchanov, S.: Lectures on random media.- Zeitouni, Ofer: Random walks in random environment.-den Hollander, Frank: Random polymers "

This brief offers a broad, yet concise, coverage of portfolio choice, containing both application-oriented and academic results, along with abundant pointers to the literature for further study. It cuts through many strands of the subject, presenting not only the classical results from financial economics but also approaches originating from information theory, machine learning and operations research. This compact treatment of the topic will be valuable to students entering the field, as well as practitioners looking for a broad coverage of the topic.

Automatic Graph Drawing is concerned with the layout of relational structures as they occur in Computer Science (Data Base Design, Data Mining, Web Mining), Bioinformatics (Metabolic Networks), Businessinformatics (Organization Diagrams, Event Driven Process Chains), or the Social Sciences (Social Networks).

In mathematical terms, such relational structures are modeled as graphs or more general objects such as hypergraphs, clustered graphs, or compound graphs. A variety of layout algorithms that are based on graph theoretical foundations have been developed in the last two decades and implemented in software systems.

After an introduction to the subject area and a concise treatment of the technical foundations for the subsequent chapters, this book features 14 chapters on state-of-the-art graph drawing software systems, ranging from general "tool boxes'' to customized software for various applications. These chapters are written by leading experts, they follow a uniform scheme and can be read independently from each other.

Note: This pocket book is available in several languages: English, German, French, Spanish, Dutch. This pocket guide is based on the PMBOK(R) Guide Fifth Edition. It contains a summary of the PMBOK(R) Guide, to provide a quick introduction as well as a structured overview of this framework for project management. This pocket guide deals with the key issues and themes within project management and the PMBOK(R) Guide as follows: - Key terms and definitions in the project management profession - A short overview of the activities of PMI Inc., the organization and its standards: PMBOK(R) Guide, Standard for Project Portfolio Management, Standard for Program Management and other standards. - The essentials of the Project Lifecycle and Organization. - What are the key project management knowledge areas and processes? Main target Group for this pocket guide is anyone with an interest in understanding the PMBOK(R) Guide framework or a systematic approach for project management. The book is also very useful for members of a project management team in a project environment using the PMBOK(R) Guide as a shared reference. A complete but concise description of the PMBOK(R) Guide, for anyone involved in projects or project management, for only 15,95!

This Handbook gives a comprehensive snapshot of a field at the intersection of mathematics and computer science with applications in physics, engineering and education. Reviews 67 software systems and offers 100 pages on applications in physics, mathematics, computer science, engineering chemistry and education.

Non-uniform random variate generation is an established research area in the intersection of mathematics, statistics and computer science. Although random variate generation with popular standard distributions have become part of every course on discrete event simulation and on Monte Carlo methods, the recent concept of universal (also called automatic or black-box) random variate generation can only be found dispersed in literature. This new concept has great practical advantages that are little known to most simulation practitioners. Being unique in its overall organization the book covers not only the mathematical and statistical theory, but also deals with the implementation of such methods. All algorithms introduced in the book are designed for practical use in simulation and have been coded and made available by the authors. Examples of possible applications of the presented algorithms (including option pricing, VaR and Bayesian statistics) are presented at the end of the book.

The theory of U-statistics goes back to the fundamental work of Hoeffding 1], in which he proved the central limit theorem. During last forty years the interest to this class of random variables has been permanently increasing, and thus, the new intensively developing branch of probability theory has been formed. The U-statistics are one of the universal objects of the modem probability theory of summation. On the one hand, they are more complicated "algebraically" than sums of independent random variables and vectors, and on the other hand, they contain essential elements of dependence which display themselves in the martingale properties. In addition, the U -statistics as an object of mathematical statistics occupy one of the central places in statistical problems. The development of the theory of U-statistics is stipulated by the influence of the classical theory of summation of independent random variables: The law of large num bers, central limit theorem, invariance principle, and the law of the iterated logarithm we re proved, the estimates of convergence rate were obtained, etc."