This comprehensive and stimulating introduction to Matlab, a computer language now widely used for technical computing, is based on an introductory course held at Qian Weichang College, Shanghai University, in the fall of 2014. Teaching and learning a substantial programming language aren't always straightforward tasks. Accordingly, this textbook is not meant to cover the whole range of this high-performance technical programming environment, but to motivate first- and second-year undergraduate students in mathematics and computer science to learn Matlab by studying representative problems, developing algorithms and programming them in Matlab. While several topics are taken from the field of scientific computing, the main emphasis is on programming. A wealth of examples are completely discussed and solved, allowing students to learn Matlab by doing: by solving problems, comparing approaches and assessing the proposed solutions.

"Logistic Core Operations with SAP" not only provides an overview of core logistics processes and functionality-it also shows how SAP's Business Suite covers logistic core operations, what features are supported, and which systems can be used to implement end-to-end processes in the following logistic core disciplines: Procurement, Distribution, Transportation, Warehouse Logistics and Inventory Management, and Compliance and Reporting. In this context the authors not only explain their integration, the organizational set-up, and master data, but also which solution fits best for a particular business need. This book serves as a solid foundation for understanding SAP software. No matter whether you are a student or a manager involved in an SAP implementation, the authors go far beyond traditional function and feature descriptions, helping you ask the right questions, providing answers, and making recommendations. The book assists you in understanding SAP terminology, concepts and technological components as well as their closed-loop integration. Written in a clear, straight-forward style and using practical examples, it contains valuable tips, illustrative screenshots and flowcharts, as well as best practices-showing how business requirements are mapped into software functionality.

Master the SAP product ecosystem, the client environment, and the feasibility of implementing critical business process with the required technical and functional configuration. SAP Project Management Pitfalls is the first book to provide you with real examples of the pitfalls that you can avoid, providing you with a road-map to a successful implementation. Jay Kay, a SAP Program Manager for Capgemini, first takes a deep dive into common pitfalls in implementing SAP ERP projects in a complex IT landscape. You will learn about the potential causes of failures, study a selection of relevant project implementation case studies in the area, and see a range of possible countermeasures. Jay Kay also provides background on each - the significance of each implementation area, its relevance to a service company that implements SAP projects, and the current state of research. Key highlights of the book: Tools and techniques for project planning and templates for allocating resources Industry standards and innovations in SAP implementation projects in the form of standard solutions aimed at successful implementation Managing SAP system ECC upgrades, EHP updates and project patches Learn effective ways to implement robust SAP release management practices (change management, BAU) Wearing a practitioner's insight, Jay Kay explores the relevance of each failed implementation scenario and how to support your company or clients to succeed in a SAP implementation. There are many considerations when implementing SAP, but as you will learn, knowledge, insight, and effective tools to mitigate risks can take you to a successful implementation project.

Take a deep dive into SAP Fiori and discover Fiori architecture, Fiori landscape installation, Fiori standard applications, Fiori Launchpad configuration, tools for developing Fiori applications and extending standard Fiori applications. You will learn: Fiori architecture and its applications Setting up a Fiori landscape and Fiori Launchpad Configuring, customizing and enhancing standard Fiori applications Developing Fiori native applications for mobile Internet of Things-based custom Fiori applications with the HANA cloud platform Bince Mathew, a SAP mobility expert working for an MNC in Germany, shows you how SAP Fiori, based on HTML5 technology, addresses the most widely and frequently used SAP transactions like purchase order approvals, sales order creation, information lookup, and self-service tasks. This set of HTML5 apps provides a very simple and accessible experience across desktops, tablets, and smartphones. Prerequisites and steps for setting up a Fiori landscape and Launchpad Fiori standard application configuration Extending and customizing standard Fiori applications Developing custom Fiori applications from scratch Building custom Fiori applications for Internet Of Things using HANA cloud Fiori apps with cordova and kapsel plugins

Gesch ftsprozesse in Unternehmen sind h ufig ereignisgesteuert. Denn im Gesch ftsumfeld treten Ereignisse auf, auf die angemessen und m glichst in Echtzeit reagiert werden muss, etwa in Sensornetzwerken oder im automatischen Wertpapierhandel. Event-Driven Architecture (EDA) ist ein neues Paradigma der Softwarearchitektur, das auf der Verarbeitung von Ereignissen beruht. Das Buch diskutiert die Grundprinzipien von EDA, f hrt in die wichtigsten Konzepte der Ereignisverarbeitung ein und veranschaulicht deren Umsetzung anhand einer Fallstudie.

In der deutschen Volkswirtschaft entstehen ca. 90% der Wertschopfung durch Informationsverarbeitung und Kommunikation an elektronisch unterstutzten Arbeitsplatzen. Aspekte wie Arbeitsorganisation, Kommunikationsprozessgestaltung, Ergonomie, Buroraumgestaltung, Motivation, Fuhrung, Strategie und I&K-Ausstattung beeinflussen das komplexe System Arbeitsplatz und damit die mogliche Wertschopfung.

In diesem Buch werden die wesentlichen Aspekte des Themas Arbeitsplatzgestaltung betrachtet: Nach einer Klarung der Bedeutung der Arbeits(platz)gestaltung fur die Wertschopfung eines Unternehmens werden die kurz- und mittelfristig relevanten optionalen Konzepte elektronischer Kommunikation und Zusammenarbeit vorgestellt. Alle diskutierten Konzepte werden mit Fallstudien abgeschlossen, die dem Leser aufzeigen, welche Bedeutung das jeweilige Konzept fur sein Unternehmen haben konnte. Abschliessend werden die Themen diskutiert, mit denen sich jeder zwangslaufig beschaftigen muss, der zum Thema Arbeits(platz)gestaltung Verantwortung tragt. Dabei werden Empfehlungen zu Knowledge Management und Prozessoptimierung gegeben."

Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.

Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. It has been completely re-written since the first edition to make use of the latest packages and features in R version 3. R is a powerful open-source language and programming environment for statistics and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets, with a constantly evolving ecosystem of packages providing new functionality for data analysis. R has also become popular in commercial use at companies such as Microsoft, Google, and Oracle. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for data analysis and research.What You Will Learn: How to acquire and install R Hot to import and export data and scripts How to analyze data and generate graphics How to program in R to write custom functions Hot to use R for interactive statistical explorations How to conduct bootstrapping and other advanced techniques

The development of software system with acceptable level of reliability and quality within available time frame and budget becomes a challenging objective. This objective could be achieved to some extent through early prediction of number of faults present in the software, which reduces the cost of development as it provides an opportunity to make early corrections during development process. The book presents an early software reliability prediction model that will help to grow the reliability of the software systems by monitoring it in each development phase, i.e. from requirement phase to testing phase. Different approaches are discussed in this book to tackle this challenging issue. An important approach presented in this book is a model to classify the modules into two categories (a) fault-prone and (b) not fault-prone. The methods presented in this book for assessing expected number of faults present in the software, assessing expected number of faults present at the end of each phase and classification of software modules in fault-prone or no fault-prone category are easy to understand, develop and use for any practitioner. The practitioners are expected to gain more information about their development process and product reliability, which can help to optimize the resources used.

This book presents multivariate time series methods for the analysis and optimal control of feedback systems. Although ships' autopilot systems are considered through the entire book, the methods set forth in this book can be applied to many other complicated, large, or noisy feedback control systems for which it is difficult to derive a model of the entire system based on theory in that subject area. The basic models used in this method are the multivariate autoregressive model with exogenous variables (ARX) model and the radial bases function net-type coefficients ARX model. The noise contribution analysis can then be performed through the estimated autoregressive (AR) model and various types of autopilot systems can be designed through the state-space representation of the models. The marine autopilot systems addressed in this book include optimal controllers for course-keeping motion, rolling reduction controllers with rudder motion, engine governor controllers, noise adaptive autopilots, route-tracking controllers by direct steering, and the reference course-setting approach. The methods presented here are exemplified with real data analysis and experiments on real ships. This book is highly recommended to readers who are interested in designing optimal or adaptive controllers not only of ships but also of any other complicated systems under noisy disturbance conditions.

SAP ERP modules are notoriously hard to configure and use effectively without a lot of practice and experience. But as SAP ERP Financial Accounting and Controlling: Configuration and Use Management shows, it doesn't have to be so difficult. The book takes a systematic approach that leads SAP Financial Accounting and Controlling (FICO) users step by step through configuring and using all the program's facets. This approach makes configuration complexities manageable. The book's author-SAP expert, trainer, and accountant Andrew Okungbowa-ensures that both you and your end users are up and running quickly and confidently with FICO. He also provides sound and tested procedures that ensure your implementation works without error. SAP ERP Financial Accounting and Controlling: Configuration and Use Management is in fact the most comprehensive and easy-to-follow SAP FICO configuration book in the market. It incorporates a hands-on approach, with hundreds of screen shots and practical examples, that allows a person without prior configuration training to make SAP FICO ready for use in the enterprise. You'll find that you don't need to be a rocket scientist to grasp the concepts explained and apply them to your work-even when the finances are complicated, such as with the ins and outs of taxes, currency conversions, or special general ledger entries such as down payments or bills of exchange. Providing an in-depth coverage of both configuration and end user procedures, the book covers most aspects of the SAP FICO certification syllabus-SAP's view of the module's key tasks and procedures-including: Configuring and using the general ledger and accounts payable and receivable screens Configuring and completing closing procedures, asset accounting, and financial reporting Configuring global settings and enterprise variables Accounting for both profit and cost centers Creating a house bank Integrating FICO with other SAP modules Taking a jargon-free tone and providing an abundance of examples, Andrew Okungbowa provides a clear understanding of configuration techniques and the breadth of functionalities encompassed by SAP FICO. And as an accountant, Okungbowa understands the needs of end users as well as of those answering to the CIO.

Through this book, researchers and students will learn to use R for analysis of large-scale genomic data and how to create routines to automate analytical steps. The philosophy behind the book is to start with real world raw datasets and perform all the analytical steps needed to reach final results. Though theory plays an important role, this is a practical book for graduate and undergraduate courses in bioinformatics and genomic analysis or for use in lab sessions. How to handle and manage high-throughput genomic data, create automated workflows and speed up analyses in R is also taught. A wide range of R packages useful for working with genomic data are illustrated with practical examples. The key topics covered are association studies, genomic prediction, estimation of population genetic parameters and diversity, gene expression analysis, functional annotation of results using publically available databases and how to work efficiently in R with large genomic datasets. Important principles are demonstrated and illustrated through engaging examples which invite the reader to work with the provided datasets. Some methods that are discussed in this volume include: signatures of selection, population parameters (LD, FST, FIS, etc); use of a genomic relationship matrix for population diversity studies; use of SNP data for parentage testing; snpBLUP and gBLUP for genomic prediction. Step-by-step, all the R code required for a genome-wide association study is shown: starting from raw SNP data, how to build databases to handle and manage the data, quality control and filtering measures, association testing and evaluation of results, through to identification and functional annotation of candidate genes. Similarly, gene expression analyses are shown using microarray and RNAseq data. At a time when genomic data is decidedly big, the skills from this book are critical. In recent years R has become the de facto< tool for analysis of gene expression data, in addition to its prominent role in analysis of genomic data. Benefits to using R include the integrated development environment for analysis, flexibility and control of the analytic workflow. Included topics are core components of advanced undergraduate and graduate classes in bioinformatics, genomics and statistical genetics. This book is also designed to be used by students in computer science and statistics who want to learn the practical aspects of genomic analysis without delving into algorithmic details. The datasets used throughout the book may be downloaded from the publisher's website.

This Festschrift in honour of Ursula Gather's 60th birthday deals with modern topics in the field of robust statistical methods, especially for time series and regression analysis, and with statistical methods for complex data structures. The individual contributions of leading experts provide a textbook-style overview of the topic, supplemented by current research results and questions. The statistical theory and methods in this volume aim at the analysis of data which deviate from classical stringent model assumptions, which contain outlying values and/or have a complex structure. Written for researchers as well as master and PhD students with a good knowledge of statistics.

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Differential Equations introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving an introduction to the MATLAB environment and MATLAB programming, this book provides all the material needed to work on differential equations using MATLAB. It includes techniques for solving ordinary and partial differential equations of various kinds, and systems of such equations, either symbolically or using numerical methods (Euler's method, Heun's method, the Taylor series method, the Runge-Kutta method,...). It also describes how to implement mathematical tools such as the Laplace transform, orthogonal polynomials, and special functions (Airy and Bessel functions), and find solutions of finite difference equations.

This book focuses on the applications of convex optimization and highlights several topics, including support vector machines, parameter estimation, norm approximation and regularization, semi-definite programming problems, convex relaxation, and geometric problems. All derivation processes are presented in detail to aid in comprehension. The book offers concrete guidance, helping readers recognize and formulate convex optimization problems they might encounter in practice.

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Linear Algebra introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving an introduction to the MATLAB environment and MATLAB programming, this book provides all the material needed to work in linear algebra with ease. In addition to exploring MATLAB's matrix algebra capabilities, it describes the MATLAB commands that are used to create two- and three-dimensional graphics, including explicit, implicit and parametric curve and surface plotting, and various methods of data representation. Methods for solving systems of equations are detailed.

Essentials of Monte Carlo Simulation focuses on the fundamentals of Monte Carlo methods using basic computer simulation techniques. The theories presented in this text deal with systems that are too complex to solve analytically. As a result, readers are given a system of interest and constructs using computer code, as well as algorithmic models to emulate how the system works internally. After the models are run several times, in a random sample way, the data for each output variable(s) of interest is analyzed by ordinary statistical methods. This book features 11 comprehensive chapters, and discusses such key topics as random number generators, multivariate random variates, and continuous random variates. Over 100 numerical examples are presented as part of the appendix to illustrate useful real world applications. The text also contains an easy to read presentation with minimal use of difficult mathematical concepts. Very little has been published in the area of computer Monte Carlo simulation methods, and this book will appeal to students and researchers in the fields of Mathematics and Statistics.

later versions. In addition, the CD-ROM contains a complete solutions manual that includes detailed solutions to all the problems in the book. If the reader does not wish to consult these solutions, then a brief list of answers is provided in printed form at the end of the book. Iwouldliketothankmyfamilymembersfortheirhelpandcontinuedsupportwi- out which this book would not have been possible. I would also like to acknowledge the help of the editior at Springer-Verlag (Dr. Thomas Ditzinger) for his assistance in bringing this book out in its present form. Finally, I would like to thank my brother, Nicola, for preparing most of the line drawings in both editions. In this edition, I am providing two email addresses for my readers to contact me (pkattan@tedata. net. jo and pkattan@lsu. edu). The old email address that appeared in the ?rst edition was cancelled in 2004. December 2006 Peter I. Kattan PrefacetotheFirstEdition 3 This is a book for people who love ?nite elements and MATLAB . We will use the popular computer package MATLAB as a matrix calculator for doing ?nite element analysis. Problems will be solved mainly using MATLAB to carry out the tedious and lengthy matrix calculations in addition to some manual manipulations especially when applying the boundary conditions. In particular the steps of the ?nite element method are emphasized in this book. The reader will not ?nd ready-made MATLAB programsforuseasblackboxes. Insteadstep-by-stepsolutionsof?niteelementpr- lems are examined in detail using MATLAB.

Introduction to Global Optimization Exploiting Space-Filling Curves provides an overview of classical and new results pertaining to the usage of space-filling curves in global optimization. The authors look at a family of derivative-free numerical algorithms applying space-filling curves to reduce the dimensionality of the global optimization problem; along with a number of unconventional ideas, such as adaptive strategies for estimating Lipschitz constant, balancing global and local information to accelerate the search. Convergence conditions of the described algorithms are studied in depth and theoretical considerations are illustrated through numerical examples. This work also contains a code for implementing space-filling curves that can be used for constructing new global optimization algorithms. Basic ideas from this text can be applied to a number of problems including problems with multiextremal and partially defined constraints and non-redundant parallel computations can be organized. Professors, students, researchers, engineers, and other professionals in the fields of pure mathematics, nonlinear sciences studying fractals, operations research, management science, industrial and applied mathematics, computer science, engineering, economics, and the environmental sciences will find this title useful .

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Symbolic Algebra and Calculus Tools introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. Starting with a look at symbolic variables and functions, you will learn how to solve equations in MATLAB, both symbolically and numerically, and how to simplify the results. Extensive coverage of polynomial solutions, inequalities and systems of equations are covered in detail. You will see how MATLAB incorporates vector, matrix and character variables, and functions thereof. MATLAB is a powerful symbolic manipulator which enables you to factorize, expand and simplify complex algebraic expressions over all common fields (including over finite fields and algebraic field extensions of the rational numbers). With MATLAB you can also work with ease in matrix algebra, making use of commands which allow you to find eigenvalues, eigenvectors, determinants, norms and various matrix decompositions, among many other features. Lastly, you will see how you can use MATLAB to explore mathematical analysis, finding limits of sequences and functions, sums of series, integrals, derivatives and solving differential equation.

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide.