Wie managen f hrende Unternehmen ihre Gesch ftsprozesse? Was sind die Grundlagen des Erfolgs? Basierend auf einer Untersuchung der Business-Process-Management-Praktiken (BPM) in 17 Unternehmen zeigt das Buch, wie in Best-Practice-Unternehmen Organisation und IT-Systeme optimal aufeinander abgestimmt werden, um die Kundenorientierung zu steigern, Kosten zu senken sowie Flexibilit t und Qualit t zu verbessern. Der Band enth lt eine Analyse der Erfolgsmuster, wichtige Umsetzungshinweise sowie einen Ausblick auf zuk nftige Entwicklungen des BPM.

Computational techniques based on simulation have now become an essential part of the statistician's toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and skills for simulation than to use simulation to solve statistical problems. Introducing Monte Carlo Methods with R covers the main tools used in statistical simulation from a programmer's point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison. While this book constitutes a comprehensive treatment of simulation methods, the theoretical justification of those methods has been considerably reduced, compared with Robert and Casella (2004). Similarly, the more exploratory and less stable solutions are not covered here.

This book does not require a preliminary exposure to the R programming language or to Monte Carlo methods, nor an advanced mathematical background. While many examples are set within a Bayesian framework, advanced expertise in Bayesian statistics is not required. The book covers basic random generation algorithms, Monte Carlo techniques for integration and optimization, convergence diagnoses, Markov chain Monte Carlo methods, including Metropolis {Hastings and Gibbs algorithms, and adaptive algorithms. All chapters include exercises and all R programs are available as an R package called mcsm. The book appeals to anyone with a practical interest in simulation methods but no previous exposure. It is meant to be useful for students and practitioners in areas such as statistics, signal processing, communications engineering, control theory, econometrics, finance and more. The programming parts are introduced progressively to be accessible to any reader.

The SharePoint user experience is critical in application architecture and user acceptance. Using tools available to all developers, Building the SharePoint User Experience will show you how to rebuild a SharePoint site, taking it all the way from the default outofthebox experience to your very own customized user experience.

Along the way you will receive a solid understanding of the SharePoint architecture that will enable you to take full advantage of the capabilities of SharePoint as a platform. This will allow you to tailor the SharePoint user experience to increase the value of solutions and to work more effectively with projects. And that, of course, leads to successful SharePoint solutions in your business that your users are happy to accept and use. What you'll learn Learn the tools needed to create effective and highly tailored user interfaces and experiences. Dissect an outofthebox site to learn how every user experience element is built. Master the core functions of sites, lists, content types, and fields. Build a site from scratch using tools available to everyone. Speed up development time by using little known tips and tricks. See how new skills can be applied to everyday tasks with simple exercises. Who this book is for

This book is for SharePoint developers who want to learn how to work with designers and other developers to create custom and tailored user experiences, including custom forms, content types, lists, fields, pages, and navigation that will better match your project's requirements. This is not a book for graphic designers--you'll find no Photoshop tips here Table of Contents Checking Your Gear for Departure Taking a Crash Course in XML Exploring Feature Basics and Not-So Basics Excavating the Site Evolving the Default User Experience What Lurks in the Forest of Lists? Encountering the Monsters in the Cave The Liquid Nitrogen of SharePoint Strolling Through Fields of Gold Intermission: The Mentality of a SharePoint Developer Starting Field Creating Your First Content Factory Accounting Gone Haywire Pages and Pages of Fun Our Empire United

There has been dramatic growth in the development and application of Bayesian inference in statistics. Berger (2000) documents the increase in Bayesian activity by the number of published research articles, the number of books, andtheextensivenumberofapplicationsofBayesianarticlesinapplied disciplines such as science and engineering. One reason for the dramatic growth in Bayesian modeling is the availab- ity of computational algorithms to compute the range of integrals that are necessary in a Bayesian posterior analysis. Due to the speed of modern c- puters, it is now possible to use the Bayesian paradigm to 't very complex models that cannot be 't by alternative frequentist methods. To 't Bayesian models, one needs a statistical computing environment. This environment should be such that one can: write short scripts to de?ne a Bayesian model use or write functions to summarize a posterior distribution use functions to simulate from the posterior distribution construct graphs to illustrate the posterior inference An environment that meets these requirements is the R system. R provides a wide range of functions for data manipulation, calculation, and graphical d- plays. Moreover, it includes a well-developed, simple programming language that users can extend by adding new functions. Many such extensions of the language in the form of packages are easily downloadable from the Comp- hensive R Archive Network (CRAN)

"Modeling with Data" fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results.

Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date.

"Modeling with Data" will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.

Can artificial intelligence learn mathematics? The question is at the heart of this original monograph bringing together theoretical physics, modern geometry, and data science. The study of Calabi-Yau manifolds lies at an exciting intersection between physics and mathematics. Recently, there has been much activity in applying machine learning to solve otherwise intractable problems, to conjecture new formulae, or to understand the underlying structure of mathematics. In this book, insights from string and quantum field theory are combined with powerful techniques from complex and algebraic geometry, then translated into algorithms with the ultimate aim of deriving new information about Calabi-Yau manifolds. While the motivation comes from mathematical physics, the techniques are purely mathematical and the theme is that of explicit calculations. The reader is guided through the theory and provided with explicit computer code in standard software such as SageMath, Python and Mathematica to gain hands-on experience in applications of artificial intelligence to geometry. Driven by data and written in an informal style, The Calabi-Yau Landscape makes cutting-edge topics in mathematical physics, geometry and machine learning readily accessible to graduate students and beyond. The overriding ambition is to introduce some modern mathematics to the physicist, some modern physics to the mathematician, and machine learning to both.

R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.

"Mathematica Cookbook" helps you master the application's core principles by walking you through real-world problems. Ideal for browsing, this book includes recipes for working with numerics, data structures, algebraic equations, calculus, and statistics. You'll also venture into exotic territory with recipes for data visualization using 2D and 3D graphic tools, image processing, and music.

Although Mathematica 7 is a highly advanced computational platform, the recipes in this book make it accessible to everyone -- whether you're working on high school algebra, simple graphs, PhD-level computation, financial analysis, or advanced engineering models.Learn how to use Mathematica at a higher level with functional programming and pattern matchingDelve into the rich library of functions for string and structured text manipulationLearn how to apply the tools to physics and engineering problemsDraw on Mathematica's access to physics, chemistry, and biology dataGet techniques for solving equations in computational financeLearn how to use Mathematica for sophisticated image processingProcess music and audio as musical notes, analog waveforms, or digital sound samples

New statistical tools are changing the ways in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for anyalsis provide consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirement for a clear exposition of the methodology through to application for a range of environmental challenges.

This volume contains selected papers presented at two joint German-Japanese symposia on data analysis and related elds. The articles substantially extend and further develop material presented at the two symposia organized on the basis of longstanding and close relationships which have been cultivated in the last couple of decades between the two classi cation societies: the German Class- cation Society (Gesellschaft fu ]r Klassi kation e. V.) and the Japanese Classi cation Society. These symposia have been very helpful in exchanging ideas, views, and knowledge between the two societies and have served as a spring board for more extensive and closer co-operation between the societies as well as among their individual members. The scienti c program of the rst Joint Japanese-German Symposium (Tokyo 2005)included23presentations;forthesecondJointGerman-JapaneseSymposium (Berlin 2006) 27 presentations were scheduled. This volume presents 21 peer refereed papers, which are grouped into three parts: 1. Part 1 Clustering and Visualization (eight papers) 2. Part 2 Methods in Fields (nine papers) 3. Part 3 Applications in Clustering and Visualization (four papers) The concept of having a joint symposium of the two classi cation societies came from the talks with Hans-Hermann and Wolfgang when Akinori attended the 28th Annual Conference of the German Classi cation Society held in Dortmund in March 2004."

International Association for Statistical Computing The International Association for Statistical Computing (IASC) is a Section of the International Statistical Institute. The objectives of the Association are to foster world-wide interest in e?ective statistical computing and to - change technical knowledge through international contacts and meetings - tween statisticians, computing professionals, organizations, institutions, g- ernments and the general public. The IASC organises its own Conferences, IASC World Conferences, and COMPSTAT in Europe. The 17th Conference of ERS-IASC, the biennial meeting of European - gional Section of the IASC was held in Rome August 28 - September 1, 2006. This conference took place in Rome exactly 20 years after the 7th COMP- STAT symposium which was held in Rome, in 1986. Previous COMPSTAT conferences were held in: Vienna (Austria, 1974); West-Berlin (Germany, 1976); Leiden (The Netherlands, 1978); Edimbourgh (UK, 1980); Toulouse (France, 1982); Prague (Czechoslovakia, 1984); Rome (Italy, 1986); Copenhagen (Denmark, 1988); Dubrovnik (Yugoslavia, 1990); Neuch atel (Switzerland, 1992); Vienna (Austria,1994); Barcelona (Spain, 1996);Bristol(UK,1998);Utrecht(TheNetherlands,2000);Berlin(Germany, 2002); Prague (Czech Republic, 2004).

Many successful project managers are beginning to utilize Microsoft SharePoint to drive their projects and operational initiatives. SharePoint Server provides teams with a centralized location for project information and facilitates collaboration between project team members. The intention of this book is to provide a hands-on case study that you can follow to create a complete project management information system (PMIS) using SharePoint Server 2010.
What you'll learn Create custom lists and content types Handle incoming emails Use web parts to customize your SharePoint portal Implement key performance indicators (KPIs) Integrate Excel charting capability Build a state machine workflow Create custom forms using InfoPath Develop a simple approach for prioritizing requirements Provide tools for managing agile development (sprints, backlog, burn down, etc.) Communicate development and testing metrics Who this book is for

This book is intended primarily for project managers and IT professionals that would like to leverage Microsoft's SharePoint technologies to help manage projects within their organization. Also, developers who are responsible for implementing a PMIS will find this book invaluable. Most of the projects presented in this book can be implemented without writing any code. Table of Contents Introduction Collecting Requirements Processing Incoming E-mail Managing Requirements Supporting Discussions User Stories Project Backlog Iteration Backlog Burndown Charts Getting Organized Creating Test Cases Reporting Defects Testing Metrics Workflow Tasks State Machine Workflows Creating Custom Forms

Create project plans that make the most of your money and time

Get your projects on track, manage resources, and share information online

Project 2007 helps you keep your projects on track by providing sophisticated tools for building task outlines and important timing relationships; efficiently assigning people, cost, and material resources; and keeping everyone and everything on schedule. Get an overview of the benefits of Project Server and Project Web Access for communicating with your team and managing your project online.

All this on the bonus CD-ROMTools for creating enhanced graphics and reportsStrategic planning and brainstorming toolsProject add-ons that improve your time reporting and tracking capabilitiesFor details and complete system requirements, see the CD-ROM appendix.

Discover how toEmploy the powerful new features of Project 2007Track down problems with Task DriversExplore Project's new Visual ReportsGet tips for saving time and money on your projects

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

.".".I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006)"

A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R

This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.

Includes numerous worked examples and exercises within each chapter.

An elementary first course for students in mathematics and engineering

Practical in approach: examples of code are provided for students to debug, and tasks - with full solutions - are provided at the end of each chapter

Includes a glossary of useful terms, with each term supported by an example of the syntaxes commonly encountered

This new edition of the successful multi-disciplinary text Statistical Modelling in GLIM takes into account new developments in both statistical software and statistical modelling. Including three new chapters on mixture and random effects models, it provides a comprehensive treatment of the theory of statistical modelling with generalised linear models with an emphasis on applications to practical problems and an expanded discussion of statistical theory. A wide range of case studies is also provided, using the normal, binomial, Poisson, multinomial, gamma, exponential and Weibull distributions. This book is ideal for graduates and research students in applied statistics and a wide range of quantitative disciplines, including biology, medicine and the social sciences. Professional statisticians at all levels will also find it an invaluable desktop companion.

The second edition of this popular guide demonstrates the process of entering and analyzing data using the latest version of SPSS (12.0), and is also appropriate for those using earlier versions of SPSS. The book is easy to follow because all procedures are outlined in a step-by-step format designed for the novice user. Students are introduced to the rationale of statistical tests and detailed explanations of results are given through clearly annotated examples of SPSS output. Topics covered range from descriptive statistics through multiple regression analysis. In addition, this guide includes topics not typically covered in other books such as probability theory, interaction effects in analysis of variance, factor analysis, and scale reliability. Chapter exercises reinforce the text examples and may be performed for further practice, for homework assignments, or in computer laboratory sessions.

This book can be used in two ways: as a stand-alone manual for students wishing to learn data analysis techniques using SPSS for Windows, or in research and statistics courses to be used with a basic statistics text. The book provides hands-on experience with actual data sets, helps students choose appropriate statistical tests, illustrates the meaning of results, and provides exercises to be completed for further practice or as homework assignments.

Susan B. Gerber, Ph.D. is Research Assistant Professor of Education at State University of New York at Buffalo. She is director of the Educational Technology program and holds degrees in Statistics and Educational Psychology.

Kristin Voelkl Finn, Ph.D. is Assistant Professor of Education at Canisius College. She teaches graduate courses in research methodology and conducts research on adolescent problem behavior.

Over two hundred novel and innovative computer algebra worksheets or "recipes" will enable readers in engineering, physics, and mathematics to easily and rapidly solve and explore most problems they encounter in their mathematical physics studies. While the aim of this text is to illustrate applications, a brief synopsis of the fundamentals for each topic is presented, the topics being organized to correlate with those found in traditional mathematical physics texts. The recipes are presented in the form of stories and anecdotes, a pedagogical approach that makes a mathematically challenging subject easier and more fun to learn.
Key features:

* Uses the MAPLE computer algebra system to allow the reader to easily and quickly change the mathematical models and the parameters and then generate new answers

* No prior knowledge of MAPLE is assumed; the relevant MAPLE commands are introduced on a need-to-know basis

* All recipes are contained on a CD-ROM provided with the text

* All MAPLE commands are indexed for easy reference

* A classroom-tested story/anecdote format is used, accompanied with amusing or thought-provoking quotations

* Study problems, which are presented as Supplementary Recipes, are fully solved and annotated and also provided on the CD-ROM

This is a self-contained and standalone text, similar in style and format to Computer Algebra Recipes: A Gourmet's Guide to Mathematical Models of Science (ISBN 0-387-95148-2), Springer New York 2001 and Computer Algebra Recipes for Classical Mechanics (ISBN 0-8176-4291-9), BirkhAuser 2003. Computer Algebra Recipes for Mathematical Physics may be used in the classroom, for self-study, as a reference, or asa text for an online course.

Technology/Engineering/Mechanical

Provides all the tools needed to begin solving optimization problems using MATLAB(R)

The Second Edition of Applied Optimization with MATLAB(R) Programming enables readers to harness all the features of MATLAB(R) to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems.

This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB(R) tools. Two important new features of the text are:

Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems

New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems

Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB(R) code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own.

This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems.

63 New and Updated Patterns for Driving and Sustaining Change "The hard part of change is enlisting the support of other people. Whether a top manager interested in improving your organization's results or a lone developer promoting a better way of working, this book will give you tools and ideas to help accomplish your goal." -George Dinwiddie, independent coach and consultant, iDIA Computing, LLC "Keep the patterns in this book and Fearless Change handy. ... These patterns transformed me from an ineffective 'voice in the wilderness' to a valued collaborator." -Lisa Crispin, co-author (with Janet Gregory) of Agile Testing and More Agile Testing In their classic work, Fearless Change, Mary Lynn Manns and Linda Rising interviewed successful leaders of change, identified 48 patterns for implementing change in teams of all sizes, and demonstrated how to use these techniques effectively. Now, in More Fearless Change the authors reflect on all they've learned about their original patterns in the past decade, and introduce 15 powerful, new techniques-all extensively validated by change leaders worldwide. Manns and Rising teach strategies that appeal to each individual's logic (head), feelings (heart), and desire to contribute (hands)-the best way to motivate real change and sustain it for the long haul. Learn how to Focus on the best things you can achieve with limited resources Strategize to build flexible plans and go after low-hanging fruit Get help from the right people in the right ways Establish emotional connections that inspire motivation and imagination Create an "elevator pitch" that keeps everyone focused on what truly matters Build bridges, work with skeptics, soften resistance, and open minds Uncover easier paths towards change, and build on what already works Sustain momentum, provide time for reflection, and celebrate small successes More Fearless Change reflects a profound understanding of how real change happens: not instantaneously in response to top-down plans and demands, but iteratively, through small steps that teach from experience. Best of all, as thousands of change agents have already discovered, its patterns are easy to use-and they work.

Die effektive und effiziente Gestaltung von Dienstleistungen wird fur Unternehmen immer entscheidender. Dies gilt nicht nur in den bewahrten Dienstleistungsbranchen, sondern auch verstarkt fur industrielle Anwendungen, bei denen der Dienstleistungsanteil am klassischen materiellen Produkt permanent steigt. Die damit verbundene zunehmende Verflechtung von Unternehmen sowie die gestiegene Produkt- und Prozesskomplexitat erfordern eine interdisziplinare Herangehensweise zwischen Dienstleistungsmanagement, Produktion und Informationstechnologie. Dieser Band stellt aktuelle und innovative Konzepte fur die modellbasierte Entwicklung, Erbringung und kontinuierliche Verbesserung von Dienstleistungen sowie ihre Einbettung in hybride Leistungsangebote vor. Neben dem Stand der Forschung zeigen zahlreiche Branchenszenarien das Potenzial und die praktische Umsetzbarkeit der Dienstleistungsmodellierung auf. Das Buch richtet sich an Dozenten und Studenten der Betriebswirtschaftslehre, der Ingenieurwissenschaften und der Wirtschaftsinformatik sowie an Praktiker in Unternehmen, die sich mit der modellbasierten Gestaltung von Dienstleistungen befassen.

This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization. It also analyzes the software resources available for BO and a few selected application areas. Some areas for which new results are shown include constrained optimization, safe optimization, and applied mathematics, specifically BO's use in solving difficult nonlinear mixed integer problems. The book will help bring readers to a full understanding of the basic Bayesian Optimization framework and gain an appreciation of its potential for emerging application areas. It will be of particular interest to the data science, computer science, optimization, and engineering communities.

This book is dedicated to the systematization and development of models, methods, and algorithms for queuing systems with correlated arrivals. After first setting up the basic tools needed for the study of queuing theory, the authors concentrate on complicated systems: multi-server systems with phase type distribution of service time or single-server queues with arbitrary distribution of service time or semi-Markovian service. They pay special attention to practically important retrial queues, tandem queues, and queues with unreliable servers. Mathematical models of networks and queuing systems are widely used for the study and optimization of various technical, physical, economic, industrial, and administrative systems, and this book will be valuable for researchers, graduate students, and practitioners in these domains.

COBIT(R)5 (Control Objectives for Information and related Technology) is the latest release of the popular framework for the governance of enterprise IT. It links controls, technical issues and business risks, enabling managers to manage the risks associated with business goals. Written for IT service managers, consultants and other practitioners in IT governance, risk and compliance, this practical book discusses all the key concepts of COBIT(R)5, and explains how to direct the governance of enterprise IT (GEIT) using the COBIT(R)5 framework. The book also covers the main frameworks and standards supporting GEIT, discusses the ideas of enterprise and governance, and shows the path from corporate governance to the governance of enterprise IT. Drawing on more than 30 years of experience in the IT sector, the author explains crucial concepts, including: the key elements of COBIT(R)5, the 5 principles, 7 enablers and the goals cascade the structure of the 37 COBIT(R)5 processes the implementation of GEIT using COBIT(R)5 and an implementation lifecycle the COBIT(R)5 Process Assessment Model (PAM) - the approach to process assessment of COBIT(R)5 processes based on International Standard ISO/IEC 15504. For those studying for the COBIT(R)5 qualifications, Governance of Enterprise IT based on COBIT(R)5 covers all the material needed for the COBIT(R)5 Foundation course, making it invaluable to anyone planning to take the exam. Read this book and get to grips with COBIT(R)5 today.