Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language.The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis on the Java Platform is a great choice for those who want to learn how statistical data analysis can be done using popular programming languages, who want to integrate data analysis algorithms in full-scale applications, and deploy such calculations on the web pages or computational servers regardless of their operating system. It is an excellent reference for scientific computations to solve real-world problems using a comprehensive stack of open-source Java libraries included in the DataMelt (DMelt) project and will be appreciated by many data-analysis scientists, engineers and students.

Information-Enabled Organization Transformation and Outsourcing.- Wirtschaftsinformatik: Von den Moden zum Trend.- MEMO: Eine werkzeuggestutzte Methode zum integrierten Entwurf von Geschaftsprozessen und Informationssystemen.- Integrierte Informationssysteme durch Modellierung von Geschaftsprozessen.- Unternehmensmodellierung - Basis fur Reengineering und Optimierung von Geschaftsprozessen.- Geschaftsprozess-Management und Qualitatssicherung am Beispiel des WIS-Projekts.- Strukturanalogien in Informationsmodellen.- Objektorientierte Spezifikation betrieblicher Informationssysteme.- Semantische Objektmodellierung anwendungsorientierter Informations systeme vom Standpunkt des Sicherheitsmanagements.- Vom Informationsmodell zum Anwendungssystem - Nutzenpotentiale fur den effizienten Einsatz von Informationssystemen.- Verfahren zur werkzeuggestutzten Integration von Datenbankschemata.- Formale Validierung von Verdichtungsoperationen in konzeptionellen Datenmodellen.- Simulation hierarchischer objekt- und transaktionsorientierter Modelle.- Aufbau einer gesamtbankweiten Geschaftsdatenbank als Grundlage fur ein globales Steuerungsinstrumentarium des Treasury und Controlling bei Sal. Oppenheim Jr. & Cie., Koeln.- Ein Entscheidungsmodell zur Automatisierung und Standardisierung in betrieblichen Informationssystemen.- Optimierung von Client/Server-Konfigurationen.- Die strategischen Implikationen von Informations- und Kommunikations technologien fur das Bankgeschaft.- Einsatz Neuronaler Netze in der Finanzprognose und -analyse.- Umgestaltung der Geschaftsprozesse und der betrieblichen Anwendungs systeme fur ein weltweit tatiges Unternehmen des Chemie-Anlagebaus.- Kundenorientierte Informationsgestaltung im oeffentlichen Personenverkehr.- Flexible Architekturen und wiederverwendbare Softwarebausteine fur die Anwendung der Zukunft - dargestellt an Systemen der Wurttembergischen Versicherung AG.- Die IV-Strategie des Energieversorgungsunternehmens RWE Energie.- Multinationale Informationsstrategien am Beispiel der Esso A. G.- Perspektiven fur den Einsatz objektorientierter Datenbanksysteme in CIM-orientierten Kosteninformationssystemen.- Datenbankgestutzte, vertragsbasierte Buchhaltung.- Funktionsintegration in heterogenen verteilten Informationssystemen - innovative Konzepte und Fallstudien.- Mobile Rechneranwendungen in dezentralen verteilten Systemumgebungen.- Podiumsdiskussion.- Abhangigkeit als Entscheidungskriterium zwischen internen und externen Organisationsformen der Informationsverarbeitung.- Diversifikationseffekte als Erklarung fur Downsizing und Outsourcing.- Redesign des Siemens-Nixdorf Service und die Erweiterung von Business Process Reengineering zu IT-enabled Business Innovation.- Geschaftsstrategie - Prozess - Informationssystem.- The Use of Worldwide Networking by Global Corporations.- Die Zukunft wird anders sein ! - Informationen verandern die Welt.- Autoren- und Adressverzeichnis.- Sponsorenverzeichnis.

This third volume in the series deals with such topics as information systems practice and theory, information systems and the accounting/auditing environment, and differing perspectives on information systems research.

This book introduces readers to the basic concepts of and latest findings in the area of differential equations with uncertain factors. It covers the analytic method and numerical method for solving uncertain differential equations, as well as their applications in the field of finance. Furthermore, the book provides a number of new potential research directions for uncertain differential equation. It will be of interest to researchers, engineers and students in the fields of mathematics, information science, operations research, industrial engineering, computer science, artificial intelligence, automation, economics, and management science.

Recent achievements in hardware and software developments have enabled the introduction of a revolutionary technology: in-memory data management. This technology supports the flexible and extremely fast analysis of massive amounts of data, such as diagnoses, therapies, and human genome data. This book shares the latest research results of applying in-memory data management to personalized medicine, changing it from computational possibility to clinical reality. The authors provide details on innovative approaches to enabling the processing, combination, and analysis of relevant data in real-time. The book bridges the gap between medical experts, such as physicians, clinicians, and biological researchers, and technology experts, such as software developers, database specialists, and statisticians. Topics covered in this book include - amongst others - modeling of genome data processing and analysis pipelines, high-throughput data processing, exchange of sensitive data and protection of intellectual property. Beyond that, it shares insights on research prototypes for the analysis of patient cohorts, topology analysis of biological pathways, and combined search in structured and unstructured medical data, and outlines completely new processes that have now become possible due to interactive data analyses.

This is a book for people who love mechanics of composite materials and ? MATLAB . We will use the popular computer package MATLAB as a matrix calculator for doing the numerical calculations needed in mechanics of c- posite materials. In particular, the steps of the mechanical calculations will be emphasized in this book. The reader will not ?nd ready-made MATLAB programs for use as black boxes. Instead step-by-step solutions of composite material mechanics problems are examined in detail using MATLAB. All the problems in the book assume linear elastic behavior in structural mechanics. The emphasis is not on mass computations or programming, but rather on learning the composite material mechanics computations and understanding of the underlying concepts. The basic aspects of the mechanics of ?ber-reinforced composite materials are covered in this book. This includes lamina analysis in both the local and global coordinate systems, laminate analysis, and failure theories of a lamina.

Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.

This book features 13 papers presented at the Fifth International Symposium on Recurrence Plots, held August 2013 in Chicago, IL. It examines recent applications and developments in recurrence plots and recurrence quantification analysis (RQA) with special emphasis on biological and cognitive systems and the analysis of coupled systems using cross-recurrence methods. Readers will discover new applications and insights into a range of systems provided by recurrence plot analysis and new theoretical and mathematical developments in recurrence plots. Recurrence plot based analysis is a powerful tool that operates on real-world complex systems that are nonlinear, non-stationary, noisy, of any statistical distribution, free of any particular model type and not particularly long. Quantitative analyses promote the detection of system state changes, synchronized dynamical regimes or classification of system states. The book will be of interest to an interdisciplinary audience of recurrence plot users and researchers interested in time series analysis of complex systems in general.

A collection of surveys and research papers on mathematical software and algorithms. The common thread is that the field of mathematical applications lies on the border between algebra and geometry. Topics include polyhedral geometry, elimination theory, algebraic surfaces, Gröbner bases, triangulations of point sets and the mutual relationship. This diversity is accompanied by the abundance of available software systems which often handle only special mathematical aspects. This is why the volume also focuses on solutions to the integration of mathematical software systems. This includes low-level and XML based high-level communication channels as well as general frameworks for modular systems.

This book provides an overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. Over 170 figures are included in the book.

This is the sixth volume in a series dealing with such topics as information systems practice and theory, information systems and the accounting/auditing environment, and differing perspectives on information systems research.

These are the proceedings of the 22nd International Conference on Domain Decomposition Methods, which was held in Lugano, Switzerland. With 172 participants from over 24 countries, this conference continued a long-standing tradition of internationally oriented meetings on Domain Decomposition Methods. The book features a well-balanced mix of established and new topics, such as the manifold theory of Schwarz Methods, Isogeometric Analysis, Discontinuous Galerkin Methods, exploitation of modern HPC architectures and industrial applications. As the conference program reflects, the growing capabilities in terms of theory and available hardware allow increasingly complex non-linear and multi-physics simulations, confirming the tremendous potential and flexibility of the domain decomposition concept.

Fully updated for Microsoft Dynamics AX 2012 R3! Dig into the architecture and internals of Microsoft Dynamics AX 2012 R3 - with firsthand insights from the team that designed and developed it. Deepen your knowledge of the underlying frameworks, components, and tools - and deliver custom ERP applications with the extensibility and performance your business needs. Useful for Microsoft Dynamics AX solution developers at all levels, this guide will provide max benefit to those who understand OOP, relational database, and Transact-SQL concepts. Gain best practices, patterns, and techniques to: Exploit interoperability with Microsoft Visual Studio tools Work with MorphX and avoid common pitfalls with X++ code Use Enterprise Portal with ASP.NET and SharePoint for rich web-based apps Simplify process automation with built-in workflow infrastructure See how the runtime implements security and configuration Design and customize the user experience Gain greater control over complex batch jobs Customize the prebuilt BI solution and reporting Test applications, publish services, and optimize performance

This second volume in the series covers such topics as information systems practice and theory, information systems and the accounting/auditing environment, and differing perspectives on information systems research.

This book prepares students to execute the quantitative and computational needs of the finance industry. The quantitative methods are explained in detail with examples from real financial problems like option pricing, risk management, portfolio selection, etc. Codes are provided in R programming language to execute the methods. Tables and figures, often with real data, illustrate the codes. References to related work are intended to aid the reader to pursue areas of specific interest in further detail. The comprehensive background with economic, statistical, mathematical, and computational theory strengthens the understanding. The coverage is broad, and linkages between different sections are explained. The primary audience is graduate students, while it should also be accessible to advanced undergraduates. Practitioners working in the finance industry will also benefit.

Discusses the usage, debate, and conceptual and theoretical issues of e-collaboration support of distributed project management.

The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. At the same time, it is now being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems.
In this extensively updated new edition there is more material on methods and examples including several new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods including approximate dynamic programming, robust optimization and online methods.

The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest.

Review of First Edition:

"The discussion on modeling issues, the large number of examples used to illustrate the material, and the breadth of the coverage make'Introduction to Stochastic Programming' an ideal textbook for the area." (Interfaces, 1998)

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This book opens the "black box" of software sourcing by explaining how dynamic software alignment is established and how it impacts business performance outcomes. By investigating how software-sourcing modes are related to value generation in the post-implementation phase, it shows researchers and managers the impact logic of on-demand, on-premises, and in-house software on dynamic fit and process-level performance outcomes in a client organization. It describes dynamic IT alignment as the key to success in a fast-moving digital world with software-as-a-service on the rise and highlights the fact that today companies can choose between developing software in-house (make) or sourcing packaged systems in an on-premises (buy) or an on-demand (lease) mode. This book is the first to explicitly compare these sourcing arrangements with each other in terms of alignment and business performance.

After the introduction of Enterprise Information Systems (EIS) and Enterprise Resources Planning (ERP) applications to many business organizations, the functional issues such as technical problems, security threats, persistent end-user resistance, and the excessive hidden costs of these systems began coming to light. Cases on Enterprise Information Systems and Implementation Stages: Learning from the Gulf Region focuses on the Gulf region and its lead on the enterprise systems adoption which has exceeded those in many developed countries. This reference book highlights experiences implementing EIS, delivering a comprehensive multi-perspective account of EIS issues, and explores the concerns, risks, and critical success factors of EIS for a variety of organizations. It aims to be beneficial for both practitioners and academics alike.

Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings.

This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL). The book examines and presents, in a systematic manner, computational probability methods that encompass data structures and algorithms. The developed techniques address problems that require exact probability calculations, many of which have been considered intractable in the past. The book addresses the plight of the probabilist by providing algorithms to perform calculations associated with random variables. Computational Probability: Algorithms and Applications in the Mathematical Sciences, 2nd Edition begins with an introductory chapter that contains short examples involving the elementary use of APPL. Chapter 2 reviews the Maple data structures and functions necessary to implement APPL. This is followed by a discussion of the development of the data structures and algorithms (Chapters 3-6 for continuous random variables and Chapters 7-9 for discrete random variables) used in APPL. The book concludes with Chapters 10-15 introducing a sampling of various applications in the mathematical sciences. This book should appeal to researchers in the mathematical sciences with an interest in applied probability and instructors using the book for a special topics course in computational probability taught in a mathematics, statistics, operations research, management science, or industrial engineering department.