Business Objects

Sample

Darren Broemmer

Learn how to apply robust application design to your J2EE projects There are a number of best practices you need to consider to build highly effective J2EE components and integrate them into applications. These practices include evaluating and selecting the right set of software components and services to handle the job. In this book, Darren Broemmer supplies you with a set of best practices for J2EE development and then teaches you how to use them to construct an application architecture referred to as the reference architecture. The design and implementation of the reference architecture is based on a set of guiding principles that are used to optimize and automate J2EE development. In addition to the author's thorough discussions of the latest technologies for J2EE implementation-including EJB 2, Jakarta Struts, Servlets, Java Server Pages, UML, design patterns, Common Business Logic Foundation components, and XML-Broemmer addresses such topics as: Understanding J2EE application architecture Building business applications with J2EE, a business object architecture, and extensible components created with design patterns Designing and implementing a sample banking Web application Integrating proven performance-engineering and optimization practices in the development process Using metadata-driven, configurable foundation components to automate much of the development and processing of Web-based business applications The companion Web site contains the source code for a Common Business Logic Foundation and sample applications from the book, including a Jakarta Struts project and a banking application. Links to the Jakarta Struts frameworks and J2EE application servers such as BEA WebLogic and IBM WebSphere are also provided.

Sample

Yoav Shoham, Kevin Leyton-Brown

Multiagent systems combine multiple autonomous entities, each having diverging interests or different information. This overview of the field offers a computer science perspective, but also draws on ideas from game theory, economics, operations research, logic, philosophy and linguistics. It will serve as a reference for researchers in each of these fields, and be used as a text for advanced undergraduate or graduate courses. The authors emphasize foundations to create a broad and rigorous treatment of their subject, with thorough presentations of distributed problem solving, game theory, multiagent communication and learning, social choice, mechanism design, auctions, cooperative game theory, and modal logics of knowledge and belief. For each topic, basic concepts are introduced, examples are given, proofs of key results are offered, and algorithmic considerations are examined. An appendix covers background material in probability theory, classical logic, Markov decision processes and mathematical programming.

Sample

Stanislav Uryasev, Panos M. Pardalos

Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic programming approaches have been successfully used in a number of areas such as energy and production planning, telecommunications, and transportation. Recently, the practical experience gained in stochastic programming has been expanded to a much larger spectrum of applications including financial modeling, risk management, and probabilistic risk analysis. Major topics in this volume include: (1) advances in theory and implementation of stochastic programming algorithms; (2) sensitivity analysis of stochastic systems; (3) stochastic programming applications and other related topics. Audience: Researchers and academies working in optimization, computer modeling, operations research and financial engineering. The book is appropriate as supplementary reading in courses on optimization and financial engineering.

Sample

C.K. Chui, G. Chen

This book presents a thorough discussion of the mathematical theory of Kalman filtering. The filtering equations are derived in a series of elementary steps enabling the optimality of the process to be understood. It provides a comprehensive treatment of various major topics in Kalman-filtering theory, including uncorrelated and correlated noise, colored noise, steady-state theory, nonlinear systems, systems identification, numerical algorithms, and real-time applications. A series of problems for the student, together with a complete set of solutions, are also included. The style of the book is informal, and the mathematics elementary but rigorous, making it accessible to all those with a minimal knowledge of linear algebra and systems theory. In this second edition, in addition to some minor corrections and up-dating, the section on real-time system identification has been expanded and a brief introduction to wavelet analysis included.