- The Bar Method Designer Sculpting
- Machine Learning Methods for Commonsense Reasoning Processes: Interactive Models
- Handbook of Floating-Point Arithmetic
- Data Mining: Special Issue in Annals of Information Systems
- Agile Java(TM): Crafting Code with Test-Driven Development
- Test Driven: Practical TDD and Acceptance TDD for Java Developers
- Open Source: A Multidisciplinary Approach
- Predicting Structured Data (Neural Information Processing)
- Engineering Secure Software and Systems: First International Symposium, ESSoS 2009, Proceedings
- Growth and Development of Computer Aided Innovation: Third IFIP WG 5.4 Working Conference, CAI 2009, Proceedings
Posted: 29 Nov 2009 05:31 PM PST
The Bar Method is a fitness program designed to produce the slim, defined body of a dancer without the use of any expensive exercise equipment. Instead, instructor Burr Leonard guides the viewer through a series of precise exercises that can be achieved with a simple piece of sturdy furniture. These highly effective movements result in elongated legs, lifted buttocks,…
Posted: 29 Nov 2009 04:01 PM PST
The reduction of machine learning algorithms to commonsense reasoning processes is now possible due to the reformulation of machine learning problems as searching the best approximation of a given classification on a given set of examples. Machine Learning Methods for Commonsense Reasoning Processes: Interactive Models provides a unique view on classification as a key to human commonsense reasoning and transforms traditional considerations of data and knowledge communications. Containing leading research evolved from international investigations, this book presents an effective classification of logical rules used in the modeling of commonsense reasoning.
Posted: 29 Nov 2009 04:01 PM PST
Floating-point arithmetic is by far the most widely used way of implementing real-number arithmetic on modern computers. Although the basic principles of floating-point arithmetic can be explained in a short amount of time, making such an arithmetic reliable and portable, yet fast, is a very difficult task. From the 1960s to the early 1980s, many different arithmetics were developed, but their implementation varied widely from one machine to another, making it difficult for nonexperts to design, learn, and use the required algorithms. As a result, floating-point arithmetic is far from being exploited to its full potential.
This handbook aims to provide a complete overview of modern floating-point arithmetic, including a detailed treatment of the newly revised (IEEE 754-2008) standard for floating-point arithmetic. Presented throughout are algorithms for implementing floating-point arithmetic as well as algorithms that use floating-point arithmetic. So that the techniques presented can be put directly into practice in actual coding or design, they are illustrated, whenever possible, by a corresponding program.
Key topics and features include:
* Presentation of the history and basic concepts of floating-point arithmetic and various aspects of the past and current standards
* Development of smart and nontrivial algorithms, and algorithmic possibilities induced by the availability of a fused multiply-add (fma) instruction, e.g., correctly rounded software division and square roots
* Implementation of floating-point arithmetic, either in software—on an integer processor—or hardware, and a discussion of issues related to compilers and languages
* Coverage of several recent advances related to elementary functions: correct rounding of these functions and computation of very accurate approximations under constraints
* Extensions of floating-point arithmetic such as certification, verification, and big precision
Handbook of Floating-Point Arithmetic is designed for programmers of numerical applications, compiler designers, programmers of floating-point algorithms, designers of arithmetic operators, and more generally, students and researchers in numerical analysis who wish to better understand a tool used in their daily work and research.
Posted: 29 Nov 2009 04:00 PM PST
Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research.
This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN'07 and DMIN'08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining. Among the suggested topics of interest were:
Posted: 29 Nov 2009 03:48 PM PST
Agile Java is a valuable tutorial and reference. It introduces the Java languagewith no assumptions about a developer’s background in Java, object-orienteddevelopment, or TDD. The book will also retain significant value as acookbook that readers will turn to time and again to learn how to approachTDD with respect to various language features.Teh author stresses the importance of TDD by showing coded tests for everyJava feature taught. A programmer learning with this book will understand howto translate oral requirements into tests, and tests into working code. Readersalso learn how TDD impacts the design of the system, and vice versa. In short,anyone who wants to understand what it takes to build a professional, robustsoftware system using Java will want this book. Agile Java will be ideally timedto coincide with Sun’s forthcoming release of Java 5 (J2SE 1.5).
Posted: 29 Nov 2009 03:45 PM PST
In test driven development, you first write an executable test of what your application code must do. Only then do you write the code itself and, with the test spurring you on, you improve your design. In acceptance test driven development (ATDD), you use the same technique to implement product features, benefiting from iterative development, rapid feedback cycles, and better-defined requirements. TDD and its supporting tools and techniques lead to better software faster. “Test Driven” brings under one cover practical TDD techniques distilled from several years of community experience. With examples in Java and the Java EE environment, it explores both the techniques and the mindset of TDD and ATDD. It uses carefully chosen examples to illustrate TDD tools and design patterns, not in the abstract but concretely in the context of the technologies you face at work. It is accessible to TDD beginners, and it offers effective and less well known techniques to older TDD hands.
What’s Inside Learn hands-on to test drive Java code How to avoid common TDD adoption pitfalls Acceptance test driven development and the Fit framework How to test Java EE components-Servlets, JSPs, and Spring Controllers Tough issues like multithreaded programs and data access code
Posted: 29 Nov 2009 03:44 PM PST
In recent years, the way open source software is developed has taken hold as a valid alternative to commercial proprietary methods, as have the products themselves, e.g., the Linux operating system, Apache web-server software, and Mozilla Firefox browser. But what is open source software? How is the open source community organized? What makes this new model successful? What effects has it had and might it have on the future of the IT industry, companies and government policies? These and many other questions are answered in this book. The first chapter gives a brief history of the open source community and the second chapter takes a close look at the relationship between intellectual property rights and software, both open source and proprietary. The next three chapters consider the who, the open source community, the how, software development both within and outside the community, and the what, open source projects and product quality. Chapters 6 and 7 focus on the different users of open source software: companies and governments respectively. These are followed by two chapters that interpret the phenomenon, first from an organizational point of view in Chapter 8 and then using the theory of complex adaptive systems in Chapter 9. The last chapter explores the current and potential applications of the concept underlying open source software in other fields.
Posted: 29 Nov 2009 03:43 PM PST
Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must satisfy the additional constraints found in structured data, poses one of machine learning's greatest challenges: learning functional dependencies between arbitrary input and output domains. This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field. The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field.
Posted: 29 Nov 2009 03:40 PM PST
This book constitutes the refereed proceedings of the First International Symposium on Engineering Secure Software and Systems, ESSoS 2009, held in Leuven, Belgium, in February 2009.
The 10 revised full papers presented together with 7 industry reports and ideas papers were carefully reviewed and selected from 57 submissions. The papers are organized in topical sections on policy verification and enforcement, model refinement and program transformation, secure system development, attack analysis and prevention, as well as testing and assurance.
Posted: 29 Nov 2009 03:39 PM PST
This volume constitutes the refereed proceedings of the Third IFIP WG 5.4. Working Conference on Computer Aided Innovation, CAI 2009, held in Harbin, China, in August 2009.
The papers deal with advanced approaches in education and training; data mining; text mining; semantic Web; optimization and innovation, shape and topology generators; design automation; integration of CAI methods and tools into engineering; innovation process and engineering information pipeline; innovation in collaborative networks of enterprises; professional virtual communities as well as engineering design.
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