If you continue for another 23 hours, 59 minutes, and 40 seconds, you will master the fundamentals of the C++ programming language. Twenty-four 1-hour lessons cover the...

The arrival and popularity of multi-core processors have sparked a renewed interest in the development of parallel programs. Similarly, the availability of low cost microprocessors and sensors has generated a great interest in embedded real-time programs. This book provides students and programmers with traditional backgrounds in...

As fields like communications, speech and image processing, and related areas are rapidly developing, the FFT as one of the essential...

The setting and attainment of goals is a fundamental aspect of human decision making, which is manifest in the modern discipline of operational research by the technique of goal programming. Influences from the fields of mathematical programming and multiple criteria decision making (MCDM) can be found in goal programming, and it is...

The Information Security...

This book will show you how to...

This volume contains the proceedings of the 8th International Workshop on Software and Compilers for Embedded Systems (SCOPES 2004) held in Amsterdam, The Netherlands, on September 2 and 3, 2004. Initially, the workshop was referred to as the International Workshop on Code Generation for Embedded Systems. The first took place in 1994 in...

This paper describes a seven-pass compiler for Per Brlnch Hansen's Concurrent Pascal [1,2] programing language. Concurrent Pascal is an abstract programming language for conputer operating systems. The language extends sequential Pascal [7] with the process, nonitor, and class concepts for structured concurrent programing. A ironitor is a...

The versatile capabilities and large set of add-on packages make R an excellent alternative to many existing and often expensive data mining tools. Exploring this area from the perspective of a practitioner, Data Mining with R: Learning with Case Studies uses practical examples to illustrate the power of R and data...

Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task....

Mainstream data mining techniques significantly limit the role of human reasoning and insight. Likewise, in data visualization, the role of computational analysis is relatively small. The power demonstrated individually by these approaches to knowledge discovery suggests that somehow uniting the two could lead to increased efficiency and more...

Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its impact, and reviews current and future research. Thoroughly evaluated by independent reviewers, each chapter focuses on a...