The explosive growth of the Internet economy over the past several years and new IP-based enterprise applications has heightened requirements for continuous availability of mission-critical data. Today's network administrators and managers are under big pressure to satisfy ever-increasing demands from customers, suppliers,...

Qualitative Case Studies on Implementation of Enterprise Wide Systems focuses on ERP Implementations in the tertiary education industry—a sector which is important not only for advancing the economy and quality of life in industrialized nations but also as a major source of export income. Systems failure in this information...

"Good old fashioned advice on how to have a great attitude, delivered in a pithy andinteresting way."
—Karen Leland, bestselling author of Watercooler Wisdom: How Smart People Prosper in the Face of Conflict, Pressure and...

Looking ahead to retirement? Depending on your circumstances and your age, you may no longer have any margin for error. And your emotions and irrational behavior could be perpetuating a dangerous cycle of overspending and rising debt that may shatter whatever vision of retirement you still have. Welcome to the world of...

An introduction to the theory and techniques for achieving high quality network communication with the best possible bandwidth economy, this book focuses on network information flow with fidelity. Covering both lossless and lossy source reconstruction, it is illustrated throughout with real-world applications, including sensor networks and...

In recent years, Fourier transform methods have emerged as one of the major methodologies for the evaluation of derivative contracts, largely due to the need to strike a balance between the extension of existing pricing models beyond the traditional Black-Scholes setting and a need to evaluate prices consistently with the market...

This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains...