The rise of large economic regions rivaling the United States will challenge its competitive strength and ability to withstand cross-border economic turbulence--a challenge the U.S. has not faced in more than 50 years. To meet this challenge, American business leaders need a comprehensive understanding of the existing global economic and monetary system. It is that, plus an explanation of international economic trend analysis, that Schaefer's book provides. Based on key economic and financial indicators published weekly in The Economist, Schaefer integrates a discussion of established international economic concepts with actual economic and financial data, giving readers a system to evaluate current economic indicators and anticipate future trends. An important resource for professionals and academics in international finance and investment, and for corporate management operating on a global scale.

This book shows how money and banks emerge to efficiently address problems of trust between economic agents. The analysis offers an innovative approach for integrating monetary theory, banking theory, and standard economic theory in a game theoretical framework. The unified perspective of the book contributes to a better understanding of the microeconomic foundations of monetary policy and banking. It emphasizes the importance of trust supported by credible institutional structures in the financial industry.

This book combines both a comprehensive analytical framework and economic statistics that enable business decision makers to anticipate developing economic trends. The author blends recent and historical economic data with economic theory to provide important benchmarks or rules of thumb that give both economists and noneconomists enhanced understanding of unfolding economic data and their interrelationships. Through the matrix system, a disciplined approach is described for integrating readily available economic data into a comprehensive analysis without complex formulas. The extensive appendix of monthly key economic factors for 1978-1991 makes this an important reference source for economic and financial trend analysis.

A new and practical method for economic trend analysis is introduced that provides more advanced knowledge than available from economic newsletters. Schaeffer begins with a general description of the business cycle and the typical behavior and effect of the credit markets, commercial banks, and the Federal Reserve. Next, fourteen key economic factors regularly reported by the business press are described, such as the capacity utilization rate and yield on three-month Treasury bills. Benchmarks for each of these key economic factors are set forth, together with an insightful discussion of the interrelationships indicating economic trends. A detailed discussion of the 1978-1991 American economy, incorporating monthly data from the historical matrix, demonstrates the practical application of the matrix system. Executives, investors, financial officers, and government policymakers will find this book useful in decision making.

CI Techniques & Algorithms for a Variety of Medical Imaging SituationsDocuments recent advances and stimulates further research A compilation of the latest trends in the field, Computational Intelligence in Medical Imaging: Techniques and Applications explores how intelligent computing can bring enormous benefit to existing technology in medical image processing as well as improve medical imaging research. The contributors also cover state-of-the-art research toward integrating medical image processing with artificial intelligence and machine learning approaches. The book presents numerous techniques, algorithms, and models. It describes neural networks, evolutionary optimization techniques, rough sets, support vector machines, tabu search, fuzzy logic, a Bayesian probabilistic framework, a statistical parts-based appearance model, a reinforcement learning-based multistage image segmentation algorithm, a machine learning approach, Monte Carlo simulations, and intelligent, deformable models. The contributors discuss how these techniques are used to classify wound images, extract the boundaries of skin lesions, analyze prostate cancer, handle the inherent uncertainties in mammographic images, and encapsulate the natural intersubject anatomical variance in medical images. They also examine prostate segmentation in transrectal ultrasound images, automatic segmentation and diagnosis of bone scintigraphy, 3-D medical image segmentation, and the reconstruction of SPECT and PET tomographic images.

Introduces aspects on security threats and their countermeasures in both fixed and wireless networks, advising on how countermeasures can provide secure communication infrastructures. Enables the reader to understand the risks of inappropriate network security, what mechanisms and protocols can be deployed to counter these risks, and how these mechanisms and protocols work.

This book shows how money and banks emerge to efficiently address problems of trust between economic agents. The analysis offers an innovative approach for integrating monetary theory, banking theory, and standard economic theory in a game theoretical framework. The unified perspective of the book contributes to a better understanding of the microeconomic foundations of monetary policy and banking. It emphasizes the importance of trust supported by credible institutional structures in the financial industry.

CI Techniques & Algorithms for a Variety of Medical Imaging Situations
Documents recent advances and stimulates further research

A compilation of the latest trends in the field, Computational Intelligence in Medical Imaging: Techniques and Applications explores how intelligent computing can bring enormous benefit to existing technology in medical image processing as well as improve medical imaging research. The contributors also cover state-of-the-art research toward integrating medical image processing with artificial intelligence and machine learning approaches.

The book presents numerous techniques, algorithms, and models. It describes neural networks, evolutionary optimization techniques, rough sets, support vector machines, tabu search, fuzzy logic, a Bayesian probabilistic framework, a statistical parts-based appearance model, a reinforcement learning-based multistage image segmentation algorithm, a machine learning approach, Monte Carlo simulations, and intelligent, deformable models. The contributors discuss how these techniques are used to classify wound images, extract the boundaries of skin lesions, analyze prostate cancer, handle the inherent uncertainties in mammographic images, and encapsulate the natural intersubject anatomical variance in medical images. They also examine prostate segmentation in transrectal ultrasound images, automatic segmentation and diagnosis of bone scintigraphy, 3-D medical image segmentation, and the reconstruction of SPECT and PET tomographic images.