Given the widespread use of real-time multitasking systems, there are tremendous optimization opportunities if reconfigurable computing can be effectively incorporated while maintaining performance and other design constraints of typical applications. The focus of this book is to describe the dynamic reconfiguration techniques that can be safely used in real-time systems. This book provides comprehensive approaches by considering synergistic effects of computation, communication as well as storage together to significantly improve overall performance, power, energy and temperature."

Describes the development and challenges associated with Intelligent Transportation Systems (ITS) Provides novel visualization software designed to serve traffic practitioners in analyzing the efficiency and safety of an intersection Has the potential to proactively identify potential conflict situations and develop an early warning system for real-time vehicle-vehicle and pedestrian-vehicle conflicts

Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem. Key Features: Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codes Provides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizers Presents descriptive data driven methods for the high utilizer population Identifies a best-fitting linear and tree-based regression model to account for patients' acute and chronic condition loads and demographic characteristics

Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem. Key Features: Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codes Provides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizers Presents descriptive data driven methods for the high utilizer population Identifies a best-fitting linear and tree-based regression model to account for patients' acute and chronic condition loads and demographic characteristics

Given the widespread use of real-time multitasking systems, there are tremendous optimization opportunities if reconfigurable computing can be effectively incorporated while maintaining performance and other design constraints of typical applications. The focus of this book is to describe the dynamic reconfiguration techniques that can be safely used in real-time systems. This book provides comprehensive approaches by considering synergistic effects of computation, communication as well as storage together to significantly improve overall performance, power, energy and temperature.

Fundamentals algorithms for SIMD and MIMD hypercubes are developed. These include algorithms for such problems as data broadcasting, data sum, prefix sum, shift, data circulation, data accumulation, sorting, random access reads and writes and data permutation. The fundamental algorithms are then used to obtain efficient hypercube algorithms for matrix multiplication, image processing problems such as convolution, template matching, hough transform, clustering and image processing transformation, and string editing. Most of the algorithms in this book are for hypercubes with the number of processors being a function of problems size. However, for image processing problems, the book also includes algorithms for and MIMD hypercube with a small number of processes. Experimental results on an NCUBE/77 MIMD hypercube are also presented. The book is suitable for use in a one-semester or one-quarter course on hypercube algorithms. For students with no prior exposure to parallel algorithms, it is recommended that one week will be spent on the material in chapter 1, about six weeks on chapter 2 and one week on chapter 3. The remainder of the term can be spent covering topics from the rest of the book.

Welcome to the proceedings of the Third International Conference on Contemporary Computing, which was held in Noida (outskirts of New Delhi), India. Computing is an exciting and evolving area. This conference, which was jointly organized by the Jaypee Institute of Information Technology, Noida, India and the University of Fl- ida, Gainesville, USA, focused on topics that are of contemporary interest to computer and computational scientists and engineers. The conference had an exciting technical program of 79 papers submitted by - searchers and practitioners from academia, industry, and government to advance the algorithmic, systems, applications, and educational aspects of contemporary comp- ing. These papers were selected from 350 submissions (with an overall acceptance rate of around 23%). The technical program was put together by a distinguished int- national Program Committee consisting of more than 150 members. The Program Committee was led by the following Track Chairs: Arunava Banerjee, Kanad Kishore Biswas, Summet Dua, Prabhat Mishra, Rajat Moona, Sheung-Hung Poon, and Cho-Li Wang. I would like to thank the Program Committee and the Track Chairs for their tremendous effort. I would like to thank the General Chairs, Prof. Sartaj Sahni and Prof. Sanjay Goel, for giving me the opportunity to lead the technical program. Sanjay Ranka

Welcome to the Second International Conference on Contemporary Computing, which was held in Noida (outskirts of New Delhi), India. Computing is an exciting and evolving area. This conference, which was jointly organized by the Jaypee Institute of Information Technology University, Noida, India and the University of Florida, Gainesville, USA, focused on topics that are of contemporary interest to computer and computational scientists and engineers. The conference had an exciting technical program of 61 papers submitted by - searchers and practitioners from academia, industry and government to advance the algorithmic, systems, applications, and educational aspects of contemporary comp- ing. These papers were selected from 213 submissions (with an overall acceptance rate of around 29%). The technical program was put together by a distinguished int- national Program Committee. The Program Committee was led by the following Track Chairs and Special Session Chairs: Srinivas Aluru, Rajkumar Buyya, Yeh-Ching Chung, Sumeet Dua, Ananth Grama, Sandeep Gupta, Rajeev Kumar and Vir Phoha. I would like to thank the Program Committee, the Track Chairs and Special Session Chairs for their tremendous effort. I would like to thank the General Chairs, Sartaj Sahni and Sanjay Goel for giving me the opportunity to lead the technical program. Sanjay Ranka

Implementing energy-efficient CPUs and peripherals as well as reducing resource consumption have become emerging trends in computing. As computers increase in speed and power, their energy issues become more and more prevalent. The need to develop and promote environmentally friendly computer technologies and systems has also come to the forefront in computing research. A pioneering publication for researchers in computer science and engineering, Handbook of Energy-Aware and Green Computing, Two-Volume Set is one of the first to present a comprehensive account of recent research in energy-aware and green computing. Edited by the co-chairs of the International Green Computing Conference, this handbook incorporates fundamental knowledge from all related areas, including circuit and component design, software, operating systems, networking, mobile computing, and data centers. It also discusses up-to-date research on many aspects of power-aware computing at the component, software, and system levels.

Implementing energy-efficient CPUs and peripherals as well as reducing resource consumption have become emerging trends in computing. As computers increase in speed and power, their energy issues become more and more prevalent. The need to develop and promote environmentally friendly computer technologies and systems has also come to the forefront in computing research. A pioneering publication for researchers in computer science and engineering, Handbook of Energy-Aware and Green Computing, Two-Volume Set is one of the first to present a comprehensive account of recent research in energy-aware and green computing. Edited by the co-chairs of the International Green Computing Conference, this handbook incorporates fundamental knowledge from all related areas, including circuit and component design, software, operating systems, networking, mobile computing, and data centers. It also discusses up-to-date research on many aspects of power-aware computing at the component, software, and system levels.