This book is a survey of recent work on the application of number theory in statistics. The essence of number-theoretic methods is to find a set of points that are universally scattered over an s-dimensional unit cube. In certain circumstances this set can be used instead of random numbers in the Monte Carlo method. The idea can also be applied to other problems such as in experimental design. This book will illustrate the idea of number-theoretic methods and their application in statistics. The emphasis is on applying the methods to practical problems so only part-proofs of theorems are given.
Data Quality provides an exposé of research and practice in the data quality field for technically oriented readers. It is based on the research conducted at the MIT Total Data Quality Management (TDQM) program and work from other leading research institutions. This book is intended primarily for researchers, practitioners, educators and graduate students in the fields of Computer Science, Information Technology, and other interdisciplinary areas. It forms a theoretical foundation that is both rigorous and relevant for dealing with advanced issues related to data quality. Written with the goal to provide an overview of the cumulated research results from the MIT TDQM research perspective as it relates to database research, this book is an excellent introduction to Ph.D. who wish to further pursue their research in the data quality area. It is also an excellent theoretical introduction to IT professionals who wish to gain insight into theoretical results in the technically-oriented data quality area, and apply some of the key concepts to their practice.
Organizations today have access to vast stores of data that come in a wide variety of forms and may be stored in places ranging from file cabinets to databases, and from library shelves to the Internet. The enormous growth in the quantity of data, however, has brought with it growing problems with the quality of information, further complicated by the struggles many organizations are experiencing as they try to improve their systems for knowledge management and organizational memory. Failure to manage information properly, or inaccurate data, costs businesses billions of dollars each year. This volume presents cutting-edge research on information quality. Part I seeks to understand how data can be measured and evaluated for quality. Part II deals with the problem of ensuring quality while processing data into information a company can use. Part III presents case studies, while Part IV explores organizational issues related to information quality. Part V addresses issues in information quality education.
Owing to the developments and applications of computer science, ma thematicians began to take a serious interest in the applications of number theory to numerical analysis about twenty years ago. The progress achieved has been both important practically as well as satisfactory from the theoretical view point. It'or example, from the seventeenth century till now, a great deal of effort was made in developing methods for approximating single integrals and there were only a few works on multiple quadrature until the 1950's. But in the past twenty years, a number of new methods have been devised of which the number theoretic method is an effective one. The number theoretic method may be describe...
In this book the author presents a self-contained account of Harnack inequalities and applications for the semigroup of solutions to stochastic partial and delayed differential equations. Since the semigroup refers to Fokker-Planck equations on infinite-dimensional spaces, the Harnack inequalities the author investigates are dimension-free. This is an essentially different point from the above mentioned classical Harnack inequalities. Moreover, the main tool in the study is a new coupling method (called coupling by change of measures) rather than the usual maximum principle in the current literature.
While widely studied, the capacity of the human mind remains largely unexplored. As such, researchers are continually seeking ways to understand the brain, its function, and its impact on human behavior. Exploring Implicit Cognition: Learning, Memory, and Social Cognitive Processes explores research surrounding the ways in which an individual’s unconscious is able to influence and impact that person’s behavior without their awareness. Focusing on topics pertaining to social cognition and the unconscious process, this title is ideal for use by students, researchers, psychologists, and academicians interested in the latest insights into implicit cognition.
This volume will present critical and comphrehensive reviews examining the latest research and developments in nanoscience in accessible articles. Quantum dot synthesis, soft lithography and graphene will feature in the debut volume, along with perspectives on research in China and India.