The present book provides the applications of uncertain measures to the field of queueing theory for measuring variations in steady and non-steady birth-death process. Moreover, we have given the applications of probabilistic measures by studying the maximum entropy principle. Another field of interest is the theory of coding which deals with probability distributions only but we have extended the idea to fuzzy distributions by proving new fuzzy coding theorems corresponding to the well-known measures of weighted fuzzy entropy. The book also deals with the applications of measures of entropy for the study of contingency tables and thus provides applications to the field of statistics. I sincerely hope that the present volume of the book will be useful to all those interested in information measures and their applications in a variety of disciplines. Moreover, it will be a source of inspiration and encouragement to research scholars and teachers to discourse the subject for the discovery of new insights.

This monograph explores the interdisciplinary applications of information theory, focusing on the concepts of entropy, mutual information, and their implications in various fields. It explains the fundamental differences between entropy and Shannon’s Measure of Information (SMI), presents the application of information theory to living systems and psychology, and also discusses the role of entropy in art. It critically overviews the definition of correlations and multivariate mutual information.These notions are used to build a new perspective for understanding the irreversibility of processes in macroscopic systems, while the dynamical laws governing the microscopic components are reversible. It also delves into the use of mutual information in linguistics, cryptography, steganography, and communication systems. The book details the theoretical and practical aspects of information theory across a spectrum of disciplines and is a useful tool for any scientist interested in what is usually called entropy.

Measurement plays a fundamental role both in physical and behavioral sciences, as well as in engineering and technology: it is the link between abstract models and empirical reality and is a privileged method of gathering information from the real world. Is it possible to develop a single theory of measurement for the various domains of science and technology in which measurement is involved? This book takes the challenge by addressing the following main issues: What is the meaning of measurement? How do we measure? What can be measured? A theoretical framework that could truly be shared by scientists in different fields, ranging from physics and engineering to psychology is developed. The future in fact will require greater collaboration between science and technology and between different sciences. Measurement, which played a key role in the birth of modern science, can act as an essential interdisciplinary tool and language for this new scenario. A sound theoretical basis for addressing key problems in measurement is provided. These include perceptual measurement, the evaluation of uncertainty, the evaluation of inter-comparisons, the analysis of risks in decision-making and the characterization of dynamical measurement. Currently, increasing attention is paid to these issues due to their scientific, technical, economic and social impact. The book proposes a unified probabilistic approach to them which may allow more rational and effective solutions to be reached. Great care was taken to make the text as accessible as possible in several ways. Firstly, by giving preference to as interdisciplinary a terminology as possible; secondly, by carefully defining and discussing all key terms. This ensures that a wide readership, including people from different mathematical backgrounds and different understandings of measurement can all benefit from this work. Concerning mathematics, all the main results are preceded by intuitive discussions and illustrated by simple examples. Moreover, precise proofs are always included in order to enable the more demanding readers to make conscious and creative use of these ideas, and also to develop new ones. The book demonstrates that measurement, which is commonly understood to be a merely experimental matter, poses theoretical questions which are no less challenging than those arising in other, apparently more theoretical, disciplines.

The present book deals with the quantitative measures of information so as to provide their applications in different fields of Operations Research and Statistics. It is worth mentioning that the two basic concepts, viz, entropy and divergence which are closely related to each other have been investigated and applied to various disciplines of Mathematical Sciences. Another idea providing a holistic view of problems comes under the domain of Jaynes "Maximum Entropy Principle" which deals with the problems of obtaining the most unbiased probability distributions under a set of specified constraints. The contents of the book provide a detailed study of the maximum entropy principle. I sincerely hope that the present volume of the book will be useful to all those interested in the mathematical models and their optimization. Moreover, it will be a source of inspiration and encouragement to all research scholars and teachers to discourse the subject for the discovery of new insights.

The last two decades have witnessed an enormous growth with regard to ap plications of information theoretic framework in areas of physical, biological, engineering and even social sciences. In particular, growth has been spectac ular in the field of information technology,soft computing,nonlinear systems and molecular biology. Claude Shannon in 1948 laid the foundation of the field of information theory in the context of communication theory. It is in deed remarkable that his framework is as relevant today as was when he 1 proposed it. Shannon died on Feb 24, 2001. Arun Netravali observes "As if assuming that inexpensive, high-speed processing would come to pass, Shan non figured out the upper limits on communication rates. First in telephone channels, then in optical communications, and now in wireless, Shannon has had the utmost value in defining the engineering limits we face". Shannon introduced the concept of entropy. The notable feature of the entropy frame work is that it enables quantification of uncertainty present in a system. In many realistic situations one is confronted only with partial or incomplete information in the form of moment, or bounds on these values etc. ; and it is then required to construct a probabilistic model from this partial information. In such situations, the principle of maximum entropy provides a rational ba sis for constructing a probabilistic model. It is thus necessary and important to keep track of advances in the applications of maximum entropy principle to ever expanding areas of knowledge.

Radiation Dosimetry, Second Edition, VOLUME III: Sources, Fields, Measurements, and Applications covers the significant aspects of radiation dosimetry. The book discusses dosimetry relating to x rays and teleisotope gamma rays, discrete and distributed alpha-, beta-, and gamma-ray sources, electron beams, and heavy charged particle beams. The text also describes dosimetry relating to reactors, neutron and mixed n-gamma fields, neutrons from accelerators and radioactive sources, initial and residual ionizing radiation from nuclear weapons, natural and man-made background radiation, radiation in space, ultra-high energy radiation, and uncommon types of particles. Dosimetry relating to health physics, diobiology, radiotherapy, implant and intracavitary therapy, ""transition-zones"" (especially at bone-tissue interfaces), and radiation processing is also considered. Physicists, biophysicists, and people involved in radiological science will find the book invaluable.

As Leonardo da Vinci once said, “Simplicity is the ultimate sophistication.” This book is evidence of how diverse problems can be solved using basic statistical methods; from the minute molecule level to widespread epidemic issues, data analysis can be accomplished using basic statistical methods with sound scientific thinking. This book is a valuable resource for students, academics and practitioners seeking simple yet effective solutions to real problems. The six chapters presented are indeed worthy additions to the literature, which will potentially enhance understanding of statistics and its applications. Statistics is a scientific way of unravelling the story behind the data – enjoy the story!