Providing more than twice the content of the original edition, this new edition is the premier source on the selection, development, and provision of safe, high-quality, and cost-effective electric utility distribution systems, and it promises vast improvements in system reliability and layout by spanning every aspect of system planning including load forecasting, scheduling, performance, and economics. Responding to the evolving needs of electric utilities, Power Distribution Planning Reference Book presents an abundance of real-world examples, procedural and managerial issues, and engineering and analytical methodologies that are crucial to efficient and enhanced system performance.
One notable new direction this century in the study of primes has been the influx of ideas from probability. The goal of this book is to provide insights into the prime numbers and to describe how a sequence so tautly determined can incorporate such a striking amount of randomness. The book opens with some classic topics of number theory. It ends with a discussion of some of the outstanding conjectures in number theory. In between are an excellent chapter on the stochastic properties of primes and a walk through an elementary proof of the Prime Number Theorem. This book is suitable for anyone who has had a little number theory and some advanced calculus involving estimates. Its engaging style and invigorating point of view will make refreshing reading for advanced undergraduates through research mathematicians.
As the digital revolution has democratised film production, a new hybrid model of distribution is the way independent filmmakers can take control of their own distribution. This approach is not just DIY or Web-based - it combines the best techniques from each distribution arena, old and new. In Think Outside the Box Office, Reiss explains audience identification and targeting, negotiating split-rights agreements, the new role of film festivals and more.
The theory of uniform distribution began with Hermann Weyl's celebrated paper of 1916. In later decades, the theory moved beyond its roots in diophantine approximations to provide common ground for topics as diverse as number theory, probability theory, functional analysis, and topological algebra. This book summarizes the theory's development from its beginnings to the mid-1970s, with comprehensive coverage of both methods and their underlying principles. A practical introduction for students of number theory and analysis as well as a reference for researchers in the field, this book covers uniform distribution in compact spaces and in topological groups, in addition to examinations of sequences of integers and polynomials. Notes at the end of each section contain pertinent bibliographical references and a brief survey of additional results. Exercises range from simple applications of theorems to proofs of propositions that expand upon results stated in the text.
Distribution Revolution is a collection of interviews with leading film and TV professionals concerning the many ways that digital delivery systems are transforming the entertainment business. These interviews provide lively insider accounts from studio executives, distribution professionals, and creative talent of the tumultuous transformation of film and TV in the digital era. The first section features interviews with top executives at major Hollywood studios, providing a window into the big-picture concerns of media conglomerates with respect to changing business models, revenue streams, and audience behaviors. The second focuses on innovative enterprises that are providing path-breaking models for new modes of content creation, curation, and distributionÑcreatively meshing the strategies and practices of Hollywood and Silicon Valley. And the final section offers insights from creative talent whose professional practices, compensation, and everyday working conditions have been transformed over the past ten years. Taken together, these interviews demonstrate that virtually every aspect of the film and television businesses is being affected by the digital distribution revolution, a revolution that has likely just begun. Interviewees include: ¥ Gary Newman, Chairman, 20th Century Fox Television ¥ Kelly Summers, Former Vice President, Global Business Development and New Media Strategy, Walt Disney Studios ¥ Thomas Gewecke, Chief Digital Officer and Executive Vice President, Strategy and Business Development, Warner Bros. Entertainment ¥ Ted Sarandos, Chief Content Officer, Netflix ¥ Felicia D. Henderson, Writer-Producer, Soul Food, Gossip Girl ¥ Dick Wolf, Executive Producer and Creator, Law & Order
A new edition of the trusted guide on commonly used statistical distributions Fully updated to reflect the latest developments on the topic, Statistical Distributions, Fourth Edition continues to serve as an authoritative guide on the application of statistical methods to research across various disciplines. The book provides a concise presentation of popular statistical distributions along with the necessary knowledge for their successful use in data modeling and analysis. Following a basic introduction, forty popular distributions are outlined in individual chapters that are complete with related facts and formulas. Reflecting the latest changes and trends in statistical distribution theory, the Fourth Edition features: A new chapter on queuing formulas that discusses standard formulas that often arise from simple queuing systems Methods for extending independent modeling schemes to the dependent case, covering techniques for generating complex distributions from simple distributions New coverage of conditional probability, including conditional expectations and joint and marginal distributions Commonly used tables associated with the normal (Gaussian), student-t, F and chi-square distributions Additional reviewing methods for the estimation of unknown parameters, such as the method of percentiles, the method of moments, maximum likelihood inference, and Bayesian inference Statistical Distributions, Fourth Edition is an excellent supplement for upper-undergraduate and graduate level courses on the topic. It is also a valuable reference for researchers and practitioners in the fields of engineering, economics, operations research, and the social sciences who conduct statistical analyses.
A major revision of an established textbook on the theory, measurement, and history of economic growth, with new material on climate change, corporate capitalism, and innovation. Authors Duncan Foley, Thomas Michl, and Daniele Tavani present Classical and Keynesian approaches to growth theory, in parallel with Neoclassical ones, and introduce students to advanced tools of intertemporal economic analysis through carefully developed treatments of land- and resource-limited growth. They cover corporate finance, the impact of government debt and social security systems, theories of endogenous technical change, and the implications of climate change. Without excessive formal complication, the models emphasize rigorous reasoning from basic economic principles and insights, and respond to students’ interest in the history and policy dilemmas of real-world economies. In addition to carefully worked out examples showing how to use the analytical techniques presented, Growth and Distribution presents many problems suitable for inclusion in problem sets and examinations. Detailed answers to these problems are available. This second edition includes fresh data throughout and new chapters on climate change, corporate capitalism, models of wealth inequality, and technical change.
This book describes the inferential and modeling advantages that this distribution, together with its generalizations and modifications, offers. The exposition systematically unfolds with many examples, tables, illustrations, and exercises. A comprehensive index and extensive bibliography also make this book an ideal text for a senior undergraduate and graduate seminar on statistical distributions, or for a short half-term academic course in statistics, applied probability, and finance.
This textbook introduces the non-specialist reader to the concepts of quantum key distribution and presents an overview of state-of-the-art quantum communication protocols and applications. The field of quantum cryptography has advanced rapidly in the previous years, not least because with the age of quantum computing drawing closer, traditional encryption methods are at risk. The textbook presents the necessary mathematical tools without assuming much background, making it accessible to readers without experience in quantum information theory. In particular, the topic of classical and quantum entropies is presented in great detail. Furthermore, the author discusses the different types of quantum key distribution protocols and explains several tools for proving the security of these protocols. In addition, a number of applications of quantum key distribution are discussed, demonstrating its value to state-of-the-art cryptography and communication. This book leads the reader through the mathematical background with a variety of worked-out examples and exercises. It is primarily targeted at graduate students and advanced undergraduates in theoretical physics. The presented material is largely self-contained and only basic knowledge in quantum mechanics and linear algebra is required.
The Dirichlet distribution appears in many areas of application, which include modelling of compositional data, Bayesian analysis, statistical genetics, and nonparametric inference. This book provides a comprehensive review of the Dirichlet distribution and two extended versions, the Grouped Dirichlet Distribution (GDD) and the Nested Dirichlet Distribution (NDD), arising from likelihood and Bayesian analysis of incomplete categorical data and survey data with non-response. The theoretical properties and applications are also reviewed in detail for other related distributions, such as the inverted Dirichlet distribution, Dirichlet-multinomial distribution, the truncated Dirichlet distribution, the generalized Dirichlet distribution, Hyper-Dirichlet distribution, scaled Dirichlet distribution, mixed Dirichlet distribution, Liouville distribution, and the generalized Liouville distribution. Key Features: Presents many of the results and applications that are scattered throughout the literature in one single volume. Looks at the most recent results such as survival function and characteristic function for the uniform distributions over the hyper-plane and simplex; distribution for linear function of Dirichlet components; estimation via the expectation-maximization gradient algorithm and application; etc. Likelihood and Bayesian analyses of incomplete categorical data by using GDD, NDD, and the generalized Dirichlet distribution are illustrated in detail through the EM algorithm and data augmentation structure. Presents a systematic exposition of the Dirichlet-multinomial distribution for multinomial data with extra variation which cannot be handled by the multinomial distribution. S-plus/R codes are featured along with practical examples illustrating the methods. Practitioners and researchers working in areas such as medical science, biological science and social science will benefit from this book.
