A collection of random events (short science fiction and fantasy stories) from the life and mind of Joe Sweeney

Nancy Kress cemented her reputation in SF with the publication of her multiple-award–winning novella, “Beggars in Spain,” which became the basis for her extremely successful Beggars Trilogy (comprising Beggars in Spain, Beggars and Choosers, and Beggars Ride). And now she brings us Probability Space, the conclusion of the trilogy that began with Probability Moon and then Probability Sun, which is centered on the same world as Kress’s Nebula Award-winning novelette, “Flowers of Aulit Prison.” The Probability Trilogy has already been widely recognized as the next great work by this important SF writer. In Probability Space, humanity’s war with the alien Fallers continues, and it is a war we are losing. Our implacable foes ignore all attempts at communication, and they take no prisoners. Our only hope lies with an unlikely coalition: Major Lyle Kaufman, retired warrior; Marbet Grant, the Sensitive who’s involved with Kaufman; Amanda, a very confused fourteen-year-old girl; and Magdalena, one of the biggest power brokers in all of human space. As the action moves from Earth to Mars to the farthest reaches of known space, with civil unrest back home and alien war in deep space, four humans--armed with little more than an unproven theory--try to enter the Fallers’ home star system. It’s a desperate gamble, and the fate of the entire universe may hang in the balance.

Even You Can Learn Statistics, 2nd Ed. is the easiest guide to using statistics in your everyday work or study. Experienced educators David Levine and David Stephan teach statistics hands-on, in plain English, with as little math and as many revealing examples as possible. Levine and Stephan define each concept and technique in plain English, and then explain why it's important, when it's used, and how you can apply it yourself. This Second Edition is fully-updated. Along the way, Levine and Stephan also help you overcome common misconceptions about statistics, so you can use any statistical method more confidently and successfully. In this classic book, long-time CEO Robert Follett shows you exactly how to "keep score" in business by reading and interpreting company financials. Step by step, Follett helps you capture crucial insights buried in balance sheets, income statements, and other key financial reports. Follett shows how to apply core tools for analyzing financial reports and investment opportunities, and demystifies key accounting terms every manager and investor needs to know. This book won't turn you into an accountant, but it will enable you to work confidently with accountants, auditors, financial analysts, budget directors, controllers, treasurers, bankers, and brokers—and make more informed business decisions every single day. Thoroughly updated for current financial practices, How to Keep Score in Business, Second Edition covers all this, and much more.

Advanced Statistics from an Elementary Point of View is a highly readable text that communicates the content of a course in mathematical statistics without imposing too much rigor. It clearly emphasizes the connection between statistics and probability, and helps students concentrate on statistical strategies without being overwhelmed by calculations. The book provides comprehensive coverage of descriptive statistics; detailed treatment of univariate and bivariate probability distributions; and thorough coverage of probability theory with numerous event classifications. This book is designed for statistics majors who are already familiar with introductory calculus and statistics, and can be used in either a one- or two-semester course. It can also serve as a statistics tutorial or review for working professionals. Students who use this book will be well on their way to thinking like a statistician in terms of problem solving and decision-making. Graduates who pursue careers in statistics will continue to find this book useful, due to numerous statistical test procedures (both parametric and non-parametric) and detailed examples. - Comprehensive coverage of descriptive statistics - More detailed treatment of univariate and bivariate probability distributions - Thorough coverage of probability theory with numerous event classifications

This two-volume set is part of a growing body of literature concerned with the history of biblical interpretation. The ample introduction first sets key players into the story of the development of the major strands of biblical interpretation since the Enlightenment, identifying how different theoretical and methodological approaches are related to each other and describing the academic environment in which they emerged and developed. Volume 1 contains fourteen essays on twenty-two interpreters who were principally active before 1980, and volume 2 has nineteen essays on twenty-seven of those who were active primarily after this date. Each chapter provides a brief biography of one or more scholars, as well as a detailed description of their major contributions to the field. This is followed by an (often new) application of the scholar's theory. By focusing on the individual scholars and their work, the book recognizes that interpretive approaches arise out of certain circumstances, and that scholars are influenced by, and have influences upon, both other interpreters and the times in which they live. This set is ideal for any class on the history of biblical interpretation and for those who want a greater understanding of how the current field of biblical studies developed.

Three men meet in Vietnam and become involved in a psychological struggle in a world of mysticism, black marketing, CIA espionage, revenge, and horrific helicopter battle campaigns. The story begins when FBI agent Alignman investigates an occult movement and its links to drugs and politics. To discover its origin and to capture its leaders, Alignman encounters Jarrett who is a retired CIA agent, voluntarily living in a mental ward. Only Jarrett understands the origin and the personality of the occult movement that first began in Vietnam during the Tet Offensive of 1972. In Dr. Peterson’s ofice, Jarrett recalls a series of events which bring into an acute focus his struggle to maintain his identity against the whims of evil and good. Badlock and Nicewander enter Jarrett’s arena of good and evil where all realities intertwine and merge into a surrealism recalling Dante and Faust. The Birdcatcher, who resides in Hades, also enters the stadium of this mystical struggle and sets in motion the terrible and horrific events that will spell either the damnation or the redemption of Jarrett.

A bridge between the application of subspace-based methods for parameter estimation in signal processing and subspace-based system identification in control systems Model-Based Processing: An Applied Subspace Identification Approach provides expert insight on developing models for designing model-based signal processors (MBSP) employing subspace identification techniques to achieve model-based identification (MBID) and enables readers to evaluate overall performance using validation and statistical analysis methods. Focusing on subspace approaches to system identification problems, this book teaches readers to identify models quickly and incorporate them into various processing problems including state estimation, tracking, detection, classification, controls, communications, and other applications that require reliable models that can be adapted to dynamic environments. The extraction of a model from data is vital to numerous applications, from the detection of submarines to determining the epicenter of an earthquake to controlling an autonomous vehicles—all requiring a fundamental understanding of their underlying processes and measurement instrumentation. Emphasizing real-world solutions to a variety of model development problems, this text demonstrates how model-based subspace identification system identification enables the extraction of a model from measured data sequences from simple time series polynomials to complex constructs of parametrically adaptive, nonlinear distributed systems. In addition, this resource features: Kalman filtering for linear, linearized, and nonlinear systems; modern unscented Kalman filters; as well as Bayesian particle filters Practical processor designs including comprehensive methods of performance analysis Provides a link between model development and practical applications in model-based signal processing Offers in-depth examination of the subspace approach that applies subspace algorithms to synthesized examples and actual applications Enables readers to bridge the gap from statistical signal processing to subspace identification Includes appendices, problem sets, case studies, examples, and notes for MATLAB Model-Based Processing: An Applied Subspace Identification Approach is essential reading for advanced undergraduate and graduate students of engineering and science as well as engineers working in industry and academia.