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This highly anticipated second volume in the Silencer History and Performance series provides an unprecedented look into the evolution, tactical employment and performance of historic and state-of-the-art silenced firearms suitable for close-quarters combat, long-distance sniping and other professional applications. It chronicles the production of pioneering silenced weapons used during World War II and the Cold War as well as the more sophisticated low-signature designs and tactics that emerged from the Vietnam War and again during an explosion of creative development in the 1990s. The authors have combined recently declassified materials, numerous confidential sources and years of hands-on evaluations to reveal a wealth of information about today's incredible screw-on and integral suppressors.

A new and general method for the critical analysis of binary data is given. Since the method invokes a memory of the distributions and structural model assumed in the processing of the data it is termed self-critical. A single parameter c generates a family of critical estimator - and tests of hypotheses, if warranted. When c=0, the procedure reduces to that of maximum likelihood. The method is derived from primitive considerations exactly parallel to those which result in critical methods for complete data. Both symmetric and asymmetric quantal distributions are considered for regression-type models. A critical procedure for the proportional hazards model, an alternative to the logistic regression model, is introduced and sucessfully applied. Asymptotic results are given. Experience with live data is reported in the examples. Keywords: Robust procedures; Gaussian distribution; Weibull distribution; Asymptotic Covariance matrix; Empirical efficiency ratio.

Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

Any organization considering migrating to open systems will need to be aware of the effects of using open technology. Further, those considering building an open system as part of a migration strategy will have to understand the resulting management and technical issues. Systems integration can be defined as the task of defining, designing, building, testing and rolling-out a system comprising many hardware and software components. By presenting a practical guide to open systems integration this book highlights management issues and provides general advice on possible approaches. The reasons for moving to open systems are highlighted and the evolution of systems integration is summarized.

The New York Times bestseller "Blinder's book deserves its likely place near the top of reading lists about the crisis. It is the best comprehensive history of the episode... A riveting tale." - Financial Times One of our wisest and most clear-eyed economic thinkers offers a masterful narrative of the crisis and its lessons. Many fine books on the financial crisis were first drafts of history—books written to fill the need for immediate understanding. Alan S. Blinder, esteemed Princeton professor, Wall Street Journal columnist, and former vice chairman of the Federal Reserve Board, held off, taking the time to understand the crisis and to think his way through to a truly comprehensive and coherent narrative of how the worst economic crisis in postwar American history happened, what the government did to fight it, and what we can do from here—mired as we still are in its wreckage. With bracing clarity, Blinder shows us how the U.S. financial system, which had grown far too complex for its own good—and too unregulated for the public good—experienced a perfect storm beginning in 2007. Things started unraveling when the much-chronicled housing bubble burst, but the ensuing implosion of what Blinder calls the “bond bubble” was larger and more devastating. Some people think of the financial industry as a sideshow with little relevance to the real economy—where the jobs, factories, and shops are. But finance is more like the circulatory system of the economic body: if the blood stops flowing, the body goes into cardiac arrest. When America’s financial structure crumbled, the damage proved to be not only deep, but wide. It took the crisis for the world to discover, to its horror, just how truly interconnected—and fragile—the global financial system is. Some observers argue that large global forces were the major culprits of the crisis. Blinder disagrees, arguing that the problem started in the U.S. and was pushed abroad, as complex, opaque, and overrated investment products were exported to a hungry world, which was nearly poisoned by them. The second part of the story explains how American and international government intervention kept us from a total meltdown. Many of the U.S. government’s actions, particularly the Fed’s, were previously unimaginable. And to an amazing—and certainly misunderstood—extent, they worked. The worst did not happen. Blinder offers clear-eyed answers to the questions still before us, even if some of the choices ahead are as divisive as they are unavoidable. After the Music Stopped is an essential history that we cannot afford to forget, because one thing history teaches is that it will happen again.

In this volume Alan Mugridge reviews claims that scribes of New Testament manuscripts altered the text of their copies to further their own beliefs, to stop people using them to support opposing beliefs, or for some other purpose. He discusses the New Testament passages about which these claims are made in detail, noting their context, exegesis, and supporting manuscripts. He concludes that while a small number of such claims are valid, most are doubtful because, unless a scribe’s habits are clear in one manuscript, we cannot know how the changes came about, why they were made, who made them, and when they were made. He argues that the bulk of the erroneous readings in New Testament manuscripts reviewed were made by scribal slips during the copying process, and not in order to further anyone’s personal agenda, adding strength to the reliability of the Greek New Testament text available today, despite the need to refine current editions to be as close as possible to the original text.