Peter Lucas - Böcker

World War II found Albania fighting a war within a war. In addition to the threat faced from the Germans, Albania was engaged in a civil war between the Nazi-sponsored Ballists and the Communist partisans led by Enver Hoxha. While America was reluctant to get involved in the civil conflict, the United States was naturally inclined to lend support to whoever fought the Nazis--even if that meant an alliance with the Communists. On a cold November night in 1943, Dale McAdoo (code named Tank) secretly landed on the Albanian coast with a team of OSS (Office of Strategic Services) agents, including Ismail Carapizzi, an Albanian guide and interpreter who would later be murdered. McAdoo's team, the first of many to follow, set up a base of operations in a deep water level cave on the rocky Albanian coast that served the OSS as it carried out its mission of gathering intelligence to support the Allied war effort and harass the Germans. McAdoo was joined by Captain Tom Stefan (code name Art), an Albanian-speaking OSS officer from Boston, whose assignment was to join Hoxha at his remote mountain headquarters and bond with the reclusive Communist leader to benefit the OSS.This volume describes how the OSS aided the Communist-led partisans in an attempt to weaken the Nazi cause in Albania and neighboring Italy. The book presents an in-depth look at the small core of hardened men who comprised these highly specialized teams, including each member's background and his special fitness for his wartime role behind enemy lines. The American and British presence in Albania during World War II and the later deterioration of Hoxha's relations with Captain Tom Stefan and the OSS mission are discussed in detail. Firsthand interviews with still-living participants and extensive onsite research make this book a unique resource for a little-known dramatic piece of World War II history.

We are facing a future of unbounded complexity.  Whether that complexity is harnessed to build a world that is safe, pleasant, humane and profitable, or whether it causes us to careen off a cliff into an abyss of mind-numbing junk is an open question. The challenges and opportunities--technical, business, and human--that this technological sea change will bring are without precedent. Entire industries will be born and others will be laid to ruin as our society navigates this journey. There are already many more computing devices in the world than there are people.  In a few more years, their number will climb into the trillions. We put microprocessors into nearly every significant thing that we manufacture, and the cost of routine computing and storage is rapidly becoming negligible.  We have literally permeated our world with computation.  But more significant than mere numbers is the fact we are quickly figuring out how to make those processors communicate with each other, and with us. We are about to be faced, not with a trillion isolated devices, but with a trillion-node network: a network whose scale and complexity will dwarf that of today’s Internet. And, unlike the Internet, this will be a network not of computation that we use, but of computation that we live in. Written by the leaders of one of America’s leading pervasive computing design firms, this book gives a no-holds-barred insiders’ account of both the promise and the risks of the age of Trillions. It is also a cautionary tale of the head-in-the-sand attitude with which many of today’s thought-leaders are at present approaching these issues. Trillions is a field guide to the future--designed to help businesses and their customers prepare to prosper, in the information.

This book constitutes the refereed proceedings of FME '97, the 4th International Symposium of Formal Methods Europe devoted to Industrial Applications and Strengthened Foundations of Formal Methods , held in Graz, Austria, in September 1997. The 35 revised full papers presented in the volume were selected from a total of 94 submissions. Formal methods and mathematically based techniques are increasingly recognized as a viable technology for the development and engineering of computing systems. The majority of the papers in this volume describe industrial applications, extensions to existing techniques, or case studies; papers on theoretical aspects show clear potential applicability.

In recent years considerable progress has been made in the area of probabilistic graphical models, in particular Bayesian networks and influence diagrams. Probabilistic graphical models have become mainstream in the area of uncertainty in artificial intelligence;contributions to the area are coming from computer science, mathematics, statistics and engineering.This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.

In recent years considerable progress has been made in the area of probabilistic graphical models, in particular Bayesian networks and influence diagrams. Probabilistic graphical models have become mainstream in the area of uncertainty in artificial intelligence;contributions to the area are coming from computer science, mathematics, statistics and engineering.This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.

This book explores the theoretical basis of our ethical obligations to others as self-knowing beings - this task being envisaged as an essential supplement to a traditional ethic of respect for persons. Authoritative knowledge of others brings with it certain obligations, which are reflected in (inter alia) the moral and legal safeguards designed to ensure that certain information is ‘put out of play’ for job selection purposes etc. However, the theoretical basis for such obligations has never been fully clarified. This book begins by identifying a distinctive class of ‘interpretive’ moral wrongs (including stereotyping, discrimination and objectification). It then shows how our obligations in respect of these wrongs can be understood, drawing on insights from the tradition of philosophical reflection on recognition. The book will be of interest to anyone concerned with the adequacy of a modern ethic of respect for persons – particularly in applied and professional ethics.