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Someone is trying to resurrect ancient viruses hidden deep within the human genetic code to create a biological weapon so specific that it can target an individual . . . or an entire race. When two young prodigies discover their "medical research" is being used to build this weapon, they seek outside help to destroy it and to flee China. Help comes in the unlikely guise of Jon Gunderson-doctor, bio-weapons expert, and devoted family man whose unsuspecting wife and nine children have unwittingly accompanied him on yet another assignment. Once the truth comes to light, the Gundersons will have to set aside their differences if they hope to rescue the prodigies and escape with their lives. The fate of the world hangs in the balance as the bittersweet dynamics of a large but loving family take center stage against the backdrop of China's breathtaking landscapes.
THE PRODIGY have sold 25 million records and single-handedly reinvented the crossover between dance and rock music, with legendary songs such as 'Firestarter', 'Omen' and 'Breathe'. However, long before they became a stadium-filling rock monster, The Prodigy were prowling the underground of the UK rave scene, first as a blistering demo of tunes by the 'prodigious' teenage Liam Howlett, then latterly with their breakthrough masterpiece, Music For The Jilted Generation.Martin Roach was present throughout the band's early years and documented their rise from the underground into the bright lights of music superstardom. Containing hours and hours of exclusive interviews, the book chronicles the band's early years in minute detail, speaking to each band member and all the key players along the way.With a new introduction by Liam Howlett putting this classic early phase in the context of their historically important career, this book is a must-buy for the millions of Prodigy fans eager to learn about the band's formative days.
Temporal Information Systems in Medicine introduces the engineering of information systems for medically-related problems and applications. The chapters are organized into four parts; fundamentals, temporal reasoning & maintenance in medicine, time in clinical tasks, and the display of time-oriented clinical information. The chapters are self-contained with pointers to other relevant chapters or sections in this book when necessary. Time is of central importance and is a key component of the engineering process for information systems. This book is designed as a secondary text or reference book for upper -undergraduate level students and graduate level students concentrating on computer science, biomedicine and engineering. Industry professionals and researchers working in health care management, information systems in medicine, medical informatics, database management and AI will also find this book a valuable asset.
From award-winning sportswriter John Feinstein, a YA novel about a teen golfer poised to blaze his way into Masters Tournament history—and he’ll face secrecy, sacrifice, and the decision of a lifetime to get there. Seventeen-year-old Frank Baker is a golfing sensation. He’s set to earn a full-ride scholarship to play at the university of his choice, but his single dad wants him to skip college and turn pro—golf has taken its toll on the family bank account, and his dad is eager to start cashing in on his son’s prowess. Frank knows he isn’t ready for life on the pro tour—regardless of the potential riches—so his swing coach enlists a professional golfer turned journalist to be Frank’s secret adviser. Pressure mounts when, after reaching the final of the U.S. Amateur tournament, Frank wins an automatic invite to the Masters. And when the prodigy, against all odds, starts tearing up the course at Augusta National, sponsors are lined up to throw money at him—and his father. But Frank’s entry in the Masters hinges on maintaining his standing as an amateur. Can he and his secret adviser—who has his own conflicts—keep Frank’s dad at bay long enough to bring home the legendary green jacket?
"A memoir about a life almost lost and a revealing look at the dark side of hip hop's golden era ... a story of struggle, survival, and hope down the mean streets of New York City" --
We all know the autistic genius stereotypes. The absentminded professor with untied shoelaces. The geeky Silicon Valley programmer who writes bullet­proof code but can’t get a date. But there is another set of (tiny) geniuses whom you would never add to those ranks—child prodigies. We mostly know them as the chatty and charming tykes who liven up day­time TV with violin solos and engaging banter. These kids aren’t autistic, and there has never been any kind of scientific connection between autism and prodigy. Until now. Over the course of her career, psychologist Joanne Ruthsatz has quietly assembled the largest-ever research sample of these children. Their accomplishments are epic. One could reproduce radio tunes by ear on a toy guitar at two years old. Another was a thirteen-year-old cooking sensation. And what Ruthsatz’s investigation revealed is noth­ing short of astonishing. Though the prodigies aren’t autistic, many have autistic family members. Each prodigy has an extraordinary memory and a keen eye for detail—well-known but often-overlooked strengths associated with autism. Ruthsatz and her daughter and coauthor, Kim­berly Stephens, now propose a startling possibility: What if the abilities of child prodigies stem from a genetic link with autism? And could prodigies— children who have many of the strengths of autism but few of the challenges—be the key to a long-awaited autism breakthrough? In The Prodigy’s Cousin, Ruthsatz and Stephens narrate the poignant stories of the children they have studied, including that of a two-year-old who loved to spell words like “algorithm” and “confeder­ation,” a six-year-old painter who churned out mas­terpieces faster than her parents could hang them, and a typically developing thirteen-year-old who smacked his head against a church floor and woke up a music prodigy. This inspiring tale of extraordinary children, indomitable parents, and a researcher’s unorthodox hunch is essential reading for anyone interested in the brain and human potential. Ruthsatz and Stephens take us from the prodigies’ homes to the depths of the autism archives to the cutting edge of genetics research, all while upending our under­standing of what makes exceptional talent possible.
This book presents thoroughly arranged tutorial papers corresponding to lectures given by leading researchers at the Second International Summer School on Reasoning Web in Lisbon, Portugal, in September 2006. Building on the predessor school held in 2005 and published as LNCS 3564, the ten tutorial lectures presented provide competent coverage of current topics in semantic Web research and development.
Machine Learning: An Artificial Intelligence Approach, Volume III presents a sample of machine learning research representative of the period between 1986 and 1989. The book is organized into six parts. Part One introduces some general issues in the field of machine learning. Part Two presents some new developments in the area of empirical learning methods, such as flexible learning concepts, the Protos learning apprentice system, and the WITT system, which implements a form of conceptual clustering. Part Three gives an account of various analytical learning methods and how analytic learning can be applied to various specific problems. Part Four describes efforts to integrate different learning strategies. These include the UNIMEM system, which empirically discovers similarities among examples; and the DISCIPLE multistrategy system, which is capable of learning with imperfect background knowledge. Part Five provides an overview of research in the area of subsymbolic learning methods. Part Six presents two types of formal approaches to machine learning. The first is an improvement over Mitchell's version space method; the second technique deals with the learning problem faced by a robot in an unfamiliar, deterministic, finite-state environment.
The first volume of a series on Cognition. Looking at Memory, Catergorization, Causal Inference and Problem Solving. First Published in 1990. Routledge is an imprint of Taylor & Francis, an informa company.
One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed.