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The construction industry is redefining effective partnering through the implementation of common information exchange standards - and no one can afford to be left behind.In a text that is steered towards commercial objectives rather than towards technological discussion, this book sets out the commercial issues driving, or hampering, recent developments, aiming to dispel the many myths that generate excuses for inertia. Business managers will then be able to make informed decisions and achieve operational benefits.
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This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition.Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and integrate by machine learning procedures. However, if the relations are captured by sets of dissimilarities, general data analysis procedures may be applied for analysis.With their detailed description of an unprecedented approach absent from traditional textbooks, the authors have crafted an essential book for every researcher and systems designer studying or developing pattern recognition systems.
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The construction industry is an information-intensive sector and low levels of productivity are often blamed on inadequate integration of information. This book shows how the different types and sources of information can be integrated to benefit individual construction projects, construction companies and in the construction industry at world-wide level.
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Reproduction of the original: Attila by George Payne Rainsford James