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Analyses, in conjunction with Internal Components, the performance requirements of building components and the effectiveness of typical solutions. External components integrates logically with the theoretical aspects explored in other titles in the Mitchell's building series. It encourages evaluation of alternative methods for putting components together.
This text provides a basic introduction to the building process and analyzes a building in terms of what it is expected to do, the processes required, the building team which implements the processes, the methods used for communicating information and a typical construction method. Topics covered include: the requirements of a building; appearance; durability; dimensional suitability; strength and stability; weather exclusion; sound control; thermal comfort; fire protection; lighting and ventilating; sanitation; security; cost; building processes; the building team; communication; and construction method.
The construction of buildings is learnt through experience and the inheritance of a tradition in forming buildings over several thousand years. Successful construction learns from this experience which becomes embodied in principles of application. Though materials and techniques change, various elements have to perform the same function. 'Principles of Element Design' identifies all the relevant elements and then breaks these elements down into all their basic constituents, making it possible for students to fully understand the given theory and principles behind each part. As all building projects are subject to guidance through the Building Regulations and British Standards, this book gives an immediate reference back to relevant information to help practitioners and contractors identify key documents needed. Yvonne Dean B.A. (Hons) B.A (Open) RIBA, an architect, energy consultant and materials technologist. She also has 15 years experience as a lecturer, travels widely and is a guest lecturer at many universities. She pioneered an access course for Women into Architecture and Building, which has been used as a template by others, and has been instrumental in helping to change the teaching of technology for architects and designers. Peter Rich AA Dipl. (Hons) Architect, started his career with 14 years experience as a qualified architectural technician. He then joined the AA School of Architecture, working with Bill Allen and John Bickerdike after his graduation, later becoming a partner of Bickerdike Allen Rich and Partners. He also taught building construction at the Bartlett School of Architecture, University College London, and architectural design at the Polytechnic of North London. He now acts as a Consultant.
Treating architecture as an international culture, this edition's world-wide coverage encompasses information targeted to those researching, working, and training in the related fields of architecture, construction, and design. Contents include associations, organizations, and libraries; databases: information technology; peri-regulations; official publications; maps, drawings, slides; real estate, site evaluation, market potential; design data; executing the design; landscape; interior design; managing the design office; quality issues; practice libraries; conservation; architectural history, and more.
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates.
"'Published by the Sustainable Agriculture Research and Education (SARE) program, with funding from the National Institute of Food and Agriculture, U.S. Department of Agriculture."

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