Solar Power in Building Design (GreenSource)

Solar Power in Building Design (GreenSource)

Author: Peter Gevorkian

Publisher: McGraw Hill Professional

Published: 2007-10-05

Total Pages: 506

ISBN-13: 0071594442

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Design, Implement, and Audit the Most Energy-Efficient, Cost-Effective Solar Power Systems for Any Type of Building! Solar Power in Building Design is a complete guide to designing, implementing, and auditing energy-efficient, cost-effective solar power systems for residential, commercial, and industrial buildings. From basic theory through project planning, cost estimating, and manufacturing methods, this vital resource offers you everything needed for solar power design success. Filled with case studies and illustrations, this state-of-the-art design tool covers new solar technologies...design implementation techniques...energy conservation...the economics of solar power systems...passive solar heating power...and more. Solar Power in Building Design features: Step-by-step instructions for designing, implementing, and auditing solar power systems Expert guidance on using solar power in any type of building-from basic theory through project planning, cost estimating, and manufacturing Complete details on Leadership in Energy and Environmental Design (LEED), plus rebate procedures and forms Inside This Cutting-Edge Solar Power Toolkit • Solar power physics and technology • Practical guide to solar power design • Solar power design implementation • Energy conservation • Leadership in Energy and Environmental Design (LEED) • Sustainable energy rebate • Economics of solar power systems • Passive solar heating power


Data Engineering and Data Science

Data Engineering and Data Science

Author: Kukatlapalli Pradeep Kumar

Publisher: John Wiley & Sons

Published: 2023-08-29

Total Pages: 367

ISBN-13: 1119841976

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DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.