Geo.Engineerings

George E. P. Box,‎ George C. Tiao ... 588 pages - Publisher: Addison-Wesley Publishing; 1st edition (June, 1973) ... Language: English - ISBN-10: 0201006227 - ISBN-13: 978-0201006223 ... Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a prior. Begins with a discussion of some important general aspects of the Bayesian approach such as the choice of prior distribution, particularly non-informative prior distribution, the problem of nuisance parameters and the role of sufficient statistics, followed by many standard problems concerned with the comparison of location and scale parameters. The main thrust is an investigation of questions with appropriate analysis of mathematical results which are illustrated with numerical examples, providing evidence of the value of the Bayesian approach.

George C. Lee, Ernest Sternberg ... 180 pages - Publisher: State Univ. of New York Press (March, 2015) ... Language: English - ISBN-10: 1438455267 - ISBN-13: 978-1438455266 ...

Whether you are a student considering a career in civil engineering and transportation planning, a public official interested in the future of infrastructure, or a person who simply cares about bridges, this book offers an accessible and illustrated introduction to the most beloved feature of our built environment. Learn about engineering basics: the forces that bridges must resist to stay aloft and the principles by which engineers decide which types of bridges make sense at which sites. Find out how engineers protect bridges from their greatest threats—the earthquakes, floods, and other hazards that can cause catastrophic damage. Moving from engineering to planning, learn how we decide whether a bridge is worth building in the first place, learn about controversial features of cost-benefit analysis, and about the transportation models by which planners forecast bridge effects on traffic patterns. Investigate a sometimes intractable problem: why a project often creeps along for a decade or more to get from initial studies to the day the ribbon is cut, undergoing vast cost escalations. Also explore the environmental impact of bridges, and the meaning of a “sustainable bridge,” and whether bridges could once again be built, like ancient Roman ones, to last a thousand years.

Convolutional networks (CNNs) are deep artificial neural networks that can be used to classify images (name what they see), cluster them by similarity (photo search), and perform object recognition within scenes. They are algorithms that can identify faces, individuals, street signs, eggplants, platypuses and many other aspects of visual data. Convolutional networks perform optical character recognition (OCR) to digitize text and make natural-language processing possible on analog and hand-written documents, where the images are symbols to be transcribed. CNNs can also be applied to sound when it is represented visually as a spectrogram. More recently, convolutional networks have been applied directly to text analytics as well as graph data with graph convolutional networks. The efficacy of convolutional nets (ConvNets or CNNs) in image recognition is one of the main reasons why the world has woken up to the efficacy of deep learning. They are powering major advances in machine vision, which has obvious applications for self-driving cars, robotics, drones, security, medical diagnoses, and treatments for the visually impaired.