8 resultados para Meaning Construction. Cognitive Domains. Discourse Pattern

em Cambridge University Engineering Department Publications Database


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This book will be of particular interest to academics, researchers, and graduate students at universities and industrial practitioners seeking to apply mobile and pervasive computing systems to improve construction industry productivity.

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A pair of blades were constructed following a Tapered Chord, Zero Twist pattern after Anderson. The construction uses the Wood Epoxy Saturation Technique, with a solid Beech main spar and leading edge joined together with laminated veneers of beech forming a D-section; the trailing edge is formed from millimetre ply skins, foam filled to resist compressive loads. This construction leads to an extremely light, flexible blade, with the centres of gravity and torsion well forward, giving good stability. Each blade has three built-in strain gauges, alowing flapwise bending to be measured. Stiffness, and natural frequencies, were measured, to input to a numerical computer model to calculate blade deformation during operation, and to determine stability boundaries of the blade. Preliminary aerodynamic performance measurements are presented and close agreement is found with theory.

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Images represent a valuable source of information for the construction industry. Due to technological advancements in digital imaging, the increasing use of digital cameras is leading to an ever-increasing volume of images being stored in construction image databases and thus makes it hard for engineers to retrieve useful information from them. Content-Based Search Engines are tools that utilize the rich image content and apply pattern recognition methods in order to retrieve similar images. In this paper, we illustrate several project management tasks and show how Content-Based Search Engines can facilitate automatic retrieval, and indexing of construction images in image databases.

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In the modern and dynamic construction environment it is important to access information in a fast and efficient manner in order to improve the decision making processes for construction managers. This capability is, in most cases, straightforward with today’s technologies for data types with an inherent structure that resides primarily on established database structures like estimating and scheduling software. However, previous research has demonstrated that a significant percentage of construction data is stored in semi-structured or unstructured data formats (text, images, etc.) and that manually locating and identifying such data is a very hard and time-consuming task. This paper focuses on construction site image data and presents a novel image retrieval model that interfaces with established construction data management structures. This model is designed to retrieve images from related objects in project models or construction databases using location, date, and material information (extracted from the image content with pattern recognition techniques).

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Over the last decade, research in medical science has focused on knowledge translation and diffusion of best practices to enable improved health outcomes. However, there has been less attention given to the role of policy in influencing the translation of best practice across different national contexts. This paper argues that the underlying set of public discourses of healthcare policy significantly influences its development with implications for the dissemination of best practices. Our research uses Critical Discourse Analysis to examine the policy discourses surrounding the treatment of stroke across Canada and the U.K. It focuses in specific on how concepts of knowledge translation, user empowerment, and service innovation construct different accounts of the health service in the two countries. These findings provide an important yet overlooked starting point for understanding the role of policy development in knowledge transfer and the translation of science into health practice. © 2011 Operational Research Society. All rights reserved.

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Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper presents the beginnings of an automatic statistician, focusing on regression problems. Our system explores an open-ended space of statistical models to discover a good explanation of a data set, and then produces a detailed report with figures and natural- language text. Our approach treats unknown regression functions non- parametrically using Gaussian processes, which has two important consequences. First, Gaussian processes can model functions in terms of high-level properties (e.g. smoothness, trends, periodicity, changepoints). Taken together with the compositional structure of our language of models this allows us to automatically describe functions in simple terms. Second, the use of flexible nonparametric models and a rich language for composing them in an open-ended manner also results in state- of-the-art extrapolation performance evaluated over 13 real time series data sets from various domains.