21 resultados para interest costs

em Cambridge University Engineering Department Publications Database


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The article provides information on a study on the potential of mixing ventilation in reducing energy costs in buildings such as theaters and schools. The study found that neither Manchester’s Contact Theatre and the Garrick Theatre in Lichfield in England is operating according to the displacement-ventilation principle upon which they were designed. Hybrid mixing ventilation has an important impact on both the ventilation rate and the thermal comfort of the theatres.

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This paper presents a novel approach using combined features to retrieve images containing specific objects, scenes or buildings. The content of an image is characterized by two kinds of features: Harris-Laplace interest points described by the SIFT descriptor and edges described by the edge color histogram. Edges and corners contain the maximal amount of information necessary for image retrieval. The feature detection in this work is an integrated process: edges are detected directly based on the Harris function; Harris interest points are detected at several scales and Harris-Laplace interest points are found using the Laplace function. The combination of edges and interest points brings efficient feature detection and high recognition ratio to the image retrieval system. Experimental results show this system has good performance. © 2005 IEEE.

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Hydroxyapatite-gelatin composites have been proposed as suitable scaffolds for bone and dentin tissue regeneration. There is considerable interest in producing these scaffolds using biomimetic methods due to their low energy costs and potential to create composites similar to the tissues they are intended to replace. Here an existing process used to coat a surface with hydroxyapatite under near physiological conditions, the alternate soaking process, is modified and automated using an inexpensive "off the shelf" robotics kit. The process is initially used to precipitate calcium phosphate coatings. Then, in contrast to previous utilizations of the alternate soaking process, gelatin was added directly to the solutions in order to co-precipitate hydroxyapatite-gelatin composites. Samples were investigated by Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive X-ray spectroscopy and nanoindentation. Calcium phosphate coatings formed by the alternate soaking process exhibited different calcium to phosphate ratios, with correspondingly distinct structural morphologies. The coatings demonstrated an interconnected structure with measurable mechanical properties, even though they were 95% porous. In contrast, hydroxyapatite-gelatin composite coatings over 2mm thick could be formed with little visible porosity. The hydroxyapatite-gelatin composites demonstrate a composition and mechanical properties similar to those of cortical bone.

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This paper presents the first performance evaluation of interest points on scalar volumetric data. Such data encodes 3D shape, a fundamental property of objects. The use of another such property, texture (i.e. 2D surface colouration), or appearance, for object detection, recognition and registration has been well studied; 3D shape less so. However, the increasing prevalence of depth sensors and the diminishing returns to be had from appearance alone have seen a surge in shape-based methods. In this work we investigate the performance of several detectors of interest points in volumetric data, in terms of repeatability, number and nature of interest points. Such methods form the first step in many shape-based applications. Our detailed comparison, with both quantitative and qualitative measures on synthetic and real 3D data, both point-based and volumetric, aids readers in selecting a method suitable for their application. © 2011 IEEE.

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The drive to reduce carbon emissions from domestic housing has led to a recent shift of focus from new-­‐build to retrofit. However there are two significant differences. Firstly more work is needed to retrofit existing housing to the same energy efficiency standards as new-­‐build. Secondly the remaining length of service life is potentially shorter. This implies that the capital expenditure – both financial and carbon -­‐ of retrofit may be disproportionate to the savings gained over the remaining life. However the Government’s definition of low and zero carbon continues to exclude the capital (embodied) carbon costs of construction, which has resulted in a lack of data for comparison. The paper addresses this gap by reporting the embodied carbon costs of retrofitting four individual pilot properties in Rampton Drift, part of an Eco-­‐Town Demonstrator Project in Cambridgeshire. Through collecting details of the materials used and their journeys from manufacturer to site, the paper conducts a ‘cradle-­‐to-­‐gate’ life cycle carbon assessment for each property. The embodied carbon figures are calculated using a software tool being developed by the Centre for Sustainable Development at the University of Cambridge. The key aims are to assess the real embodied carbon costs of retrofit of domestic properties, and to test the new tool; it is hoped that the methodology, the tool and the specific findings will be transferable to other projects. Initial changes in operational energy as a result of the retrofit works will be reported and compared with the embodied carbon costs when presenting this paper.

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We present a matching framework to find robust correspondences between image features by considering the spatial information between them. To achieve this, we define spatial constraints on the relative orientation and change in scale between pairs of features. A pairwise similarity score, which measures the similarity of features based on these spatial constraints, is considered. The pairwise similarity scores for all pairs of candidate correspondences are then accumulated in a 2-D similarity space. Robust correspondences can be found by searching for clusters in the similarity space, since actual correspondences are expected to form clusters that satisfy similar spatial constraints in this space. As it is difficult to achieve reliable and consistent estimates of scale and orientation, an additional contribution is that these parameters do not need to be determined at the interest point detection stage, which differs from conventional methods. Polar matching of dual-tree complex wavelet transform features is used, since it fits naturally into the framework with the defined spatial constraints. Our tests show that the proposed framework is capable of producing robust correspondences with higher correspondence ratios and reasonable computational efficiency, compared to other well-known algorithms. © 1992-2012 IEEE.

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Pavement condition assessment is essential when developing road network maintenance programs. In practice, the data collection process is to a large extent automated. However, pavement distress detection (cracks, potholes, etc.) is mostly performed manually, which is labor-intensive and time-consuming. Existing methods either rely on complete 3D surface reconstruction, which comes along with high equipment and computation costs, or make use of acceleration data, which can only provide preliminary and rough condition surveys. In this paper we present a method for automated pothole detection in asphalt pavement images. In the proposed method an image is first segmented into defect and non-defect regions using histogram shape-based thresholding. Based on the geometric properties of a defect region the potential pothole shape is approximated utilizing morphological thinning and elliptic regression. Subsequently, the texture inside a potential defect shape is extracted and compared with the texture of the surrounding non-defect pavement in order to determine if the region of interest represents an actual pothole. This methodology has been implemented in a MATLAB prototype, trained and tested on 120 pavement images. The results show that this method can detect potholes in asphalt pavement images with reasonable accuracy.

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We propose a new approach for quantifying regions of interest (ROIs) in medical image data. Rotationally invariant shape descriptors (ISDs) were applied to 3D brain regions extracted from MRI scans of 5 Parkinson's patients and 10 control subjects. We concentrated on the thalamus and the caudate nucleus since prior studies have suggested they are affected in Parkinson's disease (PD). In the caudate, both the ISD and volumetric analyses found significant differences between control and PD subjects. The ISD analysis however revealed additional differences between the left and right caudate nuclei in both control and PD subjects. In the thalamus, the volumetric analysis showed significant differences between PD and control subjects, while ISD analysis found significant differences between the left and right thalami in control subjects but not in PD patients, implying disease-induced shape changes. These results suggest that employing ISDs for ROI characterization both complements and extends traditional volumetric analyses. © 2006 IEEE.