110,275 research outputs found

    Designing low carbon buildings : a framework to reduce energy consumption and embed the use of renewables

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    EU policies to mitigate climate change set ambitious goals for energy and carbon reduction for the built environment. In order meet and even exceed the EU targets the UK Government's Climate Change Act 2008 sets a target to reduce greenhouse gas emissions in the UK by at least 80% from 1990 levels by 2050. To support these targets the UK government also aims to ensure that 20% of the UK's electricity is supplied from renewable sources by 2020. This article presents a design framework and a set of integrated IT tools to enable an analysis of the energy performance of building designs, including consideration of active and passive renewable energy technologies, when the opportunity to substantially improve the whole life-cycle energy performance of those designs is still open. To ensure a good fit with current architectural practices the design framework is integrated with the Royal Institute of British Architects (RIBA) key stages, which is the most widely used framework for the delivery of construction projects. The main aims of this article are to illustrate the need for new approaches to support low carbon building design that can be integrated into current architectural practice, to present the design framework developed in this research and illustrate its application in a case study

    Persuading developers to buy into software process improvement: a local opinion and empirical evidence

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    This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.---- Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.In order to investigate practitioners’ opinions of software process and software process improvement, we have collected a large volume of qualitative evidence from 13 companies. At the same time, other researchers have reported investigations of practitioners, and we are interested in how their reports may relate to our evidence. Thus, other research publications can also be treated as a form of qualitative data. In this paper, we review advice on a method, content analysis, that is used to analyse qualitative data. We use content analysis to describe and analyse discussions on software process and software process improvement. We report preliminary findings from an analysis of both the focus group evidence and four publications

    Persuading developers to buy into software process improvement: an exploratory analysis

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    In order to investigate practitioners' opinions of software process and software process improvement, we have collected information from 13 companies, in a variety of ways i.e. the use of Repertory Grid Technique, survey and focus group discussions. Both the Repertory Grid Technique and the focus group discussions (43 discussions occurred, in total) produced a large volume of qualitative data. At the same time, other researchers have reported--investigations of practitioners, and we are interested in how their reports may relate to our own. Thus, other research publications can also be treated as a form of qualitative data. In this paper, we review advice on a method, content analysis, that is used to analyse qualitative data. Content analysis is a method for identifying and classifying words and phrases used in--ordinary language. We use content analysis to describe and analyse discussions on software--process and software process improvement. We report preliminary findings from an analysis--of both the focus group evidence and some publications. Our main finding is that there is an--apparent contradiction between developers saying that they want evidence for software process improvement, and what developers will accept as evidence. This presents a serious problem for research: even if researchers could demonstrate a strong, reliable relationship between software process improvement and improved organisational performance, there would still be the problem of convincing practitioners that the evidence applies to their particular situation

    Development of a Computer Vision-Based Three-Dimensional Reconstruction Method for Volume-Change Measurement of Unsaturated Soils during Triaxial Testing

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    Problems associated with unsaturated soils are ubiquitous in the U.S., where expansive and collapsible soils are some of the most widely distributed and costly geologic hazards. Solving these widespread geohazards requires a fundamental understanding of the constitutive behavior of unsaturated soils. In the past six decades, the suction-controlled triaxial test has been established as a standard approach to characterizing constitutive behavior for unsaturated soils. However, this type of test requires costly test equipment and time-consuming testing processes. To overcome these limitations, a photogrammetry-based method has been developed recently to measure the global and localized volume-changes of unsaturated soils during triaxial test. However, this method relies on software to detect coded targets, which often requires tedious manual correction of incorrectly coded target detection information. To address the limitation of the photogrammetry-based method, this study developed a photogrammetric computer vision-based approach for automatic target recognition and 3D reconstruction for volume-changes measurement of unsaturated soils in triaxial tests. Deep learning method was used to improve the accuracy and efficiency of coded target recognition. A photogrammetric computer vision method and ray tracing technique were then developed and validated to reconstruct the three-dimensional models of soil specimen

    Digital Image Access & Retrieval

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    The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

    Curved Gabor Filters for Fingerprint Image Enhancement

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    Gabor filters play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved Gabor filters which locally adapt their shape to the direction of flow. These curved Gabor filters enable the choice of filter parameters which increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved Gabor filters are applied to the curved ridge and valley structure of low-quality fingerprint images. First, we combine two orientation field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation and they are used for estimating the local ridge frequency. Lastly, curved Gabor filters are defined based on curved regions and they are applied for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison to state-of-the-art enhancement methods

    Modeling Brain Circuitry over a Wide Range of Scales

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    If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Electron Microscopes (EM) can now provide the nanometer resolution that is needed to image synapses, and therefore connections, while Light Microscopes (LM) see at the micrometer resolution required to model the 3D structure of the dendritic network. Since both the topology and the connection strength are integral parts of the brain's wiring diagram, being able to combine these two modalities is critically important. In fact, these microscopes now routinely produce high-resolution imagery in such large quantities that the bottleneck becomes automated processing and interpretation, which is needed for such data to be exploited to its full potential. In this paper, we briefly review the Computer Vision techniques we have developed at EPFL to address this need. They include delineating dendritic arbors from LM imagery, segmenting organelles from EM, and combining the two into a consistent representation
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