866 resultados para classifying spaces


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This paper presents the results of performance monitoring under real winter weather conditions, controlled laboratory testing and computational fluid dynamics (CFD) analysis of a wall mounted ventilation air inlet heat convector. For real winter weather monitoring, the wall-mounted convector was installed in a laboratory room of the Engineering Building of the School of Construction Management and Engineering. Air and hot water temperatures and air speeds were measured at the entrance to the convector and in the room. The hot water temperature was controlled at 40, 60 and 80 °C. The monitoring results were later used as boundary conditions for a CFD simulation to investigate the air movement in the room. Controlled laboratory testing was conducted in laboratories at the University of Reading, UK and at Wetterstad Consultancy, Sweden. The results of the performance investigation showed that the system contributed greatly to the room heating, particularly at a water temperature of 80 °C. Also adequate fresh air was supplied to the room. Such a system is able to provide an energy efficient method of eliminating problems associated with cold winter draughts.

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The content of this paper is a snapshot of a current project looking at producing a real-time sensor-based building assessment tool, and a system that personalises workspaces using multi-agent technology. Both systems derive physical environment information from a wireless sensor network that allows clients to subscribe to real-time sensed data. The principal ideologies behind this project are energy efficiency and well-being of occupants; in the context of leveraging the current state-of-the-art in agent technology, wireless sensor networks and building assessment systems to enable the optimisation and assessment of buildings. Participants of this project are from both industry (construction and research) and academia.

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The results from a range of different signal processing schemes used for the further processing of THz transients are contrasted. The performance of different classifiers after adopting these schemes are also discussed.

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The content of this paper is a snapshot of a current project looking at producing a real-time sensor-based building assessment tool, and a system that personalises work-spaces using multi-agent technology. Both systems derive physical environment information from a wireless sensor network that allows clients to subscribe to real-time sensed data. The principal ideologies behind this project are energy efficiency and well-being of occupants; in the context of leveraging the current state-of-the-art in agent technology, wireless sensor networks and building assessment systems to enable the optimisation and assessment of buildings. Participants of this project are from both industry (construction and research) and academia.

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This paper presents an approach for automatic classification of pulsed Terahertz (THz), or T-ray, signals highlighting their potential in biomedical, pharmaceutical and security applications. T-ray classification systems supply a wealth of information about test samples and make possible the discrimination of heterogeneous layers within an object. In this paper, a novel technique involving the use of Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) models on the wavelet transforms of measured T-ray pulse data is presented. Two example applications are examined - the classi. cation of normal human bone (NHB) osteoblasts against human osteosarcoma (HOS) cells and the identification of six different powder samples. A variety of model types and orders are used to generate descriptive features for subsequent classification. Wavelet-based de-noising with soft threshold shrinkage is applied to the measured T-ray signals prior to modeling. For classi. cation, a simple Mahalanobis distance classi. er is used. After feature extraction, classi. cation accuracy for cancerous and normal cell types is 93%, whereas for powders, it is 98%.

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This paper argues that transatlantic hybridity connects space, visual style and ideological point of view in British television action-adventure fiction of the 1960s–1970s. It analyses the relationship between the physical location of TV series production at Elstree Studios, UK, the representation of place in programmes, and the international trade in television fiction between the UK and USA. The TV series made at Elstree by the ITC and ABC companies and their affiliates linked Britishness with an international modernity associated with the USA, while also promoting national specificity. To do this, they drew on film production techniques that were already common for TV series production in Hollywood. The British series made at Elstree adapted versions of US industrial organization and television formats, and made programmes expected to be saleable to US networks, on the basis of British experiences in TV co-production with US companies and of the international cinema and TV market.

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We propose a simple, yet sufficiently encompassing, classification scheme of monetary economics. It comprises three fundamental fields and six recent areas that expand within and across these fields. The elements of our scheme are not found together and in their mutual relationships in earlier studies of the relevant literature; neither does this attempt aim to produce a relatively complete systematization. Our intention in taking stock is not finality or exhaustiveness. We rather suggest a viewpoint and a possible ordering of the accumulating knowledge. Our purpose is to promote discussion on the evolving nature and internal consistency of monetary economics at large.