51 resultados para Application efficiency

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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In this paper, we propose the return-to-cost-ratio (RCR) as an alternative approach to the analysis of operational eco-efficiency of companies based on the notion of opportunity costs. RCR helps to overcome two fundamental deficits of existing approaches to eco-efficiency. (1) It translates eco-efficiency into managerial terms by applying the well-established notion of opportunity costs to eco-efficiency analysis. (2) RCR allows to identify and quantify the drivers behind changes in corporate eco-efficiency. RCR is applied to the analysis of the CO2-efficiency of German companies in order to illustrate its usefulness for a detailed analysis of changes in corporate eco-efficiency as well as for the development of effective environmental strategies. (C) 2010 Elsevier Ltd. All rights reserved.

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Colloidal gas aphrons (CGAs) are micron-sized gas bubbles of 25–30 µm in diameter produced by a high-speed stirrer in a vessel containing dilute surfactant solution. These bubbles, because of their small size, exhibit some colloidal properties. In this work, CGAs were used to separate fine fibres from a lean slurry of cellulosic pulp in a flotation column. The pulp fibres were recovered as foamate from the top. Sodium dodecyl sulphate at a concentration of 2.0 kg/m3 was used as a surfactant to generate the CGAs in a spinning disc apparatus. The results indicated that up to 70% flotation efficiency could be obtained within a short column height of 0.3–0.35 m. This technique can be applied to recover fine cellulosic pulp from paper-machine backwater.

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This study concerns the spatial allocation of material flows, with emphasis on construction material in the Irish housing sector. It addresses some of the key issues concerning anthropogenic impact on the environment through spatial temporal visualisation of the flow of materials, wastes and emissions at different spatial levels. This is presented in the form of a spatial model, Spatial Allocation of Material Flow Analysis (SAMFA), which enables the simulation of construction material flows and associated energy use. SAMFA parallels the Island Limits project (EPA funded under 2004-SD-MS-22-M2), which aimed to create a material flow analysis of the Irish economy classified by industrial sector. SAMFA further develops this by attempting to establish the material flows at the subnational geographical scale that could be used in the development of local authority (LA) sustainability strategies and spatial planning frameworks by highlighting the cumulative environmental impacts of the development of the built environment. By drawing on the idea of planning support systems, SAMFA also aims to provide a cross-disciplinary, integrative medium for involving stakeholders in strategies for a sustainable built environment and, as such, would help illustrate the sustainability consequences of alternative The pilot run of the model in Kildare has shown that the model can be successfully calibrated and applied to develop alternative material flows and energy-use scenarios at the ED level. This has been demonstrated through the development of an integrated and a business-as-usual scenario, with the former integrating a range of potential material efficiency and energysaving policy options and the latter replicating conditions that best describe the current trend. Their comparison shows that the former is better than the latter in terms of both material and energy use. This report also identifies a number of potential areas of future research and areas of broader application. This includes improving the accuracy of the SAMFA model (e.g. by establishing actual life expectancy of buildings in the Irish context through field surveys) and the extension of the model to other Irish counties. This would establish SAMFA as a valuable predicting and monitoring tool that is capable of integrating national and local spatial planning objectives with actual environmental impacts. Furthermore, should the model prove successful at this level, it then has the potential to transfer the modelling approach to other areas of the built environment, such as commercial development and other key contributors of greenhouse emissions. The ultimate aim is to develop a meta-model for predicting the consequences of consumption patterns at the local scale. This therefore offers the possibility of creating critical links between socio technical systems with the most important challenge of all the limitations of the biophysical environment.

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This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.

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To assess the efficiency of different agro-environmental strategies used to reduce groundwater pollution by nitrates, transport modelling in soils and groundwater has been carried out on two withdrawal areas in an alluvial plain. In a first time, the agro-environmental model AgriFlux allowed the simulation of water and nitrates fluxes flowing to groundwater. This model was calibrated for each agro-pedological unit of the studied territory. In a second time, the application of the hydrogeological model MODFLOW-MT3D allowed the simulation of nitrate transport in groundwater for the 1980-2004 period. This soil-groundwater coupled modelling has shown that soil nature is the first factor that conditions the vulnerability to nitrates. Thus, nitrate leaching occurs preferentially under sandy soils. Efficiency of different agro-environmental operations for groundwater quality recovery was quantified. The best results are obtained by combination of (1) grassland re-installation on sandy agricultural lots located in near well protection perimeter and (2) fertilization reduction on sandy agricultural lots located in the well alimentation area upstream the near protection perimeter. On other soils, the effect of grassland on groundwater quality improvement is more limited. Nevertheless, the control of nitrate fertilisation remains essential and is justified in both near and far well protection perimeters. Modelling thus allows optimising and priorizing agro-environmental actions in alluvial agricultural zones. [Comte J.-C., Banton O., Kockmann F., Villard A., Creuzot G. (2006), Assessment of groundwater quality recovery strategies using nitrate transport modelling. Application to the Saône alluvial formations (Tournus, Saône-et-Loire), Ingénieries Eau-Agriculture-Territoires, 45, 15-28]

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Embedded processors are used in numerous devices executing dedicated applications. This setting makes it worthwhile to optimize the processor to the application it executes, in order to increase its power-efficiency. This paper proposes to enhance direct mapped data caches with automatically tuned randomized set index functions to achieve that goal. We show how randomization functions can be automatically generated and compare them to traditional set-associative caches in terms of performance and energy consumption. A 16 kB randomized direct mapped cache consumes 22% less energy than a 2-way set-associative cache, while it is less than 3% slower. When the randomization function is made configurable (i.e., it can be adapted to the program), the additional reduction of conflicts outweighs the added complexity of the hardware, provided there is a sufficient amount of conflict misses.

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Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.

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This paper aims to contribute to the ongoing debate on the use of resource accounting tools in regional policy making. The Northern Limits project applied Material Flow Analysis and Ecological Footprinting to regional policy making in Northern Ireland over a number of years. The early phase of the research informed the regions first sustainable development strategy which was published in 2006 with key targets relating to the Ecological Footprint and improving the resource efficiency of the economy. Phase II identified the next steps required to address data availability and quality and the use of MFA and EF in providing a measurement and monitoring framework for the strategy and in the development of the strategy implementation plan. The use of MFA and Ecological Footprinting in sustainable regional policy making and the monitoring of its implementation is an ongoing process which has raised a number of research issues which can inform the ongoing application and development of these and other resource accounting tools to within Northern Ireland, provide insights for their use in other regions and help set out the priorities for research to support this important policy area.

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Key stakeholders in the UK charity sector have, in recent years, advocated greater accountability for charity performance. Part of that debate has focussed on the use of conversion ratios as indicators of efficiency, with importance to stakeholders being contrasted with charities’ apparent reluctance to report such measures. Whilst, before 2005, conversion ratios could have been computed from financial statements, changes in the UK charity SORP have radically altered the ability of users to do this. This article explores the impact on the visibility of such information through an analysis of the financial statements of large UK charities before and after the 2005 changes. Overall, the findings suggest that, despite the stated intention of increasing transparency in respect of charity costs, the application of the changes has resulted in charities ‘managing’ the numbers and limiting their disclosures, possibly to the detriment of external stakeholders.