979 resultados para extraction efficiency


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This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS1 database, show encouraging results

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In recent years, development of Unmanned Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This thesis presents an investigation of methods for increasing the energy efficiency on UAVs. One method is via the development of a Mission Waypoint Optimisation (MWO) procedure for a small fixed-wing UAV, focusing on improving the onboard fuel economy. MWO deals with a pre-specified set of waypoints by modifying the given waypoints within certain limits to achieve its optimisation objectives of minimising/maximising specific parameters. A simulation model of a UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. This simulation model was separately integrated with a multi-objective Evolutionary Algorithm (MOEA) optimiser and a Sequential Quadratic Programming (SQP) solver to perform single-objective and multi-objective optimisation procedures of a set of real-world waypoints in order to minimise the onboard fuel consumption. The results of both procedures show potential in reducing fuel consumption on a UAV in a ight mission. Additionally, a parallel Hybrid-Electric Propulsion System (HEPS) on a small fixedwing UAV incorporating an Ideal Operating Line (IOL) control strategy was developed. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine was determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

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This chapter provides an analysis of feedback from key stakeholders, collected as part of a research project, on the problems and tensions evident in the collective work practices of learning advisers employed in learning assistance services at an Australian metropolitan university (Peach, 2003). The term 'learning assistance' is used in the Australian higher education sector generally to refer to student support services that include assistance with academic writing and other study skills. The aim of the study was to help learning advisers and other key stakeholders develop a better understanding of the work activity with a view to using this understanding to generate improvements in service provision. Over twenty problems and associated tensions were identified through stakeholder feedback however the focus of this chapter is the analysis of tensions related to a cluster of problems referred to as cost-efficiency versus quality service. Theoretical modelling derived from the tools made available through cultural historical activity theory and expansive visibilsation (Engestrom and Miettinen, 1999) and excerpts from data are used to illustrate how different understandings of the purpose of learning assistance services impacts on the work practices of learning advisers and creates problems and tensions in relation to the type of service available (including use of technology),level of service available, and learning adviser workload.

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An automatic approach to road lane marking extraction from high-resolution aerial images is proposed, which can automatically detect the road surfaces in rural areas based on hierarchical image analysis. The procedure is facilitated by the road centrelines obtained from low-resolution images. The lane markings are further extracted on the generated road surfaces with 2D Gabor filters. The proposed method is applied on the aerial images of the Bruce Highway around Gympie, Queensland. Evaluation of the generated road surfaces and lane markings using four representative test fields has validated the proposed method.

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The motivation of the study stems from the results reported in the Excellence in Research for Australia (ERA) 2010 report. The report showed that only 12 universities performed research at or above international standards, of which, the Group of Eight (G8) universities filled the top eight spots. While performance of universities was based on number of research outputs, total amount of research income and other quantitative indicators, the measure of efficiency or productivity was not considered. The objectives of this paper are twofold. First, to provide a review of the research performance of 37 Australian universities using the data envelopment analysis (DEA) bootstrap approach of Simar and Wilson (2007). Second, to determine sources of productivity drivers by regressing the efficiency scores against a set of environmental variables.

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The main aim of this thesis is to analyse and optimise a public hospital Emergency Department. The Emergency Department (ED) is a complex system with limited resources and a high demand for these resources. Adding to the complexity is the stochastic nature of almost every element and characteristic in the ED. The interaction with other functional areas also complicates the system as these areas have a huge impact on the ED and the ED is powerless to change them. Therefore it is imperative that OR be applied to the ED to improve the performance within the constraints of the system. The main characteristics of the system to optimise included tardiness, adherence to waiting time targets, access block and length of stay. A validated and verified simulation model was built to model the real life system. This enabled detailed analysis of resources and flow without disruption to the actual ED. A wide range of different policies for the ED and a variety of resources were able to be investigated. Of particular interest was the number and type of beds in the ED and also the shift times of physicians. One point worth noting was that neither of these resources work in isolation and for optimisation of the system both resources need to be investigated in tandem. The ED was likened to a flow shop scheduling problem with the patients and beds being synonymous with the jobs and machines typically found in manufacturing problems. This enabled an analytic scheduling approach. Constructive heuristics were developed to reactively schedule the system in real time and these were able to improve the performance of the system. Metaheuristics that optimised the system were also developed and analysed. An innovative hybrid Simulated Annealing and Tabu Search algorithm was developed that out-performed both simulated annealing and tabu search algorithms by combining some of their features. The new algorithm achieves a more optimal solution and does so in a shorter time.

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Rule extraction from neural network algorithms have been investigated for two decades and there have been significant applications. Despite this level of success, rule extraction from neural network methods are generally not part of data mining tools, and a significant commercial breakthrough may still be some time away. This paper briefly reviews the state-of-the-art and points to some of the obstacles, namely a lack of evaluation techniques in experiments and larger benchmark data sets. A significant new development is the view that rule extraction from neural networks is an interactive process which actively involves the user. This leads to the application of assessment and evaluation techniques from information retrieval which may lead to a range of new methods.

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The issue of a more sustainable environment has been the aim of many governments and institutions for decades. Current research and literature has shown the continuing impact of global development and population increases on the planet as a whole. Issues such as carbon emissions, global warming, resource sustainability, industrial pollution, waste management and the decline in scarce resources, including food, are now realities and are being addressed at various levels. All levels of government, business and the public now equally share responsibility for the continued sustainable environment in general. Although these issues of global warming, climate change and the overuse of scarce resources are well documented, and constantly covered in all media forms, public attitudes to these issues vary significantly. Despite being aware of these issues many individuals consider that the problem is one for governments to tackle and that their individual efforts are not important or necessary. In many cases individuals are concerned with sustainability, but are either not in the position to take action due to economic circumstances or are not prepared to offset sustainability gains with personal interests...

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Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

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Air conditioning systems have become an integral part of many modern buildings. Proper design and operation of air conditioning systems have significant impact not only on the energy use and greenhouse gas emissions from the buildings, but also on the thermal comfort and productivity of the occupants. In this paper, the purpose and need of installing air conditioning systems is first introduced. The methods used for the classification of air conditioning systems are then presented. This is followed by a discussion on the pros and cons of each type of the air conditioning systems, including both common and new air conditioning technologies. The procedures used to design air conditioning systems are also outlined, and the implications of air conditioning systems, including design, selection, operation and maintenance, on building energy efficiency is also discussed.

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Vernier acuity, a form of visual hyperacuity, is amongst the most precise forms of spatial vision. Under optimal conditions Vernier thresholds are much finer than the inter-photoreceptor distance. Achievement of such high precision is based substantially on cortical computations, most likely in the primary visual cortex. Using stimuli with added positional noise, we show that Vernier processing is reduced with advancing age across a wide range of noise levels. Using an ideal observer model, we are able to characterize the mechanisms underlying age-related loss, and show that the reduction in Vernier acuity can be mainly attributed to the reduction in efficiency of sampling, with no significant change in the level of internal position noise, or spatial distortion, in the visual system.

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The current study was motivated by statements made by the Economic Strategies Committee that Singapore’s recent productivity levels in services were well below countries such as the US, Japan and Hong Kong. Massive employment of foreign workers was cited as the reason for poor productivity levels. To shed more light on Singapore’s falling productivity, a nonparametric Malmquist productivity index was employed which provides measures of productivity change, technical change and efficiency change. The findings reveal that growth in Total Factor Productivity (TFP) was attributed to technical change with no improvement in efficiency change. Such results suggest that gains from TFP were input-driven rather than from a ‘best-practice’ approach such as improvements in operations or better resource allocation.

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Among the available alternative sources of energy in Bangladesh bio-oil is recognized to be a promising alternative energy source. Bio-oil can be extracted by pyrolysis as well as expelling or solvent extractionmethod. In these days bio-oil is merely used in vehicles and power plants after some up gradation .However, it is not used for domestic purposes like cooking and lighting due to its high density and viscosity. This paper outlines the design of a gravity stove to use high dense and viscous bio-oil for cooking purpose. For this, Pongamia pinnata (karanj) oil extracted by solvent extraction method is used as fuel fed under gravity force. Efficiency of gravity stove with high dense and viscous bio-oil (karanj) is 11.81% which of kerosene stove is 17.80% also the discharge of karanj oil through gravity stove is sufficient for continuous burning. Thus, bio-oil can be effective replacement of kerosene for domestic purposes.