967 resultados para Performance Capture
Resumo:
The annual income return for rural property is based on two major factors being commodity prices and production yields. Commodity prices paid to rural producers can vary depending on the agricultural policies of their respective countries. Free trade countries, such as Australia and New Zealand are subject to the volatility of the world commodity markets to a greater extent than those farmers in protected or subsidised markets. In countries where rural production is protected or subsidised the annual income received by rural producers has been relatively stable. However, the high cost of agricultural protection is now being questioned, particularly in relation to the increasing economic costs of government services such as health, education and housing. When combined with the agricultural production limitations of climate, topography, chemical residues and disease issues, the impact of commodity prices on rural property income is crucial in the ability of rural producers to enter into or expand their holdings in agricultural land. These problems are then reflected in the volatility of the rural land capital returns and the investment performance of this property class. This paper will address the total and capital return performance of a major agricultural area and compare these returns on the basis of both location of land and land use. The comparison will be used to determine if location or actual land use has a greater influence on rural property capital returns. This performance analysis is based on over 35,000 rural sales transactions. These transactions cover all market based rural property transactions in New South Wales, Australia for the period January 1990 to December 2008. Correlation analysis and investment performance analysis has also been carried out to determine the possible relationships between location and land use and subsequent changes in rural land capital values.
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Unified Enterprise application security is a new emerging approach for providing protection against application level attacks. Conventional application security approach that consists of embedding security into each critical application leads towards scattered security mechanism that is not only difficult to manage but also creates security loopholes. According to the CSIIFBI computer crime survey report, almost 80% of the security breaches come from authorized users. In this paper, we have worked on the concept of unified security model, which manages all security aspect from a single security window. The basic idea is to keep business functionality separate from security components of the application. Our main focus was on the designing of frame work for unified layer which supports single point of policy control, centralize logging mechanism, granular, context aware access control, and independent from any underlying authentication technology and authorization policy.
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While IS function has gained widespread attention for over two decades, there is little consensus among information systems (IS) researchers and practitioners on how best to evaluate IS function's support performance. This paper reports on preliminary findings of a larger research effort proceeds from a central interest in the importance of evaluating IS function's support in organisations. This study is the first that attempts to re-conceptualise and conceive evaluate IS function's support as a multi- dimensional formative construct. We argue that a holistic measure for evaluating evaluate IS function's support should consist of dimensions that together assess the variety of the support functions and the quality of the support services provided to end-users. Thus, the proposed model consists of two halves, "Variety" and "Quality" within which resides seven dimensions. The Variety half includes five dimensions: Training; Documentation; Data- related Support, Software-related Support; and Hardware-related Support. The Quality half includes two dimensions: IS Support Staff and Support Services Performance. The proposed model is derived using a directed content analysis of 83 studies; from top IS outlets, employing the characteristics of the analytic theory and consistent with formative construct development procedures.
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Visual servoing has been a viable method of robot manipulator control for more than a decade. Initial developments involved positionbased visual servoing (PBVS), in which the control signal exists in Cartesian space. The younger method, image-based visual servoing (IBVS), has seen considerable development in recent years. PBVS and IBVS offer tradeoffs in performance, and neither can solve all tasks that may confront a robot. In response to these issues, several methods have been devised that partition the control scheme, allowing some motions to be performed in the manner of a PBVS system, while the remaining motions are performed using an IBVS approach. To date, there has been little research that explores the relative strengths and weaknesses of these methods. In this paper we present such an evaluation. We have chosen three recent visual servo approaches for evaluation in addition to the traditional PBVS and IBVS approaches. We posit a set of performance metrics that measure quantitatively the performance of a visual servo controller for a specific task. We then evaluate each of the candidate visual servo methods for four canonical tasks with simulations and with experiments in a robotic work cell.
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Creating sustainable urban environments is one of the challenging issues that need a clear vision and implementation strategies involving changes in governmental values and decision making process for local governments. Particularly, internalisation of environmental externalities of daily urban activities (e.g. manufacturing, transportation and so on) has immense importance for which local policies are formulated to provide better living conditions for the people inhabiting urban areas. Even if environmental problems are defined succinctly by various stakeholders, complicated nature of sustainability issues demand a structured evaluation strategy and well-defined sustainability parameters for efficient and effective policy making. Following this reasoning, this study involves assessment of sustainability performance of urban settings mainly focusing on environmental problems caused by rapid urban expansion and transformation. By taking into account land-use and transportation interaction, it tries to reveal how future urban developments would alter daily urban travel behaviour of people and affect the urban and natural environments. The paper introduces a grid-based indexing method developed for this research and trailed as a GIS-based decision support tool to analyse and model selected spatial and aspatial indicators of sustainability in the Gold Coast. This process reveals parameters of site specific relationship among selected indicators that are used to evaluate index-based performance characteristics of the area. The evaluation is made through an embedded decision support module by assigning relative weights to indicators. Resolution of selected grid-based unit of analysis provides insights about service level of projected urban development proposals at a disaggregate level, such as accessibility to transportation and urban services, and pollution. The paper concludes by discussing the findings including the capacity of the decision support system to assist decision-makers in determining problematic areas and developing intervention policies for sustainable outcomes of future developments.
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A series of short performance experiments demonstrating the creative potential of motion capture technology as a tool within performance for exploring audience behaviour and interaction. Examples highlight the possibilities for future work and give basic demonstrations of what is technically possible for the stage. Please note that people attending this performance may be videoed and motion captured for research and/or publication purposes. This work has been funded by the EPSRC c4dm platform grant.
Resumo:
Differential distortion comprising axial shortening and consequent rotation in concrete buildings is caused by the time dependent effects of “shrinkage”, “creep” and “elastic” deformation. Reinforcement content, variable concrete modulus, volume to surface area ratio of elements and environmental conditions influence these distortions and their detrimental effects escalate with increasing height and geometric complexity of structure and non vertical load paths. Differential distortion has a significant impact on building envelopes, building services, secondary systems and the life time serviceability and performance of a building. Existing methods for quantifying these effects are unable to capture the complexity of such time dependent effects. This paper develops a numerical procedure that can accurately quantify the differential axial shortening that contributes significantly to total distortion in concrete buildings by taking into consideration (i) construction sequence and (ii) time varying values of Young’s Modulus of reinforced concrete and creep and shrinkage. Finite element techniques are used with time history analysis to simulate the response to staged construction. This procedure is discussed herein and illustrated through an example.
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Microphone arrays have been used in various applications to capture conversations, such as in meetings and teleconferences. In many cases, the microphone and likely source locations are known \emph{a priori}, and calculating beamforming filters is therefore straightforward. In ad-hoc situations, however, when the microphones have not been systematically positioned, this information is not available and beamforming must be achieved blindly. In achieving this, a commonly neglected issue is whether it is optimal to use all of the available microphones, or only an advantageous subset of these. This paper commences by reviewing different approaches to blind beamforming, characterising them by the way they estimate the signal propagation vector and the spatial coherence of noise in the absence of prior knowledge of microphone and speaker locations. Following this, a novel clustered approach to blind beamforming is motivated and developed. Without using any prior geometrical information, microphones are first grouped into localised clusters, which are then ranked according to their relative distance from a speaker. Beamforming is then performed using either the closest microphone cluster, or a weighted combination of clusters. The clustered algorithms are compared to the full set of microphones in experiments on a database recorded on different ad-hoc array geometries. These experiments evaluate the methods in terms of signal enhancement as well as performance on a large vocabulary speech recognition task.
Resumo:
Intelligent surveillance systems typically use a single visual spectrum modality for their input. These systems work well in controlled conditions, but often fail when lighting is poor, or environmental effects such as shadows, dust or smoke are present. Thermal spectrum imagery is not as susceptible to environmental effects, however thermal imaging sensors are more sensitive to noise and they are only gray scale, making distinguishing between objects difficult. Several approaches to combining the visual and thermal modalities have been proposed, however they are limited by assuming that both modalities are perfuming equally well. When one modality fails, existing approaches are unable to detect the drop in performance and disregard the under performing modality. In this paper, a novel middle fusion approach for combining visual and thermal spectrum images for object tracking is proposed. Motion and object detection is performed on each modality and the object detection results for each modality are fused base on the current performance of each modality. Modality performance is determined by comparing the number of objects tracked by the system with the number detected by each mode, with a small allowance made for objects entering and exiting the scene. The tracking performance of the proposed fusion scheme is compared with performance of the visual and thermal modes individually, and a baseline middle fusion scheme. Improvement in tracking performance using the proposed fusion approach is demonstrated. The proposed approach is also shown to be able to detect the failure of an individual modality and disregard its results, ensuring performance is not degraded in such situations.
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The application of high-speed machine vision for close-loop position control, or visual servoing, of a robot manipulator. It provides a comprehensive coverage of all aspects of the visual servoing problem: robotics, vision, control, technology and implementation issues. While much of the discussion is quite general the experimental work described is based on the use of a high-speed binary vision system with a monocular "eye-in-hand" camera.
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Spectrum sensing is considered to be one of the most important tasks in cognitive radio. Many sensing detectors have been proposed in the literature, with the common assumption that the primary user is either fully present or completely absent within the window of observation. In reality, there are scenarios where the primary user signal only occupies a fraction of the observed window. This paper aims to analyse the effect of the primary user duty cycle on spectrum sensing performance through the analysis of a few common detectors. Simulations show that the probability of detection degrades severely with reduced duty cycle regardless of the detection method. Furthermore we show that reducing the duty cycle has a greater degradation on performance than lowering the signal strength.
Resumo:
Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.
Resumo:
The focus of this paper questions how the performance place was transformed to a performance space. This major change in distinction holds an ongoing significance to the development of the actors, scenographers, animators, writers and film directors craft within current digitally mediated and interactive performance environments. As part of this discussion this paper traces the crucial seed of the revolution that transformed modern scenographic practice from the droll of the romantic realism of the Victorian stage to the open potential of the performance environment of today. This is achieved through close readings on the practical work of Edward Gordon Craig and Adolphe Appia as well as the scenographic discussions of Chris Baugh.
Resumo:
BACKGROUND: Support and education for parents faced with managing a child with atopic dermatitis is crucial to the success of current treatments. Interventions aiming to improve parent management of this condition are promising. Unfortunately, evaluation is hampered by lack of precise research tools to measure change. OBJECTIVES: To develop a suite of valid and reliable research instruments to appraise parents' self-efficacy for performing atopic dermatitis management tasks; outcome expectations of performing management tasks; and self-reported task performance in a community sample of parents of children with atopic dermatitis. METHODS: The Parents' Eczema Management Scale (PEMS) and the Parents' Outcome Expectations of Eczema Management Scale (POEEMS) were developed from an existing self-efficacy scale, the Parental Self-Efficacy with Eczema Care Index (PASECI). Each scale was presented in a single self-administered questionnaire, to measure self-efficacy, outcome expectations, and self-reported task performance related to managing child atopic dermatitis. Each was tested with a community sample of parents of children with atopic dermatitis, and psychometric evaluation of the scales' reliability and validity was conducted. SETTING AND PARTICIPANTS: A community-based convenience sample of 120 parents of children with atopic dermatitis completed the self-administered questionnaire. Participants were recruited through schools across Australia. RESULTS: Satisfactory internal consistency and test-retest reliability was demonstrated for all three scales. Construct validity was satisfactory, with positive relationships between self-efficacy for managing atopic dermatitis and general perceived self-efficacy; self-efficacy for managing atopic dermatitis and self-reported task performance; and self-efficacy for managing atopic dermatitis and outcome expectations. Factor analyses revealed two-factor structures for PEMS and PASECI alike, with both scales containing factors related to performing routine management tasks, and managing the child's symptoms and behaviour. Factor analysis was also applied to POEEMS resulting in a three-factor structure. Factors relating to independent management of atopic dermatitis by the parent, involving healthcare professionals in management, and involving the child in the management of atopic dermatitis were found. Parents' self-efficacy and outcome expectations had a significant influence on self-reported task performance. CONCLUSIONS: Findings suggest that PEMS and POEEMS are valid and reliable instruments worthy of further psychometric evaluation. Likewise, validity and reliability of PASECI was confirmed.