893 resultados para performance evaluation tool
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Retinal blurring resulting from the human eye's depth of focus has been shown to assist visual perception. Infinite focal depth within stereoscopically displayed virtual environments may cause undesirable effects, for instance, objects positioned at a distance in front of or behind the observer's fixation point will be perceived in sharp focus with large disparities thereby causing diplopia. Although published research on incorporation of synthetically generated Depth of Field (DoF) suggests that this might act as an enhancement to perceived image quality, no quantitative testimonies of perceptional performance gains exist. This may be due to the difficulty of dynamic generation of synthetic DoF where focal distance is actively linked to fixation distance. In this paper, such a system is described. A desktop stereographic display is used to project a virtual scene in which synthetically generated DoF is actively controlled from vergence-derived distance. A performance evaluation experiment on this system which involved subjects carrying out observations in a spatially complex virtual environment was undertaken. The virtual environment consisted of components interconnected by pipes on a distractive background. The subject was tasked with making an observation based on the connectivity of the components. The effects of focal depth variation in static and actively controlled focal distance conditions were investigated. The results and analysis are presented which show that performance gains may be achieved by addition of synthetic DoF. The merits of the application of synthetic DoF are discussed.
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This paper presents the PETS2009 outdoor crowd image analysis surveillance dataset and the performance evaluation of people counting, detection and tracking results using the dataset submitted to five IEEE Performance Evaluation of Tracking and Surveillance (PETS) workshops. The evaluation was carried out using well established metrics developed in the Video Analysis and Content Extraction (VACE) programme and the CLassification of Events, Activities, and Relationships (CLEAR) consortium. The comparative evaluation highlights the detection and tracking performance of the authors’ systems in areas such as precision, accuracy and robustness and provides a brief analysis of the metrics themselves to provide further insights into the performance of the authors’ systems.
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This paper presents a quantitative evaluation of a tracking system on PETS 2015 Challenge datasets using well-established performance measures. Using the existing tools, the tracking system implements an end-to-end pipeline that include object detection, tracking and post- processing stages. The evaluation results are presented on the provided sequences of both ARENA and P5 datasets of PETS 2015 Challenge. The results show an encouraging performance of the tracker in terms of accuracy but a greater tendency of being prone to cardinality error and ID changes on both datasets. Moreover, the analysis show a better performance of the tracker on visible imagery than on thermal imagery.
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Predictive performance evaluation is a fundamental issue in design, development, and deployment of classification systems. As predictive performance evaluation is a multidimensional problem, single scalar summaries such as error rate, although quite convenient due to its simplicity, can seldom evaluate all the aspects that a complete and reliable evaluation must consider. Due to this, various graphical performance evaluation methods are increasingly drawing the attention of machine learning, data mining, and pattern recognition communities. The main advantage of these types of methods resides in their ability to depict the trade-offs between evaluation aspects in a multidimensional space rather than reducing these aspects to an arbitrarily chosen (and often biased) single scalar measure. Furthermore, to appropriately select a suitable graphical method for a given task, it is crucial to identify its strengths and weaknesses. This paper surveys various graphical methods often used for predictive performance evaluation. By presenting these methods in the same framework, we hope this paper may shed some light on deciding which methods are more suitable to use in different situations.
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The paper analyses empirical performance data of five commercial PV-plants in Germany. The purpose was on one side to investigate the weak light performance of the different PV-modules used. On the other hand it was to quantify and compare the shading losses of different PV-array configurations. The importance of this study relies on the fact that even if the behavior under weak light conditions or the shading losses might seem to be a relatively small percentage of the total yearly output; in projects where a performance guarantee is given, these variation can make the difference between meeting or not the conditions.When analyzing the data, a high dispersion was found. To reduce the optical losses and spectral effects, a series of data filters were applied based on the angle of incidence and absolute Air Mass. To compensate for the temperature effects and translate the values to STC (25°C), five different methods were assessed. At the end, the Procedure 2 of IEC 60891 was selected due to its relative simplicity, usage of mostly standard parameters found in datasheets, good accuracy even with missing values, and its potential to improve the results when the complete set of inputs is available.After analyzing the data, the weak light performance of the modules did not show a clear superiority of a certain technology or technology group over the others. Moreover, the uncertainties in the measurements restrictive the conclusiveness of the results.In the partial shading analysis, the landscape mounting of mc-Si PV-modules in free-field showed a significantly better performance than the portrait one. The cross-table string using CIGS modules did not proved the benefits expected and performed actually poorer than a regular one-string-per-table layout. Parallel substrings with CdTe showed a proper functioning and relatively low losses. Among the two product generations of CdTe analyzed, none showed a significantly better performance under partial shadings.
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A ventilation radiator is a combined ventilation and heat emission unit currently of interest due to its potential for increasing energy efficiency in exhaust ventilated buildings with warm water heating. This paper presents results of performance tests of several ventilation radiator models conducted under controlled laboratory conditions. The purpose of the study was to validate results achieved by Computational Fluid Dynamics (CFD) in an earlier study and indentify possible improvements in the performance of such systems. The main focus was on heat transfer from internal convection fins, but comfort and health aspects related to ventilation rates and air temperatures were also considered. The general results from the CFD simulations were confirmed; the heat output of ventilation radiators may be improved by at least 20 % without sacrificing ventilation efficiency or thermal comfort. Improved thermal efficiency of ventilation radiators allows a lower supply water temperature and energy savings both for heating up and distribution of warm water in heat pumps or district heating systems. A secondary benefit is that a high ventilation rate can be maintained all year around without risk for cold draught.
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Microwave remote sensing has high potential for soil moisture retrieval. However, the efficient retrieval of soil moisture depends on optimally choosing the soil moisture retrieval parameters. In this study first the initial evaluation of SMOS L2 product is performed and then four approaches regarding soil moisture retrieval from SMOS brightness temperature are reported. The radiative transfer equation based tau-omega rationale is used in this study for the soil moisture retrievals. The single channel algorithms (SCA) using H polarisation is implemented with modifications, which includes the effective temperatures simulated from ECMWF (downscaled using WRF-NOAH Land Surface Model (LSM)) and MODIS. The retrieved soil moisture is then utilized for soil moisture deficit (SMD) estimation using empirical relationships with Probability Distributed Model based SMD as a benchmark. The square of correlation during the calibration indicates a value of R2 =0.359 for approach 4 (WRF-NOAH LSM based LST with optimized roughness parameters) followed by the approach 2 (optimized roughness parameters and MODIS based LST) (R2 =0.293), approach 3 (WRF-NOAH LSM based LST with no optimization) (R2 =0.267) and approach 1(MODIS based LST with no optimization) (R2 =0.163). Similarly, during the validation a highest performance is reported by approach 4. The other approaches are also following a similar trend as calibration. All the performances are depicted through Taylor diagram which indicates that the H polarisation using ECMWF based LST is giving a better performance for SMD estimation than the original SMOS L2 products at a catchment scale.
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If conducted poorly and without support from all employee levels, performance management programs at institutions may devolve into annual evaluations that represent a staff burden rather than an ongoing career development opportunity. This brief analyzes the key components of successful performance evaluation systems for non-academic staff, incorporating insights from employers outside of the higher education sector as well. It examines the importance of midyear check-in meetings; employee goal-setting; simplified rating scales on evaluation forms; and core staff competencies that reflect institutional priorities. It also describes how institutions communicate modifications to the evaluation system and offers recommendations for the implementation of process change.
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Orientador: Paulo Nazareno Maia Sampaio