975 resultados para Quality assessment


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In the age of climate change and rapid urbanisation, stormwater management and water sensitive urban design have become important issues for urban policy makers. This paper reports the initial findings of a research study that develops an indexing model for assessing stormwater quality in the Gold Coast.

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Scalable video coding of H.264/AVC standard enables adaptive and flexible delivery for multiple devices and various network conditions. Only a few works have addressed the influence of different scalability parameters (frame rate, spatial resolution, and SNR) on the user perceived quality within a limited scope. In this paper, we have conducted an experiment of subjective quality assessment for video sequences encoded with H.264/SVC to gain a better understanding of the correlation between video content and UPQ at all scalable layers and the impact of rate-distortion method and different scalabilities on bitrate and UPQ. Findings from this experiment will contribute to a user-centered design of adaptive delivery of scalable video stream.

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Welcome to the Quality assessment matrix. This matrix is designed for highly qualified discipline experts to evaluate their course, major or unit in a systematic manner. The primary purpose of the Quality assessment matrix is to provide a tool that a group of academic staff at universities can collaboratively review the assessment within a course, major or unit annually. The annual review will result in you being read for an external curricula review at any point in time. This tool is designed for use in a workshop format with one, two or more academic staff, and will lead to an action plan for implementation.

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Service bundles, in the context of e-government, are used to group services together that relate to a certain citizen need. These bundles can then be presented on a governmental one-stop portal to structure the available service offerings according to citizen expectations. In order to ensure that citizens utilise the one-stop portal and comprised service bundles for future transactions, the quality of these service bundles needs to be managed and maximised accordingly. Consequently, models and tools that focus on assessing service bundle quality play an important role, when it comes to increasing or retaining usage behaviour of citizens. This study focuses on providing a rigorous and structured literature review of e-government outlets with regards to their coverage of service bundle quality and e-service quality themes. The study contributes to academia and practice by providing a framework that allows structuring and classifying existing studies relevant for the assessment of quality for government portals. Furthermore, this study provides insights into the status quo of quality models that can be used by governments to assess the quality of their service bundles. Directions for future research and limitations of the present study are provided as well.

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In this paper, we present a machine learning approach to measure the visual quality of JPEG-coded images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity (HVS) factors such as edge amplitude, edge length, background activity and background luminance. Image quality assessment involves estimating the functional relationship between HVS features and subjective test scores. The quality of the compressed images are obtained without referring to their original images ('No Reference' metric). Here, the problem of quality estimation is transformed to a classification problem and solved using extreme learning machine (ELM) algorithm. In ELM, the input weights and the bias values are randomly chosen and the output weights are analytically calculated. The generalization performance of the ELM algorithm for classification problems with imbalance in the number of samples per quality class depends critically on the input weights and the bias values. Hence, we propose two schemes, namely the k-fold selection scheme (KS-ELM) and the real-coded genetic algorithm (RCGA-ELM) to select the input weights and the bias values such that the generalization performance of the classifier is a maximum. Results indicate that the proposed schemes significantly improve the performance of ELM classifier under imbalance condition for image quality assessment. The experimental results prove that the estimated visual quality of the proposed RCGA-ELM emulates the mean opinion score very well. The experimental results are compared with the existing JPEG no-reference image quality metric and full-reference structural similarity image quality metric.

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In this study, a quality assessment method based on sampling of primary laser inventory units (microsegments) was analysed. The accuracy of a laser inventory carried out in Kuhmo was analysed as a case study. Field sample plots were measured on the sampled microsegments in the Kuhmo inventory area. Two main questions were considered. Did the ALS based inventory meet the accuracy requirements set for the provider and how should a reliable, cost-efficient and independent quality assessment be undertaken. The agreement between control measurement and ALS based inventory was analysed in four ways: 1) The root mean squared errors (RMSEs) and bias were calculated. 2) Scatter plots with 95% confidence intervals were plotted and the placing of identity lines was checked. 3) Bland-Altman plots were drawn so that the mean difference of attributes between the control method and ALS-method was calculated and plotted against average value of attributes. 4) The tolerance limits were defined and combined with Bland-Altman plots. The RMSE values were compared to a reference study from which the accuracy requirements had been set to the service provider. The accuracy requirements in Kuhmo were achieved, however comparison of RMSE values proved to be difficult. Field control measurements are costly and time-consuming, but they are considered to be robust. However, control measurements might include errors, which are difficult to take into account. Using the Bland-Altman plots none of the compared methods are considered to be completely exact, so this offers a fair way to interpret results of assessment. The tolerance limits to be set on order combined with Bland-Altman plots were suggested to be taken in practise. In addition, bias should be calculated for total area. Some other approaches for quality control were briefly examined. No method was found to fulfil all the required demands of statistical reliability, cost-efficiency, time efficiency, simplicity and speed of implementation. Some benefits and shortcomings of the studied methods were discussed.

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We have studied the as grown and annealed CdZnTe (Zn similar to 4 %) crystals for the assessment of their crystalline quality. As grown crystals suffer from tellurium precipitates and cadmium vacancies, which are inherent, due to retrograde solid solubility curve in the phase diagram. This is reflected in the Fourier transform infrared (FTIR) spectra over the 400 - 4500 cm(-1) range by a strong absorption around 2661 cm(-1) which corresponds to the band gap of tellurium confirming their presence, where-as a monotonic decrease in the transmission with the decrease in wave number indicates the presence of cadmium vacancies. Obviously the presence of Cd vacancies lead to the formation of tellurium precipitates confirming their presence. Annealed samples under cadmium + zinc ambient at 650 degrees C for 6 hours show an improvement in the transmission over the same range. This can be attributed to thermo-migration of tellurium precipitates and hence bonding with Cd or Zn to form CdZnTe. This is further supported by the reduced full width at half maximum in the X-ray diffraction rocking curve of these CdZnTe crystals. Cadmium annealing although can passivate Cd vacancy related defects and reduce the Te precipitates, as is observed in our low temperature Photoluminescence (PL) spectra, alone may not be sufficient possibly due to the loss of Zn. Vacuum annealing at 650 degrees C for 6 hours further deteriorated the material quality as is reflected in the low temperature PL spectra by the introduction of a new defect band around 0.85 eV and reduced IR transmission.

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Yhteenveto: Veden laadun arviointi vesiensuojelun suunnittelussa

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We propose a set of metrics that evaluate the uniformity, sharpness, continuity, noise, stroke width variance,pulse width ratio, transient pixels density, entropy and variance of components to quantify the quality of a document image. The measures are intended to be used in any optical character recognition (OCR) engine to a priori estimate the expected performance of the OCR. The suggested measures have been evaluated on many document images, which have different scripts. The quality of a document image is manually annotated by users to create a ground truth. The idea is to correlate the values of the measures with the user annotated data. If the measure calculated matches the annotated description,then the metric is accepted; else it is rejected. In the set of metrics proposed, some of them are accepted and the rest are rejected. We have defined metrics that are easily estimatable. The metrics proposed in this paper are based on the feedback of homely grown OCR engines for Indic (Tamil and Kannada) languages. The metrics are independent of the scripts, and depend only on the quality and age of the paper and the printing. Experiments and results for each proposed metric are discussed. Actual recognition of the printed text is not performed to evaluate the proposed metrics. Sometimes, a document image containing broken characters results in good document image as per the evaluated metrics, which is part of the unsolved challenges. The proposed measures work on gray scale document images and fail to provide reliable information on binarized document image.