961 resultados para Zero reference level


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The analysis of fluid behavior in multiphase flow is very relevant to guarantee system safety. The use of equipment to describe such behavior is subjected to factors such as the high level of investments and of specialized labor. The application of image processing techniques to flow analysis can be a good alternative, however, very little research has been developed. In this subject, this study aims at developing a new approach to image segmentation based on Level Set method that connects the active contours and prior knowledge. In order to do that, a model shape of the targeted object is trained and defined through a model of point distribution and later this model is inserted as one of the extension velocity functions for the curve evolution at zero level of level set method. The proposed approach creates a framework that consists in three terms of energy and an extension velocity function λLg(θ)+vAg(θ)+muP(0)+θf. The first three terms of the equation are the same ones introduced in (LI CHENYANG XU; FOX, 2005) and the last part of the equation θf is based on the representation of object shape proposed in this work. Two method variations are used: one restricted (Restrict Level Set - RLS) and the other with no restriction (Free Level Set - FLS). The first one is used in image segmentation that contains targets with little variation in shape and pose. The second will be used to correctly identify the shape of the bubbles in the liquid gas two phase flows. The efficiency and robustness of the approach RLS and FLS are presented in the images of the liquid gas two phase flows and in the image dataset HTZ (FERRARI et al., 2009). The results confirm the good performance of the proposed algorithm (RLS and FLS) and indicate that the approach may be used as an efficient method to validate and/or calibrate the various existing equipment used as meters for two phase flow properties, as well as in other image segmentation problems.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2015.

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Call Level Interfaces (CLI) play a key role in business tiers of relational and on some NoSQL database applications whenever a fine tune control between application tiers and the host databases is a key requirement. Unfortunately, in spite of this significant advantage, CLI are low level API, this way not addressing high level architectural requirements. Among the examples we emphasize two situations: a) the need to decouple or not to decouple the development process of business tiers from the development process of application tiers and b) the need to automatically adapt business tiers to new business and/or security needs at runtime. To tackle these CLI drawbacks, and simultaneously keep their advantages, this paper proposes an architecture relying on CLI from which multi-purpose business tiers components are built, herein referred to as Adaptable Business Tier Components (ABTC). Beyond the reference architecture, this paper presents a proof of concept based on Java and Java Database Connectivity (an example of CLI).

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Call Level Interfaces (CLI) are low level API that play a key role in database applications whenever a fine tune control between application tiers and the host databases is a key requirement. Unfortunately, in spite of this significant advantage, CLI were not designed to address organizational requirements and contextual runtime requirements. Among the examples we emphasize the need to decouple or not to decouple the development process of business tiers from the development process of application tiers and also the need to automatically adapt to new business and/or security needs at runtime. To tackle these CLI drawbacks, and simultaneously keep their advantages, this paper proposes an architecture relying on CLI from which multi-purpose business tiers components are built, herein referred to as Adaptable Business Tier Components (ABTC). This paper presents the reference architecture for those components and a proof of concept based on Java and Java Database Connectivity (an example of CLI).

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El propósito de este proyecto de graduación es dar a conocer cómo la influencia de la tecnología hoy en día puede llegar a ser una herramienta útil a la hora de aprender una lengua extranjera, como lo es en éste caso el Inglés. Mediante la herramienta llamada Storybird los estudiantes tienen la capacidad de crear, imaginar y escribir historias que les ayuda a mejorar su destreza enfocado a la escritura. Para esto se analiza tres estudios de caso, los mismos que utilizan como herramienta principal Storybird. Dichos estudios son realizados en diferentes lugares del mundo, y a la vez dirigidos a estudiantes con diferente tipo de destrezas. El propósito de estos estudios es mejorar su escritura por medio de narraciones digitales, conocidos en el ámbito extranjero como Digital Storytelling, dando asíuna alternativa diferente de enseñanza para los estudiantes. Por último, se desarrolla una Guía de Aprendizaje dirigido a docentes, con el propósito de facilitar y brindar nuevos instrumentos de aprendizaje, con el uso de Storybird, para estudiantes que desempeñan un nivel A2 dentro del Marco de Referencia Europeo para las Lenguas.

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The accuracy of a map is dependent on the reference dataset used in its construction. Classification analyses used in thematic mapping can, for example, be sensitive to a range of sampling and data quality concerns. With particular focus on the latter, the effects of reference data quality on land cover classifications from airborne thematic mapper data are explored. Variations in sampling intensity and effort are highlighted in a dataset that is widely used in mapping and modelling studies; these may need accounting for in analyses. The quality of the labelling in the reference dataset was also a key variable influencing mapping accuracy. Accuracy varied with the amount and nature of mislabelled training cases with the nature of the effects varying between classifiers. The largest impacts on accuracy occurred when mislabelling involved confusion between similar classes. Accuracy was also typically negatively related to the magnitude of mislabelled cases and the support vector machine (SVM), which has been claimed to be relatively insensitive to training data error, was the most sensitive of the set of classifiers investigated, with overall classification accuracy declining by 8% (significant at 95% level of confidence) with the use of a training set containing 20% mislabelled cases.

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The preparation of a certified reference material of polar pesticides in freeze-dried water is described. The pesticides selected were atrazine, simazine, carbaryl, propanil, linuron, fenamiphos and permethrin which were added to 6000 litres of tap water at 50–80 μg · L–1 (200–320 μg · L–1 for permethrin) level in presence of NaCl (2.5 g · L–1) prior lyophilization. After the freeze-drying process the residue was rehomogenized, filled into amber glass bottles and stored at –20 °C, +4 °C and +20 °C. All pesticides were determined by HPLC/diode array detector, except permethrin which was determined by GC/ECD. The results obtained for atrazine, simazine, carbaryl, propanil, linuron and fenamiphos showed no within- or between-bottle inhomogeneity, however the material was non-homogeneous for permethrin and therefore this was withdrawn from further studies. With respect to the stability for over one year, all pesticides were stable at –20 °C. At +4 °C all pesticides were stable for at least 9 months and at +20 °C the stability was demonstrated only during the first month of storage. The content (mass fractions) of atrazine, simazine, carbaryl, propanil and linuron in freeze-dried water (CRM 606) was certified by an interlaboratory testing and a certification campaign.

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OBJECTIVE: To determine and compare the level of implementation of policies for healthy food environments in Thailand with reference to international best practice by state and non-state actors.
DESIGN: Data on the current level of implementation of food environment policies were assessed independently using the adapted Healthy Food Environment Policy Index (Food-EPI) by two groups of actors. Concrete actions were proposed for Thai Government. A joint meeting between both groups was subsequently held to reach consensus on priority actions.
SETTING: Thailand.
SUBJECTS: Thirty state actors and twenty-seven non-state actors.
RESULTS: Level of policy implementation varied across different domains and actor groups. State actors rated implementation levels higher than non-state actors. Both state and non-state actors rated level of implementation of monitoring of BMI highest. Level of implementation of policies promoting in-store availability of healthy foods and policies increasing tax on unhealthy foods were rated lowest by state and non-state actors, respectively. Both groups reached consensus on eleven priority actions for implementation, focusing on food provision in public-sector settings, food composition, food promotion, leadership, monitoring and intelligence, and food trade.
CONCLUSIONS: Although the implementation gaps identified and priority actions proposed varied between state and non-state actors, both groups achieved consensus on a comprehensive food policy package to be implemented by the Thai Government to improve the healthiness of food environments. This consensus is a platform for continued policy dialogue towards cross-sectoral policy coherence and effective actions to address the growing burden of non-communicable diseases and obesity in Thailand.

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Our aim was to determine the normative reference values of cardiorespiratory fitness (CRF) and to establish the proportion of subjects with low CRF suggestive of future cardio-metabolic risk.

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Digital soil mapping is an alternative for the recognition of soil classes in areas where pedological surveys are not available. The main aim of this study was to obtain a digital soil map using artificial neural networks (ANN) and environmental variables that express soillandscape relationships. This study was carried out in an area of 11,072 ha located in the Barra Bonita municipality, state of São Paulo, Brazil. A soil survey was obtained from a reference area of approximately 500 ha located in the center of the area studied. With the mapping units identified together with the environmental variables elevation, slope, slope plan, slope profile, convergence index, geology and geomorphic surfaces, a supervised classification by ANN was implemented. The neural network simulator used was the Java NNS with the learning algorithm "back propagation." Reference points were collected for evaluating the performance of the digital map produced. The occurrence of soils in the landscape obtained in the reference area was observed in the following digital classification: medium-textured soils at the highest positions of the landscape, originating from sandstone, and clayey loam soils in the end thirds of the hillsides due to the greater presence of basalt. The variables elevation and slope were the most important factors for discriminating soil class through the ANN. An accuracy level of 82% between the reference points and the digital classification was observed. The methodology proposed allowed for a preliminary soil classification of an area not previously mapped using mapping units obtained in a reference area

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International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.