6 resultados para ERS

em Universidade Federal do Rio Grande do Norte(UFRN)


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Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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Introduction: The leukemias are the most common malignancy in children and adolescents. With the improvement in outcomes, there is a need to consider the morbidity to generate the protocols used in children under treatment. Aim: To evaluate pulmonary function in children with acute leukemia. Method: This study is an observational cross sectional. We evaluated 34 children distributed in groups A and B. Group A comprised 17 children with acute leukemia in the maintenance phase of chemotherapy treatment and group B with 17 healthy students from the public in the city of Natal / RN, matched for gender, age and height. The thoracic mobility was evaluated by thoracic expansion in the axillary and xiphoid levels. Spirometry was measured using a spirometer Microloop Viasys ® following the rules of the ATS and ERS. Maximal respiratory pressures were measured with digital manometer MVD300 (Globalmed ®). The maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP) were measured from residual volume and total lung capacity, respectively. The data were analyzed using the SPSS 17.0 software assigning the significance level of 5%. Descriptive analysis was expressed as mean and standard deviation. T'student test was used to compare unpaired values found in group A with group B values, as well as with the reference values used. To compare the respiratory coefficients in the axillary level with the xiphoid in each group, we used paired testing t student. Results: Group A was significantly decreased thoracic mobility and MIP compared to group B, and MIP compared to baseline. There was no significant difference between spirometric data from both groups and the values of group A with the reference values Mallozi (1995). There was no significant difference between the MIP and MEP values and lower limits of reference proposed by Borja (2011). Conclusion: Children with acute leukemia, myeloid or lymphoid, during maintenance phase of chemotherapy treatment have reduced thoracic mobility and MIP. However, to date, completion of clinical treatment, the spirometric variables and the strength of the expiratory muscles appear to remain preserved in children between five and ten years

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The use of multi-agent systems for classification tasks has been proposed in order to overcome some drawbacks of multi-classifier systems and, as a consequence, to improve performance of such systems. As a result, the NeurAge system was proposed. This system is composed by several neural agents which communicate and negotiate a common result for the testing patterns. In the NeurAge system, a negotiation method is very important to the overall performance of the system since the agents need to reach and agreement about a problem when there is a conflict among the agents. This thesis presents an extensive analysis of the NeurAge System where it is used all kind of classifiers. This systems is now named ClassAge System. It is aimed to analyze the reaction of this system to some modifications in its topology and configuration

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Objective to establish a methodology for the oil spill monitoring on the sea surface, located at the Submerged Exploration Area of the Polo Region of Guamaré, in the State of Rio Grande do Norte, using orbital images of Synthetic Aperture Radar (SAR integrated with meteoceanographycs products. This methodology was applied in the following stages: (1) the creation of a base map of the Exploration Area; (2) the processing of NOAA/AVHRR and ERS-2 images for generation of meteoceanographycs products; (3) the processing of RADARSAT-1 images for monitoring of oil spills; (4) the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products; and (5) the structuring of a data base. The Integration of RADARSAT-1 image of the Potiguar Basin of day 21.05.99 with the base map of the Exploration Area of the Polo Region of Guamaré for the identification of the probable sources of the oil spots, was used successfully in the detention of the probable spot of oil detected next to the exit to the submarine emissary in the Exploration Area of the Polo Region of Guamaré. To support the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products, a methodology was developed for the classification of oil spills identified by RADARSAT-1 images. For this, the following algorithms of classification not supervised were tested: K-means, Fuzzy k-means and Isodata. These algorithms are part of the PCI Geomatics software, which was used for the filtering of RADARSAT-1 images. For validation of the results, the oil spills submitted to the unsupervised classification were compared to the results of the Semivariogram Textural Classifier (STC). The mentioned classifier was developed especially for oil spill classification purposes and requires PCI software for the whole processing of RADARSAT-1 images. After all, the results of the classifications were analyzed through Visual Analysis; Calculation of Proportionality of Largeness and Analysis Statistics. Amongst the three algorithms of classifications tested, it was noted that there were no significant alterations in relation to the spills classified with the STC, in all of the analyses taken into consideration. Therefore, considering all the procedures, it has been shown that the described methodology can be successfully applied using the unsupervised classifiers tested, resulting in a decrease of time in the identification and classification processing of oil spills, if compared with the utilization of the STC classifier

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The piles are one of the most important types of solution adopted for the foundation of buildings. They are responsible for transmitting to the soil in deepe r and resistant layers loads from structures. The interaction of the foundation element with the soil is a very important variable, making indispensable your domain in order to determine the strength of the assembly and establish design criteria for each c ase of application of the pile. In this research analyzes were performed f rom experiments load tests for precast concrete piles and inve stigations of soil of type SPT, a study was performed for obtaining the ultimate load capacity of the foundation through methods extrapolation of load - settlement curve , semi - empirical and theoretic . After that, were realized comparisons between the different methods used for two types of soil a granular behavior and other cohesive. For obtaining soil paramet ers to be used i n the methods were established empirical correlations with the standard penetration number (NSPT). The charge - settlement curves of the piles are also analyzed. In the face of established comparisons was indicated the most reliable semiempirical method Déco urt - Quaresma as the most reliable for estimating the tensile strength for granular and cohesive soils. Meanwhile, among the methods studied extrapolation is recommended method of Van der Veen as the most appropriate for predicting the tensile strength.