38 resultados para Mining equipment
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Pós-graduação em Geociências e Meio Ambiente - IGCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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This study aimed to evaluate the sediment quality in the estuarine protected area known as Canan,ia-Iguape-Peruibe (CIP-PA), located on the southeastern coast of Brazil. The study was designed considering possible negative effects induced by the city of Canan,ia on the sediment quality of surrounding areas. This evaluation was performed using chemical and ecotoxicological analyses. Sediments were predominantly sandy, with low CaCO3 contents. Amounts of organic matter varied, but higher contents occurred closer to the city, as well as did Fe and Total Recoverable Oils and Greases (TROGs) concentrations. Contamination by Cd and Cu was revealed in some samples, while concentrations of Zn were considered low. Chronic toxicity was detected in all tested sediments and acute toxicity occurred only in sediments collected near the city. The principal component analysis (PCA) revealed an association among Cd, Cu, Fe, TROG, fines, organic matter, CaCO3, and chronic toxicity, whereas acute toxicity was found to be associated with Zn and mud. However, because Zn levels were low, acute toxicity was likely due to a contaminant that was not measured. Results show that there is a broad area within the CIP-PA that is under the influence of mining activities (chronic toxicity, moderate contamination by metals), whereas poorer conditions occur closer to Canan,ia (acute toxicity); thus, the urban area seems to constitute a relevant source of contaminants for the estuarine complex. These results show that contamination is already capable of producing risks for the local aquatic biota, which suggests that the CIP-PA effectiveness in protecting estuarine biota may be threatened.
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Background: Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods: Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results: This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion: The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.
Spatial Data Mining to Support Environmental Management and Decision Making - A Case Study in Brazil
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this work design criteria for cooling of electronic systems used in a digital transmission equipment are considered. An experimental study using a simulated electronic equipment in which vertically oriented circuit boards are aligned to form vertical channels is carried out. Resistors are used to simulate actual components. The temperature of several components in the printed circuit boards are measured and the influence of the baffles and shields on the cooling effect are discussed. It was observed that the use of the baffles reduce the temperature levels and, the use of shields, although protecting the components from magnetic effects, cause an increase in the temperature levels.
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The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.