MR-Radix: a multi-relational data mining algorithm

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.

Electrochemical oxidation of landfill leachate in a flow reactor: optimization using response surface methodology

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The "chemical oxygen demand/total volatile acids" ratio as an anaerobic treatability indicator for landfill leachates

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparative analysis between biogas flow in landfill and electrical resistivity tomography in Rio Claro city, Brazil

The biogas originated from anaerobic degradation of organic matter in landfills consists basically in CH4, CO2, and H2O. The landfills represent an important depository of organic matter with high energetic potential in Brazil, although with inexpressive use in the present. The estimation of production of the productive rate of biogas represents one of the major difficulties of technical order to the planning of capture system for rational consumption of this resource. The applied geophysics consists in a set of methods and techniques with wide use in environmental and hydrogeological studies. The DC resistivity method is largely applied in environmental diagnosis of the contamination in soil and groundwater, due to the contrast of electrical properties frequent between contaminated areas and the natural environment. This paper aims to evaluate eventual relationships between biogas flows quantified in drains located in the landfill, with characteristic patterns of electrical resistivity in depth. The drain of higher flow (117 m3 /h) in depth was characterized for values between 8000 Ω⋅m and 100.000 Ω⋅m, in contrast with values below 2000 Ω⋅m, which characterize in subsurface the drain with less flow (37 m3 /h), besides intermediary flow and electrical resistivity values, attributed to the predominance of areas with accumulation or generation of biogas.

The chemical oxygen demand / total volatile acids ratio as an anaerobic treatability indicator for landfill leachates

In some operational circumstances a fast evaluation of landfill leachate anaerobic treatability is necessary, and neither Biochemical Methane Potential nor BOD/COD ratio are fast enough. Looking for a fast indicator, this work evaluated the anaerobic treatability of landfill leachate from São Carlos-SP (Brazil) in a pilot scale Anaerobic Sequence Batch Biofilm Reactor (AnSBBR). The experiment was conducted at ambient temperature in the landfill area. After the acclimation, at a second stage of operation, the AnSBBR presented efficiency above 70%, in terms of COD removal, utilizing landfill leachate without water dilution, with an inlet COD of about 11,000 mg.L-1, a TVA/COD ratio of approximately 0.6 and reaction time equal to 7 days. To evaluate the landfill leachate biodegradability variation over time, temporal profiles of concentration were performed in the AnSBBR. The landfill leachate anaerobic biodegradability was verified to have a direct and strong relationship to the TVA/COD ratio. For a TVA/CODTotal ratio lower than 0.20, the biodegradability was considered low, for ratios between 0.20 and 0.40 it was considered medium, and above 0.40 it was considered high.

OntoSDM: an approach to improve quality on spatial data mining algorithms

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.