Mechanical tillage of degraded mining areas at Jamari national forest (Amazonian forest, Rondônia - BR)

According to the environmental legislation enforced in Brazil and the process of marketing globalization, the commitment of the nations to the preservation of the environment is intensified. By reason of nature's negative responses to its intensive use, awareness then appears from enterprises and agencies about how the anthropic action over the environment needs to be minimized, becoming a challenge: development and sustainability. In this context, the present work made use of the Mechanical tillage of the soil, as a technique to apply, in a large scale, the strategies and methods to recover mined areas that were researched and developed experimentally by researchers on a theme project about the recovering of degraded areas. This work was conducted in the Amazon ecosystem, inside the Jamari National Forest - Rondônia (FLONA do Jamari), in deactivated cassiterite mines. The objectives of this work were to: Develop a computational program capable of managing a database and assist in the selection of machines and preparation methods to execute the operations of topographical reconstitution and tillage of surfaces in areas degraded by the mineral exploitation of cassiterite. Use the program that was developed in the planning of costs and operational development, for the operations required in the strategies for recovering the areas. Analyze the vegetable productivity in the mobilized areas and the quality of the superficial mobilization, making use of indicators and tillage methods. Evaluate, through biological indicators, the efficiency of the recovery strategies and techniques that were mechanized and applied on the location. The results showed that the developed computational program (SGMAD) served the methodological purposes (the analysis of costs and operational capacity) established for the planning and the selection of the tillage machines and methods in the areas of mineral exploitation of cassiterite. The applied methods and quality of the superficial mobilization were significant to the development of leguminous plants in the areas. The use of biological indicators (microbial biomass and enzymatic activity) in the evaluation of the adopted techniques and strategies revealed that the planting of leguminous plants and their posterior incorporation have been promoting gradually positive alterations in some of the analyzed soil/substract parameters. © 2010 WIT Press.

A graph-based framework for thermal faceprint characterization

Thermal faceprint has been paramount in the last years. Since we can handle with face recognition using images acquired in the infrared spectrum, an unique individual's signature can be obtained through the blood vessels network of the face. In this work, we propose a novel framework for thermal faceprint extraction using a collection of graph-based techniques, which were never used to this task up to date. A robust method of thermal face segmentation is also presented. The experiments, which were conducted over the UND Collection C dataset, have showed promising results. © 2011 Springer-Verlag.

Comparative study of algorithms for mining association rules: Traditional approach versus multi-relational approach

The multi-relational Data Mining approach has emerged as alternative to the analysis of structured data, such as relational databases. Unlike traditional algorithms, the multi-relational proposals allow mining directly multiple tables, avoiding the costly join operations. In this paper, is presented a comparative study involving the traditional Patricia Mine algorithm and its corresponding multi-relational proposed, MR-Radix in order to evaluate the performance of two approaches for mining association rules are used for relational databases. This study presents two original contributions: the proposition of an algorithm multi-relational MR-Radix, which is efficient for use in relational databases, both in terms of execution time and in relation to memory usage and the presentation of the empirical approach multirelational advantage in performance over several tables, which avoids the costly join operations from multiple tables. © 2011 IEEE.

Multi-relational algorithm for mining association rules in large databases

Multi-relational data mining enables pattern mining from multiple tables. The existing multi-relational mining association rules algorithms are not able to process large volumes of data, because the amount of memory required exceeds the amount available. The proposed algorithm MRRadix presents a framework that promotes the optimization of memory usage. It also uses the concept of partitioning to handle large volumes of data. The original contribution of this proposal is enable a superior performance when compared to other related algorithms and moreover successfully concludes the task of mining association rules in large databases, bypass the problem of available memory. One of the tests showed that the MR-Radix presents fourteen times less memory usage than the GFP-growth. © 2011 IEEE.

Groundwater quality on a waste disposal area due to sand mining activities in São Paulo state, Brazil

This investigation reports the results of a study realized in an area related to the development of sand mining activities, which belongs to Sibelco Mineração Ltd. The site is located around Analândia municipality, nearly in the center of São Paulo State, Brazil. Hydrochemical analyses of groundwater were realized under different periods of time, with the aim of evaluating the possibility of release of several constituents to the liquid phase, which may be a source of pollution of the surface hydrological resources and of the deeper Guarani aquifer. This is because the site is located at the recharge area of Guarani aquifer and some tributaries from Corumbataí river may also be suffering contamination, implying on the impoverishment of the water quality that are very important resources in the region, as they are extensively used for drinking purposes, among others.© 2011 WIT Press.

Semiautomatic dental recognition using a graph-based segmentation algorithm and teeth shapes features

Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.

Fuzzy community structure detection by particle competition and cooperation

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

3D geovisualisation techniques applied in spatial data mining

The increase in the number of spatial data collected has motivated the development of geovisualisation techniques, aiming to provide an important resource to support the extraction of knowledge and decision making. One of these techniques are 3D graphs, which provides a dynamic and flexible increase of the results analysis obtained by the spatial data mining algorithms, principally when there are incidences of georeferenced objects in a same local. This work presented as an original contribution the potentialisation of visual resources in a computational environment of spatial data mining and, afterwards, the efficiency of these techniques is demonstrated with the use of a real database. The application has shown to be very interesting in interpreting obtained results, such as patterns that occurred in a same locality and to provide support for activities which could be done as from the visualisation of results. © 2013 Springer-Verlag.