Beatriz S. L. P. de Lima

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Complex network analysis is a growing research area in a wide variety of domains and has recently become closely associated with data, text and web mining. One of the most active areas in the study of complex networks is the detection of community structure, which can be related to the clustering problem in data mining. This paper employs a community(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: Abstract This paper presents a design method for fuzzy rule-based systems that(More)
– This article provides a derivation and a description of the analysis on pair of plots graphs, useful to data fusion of multiple targets in a multiple sensors cluttered environment. The method proposes an analysis in two stages, instead of the previously proposed single-stage method, to choose the best data from possible redundant sensors. The analysis in(More)
Different models such as diffusion-collision and nucleation-condensation have been used to unravel how secondary and tertiary structures form during protein folding. However, a simple mechanism based on physical principles that provide an accurate description of kinetics and thermodynamics for such phenomena has not yet been identified. This study(More)
Parameter adjustment of a fusion system for 3D image interpretation is often a difficult task that is emphasized by the non understandability of the parameters by the end-users. Moreover, such fusion systems are complex because they involve a complete information treatment chain (from the information extraction to the decision). The sub-parts of the system(More)
In data mining, the traditional classification algorithms tend to loose its predictive capacity when applied on a dataset which distribution between classes is imbalanced. This work aims to present a new methodology using genetic algorithms, in order to create synthetic instances from the minority class. The experiments with the proposed methodology(More)
— An approach to estimate the number of rules by spectral analysis of the training dataset has been recently proposed [1]. This work presents an analysis of such a method in high performance computing environment. Two approaches for parallel implementation of the method were studied considering the structure selection genetic algorithm and the spectral(More)