Optimizing feature selection through binary charged system search

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

CENSUS HISTOGRAMS: A SIMPLE FEATURE EXTRACTION and MATCHING APPROACH FOR FACE RECOGNITION

Most face recognition approaches require a prior training where a given distribution of faces is assumed to further predict the identity of test faces. Such an approach may experience difficulty in identifying faces belonging to distributions different from the one provided during the training. A face recognition technique that performs well regardless of training is, therefore, interesting to consider as a basis of more sophisticated methods. In this work, the Census Transform is applied to describe the faces. Based on a scanning window which extracts local histograms of Census Features, we present a method that directly matches face samples. With this simple technique, 97.2% of the faces in the FERET fa/fb test were correctly recognized. Despite being an easy test set, we have found no other approaches in literature regarding straight comparisons of faces with such a performance. Also, a window for further improvement is presented. Among other techniques, we demonstrate how the use of SVMs over the Census Histogram representation can increase the recognition performance.

New Insights on Nontechnical Losses Characterization Through Evolutionary-Based Feature Selection

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

Adaptive filter feature identification for structural health monitoring in an aeronautical panel

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Feature selection through gravitational search algorithm

In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are conducted in order to asses the robustness of the proposed technique against Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and a Particle Swarm Optimization (PSO)-based algorithm for feature selection.

Role of the surface state and structural feature in the thermoreversible sol-gel transition of a zirconyl aqueous precursor modified by sulfuric acid

The sols produced by admixture of ZrOCl2 acidified solutions to hot H2SO4 aqueous solutions were studied to clarify the effects of Cl- and SO42- ions on the kinetic stability of nanoparticles and to obtain some new evidence concerning the mechanism of a thermoreversible sol-gel transition observed in this system. The study of suspensions prepared with different molar ratios R-S = [Zr]/[SO42-] and R-Cl = [Zr]/[Cl-] revealed domains of composition of formation of thermoreversible gels, thermostable sols, and powder precipitation. The effects of R-S and R-Cl on the structural features of nanoparticles and on the particle solution interface were systematically analyzed for samples of thermoreversible and thermostable sol domains. Small-angle X-ray scattering measurements revealed the presence of small fractal aggregates in all samples of thermoreversible domains, while compact packing aggregates of primary particles are present in the thermostable sol. Extended X-ray absorption fine structure and elemental chemical analysis revealed that irrespective of the nominal value of R-S and R-Cl all studied samples of the thermoreversible domain are constituted by a well-defined compound possessing an inner core made of hydroxyl and oxo groups bridging together zirconium atoms surrounded on the surface by complexing sulfate ligands. zeta potentials of powders extracted by freeze-drying from the thermoreversible gel revealed a point of surface charge inversion attributed to the specific adsorption of SO42- ion. Thermoreversible gel formation is rationalized by considering the effect of the specific adsorption on the electrical double-layer repulsion together with the temperature dependency of the physical chemical properties of ions in solution.

Butanolides as a common feature of Iryanthera lancifolia and Virola surinamensis

A comparative phytochemical study between pericarps of Iryanthera lancifolia and Virola surinamensis showed that the first one contains a new pair of epimeric 2-alkenyl-gamma-lactones, besides an aryltetralinic lignan and one tocotrienol, while the second species contains the lignans, galgravin and veraguensin, seven juruenolides: juruenolides C, D, F, G and epi-juruenolides D, F, G, together with three pairs of epimeric aliphatic 2-alkenyl-gamma-lactones. Juruenolide F, epi-juruenolides D, F, G and the 2-alkenyl-gamma-lactones are new natural compounds. (C) 1998 Elsevier B.V. Ltd. All rights reserved.

SnO2, ZnO and related polycrystalline compound semiconductors: An overview and review on the voltage-dependent resistance (non-ohmic) feature

The present review describes mainly the history of SnO2-based voltage-dependent resistors, discusses the main characteristics of these polycrystalline semiconductor systems and includes a direct comparison with traditional ZnO-based voltage-dependent resistor systems to establish the differences and similarities, giving details of the basic physical principles involved with the non-ohmic properties in both polycrystalline systems. As an overview, the text also undertakes the main difficulties involved in processing SnO2- and ZnO-based non-ohmic systems, with an evaluation of the contribution of the dopants to the electronic properties and to the final microstructure and consequently to the system's non-ohmic behavior. However, since there are at least two review texts regarding ZnO-based systems [Levinson, L. M., and Philipp, H. R. Ceramic Bulletin 1985;64:639; Clarke, D. R. Journal of American Ceramic Society 1999;82:485], the main focus of the present text is dedicated to the SnO2-based varistor systems, although the basic physical principles described in the text are universally useful in the context of dense polycrystalline devices. However, the readers must be careful of how the microstructure heterogeneity and grain-boundary chemistry are capable to interfere in the global electrical response for particular systems. New perspectives for applications, commercialization and degradation studies involving SnO2-based polycrystalline non-ohmic systems are also outlined, including recent technological developments. Finally, at the end of this review a brief section is particularly dedicated to the presentation and discussions about others emerging non-ohmic polycrystalline ceramic devices (particularly based on perovskite ceramics) which must be deeply studied in the years to come, specially because some of these systems present combined high dielectric and non-ohmic properties. From both scientific and technological point of view these perovskite systems are quite interesting. (c) 2007 Elsevier Ltd. All rights reserved.

The dielectric suppress and the control of semiconductor non-Ohmic feature of CaCu3Ti4O12 by means of tin doping

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Adaptive filter feature identification for structural health monitoring in aeronautical panel

This paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc.

Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Improving Parkinson's disease identification through evolutionary-based feature selection

Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given that each possible solution to be optimized is guided by the OPF accuracy. We also show results that improved other ones recently obtained in the context of PD automatic identification. © 2011 IEEE.