HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

Expert system for the assessment of power transformer insulation condition based on type-2 fuzzy logic systems

An efficient expert system for the power transformer condition assessment is presented in this paper. Through the application of Duval`s triangle and the method of the gas ratios a first assessment of the transformer condition is obtained in the form of a dissolved gas analysis (DGA) diagnosis according IEC 60599. As a second step, a knowledge mining procedure is performed, by conducting surveys whose results are fed into a first Type-2 Fuzzy Logic System (T2-FLS), in order to initially evaluate the condition of the equipment taking only the results of dissolved gas analysis into account. The output of this first T2-FLS is used as the input of a second T2-FLS, which additionally weighs up the condition of the paper-oil system. The output of this last T2-FLS is given in terms of words easily understandable by the maintenance personnel. The proposed assessing methodology has been validated for several cases of transformers in service. (C) 2010 Elsevier Ltd. All rights reserved.

Fuzzy risk index for power transformer failures due to external short-circuits

A novel methodology to assess the risk of power transformer failures caused by external faults, such as short-circuit, taking the paper insulation condition into account, is presented. The risk index is obtained by contrasting the insulation paper condition with the probability that the transformer withstands the short-circuit current flowing along the winding during an external fault. In order to assess the risk, this probability and the value of the degree of polymerization of the insulating paper are regarded as inputs of a type-2 fuzzy logic system (T2-FLS), which computes the fuzzy risk level. A Monte Carlo simulation has been used to find the survival function of the currents flowing through the transformer winding during a single-phase or a three-phase short-circuit. The Roy Billinton Test System and a real power system have been used to test the results. (C) 2008 Elsevier B.V. All rights reserved.

Model for Differential Nursing Diagnosis of Alterations in Urinary Elimination Based on Fuzzy Logic

Nursing diagnoses associated with alterations of urinary elimination require different interventions, Nurses, who are not specialists, require support to diagnose and manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for differential diagnosis of alterations in urinary elimination, considering nursing diagnosis approved by the North American Nursing Diagnosis Association, 2001-2002. Fuzzy relations and the maximum-minimum composition approach were used to develop the system. The model performance was evaluated with 195 cases from the database of a previous study, resulting in 79.0% of total concordance and 19.5% of partial concordance, when compared with the panel of experts. Total discordance was observed in only three cases (1.5%). The agreement between model and experts was excellent (kappa = 0.98, P < .0001) or substantial (kappa = 0.69, P < .0001) when considering the overestimative accordance (accordance was considered when at least one diagnosis was equal) and the underestimative discordance (discordance was considered when at least one diagnosis was different), respectively. The model herein presented showed good performance and a simple theoretical structure, therefore demanding few computational resources.

A fuzzy Reed-Frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization.

Evolutionary fuzzy clustering of relational data

This paper is concerned with the computational efficiency of fuzzy clustering algorithms when the data set to be clustered is described by a proximity matrix only (relational data) and the number of clusters must be automatically estimated from such data. A fuzzy variant of an evolutionary algorithm for relational clustering is derived and compared against two systematic (pseudo-exhaustive) approaches that can also be used to automatically estimate the number of fuzzy clusters in relational data. An extensive collection of experiments involving 18 artificial and two real data sets is reported and analyzed. (C) 2011 Elsevier B.V. All rights reserved.

On the efficiency of evolutionary fuzzy clustering

This paper tackles the problem of showing that evolutionary algorithms for fuzzy clustering can be more efficient than systematic (i.e. repetitive) approaches when the number of clusters in a data set is unknown. To do so, a fuzzy version of an Evolutionary Algorithm for Clustering (EAC) is introduced. A fuzzy cluster validity criterion and a fuzzy local search algorithm are used instead of their hard counterparts employed by EAC. Theoretical complexity analyses for both the systematic and evolutionary algorithms under interest are provided. Examples with computational experiments and statistical analyses are also presented.

Inteligência artificial aplicada à Zootecnia

Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.

Spatial patterns in the brood combs of Nannotrigona testaceicornis (Hymenoptera: Meliponinae): male clusters

Genetic models of sex and caste determination in eusocial stingless bees suggest specific patterns of male, worker and gyne cell distribution in the brood comb. Conflict between queen and laying workers over male parentage and center-periphery gradients of conditions, such as food and temperature, could also contribute to non-random spatial configuration. We converted the positions of the hexagonal cells in a brood comb to Cartesian coordinates, labeled by sex or caste of the individuals inside. To detect and locate clustered patterns, the mapped brood combs were evaluated by indexes of dispersion (MMC, mean distance of cells of a given category from their centroid) and eccentricity (DMB, distance between this centroid and the overall brood comb centroid) that we developed. After randomizing the labels and recalculating the indexes, we calculated probabilities that the original values had been generated by chance. We created sets of binary brood combs in which males were aggregated, regularly or randomly distributed among females. These stylized maps were used to describe the power of MMC and DMB, and they were applied to evaluate the male distribution in the sampled Nannotrigona testaceicornis brood combs. MMC was very sensitive to slight deviations from a perfectly rounded clump; DMB detected any asymmetry in the location of these compact to fuzzy clusters. Six of the 82 brood combs of N. testaceicornis that we analyzed had more than nine males, distributed according to variations in spatial patterns, as indicated by the two indexes.

Measurement of neutral mesons in p plus p collisions at root s=200 GeV and scaling properties of hadron production

The PHENIX experiment at the Relativistic Heavy Ion Collider has measured the invariant differential cross section for production of K(S)(0), omega, eta', and phi mesons in p + p collisions at root s 200 GeV. Measurements of omega and phi production in different decay channels give consistent results. New results for the omega are in agreement with previously published data and extend the measured p(T) coverage. The spectral shapes of all hadron transverse momentum distributions measured by PHENIX are well described by a Tsallis distribution functional form with only two parameters, n and T, determining the high-p(T) and characterizing the low-p(T) regions of the spectra, respectively. The values of these parameters are very similar for all analyzed meson spectra, but with a lower parameter T extracted for protons. The integrated invariant cross sections calculated from the fitted distributions are found to be consistent with existing measurements and with statistical model predictions.

Nuclear modification factors of phi mesons in d plus Au, Cu plus Cu, and Au plus Au collisions at root s(NN)=200 GeV

The PHENIX experiment at the Relativistic Heavy Ion Collider has performed systematic measurements of phi meson production in the K(+)K(-) decay channel at midrapidity in p + p, d + Au, Cu + Cu, and Au + Au collisions at root s(NN) = 200 GeV. Results are presented on the phi invariant yield and the nuclear modification factor R(AA) for Au + Au and Cu + Cu, and R(dA) for d + Au collisions, studied as a function of transverse momentum (1 < p(T) < 7 GeV/c) and centrality. In central and midcentral Au + Au collisions, the R(AA) of phi exhibits a suppression relative to expectations from binary scaled p + p results. The amount of suppression is smaller than that of the pi(0) and the. in the intermediate p(T) range (2-5 GeV/c), whereas, at higher p(T), the phi, pi(0), and. show similar suppression. The baryon (proton and antiproton) excess observed in central Au + Au collisions at intermediate p(T) is not observed for the phi meson despite the similar masses of the proton and the phi. This suggests that the excess is linked to the number of valence quarks in the hadron rather than its mass. The difference gradually disappears with decreasing centrality, and, for peripheral collisions, the R(AA) values for both particle species are consistent with binary scaling. Cu + Cu collisions show the same yield and suppression as Au + Au collisions for the same number of N(part). The R(dA) of phi shows no evidence for cold nuclear effects within uncertainties.

Cross section and double helicity asymmetry for eta mesons and their comparison to pi(0) production in p plus p collisions at root s=200 GeV

Measurements of double-helicity asymmetries in inclusive hadron production in polarized p + p collisions are sensitive to helicity-dependent parton distribution functions, in particular, to the gluon helicity distribution, Delta g. This study focuses on the extraction of the double-helicity asymmetry in eta production ((p) over right arrow + (p) over right arrow -> eta + X), the eta cross section, and the eta/pi(0) cross section ratio. The cross section and ratio measurements provide essential input for the extraction of fragmentation functions that are needed to access the helicity-dependent parton distribution functions.

High p(T) direct photon and pi(0) triggered azimuthal jet correlations and measurement of k(T) for isolated direct photons in p plus p collisions at root s=200 GeV

Correlations of charged hadrons of 1< p(T) < 10 Gev/c with high pT direct photons and pi(0) mesons in the range 5< p(T) < 15 Gev/c are used to study jet fragmentation in the gamma + jet and dijet channels, respectively. The magnitude of the partonic transverse momentum, k(T), is obtained by comparing to a model incorporating a Gaussian kT smearing. The sensitivity of the associated charged hadron spectra to the underlying fragmentation function is tested and the data are compared to calculations using recent global fit results. The shape of the direct photon-associated hadron spectrum as well as its charge asymmetry are found to be consistent with a sample dominated by quark-gluon Compton scattering. No significant evidence of fragmentation photon correlated production is observed within experimental uncertainties.

Enhanced Production of Direct Photons in Au plus Au Collisions at root s(NN)=200 GeV and Implications for the Initial Temperature

The production of e(+)e(-) pairs for m(e+e-) < 0.3 GeV/c(2) and 1< p(T) < 5 GeV/c is measured in p + p and Au + Au collisions at root s(NN) = 200 GeV. An enhanced yield above hadronic sources is observed. Treating the excess as photon internal conversions, the invariant yield of direct photons is deduced. In central Au + Au collisions, the excess of the direct photon yield over p + p is exponential in transverse momentum, with an inverse slope T = 221 +/- 19(stat) +/- 19(syst) MeV. Hydrodynamical models with initial temperatures ranging from T(init) similar to 300-600 MeV at times of similar to 0.6-0.15 fm/c after the collision are in qualitative agreement with the data. Lattice QCD predicts a phase transition to quark gluon plasma at similar to 170 MeV.