Bifundamental fuzzy 2-Sphere and fuzzy killing spinors

We review our construction of a bifundamental version of the fuzzy 2-sphere and its relation to fuzzy Killing spinors, first obtained in the context of the ABJM membrane model. This is shown to be completely equivalent to the usual (adjoint) fuzzy sphere. We discuss the mathematical details of the bifundamental fuzzy sphere and its field theory expansion in a model-independent way. We also examine how this new formulation affects the twisting of the fields, when comparing the field theory on the fuzzy sphere background with the compactification of the 'deconstructed' (higher dimensional) field theory.

Characterization of the temperature, load and damage effects using piezoelectric transducer patches based on fuzzy clustering

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.

Application of Conservative Power Theory to load and line characterization and revenue metering

This paper proposes a set of performance factors for load characterization and revenue metering. They are based on the Conservative Power Theory, and each of them relates to a specific load non-ideality (unbalance, reactivity, distortion). The performance factors are capable to characterize the load under different operating conditions, considering also the effect of non-negligible line impedances and supply voltage deterioration. © 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.

Stability of nonlinear system using takagi-sugeno fuzzy models and hyper-rectangle of LMIs

This paper presents a theorem based on the hyper-rectangle defined by the closed set of the time derivatives of the membership functions of Takagi-Sugeno fuzzy systems. This result is also based on Linear Matrix Inequalities and allows the reduction of the conservatism of the stability analysis in the sense of Lyapunov. The theorem generalizes previous results available in the literature. © 2013 Brazilian Society for Automatics - SBA.

Análise da estabilidade de sistemas fuzzy Takagi-Sugeno utilizando as desigualdades de Lyapunov-Metzler

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detecção e classificação de faltas de alta impedância em sistemas elétricos de potência usando lógica Fuzzy

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Uma aplicação da lógica Fuzzy

Pós-graduação em Matemática Universitária - IGCE

Kappa-PSO-ARTMAP Fuzzy: uma metodologia para detecção de intrusos baseado em seleção de atributos e otimização de parâmetros numa rede neural ARTMAP Fuzzy

Pós-graduação em Engenharia Elétrica - FEIS

Análise da estabilidade transitória via rede neural Art-Artmap fuzzy Euclidiana modificada com treinamento continuado

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção, classificação e localização de faltas de curto-circuito em sistemas de distribuição de energia elétrica usando sistemas inteligentes

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

Previsão de carga multinodal usando a rede neural ART-ARTMAP fuzzy

Pós-graduação em Engenharia Elétrica - FEIS

Análise dinâmica de contingências de sistemas de energia elétrica por redes neurais baseadas na teoria da ressonância adaptativa

Pós-graduação em Engenharia Elétrica - FEIS

Desenvolvimento de um modelo fuzzy para determinação do calor latente com aplicação em sistemas de irrigação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Enquadramento tarifário de energia elétrica em agroindústria utilizando teoria Fuzzy

Pós-graduação em Agronomia (Energia na Agricultura) - FCA