38 resultados para Fuzzy K Nearest Neighbor


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

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

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Phase transitions involving spontaneous time-reversal symmetry breaking are studied on the honeycomb lattice at finite hole doping with next-nearest-neighbor repulsion. We derive an exact expression for the mean-field equation of state in closed form, valid at temperatures much less than the Fermi energy. Contrary to standard expectations, we find that thermally induced intraband particle-hole excitations can create and stabilize a uniform metallic phase with broken time-reversal symmetry as the temperature is raised in a region where the ground state is a trivial metal.

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

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The impact of peritoneal dialysis modality on patient survival and peritonitis rates is not fully understood, and no large-scale randomized clinical trial (RCT) is available. In the absence of a RCT, the use of an advanced matching procedure to reduce selection bias in large cohort studies may be the best approach. The aim of this study is to compare automated peritoneal dialysis (APD) and continuous ambulatory peritoneal dialysis (CAPD) according to peritonitis risk, technique failure and patient survival in a large nation-wide PD cohort. This is a prospective cohort study that included all incident PD patients with at least 90 days of PD recruited in the BRAZPD study. All patients who were treated exclusively with either APD or CAPD were matched for 15 different covariates using a propensity score calculated with the nearest neighbor method. Clinical outcomes analyzed were overall mortality, technique failure and time to first peritonitis. For all analysis we also adjusted the curves for the presence of competing risks with the Fine and Gray analysis. After the matching procedure, 2,890 patients were included in the analysis (1,445 in each group). Baseline characteristics were similar for all covariates including: age, diabetes, BMI, Center-experience, coronary artery disease, cancer, literacy, hypertension, race, previous HD, gender, pre-dialysis care, family income, peripheral artery disease and year of starting PD. Mortality rate was higher in CAPD patients (SHR1.44 CI95%1.21-1.71) compared to APD, but no difference was observed for technique failure (SHR0.83 CI95%0.69-1.02) nor for time till the first peritonitis episode (SHR0.96 CI95%0.93-1.11). In the first large PD cohort study with groups balanced for several covariates using propensity score matching, PD modality was not associated with differences in neither time to first peritonitis nor in technique failure. Nevertheless, patient survival was significantly better in APD patients.

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A methodology for pipeline leakage detection using a combination of clustering and classification tools for fault detection is presented here. A fuzzy system is used to classify the running mode and identify the operational and process transients. The relationship between these transients and the mass balance deviation are discussed. This strategy allows for better identification of the leakage because the thresholds are adjusted by the fuzzy system as a function of the running mode and the classified transient level. The fuzzy system is initially off-line trained with a modified data set including simulated leakages. The methodology is applied to a small-scale LPG pipeline monitoring case where portability, robustness and reliability are amongst the most important criteria for the detection system. The results are very encouraging with relatively low levels of false alarms, obtaining increased leakage detection with low computational costs. (c) 2005 Elsevier B.V. All rights reserved.

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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.