Step by step analyses of Clarke's matrix correction procedure for untransposed three-phase transmission line cases

The correction procedure for Clarke's matrix, considering three-phase transmission line analyzes, is analyzed step by step in this paper, searching to improve the application of this procedure. Changing the eigenvectors as modal transformation matrices, Clarke's matrix has been applied to analyses for transposed and untransposed three-phase transmission line cases. It is based on the fact that Clarke's matrix is an eigenvector matrix for transposed three-phase transmission lines considering symmetrical and asymmetrical cases. Because of this, the application of this matrix has been analyzed considering untransposed three-phase transmission lines. In most of these cases, the errors related to the eigenvalues can be considered negligible. It is not true when it is analyzed the elements that are not in main diagonal of the quasi-mode matrix. This matrix is obtained from the application of Clarke's matrix. The quasi-mode matrix is correspondent to the eigenvalue matrix. Their off-diagonal elements represent couplings among the quasi-modes. So, the off-diagonal quasi-mode element relative values are not negligible when compared to the eigenvalues that correspond to the coupled quasi-modes. Minimizing these relative values, the correction procedure is analyzed in detail, checking some alternatives for the correction procedure application.

Precision of yule-walker methods for the arma spectral model

In this work a new method is proposed of separated estimation for the ARMA spectral model based on the modified Yule-Walker equations and on the least squares method. The proposal of the new method consists of performing an AR filtering in the random process generated obtaining a new random estimate, which will reestimate the ARMA model parameters, given a better spectrum estimate. Some numerical examples will be presented in order to ilustrate the performance of the method proposed, which is evaluated by the relative error and the average variation coefficient.

Genetic effects on preweaning weight gain of Nelore-Hereford calves according to different models and estimation methods

Additive and nonadditive genetic effects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different genetic models and estimation methods. The data set consisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epistasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed variability in preweaning traits of Bos taurus x Bos indicus calves, and that genotype x environment interaction plays an important role in the evaluation of crossbred calves. Data were ill-conditioned to estimate the effects of genotype x environment interactions. Models including these effects presented multicolinearity problems. In this case, RR seemed to be a powerful tool for obtaining more plausible and stable estimates. Estimated prediction error variances and variance inflation factors were drastically reduced, and many effects that were not significant under ordinary least squares became significant under RR. Predictions of PWG based on RR estimates were more acceptable from a biological perspective. In temperate and subtropical regions, calves with intermediate genetic compositions (close to 1/2 Nelore) exhibited greater predicted PWG. In the tropics, predicted PWG increased linearly as genotype got closer to Nelore. ©2006 American Society of Animal Science. All rights reserved.

Correction procedure applied to a single real transformation matrix -Untransposed three-phase transmission line cases

Clarke's matrix has been used as an eigenvector matrix for transposed three-phase transmission lines and it can be applied as a phase-mode transformation matrix for transposed cases. Considering untransposed three-phase transmission lines, Clarke's matrix is not an exact eigenvector matrix. In this case, the errors related to the diagonal elements of the Z and Y matrices can be considered negligible, if these diagonal elements are compared to the exact elements in domain mode. The mentioned comparisons are performed based on the error and frequency scan analyses. From these analyses and considering untransposed asymmetrical three-phase transmission lines, a correction procedure is determined searching for better results from the Clarke's matrix use as a phase-mode transformation matrix. Using the Clarke's matrix, the relative errors of the eigenvalue matrix elements can be considered negligible and the relative values of the off-diagonal elements are significant. Applying the corrected transformation matrices, the relative values of the off-diagonal elements are decreased. The comparisons among the results of these analyses show that the homopolar mode is more sensitive to the frequency influence than the two other modes related to three-phase lines. © 2006 IEEE.

Fusion of fingerprint recognition methods for robust human identification

Biometrics is one of the biggest tendencies in human identification. The fingerprint is the most widely used biometric. However considering the automatic fingerprint recognition a completely solved problem is a common mistake. The most popular and extensively used methods, the minutiae-based, do not perform well on poor-quality images and when just a small area of overlap between the template and the query images exists. The use of multibiometrics is considered one of the keys to overcome the weakness and improve the accuracy of biometrics systems. This paper presents the fusion of a minutiae-based and a ridge-based fingerprint recognition method at rank, decision and score level. The fusion techniques implemented leaded to a reduction of the Equal Error Rate by 31.78% (from 4.09% to 2.79%) and a decreasing of 6 positions in the rank to reach a Correct Retrieval (from rank 8 to 2) when assessed in the FVC2002-DB1A database. © 2008 IEEE.

Numerical correction for the diffuse solar irradiance by the melo-escobedo shadowring measuring method

The present paper deals with numerical corrections factors proposed as a function of the clearness index in order to correct the diffuse solar irradiance measured with the Melo-Escobedo Shadowring Measuring Method (ME shadowring). The global irradiance was measured by an Eppley - PSP pyranometer ; direct normal irradiance by an Eppley-NIP pyrheliometer fitted to a ST-3 sun tracking device and the diffuse irradiance by an Eppley-PSP pyranometer fitted to a ME shadowring. The validations were performed by the MBE and RMSE statistical indicators. The results showed that the numerical correction factors were appropriate to correct the shadowring diffuse irradiance.

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

Cephalometric analysis of prediction tracings: A comparison of three different methods

The purpose of this study was to compare-using cephalometric analysis (McNamara, and Legan and Burstone)-prediction tracings performed using three different methods, that is, manual and using the Dentofacial Planner Plus and Dolphin Image computer programs, with postoperative outcomes. Pre- and postoperative (6 months after surgery) lateral cephalometric radiographs were selected from 25 long-faced patients treated with combined surgery. Prediction tracings were made with each method and compared cephalometrically with the postoperative results. This protocol was repeated once more for method error evaluation. Statistical analysis was made by ANOVA and the Tukey test. The results showed superior predictability when the manual method was applied (50% similarity to postoperative results), followed by Dentofacial Planner Plus (31.2%) and Dolphin Image (18.8%). The experimental condition suggests that the manual method provides greater accuracy, although the predictability of the digital methods proved quite satisfactory. © 2013 World Federation of Orthodontists.

Approximation of hyperbolic tangent activation function using hybrid methods

Artificial Neural Networks are widely used in various applications in engineering, as such solutions of nonlinear problems. The implementation of this technique in reconfigurable devices is a great challenge to researchers by several factors, such as floating point precision, nonlinear activation function, performance and area used in FPGA. The contribution of this work is the approximation of a nonlinear function used in ANN, the popular hyperbolic tangent activation function. The system architecture is composed of several scenarios that provide a tradeoff of performance, precision and area used in FPGA. The results are compared in different scenarios and with current literature on error analysis, area and system performance. © 2013 IEEE.

Evapotranspiração e coeficientes de cultura da melancieira irrigada por gotejamento em Alvorada do Gurguéia-PI

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Effects of the Eccentricity of a Perturbing Third Body on the Orbital Correction Maneuvers of a Spacecraft

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparative study of ultrasonographic methods for assessment of pregnancy age in bitches

Compared with human beings, the application of ultrasound in estimating fetal age in bitches is limited due to the large variation of breed and size in this species. Several formulas were developed to calculate the gestational age and to provide the date of birth in dogs, but the efficacy of these formulas on the different gestational stages and dog breeds is unknown. The aim of this study was to compare sonographic methods for assessment of gestational age and days before parturition in dogs with different body weights and pregnancy stages. Twenty seven bitches of several sizes were examined and divided into three groups according to the initial body weight (A: <10kg; B: 10.1 - 20kg; C: >20.1kg); then each group was divided into three subgroups according to pregnancy stage (1st: 18 to 30 days; 2nd: 31 to 40 days; 3rd: >40 days) estimated according to the first day of copulation. Ultrasonography was performed weekly from the first stage of pregnancy. In the first and second stage the following formulas were applied: GA = (6XGSD) + 20; DBP = 65 - IG; by Nyland & Matton (2002); GA: gestational age; DBP: days before parturition; DSG: gestational sac diameter; in the third stage: DBP = 61,2 - (24,6 X BD); DBP = 43,5 - (10,9 X CD); by Burk & Ackerman (1996); BD: biparietal diameter; CD: body diameter, and: GA = (15 X BD) + 20; GA = (7 X CD) + 29; GA = (6 X BD) + (3 X CD) + 30; DBP = 65 - GA; by Nyland & Matton (2002). Results were compared statistically. The equations proposed by Nyland & Matton (2002), were more accurate in all pregnancy stages, with a margin of error of only three days, regardless of the size of the animal; therefore these methods are the best option in veterinary practice.

Physical and chemical matrix effects in soil carbon quantification using laser-induced breakdown spectroscopy

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

Periapical Repair Following Endodontic Surgery: Two- andThree-Dimensional Imaging Evaluation Methods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Three-dimensional dental arch changes of patients submitted to orthodontic-surgical treatment for correction of Class II malocclusion

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)