Evolutionary optimization applied for fine-tuning parameter estimation in optical flow-based environments

Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work we have proposed an evolutionary-based framework for such task, thus introducing three techniques for such purpose: Particle Swarm Optimization, Harmony Search and Social-Spider Optimization. The proposed framework has been compared against with the well-known Large Displacement Optical Flow approach, obtaining the best results in three out eight image sequences provided by a public dataset. Additionally, the proposed framework can be used with any other optimization technique.

A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

Neural network based estimation of torque in induction motors for real-time applications

Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.

Estimation using 18O of the water residence time in small watersheds

From the 18O hydrograph separation method, it was found that groundwater contribution is the principal component of the total discharge produced by these two catchment areas. The weighted mean of the 18O concentration in the precipitation, obtained for a four year period, was close to -6.0‰, with a variation in range of +2.3‰ to -16.3‰. For Bufalos stream water the weighted mean of 18O values during the same period (1984-1987) was -6.3‰, with a variation from -2.5‰ to -10.1‰, whereas for Paraiso this mean was -6.4‰, with extreme values of -3.1‰ and -9.8‰. From these values it was found that the amplitude damping (Ariver/Aprecipitation) was 0.41 for the Bufalos watershed and 0.36 for Paraiso. Using the appropriate equation to estimate the mean residence time of water in the subsurface reservoir of the Bufalos and Paraiso watersheds, the results of 4.3 and 5.0 months, respectively, were obtained. -from Authors

Bayesian inference in genetic parameter estimation of visual scores in Nellore beef-cattle

The aim of this study was to estimate the components of variance and genetic parameters for the visual scores which constitute the Morphological Evaluation System (MES), such as body structure (S), precocity (P) and musculature (M) in Nellore beef-cattle at the weaning and yearling stages, by using threshold Bayesian models. The information used for this was gleaned from visual scores of 5,407 animals evaluated at the weaning and 2,649 at the yearling stages. The genetic parameters for visual score traits were estimated through two-trait analysis, using the threshold animal model, with Bayesian statistics methodology and MTGSAM (Multiple Trait Gibbs Sampler for Animal Models) threshold software. Heritability estimates for S, P and M were 0.68, 0.65 and 0.62 (at weaning) and 0.44, 0.38 and 0.32 (at the yearling stage), respectively. Heritability estimates for S, P and M were found to be high, and so it is expected that these traits should respond favorably to direct selection. The visual scores evaluated at the weaning and yearling stages might be used in the composition of new selection indexes, as they presented sufficient genetic variability to promote genetic progress in such morphological traits.

Nonlinear parameter estimation in laminar forced convection within a circular sector tube

In this article we examine an inverse heat convection problem of estimating unknown parameters of a parameterized variable boundary heat flux. The physical problem is a hydrodynamically developed, thermally developing, three-dimensional steady state laminar flow of a Newtonian fluid inside a circular sector duct, insulated in the flat walls and subject to unknown wall heat flux at the curved wall. Results are presented for polynomial and sinusoidal trial functions, and the unknown parameters as well as surface heat fluxes are determined. Depending on the nature of the flow, on the position of experimental points the inverse problem sometimes could not be solved. Therefore, an identification condition is defined to specify a condition under which the inverse problem can be solved. Once the parameters have been computed it is possible to obtain the statistical significance of the inverse problem solution. Therefore, approximate confidence bounds based on standard statistical linear procedure, for the estimated parameters, are analyzed and presented.

Real-time monitoring and kinetic parameter estimation of the affinity interaction of jArtinM and rArtinM with peroxidase glycoprotein by the electrogravimetric technique

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

UV filters in water samples: Experimental design on the SPE optimization followed by GC-MS/MS analysis

Esse estudo descreve o desenvolvimento e otimização de um método de extração em fase solida (SPE) para análise dos filtros ultravioletas (UV): benzofenona-3 (BP-3), etilhexil salicilato (ES), etilhexil metoxinamato (EHMC) e octocrileno (OC) em matrizes ambientais. Um planejamento fatorial fracionário (PFF) 25-1 foi empregado na avaliação das variáveis significativas do método de extração. As condições experimentais otimizadas da avaliação estatística foram: capacidade do cartucho de 500 mL, eluente acetato de etila, metanol como solvente de lavagem (10% em água, v/v) and volume do eluente de 3 × 2 mL e pH 3. Os parâmetros analíticos avaliados foram satisfatõrios, apresentando linearidade de 100 a 4000 ng L -1, recuperaç ões para os quatro níveis de fortificação (Limite de Quantificação do Método, 200, 1000 e 2000 ng L-1) entre 62 e 107% com desvio padrão relativo menor que 14%. Os limites de quantificação foram encontrados na faixa de ng L-1, variando entre 10 e 100 ng L-1. O método proposto foi aplicado para a determinação dos quatro filtros UV em amostras de águas naturais. This study describes the development and optimization of a solid-phase extraction (SPE) method for analysis of ultraviolet (UV) filters, benzophenone-3 (BP-3), ethylhexyl methoxycinnamate (EHMC), ethylhexyl salicylate (ES) and octocrylene (OC), in environmental matrices. A 25-1 fractional factorial design (FFD) was used to evaluate the significant variables for the extraction method. The optimized experimental conditions determined from the statistical evaluation were: breakthrough volume of 500 mL, eluent of ethyl acetate, wash solvent of methanol (10% in water, v/v), eluent volume of 3 × 2 mL and pH 3. The evaluated analytical parameters were satisfactory for the analytes and showed linearity between 100 and 4000 ng L-1, recoveries for four fortification levels (Method Quantification Limit, 200, 1000 and 2000 ng L-1) were between 62 and 107% with relative standard deviations less than 14%. Limits of quantification were in the ng L-1 range and were between 10 and 100 ng L-1. The proposed method was used to analyze four UV filters in natural water samples. ©2013 Sociedade Brasileira de Química.

Genetic parameter estimation for pre- and post-weaning traits in Brahman cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A novel approach to robust parameter estimation using neurofuzzy systems

A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its equilibrium points. Simulated examples are presented as an illustration of the proposed technique. The result represent a significant improvement over previously proposed methods. (C) 1999 IMACS/Elsevier B.V. B.V. All rights reserved.

Levenberg-Marquardt application to two-phase nonlinear parameter estimation for finned-tube coil evaporators

A procedure for calculation of refrigerant mass flow rate is implemented in the distributed numerical model to simulate the flow in finned-tube coil dry-expansion evaporators, usually found in refrigeration and air-conditioning systems. Two-phase refrigerant flow inside the tubes is assumed to be one-dimensional, unsteady, and homogeneous. In themodel the effects of refrigerant pressure drop and the moisture condensation from the air flowing over the external surface of the tubes are considered. The results obtained are the distributions of refrigerant velocity, temperature and void fraction, tube-wall temperature, air temperature, and absolute humidity. The finite volume method is used to discretize the governing equations. Additionally, given the operation conditions and the geometric parameters, the model allows the calculation of the refrigerant mass flow rate. The value of mass flow rate is computed using the process of parameter estimation with the minimization method of Levenberg-Marquardt minimization. In order to validate the developed model, the obtained results using HFC-134a as a refrigerant are compared with available data from the literature.

Laboratory essays on solid residues from an area of sand mining activities at Analandia, São Paulo, Brazil, and implications to the water resources quality

This investigation reports the results of tests performed in a laboratory with solid waste samples from an area belonging to Sibelco Mineracao Ltd., which is located around Analandia municipality, nearly in the center of São Paulo State, Brazil. Dissolution and leaching essays were realized under different experimental conditions in four samples collected from the mining front and decantation pool, with the aim of evaluating the possibility of release of several constituents to the liquid phase.

A two phase flow nonlinear parameter estimation for capillary tube-suction line heat exchanger

Here we present two-phase flow nonlinear parameter estimation for HFC's flow through capillary tube-suction line heat exchangers, commonly used as expansion devices in small refrigeration systems. The simplifying assumptions adopted are: steady state, pure refrigerant, one-dimensional flow, negligible axial heat conduction in the fluid, capillary tube and suction line walls. Additionally, it is considered that the refrigerant is free from oil and both phases are assumed to be at the same pressure, that is, surface tension effects are neglected. Metastable flow effects are also disregarded, and the vapor is assumed to be saturated at the local pressure. The so-called homogeneous model, involving three, first order, ordinary differential equations is applied to analyze the two-phase flow region. Comparison is done with experimental measurements of the mass flow rate and temperature distribution along capillary tubes working with refrigerant HFC-134a in different operating conditions.

ENCORE: Enhanced code Galileo receiver for land management applications in Brazil

Taking benefit of the new Galileo ranging signals, the ENCORE (Enhanced Code Galileo Receiver) project aims to develop a low-cost Land Management Application to cover needs of the Brazilian market in terms of geo-referencing and rural/urban cadastre, using a low-cost Enhanced Galileo Code Receiver as baseline. Land management applications require precision and accuracy levels from a few to several decimetres that are under-met with current pseudorange-based receiver and over-met with phase observations. This situation leads either to a waste of resources, or to lack of accuracy. In this project, it is proposed to fill this gap using the new possibilities of the Galileo ranging signals, in particular E5 AltBOC and E1 CBOC. This approach reduces the cost of the end-user solution, helping the rapid penetration of Galileo technology outside Europe. ©2010 IEEE.

Optimum-Path Forest pruning parameter estimation through Harmony Search

Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter. © 2011 IEEE.