Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

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

Object-Space Road Extraction in Rural Areas Using Stereoscopic Aerial Images

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

Three-Dimensional Semiautomatic Road Extraction From a High-Resolution Aerial Image by Dynamic-Programming Optimization in the Object Space

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

Supercritical fluid extraction for pesticide multiresidue analysis in honey: determination by gas chromatography with electron-capture and mass spectrometry detection

An analytical procedure using supercritical fluid extraction (SFE) and capillary gas chromatography with electron-capture detection was developed to determine simultaneously residues of different pesticides (organochlorine, organophosphorus, organonitrogen and pyrethroid) in honey samples. Fortification experiments were conducted to test conventional extraction (liquid-liquid) and optimize the extraction procedure in SFE by varying the CO2-modifier, temperature, extraction time and pressure. Best efficiency was achieved at 400 bar using acetonitrile as modifier at 90 degreesC. For the clean-up step, Florisil cartridges were used for both methods LLE and SFE. Recoveries for majority of pesticides from fortified samples of honey at fortification level of 0.01-0.10 mg/kg ranged 75-94% from both methods. Limits of detection found were less than 0.01 mg/kg for ECD and confirmation of pesticide identity was performed by gas chromatography-mass spectrometry in selected-ion monitoring mode. The multiresidue methods in real honey samples were applied and the results of developed methods were compared. (C) 2004 Elsevier B.V. All rights reserved.

Multiresidue analysis of pesticides in soil by supercritical fluid extraction/gas chromatography with electron-capture detection and confirmation by gas chromatography-mass spectrometry

The applicability of supercritical fluid extraction (SFE) in pesticide multiresidue analysis (organohalogen, organonitrogen, organophosphorus, and pyrethroid) in soil samples was investigated. Fortification experiments were conducted to test the conventional extraction (solid-liquid) and to optimize the extraction procedure in SFE by varying the CO2 Modifier, temperature, extraction time, and pressure. The best efficiency was achieved at 400 bar using methanol as modifier at 60 degreesC. For the SFE method, C-18 cartridges were used for the cleanup. The analytical screening was performed by gas chromatography equipped with electron-capture detection (ECD). Recoveries for the majority of pesticides from spiked samples of soil at different residence times were 1, 20, and 40 days at the fortification level of 0.04-0.10 mg/kg ranging from 70 to 97% for both methods. The detection limits found were <0.01 mg/kg for ECD, and the confirmation of pesticide identity was performed by gas chromatography-mass spectrometry in a selected-ion monitoring mode. Multiresidue methods were applied in real soil samples, and the results of the methods developed were compared.

A Proposal for System Performance Evaluation for an ERP Knowledge Extraction Model

Much has been researched and discussed in the importance played by knowledge in organizations. We are witnessing the establishment of the knowledge economy, but this "new economy" brings in itself a whole complex system of metrics and evaluations, and cannot be dissociated from it. Due to its importance, the initiatives of knowledge management must be continually assessed on their progress in order to verify whether they are moving towards achieving the goals of success. Thus, good measurement practices should include not only how the organization quantifies its knowledge capital, but also how resources are allocated to supply their growth. Thinking about the aspects listed above, this paper presents an approach to a model for Knowledge extraction using an ERP system, suggesting the establishment of a set of indicators for assessing organizational performance. The objective is to evaluate the implementation of projects of knowledge management and thus observe the general development of the organization.

CENSUS HISTOGRAMS: A SIMPLE FEATURE EXTRACTION and MATCHING APPROACH FOR FACE RECOGNITION

Most face recognition approaches require a prior training where a given distribution of faces is assumed to further predict the identity of test faces. Such an approach may experience difficulty in identifying faces belonging to distributions different from the one provided during the training. A face recognition technique that performs well regardless of training is, therefore, interesting to consider as a basis of more sophisticated methods. In this work, the Census Transform is applied to describe the faces. Based on a scanning window which extracts local histograms of Census Features, we present a method that directly matches face samples. With this simple technique, 97.2% of the faces in the FERET fa/fb test were correctly recognized. Despite being an easy test set, we have found no other approaches in literature regarding straight comparisons of faces with such a performance. Also, a window for further improvement is presented. Among other techniques, we demonstrate how the use of SVMs over the Census Histogram representation can increase the recognition performance.

On 3-Parameter Families of Piecewise Smooth Vector Fields in the Plane

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

On line extraction and separation of bendiocarb, methomyl, methylparathion, and pentachlorophenol pesticides from raw milk

A high performance liquid chromatography (HPLC) method for extraction and determination of pesticides from raw milk was developed. The method involves direct injection of raw milk samples on a bovine serum albumin-dimethyl-octyl-silica gel (BSA-Si-Cs) column. The mobile phase 0.05 mol.L-1 phosphate buffer pH6.0 in acetonitrile (70:30 v/v) was employed for extraction and separation of bendiocarb, methylparathion, pentachlorophenol, and methomyl pesticides. The method shows good results of recovery in the pesticides studied, higher than 99.6%.

Off line extraction of phenol from human urine sample with isoamyl alcohol and determination by HPLC

This method has been developed for extraction and determination of phenol in a urine sample by high performance liquid chromatography.After acid hydrolysis, the free phenol was extracted with isoamyl alcohol solvent, followed by back extraction with 0.5 mol.L-1 sodium hydroxide solution and analyzed by an isocratic HPLC Varian System, equipped with reverse-phase column (MicroPak-C-18). The mobile phase was acetonitrile in 0.01 mol.L-1 hydrochloric acid solution, (20:80 v/v), and at a now-rate of 1.0 mL.min-1. The chromatogram was monitored at 220 nm in room temperature. The identification was based on retention time and the quantification was performed by automatic peak-area determination, corrected for the external standards method.The recovery was higher than 99.5 % for phenol and reproducibility of method was shown to be 2.3% standard deviation and 5.6% coefficient of variance (n=20). The limit detection was 0.05 mgL(-1) and a range of 0.05 to 20.0 mgL(-1) of phenol for linearity.

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.

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.

Variable parameter and double sampling (X)over-bar charts in the presence of correlation: The Markov chain approach

The general assumption under which the (X) over bar chart is designed is that the process mean has a constant in-control value. However, there are situations in which the process mean wanders. When it wanders according to a first-order autoregressive (AR (1)) model, a complex approach involving Markov chains and integral equation methods is used to evaluate the properties of the (X) over bar chart. In this paper, we propose the use of a pure Markov chain approach to study the performance of the (X) over bar chart. The performance of the chat (X) over bar with variable parameters and the (X) over bar with double sampling are compared. (C) 2011 Elsevier B.V. All rights reserved.

Parameter-dependent Lyapunov functions for state-derivative feedback control in polytopic linear systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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.