Defects location in power systems components through a dedicated genetic algorithm

In this work the problem of defects location in power systems is formulated through a binary linear programming (BLP) model based on alarms historical database of control and protection devices from the system control center, sets theory of minimal coverage (AI) and protection philosophy adopted by the electric utility. In this model, circuit breaker operations are compared to their expected states in a strictly mathematical manner. For solving this BLP problem, which presents a great number of decision variables, a dedicated Genetic Algorithm (GA), is proposed. Control parameters of the GA, such as crossing over and mutation rates, population size, iterations number and population diversification, are calibrated in order to obtain efficiency and robustness. Results for a test system found in literature, are presented and discussed. © 2004 IEEE.

Soil sampling intensity and spatial distribution pattern of soils attributes and corn yield in no-tillage system

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

Deriving the magnitude of niobium off-center displacement in ferroelectric niobates from infrared spectroscopy

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reversibility properties of semigroup actions on homogeneous spaces

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

MICROBIOLOGICAL CONTAMINATION of A HEMODIALYSIS CENTER WATER DISTRIBUTION SYSTEM

The microbiological monitoring of the water used for hemodialysis is extremely important, especially because of the debilitated immune system of patients suffering from chronic renal insufficiency. To investigate the occurrence and species diversity of bacteria in waters, water samples were collected monthly from a hemodialysis center in upstate São Paulo and tap water samples at the terminal sites of the distribution system was sampled repeatedly (22 times) at each of five points in the distribution system; a further 36 samples were taken from cannulae in 19 hemodialysis machines that were ready for the next patient, four samples from the reuse system and 13 from the water storage system. To identify bacteria, samples were filtered through 0.22 mu m-pore membranes; for mycobacteria, 0.45 mu m pores were used. Conventional microbiological and molecular methods were used in the analysis. Bacteria were isolated from the distribution system (128 isolates), kidney machine water (43) and reuse system (3). Among these isolates, 32 were Gram-positive rods, 120 Gram-negative rods, 20 Gram-positive cocci and 11 mycobacteria. We propose the continual monitoring of the water supplies in hemodialysis centers and the adoption of effective prophylactic measures that minimize the exposure of these immunodeficient patients to contaminated sources of water.

Classic and molecular study of Giardia duodenalis in children from a daycare center in the region of Presidente Prudente, São Paulo, Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Projections Onto Convex Sets through Particle Swarm Optimization and its application for remote sensing image restoration

Image restoration attempts to enhance images corrupted by noise and blurring effects. Iterative approaches can better control the restoration algorithm in order to find a compromise of restoring high details in smoothed regions without increasing the noise. Techniques based on Projections Onto Convex Sets (POCS) have been extensively used in the context of image restoration by projecting the solution onto hyperspaces until some convergence criteria be reached. It is expected that an enhanced image can be obtained at the final of an unknown number of projections. The number of convex sets and its combinations allow designing several image restoration algorithms based on POCS. Here, we address two convex sets: Row-Action Projections (RAP) and Limited Amplitude (LA). Although RAP and LA have already been used in image restoration domain, the former has a relaxation parameter (A) that strongly depends on the characteristics of the image that will be restored, i.e., wrong values of A can lead to poorly restoration results. In this paper, we proposed a hybrid Particle Swarm Optimization (PS0)-POCS image restoration algorithm, in which the A value is obtained by PSO to be further used to restore images by POCS approach. Results showed that the proposed PSO-based restoration algorithm outperformed the widely used Wiener and Richardson-Lucy image restoration algorithms. (C) 2010 Elsevier B.V. All rights reserved.

Prolapse-free relativistic Gaussian basis sets for the superheavy elements up to Uuo (Z=118) and Lr (Z=103)

Prolapse-free basis sets suitable for four-component relativistic quantum chemical calculations are presented for the superheavy elements UP to (118)Uuo ((104)Rf, (105)Db, (106)Sg, (107)Bh, (108)Hs, (109)Mt, (110)Ds, (111)Rg, (112)Uub, (113)Uut, (114)Uuq, (115)Uup, (116)Uuh, (117)Uus, (118)Uuo) and Lr-103. These basis sets were optimized by minimizing the absolute values of the energy difference between the Dirac-Fock-Roothaan total energy and the corresponding numerical value at a milli-Hartree order of magnitude, resulting in a good balance between cost and accuracy. Parameters for generating exponents and new numerical data for some superheavy elements are also presented. (c) 2007 Elsevier B.V. All rights reserved.

Assessment of liquid disposal originated by uranium enrichment at Aramar Experimental Center São Paulo-Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Synthesis and characterization of mono and polymeric cyclopalladated compounds: Crystal and molecular structure of [{Pd(dmba)(ONO2)}(2)(mu-pz)] center dot H2O (pz = pyrazine)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A neural system to robust Nonlinear optimization subject to disjoint and constrained sets

The ability of neural networks to realize some complex nonlinear function makes them attractive for system identification. This paper describes a novel method using artificial neural networks to solve robust parameter estimation problems for nonlinear models 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.

NOVEL CELLULOSE/NbOPO4 center dot nH(2)O HYBRID MATERIAL FROM SUGARCANE BAGASSE

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

Influence of thermal annealing treatment in oxygen atmosphere on grain boundary chemistry and non-ohmic properties of SnO2 center dot MnO polycrystalline semiconductors

The present work studied the influence of thermal treatment in oxygen rich atmosphere on heterogenous junctions in Mn-doped SnO2 polycrystalline system presenting varistor behavior. The samples were prepared by conventional oxide mixture methodology, and were submitted to heat treatment in oxygen rich atmosphere at 900 degrees C for 2h. The samples were characterized by X-ray diffraction, scanning electron microscopy, dc and ac electrical measurements. The results showed that there is an evident relationship between the microstructure heterogeneity and non-ohmic electrical properties. It was found that for this SnO2 center dot MnO-based varistor system the heat treatment in oxygen rich atmosphere does not necessarily increase the varistors properties, which was related to the decrease in the grain boundary resistance. The results are compared with Co-doped SnO2 varistors and ZnO based varistors. (C) 2008 WILEY-VCH Verlay GmbH & Co. KGaA, Weinheim.

Bifurcation of limit cycles from an n-dimensional linear center inside a class of piecewise linear differential systems

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