Metaheurística particle swarm utilizada para alocação ótima de bancos de capacitores em sistemas de distribuição radial

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A intermediação da noção de probabilidade na construção de conceitos relacionados à cinética química

Este trabalho procurou identificar como estudantes do Ensino Médio se apropriam de conceitos e elaboram determinados modelos inseridos em cinética química, especificamente o modelo cinético de colisão de partículas numa reação (Teoria das Colisões). Esta análise e as reflexões que a seguiram foram baseadas, sobretudo, nos estudos realizados por Piaget, Piaget e Inhelder, Jun e Fischbein. Utilizamos como documentos as transcrições das entrevistas (pré e pós-testes) realizadas individualmente com cada aluno. Inicialmente, os estudantes foram entrevistados (pré-testes) com o intuito de identificar a familiaridade com a noção de evento probabilístico ou aleatório. Numa segunda etapa (pós-testes), esse conhecimento (ou a ausência parcial/total dele) foi posto à prova numa tentativa de se estabelecerem relações com um conteúdo específico da Química (Teoria das Colisões). Os resultados obtidos apontam para grandes discrepâncias entre o modelo cinético de colisões elaborado pelos estudantes e aquele cientificamente aceito.

Feature selection through gravitational search algorithm

In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are conducted in order to asses the robustness of the proposed technique against Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and a Particle Swarm Optimization (PSO)-based algorithm for feature selection.

Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm

This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The results are compared with bio-inspired methods, and rule induction and decision tree algorithms for data mining. © 2009 Springer Berlin Heidelberg.

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.

Numerical simulation of magnetic field enhanced plasma immersion ion implantation

The behavior of plasma and sheath characteristics under the action of an applied magnetic field is important in many applications including plasma probes and material processing. Plasma immersion ion implantation (PIII) has been developed as a fast and efficient surface modification technique of complex shaped three-dimensional objects. The PIII process relies on the acceleration of ions across a high-voltage plasma sheath that develops around the target. Recent studies have shown that the sheath dynamics is significantly affected by an external magnetic field. In this work we describe a two-dimensional computer simulation of magnetic field enhanced plasma immersion implantation system. Negative bias voltage is applied to a cylindrical target located on the axis of a grounded cylindrical vacuum chamber filled with uniform nitrogen plasma. An axial magnetic field is created by a solenoid installed inside the cylindrical target. The computer code employs the Monte Carlo method for collision of electrons and neutrals in the plasma and a particle-in-cell (PIC) algorithm for simulating the movement of charged particles in the electromagnetic field. Secondary electron emission from the target subjected to ion bombardment is also included. It is found that a high-density plasma region is formed around the cylindrical target due to the intense background gas ionization by the magnetized electrons drifting in the crossed ExB fields. An increase of implantation current density in front of high density plasma region is observed. (C) 2007 Elsevier B.V. All rights reserved.

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

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

Search for scalar leptoquarks and T-odd quarks in the acoplanar jet topology using 2.5 fb(-1) of p(p)over-bar collision data at root s=1.96 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

SPH simulations of clumps formation by dissipative collision of molecular clouds - I. Non magnetic case

Computer experiments of interstellar cloud collisions were performed with a new smoothed-particle-hydrodynamics (SPH) code. The SPH quantities were calculated by using spatially adaptive smoothing lengths and the SPH fluid equations of motion were solved by means of a hierarchical multiple time-scale leapfrog. Such a combination of methods allows the code to deal with a large range of hydrodynamic quantities. A careful treatment of gas cooling by H, H(2), CO and H II, as well as a heating mechanism by cosmic rays and by H(2) production on grains surface, were also included in the code. The gas model reproduces approximately the typical environment of dark molecular clouds. The experiments were performed by impinging two dynamically identical spherical clouds onto each other with a relative velocity of 10 km s(-1) but with a different impact parameter for each case. Each object has an initial density profile obeying an r(-1)-law with a cutoff radius of 10 pc and with an initial temperature of 20 K. As a main result, cloud-cloud collision triggers fragmentation but in expense of a large amount of energy dissipated, which occurred in the head-on case only. Off-center collision did not allow remnants to fragment along the considered time (similar to 6 Myr). However, it dissipated a considerable amount of orbital energy. Structures as small as 0.1 pc, with densities of similar to 10(4) cm(-3), were observed in the more energetic collision.

The thermohydrodynamical picture of a charged Brownian particle

We study a charged Brownian gas with a non uniform bath temperature, and present a thermohydrodynamical picture. Expansion on the collision time probes the validity of the local equilibrium approach and the relevant thermodynamical variables. For the linear regime we present several applications (some novel).

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Collision and Stable Regions around Bodies with Simple Geometric Shape

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

Photon-induced multiple particle emissions of Zr90 and natZr from 10 to 140 MeV

A comprehensive analysis of electrodisintegration yields of protons on Zr90 is proposed taking into account the giant dipole resonance, isovector giant quadrupole resonance (IVGQR), and quasideuteron contributions to the total photoabsorption cross section from 10 to 140 MeV. The calculation applies the MCMC intranuclear cascade to address the direct and pre-equilibrium emissions and another Monte Carlo-based algorithm to describe the evaporation step. The final results of the total photoabsorption cross section for Zr90 and relevant decay channels are obtained by fitting the (e,p) measurements from the National Bureau of Standards and show that multiple proton emissions dominate the photonuclear reactions at higher energies. These results provide a consistent explanation for the exotic and steady increase of the (e,p) yield and also a strong evidence of a IVGQR with a strength parameter compatible with the E2 energy-weighted sum rule. The inclusive photoneutron cross sections for Zr90 and natZr, derived from these results and normalized with the (e,p) data, are in agreement within 10% with both Livermore and Saclay data up to 140 MeV. © 2007 The American Physical Society.

Multiple particle and cluster emissions from Zr following intermediate energies photo absorption

A new approach based on a N-a cluster photoabsorption model is proposed for the understanding of the puzzling steady increase behavior of the 90Zr (e, α) yield measured at the National Bureau of Standards (NBS) within the Giant Dipole Resonance and quasideuteron energy range. The calculation takes into account the pre-equilibrium emissions of protons, neutrons and alpha particles in the framework of an extended version of the multicollisional intranuclear cascade model (MCMC). Another Monte Carlo based algorithm describes the statistical decay of the compound nucleus in terms of the competition between particle evaporation (p, n, d, α, 3He and t) and nuclear fission. The results reproduce quite successfully the 90Zr (e,α) yield, suggesting that emissions of a particles are essential for the interpretation of the exotic increase of the cross sections.

Charged particle transverse momentum spectra in pp collisions at √s = 0:9 and 7 TeV

The charged particle transverse momentum (pT) spectra are presented for pp collisions at √s = 0:9 and 7TeV. The data samples were collected with the CMS detector at the LHC and correspond to integrated luminosities of 231 μb-1 and 2.96 pb-1, respectively. Calorimeter-based high-transverse-energy triggers are employed to enhance the statistical reach of the high-pT measurements. The results are compared with leading and next-toleading order QCD and with an empirical scaling of measurements at different collision energies using the scaling variable xT - 2pT=ps over the pT range up to 136 GeV/c. Using a combination of xT scaling and direct interpolation at fixed pT, a reference transverse momentum spectrum at √s = 2:76TeV is constructed, which can be used for studying high-pT particle suppression in the dense QCD medium produced in heavy-ion collisions at that centre-of-mass energy. Copyright CERN.