An Optimum-Path Forest framework for intrusion detection in computer networks

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

Efficient supervised optimum-path forest classification for large datasets

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

DETERMINATION of SILICON IN LUBRICANT OIL BY HIGH-RESOLUTION CONTINUUM SOURCE FLAME ATOMIC ABSORPTION SPECTROMETRY USING LEAST-SQUARE BACKGROUND CORRECTION and INTERNAL STANDARDIZATION

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

Análise de fatores genéticos e ambientais que afetam a infestação de fêmeas bovinas da raça Caracu por carrapatos (Boophilus microplus)

Este trabalho foi conduzido com o objetivo de avaliar o efeito de fatores de meio sobre a infestação de bovinos Caracu pelo carrapato Boophilus microplus (Canestrini, 1887) e estimar parâmetros genéticos do grau de infestação por esse ectoparasita. Foram realizadas contagens em fêmeas de dois rebanhos, nas quatro estações, por dois anos consecutivos (setembro/1998 a julho/2000). Contou-se o número de carrapatos (NC) em um dos lados do animal e atribuiu-se escore visual (EC) de acordo com a quantidade de carrapatos no animal. Foram feitas de uma a oito avaliações, totalizando-se 4.079 e 3.994 observações de NC e EC, respectivamente, em 718 animais. Os dados foram analisados pelo método dos quadrados mínimos com um modelo que incluiu efeitos de rebanho (R), cor do animal (C), R x C, animal dentro de R x C como erro a, ano e estação da avaliação, espessura de pelame e idade do animal como covariável. As estimativas dos componentes de variância foram obtidas pelo método da máxima verossimilhança restrita livre de derivadas, utilizando-se um modelo que incluiu os efeitos fixos de grupo de contemporâneos (fazenda-ano-época), espessura do pelame e idade do animal como covariável e os efeitos aleatórios aditivos diretos e de ambiente permanente. Antes das análises, a variável NC foi transformada para log10 (n + 1) e EC para (x + 0,5)½, em que n é o número de carrapatos contados no animal e x, o escore (0 a 4). A incidência de carrapatos foi maior no verão e, quanto maior a espessura do pelame, maior o nível de infestação. As estimativas de herdabilidade e repetibilidade foram, respectivamente, 0,22 e 0,29 para NC e 0,15 e 0,21 para EC; a correlação genética entre NC e EC foi igual a 1,00. Os resultados sugerem que é possível obter progresso genético para resistência a carrapato pela seleção.

Robust and fast vowel recognition using optimum-path forest

The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art systems for AVR are based on traditional machine learning models such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), however, such classifiers can not deal with efficiency and effectiveness at the same time, existing a gap to be explored when real-time processing is required. In this work, we present an algorithm for AVR based on the Optimum-Path Forest (OPF), which is an emergent pattern recognition technique recently introduced in literature. Adopting a supervised training procedure and using speech tags from two public datasets, we observed that OPF has outperformed ANNs, SVMs, plus other classifiers, in terms of training time and accuracy. ©2010 IEEE.

New trends in musical genre classification using optimum-path forest

Musical genre classification has been paramount in the last years, mainly in large multimedia datasets, in which new songs and genres can be added at every moment by anyone. In this context, we have seen the growing of musical recommendation systems, which can improve the benefits for several applications, such as social networks and collective musical libraries. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for musical genre classification, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster for some applications. Experiments in two public datasets were conducted against Support Vector Machines and a Bayesian classifier to show the validity of our work. In addition, we have executed an experiment using very recent hybrid feature selection techniques based on OPF to speed up feature extraction process. © 2011 International Society for Music Information Retrieval.

Fast robot voice interface through optimum-path forest

Voice-based user interfaces have been actively pursued aiming to help individuals with motor impairments, providing natural interfaces to communicate with machines. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for voice-based robot interface, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster. Experiments were conducted against Support Vector Machines, Neural Networks and a Bayesian classifier to show the OPF robustness. The proposed architecture provides high accuracy rates allied with low computational times. © 2012 IEEE.

Financial market reaction to central bank monetary policy communications under an inflation- targeting regime: the case of Brazil

Includes bibliography

Estudo comparativo entre as ventilações espontânea, mandatória intermitente sincronizada, pressão de suporte e volume garantido e suporte pressórico, em coelhos anestesiados com propofol e induzidos à hipovolemia aguda

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

Interpretação aeromagnética automática com uso da equação homogênea de Euler e sua aplicação na Bacia do Solimões

ABSTRACT: We present here a methodology for the rapid interpretation of aeromagnetic data in three dimensions. An estimation of the x, y and z coordinates of prismatic elements is obtained through the application of "Euler's Homogeneous equation" to the data. In this application, it is necessary to have only the total magnetic field and its derivatives. These components can be measured or calculated from the total field data. In the use of Euler's Homogeneous equation, the structural index, the coordinates of the corners of the prism and the depth to the top of the prism are unknown vectors. Inversion of the data by classical least-squares methods renders the problem ill-conditioned. However, the inverse problem can be stabilized by the introduction of both a priori information within the parameter vector together with a weighting matrix. The algorithm was tested with synthetic and real data in a low magnetic latitude region and the results were satisfactory. The applicability of the theorem and its ambiguity caused by the lack of information about the direction of total magnetization, inherent in all automatic methods, is also discussed. As an application, an area within the Solimões basin was chosen to test the method. Since 1977, the Solimões basin has become a center of exploration activity, motivated by the first discovery of gas bearing sandstones within the Monte Alegre formation. Since then, seismic investigations and drilling have been carried on in the region. A knowledge of basement structures is of great importance in the location of oil traps and understanding the tectonic history of this region. Through the application of this method a preliminary estimate of the areal distribution and depth of interbasement and sedimentary magnetic sources was obtained.

Interface para classificação de dados por máquinas de vetores de suporte

In this project the Pattern Recognition Problem is approached with the Support Vector Machines (SVM) technique, a binary method of classification that provides the best solution separating the data in the better way with a hiperplan and an extension of the input space dimension, as a Machine Learning solution. The system aims to classify two classes of pixels chosen by the user in the interface in the interest selection phase and in the background selection phase, generating all the data to be used in the LibSVM library, a library that implements the SVM, illustrating the library operation in a casual way. The data provided by the interface is organized in three types, RGB (Red, Green and Blue color system), texture (calculated) or RGB + texture. At last the project showed successful results, where the classification of the image pixels was showed as been from one of the two classes, from the interest selection area or from the background selection area. The simplest user view of results classification is the RGB type of data arrange, because it’s the most concrete way of data acquisition

Programa computacional ODR-ATA para densitometria óssea baseado na densitometria radiografica

Pós-graduação em Ciência Animal - FMVA

Estimativa da irradiação solar global pelo método de Angstrom-Prescott e técnicas de aprendizado de máquinas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Experimental model identification of open-frame underwater vehicles

Most of the works published on hydrodynamic parameter identification of open-frame underwater vehicles focus their attention almost exclusively on good coherence between simulated and measured responses, giving less importance to the determination of “actual values” for hydrodynamic parameters. To gain insight into hydrodynamic parameter experimental identification of open-frame underwater vehicles, an experimental identification procedure is proposed here to determine parameters of uncoupled and coupled models. The identification procedure includes: (i) a prior estimation of actual values of the forces/torques applied to the vehicle, (ii) identification of drag parameters from constant velocity tests and (iii) identification of inertia and coupling parameters from oscillatory tests; at this stage, the estimated values of drag parameter obtained in item (ii) are used. The procedure proposed here was used to identify the hydrodynamic parameters of LAURS—an unmanned underwater vehicle developed at the University of São Paulo. The thruster–thruster and thruster–hull interactions and the advance velocity of the vehicle are shown to have a strong impact on the efficiency of thrusters appended to open-frame underwater vehicles, especially for high advance velocities. Results of tests with excitation in 1-DOF and 3-DOF are reported and discussed, showing the feasibility of the developed procedure.

A generalization of the Moore-Penrose inverse related to matrix subspaces of C(nxm)

[EN]A natural generalization of the classical Moore-Penrose inverse is presented. The so-called S-Moore-Penrose inverse of a m x n complex matrix A, denoted by As, is defined for any linear subspace S of the matrix vector space Cnxm. The S-Moore-Penrose inverse As is characterized using either the singular value decomposition or (for the nonsingular square case) the orthogonal complements with respect to the Frobenius inner product. These results are applied to the preconditioning of linear systems based on Frobenius norm minimization and to the linearly constrained linear least squares problem.