Qualidade do gasto público em educação para os municípios da região metropolitana de Natal-2007

The aim of this thesis is to evaluate the quality of public spending on education for the municipalities of the Metropolitan Region of Natal (RMN) in 2009 by use of two theories: The Theory of Welfare (Welfare State) and the Public Choice Theory (TEP), both important to understand the relationship between education and economics. The study also uses principles of microeconomics and public sector economics to get a better idea of the role of education in economy and society. It describes the development of the educational policy in Brazil from 1988 to the Federal Constitution of 2010, following the major changes in basic education during each government. The characteristics of the RMN municipalities were illustrated with socioeconomic indicators, while educational indicators were used to characterize each municipality regarding education. The model used in this study was developed by Bertê, Brunet and Borges, the data was collected on the back of the School Census 2009 and the Brazil Exam 2009 and it was processed quantitavely in the Information System on Public Budgets in Education (SIOPE) by use of the statistical method called standardized score of the normal cumulative distribution function. The quality of public spending on education is the result of the relation between performance indicator ratio and expense ratio. For the qualitative analysis of results, the criteria of efficiency, efficacy and effectiveness were used. The study found that municipalities with higher expenses showed a worse quality of spending and failed to convert the expenditure incurred into performance, thus confirming ineffectiveness

Um algoritmo para estimação de estado em alimentadores de distribuição de energia elétrica com base no método da soma de potências

Most algorithms for state estimation based on the classical model are just adequate for use in transmission networks. Few algorithms were developed specifically for distribution systems, probably because of the little amount of data available in real time. Most overhead feeders possess just current and voltage measurements at the middle voltage bus-bar at the substation. In this way, classical algorithms are of difficult implementation, even considering off-line acquired data as pseudo-measurements. However, the necessity of automating the operation of distribution networks, mainly in regard to the selectivity of protection systems, as well to implement possibilities of load transfer maneuvers, is changing the network planning policy. In this way, some equipments incorporating telemetry and command modules have been installed in order to improve operational features, and so increasing the amount of measurement data available in real-time in the System Operation Center (SOC). This encourages the development of a state estimator model, involving real-time information and pseudo-measurements of loads, that are built from typical power factors and utilization factors (demand factors) of distribution transformers. This work reports about the development of a new state estimation method, specific for radial distribution systems. The main algorithm of the method is based on the power summation load flow. The estimation is carried out piecewise, section by section of the feeder, going from the substation to the terminal nodes. For each section, a measurement model is built, resulting in a nonlinear overdetermined equations set, whose solution is achieved by the Gaussian normal equation. The estimated variables of a section are used as pseudo-measurements for the next section. In general, a measurement set for a generic section consists of pseudo-measurements of power flows and nodal voltages obtained from the previous section or measurements in real-time, if they exist -, besides pseudomeasurements of injected powers for the power summations, whose functions are the load flow equations, assuming that the network can be represented by its single-phase equivalent. The great advantage of the algorithm is its simplicity and low computational effort. Moreover, the algorithm is very efficient, in regard to the accuracy of the estimated values. Besides the power summation state estimator, this work shows how other algorithms could be adapted to provide state estimation of middle voltage substations and networks, namely Schweppes method and an algorithm based on current proportionality, that is usually adopted for network planning tasks. Both estimators were implemented not only as alternatives for the proposed method, but also looking for getting results that give support for its validation. Once in most cases no power measurement is performed at beginning of the feeder and this is required for implementing the power summation estimations method, a new algorithm for estimating the network variables at the middle voltage bus-bar was also developed

Sistema inteligente para detecção de manchas de óleo na superfície marinha através de imagens de SAR

Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents

Teoria cinética não extensiva: efeitos físicos em gases e plasmas

The standard kinetic theory for a nonrelativistic diluted gas is generalized in the spirit of the nonextensive statistic distribution introduced by Tsallis. The new formalism depends on an arbitrary q parameter measuring the degree of nonextensivity. In the limit q = 1, the extensive Maxwell-Boltzmann theory is recovered. Starting from a purely kinetic deduction of the velocity q-distribution function, the Boltzmann H-teorem is generalized for including the possibility of nonextensive out of equilibrium effects. Based on this investigation, it is proved that Tsallis' distribution is the necessary and sufficient condition defining a thermodynamic equilibrium state in the nonextensive context. This result follows naturally from the generalized transport equation and also from the extended H-theorem. Two physical applications of the nonextensive effects have been considered. Closed analytic expressions were obtained for the Doppler broadening of spectral lines from an excited gas, as well as, for the dispersion relations describing the eletrostatic oscillations in a diluted electronic plasma. In the later case, a comparison with the experimental results strongly suggests a Tsallis distribution with the q parameter smaller than unity. A complementary study is related to the thermodynamic behavior of a relativistic imperfect simple fluid. Using nonequilibrium thermodynamics, we show how the basic primary variables, namely: the energy momentum tensor, the particle and entropy fluxes depend on the several dissipative processes present in the fluid. The temperature variation law for this moving imperfect fluid is also obtained, and the Eckart and Landau-Lifshitz formulations are recovered as particular cases

Tensor coupling and pseudospin symmetry in nuclei

In this work we study the contribution of the isoscalar tensor coupling to the realization of pseudospin symmetry in nuclei. Using realistic values for the tensor coupling strength, we show that this coupling reduces noticeably the pseudospin splittings, especially for single-particle levels near the Fermi surface. By using an energy. decomposition of the pseudospin energy splittings, we show that the changes in these splittings come mainly through the changes induced in the lower radial wave function for the low-lying pseudospin partners and through changes in the expectation value of the pseudospin-orbit coupling term for surface partners. This allows us to confirm the conclusion already reached in previous studies, namely that the pseudospin symmetry in nuclei is of a dynamical nature.

A DOE based approach for the design of RBF artificial neural networks applied to prediction of surface roughness in AISI 52100 hardened Steel turning

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Algoritmos evolutivos dedicados à reconfiguração de redes radiais de distribuição sob demandas fixas e variáveis: estudo dos operadores genéticos e parâmetros de controle

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

Modeling the dielectric response of lanthanum modified lead zirconate titanate ferroelectric ceramics-an approach to the phase transitions in relaxor ferroelectrics

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

Classificador neural híbrido para imagens obtidas por sensoriamento remoto

Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results.

Artificial neural networks: A novel approach to analysing the nutritional ecology of a blowfly species, Chrysomya megacephala

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

Pion structure in the instanton liquid model

The covariant quark model of the pion based on the effective nonlocal quark-hadron Lagrangian involving nonlocality induced by instanton fluctuations of the QCD vacuum is reviewed. Explicit gauge invariant formalism allows us to construct the conserved vector and axial currents and to demonstrate their consistency with the Ward-Takahashi identities and low-energy theorems. The spontaneous breaking of chiral symmetry results in the dynamic quark mass and the vertex of the quark-pion interaction, both momentum-dependent. The parameters of the instanton vacuum, the average size of the instantons, and the effective quark mass are expressed in terms of the vacuum expectation values of the lowest dimension quark-gluon operators and low-energy pion observables. The transition pion form factor for the processes gamma*gamma --> pi (0) and gamma*gamma* --> pi (0) is analyzed in detail. The kinematic dependence of the transition form factor at high momentum transfers allows one to determine the relationship between the light-cone amplitude of the quark distribution in the pion and the quark-pion vertex function. Its dynamic dependence implies that the transition form factor gamma*gamma --> pi (0) at high momentum transfers is acutely sensitive to the size of the nonlocality of nonperturbative fluctuations in the QCD vacuum. In the leading twist, the distribution amplitude and the distribution function of the valence quarks in the pion are calculated at a low normalization point of the order of the inverse average instanton size rho (-1)(c). The QCD results are evolved to higher momentum transfers and are in reasonable agreement with available experimental data on the pion structure.

Dynamics of Bose-Einstein condensates in cigar-shaped traps

The Gross-Pitaevskii equation for a Bose-Einstein condensate confined in an elongated cigar-shaped trap is reduced to an effective system of nonlinear equations depending on only one space coordinate along the trap axis. The radial distribution of the condensate density and its radial velocity are approximated by Gaussian functions with real and imaginary exponents, respectively, with parameters depending on the axial coordinate and time. The effective one-dimensional system is applied to a description of the ground state of the condensate, to dark and bright solitons, to the sound and radial compression waves propagating in a dense condensate, and to weakly nonlinear waves in repulsive condensate. In the low-density limit our results reproduce the known formulas. In the high-density case our description of solitons goes beyond the standard approach based on the nonlinear Schrodinger equation. The dispersion relations for the sound and radial compression waves are obtained in a wide region of values of the condensate density. The Korteweg-de Vries equation for weakly nonlinear waves is derived and the existence of bright solitons on a constant background is predicted for a dense enough condensate with a repulsive interaction between the atoms.

Measurement of the muon charge asymmetry from W boson decays

We present a measurement of the muon charge asymmetry from W boson decays using 0.3 fb(-1) of data collected at root s =1.96 GeV between 2002 and 2004 with the D0 detector at the Fermilab Tevatron (p) over bar Collider. We compare our findings with expectations from next-to-leading-order calculations performed using the CTEQ6.1M and MRST04 NLO parton distribution functions. Our findings can be used to constrain future parton distribution function fits.

Linking the hydrodynamic and kinetic description of a dissipative relativistic conformal theory

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

Sol phase and sol-gel transition in SnO2 colloidal suspensions

The effect of concentration on the structure of SnO2 colloids in aqueous suspension, on their spatial correlation and on the gelation process was studied by small angle x-ray scattering (SAXS). The shape of the experimental SAXS curves varies with suspension concentration. For diluted suspensions ([SnO2] less than or equal to 0.13 mol L-1), SAXS results indicate the presence of colloidal fractal aggregates with an internal correlation length xi congruent to 20 Angstrom, without any noticeable spatial correlation between them. This suggests that the aggregates are spatially arranged without any significant interaction like in ideal gas structures. For higher concentrations ([SnO2] = 0.16, 0.32, and 0.64 mol L-1), the colloidal aggregates are larger (xi = 24 Angstrom) and exhibit a certain degree of spatial correlation between them. The pair correlation function corresponding to the sol with the highest concentration (0.92 mol L-1) reveals a rather strong short range order between aggregates, characteristic of a fluid-like structure, with an average nearest-neighbor distance between aggregates d(1) = 125 Angstrom and an average second-neighbor distance d(2) = 283 Angstrom. The pair distribution function remains essentially invariant during the sol-gel transition, suggesting that gelation involves the formation of a few points of connection between the aggregates resulting in a gel network constituted by essentially linear chains of clusters..