Estimador do Tipo Núcleo para Densidades Limites de Cadeias de Markov com Espaço de Estados Geral

In this work we studied the consistency for a class of kernel estimates of f f (.) in the Markov chains with general state space E C Rd case. This study is divided into two parts: In the first one f (.) is a stationary density of the chain, and in the second one f (x) v (dx) is the limit distribution of a geometrically ergodic chain

Estimativas de mortalidade para a região nordeste do Brasil em 2010: uma associação do método demográfico equação geral de balanceamento, com o estimador bayesiano empírico

One of the greatest challenges of demography, nowadays, is to obtain estimates of mortality, in a consistent manner, mainly in small areas. The lack of this information, hinders public health actions and leads to impairment of quality of classification of deaths, generating concern on the part of demographers and epidemiologists in obtaining reliable statistics of mortality in the country. In this context, the objective of this work is to obtain estimates of deaths adjustment factors for correction of adult mortality, by States, meso-regions and age groups in the northeastern region, in 2010. The proposal is based on two lines of observation: a demographic one and a statistical one, considering also two areas of coverage in the States of the Northeast region, the meso-regions, as larger areas and counties, as small areas. The methodological principle is to use the General Equation and Balancing demographic method or General Growth Balance to correct the observed deaths, in larger areas (meso-regions) of the states, since they are less prone to breakage of methodological assumptions. In the sequence, it will be applied the statistical empirical Bayesian estimator method, considering as sum of deaths in the meso-regions, the death value corrected by the demographic method, and as reference of observation of smaller area, the observed deaths in small areas (counties). As results of this combination, a smoothing effect on the degree of coverage of deaths is obtained, due to the association with the empirical Bayesian Estimator, and the possibility of evaluating the degree of coverage of deaths by age groups at counties, meso-regions and states levels, with the advantage of estimete adjustment factors, according to the desired level of aggregation. The results grouped by State, point to a significant improvement of the degree of coverage of deaths, according to the combination of the methods with values above 80%. Alagoas (0.88), Bahia (0.90), Ceará (0.90), Maranhão (0.84), Paraíba (0.88), Pernambuco (0.93), Piauí (0.85), Rio Grande do Norte (0.89) and Sergipe (0.92). Advances in the control of the registry information in the health system, linked to improvements in socioeconomic conditions and urbanization of the counties, in the last decade, provided a better quality of information registry of deaths in small areas

Um estimador de estado trifásico para sistemas de distribuição de energia elétrica com base no método da soma de potências

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Controle vetorial para velocidade de um motor de indução trifásico utilizando estimador filtro de Kalman

This paper describes the study, computer simulation and feasibility of implementation of vector control speed of an induction motor using for this purpose the Extended Kalman Filter as an estimator of rotor flux. The motivation for such work is the use of a control system that requires no sensors on the machine shaft, thus providing a considerable cost reduction of drives and their maintenance, increased reliability, robustness and noise immunity as compared to control systems with conventional sensors

Não vício assintótico, consistência forte e uniformemente forte de estimadores do tipo núcleo para dados direcionais sobre uma esfera unitária k-dimensional

In this work we studied the asymptotic unbiasedness, the strong and the uniform strong consistencies of a class of kernel estimators fn as an estimator of the density function f taking values on a k-dimensional sphere

Estimadores do tipo núcleo para a densidade de transição de uma cadeia de markov com espaço de estados geral

In this work, we studied the strong consistency for a class of estimates for a transition density of a Markov chain with general state space E ⊂ Rd. The strong ergodicity of the estimates for the density transition is obtained from the strong consistency of the kernel estimates for both the marginal density p(:) of the chain and the joint density q(., .). In this work the Markov chain is supposed to be homogeneous, uniformly ergodic and possessing a stationary density p(.,.)

Processo de implantação de um sistema integrado de gestão em uma organização pública à luz da teoria da hospitalidade :um estudo de caso

In the present time, public organizations are employing more and more solutions that uses information technology in order to ofer more transparency and better services for all citizens. Integrated Systems are IT which carry in their kernel features of integration and the use of a unique database. These systems bring several benefits and face some obstacles that make their adoption difficult. The conversion to a integrated system may take years and, thus, the study of the adoption of this IT in public sector organizations become very stimulant due to some peculiarities of this sector and the features of this technology. First of all, information about the particular integrated system in study and about its process of conversion are offered. Then, the researcher designs the configuration of the conversion process aim of this study the agents envolved and the moments and the tools used to support the process in order to elaborate the methodology of the conversion process understood as the set of procedures and tools used during all the conversion process. After this, the researcher points out, together with all the members of the conversion team, the negative and positive factors during the project. Finally, these factors were analysed through the Hospitality Theory lens which, in the researcher opinion, was very useful to understand the elements, events and moments that interfered in the project. The results consolidated empirically the Hospitality Theory presumptions, showing yet a limitation of this theory in the case in study

Avaliação do potencial genotóxico e citotóxico associado a queima artesanal da castanha de caju no Município de João Câmara

The Brazil is the third largest producer of cashew nuts in the world. Despite the social and economic importance of the cashew nut, its production is still carried out artisanally. One of the main problems encountered in the cashew production chain are the conditions under which the roasting of the nut occurs to obtain the kernel from the shell. In the present study was conducted a biomonitoring of the genotoxic and cytotoxicity effects associated with the elements from the cashew nut roasting in João Câmara - RN, semi-arid region of Brazil. To assess the genotoxic was used the bioassay of micronucleus (MN) in Tradescantia pallida. In addition, it was performed a comparative between the Tradescantia pallida and KU-20 and other biomarkers of DNA damage, such as the nucleoplasmic bridges (NBP) and nuclear fragments (NF) were quantified. The levels of particulate matter (PM1.0, PM2.5, PM10) and black carbon (BC) were also measured and the inorganic chemical composition of the PM2.5 collected was determined using X-ray fluorescence spectrometry analysis and the assessment of the cytotoxicity by MTT assay and exclusion method by trypan blue. . For this purpose, were chosen: the Amarelão community where the roasting occurs and the Santa Luzia farm an area without influence of this process. The mean value of PM2.5 (Jan 2124.2 μg/m3; May 1022.2 μg/m3; Sep 1291.9 μg/m3) and BC (Jan 363.6 μg/m3; May 70.0 μg/m3; Sep 69.4 μg/m3) as well as the concentration of the elements Al, Si, P, S, Cl, K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Se, Br and Pb obtained at Amarelão was significantly higher than at Santa Luzia farm. The genotoxicity tests with T. pallida indicated a significant increase in the number of MN, NBP and NF and it was found a negative correlation between the frequency of these biomarkers and the rainfall. The concentrations of 200 μg/mL and 400 μg/mL of PM2.5 were cytotoxic to MRC-5 cells. All together, the results indicated genotoxicity and citotoxicity for the community of Amarelão, and the high rates of PM2.5 considered a potential contributor to this effect, mainly by the high presence of transition metals, especially Fe, Ni, Cu, Cr and Zn, these elements have the potential to cause DNA damage. Other nuclear alterations, such as the NPBs and NFs may be used as effective biomarkers of DNA damage in tetrads of Tradescantia pallida. The results of this study enabled the identification of a serious occupational problem. Accordingly, preventative measures and better practices should be adopted to improve both the activity and the quality of life of the population. These measures are of fundamental importance for the sustainable development of this activity.

Avaliação dos impactos do programa bolsa família na renda, na educação e no mercado de trabalho das famílias pobres do Brasil

This study aims to verify the impact of the Bolsa Família Program (BFP) in income and school attendance of poor Brazilian families. It is intended to also check the existence of a possible negative effect of the program on the labor market, titled as sloth effect. For such, microdata from the IBGE Census sample in 2010 were used. Seeking to purge possible selection biases, methodology of Quantilic Treatment Effect (QTE) was applied, in particular the estimator proposed by Firpo (2007), which assumes an exogenous and non-conditional treatment. Moreover, Foster- Greer-Thorbecke (FGT) index was calculated to check if there are fewer households below the poverty line, as well as if the inequality among the poor decreases. Human Opportunity Index (HOI) was also calculated to measure the access of young people / children education. Results showed that BFP has positively influenced the family per capita income and education (number of children aged 5-17 years old attending school). As for the labor market (worked hours and labor income), the program showed a negative effect. Thus, when compared with not benefiting families, those families who receive the BFP have: a) a higher family income (due to the shock of the transfer budget money) b) more children attending school (due to the conditionality imposed by the program); c) less worked hours (due to sloth effect in certain family groups) and d) a lower income from work. All these effects were potentiated separating the sample in the five Brazilian regions, being observed that the BFP strongly influenced the Northeast, showing a greater decrease in income inequality and poverty, and at the same time, achieved a greater negative impact on the labor market

Controle vetorial de velocidade de uma máquina de indução sem mancais trifásica com bobinado dividido utilizando estimação neural de fluxo

This work describes the study and the implementation of the vector speed control for a three-phase Bearingless induction machine with divided winding of 4 poles and 1,1 kW using the neural rotor flux estimation. The vector speed control operates together with the radial positioning controllers and with the winding currents controllers of the stator phases. For the radial positioning, the forces controlled by the internal machine magnetic fields are used. For the radial forces optimization , a special rotor winding with independent circuits which allows a low rotational torque influence was used. The neural flux estimation applied to the vector speed controls has the objective of compensating the parameter dependences of the conventional estimators in relation to the parameter machine s variations due to the temperature increases or due to the rotor magnetic saturation. The implemented control system allows a direct comparison between the respective responses of the speed and radial positioning controllers to the machine oriented by the neural rotor flux estimator in relation to the conventional flux estimator. All the system control is executed by a program developed in the ANSI C language. The DSP resources used by the system are: the Analog/Digital channels converters, the PWM outputs and the parallel and RS-232 serial interfaces, which are responsible, respectively, by the DSP programming and the data capture through the supervisory system

Classificação de imagens de ambientes coralinos: uma abordagem empregando uma combinação de classificadores e máquina de vetor de suporte

The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column

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

Controle vetorial de velocidade de um motor de indução trifásico com estimação neural de fluxo

This work describes the study and the implementation of the speed control for a three-phase induction motor of 1,1 kW and 4 poles using the neural rotor flux estimation. The vector speed control operates together with the winding currents controller of the stator phasis. The neural flux estimation applied to the vector speed controls has the objective of compensating the parameter dependences of the conventional estimators in relation to the parameter machine s variations due to the temperature increases or due to the rotor magnetic saturation. The implemented control system allows a direct comparison between the respective responses of the speed controls to the machine oriented by the neural rotor flux estimator in relation to the conventional flux estimator. All the system control is executed by a program developed in the ANSI C language. The main DSP recources used by the system are, respectively, the Analog/Digital channels converters, the PWM outputs and the parallel and RS-232 serial interfaces, which are responsible, respectively, by the DSP programming and the data capture through the supervisory system

Modelagem e controle de um microveículo aéreo: uma aplicação de estabilidade robusta com a técnica backstepping em uma estrutura hexarrotor

In this Thesis, the development of the dynamic model of multirotor unmanned aerial vehicle with vertical takeoff and landing characteristics, considering input nonlinearities and a full state robust backstepping controller are presented. The dynamic model is expressed using the Newton-Euler laws, aiming to obtain a better mathematical representation of the mechanical system for system analysis and control design, not only when it is hovering, but also when it is taking-off, or landing, or flying to perform a task. The input nonlinearities are the deadzone and saturation, where the gravitational effect and the inherent physical constrains of the rotors are related and addressed. The experimental multirotor aerial vehicle is equipped with an inertial measurement unit and a sonar sensor, which appropriately provides measurements of attitude and altitude. A real-time attitude estimation scheme based on the extended Kalman filter using quaternions was developed. Then, for robustness analysis, sensors were modeled as the ideal value with addition of an unknown bias and unknown white noise. The bounded robust attitude/altitude controller were derived based on globally uniformly practically asymptotically stable for real systems, that remains globally uniformly asymptotically stable if and only if their solutions are globally uniformly bounded, dealing with convergence and stability into a ball of the state space with non-null radius, under some assumptions. The Lyapunov analysis technique was used to prove the stability of the closed-loop system, compute bounds on control gains and guaranteeing desired bounds on attitude dynamics tracking errors in the presence of measurement disturbances. The controller laws were tested in numerical simulations and in an experimental hexarotor, developed at the UFRN Robotics Laboratory

Máquina de vetores-suporte intervalar

The Support Vector Machines (SVM) has attracted increasing attention in machine learning area, particularly on classification and patterns recognition. However, in some cases it is not easy to determinate accurately the class which given pattern belongs. This thesis involves the construction of a intervalar pattern classifier using SVM in association with intervalar theory, in order to model the separation of a pattern set between distinct classes with precision, aiming to obtain an optimized separation capable to treat imprecisions contained in the initial data and generated during the computational processing. The SVM is a linear machine. In order to allow it to solve real-world problems (usually nonlinear problems), it is necessary to treat the pattern set, know as input set, transforming from nonlinear nature to linear problem. The kernel machines are responsible to do this mapping. To create the intervalar extension of SVM, both for linear and nonlinear problems, it was necessary define intervalar kernel and the Mercer s theorem (which caracterize a kernel function) to intervalar function