Made available in DSpace on 2016-04-29T14:16:46Z (GMT). No. of bitstreams: 1 Nathalie Jacinta Rodrigues de Oliveira Py.pdf: 1071074 bytes, checksum: 13862fca79bbb6cfa67df01abeb5b819 (MD5) Previous issue date: 2015-12-02 / Goals: The goal of the study is an analyze of the implantation of health care public polities for mammography access in the Oiapoque river frontier between France and Brazil where there is several social inequalities in health care. Justifications: The interest to this subject has two influences: The work realized at the coordination of the Regional Cancer Network of French Guiana in collaboration with health care professionals, a social worker and a psychologist in the support to patients and their dose relatives. The knowledge of the frontier zone with the richness of the population and the challenges they take up in the everyday life by living far away from the main cities. Hypotheses: Two questions will be analyzed to answer the main problematic: Are the social determinants on health care for the frontier population regarded for the implantation of polities for breast cancer detection access? Which are the strategies of the public powers, institutional actors and the professionals to facilitate the access to mammography for the frontier population? Teorico-metodological aspects: The analyze of the social inequalities on health care influence will be based on the economist Amartya Sen theory on the link between social inequalities and individual freedom. A documental research and interviews of professionals working on the frontier had been realized to understand the specific context of the region, the brazilian and french health care system, the organization of the breast cancer detection for the frontier population. Results: We can conclude that the territorial inequalities has most impact on the access of mammographyfor the women living on frontier. The inequalities needs a coordination of the public action to realized the structural modifications, and also local actions promoting more interaction between professionals and population / Objetivos: Este trabalho tem como objetivo analisar a implementação das políticas publicas de saúde para o acesso à mamografia na região da fronteira fluvial do rio Oiapoque entre a França e o Brasil que apresenta varias situações de desigualdades sociais de saúde. Justificativa: O interesse por essa problemática teve duas influências: O trabalho realizado na coordenação da Rede regional do câncer da Guiana Francesa, em colaboração com os profissionais de saúde, uma assistente social e uma psicóloga no atendimento aos pacientes e familiares. O conhecimento de uma região de fronteira rica pela diversidade de sua população e dos desafios que enfrentam no seu quotidiano pelo distanciamento com as cidades principais. Duas questões foram contempladas para responder à problemática principal: Os determinantes sociais de saúde da população da região fronteiriça estão sendo contemplados na implementação das políticas de acesso à detecção do câncer de mama? Quais são as estratégias propostas pelos poderes públicos, os atores institucionais, os profissionais para facilitar o acesso à mamografia para a população da fronteira? Aspectos teórico-metodológicos: A análise da influência das desigualdades sociais de saúde no acesso a mamografia foi realizada com base na teoria do economista Amartya Sen sobre a relação entre as desigualdades sociais e a liberdade dos indivíduos. Uma pesquisa documental e entrevistas com profissionais da fronteira foram realizadas para entender o contexto específico da região, os sistemas de saúde brasileiros e francês e a organização da detecção do câncer de mama para a população fronteiriça. Resultados obtidos: Pudemos concluir que as desigualdades territoriais são maior impacto na falta de participação ao exame de as que tem detecção do câncer de mama das mulheres de vivem na fronteira. Essas desigualdades requerem uma ação pública coordenada para realizar mudanças estruturais "e de organização dos serviços públicos, mais também ações localizadas, promovendo maior interação entre os profissionais e a população

This thesis presents the research results on the development of a microwave tomography imaging algorithm capable of reconstructing the dielectric properties of the unknown object. Our focus was on the theoretical aspects of the non-linear tomographic image reconstruction problem with particular emphasis on developing efficient numerical and non-linear optimization for solving the inverse scattering problem. A detailed description of a novel microwave tomography method based on frequency dependent finite difference time domain, a numerical method for solving Maxwell's equations and Genetic Algorithm (GA) as a global optimization technique is given. The proposed technique has the ability to deal with the heterogeneous and dispersive object with complex distribution of dielectric properties and to provide a quantitative image of permittivity and conductivity profile of the object. It is shown that the proposed technique is capable of using the multi-frequency, multi-view, and multi-incident planer techniques which provide useful information for the reconstruction of the dielectric properties profile and improve image quality. In addition, we show that when a-priori information about the object under test is known, it can be easily integrated with the inversion process. This provides realistic regularization of the solution and removes or reduces the possibility of non-true solutions. We further introduced application of the GA such as binary-coded GA, real-coded GA, hybrid binary and real coded GA, and neural-network/GA for solving the inverse scattering problem which improved the quality of the images as well as the conversion rate. The implications and possible advantages of each type of optimization are discussed, and synthetic inversion results are presented. The results showed that the proposed algorithm was capable of providing the quantitative images, although more research is still required to improve the image quality. In the proposed technique the computation time for solution convergence varies from a few hours to several days. Therefore, the parallel implementation of the algorithm was carried out to reduce the runtime. The proposed technique was evaluated for application in microwave breast cancer imaging as well as measurement data from university of Manitoba and Institut Frsenel's microwave tomography systems.

This thesis presents the research results on the development of a microwave tomography imaging algorithm capable of reconstructing the dielectric properties of the unknown object. Our focus was on the theoretical aspects of the non-linear tomographic image reconstruction problem with particular emphasis on developing efficient numerical and non-linear optimization for solving the inverse scattering problem. A detailed description of a novel microwave tomography method based on frequency dependent finite difference time domain, a numerical method for solving Maxwell's equations and Genetic Algorithm (GA) as a global optimization technique is given. The proposed technique has the ability to deal with the heterogeneous and dispersive object with complex distribution of dielectric properties and to provide a quantitative image of permittivity and conductivity profile of the object. It is shown that the proposed technique is capable of using the multi-frequency, multi-view, and multi-incident planer techniques which provide useful information for the reconstruction of the dielectric properties profile and improve image quality. In addition, we show that when a-priori information about the object under test is known, it can be easily integrated with the inversion process. This provides realistic regularization of the solution and removes or reduces the possibility of non-true solutions. We further introduced application of the GA such as binary-coded GA, real-coded GA, hybrid binary and real coded GA, and neural-network/GA for solving the inverse scattering problem which improved the quality of the images as well as the conversion rate. The implications and possible advantages of each type of optimization are discussed, and synthetic inversion results are presented. The results showed that the proposed algorithm was capable of providing the quantitative images, although more research is still required to improve the image quality. In the proposed technique the computation time for solution convergence varies from a few hours to several days. Therefore, the parallel implementation of the algorithm was carried out to reduce the runtime. The proposed technique was evaluated for application in microwave breast cancer imaging as well as measurement data from university of Manitoba and Institut Frsenel's microwave tomography systems.

The aim of the thesis is to verify synergy of genetic programming and neural networks. Solution is provided by set of experiments with implemented library built upon benchmark tasks. I've done experiments with directly and also indirectly encoded neural netwrok. I focused on finding robust solutions and the best calculation of configurations, overfitting detection and advanced stimulations of solution with fitness function. Generally better solutions were found using lower values of parameters n_c and n_r. These solutions tended less to be overfitted. I was able to evolve neurocontroller eliminating oscilations in pole balancing problem. In cancer detection problem, precision of provided solution was over 98%, which overcame compared techniques. I succeeded also in designing of maze model, where agent was able to perform multistep tasks.