Doutorado em Engenharia Elétrica e da Computação (EMC)

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http://200.137.215.59/tede/handle/tede/3828

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Navegando Doutorado em Engenharia Elétrica e da Computação (EMC) por Por Área do CNPQ "CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO"

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    Controle e estabilização de aeronaves não tripuladas submetidas a falhas nos motores
    (Universidade Federal de Goiás, 2024-06-07) Bulhões, Júnio Santos; Magalhães, Alana da Silva; http://lattes.cnpq.br/4812531916179139; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Magalhães, Alana da Silva; Coimbra, Antonio Paulo; Araújo, Wanderson Rainer Hilário de; Martins, Marcella Scoczynski Ribeiro
    The objective of this work was to develop a methodology that utilizes control techniques to stabilize unmanned aerial vehicles subjected to engine failures. The methodology includes the creation of a test bench that allows independent rotational movements of ϕ and θ, eliminating translational movements and reducing its interference with the aircraft’s inertia matrix. Control techniques are implemented to stabilize the aircraft in situations of propulsor failure. The experiments demonstrate an improvement in the aircraft’s stability, with a reduction of more than 80% in the effects produced by the failure in the initial moments and the maintenance of stability in scenarios with up to 30% propulsor performance degradation. The proposed method surpasses other approaches in terms of efficiency and preservation of the aircraft’s autonomy. Both the developed test bench and the simulator are validated, and the auxiliary control that operates post-failure is tested in simulation and on the test bench, demonstrating its ability to stabilize the aircraft during failures in one of its propulsors, providing a viable and efficient solution for real-world situations.
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    Modelo não supervisionado de segmentação de estruturas em exames de tomografia de crânio
    (Universidade Federal de Goiás, 2024-07-10) Santos, Paulo Victor dos; Martins, Marcella Scoczynski Ribeiro; http://lattes.cnpq.br/5212122361603572; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Delgado, Myriam Regattieri de Biase da Silva; Vieira, Flavio Henrique Teles; Gonçalves, Cristhiane; Martins, Marcella Scoczynski Ribeiro
    This work proposes the development of an unsupervised method for segmenting cranial CT images. The methodology involves extracting image features and applying similarity and continuity constraints to create segmentation maps of intracranial structures and observable tissues. This approach aims to assist specialists in diagnosis by identifying regions with specific anomalies. Applied to real-world datasets, the method uses a spatial continuity evaluation function related to the desired number of structures. Results show satisfactory performance, indicating a simplified and accessible approach that reduces computational load, training time, and financial costs. This proposal serves as a practical tool for cranial CT image segmentation, providing significant contributions to the analysis of medical images in clinical and diagnostic settings.