Engenharia de Computação

URI Permanente desta comunidadehttps://repositorio.cesupa.br/handle/prefix/31

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Navegando Engenharia de Computação por Orientador "Nascimento, Polyana Santos Fonseca"

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    Inferência baseada em regras de produção para o diagnóstico laboratorial da anemia
    (Centro Universitário do Estado do Pará, 2018-06-11) Gouveia, Rafael Santos; Rocha, Thiago Maia da; Nascimento, Polyana Santos Fonseca; Bezerra, Deisiany Santos; http://lattes.cnpq.br/6889523334917369; Araújo, Andrea Cristina Marques de; http://lattes.cnpq.br/7322421741765559
    Artificial intelligence is a technology that presents relevant applications in several areas. Soon after the emergence of this technology, its usefulness in the field of medicine stood out, culminating in notorious results regarding clinical process aid and long-term financial return. When dealing with the medical diagnostic procedure, the large number of variables can affect the decision process, causing differences in the opinions of the practitioners. There are many uncertainties regarding risk factors, therefore the diagnosis of the disease can be difficult even for specialists. Aiming in creating a tool to support the laboratory diagnosis of anemia, this project carried out a study that combined concepts in hematology with artificial intelligence under the approach of knowledge based systems to develop an inference system prototype that supports the process of diagnosis. This study also presents reports about the system development process. Consequently, it was possible to study anemia diagnosis and how to apply the acquired knowledge to the computational language and formal representation of the problem. As a result, it was possible to understand the stages which are part in a medical área knowledge based system development.
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    Otimização dos tempos de um semáforo por processamento de imagem e controladores
    (Centro Universitário do Estado do Pará, 2019) Silva, Raul Vitor Mesquita da; Corrêa Filho, Sérgio Teixeira; Brasil, Vitor Henrique Morais; Nascimento, Polyana Santos Fonseca; http://lattes.cnpq.br/6889523334917369; Brito, Itamar Jorge Vilhena de; http://lattes.cnpq.br/5143837732124006; Mendes, Marcelo Pinto da Costa; http://lattes.cnpq.br/3099832904134964
    This course completion work has as main objective to provide an improvement to the flow of traffic with the optimization of traffic light times, through a digital image processing application and controllers. So that it is possible to create intelligent traffic lights that can contribute to a better traffic in big cities. The whole system has a set of scripts that use the Python language and its specific modules to perform different functions, such as digitally processing an urban traffic video, analyzing the state of the road and determining its state as light, moderate, intense flow and finally, to perform the optimization of the green signal time of a certain semaphore.