http://repositorio.jesuita.org.br/handle/UNISINOS/10023 Engenharia de Controle e Automação Wed, 22 Apr 2026 00:20:31 GMT 2026-04-22T00:20:31Z http://repositorio.jesuita.org.br/handle/UNISINOS/12972 Internet das Coisas Industrial: dispositivo para comunicação Modbus através de redes celular Nör, Gustavo Haussmann Mon, 29 Nov 2021 00:00:00 GMT http://repositorio.jesuita.org.br/handle/UNISINOS/12972 2021-11-29T00:00:00Z http://repositorio.jesuita.org.br/handle/UNISINOS/12719 Sistema de controle intuitivo baseado na captura de movimentos do braço humano para operação de manipuladores robóticos Souza, Gustavo Eismann Tue, 22 Nov 2022 00:00:00 GMT http://repositorio.jesuita.org.br/handle/UNISINOS/12719 2022-11-22T00:00:00Z http://repositorio.jesuita.org.br/handle/UNISINOS/12718 Sistema classificador de sons cardíacos baseado em redes neurais artificiais Farinha, Ben-Hur Daniel Morais The World Health Organization (WHO) asserts that cardiovascular diseases are, nowadays, the major cause of mortality in the world. For its part, the entity also observes that the improvement in processes of prevention, diagnostic and treatment contribute to the decrease in lethality rates. Furthermore, inside the group of heart diseases, some have the possibility of diagnose through the identification of heart murmurs, that can be detected by means of an exam of cardiac auscultation – where the professional listens to the sounds originating in the heart, through a stethoscope, and performs the analysis of the patient's condition. Therefore, this work focuses on propounding a computer system that executes the classification of these heart murmurs in normal and abnormal. For that reason, the system uses database Physionet, in which the cardiac sounds, both pathological and not, are applied to train and validate classifiers, based in artificial neural networks. In this way, three types of classifiers are proposed, underpinned by MLP, LSTM and CNN, which are submitted to the audios of the database. The validation of these models, for its turn, will be carried out by evaluating the performance of the classifiers in terms of predicting heart sounds, based on the application of validation techniques suggested by the bibliographies. Consequently, by the end of the process, the objective is to obtain a robust and reliable classifier model, which is capable of performing heart sound predictions efficiently. After applying the methodologies to the classifier models, the CNN model performed best, with an accuracy of 0.8947, associated with a sensitivity of 0.8915 and a specificity of 0.8973. Mon, 21 Nov 2022 00:00:00 GMT http://repositorio.jesuita.org.br/handle/UNISINOS/12718 2022-11-21T00:00:00Z http://repositorio.jesuita.org.br/handle/UNISINOS/12560 Sistema de otimização do perfil de movimento de um robô omnidirecional autônomo com base em pontos de interesse Toso, Bruno Nunes Tue, 14 Jun 2022 00:00:00 GMT http://repositorio.jesuita.org.br/handle/UNISINOS/12560 2022-06-14T00:00:00Z http://repositorio.jesuita.org.br/handle/UNISINOS/11237 Manutenção preditiva utilizando técnicas de machine learning em um sistema embarcado Franco, Igor Tedeschi Tue, 02 Jun 2020 00:00:00 GMT http://repositorio.jesuita.org.br/handle/UNISINOS/11237 2020-06-02T00:00:00Z http://repositorio.jesuita.org.br/handle/UNISINOS/11236 Sistema de redes neurais para controle de prótese de membro superior utilizando visão computacional Bertoluci, Lorenzo da Silva Tue, 01 Dec 2020 00:00:00 GMT http://repositorio.jesuita.org.br/handle/UNISINOS/11236 2020-12-01T00:00:00Z http://repositorio.jesuita.org.br/handle/UNISINOS/11235 Caracterização de transmissores 4-20 mA visando sensoriamento de baixo consumo Silveira, Gabriel do Nascimento Thu, 28 Nov 2019 00:00:00 GMT http://repositorio.jesuita.org.br/handle/UNISINOS/11235 2019-11-28T00:00:00Z http://repositorio.jesuita.org.br/handle/UNISINOS/11234 Tratamento e processamento de sinais cerebrais por meio de eletroencefalografia Santos, Carlos Júnior Oliveira dos Thu, 28 Nov 2019 00:00:00 GMT http://repositorio.jesuita.org.br/handle/UNISINOS/11234 2019-11-28T00:00:00Z http://repositorio.jesuita.org.br/handle/UNISINOS/11233 Desenvolvimento de um controlador PID com auto sintonia usando redes neurais artificiais e regressão não-linear robusta para o controle de atitude de um simulador de satélites com rodas de reação. Piaia, Guilherme Angelo Fri, 30 Nov 2018 00:00:00 GMT http://repositorio.jesuita.org.br/handle/UNISINOS/11233 2018-11-30T00:00:00Z