Pub Date : 2023-01-05DOI: 10.5747/ce.2022.v14.e391
Beatriz Marques Carvalho, Vitor Hugo Uzeloto Fernandes Mingroni, André Soares da Silva, P. Silva, C. A. Olivati, L. Martins, Luiz Carlos Silva Filho, Deuber Lincon da Silva Agostini
With the advancement of nanotechnology, nanomaterials such as nanofibers have gained attention, as they have applications in technological, environmental and health areas. In this context, electrospinning stands out for being considered a simple and versatile technique that allows the production of nanofibers. Carbon-based additives have been used to compose the polymeric matrix responsible for obtaining nanofibers, such as graphene, which among its applications has been used in gas sensors, as it can detect some molecules, including the ammonia. Thus, it is interesting to carry out studies of the polymer poly(vinyl alcohol) (PVA), together with the additive reduced graphene oxide (rGO), aiming at the application in ammonia gas sensor. Thus, electrospun PVA nanofibers with rGO were produced at different concentrations. To analyze the influence of rGO on PVA nanofibers, they were characterized by optical microscopy (OM) and tested in the presence of ammonia gas, generating graphs of current (i) by time (t). Therefore, electrospun nanofibers with considerable quantity and good formats were obtained, as seen in the OM images. By the graphs of i vs t, it was observed that the nanofibers that contained 4% of rGO showed greater sensitivity in the presence of ammonia gas, proving that rGO can be used as an additive in polymeric nanofibers with application in ammonia gas sensor.
{"title":"NANOFIBRAS DE POLI(ÁLCOOL VINÍLICO) COM ÓXIDO DE GRAFENO REDUZIDO PARA APLICAÇÃO EM SENSOR DE GÁS","authors":"Beatriz Marques Carvalho, Vitor Hugo Uzeloto Fernandes Mingroni, André Soares da Silva, P. Silva, C. A. Olivati, L. Martins, Luiz Carlos Silva Filho, Deuber Lincon da Silva Agostini","doi":"10.5747/ce.2022.v14.e391","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.e391","url":null,"abstract":"With the advancement of nanotechnology, nanomaterials such as nanofibers have gained attention, as they have applications in technological, environmental and health areas. In this context, electrospinning stands out for being considered a simple and versatile technique that allows the production of nanofibers. Carbon-based additives have been used to compose the polymeric matrix responsible for obtaining nanofibers, such as graphene, which among its applications has been used in gas sensors, as it can detect some molecules, including the ammonia. Thus, it is interesting to carry out studies of the polymer poly(vinyl alcohol) (PVA), together with the additive reduced graphene oxide (rGO), aiming at the application in ammonia gas sensor. Thus, electrospun PVA nanofibers with rGO were produced at different concentrations. To analyze the influence of rGO on PVA nanofibers, they were characterized by optical microscopy (OM) and tested in the presence of ammonia gas, generating graphs of current (i) by time (t). Therefore, electrospun nanofibers with considerable quantity and good formats were obtained, as seen in the OM images. By the graphs of i vs t, it was observed that the nanofibers that contained 4% of rGO showed greater sensitivity in the presence of ammonia gas, proving that rGO can be used as an additive in polymeric nanofibers with application in ammonia gas sensor.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89692200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-05DOI: 10.5747/ce.2022.v14.e392
Eliane Vendramini de Oliveira
The Two-Dimensional Cutting Problem has a direct relationship with problems of industries. There are several proposals for solving this problem. In particular, solution proposals using metaheuristics were the focus of this research. Thus, in this paper we present a specialized genetic algorithm of randomized random keys. Several tests were performed using known instances in the specific literature, and the results found by the metaheuristic proposed were in many cases, equal or superior, to the results already published in the literature. Another comparative of results presented in this paper is related to the results obtained by the metaheuristic expert and results found by mathematical modeling using commercial software. In this case, again the genetic algorithm presented results equal to or very close to the optimum found by the mathematical model. In addition, the optimization proposal was extended to two-dimensional non-guillotine cut without parts orientation.
{"title":"ALGORITMO GENÉTICO DE CHAVES ALEATÓRIAS VICIADAS ESPECIALIZADO PARA O PROBLEMA DE CORTE BIDIMENSIONAL NÃO GUILHOTINADO","authors":"Eliane Vendramini de Oliveira","doi":"10.5747/ce.2022.v14.e392","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.e392","url":null,"abstract":"The Two-Dimensional Cutting Problem has a direct relationship with problems of industries. There are several proposals for solving this problem. In particular, solution proposals using metaheuristics were the focus of this research. Thus, in this paper we present a specialized genetic algorithm of randomized random keys. Several tests were performed using known instances in the specific literature, and the results found by the metaheuristic proposed were in many cases, equal or superior, to the results already published in the literature. Another comparative of results presented in this paper is related to the results obtained by the metaheuristic expert and results found by mathematical modeling using commercial software. In this case, again the genetic algorithm presented results equal to or very close to the optimum found by the mathematical model. In addition, the optimization proposal was extended to two-dimensional non-guillotine cut without parts orientation.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"161 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73699921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-05DOI: 10.5747/ce.2022.v14.e395
Luis Eduardo Anitelli Artero, Weslen Gabriel Dos Santos Piveta, R. Bratifich, Marcelo Amaro Manoel da Silva
The algorithm of artificial neural networks (RNA), are computational models that can perform generalization, inferences, identification, and classification of information and patterns. Thus, in this work, a study was developed through the creation of a neural network classifying patterns to identify and classify the types of short circuits that occur in the electrical distribution system. Thus, a multilayer perceptron neural network was developed in the Matlab software with 3 hidden layers, 25 neurons in each hidden layer, and a hyperbolic tangent activation function. The PMC was trained using simulated short-circuit data in the ATPDraw software and presented an efficiency of 94.7% in the identification of short circuits in the validation stage. The trained network was also able to evaluate short circuits on an IEEE 9-bar test bus demonstrating the potential to be applied as an additional measure of network information in integrated operation centers (IOC).
{"title":"ESTUDO DA APLICAÇÃO DE REDES NEURAIS ARTIFICIAIS PARA IDENTIFICAÇÃO DE CURTO-CIRCUITOS NO SISTEMA ELÉTRICO DE DISTRIBUIÇÃO","authors":"Luis Eduardo Anitelli Artero, Weslen Gabriel Dos Santos Piveta, R. Bratifich, Marcelo Amaro Manoel da Silva","doi":"10.5747/ce.2022.v14.e395","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.e395","url":null,"abstract":"The algorithm of artificial neural networks (RNA), are computational models that can perform generalization, inferences, identification, and classification of information and patterns. Thus, in this work, a study was developed through the creation of a neural network classifying patterns to identify and classify the types of short circuits that occur in the electrical distribution system. Thus, a multilayer perceptron neural network was developed in the Matlab software with 3 hidden layers, 25 neurons in each hidden layer, and a hyperbolic tangent activation function. The PMC was trained using simulated short-circuit data in the ATPDraw software and presented an efficiency of 94.7% in the identification of short circuits in the validation stage. The trained network was also able to evaluate short circuits on an IEEE 9-bar test bus demonstrating the potential to be applied as an additional measure of network information in integrated operation centers (IOC).","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"1998 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88245822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-05DOI: 10.5747/ce.2022.v14.e390
Caique Cesar Gargel de Oliveira, Leandro Luiz de Almeida, Francisco Assis da Silva, Robson Augusto Siscoutto
With the emergence of the INTERNET and the growth of social networks, the sharing of content, such as images, audios and videos, and access to this content through websites and social networks, has become much greater. Shared content, consisting of images, audio and/or videos, may not be appropriate for all audiences or environments, for various reasons. One of them is in relation to nudity and pornography, which is very present on the INTERNET and social networks, and can cause negative impacts when accessed in business environments, as well as it can cause problems in the development and behavior of children and adolescents. In order to control access to these types of content, it is necessary to develop resources that perform filtering. Therefore, this work seeks to contribute to the development of a tool capable of detecting nudity in images by combining existing image processing techniques, such as the detection of skin color pixels, counting of related elements, zoning techniques and nudity classifiers using machine learning algorithms. Tests carried out on showed an accuracy of 90.5% in the best case.
{"title":"DETECÇÃO DE NUDEZ EM IMAGENS POR SEGMENTAÇÃO E RECONHECIMENTO DE PADRÕES","authors":"Caique Cesar Gargel de Oliveira, Leandro Luiz de Almeida, Francisco Assis da Silva, Robson Augusto Siscoutto","doi":"10.5747/ce.2022.v14.e390","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.e390","url":null,"abstract":"With the emergence of the INTERNET and the growth of social networks, the sharing of content, such as images, audios and videos, and access to this content through websites and social networks, has become much greater. Shared content, consisting of images, audio and/or videos, may not be appropriate for all audiences or environments, for various reasons. One of them is in relation to nudity and pornography, which is very present on the INTERNET and social networks, and can cause negative impacts when accessed in business environments, as well as it can cause problems in the development and behavior of children and adolescents. In order to control access to these types of content, it is necessary to develop resources that perform filtering. Therefore, this work seeks to contribute to the development of a tool capable of detecting nudity in images by combining existing image processing techniques, such as the detection of skin color pixels, counting of related elements, zoning techniques and nudity classifiers using machine learning algorithms. Tests carried out on showed an accuracy of 90.5% in the best case.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79121905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.5747/ce.2022.v14.n1.e386
H. Secchi, Silvio Antonio Carro
The use of computer vision plays an important role for security purposes. However, the combination with deep learning techniques and convolutional neural networks are still little explored because they demand a lot of computational processing capacity. This work aims to combine these techniques in order to generate an algorithm that is capable of identifying and tracking individuals in videos, in addition to monitoring their actions with the purpose of identifying movements that could signify a criminal act, using the YOLO algorithm for identification, Kalman filter for tracking and BlazePose for movement identification. This work resulted in a 95% accuracy rate on well-defined videos and an 81% accuracy rate using video from the most popular security cameras.
{"title":"USO DE DEEP LEARNING APLICADO NO RECONHECIMENTO DE AÇÕES HUMANAS A PARTIR DE VÍDEOS EM ALTA RESOLUÇÃO VISANDO IDENTIFICAR MOVIMENTOS SUSPEITOS","authors":"H. Secchi, Silvio Antonio Carro","doi":"10.5747/ce.2022.v14.n1.e386","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.n1.e386","url":null,"abstract":"The use of computer vision plays an important role for security purposes. However, the combination with deep learning techniques and convolutional neural networks are still little explored because they demand a lot of computational processing capacity. This work aims to combine these techniques in order to generate an algorithm that is capable of identifying and tracking individuals in videos, in addition to monitoring their actions with the purpose of identifying movements that could signify a criminal act, using the YOLO algorithm for identification, Kalman filter for tracking and BlazePose for movement identification. This work resulted in a 95% accuracy rate on well-defined videos and an 81% accuracy rate using video from the most popular security cameras.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"103 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80746940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.5747/ce.2022.v14.n1.e385
Bruno Mattos Braga, Francisco Assis da Silva, Robson Augusto Siscoutto, Leandro Luiz de Almeida
Every day CPFs are registered on the stock exchange. People seeking greater profitability, exposing themselves to great risks without even knowing how to analyze the best opportunities. Whenever you start to learn something, it is normal to have many difficulties and challenges, because the act of knowing something “new” is challenging, even more so when it involves money. Therefore, a comparative analysis was carried out between some of the Artificial Intelligence methods, applied in standards on the stock exchange, aiming to improve the assertiveness of the operations carried out and seeking their statistically proven efficiency. In this way, increasing the chances of the operations being winners. The algorithms were trained separately from historical data of five stocks, namely: Petrobras, Itaú, Bradesco, Vale and Ambev. And the algorithms of Linear Regression, Support Vector Machine (SVM), K Nearest Neighbor (KNN), Random Forest and Decision Trees were used.
{"title":"MACHINE LEARNING APLICADO EM AÇÕES NO MERCADO FINANCEIRO B3","authors":"Bruno Mattos Braga, Francisco Assis da Silva, Robson Augusto Siscoutto, Leandro Luiz de Almeida","doi":"10.5747/ce.2022.v14.n1.e385","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.n1.e385","url":null,"abstract":"Every day CPFs are registered on the stock exchange. People seeking greater profitability, exposing themselves to great risks without even knowing how to analyze the best opportunities. Whenever you start to learn something, it is normal to have many difficulties and challenges, because the act of knowing something “new” is challenging, even more so when it involves money. Therefore, a comparative analysis was carried out between some of the Artificial Intelligence methods, applied in standards on the stock exchange, aiming to improve the assertiveness of the operations carried out and seeking their statistically proven efficiency. In this way, increasing the chances of the operations being winners. The algorithms were trained separately from historical data of five stocks, namely: Petrobras, Itaú, Bradesco, Vale and Ambev. And the algorithms of Linear Regression, Support Vector Machine (SVM), K Nearest Neighbor (KNN), Random Forest and Decision Trees were used.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78335233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-30DOI: 10.5747/ce.2022.v14.n1.e383
Thales Santos Verne, Francisco Assis da Silva, Leandro Luiz de Almeida, Danillo Roberto Pereira, A. O. Artero
The detection and recognition of plants has always been a difficult task even for connoisseurs and scholars due to the wide variety of plants found worldwide. With the advancement of technology, it has become possible to solve this problem computationally. This paper presents a method to perform plant detection and recognition from images using computer vision and artificial intelligence algorithms. The results show that the computational cost and recognition rate were satisfactory for use in controlled environments. The processing time to recognize each plant was 375 milliseconds, with an accuracy of 92%.
{"title":"DETECÇÃO E RECONHECIMENTO DE PLANTAS DE PEQUENO PORTE UTILIZANDO APRENDIZAGEM DE MÁQUINA","authors":"Thales Santos Verne, Francisco Assis da Silva, Leandro Luiz de Almeida, Danillo Roberto Pereira, A. O. Artero","doi":"10.5747/ce.2022.v14.n1.e383","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.n1.e383","url":null,"abstract":"The detection and recognition of plants has always been a difficult task even for connoisseurs and scholars due to the wide variety of plants found worldwide. With the advancement of technology, it has become possible to solve this problem computationally. This paper presents a method to perform plant detection and recognition from images using computer vision and artificial intelligence algorithms. The results show that the computational cost and recognition rate were satisfactory for use in controlled environments. The processing time to recognize each plant was 375 milliseconds, with an accuracy of 92%.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77910189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-30DOI: 10.5747/ce.2022.v14.n1.e381
Luiz Fernando do Nascimento, Francisco Assis da Silva, Leandro Luiz de Almeida, A. O. Artero, M. A. Piteri
A big obstacle for the Computer Vision area is the quality of the processed input images. As an example, there are dark images, which can be caused by several factors such as low light source at night, adverse weather conditions, among others. This work aims to use images with low lighting for the development of algorithms that help to improve the quality of light and image. Computer Vision techniques were used with the help of the OpenCV library in the development of algorithms to perform smoothing, correlation between minimum and maximum intensities, intensities reinforcement and exposure correction, definition of weight matrix and image enhancement. The results show that the proposed method was able to improve the images, considerably reducing unwanted features, maintaining good lighting and image quality.
{"title":"CORREÇÃO DE ILUMINAÇÃO EM IMAGENS CAPTURADAS EM AMBIENTES COM BAIXA LUMINOSIDADE","authors":"Luiz Fernando do Nascimento, Francisco Assis da Silva, Leandro Luiz de Almeida, A. O. Artero, M. A. Piteri","doi":"10.5747/ce.2022.v14.n1.e381","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.n1.e381","url":null,"abstract":"A big obstacle for the Computer Vision area is the quality of the processed input images. As an example, there are dark images, which can be caused by several factors such as low light source at night, adverse weather conditions, among others. This work aims to use images with low lighting for the development of algorithms that help to improve the quality of light and image. Computer Vision techniques were used with the help of the OpenCV library in the development of algorithms to perform smoothing, correlation between minimum and maximum intensities, intensities reinforcement and exposure correction, definition of weight matrix and image enhancement. The results show that the proposed method was able to improve the images, considerably reducing unwanted features, maintaining good lighting and image quality.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"88 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86526090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-30DOI: 10.5747/ce.2022.v14.n1.e380
Caio Kraut
With the urbanization of Brazilian cities, automobile locomotion has become indispensable, so the area of urban mobility has increased on an exponential scale, resulting in an increase in traffic violence, whether caused by traffic jams, human bias or infrastructure problems. This work proposes a solution that predicts accident locations within urban areas based on temporal data (date and time) of accidents. It uses the K-Means algorithm to group and KNN Regressor to predict, within the sample of accident data from the city of São Paulo collected between 2019 and 2021, a predictive model with an accuracy of 96.04% within a tolerance of 500m was obtained.
{"title":"APRENDIZADO DE MÁQUINA UTILIZANDO AGRUPAMENTO E REGRESSÃO NA PREVISÃO DE LOCAIS DE ACIDENTES DE TRÂNSITO EM ZONAS URBANAS","authors":"Caio Kraut","doi":"10.5747/ce.2022.v14.n1.e380","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.n1.e380","url":null,"abstract":"With the urbanization of Brazilian cities, automobile locomotion has become indispensable, so the area of urban mobility has increased on an exponential scale, resulting in an increase in traffic violence, whether caused by traffic jams, human bias or infrastructure problems. This work proposes a solution that predicts accident locations within urban areas based on temporal data (date and time) of accidents. It uses the K-Means algorithm to group and KNN Regressor to predict, within the sample of accident data from the city of São Paulo collected between 2019 and 2021, a predictive model with an accuracy of 96.04% within a tolerance of 500m was obtained.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"41 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83201669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-30DOI: 10.5747/ce.2022.v14.n1.e384
Wellington Lima Salomão, A. O. Artero, F. Ribeiro, Luiz Carlos Marques Vamderlei, M. Dias, Francisco Assis da Silva
The Electrocardiogram remains a very important exam for the cardiologist, as it is a simple and low-cost exam to obtain a first diagnosis of the heart. However, the cost of commercial equipment still makes it impossible to use it in many places. Thus, this work presents a low-cost device, called MICROcardio, built with a microcontroller, which also provides a connection to a computer, in order to allow the visualization of the signals on the screen and also printed, in addition to the possibility of supporting their sharing. by different professionals, using the Internet. The results obtained in the experiments carried out with the MICROcardio were compared, by specialists in the medical field, with those obtained by commercial devices, and proved to be completely satisfactory.
{"title":"MICROcardio - UM DISPOSITIVO PARA COLETA E ANÁLISE DE SINAIS CARDÍACOS","authors":"Wellington Lima Salomão, A. O. Artero, F. Ribeiro, Luiz Carlos Marques Vamderlei, M. Dias, Francisco Assis da Silva","doi":"10.5747/ce.2022.v14.n1.e384","DOIUrl":"https://doi.org/10.5747/ce.2022.v14.n1.e384","url":null,"abstract":"The Electrocardiogram remains a very important exam for the cardiologist, as it is a simple and low-cost exam to obtain a first diagnosis of the heart. However, the cost of commercial equipment still makes it impossible to use it in many places. Thus, this work presents a low-cost device, called MICROcardio, built with a microcontroller, which also provides a connection to a computer, in order to allow the visualization of the signals on the screen and also printed, in addition to the possibility of supporting their sharing. by different professionals, using the Internet. The results obtained in the experiments carried out with the MICROcardio were compared, by specialists in the medical field, with those obtained by commercial devices, and proved to be completely satisfactory.","PeriodicalId":30414,"journal":{"name":"Colloquium Exactarum","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88138825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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