Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Lenardo Chaves e Silva"'
Autor:
Tássio Fernandes Costa, Álvaro Sobrinho, Lenardo Chaves e Silva, Leandro Dias da Silva, Angelo Perkusich
Publikováno v:
Applied Sciences, Vol 12, Iss 3, p 1475 (2022)
Safety and effectiveness are crucial quality attributes for insulin infusion pump systems. Therefore, regulatory agencies require the quality evaluation and approval of such systems before the market to decrease the risk of harm, motivating the usage
Externí odkaz:
https://doaj.org/article/743bd0cdbbef4c5e86f16a555d89ff44
Autor:
Álvaro Sobrinho, Ially Almeida, Leandro Dias da Silva, Lenardo Chaves e Silva, Adriano Araújo, Tássio Fernandes Costa, Angelo Perkusich
Publikováno v:
Software Testing, Verification and Reliability. 33
Autor:
Alvaro Sobrinho, Carlos Heitor Pereira Liberalino, Lenardo Chaves e Silva, Johnattan Douglas Ferreira Viana, Sebastião Emidio Alves Filho, Thalia Katiane Sampaio Gurgel
Publikováno v:
Brazilian Journal of Development. 7:2209-2227
Autor:
Paulo Gabriel Gadelha Queiroz, Jesaías Carvalho Pereira Silva, Leonardo Torres Marques, Rayana Souza Rocha, Angélica Félix de Castro, Carlos Alexandre Morais Silva, Lenardo Chaves e Silva, Bruno Torres Marques
Publikováno v:
Brazilian Journal of Development. 6:103334-103350
A evasao academica e um problema importante e complexo enfrentado por muitas instituicoes de ensino superior. Nesse contexto, este estudo desvenda suas causas no curso de Ciencia da Computacao em UFERSA. Em especial, utilizamos uma tecnica de agrupam
Autor:
Tássio Fernandes Costa, Álvaro Sobrinho, Lenardo Chaves e Silva, Leandro Dias da Silva, Angelo Perkusich
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030976514
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e7190fc8cb46264c17f24a75a3939b3
https://doi.org/10.1007/978-3-030-97652-1_8
https://doi.org/10.1007/978-3-030-97652-1_8
Autor:
Hidalyn Theodory C. M. Souza, Helder Fernando de Araujo Oliveira, John David S. Belém, Lenardo Chaves e Silva, Alvaro Sobrinho
Publikováno v:
International Journal of Modeling, Simulation, and Scientific Computing. 13
People who live in low-income and hard-to-reach regions are usually the most affected ones by high incidences of arboviral diseases, increasing morbidity and mortality rates, and public health costs. We present the modeling of hardware and software c
Autor:
Alvaro Sobrinho, Andressa C. M. da Silveira, Angelo Perkusich, Íris Viana dos Santos Santana, Danilo F. S. Santos, Edmar C. Gurjao, Lenardo Chaves e Silva, Leandro Dias da Silva
Publikováno v:
Journal of Medical Internet Research
Journal of Medical Internet Research, Vol 23, Iss 4, p e27293 (2021)
Journal of Medical Internet Research, Vol 23, Iss 4, p e27293 (2021)
Background Controlling the COVID-19 outbreak in Brazil is a challenge due to the population’s size and urban density, inefficient maintenance of social distancing and testing strategies, and limited availability of testing resources. Objective The
Autor:
Íris Viana dos Santos Santana, Andressa CM da Silveira, Álvaro Sobrinho, Lenardo Chaves e Silva, Leandro Dias da Silva, Danilo F S Santos, Edmar C Gurjão, Angelo Perkusich
BACKGROUND Controlling the COVID-19 outbreak in Brazil is a challenge due to the population’s size and urban density, inefficient maintenance of social distancing and testing strategies, and limited availability of testing resources. OBJECTIVE The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::944327844594970ec70f1224e4ce8ecd
https://doi.org/10.2196/preprints.27293
https://doi.org/10.2196/preprints.27293
Autor:
Jesaías Carvalho Pereira Silva, Leonardo Torres Marques, Angélica Félix de Castro, Paulo Gabriel Gadelha Queiroz, Rayana Souza Rocha, Bruno Torres Marques, Lenardo Chaves e Silva, Carlos Alexandre Morais Silva
Publikováno v:
Educação Contemporânea – Volume 15 – Ensino Superior
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2d5467d20afb5183cb4e4737cd44355
https://doi.org/10.36229/978-65-5866-057-6.cap.09
https://doi.org/10.36229/978-65-5866-057-6.cap.09
Autor:
Cynthia Moreira Maia, Christina Pacheco, Julio Cartier Maia Gomes, Cicilia Raquel Maia Leite, Otília de Sousa Santos, Patrício de Alencar Silva, Lenardo Chaves e Silva, Angélica Félix de Castro
Publikováno v:
EATIS
This paper presents a comparative analysis of five classification algorithms: k-nearest neighbor (k-NN), Support Vector Machine (SVM), Classification and Regression Trees (CART), Naive Bayes (NB) and Random Forest (RF) for recognition of three types