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Trabalho de evento-anais periodico
An experience on short course of computational geometric modeling in engineering design for high school students (2021)
Cheng, Liang Yee ; Correa, Fabiano Rogério ; Motezuki, Fabio Kenji
Fonte: Advances in Intelligent Systems and Computing - AISC. Nome do evento: International Conference on Geometry And Graphics - ICGG 2020. Unidade: EP
Assuntos: GEOMETRIA E MODELAGEM COMPUTACIONAL, ENGENHARIA, UNIVERSIDADE, ENSINO MÉDIO
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ABNT
CHENG, Liang Yee e CORREA, Fabiano Rogério e MOTEZUKI, Fabio Kenji. An experience on short course of computational geometric modeling in engineering design for high school students. Advances in Intelligent Systems and Computing - AISC. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-63403-2_57. Acesso em: 01 out. 2024. , 2021
APA
Cheng, L. Y., Correa, F. R., & Motezuki, F. K. (2021). An experience on short course of computational geometric modeling in engineering design for high school students. Advances in Intelligent Systems and Computing - AISC. Cham: Springer. doi:10.1007/978-3-030-63403-2_57
NLM
Cheng LY, Correa FR, Motezuki FK. An experience on short course of computational geometric modeling in engineering design for high school students [Internet]. Advances in Intelligent Systems and Computing - AISC. 2021 ; 1296 639-650.[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-3-030-63403-2_57
Vancouver
Cheng LY, Correa FR, Motezuki FK. An experience on short course of computational geometric modeling in engineering design for high school students [Internet]. Advances in Intelligent Systems and Computing - AISC. 2021 ; 1296 639-650.[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-3-030-63403-2_57
Trabalho de evento
A hybrid model to predict glucose oscillation for patients with type 1 diabetes and suggest customized recommendations (2020)
Pereira, João Paulo Aragão; Brandão, Anarosa Alves Franco ; Bevilacqua, Joyce da Silva; Giannella, Maria Lucia Cardillo Correa
Fonte: Proceedings. Nome do evento: Intelligent Systems Conference - IntelliSys. Unidades: EP, IME, FM
Assuntos: EQUAÇÕES DIFERENCIAIS ORDINÁRIAS, GEOMETRIA E MODELAGEM COMPUTACIONAL, DIABETES MELLITUS
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ABNT
PEREIRA, João Paulo Aragão et al. A hybrid model to predict glucose oscillation for patients with type 1 diabetes and suggest customized recommendations. 2020, Anais.. Cham: Springer, 2020. Disponível em: https://doi.org/10.1007/978-3-030-29513-4_59. Acesso em: 01 out. 2024.
APA
Pereira, J. P. A., Brandão, A. A. F., Bevilacqua, J. da S., & Giannella, M. L. C. C. (2020). A hybrid model to predict glucose oscillation for patients with type 1 diabetes and suggest customized recommendations. In Proceedings. Cham: Springer. doi:10.1007/978-3-030-29513-4_59
NLM
Pereira JPA, Brandão AAF, Bevilacqua J da S, Giannella MLCC. A hybrid model to predict glucose oscillation for patients with type 1 diabetes and suggest customized recommendations [Internet]. Proceedings. 2020 ;[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-3-030-29513-4_59
Vancouver
Pereira JPA, Brandão AAF, Bevilacqua J da S, Giannella MLCC. A hybrid model to predict glucose oscillation for patients with type 1 diabetes and suggest customized recommendations [Internet]. Proceedings. 2020 ;[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-3-030-29513-4_59
Trabalho de evento
The descriptive complexity of bayesian network specifications (2017)
Cozman, Fabio Gagliardi ; Mauá, Denis Deratani
Fonte: Symbolic and quantitative approaches to reasoning with bncertainty: Proceedings. Nome do evento: European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty - ECSQARU 2017. Unidades: IME, EP
Assuntos: ESTATÍSTICA E PROBABILIDADE, GEOMETRIA E MODELAGEM COMPUTACIONAL
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ABNT
COZMAN, Fabio Gagliardi e MAUÁ, Denis Deratani. The descriptive complexity of bayesian network specifications. 2017, Anais.. Cham: Springer, 2017. Disponível em: https://doi.org/10.1007/978-3-319-61581-3_9. Acesso em: 01 out. 2024.
APA
Cozman, F. G., & Mauá, D. D. (2017). The descriptive complexity of bayesian network specifications. In Symbolic and quantitative approaches to reasoning with bncertainty: Proceedings. Cham: Springer. doi:10.1007/978-3-319-61581-3_9
NLM
Cozman FG, Mauá DD. The descriptive complexity of bayesian network specifications [Internet]. Symbolic and quantitative approaches to reasoning with bncertainty: Proceedings. 2017 ;[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-3-319-61581-3_9
Vancouver
Cozman FG, Mauá DD. The descriptive complexity of bayesian network specifications [Internet]. Symbolic and quantitative approaches to reasoning with bncertainty: Proceedings. 2017 ;[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-3-319-61581-3_9
Trabalho de evento
The complexity of inferences and explanations in probabilistic logic programming (2017)
Cozman, Fabio Gagliardi ; Mauá, Denis Deratani
Fonte: Symbolic and quantitative approaches to reasoning with bncertainty: Proceedings. Nome do evento: European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty - ECSQARU 2017. Unidades: IME, EP
Assuntos: ESTATÍSTICA E PROBABILIDADE, GEOMETRIA E MODELAGEM COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COZMAN, Fabio Gagliardi e MAUÁ, Denis Deratani. The complexity of inferences and explanations in probabilistic logic programming. 2017, Anais.. Cham: Springer, 2017. Disponível em: https://doi.org/10.1007/978-3-319-61581-3_40. Acesso em: 01 out. 2024.
APA
Cozman, F. G., & Mauá, D. D. (2017). The complexity of inferences and explanations in probabilistic logic programming. In Symbolic and quantitative approaches to reasoning with bncertainty: Proceedings. Cham: Springer. doi:10.1007/978-3-319-61581-3_40
NLM
Cozman FG, Mauá DD. The complexity of inferences and explanations in probabilistic logic programming [Internet]. Symbolic and quantitative approaches to reasoning with bncertainty: Proceedings. 2017 ;[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-3-319-61581-3_40
Vancouver
Cozman FG, Mauá DD. The complexity of inferences and explanations in probabilistic logic programming [Internet]. Symbolic and quantitative approaches to reasoning with bncertainty: Proceedings. 2017 ;[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-3-319-61581-3_40
Trabalho de evento
Computational representation, heterogeneity and integration of production system models (2006)
Arata, Wilson Munemassa; Miyagi, Paulo Eigi
Fonte: Information technology for balanced manufacturing systems. Nome do evento: International Conference on Information Technology for Balanced Automation Systems in Manufacture and Services. Unidade: EP
Assuntos: GEOMETRIA E MODELAGEM COMPUTACIONAL, SISTEMAS DINÂMICOS, SISTEMAS DISCRETOS
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ABNT
ARATA, Wilson Munemassa e MIYAGI, Paulo Eigi. Computational representation, heterogeneity and integration of production system models. 2006, Anais.. New York: Springer, 2006. Disponível em: https://doi.org/10.1007/978-0-387-36594-7_43. Acesso em: 01 out. 2024.
APA
Arata, W. M., & Miyagi, P. E. (2006). Computational representation, heterogeneity and integration of production system models. In Information technology for balanced manufacturing systems. New York: Springer. doi:10.1007/978-0-387-36594-7_43
NLM
Arata WM, Miyagi PE. Computational representation, heterogeneity and integration of production system models [Internet]. Information technology for balanced manufacturing systems. 2006 ;[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-0-387-36594-7_43
Vancouver
Arata WM, Miyagi PE. Computational representation, heterogeneity and integration of production system models [Internet]. Information technology for balanced manufacturing systems. 2006 ;[citado 2024 out. 01 ] Available from: https://doi.org/10.1007/978-0-387-36594-7_43

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