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  • Source: Computational and Applied Mathematics. Unidade: ICMC

    Subjects: ALGORITMOS, TOPOLOGIA COMBINATÓRIA, ANÁLISE DE DESEMPENHO

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      CASTELO, Antonio et al. A generalized combinatorial marching hypercube algorithm. Computational and Applied Mathematics, v. 43, p. 1-23, 2024Tradução . . Disponível em: https://doi.org/10.1007/s40314-024-02627-4. Acesso em: 09 nov. 2024.
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      Castelo, A., Nakassima, G. K., Bueno, L. M., & Gameiro, M. F. (2024). A generalized combinatorial marching hypercube algorithm. Computational and Applied Mathematics, 43, 1-23. doi:10.1007/s40314-024-02627-4
    • NLM

      Castelo A, Nakassima GK, Bueno LM, Gameiro MF. A generalized combinatorial marching hypercube algorithm [Internet]. Computational and Applied Mathematics. 2024 ; 43 1-23.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s40314-024-02627-4
    • Vancouver

      Castelo A, Nakassima GK, Bueno LM, Gameiro MF. A generalized combinatorial marching hypercube algorithm [Internet]. Computational and Applied Mathematics. 2024 ; 43 1-23.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s40314-024-02627-4
  • Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, VISUALIZAÇÃO, MODELOS PARA PROCESSOS ESTOCÁSTICOS

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      XENOPOULOS, Peter et al. Calibrate: interactive analysis of probabilistic model output. IEEE Transactions on Visualization and Computer Graphics, v. 29, n. Ja 2023, p. 853-863, 2023Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2022.3209489. Acesso em: 09 nov. 2024.
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      Xenopoulos, P., Rulff, J., Nonato, L. G., Barr, B., & Silva, C. (2023). Calibrate: interactive analysis of probabilistic model output. IEEE Transactions on Visualization and Computer Graphics, 29( Ja 2023), 853-863. doi:10.1109/TVCG.2022.3209489
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      Xenopoulos P, Rulff J, Nonato LG, Barr B, Silva C. Calibrate: interactive analysis of probabilistic model output [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( Ja 2023): 853-863.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/TVCG.2022.3209489
    • Vancouver

      Xenopoulos P, Rulff J, Nonato LG, Barr B, Silva C. Calibrate: interactive analysis of probabilistic model output [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( Ja 2023): 853-863.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/TVCG.2022.3209489
  • Source: Boundary-Layer Meteorology. Unidade: ICMC

    Subjects: TURBULÊNCIA ATMOSFÉRICA, ESPECTROS, TÚNEIS DE VENTO

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      FREIRE, Lívia Souza e CHAMECKI, Marcelo e PATTON, Edward Garrett. Atmospheric small-scale turbulence from three-dimensional hot-film data. Boundary-Layer Meteorology, v. 189, p. 77-101, 2023Tradução . . Disponível em: https://doi.org/10.1007/s10546-023-00826-w. Acesso em: 09 nov. 2024.
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      Freire, L. S., Chamecki, M., & Patton, E. G. (2023). Atmospheric small-scale turbulence from three-dimensional hot-film data. Boundary-Layer Meteorology, 189, 77-101. doi:10.1007/s10546-023-00826-w
    • NLM

      Freire LS, Chamecki M, Patton EG. Atmospheric small-scale turbulence from three-dimensional hot-film data [Internet]. Boundary-Layer Meteorology. 2023 ; 189 77-101.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10546-023-00826-w
    • Vancouver

      Freire LS, Chamecki M, Patton EG. Atmospheric small-scale turbulence from three-dimensional hot-film data [Internet]. Boundary-Layer Meteorology. 2023 ; 189 77-101.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10546-023-00826-w
  • Source: Biometrical Journal. Unidades: ICMC, INTER: ICMC -UFSCAR

    Subjects: FRAMEWORKS, INFERÊNCIA BAYESIANA, RESPOSTAS

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      OLIVEIRA, Eduardo Schneider Bueno de e WANG, Xiaojing e BAZÁN GUZMÁN, Jorge Luis. A classification model for continuous responses: identifying risk perception groups on health-related activities. Biometrical Journal, v. 65, n. 4, p. 1-22, 2023Tradução . . Disponível em: https://doi.org/10.1002/bimj.202100222. Acesso em: 09 nov. 2024.
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      Oliveira, E. S. B. de, Wang, X., & Bazán Guzmán, J. L. (2023). A classification model for continuous responses: identifying risk perception groups on health-related activities. Biometrical Journal, 65( 4), 1-22. doi:10.1002/bimj.202100222
    • NLM

      Oliveira ESB de, Wang X, Bazán Guzmán JL. A classification model for continuous responses: identifying risk perception groups on health-related activities [Internet]. Biometrical Journal. 2023 ; 65( 4): 1-22.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1002/bimj.202100222
    • Vancouver

      Oliveira ESB de, Wang X, Bazán Guzmán JL. A classification model for continuous responses: identifying risk perception groups on health-related activities [Internet]. Biometrical Journal. 2023 ; 65( 4): 1-22.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1002/bimj.202100222
  • Source: IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM. Unidade: ICMC

    Subjects: PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), APRENDIZADO COMPUTACIONAL, REDES NEURAIS, TEORIA DOS GRAFOS

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      SPADON, Gabriel et al. Pay attention to evolution: time series forecasting with deep graph-evolution learning. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM, v. 44, n. 9, p. Se 2022, 2022Tradução . . Disponível em: https://doi.org/10.1109/TPAMI.2021.3076155. Acesso em: 09 nov. 2024.
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      Spadon, G., Hong, S., Machado, B. B., Matwin, S., Rodrigues Junior, J. F., & Sun, J. (2022). Pay attention to evolution: time series forecasting with deep graph-evolution learning. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM, 44( 9), Se 2022. doi:10.1109/TPAMI.2021.3076155
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      Spadon G, Hong S, Machado BB, Matwin S, Rodrigues Junior JF, Sun J. Pay attention to evolution: time series forecasting with deep graph-evolution learning [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM. 2022 ; 44( 9): Se 2022.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/TPAMI.2021.3076155
    • Vancouver

      Spadon G, Hong S, Machado BB, Matwin S, Rodrigues Junior JF, Sun J. Pay attention to evolution: time series forecasting with deep graph-evolution learning [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM. 2022 ; 44( 9): Se 2022.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/TPAMI.2021.3076155
  • Source: Applied Numerical Mathematics. Unidade: ICMC

    Subjects: PROBLEMAS DE CONTORNO, TEOREMAS LIMITES

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      RAMOS, Eduardo e NOLASCO, Victor Hugo e GAMEIRO, Márcio Fuzeto. Rigorous enclosures of solutions of Neumann boundary value problems. Applied Numerical Mathematics, v. 180, p. 104-119, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.apnum.2022.05.011. Acesso em: 09 nov. 2024.
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      Ramos, E., Nolasco, V. H., & Gameiro, M. F. (2022). Rigorous enclosures of solutions of Neumann boundary value problems. Applied Numerical Mathematics, 180, 104-119. doi:10.1016/j.apnum.2022.05.011
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      Ramos E, Nolasco VH, Gameiro MF. Rigorous enclosures of solutions of Neumann boundary value problems [Internet]. Applied Numerical Mathematics. 2022 ; 180 104-119.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.apnum.2022.05.011
    • Vancouver

      Ramos E, Nolasco VH, Gameiro MF. Rigorous enclosures of solutions of Neumann boundary value problems [Internet]. Applied Numerical Mathematics. 2022 ; 180 104-119.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.apnum.2022.05.011
  • Source: IEEE Robotics and Automation Letters. Unidade: ICMC

    Subjects: ROBÓTICA, VISÃO COMPUTACIONAL, AERONAVES NÃO TRIPULADAS

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      LIU, Xu et al. Large-scale autonomous flight with real-time semantic SLAM under dense forest canopy. IEEE Robotics and Automation Letters, v. 7, n. 2, p. 5512-5519, 2022Tradução . . Disponível em: https://doi.org/10.1109/LRA.2022.3154047. Acesso em: 09 nov. 2024.
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      Liu, X., Nardari, G. V., Ojeda, F. C., Tao, Y., Zhou, A., Donnelly, T., et al. (2022). Large-scale autonomous flight with real-time semantic SLAM under dense forest canopy. IEEE Robotics and Automation Letters, 7( 2), 5512-5519. doi:10.1109/LRA.2022.3154047
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      Liu X, Nardari GV, Ojeda FC, Tao Y, Zhou A, Donnelly T, Qu C, Chen SW, Romero RAF, Taylor CJ, Kumar V. Large-scale autonomous flight with real-time semantic SLAM under dense forest canopy [Internet]. IEEE Robotics and Automation Letters. 2022 ; 7( 2): 5512-5519.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/LRA.2022.3154047
    • Vancouver

      Liu X, Nardari GV, Ojeda FC, Tao Y, Zhou A, Donnelly T, Qu C, Chen SW, Romero RAF, Taylor CJ, Kumar V. Large-scale autonomous flight with real-time semantic SLAM under dense forest canopy [Internet]. IEEE Robotics and Automation Letters. 2022 ; 7( 2): 5512-5519.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1109/LRA.2022.3154047
  • Source: Atmospheric Environment. Unidade: ICMC

    Subjects: TURBULÊNCIA ATMOSFÉRICA, DINÂMICA DOS FLUÍDOS COMPUTACIONAL, HIDROCARBONETOS, FLORESTAS TROPICAIS, AMAZÔNIA

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      FUENTES, Jose D et al. Turbulent transport and reactions of plant-emitted hydrocarbons in an Amazonian rain forest. Atmospheric Environment, v. 279, p. 1-13, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.atmosenv.2022.119094. Acesso em: 09 nov. 2024.
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      Fuentes, J. D., Gerken, T., Chamecki, M., Stoy, P. C., Freire, L. S., & Ruiz-Plancarte, J. (2022). Turbulent transport and reactions of plant-emitted hydrocarbons in an Amazonian rain forest. Atmospheric Environment, 279, 1-13. doi:10.1016/j.atmosenv.2022.119094
    • NLM

      Fuentes JD, Gerken T, Chamecki M, Stoy PC, Freire LS, Ruiz-Plancarte J. Turbulent transport and reactions of plant-emitted hydrocarbons in an Amazonian rain forest [Internet]. Atmospheric Environment. 2022 ; 279 1-13.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.atmosenv.2022.119094
    • Vancouver

      Fuentes JD, Gerken T, Chamecki M, Stoy PC, Freire LS, Ruiz-Plancarte J. Turbulent transport and reactions of plant-emitted hydrocarbons in an Amazonian rain forest [Internet]. Atmospheric Environment. 2022 ; 279 1-13.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.atmosenv.2022.119094
  • Source: Computers and Graphics. Unidade: ICMC

    Subjects: COMPUTAÇÃO GRÁFICA, ALGORITMOS ÚTEIS E ESPECÍFICOS

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      CASTELO, Antonio e BUENO, Lucas Moutinho e GAMEIRO, Márcio Fuzeto. A combinatorial marching hypercubes algorithm. Computers and Graphics, v. 102, p. 67-77, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.cag.2021.10.023. Acesso em: 09 nov. 2024.
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      Castelo, A., Bueno, L. M., & Gameiro, M. F. (2022). A combinatorial marching hypercubes algorithm. Computers and Graphics, 102, 67-77. doi:10.1016/j.cag.2021.10.023
    • NLM

      Castelo A, Bueno LM, Gameiro MF. A combinatorial marching hypercubes algorithm [Internet]. Computers and Graphics. 2022 ; 102 67-77.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.cag.2021.10.023
    • Vancouver

      Castelo A, Bueno LM, Gameiro MF. A combinatorial marching hypercubes algorithm [Internet]. Computers and Graphics. 2022 ; 102 67-77.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.cag.2021.10.023
  • Source: PLoS Computational Biology. Unidade: ICMC

    Subjects: HIPÓTESE, EXPRESSÃO GÊNICA, ANÁLISE DE SÉRIES TEMPORAIS

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      CUMMINS, Breschine et al. Experimental guidance for discovering genetic networks through hypothesis reduction on time series. PLoS Computational Biology, v. 18, n. 10, p. 1-31, 2022Tradução . . Disponível em: https://doi.org/10.1371/journal.pcbi.1010145. Acesso em: 09 nov. 2024.
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      Cummins, B., Motta, F. C., Moseley, R. C., Deckard, A., Campione, S., Gameiro, M. F., et al. (2022). Experimental guidance for discovering genetic networks through hypothesis reduction on time series. PLoS Computational Biology, 18( 10), 1-31. doi:10.1371/journal.pcbi.1010145
    • NLM

      Cummins B, Motta FC, Moseley RC, Deckard A, Campione S, Gameiro MF, Gedeon T, Mischaikow K, Haase S. Experimental guidance for discovering genetic networks through hypothesis reduction on time series [Internet]. PLoS Computational Biology. 2022 ; 18( 10): 1-31.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1371/journal.pcbi.1010145
    • Vancouver

      Cummins B, Motta FC, Moseley RC, Deckard A, Campione S, Gameiro MF, Gedeon T, Mischaikow K, Haase S. Experimental guidance for discovering genetic networks through hypothesis reduction on time series [Internet]. PLoS Computational Biology. 2022 ; 18( 10): 1-31.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1371/journal.pcbi.1010145
  • Source: Sensors. Unidade: ICMC

    Subjects: TEORIA DOS CONJUNTOS, VISUALIZAÇÃO, ACIDENTE VASCULAR CEREBRAL

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      CONTRERAS, Rodrigo Colnago et al. NE-Motion: visual analysis of stroke patients using motion sensor networks. Sensors, v. 21, p. 1-22, 2021Tradução . . Disponível em: https://doi.org/10.3390/s21134482. Acesso em: 09 nov. 2024.
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      Contreras, R. C., Parnandi, A., Coelho, B. G., Silva, C., Schambra, H., & Nonato, L. G. (2021). NE-Motion: visual analysis of stroke patients using motion sensor networks. Sensors, 21, 1-22. doi:10.3390/s21134482
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      Contreras RC, Parnandi A, Coelho BG, Silva C, Schambra H, Nonato LG. NE-Motion: visual analysis of stroke patients using motion sensor networks [Internet]. Sensors. 2021 ; 21 1-22.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/s21134482
    • Vancouver

      Contreras RC, Parnandi A, Coelho BG, Silva C, Schambra H, Nonato LG. NE-Motion: visual analysis of stroke patients using motion sensor networks [Internet]. Sensors. 2021 ; 21 1-22.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/s21134482
  • Source: Knowledge and Information Systems. Unidade: ICMC

    Subjects: MINERAÇÃO DE DADOS, APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS

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      SOUZA, Vinícius Mourão Alves de et al. Efficient unsupervised drift detector for fast and high-dimensional data streams. Knowledge and Information Systems, v. 63, n. 6, p. 1497-1527, 2021Tradução . . Disponível em: https://doi.org/10.1007/s10115-021-01564-6. Acesso em: 09 nov. 2024.
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      Souza, V. M. A. de, Parmezan, A. R. S., Chowdhury, F. A., & Mueen, A. (2021). Efficient unsupervised drift detector for fast and high-dimensional data streams. Knowledge and Information Systems, 63( 6), 1497-1527. doi:10.1007/s10115-021-01564-6
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      Souza VMA de, Parmezan ARS, Chowdhury FA, Mueen A. Efficient unsupervised drift detector for fast and high-dimensional data streams [Internet]. Knowledge and Information Systems. 2021 ; 63( 6): 1497-1527.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10115-021-01564-6
    • Vancouver

      Souza VMA de, Parmezan ARS, Chowdhury FA, Mueen A. Efficient unsupervised drift detector for fast and high-dimensional data streams [Internet]. Knowledge and Information Systems. 2021 ; 63( 6): 1497-1527.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s10115-021-01564-6
  • Source: Information Visualization. Unidade: ICMC

    Subjects: SIMULAÇÃO (ESTATÍSTICA), ANÁLISE DE SÉRIES TEMPORAIS, TERREMOTOS

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      ZHAO, Zhenge et al. STFT-LDA: an algorithm to facilitate the visual analysis of building seismic responses. Information Visualization, v. 20, n. 4, p. 263-282, 2021Tradução . . Disponível em: https://doi.org/10.1177/14738716211038618. Acesso em: 09 nov. 2024.
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      Zhao, Z., Motta, D. A., Berger, M., Levine, J. A., Kuzucu, I. B., Fleischman, R. B., et al. (2021). STFT-LDA: an algorithm to facilitate the visual analysis of building seismic responses. Information Visualization, 20( 4), 263-282. doi:10.1177/14738716211038618
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      Zhao Z, Motta DA, Berger M, Levine JA, Kuzucu IB, Fleischman RB, Paiva A, Scheidegger C. STFT-LDA: an algorithm to facilitate the visual analysis of building seismic responses [Internet]. Information Visualization. 2021 ; 20( 4): 263-282.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1177/14738716211038618
    • Vancouver

      Zhao Z, Motta DA, Berger M, Levine JA, Kuzucu IB, Fleischman RB, Paiva A, Scheidegger C. STFT-LDA: an algorithm to facilitate the visual analysis of building seismic responses [Internet]. Information Visualization. 2021 ; 20( 4): 263-282.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1177/14738716211038618
  • Source: Oecologia. Unidade: ICMC

    Subjects: ECOLOGIA MATEMÁTICA, MODELOS MATEMÁTICOS, COMPOSTOS VOLÁTEIS, METANOL, FLORESTAS

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      STOY, Paul C et al. Vapor pressure deficit helps explain biogenic volatile organic compound fluxes from the forest floor and canopy of a temperate deciduous forest. Oecologia, v. 197, n. 4, p. 971-988, 2021Tradução . . Disponível em: https://doi.org/10.1007/s00442-021-04891-1. Acesso em: 09 nov. 2024.
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      Stoy, P. C., Trowbridge, A. M., Siqueira, M. B., Freire, L. S., Phillips, R. P., Jacobs, L., et al. (2021). Vapor pressure deficit helps explain biogenic volatile organic compound fluxes from the forest floor and canopy of a temperate deciduous forest. Oecologia, 197( 4), 971-988. doi:10.1007/s00442-021-04891-1
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      Stoy PC, Trowbridge AM, Siqueira MB, Freire LS, Phillips RP, Jacobs L, Wiesner S, Monson RK, Novick KA. Vapor pressure deficit helps explain biogenic volatile organic compound fluxes from the forest floor and canopy of a temperate deciduous forest [Internet]. Oecologia. 2021 ; 197( 4): 971-988.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s00442-021-04891-1
    • Vancouver

      Stoy PC, Trowbridge AM, Siqueira MB, Freire LS, Phillips RP, Jacobs L, Wiesner S, Monson RK, Novick KA. Vapor pressure deficit helps explain biogenic volatile organic compound fluxes from the forest floor and canopy of a temperate deciduous forest [Internet]. Oecologia. 2021 ; 197( 4): 971-988.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1007/s00442-021-04891-1
  • Source: Computers and Fluids. Unidade: ICMC

    Subjects: TURBULÊNCIA ATMOSFÉRICA, SISTEMAS DINÂMICOS, MODELOS PARA PROCESSOS ESTOCÁSTICOS, DINÂMICA DOS FLUÍDOS

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      FREIRE, Lívia Souza e CHAMECKI, Marcelo. Large-eddy simulation of smooth and rough channel flows using a one-dimensional stochastic wall model. Computers and Fluids, v. No 2021, p. 1-17, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.compfluid.2021.105135. Acesso em: 09 nov. 2024.
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      Freire, L. S., & Chamecki, M. (2021). Large-eddy simulation of smooth and rough channel flows using a one-dimensional stochastic wall model. Computers and Fluids, No 2021, 1-17. doi:10.1016/j.compfluid.2021.105135
    • NLM

      Freire LS, Chamecki M. Large-eddy simulation of smooth and rough channel flows using a one-dimensional stochastic wall model [Internet]. Computers and Fluids. 2021 ; No 2021 1-17.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.compfluid.2021.105135
    • Vancouver

      Freire LS, Chamecki M. Large-eddy simulation of smooth and rough channel flows using a one-dimensional stochastic wall model [Internet]. Computers and Fluids. 2021 ; No 2021 1-17.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1016/j.compfluid.2021.105135
  • Source: International Journal of Electrical Power & Energy Systems. Unidade: EESC

    Subjects: CIBERNÉTICA, REDES DE DISTRIBUIÇÃO DE ENERGIA ELÉTRICA, ENGENHARIA ELÉTRICA

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      BRETAS, Arturo Suman e BRETAS, Newton Geraldo e CARVALHO, Breno Elias Bretas de. Further contributions to smart grids cyber-physical security as a malicious data attack: proof and properties of the parameter error spreading out to the measurements and a relaxed correction model. International Journal of Electrical Power & Energy Systems, v. 104, p. 43-51, 2019Tradução . . Disponível em: http://dx.doi.org/10.1016/j.ijepes.2018.06.039. Acesso em: 09 nov. 2024.
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      Bretas, A. S., Bretas, N. G., & Carvalho, B. E. B. de. (2019). Further contributions to smart grids cyber-physical security as a malicious data attack: proof and properties of the parameter error spreading out to the measurements and a relaxed correction model. International Journal of Electrical Power & Energy Systems, 104, 43-51. doi:10.1016/j.ijepes.2018.06.039
    • NLM

      Bretas AS, Bretas NG, Carvalho BEB de. Further contributions to smart grids cyber-physical security as a malicious data attack: proof and properties of the parameter error spreading out to the measurements and a relaxed correction model [Internet]. International Journal of Electrical Power & Energy Systems. 2019 ; 104 43-51.[citado 2024 nov. 09 ] Available from: http://dx.doi.org/10.1016/j.ijepes.2018.06.039
    • Vancouver

      Bretas AS, Bretas NG, Carvalho BEB de. Further contributions to smart grids cyber-physical security as a malicious data attack: proof and properties of the parameter error spreading out to the measurements and a relaxed correction model [Internet]. International Journal of Electrical Power & Energy Systems. 2019 ; 104 43-51.[citado 2024 nov. 09 ] Available from: http://dx.doi.org/10.1016/j.ijepes.2018.06.039

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