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Artigo de periodico
On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments (2024)
Alves, Caroline Lourenço ; Ciba, Manuel ; Toutain, Thaise Graziele Lima de ; Porto, Joel Augusto Moura ; Sena, Eduardo Pondé de ; Thielemann, Christiane ; Rodrigues, Francisco
Source: Journal of Physics: Complexity. Unidades: ICMC, IFSC
Subjects: VISÃO COMPUTACIONAL, APRENDIZADO COMPUTACIONAL, TOPOLOGIA EM COMPUTAÇÃO, REDES NEURAIS, TEORIA DOS GRAFOS, CÓRTEX CEREBRAL (ANÁLISE), CÉREBRO (ANÁLISE;ESTUDO)
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ALVES, Caroline Lourenço et al. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments. Journal of Physics: Complexity, v. 5, n. Ja 2024, p. 015002-1-015002-23, 2024Tradução . . Disponível em: https://doi.org/10.1088/2632-072X/ad1c68. Acesso em: 12 jun. 2024.
APA
Alves, C. L., Ciba, M., Toutain, T. G. L. de, Porto, J. A. M., Sena, E. P. de, Thielemann, C., & Rodrigues, F. (2024). On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments. Journal of Physics: Complexity, 5( Ja 2024), 015002-1-015002-23. doi:10.1088/2632-072X/ad1c68
NLM
Alves CL, Ciba M, Toutain TGL de, Porto JAM, Sena EP de, Thielemann C, Rodrigues F. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments [Internet]. Journal of Physics: Complexity. 2024 ; 5( Ja 2024): 015002-1-015002-23.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/2632-072X/ad1c68
Vancouver
Alves CL, Ciba M, Toutain TGL de, Porto JAM, Sena EP de, Thielemann C, Rodrigues F. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments [Internet]. Journal of Physics: Complexity. 2024 ; 5( Ja 2024): 015002-1-015002-23.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/2632-072X/ad1c68
Artigo de periodico
Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection (2024)
Pazin, Wallance Moreira ; Furini, Leonardo Negri; Braz, Daniel César ; Popolin Neto, Mário ; Fernandes, José Diego ; Constantino, Carlos José Leopoldo ; Oliveira Junior, Osvaldo Novais de
Source: ACS Applied Nano Materials. Unidades: IFSC, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, COVID-19, EFEITO RAMAN
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PAZIN, Wallance Moreira et al. Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection. ACS Applied Nano Materials, v. 7, n. Ja 2024, p. 2335-2342, 2024Tradução . . Disponível em: https://doi.org/10.1021/acsanm.3c05848. Acesso em: 12 jun. 2024.
APA
Pazin, W. M., Furini, L. N., Braz, D. C., Popolin Neto, M., Fernandes, J. D., Constantino, C. J. L., & Oliveira Junior, O. N. de. (2024). Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection. ACS Applied Nano Materials, 7( Ja 2024), 2335-2342. doi:10.1021/acsanm.3c05848
NLM
Pazin WM, Furini LN, Braz DC, Popolin Neto M, Fernandes JD, Constantino CJL, Oliveira Junior ON de. Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection [Internet]. ACS Applied Nano Materials. 2024 ; 7( Ja 2024): 2335-2342.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1021/acsanm.3c05848
Vancouver
Pazin WM, Furini LN, Braz DC, Popolin Neto M, Fernandes JD, Constantino CJL, Oliveira Junior ON de. Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection [Internet]. ACS Applied Nano Materials. 2024 ; 7( Ja 2024): 2335-2342.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1021/acsanm.3c05848
Artigo de periodico
Color-texture classification based on spatio-spectral complex network representations (2024)
Ribas, Lucas Correia ; Scabini, Leonardo Felipe dos Santos ; Condori, Rayner Harold Montes ; Bruno, Odemir Martinez
Source: Physica A. Unidades: IFSC, ICMC
Subjects: REDES NEURAIS, RECONHECIMENTO DE PADRÕES, APRENDIZAGEM PROFUNDA, REDES COMPLEXAS, TEXTURA
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RIBAS, Lucas Correia et al. Color-texture classification based on spatio-spectral complex network representations. Physica A, v. 635, p. 129518-1-129518-15, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.physa.2024.129518. Acesso em: 12 jun. 2024.
APA
Ribas, L. C., Scabini, L. F. dos S., Condori, R. H. M., & Bruno, O. M. (2024). Color-texture classification based on spatio-spectral complex network representations. Physica A, 635, 129518-1-129518-15. doi:10.1016/j.physa.2024.129518
NLM
Ribas LC, Scabini LF dos S, Condori RHM, Bruno OM. Color-texture classification based on spatio-spectral complex network representations [Internet]. Physica A. 2024 ; 635 129518-1-129518-15.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.physa.2024.129518
Vancouver
Ribas LC, Scabini LF dos S, Condori RHM, Bruno OM. Color-texture classification based on spatio-spectral complex network representations [Internet]. Physica A. 2024 ; 635 129518-1-129518-15.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.physa.2024.129518
Artigo de periodico-carta/editorial
History of Chemistry of Materials according to topic evolution based on network analysis and natural language processing. [Editorial] (2024)
Brito, Ana Caroline Medeiros ; Oliveira, Maria Cristina Ferreira de ; Oliveira Junior, Osvaldo Novais de ; Silva, Filipi Nascimento ; Amancio, Diego Raphael
Source: Chemistry of Materials. Unidades: ICMC, IFSC
Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL, DESCOBERTA DE CONHECIMENTO, MINERAÇÃO DE DADOS, CIENTOMETRIA, MATERIAIS
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BRITO, Ana Caroline Medeiros et al. History of Chemistry of Materials according to topic evolution based on network analysis and natural language processing. [Editorial]. Chemistry of Materials. Washington: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. Disponível em: https://doi.org/10.1021/acs.chemmater.3c02962. Acesso em: 12 jun. 2024. , 2024
APA
Brito, A. C. M., Oliveira, M. C. F. de, Oliveira Junior, O. N. de, Silva, F. N., & Amancio, D. R. (2024). History of Chemistry of Materials according to topic evolution based on network analysis and natural language processing. [Editorial]. Chemistry of Materials. Washington: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. doi:10.1021/acs.chemmater.3c02962
NLM
Brito ACM, Oliveira MCF de, Oliveira Junior ON de, Silva FN, Amancio DR. History of Chemistry of Materials according to topic evolution based on network analysis and natural language processing. [Editorial] [Internet]. Chemistry of Materials. 2024 ; 36( Ja 2024): 1-7.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1021/acs.chemmater.3c02962
Vancouver
Brito ACM, Oliveira MCF de, Oliveira Junior ON de, Silva FN, Amancio DR. History of Chemistry of Materials according to topic evolution based on network analysis and natural language processing. [Editorial] [Internet]. Chemistry of Materials. 2024 ; 36( Ja 2024): 1-7.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1021/acs.chemmater.3c02962
Artigo de periodico
Using full-text content to characterize and identify best seller books: a study of early 20th-century literature (2024)
Silva, Giovana Daniele da ; Silva, Filipi Nascimento ; Arruda, Henrique Ferraz de ; Souza, Bárbara Côrtes e ; Costa, Luciano da Fontoura ; Amancio, Diego Raphael
Source: PLOS ONE. Unidades: IFSC, ICMC
Subjects: CIÊNCIA DA COMPUTAÇÃO, REDES NEURAIS, APRENDIZADO COMPUTACIONAL
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SILVA, Giovana Daniele da et al. Using full-text content to characterize and identify best seller books: a study of early 20th-century literature. PLOS ONE, v. 19, n. 4, p. e0302070-1-e0302070-20 + supporting information, 2024Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0302070. Acesso em: 12 jun. 2024.
APA
Silva, G. D. da, Silva, F. N., Arruda, H. F. de, Souza, B. C. e, Costa, L. da F., & Amancio, D. R. (2024). Using full-text content to characterize and identify best seller books: a study of early 20th-century literature. PLOS ONE, 19( 4), e0302070-1-e0302070-20 + supporting information. doi:10.1371/journal.pone.0302070
NLM
Silva GD da, Silva FN, Arruda HF de, Souza BC e, Costa L da F, Amancio DR. Using full-text content to characterize and identify best seller books: a study of early 20th-century literature [Internet]. PLOS ONE. 2024 ; 19( 4): e0302070-1-e0302070-20 + supporting information.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1371/journal.pone.0302070
Vancouver
Silva GD da, Silva FN, Arruda HF de, Souza BC e, Costa L da F, Amancio DR. Using full-text content to characterize and identify best seller books: a study of early 20th-century literature [Internet]. PLOS ONE. 2024 ; 19( 4): e0302070-1-e0302070-20 + supporting information.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1371/journal.pone.0302070
Artigo de periodico
Multidimensional calibration spaces in Staphylococcus Aureus detection using chitosan-based genosensors and electronic tongue (2024)
Soares, Andrey Coatrini ; Soares, Juliana Coatrini ; Popolin Neto, Mário ; Mello, Suelen Scarpa de; Sanches, Edgar Aparecido ; Paulovich, Fernando Vieira ; Oliveira Junior, Osvaldo Novais de ; Mattoso, Luiz Henrique Capparelli
Source: International Journal of Biological Macromolecules. Unidades: IFSC, ICMC
Subjects: STAPHYLOCOCCUS, BACTÉRIAS, POLÍMEROS (MATERIAIS)
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SOARES, Andrey Coatrini et al. Multidimensional calibration spaces in Staphylococcus Aureus detection using chitosan-based genosensors and electronic tongue. International Journal of Biological Macromolecules, v. 271, p. 132460-1-132460-10 + supplementary data, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.ijbiomac.2024.132460. Acesso em: 12 jun. 2024.
APA
Soares, A. C., Soares, J. C., Popolin Neto, M., Mello, S. S. de, Sanches, E. A., Paulovich, F. V., et al. (2024). Multidimensional calibration spaces in Staphylococcus Aureus detection using chitosan-based genosensors and electronic tongue. International Journal of Biological Macromolecules, 271, 132460-1-132460-10 + supplementary data. doi:10.1016/j.ijbiomac.2024.132460
NLM
Soares AC, Soares JC, Popolin Neto M, Mello SS de, Sanches EA, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Multidimensional calibration spaces in Staphylococcus Aureus detection using chitosan-based genosensors and electronic tongue [Internet]. International Journal of Biological Macromolecules. 2024 ; 271 132460-1-132460-10 + supplementary data.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.ijbiomac.2024.132460
Vancouver
Soares AC, Soares JC, Popolin Neto M, Mello SS de, Sanches EA, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Multidimensional calibration spaces in Staphylococcus Aureus detection using chitosan-based genosensors and electronic tongue [Internet]. International Journal of Biological Macromolecules. 2024 ; 271 132460-1-132460-10 + supplementary data.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.ijbiomac.2024.132460
Artigo de periodico
Diagnosis of autism spectrum disorder based on functional brain networks and machine learning (2023)
Alves, Caroline Lourenço ; Oliveira, Thaise Graziele Lima de ; Aguiar, Patricia Maria de Carvalho ; Pineda, Aruane Mello ; Roster, Kirstin ; Thielemann, Christiane ; Porto, Joel Augusto Moura ; Rodrigues, Francisco Aparecido
Source: Scientific Reports. Unidades: ICMC, IFSC
Subjects: TECNOLOGIAS DA SAÚDE, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR
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ALVES, Caroline Lourenço et al. Diagnosis of autism spectrum disorder based on functional brain networks and machine learning. Scientific Reports, v. 13, p. 8072-1-8072-20, 2023Tradução . . Disponível em: https://doi.org/10.1038/s41598-023-34650-6. Acesso em: 12 jun. 2024.
APA
Alves, C. L., Oliveira, T. G. L. de, Aguiar, P. M. de C., Pineda, A. M., Roster, K., Thielemann, C., et al. (2023). Diagnosis of autism spectrum disorder based on functional brain networks and machine learning. Scientific Reports, 13, 8072-1-8072-20. doi:10.1038/s41598-023-34650-6
NLM
Alves CL, Oliveira TGL de, Aguiar PM de C, Pineda AM, Roster K, Thielemann C, Porto JAM, Rodrigues FA. Diagnosis of autism spectrum disorder based on functional brain networks and machine learning [Internet]. Scientific Reports. 2023 ; 13 8072-1-8072-20.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1038/s41598-023-34650-6
Vancouver
Alves CL, Oliveira TGL de, Aguiar PM de C, Pineda AM, Roster K, Thielemann C, Porto JAM, Rodrigues FA. Diagnosis of autism spectrum disorder based on functional brain networks and machine learning [Internet]. Scientific Reports. 2023 ; 13 8072-1-8072-20.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1038/s41598-023-34650-6
Artigo de periodico
A Markov chain for metapopulations of small sizes with attraction landscape (2023)
Silva, Paulo Cesar Ventura da ; Tokuda, Eric Keiji ; Costa, Luciano da Fontoura ; Rodrigues, Francisco Aparecido
Source: Chaos, Solitons and Fractals. Unidades: IFSC, ICMC
Subjects: COMPLEXIDADE, CIÊNCIAS SOCIAIS, MÉTODOS MCMC, CADEIAS DE MARKOV
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SILVA, Paulo Cesar Ventura da et al. A Markov chain for metapopulations of small sizes with attraction landscape. Chaos, Solitons and Fractals, v. 167, p. 113003-1-113003-8, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.chaos.2022.113003. Acesso em: 12 jun. 2024.
APA
Silva, P. C. V. da, Tokuda, E. K., Costa, L. da F., & Rodrigues, F. A. (2023). A Markov chain for metapopulations of small sizes with attraction landscape. Chaos, Solitons and Fractals, 167, 113003-1-113003-8. doi:10.1016/j.chaos.2022.113003
NLM
Silva PCV da, Tokuda EK, Costa L da F, Rodrigues FA. A Markov chain for metapopulations of small sizes with attraction landscape [Internet]. Chaos, Solitons and Fractals. 2023 ; 167 113003-1-113003-8.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.chaos.2022.113003
Vancouver
Silva PCV da, Tokuda EK, Costa L da F, Rodrigues FA. A Markov chain for metapopulations of small sizes with attraction landscape [Internet]. Chaos, Solitons and Fractals. 2023 ; 167 113003-1-113003-8.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.chaos.2022.113003
Artigo de periodico
Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models (2023)
Soares, Andrey Coatrini ; Soares, Juliana Coatrini ; Popolin Neto, Mário ; Mello, Suelen Scarpa de; Pinto, Danielle Dos Santos Cinelli; Carvalho, Wanessa Araújo; Gilmore, Michael Shaffer; Piazzetta, Maria Helena de Oliveira; Gobbi, Angelo Luiz ; Brandão, Humberto de Mello; Paulovich, Fernando Vieira ; Oliveira Junior, Osvaldo Novais de ; Mattoso, Luiz Henrique Capparelli
Source: Chemical Engineering Journal. Unidades: IFSC, ICMC
Subjects: MASTITE ANIMAL, ELETROQUÍMICA, APRENDIZADO COMPUTACIONAL, PECUÁRIA LEITEIRA, MONITORAMENTO AMBIENTAL, STAPHYLOCOCCUS, SENSOR
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SOARES, Andrey Coatrini et al. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models. Chemical Engineering Journal, v. 451, n. Ja 2023, p. 138523-1-138523-9, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.cej.2022.138523. Acesso em: 12 jun. 2024.
APA
Soares, A. C., Soares, J. C., Popolin Neto, M., Mello, S. S. de, Pinto, D. D. S. C., Carvalho, W. A., et al. (2023). Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models. Chemical Engineering Journal, 451( Ja 2023), 138523-1-138523-9. doi:10.1016/j.cej.2022.138523
NLM
Soares AC, Soares JC, Popolin Neto M, Mello SS de, Pinto DDSC, Carvalho WA, Gilmore MS, Piazzetta MH de O, Gobbi AL, Brandão H de M, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models [Internet]. Chemical Engineering Journal. 2023 ; 451( Ja 2023): 138523-1-138523-9.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.cej.2022.138523
Vancouver
Soares AC, Soares JC, Popolin Neto M, Mello SS de, Pinto DDSC, Carvalho WA, Gilmore MS, Piazzetta MH de O, Gobbi AL, Brandão H de M, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models [Internet]. Chemical Engineering Journal. 2023 ; 451( Ja 2023): 138523-1-138523-9.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.cej.2022.138523
Artigo de periodico
Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy (2023)
Neves, Ruan Felipe de Oliveira; Wetterich, Caio Bruno; Sousa, Elaine Parros Machado de ; Marcassa, Luís Gustavo
Source: Laser Physics. Unidades: IFSC, ICMC
Subjects: IMAGEM, PRAGAS DE PLANTAS, ESPECTROSCOPIA
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NEVES, Ruan Felipe de Oliveira et al. Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy. Laser Physics, v. 33, n. 5, p. 055602-1-055602-9, 2023Tradução . . Disponível em: https://doi.org/10.1088/1555-6611/acc6bd. Acesso em: 12 jun. 2024.
APA
Neves, R. F. de O., Wetterich, C. B., Sousa, E. P. M. de, & Marcassa, L. G. (2023). Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy. Laser Physics, 33( 5), 055602-1-055602-9. doi:10.1088/1555-6611/acc6bd
NLM
Neves RF de O, Wetterich CB, Sousa EPM de, Marcassa LG. Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy [Internet]. Laser Physics. 2023 ; 33( 5): 055602-1-055602-9.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/1555-6611/acc6bd
Vancouver
Neves RF de O, Wetterich CB, Sousa EPM de, Marcassa LG. Multiclass classifier based on deep learning for detection of citrus disease using fluorescence imaging spectroscopy [Internet]. Laser Physics. 2023 ; 33( 5): 055602-1-055602-9.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/1555-6611/acc6bd
Artigo de periodico
Exploring ordered patterns in the adjacency matrix for improving machine learning on complex networks (2023)
Neiva, Mariane Barros ; Bruno, Odemir Martinez
Source: Physica A. Unidades: IFSC, ICMC
Subjects: REDES NEURAIS, RECONHECIMENTO DE PADRÕES, APRENDIZAGEM PROFUNDA, REDES COMPLEXAS
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NEIVA, Mariane Barros e BRUNO, Odemir Martinez. Exploring ordered patterns in the adjacency matrix for improving machine learning on complex networks. Physica A, v. 626, p. 129086-1-129086-11, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.physa.2023.129086. Acesso em: 12 jun. 2024.
APA
Neiva, M. B., & Bruno, O. M. (2023). Exploring ordered patterns in the adjacency matrix for improving machine learning on complex networks. Physica A, 626, 129086-1-129086-11. doi:10.1016/j.physa.2023.129086
NLM
Neiva MB, Bruno OM. Exploring ordered patterns in the adjacency matrix for improving machine learning on complex networks [Internet]. Physica A. 2023 ; 626 129086-1-129086-11.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.physa.2023.129086
Vancouver
Neiva MB, Bruno OM. Exploring ordered patterns in the adjacency matrix for improving machine learning on complex networks [Internet]. Physica A. 2023 ; 626 129086-1-129086-11.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.physa.2023.129086
Artigo de periodico
Text characterization based on recurrence networks (2023)
Souza, Bárbara Côrtes e ; Silva, Filipi Nascimento ; Arruda, Henrique Ferraz de ; Silva, Giovana Daniele da ; Costa, Luciano da Fontoura ; Amancio, Diego Raphael
Source: Information Sciences. Unidades: IFSC, ICMC
Subjects: REDES COMPLEXAS, GEOMETRIA E MODELAGEM COMPUTACIONAL
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SOUZA, Bárbara Côrtes e et al. Text characterization based on recurrence networks. Information Sciences, v. 641, p. 119124-1-119124-15, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2023.119124. Acesso em: 12 jun. 2024.
APA
Souza, B. C. e, Silva, F. N., Arruda, H. F. de, Silva, G. D. da, Costa, L. da F., & Amancio, D. R. (2023). Text characterization based on recurrence networks. Information Sciences, 641, 119124-1-119124-15. doi:10.1016/j.ins.2023.119124
NLM
Souza BC e, Silva FN, Arruda HF de, Silva GD da, Costa L da F, Amancio DR. Text characterization based on recurrence networks [Internet]. Information Sciences. 2023 ; 641 119124-1-119124-15.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.ins.2023.119124
Vancouver
Souza BC e, Silva FN, Arruda HF de, Silva GD da, Costa L da F, Amancio DR. Text characterization based on recurrence networks [Internet]. Information Sciences. 2023 ; 641 119124-1-119124-15.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.ins.2023.119124
Artigo de periodico
Cultural heterogeneity constrains diffusion of innovations (2023)
Pineda, Aruane Mello ; Reia, Sandro Martinelli ; Connaughton, Colm ; Fontanari, José Fernando ; Rodrigues, Francisco Aparecido
Source: EPL - Europhysics Letters. Unidades: IFSC, ICMC
Subjects: MODELOS, COMPORTAMENTO SOCIAL (ESTUDO), CONSCIÊNCIA (PERCEPÇÃO), INTELIGÊNCIA COLETIVA, APRENDIZAGEM SOCIAL, FÍSICA TEÓRICA
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PINEDA, Aruane Mello et al. Cultural heterogeneity constrains diffusion of innovations. EPL - Europhysics Letters, v. 143, n. 4, p. 42003-p1-42003-p6, 2023Tradução . . Disponível em: https://doi.org/10.1209/0295-5075/aceeab. Acesso em: 12 jun. 2024.
APA
Pineda, A. M., Reia, S. M., Connaughton, C., Fontanari, J. F., & Rodrigues, F. A. (2023). Cultural heterogeneity constrains diffusion of innovations. EPL - Europhysics Letters, 143( 4), 42003-p1-42003-p6. doi:10.1209/0295-5075/aceeab
NLM
Pineda AM, Reia SM, Connaughton C, Fontanari JF, Rodrigues FA. Cultural heterogeneity constrains diffusion of innovations [Internet]. EPL - Europhysics Letters. 2023 ; 143( 4): 42003-p1-42003-p6.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1209/0295-5075/aceeab
Vancouver
Pineda AM, Reia SM, Connaughton C, Fontanari JF, Rodrigues FA. Cultural heterogeneity constrains diffusion of innovations [Internet]. EPL - Europhysics Letters. 2023 ; 143( 4): 42003-p1-42003-p6.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1209/0295-5075/aceeab
Artigo de periodico
Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning (2023)
Pineda, Aruane Mello ; Rodrigues, Francisco Aparecido ; Alves, Caroline Lourenço ; Möckel, Michael; Oliveira, Thaise Graziele Lima de ; Porto, Joel Augusto Moura
Source: Journal of Complex Networks. Unidades: ICMC, IFSC
Subjects: TECNOLOGIAS DA SAÚDE, APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR, DOENÇAS VASCULARES
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ABNT
PINEDA, Aruane Mello et al. Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning. Journal of Complex Networks, v. 11, n. 5, p. cnad030-1-cnad030-21, 2023Tradução . . Disponível em: https://doi.org/10.1093/comnet/cnad030. Acesso em: 12 jun. 2024.
APA
Pineda, A. M., Rodrigues, F. A., Alves, C. L., Möckel, M., Oliveira, T. G. L. de, & Porto, J. A. M. (2023). Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning. Journal of Complex Networks, 11( 5), cnad030-1-cnad030-21. doi:10.1093/comnet/cnad030
NLM
Pineda AM, Rodrigues FA, Alves CL, Möckel M, Oliveira TGL de, Porto JAM. Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning [Internet]. Journal of Complex Networks. 2023 ; 11( 5): cnad030-1-cnad030-21.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1093/comnet/cnad030
Vancouver
Pineda AM, Rodrigues FA, Alves CL, Möckel M, Oliveira TGL de, Porto JAM. Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning [Internet]. Journal of Complex Networks. 2023 ; 11( 5): cnad030-1-cnad030-21.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1093/comnet/cnad030
Artigo de periodico
Present and future constraints on secluded dark matter in the Galactic Halo with TeV Gamma-ray observatories (2023)
Fortes, Guilherme Nishina; Queiroz, Farinaldo da Silva; Siqueira, Clarissa Martins ; Viana, Aion
Source: Journal of Cosmology and Astroparticle Physics. Unidades: IFSC, ICMC
Subjects: OBSERVATÓRIOS, RAIOS GAMA, MATÉRIA ESCURA, ASTROFÍSICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FORTES, Guilherme Nishina et al. Present and future constraints on secluded dark matter in the Galactic Halo with TeV Gamma-ray observatories. Journal of Cosmology and Astroparticle Physics, v. 2023, p. 043-1-043-18, 2023Tradução . . Disponível em: https://doi.org/10.1088/1475-7516/2023/07/043. Acesso em: 12 jun. 2024.
APA
Fortes, G. N., Queiroz, F. da S., Siqueira, C. M., & Viana, A. (2023). Present and future constraints on secluded dark matter in the Galactic Halo with TeV Gamma-ray observatories. Journal of Cosmology and Astroparticle Physics, 2023, 043-1-043-18. doi:10.1088/1475-7516/2023/07/043
NLM
Fortes GN, Queiroz F da S, Siqueira CM, Viana A. Present and future constraints on secluded dark matter in the Galactic Halo with TeV Gamma-ray observatories [Internet]. Journal of Cosmology and Astroparticle Physics. 2023 ; 2023 043-1-043-18.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/1475-7516/2023/07/043
Vancouver
Fortes GN, Queiroz F da S, Siqueira CM, Viana A. Present and future constraints on secluded dark matter in the Galactic Halo with TeV Gamma-ray observatories [Internet]. Journal of Cosmology and Astroparticle Physics. 2023 ; 2023 043-1-043-18.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/1475-7516/2023/07/043
Artigo de periodico
Quantifying the hierarchical adherence of modular documents (2023)
Benatti, Alexandre ; Brito, Ana Caroline Medeiros ; Amancio, Diego Raphael ; Costa, Luciano da Fontoura
Source: Journal of Physics : Complexity. Unidades: ICMC, IFSC, IME
Subjects: REDES COMPLEXAS, PROCESSAMENTO DE LINGUAGEM NATURAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BENATTI, Alexandre et al. Quantifying the hierarchical adherence of modular documents. Journal of Physics : Complexity, v. 4, n. 4, p. 045008-01-045008-18, 2023Tradução . . Disponível em: https://doi.org/10.1088/2632-072X/ad0a9b. Acesso em: 12 jun. 2024.
APA
Benatti, A., Brito, A. C. M., Amancio, D. R., & Costa, L. da F. (2023). Quantifying the hierarchical adherence of modular documents. Journal of Physics : Complexity, 4( 4), 045008-01-045008-18. doi:10.1088/2632-072X/ad0a9b
NLM
Benatti A, Brito ACM, Amancio DR, Costa L da F. Quantifying the hierarchical adherence of modular documents [Internet]. Journal of Physics : Complexity. 2023 ; 4( 4): 045008-01-045008-18.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/2632-072X/ad0a9b
Vancouver
Benatti A, Brito ACM, Amancio DR, Costa L da F. Quantifying the hierarchical adherence of modular documents [Internet]. Journal of Physics : Complexity. 2023 ; 4( 4): 045008-01-045008-18.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/2632-072X/ad0a9b
Artigo de periodico
Artificial intelligence agents for materials sciences (2023)
Oliveira Junior, Osvaldo Novais de ; Christino, Leonardo Milhomem Franco; Oliveira, Maria Cristina Ferreira de ; Paulovich, Fernando Vieira
Source: Journal of Chemical Information and Modeling. Unidades: IFSC, ICMC
Subjects: ALGORITMOS, APRENDIZADO COMPUTACIONAL, GENÔMICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA JUNIOR, Osvaldo Novais de et al. Artificial intelligence agents for materials sciences. Journal of Chemical Information and Modeling, v. 63, n. 24, p. 7605-7609, 2023Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.3c01778. Acesso em: 12 jun. 2024.
APA
Oliveira Junior, O. N. de, Christino, L. M. F., Oliveira, M. C. F. de, & Paulovich, F. V. (2023). Artificial intelligence agents for materials sciences. Journal of Chemical Information and Modeling, 63( 24), 7605-7609. doi:10.1021/acs.jcim.3c01778
NLM
Oliveira Junior ON de, Christino LMF, Oliveira MCF de, Paulovich FV. Artificial intelligence agents for materials sciences [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63( 24): 7605-7609.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1021/acs.jcim.3c01778
Vancouver
Oliveira Junior ON de, Christino LMF, Oliveira MCF de, Paulovich FV. Artificial intelligence agents for materials sciences [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63( 24): 7605-7609.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1021/acs.jcim.3c01778
Artigo de periodico
Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia (2023)
Alves, Caroline Lourenço ; Oliveira, Thaise Graziele Lima de ; Porto, Joel Augusto Moura ; Aguiar, Patricia Maria de Carvalho ; Sena, Eduardo Pondé de ; Rodrigues, Francisco Aparecido ; Pineda, Aruane Mello ; Thielemann, Christiane
Source: Journal of Neural Engineering. Unidades: ICMC, IFSC
Subjects: TECNOLOGIAS DA SAÚDE, APRENDIZADO COMPUTACIONAL, ESQUIZOFRENIA, REDES COMPLEXAS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR, CÉREBRO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ALVES, Caroline Lourenço et al. Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia. Journal of Neural Engineering, v. 20, n. 5, p. 056025-1-056025-28, 2023Tradução . . Disponível em: https://doi.org/10.1088/1741-2552/acf734. Acesso em: 12 jun. 2024.
APA
Alves, C. L., Oliveira, T. G. L. de, Porto, J. A. M., Aguiar, P. M. de C., Sena, E. P. de, Rodrigues, F. A., et al. (2023). Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia. Journal of Neural Engineering, 20( 5), 056025-1-056025-28. doi:10.1088/1741-2552/acf734
NLM
Alves CL, Oliveira TGL de, Porto JAM, Aguiar PM de C, Sena EP de, Rodrigues FA, Pineda AM, Thielemann C. Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia [Internet]. Journal of Neural Engineering. 2023 ; 20( 5): 056025-1-056025-28.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/1741-2552/acf734
Vancouver
Alves CL, Oliveira TGL de, Porto JAM, Aguiar PM de C, Sena EP de, Rodrigues FA, Pineda AM, Thielemann C. Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia [Internet]. Journal of Neural Engineering. 2023 ; 20( 5): 056025-1-056025-28.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1088/1741-2552/acf734
Artigo de periodico
Network analysis and natural language processing to obtain a landscape of the scientific literature on materials applications (2023)
Brito, Ana Caroline Medeiros ; Oliveira, Maria Cristina Ferreira de ; Oliveira Junior, Osvaldo Novais de ; Silva, Filipi Nascimento ; Amancio, Diego Raphael
Source: ACS Applied Materials and Interfaces. Unidades: ICMC, IFSC
Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DE TEXTO, DESCOBERTA DE CONHECIMENTO, MINERAÇÃO DE DADOS, MATERIAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BRITO, Ana Caroline Medeiros et al. Network analysis and natural language processing to obtain a landscape of the scientific literature on materials applications. ACS Applied Materials and Interfaces, v. 15, n. 23, p. 27437-27446, 2023Tradução . . Disponível em: https://doi.org/10.1021/acsami.3c01632. Acesso em: 12 jun. 2024.
APA
Brito, A. C. M., Oliveira, M. C. F. de, Oliveira Junior, O. N. de, Silva, F. N., & Amancio, D. R. (2023). Network analysis and natural language processing to obtain a landscape of the scientific literature on materials applications. ACS Applied Materials and Interfaces, 15( 23), 27437-27446. doi:10.1021/acsami.3c01632
NLM
Brito ACM, Oliveira MCF de, Oliveira Junior ON de, Silva FN, Amancio DR. Network analysis and natural language processing to obtain a landscape of the scientific literature on materials applications [Internet]. ACS Applied Materials and Interfaces. 2023 ; 15( 23): 27437-27446.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1021/acsami.3c01632
Vancouver
Brito ACM, Oliveira MCF de, Oliveira Junior ON de, Silva FN, Amancio DR. Network analysis and natural language processing to obtain a landscape of the scientific literature on materials applications [Internet]. ACS Applied Materials and Interfaces. 2023 ; 15( 23): 27437-27446.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1021/acsami.3c01632
Artigo de periodico
Finding contrasting patterns in rhythmic properties between prose and poetry (2022)
Arruda, Henrique Ferraz de ; Reia, Sandro Martinelli ; Silva, Filipi Nascimento ; Amancio, Diego Raphael ; Costa, Luciano da Fontoura
Source: Physica A. Unidades: ICMC, IFSC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, ANÁLISE DE SÉRIES TEMPORAIS, RECONHECIMENTO DE TEXTO, TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ARRUDA, Henrique Ferraz de et al. Finding contrasting patterns in rhythmic properties between prose and poetry. Physica A, v. 598, p. 127387-1-127387-13, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.physa.2022.127387. Acesso em: 12 jun. 2024.
APA
Arruda, H. F. de, Reia, S. M., Silva, F. N., Amancio, D. R., & Costa, L. da F. (2022). Finding contrasting patterns in rhythmic properties between prose and poetry. Physica A, 598, 127387-1-127387-13. doi:10.1016/j.physa.2022.127387
NLM
Arruda HF de, Reia SM, Silva FN, Amancio DR, Costa L da F. Finding contrasting patterns in rhythmic properties between prose and poetry [Internet]. Physica A. 2022 ; 598 127387-1-127387-13.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.physa.2022.127387
Vancouver
Arruda HF de, Reia SM, Silva FN, Amancio DR, Costa L da F. Finding contrasting patterns in rhythmic properties between prose and poetry [Internet]. Physica A. 2022 ; 598 127387-1-127387-13.[citado 2024 jun. 12 ] Available from: https://doi.org/10.1016/j.physa.2022.127387

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