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Filtros : "IF-FNC" "EACH" Removidos: "Noruega" "Carlson, B V" "Annals of Physics" Limpar

Filtros

USP affiliated authors
- faria, regis rossi alves (1)
- mochizuki, luis (1)
- pennone, juliana (1)
- ramos, júlia baruque (1)
- rizzutto, marcia de almeida (1)

Artigo de periodico
Raw cellulosic fibers: characterization and classifcation by FTIR‑ATR spectroscopy and multivariate analysis (PCA and LDA) (2024)
Santos, Elvis da Cruz ; Silva, Ana Amélia Benedito ; Faria, Regis Rossi Alves ; Rizzutto, Márcia de Almeida ; Rodrigues, Pedro Henrique Sebe ; Ramos, Julia Baruque
Source: Materials Circular Economy. Unidades: EACH, IF, BIOINFORMÁTICA
Assunto: CLASSIFICAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Elvis da Cruz et al. Raw cellulosic fibers: characterization and classifcation by FTIR‑ATR spectroscopy and multivariate analysis (PCA and LDA). Materials Circular Economy, p. 01-14, 2024Tradução . . Disponível em: http://dx.doi.org/10.1007/s42824-024-00104-1. Acesso em: 12 out. 2024.
APA
Santos, E. da C., Silva, A. A. B., Faria, R. R. A., Rizzutto, M. de A., Rodrigues, P. H. S., & Ramos, J. B. (2024). Raw cellulosic fibers: characterization and classifcation by FTIR‑ATR spectroscopy and multivariate analysis (PCA and LDA). Materials Circular Economy, 01-14. doi:10.1007/s42824-024-00104-1
NLM
Santos E da C, Silva AAB, Faria RRA, Rizzutto M de A, Rodrigues PHS, Ramos JB. Raw cellulosic fibers: characterization and classifcation by FTIR‑ATR spectroscopy and multivariate analysis (PCA and LDA) [Internet]. Materials Circular Economy. 2024 ; 01-14.[citado 2024 out. 12 ] Available from: http://dx.doi.org/10.1007/s42824-024-00104-1
Vancouver
Santos E da C, Silva AAB, Faria RRA, Rizzutto M de A, Rodrigues PHS, Ramos JB. Raw cellulosic fibers: characterization and classifcation by FTIR‑ATR spectroscopy and multivariate analysis (PCA and LDA) [Internet]. Materials Circular Economy. 2024 ; 01-14.[citado 2024 out. 12 ] Available from: http://dx.doi.org/10.1007/s42824-024-00104-1
Artigo de periodico
Fall prediction in a quiet standing balance test via machine learning: is it possible? (2024)
Pennone, Juliana ; Aguero, Natasha Fioretto ; Martini, Daniel Marczuk; Mochizuki, Luis ; Suaide, Alexandre Alarcon do Passo
Source: PLoS One. Unidades: EACH, IF, FM
Assunto: IDOSOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PENNONE, Juliana et al. Fall prediction in a quiet standing balance test via machine learning: is it possible?. PLoS One, p. 01-11, 2024Tradução . . Disponível em: http://dx.doi.org/10.1371/journal.pone.0296355. Acesso em: 12 out. 2024.
APA
Pennone, J., Aguero, N. F., Martini, D. M., Mochizuki, L., & Suaide, A. A. do P. (2024). Fall prediction in a quiet standing balance test via machine learning: is it possible? PLoS One, 01-11. doi:10.1371/journal.pone.0296355
NLM
Pennone J, Aguero NF, Martini DM, Mochizuki L, Suaide AA do P. Fall prediction in a quiet standing balance test via machine learning: is it possible? [Internet]. PLoS One. 2024 ; 01-11.[citado 2024 out. 12 ] Available from: http://dx.doi.org/10.1371/journal.pone.0296355
Vancouver
Pennone J, Aguero NF, Martini DM, Mochizuki L, Suaide AA do P. Fall prediction in a quiet standing balance test via machine learning: is it possible? [Internet]. PLoS One. 2024 ; 01-11.[citado 2024 out. 12 ] Available from: http://dx.doi.org/10.1371/journal.pone.0296355

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