Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Diego C, Nascimento"'
Autor:
Luiz H. Stefano, Diandra B. Favoretto, Diego C. Nascimento, Luan R.A. Santos, Marom Bikson, Joao P. Leite, Octavio M. Pontes-Neto, Dylan J. Edwards, Taiza G.S. Edwards
Publikováno v:
Data in Brief, Vol 45, Iss , Pp 108603- (2022)
This supplementary dataset is supportive of the randomized sham-controlled, double-blind, crossover clinical trial investigating polarity- and intensity-dependent effects of high-definition transcranial electrical stimulation (HD-tDCS) applied over t
Externí odkaz:
https://doaj.org/article/50b90d55b0f34570870c06d7b2de227d
Autor:
Paulo H. Ferreira, Anderson O. Fonseca, Diego C. Nascimento, Estefania Bonnail, Francisco Louzada
Publikováno v:
PLoS ONE, Vol 17, Iss 10 (2022)
Learning techniques involve unraveling regression structures, which aim to analyze in a probabilistic frame the associations across variables of interest. Thus, analyzing fraction and/or proportion data may not be adequate with standard regression pr
Externí odkaz:
https://doaj.org/article/9d3a731438a44b97acc0e409134800de
Autor:
Diego C. Nascimento, Marco A. Pinto-Orellana, Joao P. Leite, Dylan J. Edwards, Francisco Louzada, Taiza E. G. Santos
Publikováno v:
Frontiers in Systems Neuroscience, Vol 14 (2020)
Sparse time series models have shown promise in estimating contemporaneous and ongoing brain connectivity. This paper was motivated by a neuroscience experiment using EEG signals as the outcome of our established interventional protocol, a new method
Externí odkaz:
https://doaj.org/article/26ea8416ae784dbca609cce4572765d3
Autor:
Pedro L Ramos, Diego C Nascimento, Paulo H Ferreira, Karina T Weber, Taiza E G Santos, Francisco Louzada
Publikováno v:
PLoS ONE, Vol 14, Iss 8, p e0221332 (2019)
In this paper, from the practical point of view, we focus on modeling traumatic brain injury data considering different stages of hospitalization, related to patients' survival rates following traumatic brain injury caused by traffic accidents. From
Externí odkaz:
https://doaj.org/article/d77eb7aa4c304368ad4a8e647c511bec
Autor:
Taiza E. G. Santos, Diandra B. Favoretto, Iman Ghodratti Toostani, Diego C. Nascimento, Brunna P. Rimoli, Eduardo Bergonzoni, Tenysson Will Lemos, Dennis Q. Truong, Alexandre C. B. Delbem, Bahador Makkiabadi, Renato Moraes, Francisco Louzada, Marom Bikson, Joao P. Leite, Dylan J. Edwards
Publikováno v:
Frontiers in Neurology, Vol 9 (2018)
Background: Using conventional tDCS over the temporo-parietal junction (TPJ) we previously reported that it is possible to manipulate subjective visual vertical (SVV) and postural control. We also demonstrated that high-definition tDCS (HD-tDCS) can
Externí odkaz:
https://doaj.org/article/21a4bee788df458fb85f5ae97ea5a54d
Autor:
Pedro L. Ramos, Diego C. Nascimento, Camila Cocolo, Márcio J. Nicola, Carlos Alonso, Luiz G. Ribeiro, André Ennes, Francisco Louzada
Publikováno v:
Modelling and Simulation in Engineering, Vol 2018 (2018)
We considered five generalizations of the standard Weibull distribution to describe the lifetime of two important components of sugarcane harvesting machines. The harvesters considered in the analysis harvest an average of 20 tons of sugarcane per ho
Externí odkaz:
https://doaj.org/article/da37f1d38df34982a5507d0133d44e31
Autor:
Diego C. Nascimento, Bruno Barbosa, André M. Perez, Daniel O. Caires, Edgar Hirama, Pedro L. Ramos, Francisco Louzada
Publikováno v:
Entropy, Vol 21, Iss 11, p 1087 (2019)
This work aimed to develop business intelligence towards fraud detection using buyer-placed information combined with the sound analysis from a confirmation purchase call. We used a dataset of 789 orders in 2018, provided by different e-commerce webs
Externí odkaz:
https://doaj.org/article/eb0ebe4bb6ec49eab1ec99315d5ebd88
Autor:
Diego C. Nascimento, Gabriela Depetri, Luiz H. Stefano, Osvaldo Anacleto, Joao P. Leite, Dylan J. Edwards, Taiza E. G. Santos, Francisco Louzada Neto
Publikováno v:
Brain Sciences, Vol 9, Iss 8, p 208 (2019)
A foundation of medical research is time series analysis—the behavior of variables of interest with respect to time. Time series data are often analyzed using the mean, with statistical tests applied to mean differences, and has the assumption that
Externí odkaz:
https://doaj.org/article/cebd65d3be37493e90f204fb10955969
Autor:
Israel José dos Santos Felipe, Diego C. Nascimento, Francisco Louzada Neto, Cleber Martins Xavier
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
The Dynamic Conditional Correlation GARCH (DCC-GARCH) mutation model is considered using a Monte Carlo approach via Markov chains in the estimation of parameters, time-dependence variation is visually demonstrated. Fifteen indices were analyzed from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06655f90ba04f91b5cf8f3181833666b
https://doi.org/10.22237/jmasm/1556669220
https://doi.org/10.22237/jmasm/1556669220
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58b93a570a156bc3e96a7233e22b69ee
https://doi.org/10.1002/asmb.2511
https://doi.org/10.1002/asmb.2511