Results 11 to 20 of about 2,114,322 (282)

Disruption of Cerebellar Prediction in Verbal Working Memory [PDF]

Frontiers in Human Neuroscience, 2019
Mounting evidence suggests that the right cerebellum contributes to verbal working memory, but the functional role of this contribution remains unclear. In an established theory of motor control, the cerebellum is thought to predict sensory consequences ...
Yi-Shin Sheu, Yu Liang, John E. Desmond
doaj   +3 more sources

Adaptive anomaly detection disruption prediction starting from first discharge on tokamak

Nuclear Fusion
Plasma disruption presents a significant challenge in tokamak fusion, especially in large-size devices like ITER, where it causes severe damage. While current data-driven machine learning methods perform well in disruption prediction, they require ...
X.K. Ai, W. Zheng, M. Zhang, Y.H. Ding, D.L. Chen, Z.Y. Chen, B.H. Guo, C.S. Shen, N.C. Wang, Z.J. Yang, Z.P. Chen, Y. Pan, B. Shen, B.J. Xiao, J-TEXT team   +14 more
doaj   +2 more sources

Cross-tokamak disruption prediction based on domain adaptation

Nuclear Fusion
The high acquisition cost and the significant demand for disruptive discharges for data-driven disruption prediction models in future tokamaks pose an inherent contradiction in disruption prediction research.
Chengshuo Shen, Wei Zheng, Bihao Guo, Yonghua Ding, Dalong Chen, Xinkun Ai, Fengming Xue, Yu Zhong, Nengchao Wang, Biao Shen, Binjia Xiao, Zhongyong Chen, Yuan Pan, J-TEXT Team   +13 more
doaj   +2 more sources

Real-time data-driven disruption prediction and its mitigation of MA-plasma experiments in KSTAR with a lower carbon divertor

Nuclear Fusion
Real-time disruption prediction and its mitigation of mega-ampere (MA) plasma experiments have been performed in the 2022 KSTAR carbon lower divertor condition.
Jeongwon Lee, Sang-hee Hahn, Hyunsun Han, Jayhyun Kim, June-Woo Juhn, Jun-Gyo Bak, Jae-in Song, YongUn Nam   +7 more
doaj   +2 more sources

Machine Learning for Plasma Disruption Prediction in TCABR

IEEE Access
Plasma disruptions are one of the most critical challenges in tokamak operations, as they can severely damage reactor components and compromise fusion performance.
Vinicius M. Neto, Felipe V. De Almeida, Wanderley P. De Sa, Jose H. F. Severo   +3 more
doaj   +2 more sources

Travel Disruption: Three Case Studies [PDF]

This report draws together the findings of three studies of travel disruption and its impacts on travellers: the volcanic ash cloud which disrupted aviation in Europe in 2010, the loss of road bridges between November 2009 and April 2010 at Workington ...
Guiver, Jo W, Disruption Project
core   +6 more sources

A machine-learning approach for disruption prediction

, 2016
A machine-learning approach for disruption prediction.
Pau A., Aledda R., Cannas B., Fanni A., Sias G., Mele D., Pisano G., Murari A., Coda S., Baruzzo M., de Vries P. C., Drewelow P., Gerasimov S., Joffrin E., Nunes I., Pautasso G., Rimini F., Tsalas M., JET contributors, the ASDEX Upgrade Team, the EUROfusion MST1 Team   +20 more
openaire   +2 more sources

Prediction of the endocrine disruption profile of pesticides [PDF]

SAR and QSAR in Environmental Research, 2015
Numerous manmade chemicals released into the environment can interfere with normal, hormonally regulated biological processes to adversely affect the development and reproductive functions of living species. Various in vivo and in vitro tests have been designed for detecting endocrine disruptors, but the number of chemicals to test is so high that to ...
J, Devillers, E, Bro, F, Millot
openaire   +2 more sources

TMS Over V5 Disrupts Motion Prediction [PDF]

Cerebral Cortex, 2013
Given the vast amount of sensory information the brain has to deal with, predicting some of this information based on the current context is a resource-efficient strategy. The framework of predictive coding states that higher-level brain areas generate a predictive model to be communicated via feedback connections to early sensory areas.
Vetter, Petra, Grosbras, Marie-Helene, Muckli, Lars   +2 more
openaire   +5 more sources

Cerebellar rTMS disrupts predictive language processing [PDF]

Current Biology, 2012
The human cerebellum plays an important role in language, amongst other cognitive and motor functions [1], but a unifying theoretical framework about cerebellar language function is lacking. In an established model of motor control, the cerebellum is seen as a predictive machine, making short-term estimations about the outcome of motor commands.
Lesage, E., Morgan, B., Olson, A., Meyer, A., Miall, R.   +4 more
openaire   +3 more sources