Zobrazeno 1 - 10
of 228
pro vyhledávání: '"X P, Liang"'
Autor:
Shiqi Yu, Bin Mao, Yuanhang Zhou, Yunhong Liu, Chanlin Yi, Fali Li, Dezhong Yao, Peng Xu, X. San Liang, Tao Zhang
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 2187-2197 (2024)
Motor imagery (MI) is a high-level cognitive process that has been widely applied to clinical rehabilitation and brain-computer interfaces (BCIs). However, the decoding of MI tasks still faces challenges, and the neural mechanisms underlying its appl
Externí odkaz:
https://doaj.org/article/9cef0e2ca405494eb0090c0e10c67ed2
Autor:
Y. Zhao, J. C. Liu, S. L. Xiong, W. C. Xue, Q. B. Yi, G. P. Lu, W. Xu, F. C. Lyu, J. C. Sun, W. X. Peng, C. Zheng, Y. Q. Zhang, C. Cai, S. Xiao, S. L. Xie, C. W. Wang, W. J. Tan, Z. H. An, G. Chen, Y. Q. Du, Y. Huang, M. Gao, K. Gong, D. Y. Guo, J. J. He, B. Li, G. Li, X. Q. Li, X. B. Li, J. Y. Liao, J. Liang, X. H. Liang, Y. Q. Liu, X. Ma, R. Qiao, L. M. Song, X. Y. Song, X. L. Sun, J. Wang, J. Z. Wang, P. Wang, X. Y. Wen, H. Wu, Y. B. Xu, S. Yang, B. X. Zhang, D. L. Zhang, F. Zhang, P. Zhang, H. M. Zhang, Z. Zhang, X. Y. Zhao, S. J. Zheng, K. K. Zhang, X. B. Han, H. Y. Wu, T. Hu, H. Geng, H. B. Zhang, F. J. Lu, S. N. Zhang, H. Yu
Publikováno v:
Geophysical Research Letters, Vol 50, Iss 14, Pp n/a-n/a (2023)
Abstract Gravitational‐wave high‐energy Electromagnetic Counterpart All‐sky Monitor (GECAM) is a space‐borne instrument dedicated to monitoring high‐energy transients, including Terrestrial Gamma‐ray Flashes (TGFs) and Terrestrial Electro
Externí odkaz:
https://doaj.org/article/4df1c9db46fe42fd97a533da9c579c60
Autor:
Jiwang Ma, X. San Liang
Publikováno v:
Geophysical Research Letters, Vol 50, Iss 10, Pp n/a-n/a (2023)
Abstract Positive feedback between high‐frequency eddies and low‐frequency processes is believed to play an essential role in the NAO evolution. In this study, however, it is found that the previously well‐studied upscale forcing to the intrase
Externí odkaz:
https://doaj.org/article/33a0f1c0512548aa80b9c92978aa732d
Publikováno v:
Journal of Applied Fluid Mechanics, Vol 15, Iss 5, Pp 1403-1416 (2022)
In previous studies, researchers established mathematical models for predicting the pressure coefficient in simple cavities and tubed vortex reducers based on the assumptions of incompressibility and adiabatic reversibility. However, these mathematic
Externí odkaz:
https://doaj.org/article/df7ab4fce4644bfaa5a5578b30572894
Publikováno v:
Ocean-Land-Atmosphere Research, Vol 2 (2023)
It has been said, arguably, that causality analysis should pave a promising way to interpretable deep learning and generalization. Incorporation of causality into artificial intelligence algorithms, however, is challenged with its vagueness, nonquant
Externí odkaz:
https://doaj.org/article/66c1ca3b5b2a4d59a026c9fef8f417a7
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract Classical laws of friction suggest that friction force is proportional to the normal load and independent of the nominal contact area. As a great improvement in this subject, it is now widely accepted that friction force is proportional to t
Externí odkaz:
https://doaj.org/article/34c155256fee450baabc2b0b04f09645
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Abstract The 2014–2015 “Monster”/“Super” El Niño failed to be predicted one year earlier due to the growing importance of a new type of El Niño, El Niño Modoki, which reportedly has much lower forecast skill with the classical models. In
Externí odkaz:
https://doaj.org/article/382a56d14b4c4b7c8a28b5c15e4757f1
Autor:
Y. Xue, T. Yao, A. A. Boone, I. Diallo, Y. Liu, X. Zeng, W. K. M. Lau, S. Sugimoto, Q. Tang, X. Pan, P. J. van Oevelen, D. Klocke, M.-S. Koo, T. Sato, Z. Lin, Y. Takaya, C. Ardilouze, S. Materia, S. K. Saha, R. Senan, T. Nakamura, H. Wang, J. Yang, H. Zhang, M. Zhao, X.-Z. Liang, J. D. Neelin, F. Vitart, X. Li, P. Zhao, C. Shi, W. Guo, J. Tang, M. Yu, Y. Qian, S. S. P. Shen, Y. Zhang, K. Yang, R. Leung, Y. Qiu, D. Peano, X. Qi, Y. Zhan, M. A. Brunke, S. C. Chou, M. Ek, T. Fan, H. Guan, H. Lin, S. Liang, H. Wei, S. Xie, H. Xu, W. Li, X. Shi, P. Nobre, Y. Pan, Y. Qin, J. Dozier, C. R. Ferguson, G. Balsamo, Q. Bao, J. Feng, J. Hong, S. Hong, H. Huang, D. Ji, Z. Ji, S. Kang, Y. Lin, W. Liu, R. Muncaster, P. de Rosnay, H. G. Takahashi, G. Wang, S. Wang, W. Wang, X. Zhou, Y. Zhu
Publikováno v:
Geoscientific Model Development, Vol 14, Pp 4465-4494 (2021)
Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the G
Externí odkaz:
https://doaj.org/article/9216b5e9620e4c929496ae526d1bff7c
Autor:
V. Kholodovsky, X.-Z. Liang
Publikováno v:
Advances in Statistical Climatology, Meteorology and Oceanography, Vol 7, Pp 35-52 (2021)
Extreme weather and climate events such as floods, droughts, and heat waves can cause extensive societal damages. While various statistical and climate models have been developed for the purpose of simulating extremes, a consistent definition of extr
Externí odkaz:
https://doaj.org/article/020685b0f75c41cebcf0591dfdae6ce0
Autor:
Yineng Rong, X. San Liang
Publikováno v:
IEEE Access, Vol 9, Pp 47266-47274 (2021)
Panel data, which consist of observations on many individual units over two or more instances of time, have gradually become an important type of scientific data. Subsequently causal inference for panel data has attracted enormous interest from many
Externí odkaz:
https://doaj.org/article/7c9c3ba6c2d24ff5b6f5a980bb0015f6