Zobrazeno 1 - 10
of 4 162
pro vyhledávání: '"Lu Dan"'
Autor:
LU Dan, LU Weifu
Publikováno v:
Shipin Kexue, Vol 45, Iss 14, Pp 366-373 (2024)
China has initially established a legal system regarding food safety risk monitoring and assessment, and has completed the construction of a national food safety risk monitoring network. This legal system belongs to the category of administrative law
Externí odkaz:
https://doaj.org/article/1c082192bb134f52bd8471ceb24a7663
Autor:
Wu Jianhong, Fan Linyuan, Li Lin, Zhang Yudi, Tian Yucui, Jiang Ziwen, Liu Zhaohui, Lu Dan, Dai Yinmei
Publikováno v:
Acta Biochimica et Biophysica Sinica, Vol 56, Pp 952-955 (2024)
Externí odkaz:
https://doaj.org/article/300d079c9f884ad686b19b0f2a6c14fe
Publikováno v:
BMC Medical Education, Vol 24, Iss 1, Pp 1-5 (2024)
Abstract Objective To explore the teaching effect of Advanced Life Support in Obstetrics (ALSO) Course in the standardized training resident in obstetric. Methods 60 residents of obstetrics from January 2021 to December 2022 were randomly divided int
Externí odkaz:
https://doaj.org/article/7906cb2d5aac407a85a8eea7f8f8bf43
Accurate long-term predictions are the foundations for many machine learning applications and decision-making processes. Traditional time series approaches for prediction often focus on either autoregressive modeling, which relies solely on past obse
Externí odkaz:
http://arxiv.org/abs/2410.12184
Autor:
Yin, Junqi, Liang, Siming, Liu, Siyan, Bao, Feng, Chipilski, Hristo G., Lu, Dan, Zhang, Guannan
The weather and climate domains are undergoing a significant transformation thanks to advances in AI-based foundation models such as FourCastNet, GraphCast, ClimaX and Pangu-Weather. While these models show considerable potential, they are not ready
Externí odkaz:
http://arxiv.org/abs/2407.12168
Autor:
Xu, Guizhen, Xue, Zhanqiang, Fan, Junxing, Lu, Dan, Xing, Hongyang, Shum, Perry Ping, Cong, Longqing
Terahertz absorbers are crucial to the cutting-edge techniques in the next-generation wireless communications, imaging, sensing, and radar stealth, as they fundamentally determine the performance of detectors and cloaking capabilities. It has long be
Externí odkaz:
http://arxiv.org/abs/2405.03600
Autor:
Wang, Xiao, Liu, Siyan, Tsaris, Aristeidis, Choi, Jong-Youl, Aji, Ashwin, Fan, Ming, Zhang, Wei, Yin, Junqi, Ashfaq, Moetasim, Lu, Dan, Balaprakash, Prasanna
Earth system predictability is challenged by the complexity of environmental dynamics and the multitude of variables involved. Current AI foundation models, although advanced by leveraging large and heterogeneous data, are often constrained by their
Externí odkaz:
http://arxiv.org/abs/2404.14712
Autor:
Tsaris, Aristeidis, Zhang, Chengming, Wang, Xiao, Yin, Junqi, Liu, Siyan, Ashfaq, Moetasim, Fan, Ming, Choi, Jong Youl, Wahib, Mohamed, Lu, Dan, Balaprakash, Prasanna, Wang, Feiyi
Vision Transformers (ViTs) are pivotal for foundational models in scientific imagery, including Earth science applications, due to their capability to process large sequence lengths. While transformers for text has inspired scaling sequence lengths i
Externí odkaz:
http://arxiv.org/abs/2405.15780
We introduce a conditional pseudo-reversible normalizing flow for constructing surrogate models of a physical model polluted by additive noise to efficiently quantify forward and inverse uncertainty propagation. Existing surrogate modeling approaches
Externí odkaz:
http://arxiv.org/abs/2404.00502
Publikováno v:
Reliability Engineering & System Safety, 247, 110128 (2024)
Most theoretical analysis for lifetime distribution explains origins of specific distribution based on independent failure. We develop a unified framework encompassing different lifetime distribution for failure-coupled network systems. We find three
Externí odkaz:
http://arxiv.org/abs/2311.07393