Zobrazeno 1 - 10
of 2 631
pro vyhledávání: '"Chen Liwei"'
Publikováno v:
Energy Reports, Vol 8, Iss , Pp 265-272 (2022)
Coriolis mass flowmeter has been widely used in the energy field, and the key of mass flowrate measurement is to calculate the frequency and phase difference of the signal accurately. Aiming at the poor measurement precision problem in Coriolis mass
Externí odkaz:
https://doaj.org/article/dba8378ff6fc443d88b52573bb2ae0c0
Publikováno v:
Fushe yanjiu yu fushe gongyi xuebao, Vol 40, Iss 4, Pp 56-65 (2022)
Considering the special circumstances after nuclear accidents, such as continuous change of source term release rate, limited monitoring data, and variable observed noise, a source term inversion method based on the Gaussian puff dispersion model and
Externí odkaz:
https://doaj.org/article/280a24c4d328404081cb83aab338ba9e
Publikováno v:
Fushe yanjiu yu fushe gongyi xuebao, Vol 41, Iss 4, Pp 040601-040601 (2023)
During the transportation of components related to nuclear materials, accidental chemical explosions may occur, resulting in the release of radionuclides. Effective decision-making during nuclear transport accidents, especially in cases with incomple
Externí odkaz:
https://doaj.org/article/0bdbca108c2b4e868448c3c3316e98aa
Publikováno v:
Fushe yanjiu yu fushe gongyi xuebao, Vol 39, Iss 2, Pp 84-89 (2021)
In this study, we analyzed a region where accidentally released radionuclides were affected by the surrounding vegetation. A radioactive leakage accident affecting shelterbelts located on both sides of a road was selected for modeling. A model of rad
Externí odkaz:
https://doaj.org/article/271599a408b142d99cd4a1924c7b3e3a
Autor:
Sun, Zhicheng, Yang, Zhenhao, Jin, Yang, Chi, Haozhe, Xu, Kun, Chen, Liwei, Jiang, Hao, Song, Yang, Gai, Kun, Mu, Yadong
Customizing diffusion models to generate identity-preserving images from user-provided reference images is an intriguing new problem. The prevalent approaches typically require training on extensive domain-specific images to achieve identity preserva
Externí odkaz:
http://arxiv.org/abs/2405.14677
Autor:
Huang, Quzhe, An, Zhenwei, Zhuang, Nan, Tao, Mingxu, Zhang, Chen, Jin, Yang, Xu, Kun, Chen, Liwei, Huang, Songfang, Feng, Yansong
In this paper, we introduce a novel dynamic expert selection framework for Mixture of Experts (MoE) models, aiming to enhance computational efficiency and model performance by adjusting the number of activated experts based on input difficulty. Unlik
Externí odkaz:
http://arxiv.org/abs/2403.07652
The advancement of Multimodal Large Language Models (MLLMs) has greatly accelerated the development of applications in understanding integrated texts and images. Recent works leverage image-caption datasets to train MLLMs, achieving state-of-the-art
Externí odkaz:
http://arxiv.org/abs/2402.17304
Autor:
Jin, Yang, Sun, Zhicheng, Xu, Kun, Chen, Liwei, Jiang, Hao, Huang, Quzhe, Song, Chengru, Liu, Yuliang, Zhang, Di, Song, Yang, Gai, Kun, Mu, Yadong
In light of recent advances in multimodal Large Language Models (LLMs), there is increasing attention to scaling them from image-text data to more informative real-world videos. Compared to static images, video poses unique challenges for effective l
Externí odkaz:
http://arxiv.org/abs/2402.03161
While large language models exhibit remarkable performance in the Question Answering task, they are susceptible to hallucinations. Challenges arise when these models grapple with understanding multi-hop relations in complex questions or lack the nece
Externí odkaz:
http://arxiv.org/abs/2311.07491
Autor:
Chen, Liwei, Yuan, Yuan
The Hardy spaces are defined on the quotient domain of a bounded complete Reinhardt domain by a finite subgroup of $U(n)$. The Szeg\H{o} projection on the quotient domain can be studied by lifting to the covering space. This setting builds on the sol
Externí odkaz:
http://arxiv.org/abs/2310.12151