Zobrazeno 1 - 10
of 206
pro vyhledávání: '"Wang, Keqi"'
The 4H-SiC material exhibits good detection performance, but there are still many problems like signal distortion and poor signal quality. The 4H-SiC low gain avalanche detector (LGAD) has been fabricated for the first time to solve these problems, w
Externí odkaz:
http://arxiv.org/abs/2405.18112
Autor:
He, Ye, Li, Xingchen, Xu, Zijun, Qi, Ming, Wang, Congcong, Wang, Chenwei, Lu, Hai, Nie, Xiaojun, Fan, Ruirui, Jing, Hantao, Song, Weiming, Wang, Keqi, Liu, Kai, Liu, Peilian, Li, Hui, Li, Zaiyi, Fu, Chenxi, Zhang, Xiyuan, Kang, Xiaoshen, Li, Zhan, Lu, Weiguo, Xiao, Suyu, Shi, Xin
A high precision beam monitor system based on silicon carbide PIN sensor is designed for China Spallation Neutron Source 1.6 GeV proton beam to monitor the proton beam fluence.The concept design of the beam monitor system is finished together with fr
Externí odkaz:
http://arxiv.org/abs/2403.09244
Autor:
Wang, Keqi, Yang, Tao, Fu, Chenxi, Gong, Li, Jiang, Songting, Kang, Xiaoshen, Li, Zaiyi, Shi, Hangrui ShiXin, Song, Weimin, Wang, Congcong, Xiao, Suyu, Xu, Zijun, Zhang, Xiyuan
Silicon-based fast time detectors have been widely used in high energy physics, nuclear physics, space exploration and other fields in recent years. However, silicon detectors often require complex low-temperature systems when operating in irradiatio
Externí odkaz:
http://arxiv.org/abs/2306.09576
To facilitate a rapid response to pandemic threats, this paper focuses on developing a mechanistic simulation model for in vitro transcription (IVT) process, a crucial step in mRNA vaccine manufacturing. To enhance production and support industry 4.0
Externí odkaz:
http://arxiv.org/abs/2305.09867
The rapidly expanding market for regenerative medicines and cell therapies highlights the need to advance the understanding of cellular metabolisms and improve the prediction of cultivation production process for human induced pluripotent stem cells
Externí odkaz:
http://arxiv.org/abs/2305.00165
Driven by the critical needs of biomanufacturing 4.0, we introduce a probabilistic knowledge graph hybrid model characterizing the risk- and science-based understanding of bioprocess mechanisms. It can faithfully capture the important properties, inc
Externí odkaz:
http://arxiv.org/abs/2205.02410
Motivated by critical challenges and needs from biopharmaceuticals manufacturing, we propose a general metamodel-assisted stochastic simulation uncertainty analysis framework to accelerate the development of a simulation model with modular design for
Externí odkaz:
http://arxiv.org/abs/2203.08980
Autor:
Wang, Keqi, Cui, Ziteng, Jia, Jieru, Xu, Hao, Wu, Ge, Zhuang, Yin, Chen, Lu, Hu, Zhiguo, Qian, Yuhua
Convolution neural networks (CNNs) based methods have dominated the low-light image enhancement tasks due to their outstanding performance. However, the convolution operation is based on a local sliding window mechanism, which is difficult to constru
Externí odkaz:
http://arxiv.org/abs/2201.08996
Driven by the key challenges of cell therapy manufacturing, including high complexity, high uncertainty, and very limited process observations, we propose a hybrid model-based reinforcement learning (RL) to efficiently guide process control. We first
Externí odkaz:
http://arxiv.org/abs/2201.03116
Publikováno v:
In Composite Structures 1 July 2024 339