Zobrazeno 1 - 10
of 2 658
pro vyhledávání: '"XIAN, Min"'
Identifying and classifying shutdown initiating events (SDIEs) is critical for developing low power shutdown probabilistic risk assessment for nuclear power plants. Existing computational approaches cannot achieve satisfactory performance due to the
Externí odkaz:
http://arxiv.org/abs/2410.00929
Autor:
Shang, Xiao-Wen, Chen, Xuan, Hegade, Narendra N., Lan, Ze-Feng, Li, Xuan-Kun, Tang, Hao, Peng, Yu-Quan, Solano, Enrique, Jin, Xian-Min
Codesign, an integral part of computer architecture referring to the information interaction in hardware-software stack, is able to boost the algorithm mapping and execution in the computer hardware. This well applies to the noisy intermediate-scale
Externí odkaz:
http://arxiv.org/abs/2409.17930
In quantum mechanics, a long-standing question remains: How does a single photon traverse double slits? One intuitive picture suggests that the photon passes through only one slit, while its wavefunction splits into an ``empty" wave and a ``full" wav
Externí odkaz:
http://arxiv.org/abs/2409.13383
Conventionally, atomic vapor is perceived as a non-living system governed by the principles of thermodynamics and statistical physics. However, the demarcation line between life and non-life appears to be less distinct than previously thought. In a s
Externí odkaz:
http://arxiv.org/abs/2408.04950
Effective clinical deployment of deep learning models in healthcare demands high generalization performance to ensure accurate diagnosis and treatment planning. In recent years, significant research has focused on improving the generalization of deep
Externí odkaz:
http://arxiv.org/abs/2408.04065
Autor:
Zhou, Xingchen, Gong, Yan, Zhang, Xin, Li, Nan, Meng, Xian-Min, Chen, Xuelei, Wen, Run, Han, Yunkun, Zou, Hu, Zheng, Xian Zhong, Yang, Xiaohu, Guo, Hong, Zhang, Pengjie
Chinese Space Station Telescope (CSST) has the capability to conduct slitless spectroscopic survey simultaneously with photometric survey. The spectroscopic survey will measure slitless spectra, potentially providing more accurate estimations of gala
Externí odkaz:
http://arxiv.org/abs/2407.13991
Autor:
Luo, Zhijian, Tang, Zhirui, Chen, Zhu, Fu, Liping, Du, Wei, Zhang, Shaohua, Gong, Yan, Shu, Chenggang, Lu, Junhao, Li, Yicheng, Meng, Xian-Min, Zhou, Xingchen, Fan, Zuhui
Accurate photometric redshift (photo-$z$) estimation requires support from multi-band observational data. However, in the actual process of astronomical observations and data processing, some sources may have missing observational data in certain ban
Externí odkaz:
http://arxiv.org/abs/2406.01719
Industry-wide nuclear power plant operating experience is a critical source of raw data for performing parameter estimations in reliability and risk models. Much operating experience information pertains to failure events and is stored as reports con
Externí odkaz:
http://arxiv.org/abs/2404.05656
In recent years, convolutional neural networks for semantic segmentation of breast ultrasound (BUS) images have shown great success; however, two major challenges still exist. 1) Most current approaches inherently lack the ability to utilize tissue a
Externí odkaz:
http://arxiv.org/abs/2403.15560
Autor:
Lu, Junhao, Luo, Zhijian, Chen, Zhu, Fu, Liping, Du, Wei, Gong, Yan, Li, Yicheng, Meng, Xian-Min, Tang, Zhirui, Zhang, Shaohua, Shu, Chenggang, Zhou, Xingchen, Fan, Zuhui
Accurate estimation of photometric redshifts (photo-$z$) is crucial in studies of both galaxy evolution and cosmology using current and future large sky surveys. In this study, we employ Random Forest (RF), a machine learning algorithm, to estimate p
Externí odkaz:
http://arxiv.org/abs/2312.12949