Zobrazeno 1 - 10
of 2 880
pro vyhledávání: '"Li Weifeng"'
In recent years, mobile phone data has been widely used for human mobility analytics. Identifying individual activity locations is the fundamental step for mobile phone data processing. Current methods typically aggregate spatially adjacent location
Externí odkaz:
http://arxiv.org/abs/2410.13912
With the development of urbanization, the scale of urban road network continues to expand, especially in some Asian countries. Short-term traffic state prediction is one of the bases of traffic management and control. Constrained by the space-time co
Externí odkaz:
http://arxiv.org/abs/2409.05132
Publikováno v:
He jishu, Vol 46, Iss 8, Pp 080013-080013 (2023)
Backgroundβ-decay half-life is one of the fundamental physical properties of unstable nuclei and plays an important role in nuclear physics and astrophysics.PurposeThis study aimed to provide accurate nuclear β-decay half-life predictions and reaso
Externí odkaz:
https://doaj.org/article/f1c6eccc16a44161a8a51da594860f95
Autor:
Zhao Xiaofei, Liu Chundong, Yu Jing, Li Zhen, Liu Lu, Li Chonghui, Xu Shicai, Li Weifeng, Man Baoyuan, Zhang Chao
Publikováno v:
Nanophotonics, Vol 9, Iss 16, Pp 4761-4773 (2020)
Cavity array, with excellent optical capture capability, has received increasing attention for the surface-enhanced Raman spectroscopy (SERS)-active substrates. Here, we proposed molybdenum disulfide (MoS2) nanocavities growing on pyramid Si (PSi) co
Externí odkaz:
https://doaj.org/article/4cd99b98d20e4ff6b4aa4ff60f7c09d9
Publikováno v:
网络与信息安全学报, Vol 4, Iss 1, Pp 26-35 (2018)
Cloud computing is the mainstream information system technology, however, privacy protection of user and privacy violation tracking and forensics in the cloud computing environment have always been a challenge. The current mainstream cloud computing
Externí odkaz:
https://doaj.org/article/f860694f221d45d491e4034e2189145c
Adversarial Malware Generation (AMG), the generation of adversarial malware variants to strengthen Deep Learning (DL)-based malware detectors has emerged as a crucial tool in the development of proactive cyberdefense. However, the majority of extant
Externí odkaz:
http://arxiv.org/abs/2402.02600
Publikováno v:
Kybernetes, 2023, Vol. 53, Issue 10, pp. 3365-3400.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/K-11-2022-1580
Deep convolutional neural networks (CNNs) have been widely used in surface defect detection. However, no CNN architecture is suitable for all detection tasks and designing effective task-specific requires considerable effort. The neural architecture
Externí odkaz:
http://arxiv.org/abs/2311.10952