Zobrazeno 1 - 10
of 3 126
pro vyhledávání: '"LIU Zhenhua"'
Autor:
NIU Wenzhi, HE Fubing, LIU Zhenhua, CUI Yubin, BAI Lingyan, WANG Anguo, ZHANG Yueze, CAO Mengmeng, ZHOU Jieming
Publikováno v:
Dizhi lixue xuebao, Vol 29, Iss 6, Pp 879-887 (2023)
The Nanyuan–Tongxian fault is the boundary fault between the Beijing depression and the Daxing uplift, also the primary seismic-controlling fault of the Beijing M \begin{document}$ 6{\dfrac{1}{2}}$\end{document} earthquake in 1665. Its activity is
Externí odkaz:
https://doaj.org/article/45f49cd8201646a48a2ccb7fa108585f
Publikováno v:
Jixie chuandong, Vol 47, Pp 67-73 (2023)
Aiming at the problem that the internal condition of the pipeline can not pass the manual inspection after the completion of welding, a pipeline robot which can independently inspect the welded pipeline is proposed. The robot can adapt to the change
Externí odkaz:
https://doaj.org/article/2252801cbe214195b76d2007565d2ec2
Publikováno v:
Security and Safety, Vol 3, p 2023025 (2024)
Jamming attacks and unintentional radio interference are some of the most urgent threats harming the dependability of wireless communication and endangering the successful deployment of pervasive applications built on top of wireless networks. Unlike
Externí odkaz:
https://doaj.org/article/d3565eb3ab674e598ffe6542474e55b5
Autor:
Liang, Cong, Song, Xiangli, Cheng, Jing, Wang, Mowei, Liu, Yashe, Liu, Zhenhua, Zhao, Shizhen, Cui, Yong
Recent advances in fast optical switching technology show promise in meeting the high goodput and low latency requirements of datacenter networks (DCN). We present NegotiaToR, a simple network architecture for optical reconfigurable DCNs that utilize
Externí odkaz:
http://arxiv.org/abs/2407.20045
Large language models (LLMs) exhibit remarkable capabilities in understanding and generating natural language. However, these models can inadvertently memorize private information, posing significant privacy risks. This study addresses the challenge
Externí odkaz:
http://arxiv.org/abs/2407.10058
Autor:
LIU Zhenhua, XU Xukan
Publikováno v:
Gong-kuang zidonghua, Vol 45, Iss 4, Pp 101-104 (2019)
In view of problems of low efficiency of manual registration management and poor cooperative control of coal mine electromechanical equipments, an intelligent management platform for coal mine electromechanical equipments based on Internet of things
Externí odkaz:
https://doaj.org/article/ddec581d38a349838ff2fe2613398a7a
Large Language Models (LLMs) have shown their impressive capabilities, while also raising concerns about the data contamination problems due to privacy issues and leakage of benchmark datasets in the pre-training phase. Therefore, it is vital to dete
Externí odkaz:
http://arxiv.org/abs/2406.01333
The demand for large language model (LLM) inference is gradually dominating the artificial intelligence workloads. Therefore, there is an urgent need for cost-efficient inference serving. Existing work focuses on single-worker optimization and lacks
Externí odkaz:
http://arxiv.org/abs/2405.06856
Speculative decoding has demonstrated its effectiveness in accelerating the inference of large language models while maintaining a consistent sampling distribution. However, the conventional approach of training a separate draft model to achieve a sa
Externí odkaz:
http://arxiv.org/abs/2404.18911
Compact neural networks are specially designed for applications on edge devices with faster inference speed yet modest performance. However, training strategies of compact models are borrowed from that of conventional models at present, which ignores
Externí odkaz:
http://arxiv.org/abs/2404.11202