Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Yewen Cao"'
Autor:
Zhongwei Huang, Tong Li, Chenghao Song, Zhenxing Li, Jie Wang, Xiao Liu, Haibo Chen, Xiaorong Zhao, Yewen Cao
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2024, Iss 1, Pp 1-16 (2024)
Abstract Device-to-device (D2D) communications allow short-range communication devices to multiplex cellular-licensed spectrum to directly establish local connections for ultra-high number of terminal connections and greater system throughput. Howeve
Externí odkaz:
https://doaj.org/article/6f7595a2d5bd4274a2ead922dba014ba
Publikováno v:
IEEE Access, Vol 12, Pp 6745-6751 (2024)
Deep reinforcement learning (DRL) methods have emerged as a feasible solution for addressing the power resource allocation problem in ultra-dense small-cell networks (UDSCNs). In this paper, we propose a novel actor-critic-based low-coupling policy o
Externí odkaz:
https://doaj.org/article/572e103f7a094e02986669d978f0af4e
Autor:
Haibo Chen, Zhongwei Huang, Xiaorong Zhao, Xiao Liu, Youjun Jiang, Pinyong Geng, Guang Yang, Yewen Cao, Deqiang Wang
Publikováno v:
Mathematics, Vol 11, Iss 7, p 1702 (2023)
A practical solution to the power allocation problem in ultra-dense small cell networks can be achieved by using deep reinforcement learning (DRL) methods. Unlike traditional algorithms, DRL methods are capable of achieving low latency and operating
Externí odkaz:
https://doaj.org/article/d00853c5726c4bfe857d6ddc32a307d6
Publikováno v:
Journal of Marine Science and Engineering, Vol 11, Iss 3, p 541 (2023)
Ships are equipped with power plants and operational assistance devices, both of which need oil for lubrication or energy transfer. Oil carries a large number of metal particles. By identifying the materials and sizes of metal particles in oil, the p
Externí odkaz:
https://doaj.org/article/98d95ab6931e453ea6de8a5f90602783
Autor:
Qiang Zhao, Rundong Guo, Xiaowei Feng, Weifeng Hu, Siwen Zhao, Zihan Wang, Yujun Li, Yewen Cao
Publikováno v:
Mathematics, Vol 10, Iss 13, p 2281 (2022)
Legal judgement prediction (LJP) is a crucial part of legal AI, and its goal is to predict the outcome of a case based on the information in the description of criminal facts. This paper proposes a decision prediction method based on causal inference
Externí odkaz:
https://doaj.org/article/002d365ecdc9491590a24ac008448057
Publikováno v:
ETRI Journal, Vol 40, Iss 2, Pp 227-236 (2018)
Ultra‐dense small cell networks (UD‐SCNs) have been identified as a promising scheme for next‐generation wireless networks capable of meeting the ever‐increasing demand for higher transmission rates and better quality of service. However, UD
Externí odkaz:
https://doaj.org/article/bf8162388ec2455db2a3d378624b53d2
Publikováno v:
IEEE Transactions on Vehicular Technology. 72:2066-2081
Autor:
Renping Cao, Yongtong Rong, Yewen Cao, Ban Lan, Chenxing Liao, Jingheng Nie, Fangrui Cheng, Jing Wang
Publikováno v:
Materials Research Bulletin. 166:112344
Most of the existing research focuses on the recognition of micro-expressions, and few studies how to recognize the action units of micro-expressions. This is due to the low intensity of the facial action unit, which is not easily to be recognized. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb8da684b4f6342e6094284c648b306c
https://doi.org/10.21203/rs.3.rs-2449787/v1
https://doi.org/10.21203/rs.3.rs-2449787/v1
Autor:
Renping Cao, Zibin Lai, Yewen Cao, Fangrui Cheng, Chenxing Liao, Shuijing Nie, Xuehua Yi, Jing Wang
Publikováno v:
New Journal of Chemistry.
Luminescent materials used in solid-state lighting usually face the challenge of the adjustment of luminescence properties.