Zobrazeno 1 - 10
of 1 078
pro vyhledávání: '"LI PengYu"'
Autor:
LI Yixiao, ZHENG Tianlong, YANG Xiaoxia, LI Pengyu, WANG Zixuan, WANG Juan, CAO Yingnan, LIU Jianguo, LIU Junxin
Publikováno v:
Gongye shui chuli, Vol 44, Iss 1, Pp 13-21 (2024)
The overall treatment rate of rural domestic sewage in Northwest China is lower than that of national average level. In order to effectively improve regional rural sewage treatment capacity and enhance management level of water environment during loc
Externí odkaz:
https://doaj.org/article/622d227571044897bf713740260b139a
Autor:
XIA Maolin, LI Hongchen, ZHAO Huaxin, LI Pengyu, LIU Lingling, GUAN Weidong, CHANG Jianbo, WANG Zhijun, JI Xiaoming
Publikováno v:
Guan'gai paishui xuebao, Vol 41, Iss 11, Pp 14-21 (2022)
【Objective】 Drought is the most common abiotic stress affecting agricultural production in most countries, and alleviating its detrimental effect is critical to safeguarding crop growth. The purpose of this paper is to compare the efficacy of wat
Externí odkaz:
https://doaj.org/article/302cf3bf4b654a0d94ffefa087055892
Autor:
Kong, Weijie, Tian, Qi, Zhang, Zijian, Min, Rox, Dai, Zuozhuo, Zhou, Jin, Xiong, Jiangfeng, Li, Xin, Wu, Bo, Zhang, Jianwei, Wu, Kathrina, Lin, Qin, Yuan, Junkun, Long, Yanxin, Wang, Aladdin, Wang, Andong, Li, Changlin, Huang, Duojun, Yang, Fang, Tan, Hao, Wang, Hongmei, Song, Jacob, Bai, Jiawang, Wu, Jianbing, Xue, Jinbao, Wang, Joey, Wang, Kai, Liu, Mengyang, Li, Pengyu, Li, Shuai, Wang, Weiyan, Yu, Wenqing, Deng, Xinchi, Li, Yang, Chen, Yi, Cui, Yutao, Peng, Yuanbo, Yu, Zhentao, He, Zhiyu, Xu, Zhiyong, Zhou, Zixiang, Xu, Zunnan, Tao, Yangyu, Lu, Qinglin, Liu, Songtao, Zhou, Daquan, Wang, Hongfa, Yang, Yong, Wang, Di, Liu, Yuhong, Jiang, Jie, Zhong, Caesar
Recent advancements in video generation have significantly impacted daily life for both individuals and industries. However, the leading video generation models remain closed-source, resulting in a notable performance gap between industry capabilitie
Externí odkaz:
http://arxiv.org/abs/2412.03603
The detection of small objects, particularly traffic signs, is a critical subtask within object detection and autonomous driving. Despite the notable achievements in previous research, two primary challenges persist. Firstly, the main issue is the si
Externí odkaz:
http://arxiv.org/abs/2408.14189
Recently customized generation has significant potential, which uses as few as 3-5 user-provided images to train a model to synthesize new images of a specified subject. Though subsequent applications enhance the flexibility and diversity of customiz
Externí odkaz:
http://arxiv.org/abs/2407.09057
Publikováno v:
E3S Web of Conferences, Vol 385, p 01019 (2023)
Olivine-type lithium iron phosphate (LiFePO4) has become the most widely used cathode material for power batteries due to its good structural stability, stable voltage platform, low cost and high safety. The olivine-type iron phosphate material after
Externí odkaz:
https://doaj.org/article/1e44605a80a546a39dfe30157b004a0b
Publikováno v:
E3S Web of Conferences, Vol 385, p 03029 (2023)
Further increasing the voltage is the most efficient means of acquisition to obtain lithium cobalt oxide with high specific capacity, but the irreversible phase transition of LiCoO2 at high voltage leads to poor electrochemical performance. In this p
Externí odkaz:
https://doaj.org/article/cbc162cf20474ba3b59e10cda0d2d386
Publikováno v:
Jixie qiangdu, Vol 40, Pp 160-164 (2018)
In order to make the exciting force adjustment of inertia vibrator during operation possible,and to meet the demand of particular vibrating machines,a kind of inertia vibrator is designed,it’s eccentric mass can be adjusted by pressure air. The des
Externí odkaz:
https://doaj.org/article/1bdc1dde710c4f98906cd3f1f12a921a
This work proposes a deep learning (DL)-based framework, namely Sim2Real, for spectral signal reconstruction in reconstructive spectroscopy, focusing on efficient data sampling and fast inference time. The work focuses on the challenge of reconstruct
Externí odkaz:
http://arxiv.org/abs/2403.12354
We study deep neural networks for the multi-label classification (MLab) task through the lens of neural collapse (NC). Previous works have been restricted to the multi-class classification setting and discovered a prevalent NC phenomenon comprising o
Externí odkaz:
http://arxiv.org/abs/2310.15903