Zobrazeno 1 - 10
of 1 791
pro vyhledávání: '"Wang Zehua"'
Autor:
Tian Huiyuan, Li Yang, Xia Mengyan, Cui Baoyu, Liu Chang, Du Xiuhong, Wang Zehua, Duan Xianying, Cui Jiehu
Publikováno v:
Arabian Journal of Chemistry, Vol 17, Iss 3, Pp 105645- (2024)
Layered double hydroxides (LDHs) have attracted increasing attention as promising candidates by anion exchanges and selective adsorption in the fluoride treatment field. In this study, three new ternary Zn-Co-Cr-LDHs were synthesized by primarily a o
Externí odkaz:
https://doaj.org/article/fea3fa0e11c344f5974d13e5575e7024
Autor:
Li Yang, Tian Huiyuan, Xia Mengyan, Cui Baoyu, Liu Chang, Du Xiuhong, Wang Zehua, Duan Xianying, Cui Jiehu
Publikováno v:
Arabian Journal of Chemistry, Vol 16, Iss 10, Pp 105163- (2023)
Layered bimetallic hydroxide (LDHs) nanomaterials have shown excellent potential in the field of recovery of pollutants from wastewater through anion exchange and surface electrostatic interaction. In this paper, three new ternary ZnCrNi-LDHs with th
Externí odkaz:
https://doaj.org/article/31da8d7079454c499abd9ced66ff54c9
Publikováno v:
Journal of Aeronautical Materials, Vol 42, Iss 1, Pp 92-99 (2022)
ZnO nanofibers were prepared by electrospinning method in this work. The effects of PVA concentration on the morphology, dielectric properties and microwave absorption properties of ZnO nanofibers were studied. Results show that with the concentratio
Externí odkaz:
https://doaj.org/article/ea77153325134ac9b4f36abf057ed054
Autor:
Wu, Jiaqi, Chen, Simin, Yang, Yuzhe, Li, Yijiang, Hou, Shiyue, Jing, Rui, Wang, Zehua, Chen, Wei, Tian, Zijian
In recent years, large language models (LLMs) have significantly advanced the field of natural language processing (NLP). By fine-tuning LLMs with data from specific scenarios, these foundation models can better adapt to various downstream tasks. How
Externí odkaz:
http://arxiv.org/abs/2411.00985
Federated learning (FL) is a learning paradigm that enables collaborative training of models using decentralized data. Recently, the utilization of pre-trained weight initialization in FL has been demonstrated to effectively improve model performance
Externí odkaz:
http://arxiv.org/abs/2410.23660
Autor:
Wu, Jiaqi, Chen, Simin, Wang, Zehua, Chen, Wei, Tian, Zijian, Yu, F. Richard, Leung, Victor C. M.
As the volume of image data grows, data-oriented cloud computing in Internet of Video Things (IoVT) systems encounters latency issues. Task-oriented edge computing addresses this by shifting data analysis to the edge. However, limited computational p
Externí odkaz:
http://arxiv.org/abs/2411.00838
Autor:
Su Xiaowen, Wang Zehua, Huang Yuan, Miao Zhenyu, Wang Shuhua, Wang Jianjun, Zhang Xiao Li, Sun Xiaomin, Liu Hong, Sang Yuanhua
Publikováno v:
Nanotechnology Reviews, Vol 10, Iss 1, Pp 847-856 (2021)
The hazard-free treatment of Cr(vi) ions is critical in modern industry. Photocatalytic reduction and detoxification are high-potential strategies. Photocatalysts with high efficiency, low cost, environmental friendliness, and easy mass products are
Externí odkaz:
https://doaj.org/article/b7a48113e4d5490b9ac490bfb0832355
Publikováno v:
Zhongliu Fangzhi Yanjiu, Vol 48, Iss 3, Pp 314-318 (2021)
Tie2 expressing monocytes/macrophages (TEMs) are a subtype of monocytes or macrophages which expressing tyrosine kinase receptor Tie2. They can exist in peripheral blood and tissues of both human and mouse. TEMs can participate in the formation of tu
Externí odkaz:
https://doaj.org/article/6ba3e320d0ad4c2ea63cc74da8af02b9
We consider the problem of model selection in a high-dimensional sparse linear regression model under privacy constraints. We propose a differentially private (DP) best subset selection method with strong statistical utility properties by adopting th
Externí odkaz:
http://arxiv.org/abs/2310.07852
Cross-silo federated learning (FL) enables the development of machine learning models on datasets distributed across data centers such as hospitals and clinical research laboratories. However, recent research has found that current FL algorithms face
Externí odkaz:
http://arxiv.org/abs/2307.10507