Zobrazeno 1 - 10
of 1 122
pro vyhledávání: '"Cao Xiaoyu"'
Publikováno v:
E3S Web of Conferences, Vol 466, p 02005 (2023)
As global focus sharpens on carbon emissions and environmental protection; the pursuit of sustainable development permeates every sector. Against the backdrop of increasing fossil fuel prices and relentless energy demand, the exploration of clean ene
Externí odkaz:
https://doaj.org/article/5e5511830113444ab0e3093ac2093c1d
Publikováno v:
IEEE Transactions on Smart Grid (2024)
Hydrogen-electrical microgrids are increasingly assuming an important role on the pathway toward decarbonization of energy and transportation systems. This paper studies networked hydrogen-electrical microgrids planning (NHEMP), considering a critica
Externí odkaz:
http://arxiv.org/abs/2404.00568
Autor:
Chen Junren, Xie Xiaofang, Zhang Huiqiong, Li Gangmin, Yin Yanpeng, Cao Xiaoyu, Gao Yuqing, Li Yanan, Zhang Yue, Peng Fu, Peng Cheng
Publikováno v:
Frontiers in Pharmacology, Vol 12 (2021)
Hirudin, an acidic polypeptide secreted by the salivary glands of Hirudo medicinalis (also known as “Shuizhi” in traditional Chinese medicine), is the strongest natural specific inhibitor of thrombin found so far. Hirudin has been demonstrated to
Externí odkaz:
https://doaj.org/article/1d0dc8249e924d2dacf0777b6dc7afe7
Unscheduled islanding events of microgrids result in the transition between grid-connected and islanded modes and induce a sudden and unknown power imbalance, posing a threat to frequency security. To achieve seamless islanding, we propose a distribu
Externí odkaz:
http://arxiv.org/abs/2401.03381
Video data and algorithms have been driving advances in multi-object tracking (MOT). While existing MOT datasets focus on occlusion and appearance similarity, complex motion patterns are widespread yet overlooked. To address this issue, we introduce
Externí odkaz:
http://arxiv.org/abs/2308.11157
Autor:
Zhu, Jianzhuo, Zhang, Qian, Ma, Liang, Wang, Sheng, Ma, Ying, Duan, Xiangyi, Cao, Xiaoyu, Fang, Zhihang, Liu, Yang, Wei, Yong, Feng, Chao
Publikováno v:
Journal of Chemical Physics; 11/7/2024, Vol. 161 Issue 17, p1-8, 8p
Federated learning is vulnerable to poisoning attacks in which malicious clients poison the global model via sending malicious model updates to the server. Existing defenses focus on preventing a small number of malicious clients from poisoning the g
Externí odkaz:
http://arxiv.org/abs/2210.10936
Due to its distributed nature, federated learning is vulnerable to poisoning attacks, in which malicious clients poison the training process via manipulating their local training data and/or local model updates sent to the cloud server, such that the
Externí odkaz:
http://arxiv.org/abs/2210.00584
Federated learning (FL) is vulnerable to model poisoning attacks, in which malicious clients corrupt the global model via sending manipulated model updates to the server. Existing defenses mainly rely on Byzantine-robust FL methods, which aim to lear
Externí odkaz:
http://arxiv.org/abs/2207.09209
Motion and interaction of social insects (such as ants) have been studied by many researchers to understand the clustering mechanism. Most studies in the field of ant behavior have only focused on indoor environments, while outdoor environments are s
Externí odkaz:
http://arxiv.org/abs/2204.04380