Zobrazeno 1 - 10
of 7 064
pro vyhledávání: '"Wei, Kang"'
As an emerging technology, digital twin (DT) can provide real-time status and dynamic topology mapping for Internet of Things (IoT) devices. However, DT and its implementation within industrial IoT networks necessitates substantial, distributed data
Externí odkaz:
http://arxiv.org/abs/2408.14298
Autor:
Tuyen, LE Quang, Van Bo, Nguyen, Shengwei, Ma, Siong, Neo Boon, Arthur, Lim, Wei, KAng Chang, Huangwei, Zhang
The objective of the LES simulation is to investigate how operational parameters affect flame properties in combustion of the premixed NH3/H2/air inside a swirling burner. Key parameters explored include the differential blend ratio of NH3/H2 fuels,
Externí odkaz:
http://arxiv.org/abs/2408.05553
CO2 hydrogenation to hydrocarbon refers to an indirect pathway of CO2 utilization. Among them, the conversion of CO2 with green H2 to sustainable aviation fuel (SAF) with high energy density has gained much attention. It offers a promising way to red
Externí odkaz:
http://arxiv.org/abs/2408.05551
Autor:
Li, Yifan, Shu, Feng, Wei, Kang, Bai, Jiatong, Pan, Cunhua, Wu, Yongpeng, Song, Yaoliang, Wang, Jiangzhou
As a green MIMO structure, the partially-connected hybrid analog and digital (PC-HAD) structure has been widely used in the far-field (FF) scenario for it can significantly reduce the hardware cost and complexity of large-scale or extremely large-sca
Externí odkaz:
http://arxiv.org/abs/2406.09695
Federated learning (FL) based on the centralized design faces both challenges regarding the trust issue and a single point of failure. To alleviate these issues, blockchain-aided decentralized FL (BDFL) introduces the decentralized network architectu
Externí odkaz:
http://arxiv.org/abs/2406.00752
Autor:
Deng, Xiumei, Li, Jun, Wei, Kang, Shi, Long, Xiong, Zeihui, Ding, Ming, Chen, Wen, Jin, Shi, Poor, H. Vincent
Adaptive moment estimation (Adam), as a Stochastic Gradient Descent (SGD) variant, has gained widespread popularity in federated learning (FL) due to its fast convergence. However, federated Adam (FedAdam) algorithms suffer from a threefold increase
Externí odkaz:
http://arxiv.org/abs/2405.17932
Digital twin (DT) has emerged as a promising solution to enhance manufacturing efficiency in industrial Internet of Things (IIoT) networks. To promote the efficiency and trustworthiness of DT for wireless IIoT networks, we propose a blockchain-enable
Externí odkaz:
http://arxiv.org/abs/2405.17914
Federated self-supervised learning (FSSL) has recently emerged as a promising paradigm that enables the exploitation of clients' vast amounts of unlabeled data while preserving data privacy. While FSSL offers advantages, its susceptibility to backdoo
Externí odkaz:
http://arxiv.org/abs/2405.13080
Autor:
Shao, Yumeng, Li, Jun, Shi, Long, Wei, Kang, Ding, Ming, Li, Qianmu, Li, Zengxiang, Chen, Wen, Jin, Shi
Conventional synchronous federated learning (SFL) frameworks suffer from performance degradation in heterogeneous systems due to imbalanced local data size and diverse computing power on the client side. To address this problem, asynchronous FL (AFL)
Externí odkaz:
http://arxiv.org/abs/2405.06993
As an emerging artificial intelligence technology, graph neural networks (GNNs) have exhibited promising performance across a wide range of graph-related applications. However, information exchanges among neighbor nodes in GNN pose new challenges in
Externí odkaz:
http://arxiv.org/abs/2405.05802