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Yingxun Wang

As seen in: Nature, Future Internet, MDPI
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Articles

BRIDGE-T: addressing temporal unreliability in federated learning for edge-enabled IoT networks

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By Fahmida Islam, Adnan Mahmood, Yingxun Wang, Maryam Tahermazandarani
| Nature Verified
Abstract Federated Learning (FL) in edge-enabled Internet of Things (IoT) networks faces considerable challenges owing to intermittent client participation and distributional drift, and which undermines the stability of a global model’s optimization. This coupled impact introduces temporal unreliability, in turn, impairing the training stability.
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MEMS electrochemical angular accelerometer: a paradigm shift for attitude detection and control in rotorcraft UAVs

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By Maoqi Zhu, Qinghua Liu, Honghao Zhang, Lintao Hu, Yulan Lu, Jian Chen, Yingxun Wang, Deyong Chen, Junbo Wang, Jiesong Yang, Wenlang Zhao, Hongmin Jiang, Xiaoye Huo
| Nature Verified
Abstract Angular acceleration plays a very critical role for the dynamic control of the accurate attitude estimation of the unmanned aerial vehicles (UAVs), which is conventionally acquired by the differentiation of the gyroscope signals. However, this indirect derivation inherently introduces detrimental phase lags and amplifies noise, thereby compromising the control stability of flight control systems.
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TM-IoV: A First-of-Its-Kind Multilabeled Trust Parameter Dataset for Evaluating Trust in the Internet of Vehicles

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By Yingxun Wang, Adnan Mahmood, Hushairi Zen, Mohamad Faizrizwan Mohd
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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