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Pengyu Wei, Chuntong Li, Ze Jiang and Deyu Wang
Digital twins, an innovative technology propelled by data and models, play a seminal role in the digital transformation and intelligent upgrade of ships. This study introduces a digital twin methodology for the real-time monitoring of ship structure defo...
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Weihan Huang, Ke Gao and Yu Feng
Predicting earthquakes through reasonable methods can significantly reduce the damage caused by secondary disasters such as tsunamis. Recently, machine learning (ML) approaches have been employed to predict laboratory earthquakes using stick-slip dynamic...
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Jinwu Wang, Zhe Liu, Mao Yang, Wenqi Zhou, Han Tang, Long Qi, Qi Wang and Yi-Jia Wang
Weeds compete with rice for sunlight and nutrients and are prone to harboring pathogens, leading to reduced rice yields. Addressing the issues of low weeding efficiency and weed mortality rates in existing inter-row weeding devices, the study proposes th...
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Todd Kelmar, Maria Chierichetti and Fatemeh Davoudi Kakhki
This study introduces an innovative approach for optimizing sensor placement in modal testing by applying machine learning with enhanced efficiency and precision.
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Chang Yan, Wen-Jie Fan, Da-Miao Wang and Wen-Zhang Zhang
Mechanical interfaces are prevalent in industries like aerospace and maritime, where the normal contact stiffness on these surfaces is a crucial component of the overall stiffness of mechanical structures. From the perspective of structural mechanics, no...
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