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Haipeng Lin, Xuefeng Song, Fei Dai, Fengwei Zhang, Qiang Xie and Huhu Chen
Hardness is a critical mechanical property of grains. Accurate predictions of grain hardness play a crucial role in improving grain milling efficiency, reducing grain breakage during transportation, and selecting high-quality crops. In this study, we dev...
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Matija Zvonaric, Mirta Ben?ic, Ivana Bari?ic and Tihomir Dok?anovic
The high stiffness of cement-bound aggregate (CBA) is recognized as its main drawback. The stiffness is described by the modulus of elasticity, which is difficult to determine precisely in CBA. Incorporating rubber in these mixtures reduces their stiffne...
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Dwaipayan Chakraborty and Subhashis Mallick
Ocean-water temperature and salinity are two vital properties that are required for weather-, climate-, and marine biology-related research. These properties are usually measured using disposable instruments at sparse locations, typically from tens to hu...
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Sai Wang, Guoping Fu, Yongduo Song, Jing Wen, Tuanqi Guo, Hongjin Zhang and Tuantuan Wang
The development of intelligent oceans requires exploration and an understanding of the various characteristics of the oceans. The emerging Internet of Underwater Things (IoUT) is an extension of the Internet of Things (IoT) to underwater environments, an...
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Dibo Dong, Shangwei Wang, Qiaoying Guo, Yiting Ding, Xing Li and Zicheng You
Predicting wind speed over the ocean is difficult due to the unequal distribution of buoy stations and the occasional fluctuations in the wind field. This study proposes a dynamic graph embedding-based graph neural network?long short-term memory joint fr...
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Kostiantyn Medvediev, Anna Kharchenko, Anzhelika Stakhova, Yurii Yevseichyk, Vitalii Tsybulskyi and Adrián Bekö
The proposed methodology aims to determine and forecast the technical condition of bridge elements, which could serve as an advanced engineering tool for assessing reliability and durability. It is developed based on fundamental studies that synthesize t...
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Sipho G. Thango, Georgios A. Drosopoulos, Siphesihle M. Motsa and Georgios E. Stavroulakis
A methodology to predict key aspects of the structural response of masonry walls under blast loading using artificial neural networks (ANN) is presented in this paper. The failure patterns of masonry walls due to in and out-of-plane loading are complex d...
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Gao Huang, Chengjun Qiu, Mengtian Song, Wei Qu, Yuan Zhuang, Kaixuan Chen, Kaijie Huang, Jiaqi Gao, Jianfeng Hao and Huili Hao
Cavitation is typically observed when high-pressure submerged water jets are used. A composite nozzle, based on an organ pipe, can increase shear stress on the incoming flow, significantly enhancing cavitation performance by stacking Helmholtz cavities i...
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Bimkubwa Seif Ali, Juan Jose Castro, Shogo Omi and Karishma Nazimi
Ancient civilizations have imprinted their legacy on Zanzibar Stone Town through the construction of revered stone masonry buildings, which are experiencing rapid deterioration due to severe ambient environmental impacts. In response to these challenges,...
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Sihan Song, Qiujing Zhou, Tao Zhang and Yintao Hu
Concrete dam deformation prediction is important for assessing the safety of dams. A TPE-STL-LSTM deformation prediction model for concrete dams is established by introducing the TPE algorithm based on the decomposition?prediction model. Taking the Wanji...
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