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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Junbing Liu, Maohui Zheng, Jinwei Gao, Xinshu Wang, Hu Zhang and Simin Jiang
This article addresses the challenge of simulating rainstorm waterlogging in urban-scale areas where reliable drainage pipe network data are often lacking. Although methods have been developed to tackle this issue, there remains a gap in their effectiven...
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Dmitry Shved, Natalia Supolkina and Anna Yusupova
The increasing complexity of the space flight program and the increase in the duration of missions require an improvement in psychological monitoring tools for astronauts in orbit. This article summarizes the experience of using quantitative content anal...
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Louis Closson, Christophe Cérin, Didier Donsez and Jean-Luc Baudouin
This paper aims to provide discernment toward establishing a general framework, dedicated to data analysis and forecasting in smart buildings. It constitutes an industrial return of experience from an industrialist specializing in IoT supported by the ac...
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Liang Liu, Tianbin Li and Chunchi Ma
Three-dimensional (3D) models provide the most intuitive representation of geological conditions. Traditional modeling methods heavily depend on technicians? expertise and lack ease of updating. In this study, we introduce a deep learning-based method fo...
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Bowen Zhang, Ying Chen, Xingwei Chen, Lu Gao and Meibing Liu
Under climate change, the frequency of drought-flood abrupt alternation (DFAA) events is increasing in Southeast China. However, there is limited research on the evolution characteristics of DFAA in this region. This study evaluated the effectiveness of ...
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Ryota Higashimoto, Soh Yoshida and Mitsuji Muneyasu
This paper addresses the performance degradation of deep neural networks caused by learning with noisy labels. Recent research on this topic has exploited the memorization effect: networks fit data with clean labels during the early stages of learning an...
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Jiahao Chen, Jiaxin Li, Deqian Zheng, Qianru Zheng, Jiayi Zhang, Meimei Wu and Chaosai Liu
The multi-field coupling of grain piles in grain silos is a focal point of research in the field of grain storage. The porosity of grain piles is a critical parameter that affects the heat and moisture transfer in grain piles. To investigate the distribu...
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Zhiqiang Jiang, Yongyan Ma and Weijia Li
Accurate forecasting of ship motion is of great significance for ensuring maritime operational safety and working efficiency. A data-driven ship motion forecast method is proposed in this paper, aiming at the problems of low generalization of a single fo...
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Eduardo Morales-Vargas, Hayde Peregrina-Barreto, Rita Q. Fuentes-Aguilar, Juan Pablo Padilla-Martinez, Wendy Argelia Garcia-Suastegui and Julio C. Ramirez-San-Juan
Microvasculature analysis is an important task in the medical field due to its various applications. It has been used for the diagnosis and threat of diseases in fields such as ophthalmology, dermatology, and neurology by measuring relative blood flow or...
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