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Gilbert Hinge, Mohamed A. Hamouda and Mohamed M. Mohamed
In recent years, there has been a growing interest in flood susceptibility modeling. In this study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the nature and evolution of literature, intellectual structure networks, ...
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Jingxiong Lei, Xuzhi Liu, Haolang Yang, Zeyu Zeng and Jun Feng
High-resolution remote sensing images (HRRSI) have important theoretical and practical value in urban planning. However, current segmentation methods often struggle with issues like blurred edges and loss of detailed information due to the intricate back...
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Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
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Hang Li, Shengjie Zhao and Hao Deng
The extraction of community-scale green infrastructure (CSGI) poses challenges due to limited training data and the diverse scales of the targets. In this paper, we reannotate a training dataset of CSGI and propose a three-stage transfer learning method ...
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Enrico Santangelo, Angelo Del Giudice, Simone Figorilli, Simona Violino, Corrado Costa, Marco Bascietto, Simone Bergonzoli and Claudio Beni
The autonecrotic tomato line V20368 (working code IGSV) spontaneously develops necrotic lesions with acropetal progression in response to an increase in temperature and light irradiation. The process is associated with the interaction between tomato and ...
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Lijun Ma, Meng Sun and Yunlong Zhang
In order to facilitate waste glass recycling and enable the monitoring of concrete structures, this study prepares a new type of self-sensing engineered cementitious composite (ECC) via the use of glass sand instead of silica sand. The health monitoring ...
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Ali Mirzazade, Cosmin Popescu and Björn Täljsten
The aim of this study was to find strains in embedded reinforcement by monitoring surface deformations. Compared with analytical methods, application of the machine learning regression technique imparts a noteworthy reduction in modeling complexity cause...
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Valery Nkemeni, Fabien Mieyeville and Pierre Tsafack
In wireless sensor network-based water pipeline monitoring (WWPM) systems, a vital requirement emerges: the achievement of low energy consumption. This primary goal arises from the fundamental necessity to ensure the sustained operability of sensor nodes...
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Marco Bonopera
Stress state evaluation in axially loaded structural members is significant for sustaining and preserving the service life of buildings. While successful monitoring furnishes staunch information on the health, integrity, safety and serviceability of stru...
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Qianlong Jin, Yu Tian, Weicong Zhan, Qiming Sang, Jiancheng Yu and Xiaohui Wang
Efficiently predicting high-resolution and accurate flow fields through networked autonomous marine vehicles (AMVs) is crucial for diverse applications. Nonetheless, a research gap exists in the seamless integration of data-driven flow modeling, real-tim...
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