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Yadong Zhou, Zhenchao Teng, Linlin Chi and Xiaoyan Liu
Based on the unit life and death technology, the dynamic evolution process of soil loss is considered, and a pipe-soil nonlinear coupling model of buried pipelines passing through the collapse area is constructed. The analysis shows that after the third ...
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Choong Hee Cho, Yang Woo Yu and Hyeon Gyu Kim
Student dropout is a serious issue in that it not only affects the individual students who drop out but also has negative impacts on the former university, family, and society together. To resolve this, various attempts have been made to predict student ...
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Zihan Song, Sang-Ha Sung, Do-Myung Park and Byung-Kwon Park
The core of dropout prediction lies in the selection of predictive models and feature tables. Machine learning models have been shown to predict student dropouts accurately. Because students may drop out of school in any semester, the student history dat...
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José Manuel Porras, Juan Alfonso Lara, Cristóbal Romero and Sebastián Ventura
Predicting student dropout is a crucial task in online education. Traditionally, each educational entity (institution, university, faculty, department, etc.) creates and uses its own prediction model starting from its own data. However, that approach is ...
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Arup Dey, Nita Yodo, Om P. Yadav, Ragavanantham Shanmugam and Monsuru Ramoni
Data-driven algorithms have been widely applied in predicting tool wear because of the high prediction performance of the algorithms, availability of data sets, and advancements in computing capabilities in recent years. Although most algorithms are supp...
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Emanuel Marques Queiroga, Matheus Francisco Batista Machado, Virgínia Rodés Paragarino, Tiago Thompsen Primo and Cristian Cechinel
This paper describes a nationwide learning analytics initiative in Uruguay focused on the future implementation of governmental policies to mitigate student retention and dropouts in secondary education. For this, data from a total of 258,440 students we...
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Andualem Aklilu Tesfaye, Berhan Gessesse Awoke, Tesfaye Shiferaw Sida and Daniel E. Osgood
Field-scale prediction methods that use remote sensing are significant in many global projects; however, the existing methods have several limitations. In particular, the characteristics of smallholder systems pose a unique challenge in the development o...
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Sergei Strijhak, Daniil Ryazanov, Konstantin Koshelev and Aleksandr Ivanov
In this article the procedure and method for the ice accretion prediction for different airfoils using artificial neural networks (ANNs) are discussed. A dataset for the neural network is based on the numerical experiment results?obtained through iceFoam...
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Changcai Yang, Zixuan Teng, Caixia Dong, Yaohai Lin, Riqing Chen and Jian Wang
A high-efficiency, nondestructive, rapid, and automatic crop disease classification method is essential for the modernization of agriculture. To more accurately extract and fit citrus disease image features, we designed a new 13-layer convolutional neura...
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Jinsong Zhang, Yongtao Peng, Bo Ren and Taoying Li
The concentration of PM2.5 is an important index to measure the degree of air pollution. When it exceeds the standard value, it is considered to cause pollution and lower the air quality, which is harmful to human health and can cause a variety of diseas...
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