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Carlos Alfonso Zafra-Mejía, Hugo Alexander Rondón-Quintana and Carlos Felipe Urazán-Bonells
The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply sy...
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Hao Sun, Zile Jia, Meng Zhao, Jiayuan Tian, Dan Liu and Yifei Wang
The current lack of a high-precision, real-time model applicable to the control optimization process of heat exchange systems, especially the difficulty in determining the overall heat transfer coefficient K of heat exchanger operating parameters in real...
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Florent Grotto, Oscar Peta, Christophe Bouvet, Bruno Castanié and Joël Serra
Airworthiness certification requires proof of structure strength, which is performed generally through a building block approach. To achieve this, representative intermediate-scale experiments generated by test benches are, in general, needed, in additio...
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Yifei Xu, Te Li, Min Xu, Ling Tan and Shuanghe Shen
Climate change exerts significant impacts on regional agricultural production. This study assesses the implications of climate change on winter wheat yields in the Huang-Huai-Hai Plain (3H Plain), utilizing bias-corrected climate projections from the Cou...
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Zhenyu Yin, Feiqing Zhang, Guangyuan Xu, Guangjie Han and Yuanguo Bi
Confronting the challenge of identifying unknown fault types in rolling bearing fault diagnosis, this study introduces a multi-scale bearing fault diagnosis method based on transfer learning. Initially, a multi-scale feature extraction network, MBDCNet, ...
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Baoyu Fan, Han Ma, Yue Liu and Xiaochen Yuan
With the growth of data in the real world, datasets often encounter the problem of long-tailed distribution of class sample sizes. In long-tailed image recognition, existing solutions usually adopt a class rebalancing strategy, such as reweighting based ...
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George Tzougas and Konstantin Kutzkov
We developed a methodology for the neural network boosting of logistic regression aimed at learning an additional model structure from the data. In particular, we constructed two classes of neural network-based models: shallow?dense neural networks with ...
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Hongmei Zhang, Zhijie Li, Zishang Yang, Chenhui Zhu, Yinhai Ding, Pengchang Li and Xun He
Real-time knowledge of kernel breakage during corn harvesting plays a significant role in the adjustment of operational parameters of corn kernel harvesters. (1) Transfer learning by initializing the DenseNet121 network with pre-trained weights for train...
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Dmitry Grebennikov, Rostislav Savinkov, Ekaterina Zelenova, Gennady Lobov and Gennady Bocharov
Animal models of diseases, particularly mice, are considered to be the cornerstone for translational research in immunology. The aim of the present study is to model the geometry and analyze the network structure of the murine lymphatic system (LS). The ...
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Martin Wynn and Kerstin Felser
As digitalisation sweeps through industries, companies are having to deal with the resultant changes in business models, core processes and organisational structures. This includes the reassessment of the role of the IT department, traditionally the guar...
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