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Fengyun Xie, Gang Li, Hui Liu, Enguang Sun and Yang Wang
In the context of addressing the challenge posed by limited fault samples in agricultural machinery rolling bearings, especially when early fault characteristics are subtle, this study introduces a novel approach. The proposed multi-domain fault diagnosi...
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George Ioannou, Georgios Alexandridis and Andreas Stafylopatis
Importance sampling, a variant of online sampling, is often used in neural network training to improve the learning process, and, in particular, the convergence speed of the model. We study, here, the performance of a set of batch selection algorithms, n...
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Kenan Shen and Dongbiao Zhao
Safe and stable operation of the aircraft hydraulic system is of great significance to the flight safety of an aircraft. Any fault may be a threat to flight safety and may lead to enormous economic losses and even human casualties. Hence, the normal stat...
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Emilija Strelcenia and Simant Prakoonwit
In many industrialized and developing nations, credit cards are one of the most widely used methods of payment for online transactions. Credit card invention has streamlined, facilitated, and enhanced internet transactions. It has, however, also given cr...
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Fang Wang, Xueliang Fu, Weijun Duan, Buyu Wang and Honghui Li
As the unique identifier of individual breeding pigs, the loss of ear tags can result in the loss of breeding pigs? identity information, leading to data gaps and confusion in production and genetic breeding records, which can have catastrophic consequen...
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Chenbo Shi, Yanhong Cheng, Chun Zhang, Jin Yuan, Yuxin Wang, Xin Jiang and Changsheng Zhu
The detection of poultry egg microcracks based on electrical characteristic models is a new and effective method. However, due to the disorder, mutation, nonlinear, time discontinuity, and other factors of the current data, detection algorithms such as s...
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Qingbin Tong, Feiyu Lu, Ziwei Feng, Qingzhu Wan, Guoping An, Junci Cao and Tao Guo
The data-driven intelligent fault diagnosis method of rolling bearings has strict requirements regarding the number and balance of fault samples. However, in practical engineering application scenarios, mechanical equipment is usually in a normal state, ...
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Shucong Liu, Hongjun Wang and Xiang Zhang
In gas turbine rotor systems, an intelligent data-driven fault diagnosis method is an important means to monitor the health status of the gas turbine, and it is necessary to obtain sufficient fault data to train the intelligent diagnosis model. In the ac...
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Jaekyung Kim, Jungwoo Huh, Ingu Park, Junhyeong Bak, Donggeon Kim and Sanghoon Lee
Deep learning-based object detection is one of the most popular research topics. However, in cases where large-scale datasets are unavailable, the training of detection models remains challenging due to the data-driven characteristics of deep learning. S...
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Jingye Ma, Xin Zeng, Xiaoping Xue and Ranran Deng
The metro transportation system will have emergency passenger flow for various reasons, resulting in passenger flow congestion, affecting efficiency and risks. In this paper, the LSTM network is applied to predict the normal passenger flow and emergency ...
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