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Yongsheng Yang, Zhongtao He, Haiqing Yao, Yifei Wang, Junkai Feng and Yuzhen Wu
Due to their unique structural design, portal cranes have been extensively utilized in bulk cargo and container terminals. The bearing fault of their drive motors is a critical issue that significantly impacts their operational efficiency. Moreover, the ...
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Zafar Mahmood, Naveed Anwer Butt, Ghani Ur Rehman, Muhammad Zubair, Muhammad Aslam, Afzal Badshah and Syeda Fizzah Jilani
The classification of imbalanced and overlapping data has provided customary insight over the last decade, as most real-world applications comprise multiple classes with an imbalanced distribution of samples. Samples from different classes overlap near c...
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Alysha van Duynhoven and Suzana Dragicevic
An open problem impeding the use of deep learning (DL) models for forecasting land cover (LC) changes is their bias toward persistent cells. By providing sample weights for model training, LC changes can be allocated greater influence in adjustments to m...
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Fei Sun, Run Wang, Bo Wan, Yanjun Su, Qinghua Guo, Youxin Huang and Xincai Wu
Imbalanced learning is a methodological challenge in remote sensing communities, especially in complex areas where the spectral similarity exists between land covers. Obtaining high-confidence classification results for imbalanced class issues is highly ...
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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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Marek Gruszczynski
The paper discusses methodological topics of bankruptcy prediction modelling?unbalanced sampling, sample bias, and unbiased predictions of bankruptcy. Bankruptcy models are typically estimated with the use of non-random samples, which creates sample choi...
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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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Valerii Kozlovskyi, Ivan Shvets, Yurii Lysetskyi, Mikolaj Karpinski, Aigul Shaikhanova and Gulmira Shangytbayeva
The classification of the natural and anthropogenic destabilizing factors of a telecommunications network as a complex system is presented herein. This research shows that to evaluate the parameters of a telecommunications network in the presence of dest...
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Zibo Zhuang, Hui Zhang, Pak-Wai Chan, Hongda Tai and Zheng Deng
By addressing the imbalanced proportions of the data category samples in the velocity structure function of the LiDAR turbulence identification model, we propose a flight turbulence identification model utilizing both a conditional generative adversarial...
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Yingze Song, Degang Yang, Weicheng Wu, Xin Zhang, Jie Zhou, Zhaoxu Tian, Chencan Wang and Yingxu Song
Landslide susceptibility assessment (LSA) based on machine learning methods has been widely used in landslide geological hazard management and research. However, the problem of sample imbalance in landslide susceptibility assessment, where landslide samp...
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Usman Sammani Sani, Owais Ahmed Malik and Daphne Teck Ching Lai
Wireless network parameters such as transmitting power, antenna height, and cell radius are determined based on predicted path loss. The prediction is carried out using empirical or deterministic models. Deterministic models provide accurate predictions ...
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J. Madhu Babu,S. Venkateswarlu
Pág. 38 - 46
A 22-year-old youth, a native of Andhra Pradesh, who had converted to Islam and allegedly joined the Islamic State terror group taking an oath to carry out subversive activities in the country at the instigation of a Mumbai-based IS sympathiser, was arre...
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Hyeon-Su Lee, Seung-Hwan Hong, Gwan-Heon Kim, Hye-Jin You, Eun-Young Lee, Jae-Hwan Jeong, Jin-Woo Ahn and June-Hyuk Kim
Technological advances in information-processing capacity have enabled integrated analyses (multi-omics) of different omics data types, improving target discovery and clinical diagnosis. This study proposes novel artificial intelligence (AI) learning str...
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Yiliang Wan, Yuwen Fei, Rui Jin, Tao Wu and Xinguang He
The effective extraction of impervious surfaces is critical to monitor their expansion and ensure the sustainable development of cities. Open geographic data can provide a large number of training samples for machine learning methods based on remote-sens...
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Javed Rashid, Maryam Ishfaq, Ghulam Ali, Muhammad R. Saeed, Mubasher Hussain, Tamim Alkhalifah, Fahad Alturise and Noor Samand
Melanoma is a fatal type of skin cancer; the fury spread results in a high fatality rate when the malignancy is not treated at an initial stage. The patients? lives can be saved by accurately detecting skin cancer at an initial stage. A quick and precise...
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Fujun Du, Shuangjian Jiao and Kaili Chu
To ensure the safety and rational use of bridge traffic lines, the existing bridge structural damage detection models are not perfect for feature extraction and have difficulty meeting the practicability of detection equipment. Based on the YOLO (You Onl...
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Yuchao Wang, Jingdong Li, Zeming Chen and Chenglong Wang
In order to solve the problem of low accuracy of small target detection in traditional target detection algorithms, the YOLOX algorithm combined with Convolutional Block Attention Module (CBAM) is proposed. The algorithm first uses CBAM on the shallow fe...
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Zhipeng Qing, Qiangyu Zeng, Hao Wang, Yin Liu, Taisong Xiong and Shihao Zhang
Early warning and forecasting of tornadoes began to combine artificial intelligence (AI) and machine learning (ML) algorithms to improve identification efficiency in the past few years. Applying machine learning algorithms to detect tornadoes usually enc...
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Yong Hu, Boyu Ping, Deliang Zeng, Yuguang Niu and Yaokui Gao
Monitoring and diagnosis of coal mill systems are critical to the security operation of power plants. The traditional data-driven fault diagnosis methods often result in low fault recognition rate or even misjudgment due to the imbalance between fault da...
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Partomo Partomo,Sjafri Mangkuprawira,Aida Vitayala S. Hubeis,Luky Adrianto
Pág. 104
Rawa Pening is an ecological system which plays an important social role for surrounding residents. Human activities which exploited it initiate crisis of fishery natural resources. Rawa Pening management could not ignore involvement of stakeholders if i...
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