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Analysis of the frequency–response stability and reliability of a tower-column unstable rock mass on a high and steep slope

Autor: Fuchuan Zhou, Xinrong Liu, Hongmei Tang, Mengqi Miao, Bin Xu, Xueyan Guo

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)

Abstract The first-order second-moment checking point method was introduced to judge the instability probability and evaluate the stability of the TCURM. The frequency–response stability calculation and the reliability results were compared, and a

Externí odkaz: https://doaj.org/article/c69476cc41994a029dcd517a6c75abf2

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Sparse-Representation-Network-Based Feature Learning of Vibration Signal for Machinery Fault Diagnosis

Autor: Mengqi Miao, Jianbo Yu

Publikováno v: IEEE Transactions on Industrial Informatics. 19:6706-6716

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2dce29e3e7b757d55c4a59459fe8e8dc
https://doi.org/10.1109/tii.2022.3188507

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Sparse Representation Convolutional Autoencoder for Feature Learning of Vibration Signals and its Applications in Machinery Fault Diagnosis

Autor: Mengqi Miao, Yuanhang Sun, Jianbo Yu

Publikováno v: IEEE Transactions on Industrial Electronics. 69:13565-13575

Vibration signals are widely utilized in many fields, which can reflect machine health state. Those typical deep learning techniques cannot learn impulsive features from vibration signals due to interference of strong background noise. Supervised lea

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fd5e1dd1352aaef2605a5e1e49de2da7
https://doi.org/10.1109/tie.2021.3128895

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A Deep Domain Adaptative Network for Remaining Useful Life Prediction of Machines Under Different Working Conditions and Fault Modes

Autor: Jianbo Yu, Mengqi Miao

Publikováno v: IEEE Transactions on Instrumentation and Measurement. 70:1-14

As one of the key techniques in prognostic health management (PHM), remaining useful life (RUL) prediction of machine relies on sufficient prior observed degradation data. Most previous RUL prediction methods assume that feature distributions of both

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8be9590183aa1469f3c68e69c21f0a6b
https://doi.org/10.1109/tim.2021.3084305

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Combining combretastatin A4 phosphate with ginsenoside Rd synergistically inhibited hepatocellular carcinoma by reducing HIF-1α via PI3K/AKT/mTOR signalling pathway

Autor: Cuihua Jiang, Dongjian Zhang, Yicheng Ni, Xinxiu Yang, Mengqi Miao, Zhiqi Yin, Jing Chen, Meng Gao, Jian Zhang

Publikováno v: Journal of Pharmacy and Pharmacology. 73:263-271

Objectives Combretastatin A4 phosphate (CA4P), a vascular disrupting agent (VDA), can cause rapid tumour vessel occlusion. Subsequently, extensive necrosis is discovered in the tumour center, which induces widespread hypoxia and the rise of the α su

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6582019cb26d4347d2a1b7e2cdda34fa
https://doi.org/10.1093/jpp/rgaa006

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Prevent the Language Model from being Overconfident in Neural Machine Translation

Autor: Fandong Meng, Xiao-Hua Zhou, Jie Zhou, Yijin Liu, Mengqi Miao

Publikováno v: Scopus-Elsevier
ACL/IJCNLP (1)

The Neural Machine Translation (NMT) model is essentially a joint language model conditioned on both the source sentence and partial translation. Therefore, the NMT model naturally involves the mechanism of the Language Model (LM) that predicts the n

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::edf79a3b8af891cb82eeb5174360e74b

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