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TP-MobNet: A Two-pass Mobile Network for Low-complexity Classification of Acoustic Scene

Computers, Materials & Continua 2022年第11期73卷 3291-3303页

作者： Soonshin Seo Junseok Oh eunsoo cho Hosung Park Gyujin Kim Ji-Hwan Kim NAVER Corporation Seongnam13561Korea Department of Computer Science and Engineering Sogang UniversitySeoul04107Korea

Acoustic scene classification(ASC)is a method of recognizing and classifying environments that employ acoustic *** ASC approaches based on deep learning have been developed,with convolutional neural networks(CNNs)proving to be the most reliable and commonly utilized in ASC systems due to their suitability for constructing lightweight *** using ASC systems in the real world,model complexity and device robustness are essential *** this paper,we propose a two-pass mobile network for low-complexity classification of the acoustic scene,named *** inverse residuals and linear bottlenecks,TPMobNet is based on MobileNetV2,and following mobile blocks,coordinate attention and two-pass fusion approaches are *** log-range dependencies and precise position information in feature maps can be trained via coordinate *** capturing more diverse feature resolutions at the network’s end sides,two-pass fusions can also train ***,the model size is reduced by applying weight quantization to the trained *** adding weight quantization to the trained model,the model size is also *** TAU Urban Acoustic Scenes 2020 Mobile development set was used for all of the *** has been confirmed that the proposed model,with a model size of 219.6 kB,achieves an accuracy of 73.94%.

关键词： Acoustic scene classification low-complexity device robustness two-pass mobile network coordinate attention weight quantization

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Probabilistic seismic performance assessment of lap-spliced RC columns retrofitted by steel wrapping jackets

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Earthquake Engineering and Engineering Vibration 2016年第2期15卷 223-238页

作者： eunsoo choi Heejung Youn Baik-Soon cho Department of Civil Engineering Hongik University Department of Civil Engineering CTRCInje University

In this study, the seismic fragility curves of two reinforced concrete（RC） columns that were lap-spliced at the bottom and retrofitted with steel wrapping jackets were generated. Their seismic performance was probabilistically assessed in comparison to that of lap-spliced or continuous reinforcement RC columns. This study used two types of steel wrapping jackets, a full jacket and a split jacket. Analytical models of the four types of columns were developed based on the experimental results of the columns using Open SEES, which is effective in conducting nonlinear time history analyses. A suite of ten artificial ground motions, modified from recorded ground motions, was used to perform nonlinear time history analyses of the analytical models with scaling of the peak ground acceleration from 0.1 g to 1.0 g in increments of 0.1 g. The steel wrapping jackets did not increase the medians for yield（slight damage state） of the lap-spiced column and did not exceed the corresponding median of the continuous reinforcement column. However, the two steel jackets increased the medians for failure by 1.872 and 2.017 times, respectively, and exceeded the corresponding median of the continuous reinforcement column by 11.8% and 20.5%, respectively.

关键词： columns reinforcement reinforced exceed acceleration scaling median assessed split probabilistic

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