AI blended teaching in business English based on deep learning theory

Author(s):  
Chuan Liu
2019 ◽  
Vol 15 (11) ◽  
pp. 155014771988816 ◽  
Author(s):  
Bing Han ◽  
Xiaohui Yang ◽  
Yafeng Ren ◽  
Wanggui Lan

The running state of a geared transmission system affects the stability and reliability of the whole mechanical system. It will greatly reduce the maintenance cost of a mechanical system to identify the faulty state of the geared transmission system. Based on the measured gear fault vibration signals and the deep learning theory, four fault diagnosis neural network models including fast Fourier transform–deep belief network model, wavelet transform–convolutional neural network model, Hilbert-Huang transform–convolutional neural network model, and comprehensive deep neural network model are developed and trained respectively. The results show that the gear fault diagnosis method based on deep learning theory can effectively identify various gear faults under real test conditions. The comprehensive deep neural network model is the most effective one in gear fault recognition.


2020 ◽  
Vol 218 ◽  
pp. 04030
Author(s):  
Jinchun Zhang ◽  
Dongshui Zhang

As the new direction of education reform in the internet era, the SPOC-based blended teaching mode has become increasingly popular in universities, because it can enrich teaching content, diversify learning path, enhance interaction between teachers and learners, and most importantly improve students’ learning enthusiasm and effectiveness. However, due to the lack of substantial knowledge and strategies on SPOC-based teaching concept as well as computer technology, many English teachers cannot conduct SPOC-based blended teaching mode well in their classes even though they have the intention to do it well. Therefore, taking business English reading course as a case study, this paper explores some effective strategies on how to apply SPOC-based blended teaching in English courses, so as to provide useful enlightenment for foreign language teachers in universities and colleges to better conduct blended teaching in their classes in the future.


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