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The Influence of Public Mental Health Based on Artificial Intelligence Technology on the Teaching Effect of Business Administration Major
As an emerging technology, public mental health based on artificial intelligence engineering has broad application and development prospects in improving teaching effects, realizing high efficiency and intelligence, and improving refined education. The application of public mental health based on ar...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Hindawi
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481349/ https://www.ncbi.nlm.nih.gov/pubmed/36120146 http://dx.doi.org/10.1155/2022/5353889 |
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author | Lu, Yixia |
author_facet | Lu, Yixia |
author_sort | Lu, Yixia |
collection | PubMed |
description | As an emerging technology, public mental health based on artificial intelligence engineering has broad application and development prospects in improving teaching effects, realizing high efficiency and intelligence, and improving refined education. The application of public mental health based on artificial intelligence engineering in the practice of the teaching effect of business administration has a very positive significance for accurately discovering the mental health and teaching effect of business administration students. For the sake of improving the teaching effect of business administration major, we come up with a method for the influence of public mental health on the teaching effect of business administration profession based on artificial intelligence engineering. Firstly, we collect the video and audio of the teaching of business administration, conducts data screening and cleaning, and sorts out the video and audio synchronization clips as training data. Secondly, we propose a multimodal feature extraction network and a multimodal fusion network for the extraction and fusion of video and audio clips, respectively. Then, the fully connected network structure is used to evaluate and classify the effect of business administration professional teaching, and use mental health factors for evaluation to avoid human intervention and improve the prediction effect. Finally, through intensive experimental results, we prove that the method raised by us can use artificial intelligence engineering to evaluate the teaching effect of business administration majors from the perspective of public mental health and achieve good experimental results. |
format | Online Article Text |
id | pubmed-9481349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94813492022-09-17 The Influence of Public Mental Health Based on Artificial Intelligence Technology on the Teaching Effect of Business Administration Major Lu, Yixia J Environ Public Health Research Article As an emerging technology, public mental health based on artificial intelligence engineering has broad application and development prospects in improving teaching effects, realizing high efficiency and intelligence, and improving refined education. The application of public mental health based on artificial intelligence engineering in the practice of the teaching effect of business administration has a very positive significance for accurately discovering the mental health and teaching effect of business administration students. For the sake of improving the teaching effect of business administration major, we come up with a method for the influence of public mental health on the teaching effect of business administration profession based on artificial intelligence engineering. Firstly, we collect the video and audio of the teaching of business administration, conducts data screening and cleaning, and sorts out the video and audio synchronization clips as training data. Secondly, we propose a multimodal feature extraction network and a multimodal fusion network for the extraction and fusion of video and audio clips, respectively. Then, the fully connected network structure is used to evaluate and classify the effect of business administration professional teaching, and use mental health factors for evaluation to avoid human intervention and improve the prediction effect. Finally, through intensive experimental results, we prove that the method raised by us can use artificial intelligence engineering to evaluate the teaching effect of business administration majors from the perspective of public mental health and achieve good experimental results. Hindawi 2022-09-09 /pmc/articles/PMC9481349/ /pubmed/36120146 http://dx.doi.org/10.1155/2022/5353889 Text en Copyright © 2022 Yixia Lu. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Lu, Yixia The Influence of Public Mental Health Based on Artificial Intelligence Technology on the Teaching Effect of Business Administration Major |
title | The Influence of Public Mental Health Based on Artificial Intelligence Technology on the Teaching Effect of Business Administration Major |
title_full | The Influence of Public Mental Health Based on Artificial Intelligence Technology on the Teaching Effect of Business Administration Major |
title_fullStr | The Influence of Public Mental Health Based on Artificial Intelligence Technology on the Teaching Effect of Business Administration Major |
title_full_unstemmed | The Influence of Public Mental Health Based on Artificial Intelligence Technology on the Teaching Effect of Business Administration Major |
title_short | The Influence of Public Mental Health Based on Artificial Intelligence Technology on the Teaching Effect of Business Administration Major |
title_sort | influence of public mental health based on artificial intelligence technology on the teaching effect of business administration major |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481349/ https://www.ncbi.nlm.nih.gov/pubmed/36120146 http://dx.doi.org/10.1155/2022/5353889 |
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