2023年学术委员会工作总结报告
2024-11-06 12:00  

2023年学术委员会工作总结报告



为进一步加强我校学术工作管理,完善学术管理体制和教授治学途径,发挥学术委员会在学校学术事务中的作用,不断提高我校学术管理水平,在2023年期间,校学术委员会成员在行政楼二楼会议室总计召开了2次学术委员会。

会议议题分别有:

一、关于对论文“Design of Network-Assisted Teaching of Ideological and Political Courses for College Students Based on Android System”、“A Deep Learning and Clustering Extraction Mechanism for Recognizing the Actions of Athletes in Sports”是否涉嫌学术不端的认定

二、是否认定“河南省艾及艾制品质量监督检验中心”、“河南省殷商文化外译与传播研究中心”为省级科研平台;

三、关于对论文“Synergy of propylene-based copolymer in high-melt-strength polypropylene for wxtrusion foaming process(张允 化学与环境工程学院)”、“Green city landscape design based on GIS system(梁彦兰 土木与建筑工程学院)、“Research on Improving the Accuracy of Ideological and Political Education in Colleges under Artificial Intelligence Technology in the Era of Big Data(孙艺斐 马克思主义学院)”、“High-Intensity Injury Recognition Pattern of Sports Athletes Based on the Deep Neural Network(陈楠 体育教学部)”、“Neural Network Model for Perceptual Evaluation of Product Modelling Design Based on Multimodal Image Recognition(吴杰 艺术设计学院)”、“Application of an Improved LSTM Model to Emotion Recognition(李源 计算机科学与信息工程学院)”是否涉嫌学术不端的认定。


经校学术委员会表决:

一、同意认定两篇论文Design of Network-Assisted Teaching of Ideological and Political Courses for College Students Based on Android System”、“A Deep Learning and Clustering Extraction Mechanism for Recognizing the Actions of Athletes in Sports”存在学术不端。

二、同意认定“河南省艾及艾制品质量监督检验中心”、“河南省殷商文化外译与传播研究中心”为省级科研平台。

三、同意认定六篇论文Synergy of propylene-based copolymer in high-melt-strength polypropylene for wxtrusion foaming process(张允 化学与环境工程学院)”、“Green city landscape design based on GIS system(梁彦兰 土木与建筑工程学院)、“Research on Improving the Accuracy of Ideological and Political Education in Colleges under Artificial Intelligence Technology in the Era of Big Data(孙艺斐 马克思主义学院)”、“High-Intensity Injury Recognition Pattern of Sports Athletes Based on the Deep Neural Network(陈楠 体育教学部)”、“Neural Network Model for Perceptual Evaluation of Product Modelling Design Based on Multimodal Image Recognition(吴杰 艺术设计学院)”、“Application of an Improved LSTM Model to Emotion Recognition(李源 计算机科学与信息工程学院)”不存在学术不端。




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