2021 11th International Conference on Information Technology in Medicine and Education (ITME)最新文献_第10页

OFHR: Online Streaming Feature Selection With Hierarchical Structure Based on Relief 基于浮雕的分层结构在线流媒体特征选择

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00038

Chenxi Wang, Xiaoqing Zhang, Jinkun Chen, Yu Mao, Shaozi Li, Yaojin Lin

{"title":"OFHR: Online Streaming Feature Selection With Hierarchical Structure Based on Relief","authors":"Chenxi Wang, Xiaoqing Zhang, Jinkun Chen, Yu Mao, Shaozi Li, Yaojin Lin","doi":"10.1109/ITME53901.2021.00038","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00038","url":null,"abstract":"Hierarchical classification learning, an emerging classification task in machine learning, is an essential topic. In which various feature selection algorithms have been proposed to select informative features for hierarchical classification. How-ever, existing hierarchical feature selection algorithms consider that the feature space of data is completely obtained in advance, and neglect the uncertainty and dynamism, i.e., feature arrives dynamically in an online manner. In this paper, we present an online streaming feature selection framework with hierarchical structure. First, we apply the closeness matrix between internal nodes to the Relief algorithm, which can calculate the weights of the dynamic features. Second, significant features are dynamically selected for each internal node by considering the hierarchical relationships and feature weights between nodes in the tree structure. Moreover, we perform redundant analysis of features by calculating the covariance between features, and then obtain a superior online feature subset for each internal node. Finally, the proposed algorithm is compared with six online streaming feature selection methods on six hierarchical data sets. The experimental results prove that our algorithm can improve the classification accuracy of the classifier by 10% compared to the suboptimal algorithms, which indicates that the algorithm outperforms other comparative algorithms in hierarchical data sets.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"1 1","pages":"140-145"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82962993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploration of the mechanism of action of stabbing and releasing blood combined with auricular acupressure in the treatment of chronic urticaria 针刺放血配合耳穴按压治疗慢性荨麻疹的作用机制探讨

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00094

Boyuan Wang, Fangzi Shi, Yu Shi, Xuejun Zhang, Mingxin Sun, Yanjun Wang

{"title":"Exploration of the mechanism of action of stabbing and releasing blood combined with auricular acupressure in the treatment of chronic urticaria","authors":"Boyuan Wang, Fangzi Shi, Yu Shi, Xuejun Zhang, Mingxin Sun, Yanjun Wang","doi":"10.1109/ITME53901.2021.00094","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00094","url":null,"abstract":"Objectives: This study aimed to investigate the efficacy of stabbing and bleeding combined with auricular pressure in the treatment of chronic urticaria (CU) and the differential metabolites in the serum of patients before and after the treatment. Methods: Six patients with CU who met the requirements were recruited, and the changes in the degree of wind mass and itching at different time points were assessed using the Urticaria Activity Score (UAS), the Visual Analog Scale (VAS) score of pruritus intensity, and the Dermatologic Disease Quality of Life Index (DLQI). The differential metabolites in the serum of patients before and after the treatment were further analyzed using liquid chromatography-mass spectrometry duplex (LC/MS) and non-targeted metabolomics analysis. Results: Compared with baseline scores, UAS, VAS, and DLQI scores decreased significantly in six patients after the treatment, with statistically significant differences (P < 0.05). Results also suggested that stabbing and releasing blood for CU could down-regulate lysophosphatidylcholine (LPC) in patients' serum. Conclusion: The combination of piercing and bloodletting with auricular acupressure can effectively improve the life quality of CU patients through lowering LPC in serum, and thus alleviating the clinical symptoms and improving the cure rate of CU patients.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"32 1","pages":"439-445"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81186094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Intelligent Personalized Learning Mode in Big Data Era 大数据时代智能个性化学习模式分析

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00116

Wang Haipeng, Tang Tiantian, M. Zhongyang, Zheng Yuanjie, Wang Hong, Jia Weikuan, Guo Qiang

{"title":"Analysis of Intelligent Personalized Learning Mode in Big Data Era","authors":"Wang Haipeng, Tang Tiantian, M. Zhongyang, Zheng Yuanjie, Wang Hong, Jia Weikuan, Guo Qiang","doi":"10.1109/ITME53901.2021.00116","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00116","url":null,"abstract":"With the advent of the era of big data, a new generation of intelligent information processing technology develop rapidly and vigorously, which has greatly promoted the innovative reform in the concept of education and teaching. The aim of this research is to promote learning efficiency and teaching precision through using big data technology and intelligent means. An intelligent personalized learning mode is built, which mainly including four aspects: academic analysis, intelligent push, individual feedback, multiple evaluations. The mode can conduct in-depth mining and analysis of student data, enrich students' off-class learning resources, intelligently push students' individual learning feedback in real time, and conduct multiple evaluations for each student. Consequently the mode completely changing the deficiency of the traditional learning mode, including one-sided cognition of each students, insufficient learning resources, lack of real-time feedback and single learning evaluation. The mode can form an intelligent and efficient personalized learning environment based on making the overall learning process quantifiable, real-time feedback, and evaluable.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"21 1","pages":"548-551"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78410240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Construction Path Exploration on the External Practice Teaching Bases under the Background of New Engineering 新工程背景下校外实践教学基地建设路径探索

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00130

Zhong-hua Luo

{"title":"Construction Path Exploration on the External Practice Teaching Bases under the Background of New Engineering","authors":"Zhong-hua Luo","doi":"10.1109/ITME53901.2021.00130","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00130","url":null,"abstract":"The external practice teaching bases for college students is an important mode for collaborative education between universities and enterprises. During the process of talent training in applied universities, the external practicing and teaching plays a key role in promoting students to consolidate professional knowledge, improving engineering practical ability and innovation ability, and cultivate new engineering talents urgently needed for enterprises. In view of the problems existing in the construction of external practicing and teaching bases, combined with professional characteristics and enterprise needs, the strategies of practical teaching bases construction and management are discussed in the paper. The practice of bases construction in recent years has shown that students' engineering practical ability, teamwork ability and employment competitiveness have been significantly improved, and the quality of practical teaching has been steadily improved, which provides a valuable reference for innovating practical teaching reform in application-oriented universities.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"34 1","pages":"614-617"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79288827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using Visualization to Teach an Introductory Programming Course with Python 使用可视化来教授Python编程入门课程

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00109

Zhiqi Xu, Xuewen Shen, Shengyou Lin, Fan Zhang

引用次数: 1

3D Forest-tree Modeling Approach Based on Loading Segment Models 基于加载段模型的三维森林树木建模方法

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00022

Cui Zeyu, Huaiqing Zhang, Nianfu Zhu, Tingdong Yang, Liu Yang, Yuanqing Zuo, Zhang Jing, Hua-Lin Zhang, Lin-lin Wang

引用次数: 3

Skeleton Based Action Quality Assessment of Figure Skating Videos 基于骨架的花样滑冰视频动作质量评价

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00048

Huiyong Li, Qing Lei, Hongbo Zhang, Jixiang Du

{"title":"Skeleton Based Action Quality Assessment of Figure Skating Videos","authors":"Huiyong Li, Qing Lei, Hongbo Zhang, Jixiang Du","doi":"10.1109/ITME53901.2021.00048","DOIUrl":"https://doi.org/10.1109/ITME53901.2021.00048","url":null,"abstract":"Action quality assessment(AQA) aims at achieving automatic evaluation the performance of human actions in video. Compared with action recognition problem, AQA focuses more on subtle differences both in spatial and temporal dimensions during the whole executing process of actions. However, most existing AQA methods tried to extract features directly from RGB videos through a 3D ConvNets, which makes the features mixed with useless scene information. To overcome this problem, We propose a deep pose feature learning AQA method that captured detailed and meaningful representations for skeleton information to discover the subtle motion difference of AQA problem. We first apply pose estimation method to obtain human skeleton data from RGB videos. Then a spatio-temporal graph convolutional network (ST-GCN) is employed to extract the dynamic changes of skeleton data and obtain the representative pose features. Finally, a regressor composed of three fully connected layers is developed to reduce the dimension of the obtained pose features and predict the final score. Experiments on MIT figure skating dataset have been extensively conducted, and the results demonstrate that the proposed method has achieved improvements that outperformed current state-of-the-art methods.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"64 1","pages":"196-200"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90428058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Keyword-based Data Augmentation Guided Chinese Medical Questions Classification 基于关键字的数据增强引导中医问题分类

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00076

XU Xinghao, Hu Rong, Du Guodong, Xiang Yan, Ma Lei

引用次数: 0

Analysis of a Worm Virus Propagation Model Based on Differential Equation 基于微分方程的蠕虫病毒传播模型分析

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00057

Yu Xiehua, Li Shaozi

引用次数: 0

MCFF: Plant leaf detection based on multi-scale CNN feature fusion MCFF:基于多尺度CNN特征融合的植物叶片检测

2021 11th International Conference on Information Technology in Medicine and Education (ITME) Pub Date : 2021-11-01 DOI: 10.1109/ITME53901.2021.00058

Ying Li, Zhaohong Huang, Yang Sun

引用次数: 2