2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)最新文献_第5页

Research on the Problems and Countermeasures in Network teaching of law Major in the era of artificial intelligence 人工智能时代法律专业网络教学存在的问题及对策研究

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00018

Xiaoxian Pu

{"title":"Research on the Problems and Countermeasures in Network teaching of law Major in the era of artificial intelligence","authors":"Xiaoxian Pu","doi":"10.1109/ICAIE53562.2021.00018","DOIUrl":"https://doi.org/10.1109/ICAIE53562.2021.00018","url":null,"abstract":"Artificial intelligence constantly puts forward new and sensitive requirements for the knowledge transmission of law discipline, focusing on the development and reform of legal education mode in the era of artificial intelligence, and realizing the perfect integration of artificial intelligence and law. The network teaching caused by novel coronavirus epidemic is changing the teaching methods of teachers and the learning methods of students, especially the influence on the education mode of law major. In the era of artificial intelligence, legal talents should pay close attention to the social reality and actively respond to the great challenges and opportunities given by artificial intelligence and other emerging technologies. With the popularization of network education, its own shortcomings have gradually emerged. This paper investigates the views of law students on the network teaching effect of law major in the era of artificial intelligence through questionnaire survey, and summarizes the survey data to find out the shortcomings of the network teaching model. Aiming at the existing problems, this paper puts forward some innovative strategies, such as establishing a normal crisis coping mechanism, selecting ways to stimulate students' interest in learning and implementing teaching, and establishing a diversified teaching system, in the hope of improving the online teaching of law major.","PeriodicalId":285278,"journal":{"name":"2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121225746","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

Performance of compression algorithms for radio signal data 无线电信号数据压缩算法的性能

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00056

Wang Zhi-xin, Yu Xin-dong, Li Hai-Feng, Feng Tao, Zheng Lu, Liu Jun-Wei

{"title":"Performance of compression algorithms for radio signal data","authors":"Wang Zhi-xin, Yu Xin-dong, Li Hai-Feng, Feng Tao, Zheng Lu, Liu Jun-Wei","doi":"10.1109/ICAIE53562.2021.00056","DOIUrl":"https://doi.org/10.1109/ICAIE53562.2021.00056","url":null,"abstract":"In the face of the shortage of radio spectrum resources, the contradiction between supply and demand and other issues, data compression technology can ensure data integrity while saving storage space, effectively improving the utilization of spectrum resources. This article first makes lossless Huffman coding, LZ77, LZ78, and LZW algorithms. The compression technology is briefly introduced, and the application of various algorithms and the corresponding advantages and disadvantages are analyzed with examples. Secondly, for the radio signal data of the radio monitoring station in Gansu Province, the performance of these commonly used lossless compression algorithms is compared. Finally, the experimental test result data proves that when the compressed file is large, the LZ series algorithm has a better compression effect than the Huffman algorithm. In LZ series, LZW algorithm has the best compression effect, LZ77 algorithm has the worst compression effect, and the compression effect of LZ78 is between them. When the compressed file is small, because the data in the compressed file is less, the compression effect of several algorithms is not obvious.","PeriodicalId":285278,"journal":{"name":"2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127157937","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

A study on the reform of course teaching under the concept of blended learning based on Chaoxing platform 基于超星平台的混合学习理念下的课程教学改革研究

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00069

Song Hao

{"title":"A study on the reform of course teaching under the concept of blended learning based on Chaoxing platform","authors":"Song Hao","doi":"10.1109/ICAIE53562.2021.00069","DOIUrl":"https://doi.org/10.1109/ICAIE53562.2021.00069","url":null,"abstract":"The current Internet era is an era of interconnectedness and information explosion, and most people can obtain all kinds of knowledge and practical skills they need from the vast amount of information, which has brought a great impact on the traditional teaching mode: in the past, teachers had to teach a lot of knowledge in the traditional classroom, but this has become less necessary in the Internet era. In this paper, the importance and special characteristics of the course are clarified from the position and role of the course \"History of Urban Construction and Planning\" in the teaching of urban and rural planning majors; combined with the author’s teaching practice of the course in the past ten years, the teaching mode of the course and the traditional classroom is summarized and reflected to a certain extent. The paper focuses on the significance and application of blended learning concept in the teaching reform of History of Urban Construction and Planning, and clarifies through a comprehensive discussion that it is indeed the best time to carry out catechism teaching and blended learning. The paper focuses on the significance and application of the blended learning concept in the teaching reform of Urban Construction History and Planning History.","PeriodicalId":285278,"journal":{"name":"2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127520920","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

Application of Big Data Technology in the Research on Mental Health Education of College Students from Poverty-Stricken Families 大数据技术在贫困家庭大学生心理健康教育研究中的应用

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00077

Sui Yanfang, Wu Yamin

{"title":"Application of Big Data Technology in the Research on Mental Health Education of College Students from Poverty-Stricken Families","authors":"Sui Yanfang, Wu Yamin","doi":"10.1109/ICAIE53562.2021.00077","DOIUrl":"https://doi.org/10.1109/ICAIE53562.2021.00077","url":null,"abstract":"In the information age, the big data technology has been applied to all walks of life, bringing a new angle of thinking to personal life and social development. The mental health education problems have been increasingly prominent among college students and gradually become a focus of attention from universities and colleges, families and society due to the particularity of their identity and severity of their impacts. Affected by various factors, these students are more susceptible to some unhealthy mental states and mental problems in daily study and life. In this paper, the K-means clustering algorithm and C4.5 decision tree algorithm were used to establish mental health databases based on the Hadoop technology. The limitations of physical space were broken through and those of static data were improved through the data collection and processing, storage and management, analysis and mining, etc., so as to realize the accurate recognition, comprehensive mastery, coordinated development and active forewarning of students from poverty-stricken families. This study can further enhance the timeliness and pertinence of mental health education among college students from poverty-stricken families and drive the students to welcome healthy growth and become useful persons.","PeriodicalId":285278,"journal":{"name":"2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127017933","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: 1

Graphical programming modeling optimization design based on cognitive development theory 基于认知发展理论的图形化编程建模优化设计

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00135

Mengmeng Xu, Lin Liu, Zhiyuan Shao

引用次数: 0

Big Data Analysis Capability Demand Analysis and Training Measures for Smart Supply Chain Management Talents 智能供应链管理人才大数据分析能力需求分析及培养措施

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00157

Meng Linli

引用次数: 2

The Application of VR Technology in Preschool Education Professional Teaching VR技术在学前教育专业教学中的应用

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00072

Huiru Zhai

引用次数: 2

Vegetation phenology detection of deciduous broad-leaf forest using YOLOv3 from PhenoCam 利用PhenoCam的YOLOv3进行落叶阔叶林植被物候学检测

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00061

Mengying Cao, Q. Xin

{"title":"Vegetation phenology detection of deciduous broad-leaf forest using YOLOv3 from PhenoCam","authors":"Mengying Cao, Q. Xin","doi":"10.1109/ICAIE53562.2021.00061","DOIUrl":"https://doi.org/10.1109/ICAIE53562.2021.00061","url":null,"abstract":"Vegetation phenology identification is significance to the exploration of vegetation growth and is also conducive to the impact of phenology on the ecological environment. Recently, vegetation phenology detection is based on a time series of vegetation phenology to index simulation of vegetation growth time indirectly. In this study, we identify the vegetation phenology of deciduous broad-leaved forest through the deep learning method within a single PhenoCam image. The result of the phenology identification of growing regions, the accuracy MAP of daily identification in daily scales mAP up to 10.2%, which could identify the growing period of most deciduous broad-leaved forests. The identification accuracy mAP in the 8-day scale is up to 69%, and the identification mAP accuracy of vegetation could reach 98.2% when it was divided into four categories. The purpose of this study is to detect the phenological growth period of deciduous broad- leaved forest with rapid development, high precision, and fast deep learning methods. It has a great improvement on the current method of calculating the vegetation phenology period by using the traditional measurement and related mathematical and physical models. While obtaining the phenology period more quickly, it can automatically and accurately obtain the growth area and growth period of the study area, making a certain contribution to the study of vegetation phenology.","PeriodicalId":285278,"journal":{"name":"2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133794678","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

Research of firefly ecological sightseeing sites : -Based on AHP and Fuzzy Comprehensive Methods 萤火虫生态旅游点研究:基于AHP和模糊综合方法

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00130

Jia-jia Yang, Yan Liang, Xinlei Wu, Yuewei Hu, Xiao-yan Mo, Wen-Tsao Pan

引用次数: 0

The Implications of the Artificial Intelligence Capability for Language Industry Professionals: A Scientometric Analysis 人工智能能力对语言行业专业人士的影响:科学计量分析

2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) Pub Date : 2021-06-01 DOI: 10.1109/ICAIE53562.2021.00047

H. Liao, Tao Guo

引用次数: 0