摘要：
Mobile augmented reality (AR) technology creates realistic learning situations and a strong sense of immersion, which is conducive to enhance learning experience and stimulate learning motivation. However, existing mobile outdoor augmented reality applications generally have a complicated operation process and a mismatch between learning resources and corresponding scenes, which leads to a poor learning experience. Therefore, we propose a lightweight mobile outdoor AR method that combines deep learning and knowledge modeling to perceive learning scenes with a goal to improve learning experience. This method improves the accuracy of scene perception and resources retrieval and provides a convenient mobile AR technology solution for outdoor learning. To evaluate the proposed method, we provide objective criteria to assess the effectiveness of the lightweight object detection model and the learning resources retrieval approach. Simultaneously, we investigate the evaluation of participants majoring in teacher education on the usability of the proposed method by the modified system usability scale questionnaire and net promoter score. Experimental results demonstrate that our method achieves high detection accuracy, good usability, and is of great significance to improve outdoor learning experience.
摘要：
In recent years, online education service platform has swept the world due to its high quality, openness and variety of education resource, and user registered in online platform has increased dramatically. However, the traditional centralized information storage method based on the third-party may cause problems such as the loss and disclosure of the transaction subject identity data, seriously threatening the legitimate rights and interests of users. Therefore, based on education service theory, this paper applies blockchain technology to identity authentication to design and implement a blockchain-based digital education transaction subject identity authentication system. The system proposed in this study can store identity information in ciphertext form and is jointly verified and maintained by the entire network node, thus it can guarantee the security and reliability of identity data in the digital identity authentication.
关键词：
Belief;Community of practice;Engagement;Teachers' professional development;Teaching thinking
摘要：
This study investigated how teachers' beliefs (i.e., beliefs about teaching thinking, acceptance of the community of practice, and acceptance of the school culture) and engagement (i.e., engagement in learning and engagement in practice on teaching thinking) affected their perceived professional development in the Alliance of Thinking Schools (ATS), which is a multi-regional community of practice (CoP) on teaching thinking for K-12 teachers in China. A total of 478 teachers from 39 schools in 10 cities participated in this study. The regression analysis results indicated that teachers' beliefs about teaching thinking, followed by engagement in practice, engagement in learning, and acceptance of the CoP, were significant predictors to their perceived professional development. However, teachers' acceptance of the school culture was not a significant predictor. This study suggests that multi-regional CoPs could eliminate the barriers to teachers' professional development regarding the school culture. Schools should provide opportunities for teachers to engage in the practice, rather than one-shot training.
期刊：
International Journal of Wavelets, Multiresolution and Information Processing,2019年17(1):1950001 ISSN：0219-6913
通讯作者：
Wei, Yantao
作者机构：
[Yao, Huang; Shi, Yafei; Wei, Yantao; Tong, Mingwen; Liu, Qingtang; Chen, Tiantian; Deng, Wei; Zhao, Gang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.;[Pan, Donghui] Anhui Univ, Sch Math Sci, Hefei 230601, Anhui, Peoples R China.
通讯机构：
[Wei, Yantao] C;Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.
关键词：
Student body gesture recognition;fisher broad learning system;learning analytics
摘要：
<jats:p> Observing student body gesture has been widely used to assess teaching effectiveness over the past few decades. However, manual observation is not suitable for the automatic data analysis in the field of learning analytics. Consequently, a student body gesture recognition method based on Fisher Broad Learning System (FBLS) and Local Log-Euclidean Multivariate Gaussian (L<jats:sup>2</jats:sup>EMG) is proposed in this paper. FBLS is designed by introducing the discriminative information into the hidden layer of Broad Learning System (BLS) and reducing the dimensionality of hidden-layer representations. FBLS has superiorities in accuracy and speed. In addition, L<jats:sup>2</jats:sup>EMG, which is a highly distinctive descriptor, characterizes the local image with a multivariate Gaussian distribution. So L<jats:sup>2</jats:sup>EMG features are fed into the FBLS for recognition in this paper. Extensive experimental results on self-built dataset show that the proposed student body gesture recognition method obtains better results than other benchmarking methods. </jats:p>
期刊：
Proceedings of 2017 6th International Conference on Computer Science and Network Technology, ICCSNT 2017,2018年2018-January:157-160
通讯作者：
Zan, Hui(zxydhh@163.com)
作者机构：
[Luo, Zhuoran; Yu, Peng; Zhao, Gang; Lu, Shuai] School of Educational Information Technology, Central China Normal University, Wuhan, 430079, China;[Zhao, Dasheng] Wuhan Maritime Communication Research Institute, Wuhan, 430079, China;[Zan, Hui] National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, 430079, China
通讯机构：
National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China
期刊：
Lecture Notes in Computer Science,2018年10749:314-325 ISSN：0302-9743
通讯作者：
He, Bin
作者机构：
[Yu, Xinguo; He, Bin; Jian, Pengpeng; Xia, Meng] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.;[Zhao, Gang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.
通讯机构：
[He, Bin] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
会议名称：
8th Pacific-Rim Symposium on Image and Video Technology (PSIVT)
会议时间：
NOV 20-24, 2017
会议地点：
Wuhan, PEOPLES R CHINA
会议主办单位：
[Yu, Xinguo;Jian, Pengpeng;He, Bin;Xia, Meng] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.^[Zhao, Gang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.
摘要：
This paper presents an algorithm for understanding problems from circuit schematics in exercise problems in physics at secondary school. This paper models the problem understanding as a problem of extracting a set of relations that can be used to solve problems with enough information. The challenges lie in not only analyzing the circuit schematics but also extracting the proper relations for a given exercise problem. To face these challenges a novel approach is proposed to detect circuit nodes with their current flows to extract the current equations for nodes. And the other novel approach is proposed to extract voltage equations of independent loops. The proposed approach was tested with a dataset collected from the text books and the exam papers for the students at secondary schools. Experimental results show that the effect of recognition and analysis we designed delivers promising result, and our approach can be adapted to more complex electrical circuit analysis.
期刊：
PROCEEDINGS OF 2018 IEEE 9TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS),2018年2018-November:1108-1111 ISSN：2327-0586
通讯作者：
Zhao, Gang
作者机构：
[Liu, Shan; Chu, Jie; Zhao, Gang; Zhang, Qing; Li, Yaxu] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.;[Lin, Luyu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
通讯机构：
[Zhao, Gang] C;Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.
会议名称：
2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS)
会议时间：
November 2018
会议地点：
Beijing, China
会议主办单位：
China Hall Sci & Technol
会议论文集名称：
2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS)
摘要：
High school statistical graph classification is one of the key steps in intelligent mathematics problem solving system. In this paper, a hierarchial classification method is proposed for high school statistical graph classification. Firstly, the dense Scale-invariant Feature Transform (SIFT) features of the input images are extracted. Secondly, the sparse coding of the SIFT features are obtained. Thirdly, these sparse features are pooled in multiscale. Finally, these pooled features are concatenated and then fed into single-hidden layer feedforward neural network for classification. The effectiveness of the proposed method is demonstrated on the constructed dataset, which contains 400 statistical graphs. In contrast to several state-of-the-art methods, the proposed method achieves better performance in terms of classification accuracy, especially when the size of the training samples is small.
摘要：
Tujia brocade as one of the national intangible cultural heritages in China, is an outstanding representative of traditional Chinese folk handicraft. However, there are many problems with cultural resources on Tujia brocade skills, such as its distribution is not concentrated, lack of semantic organization, difficult to obtain and dissemination and so on. In view of these problems, this paper constructs a set of Tujia brocade cultural knowledge base system based on ontology, initially, we proposes a method of ontology modeling in Tujia brocade domain, and constructs the ontology model of Tujia brocade domain via using ontology technology, and then design and realize the ontology annotation, semantic association and knowledge retrieval and display functions for Tujia brocade cultural knowledge through the system demand analysis. The system has realized the reasonable organization of Tujia brocade cultural resources, it will contributes to the widespread dissemination and sharing of Tujia brocade cultural knowledge.
期刊：
Journal of Computing Science and Engineering,2017年11(2):39-48 ISSN：1976-4677
通讯作者：
Liu, Qingtang(liuqtang@mail.ccnu.edu.cn)
作者机构：
[Qingtang Liu; Mingbo Shao; Linjing Wu; Gang Zhao; Guilin Fan] School of Educational Information Technology, Central China Normal University, Wuhan, China;[Jun Li] School of Information Engineering, Hubei University for Nationalities, Enshi, China
通讯机构：
School of Educational Information Technology, Central China Normal University, Wuhan, China
摘要：
Tujia Brocade is one of the five Chinese famous brocades. Tujia brocade yarn, which uses botanic dyeing, is gradually disappearing because of the impact of modern industry. China has attached great importance to the digital protection of ancient craftsmanship nowadays; it is of great significance for the protection of Tujia brocade culture by using digital technology to show the process and reproduce history and human environment what has disappeared. This paper studies the modeling and realistic simulation of Tujia brocade yarn, initially and gets the twist, hairiness, color and shape characteristics of Tujia brocade yarn via instrument measuring and image processing technology, subsequently utilizes the simulation technology to realize the realistic simulation of Tujia brocade yarn, as so to achieve the digital and virtual reproduction of Tujia Brocade.
期刊：
2017 6th Data Driven Control and Learning Systems (DDCLS),2017年:553-557
通讯作者：
Zan, Hui
作者机构：
[Lu, Shuai; Chen, Yawen; Yu, Yali; Di, Bingbing; Zhao, Gang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.;[Zan, Hui; Zhao, Gang] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Zan, Hui] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
会议名称：
6th IEEE Data Driven Control and Learning Systems Conference (DDCLS)
会议时间：
MAY 26-27, 2017
会议地点：
Chongqing, PEOPLES R CHINA
会议主办单位：
[Zhao, Gang;Chen, Yawen;Di, Bingbing;Lu, Shuai;Yu, Yali] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.^[Zhao, Gang;Zan, Hui] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
摘要：
The Tujia nationality's brocade (short as Tujia brocade or Xilankapu) is one of the Tujia traditional handicrafts; it has been widely used in Tujia people's daily life, especially for the people reside in the YouShui River Basin. Tujia brocade not only has many varieties, manifestations and performance styles, but also very rich design patterns, these exhibits aesthetic sentiment and national consciousness. It is important effect on the deep excavation of Tujia brocade culture and virtual design by analyzing the compositional structure and structural parameters of Tujia brocade, The paper deconstructs and analysis the structures of Tujia brocade, discusses the hierarchical composition and structure parameter in the analysis of a large number of traditional classic patterns. It develops Tujia brocade structure simulation and interactive design system based on Unity 3D technology, which simulates innovative patterns and presents them visually by changing the compositional structure parameters values, these vector diagrams of Tujia brocade could be directly used in the intelligent machine production.
作者机构：
[Chen, Yawen; Liu, Shan; Chu, Jie; Luo, Zhuoran; Zhao, Gang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.;[Lin, Luyu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
会议名称：
3rd IEEE International Conference on Computer and Communications (ICCC)
会议时间：
DEC 13-16, 2017
会议地点：
Chengdu, PEOPLES R CHINA
会议主办单位：
[Zhao, Gang;Chen, Yawen;Liu, Shan;Chu, Jie;Luo, Zhuoran] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Hubei, Peoples R China.^[Lin, Luyu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
摘要：
With the continuous development of information technology, the applications of barcode have become more and more widely, and its quality requirements are also increasing. Due to the poverty typography and printing equipment, and the imperfect printing technology, there are a lot of problems such as flying ink, missing printed, wrong print, black spots and improper registration existing in the process of barcode printing. The traditional way of manually sorting defective barcode is not only inefficient but also easily influenced by many factors, which leads to the low precision of the detection. In order to solve these problems, this paper proposes a method of barcode defect detection based on Tesseract-OCR, firstly, the method uses the horizontal projection method to segment the barcode, and then it uses the Tesseract-OCR method to recognize the characters in the barcode, lastly, it combines Levenshtein Distance algorithm to detect the character defects. In this paper, 1000 barcode images were used to the experiment, and the experimental results show that the accuracy of detection results can reach 94.3%, which proves the feasibility of the method.
期刊：
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE,2017年30(23):e4457- ISSN：1532-0626
通讯作者：
Zhao, Gang
作者机构：
[Chen, Yawen; Wang, Qi; Liu, Shan; Zhao, Gang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.;[Hu, Tao] Hubei Univ Nationalities, Sch Informat Engn, Enshi 445000, Peoples R China.;[Lin, Luyu] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.;[Zhao, Dasheng] Wuhan Maritime Commun Res Inst, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Zhao, Gang] C;Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.
关键词：
convolutional neural network;deep learning;eye state classification;face detection;student drowsiness
摘要：
Drowsy student state detection is helpful to understand the students' learning state, which is the necessary and basic aspect of teaching activities evaluation and assessment. The performance of traditional methods may deteriorate dramatically because of the external environment factors. In this paper, a novel drowsy student state detection method by integrating deep convolutional neural network is proposed at the first time in the literature. The proposed method avoids the complicated manual feature extraction operation and it can effectively reduce the interference of environmental factors in the application scenarios. Experimental results demonstrate that our approach can achieve high accuracy and lower error rate for drowsy student state detection. In addition, the results also show that our method outperforms traditional methods.
