摘要：
Evaluation of children with Autism Spectrum Disorders (ASD) is crucial to clinical diagnosis and educational intervention. The traditional evaluation methods based on questionnaires and scales rely on the experience and expertise of the evaluator, are time-consuming and clinically demanding. Computer games can provide an objective, motiving and safe way for evaluating and reflecting children's development. Therefore, the study aimed to investigate a technology-based method using computer games to evaluate children with ASD. The performance of 40 children with ASD and 51 aged-matched typically developing (TD) children was compared. We found: 1) The completion ratio for children with ASD was lower than TD children for the tasks in most of the games. 2) Significant differences between the ASD and TD groups, but no significant differences within group. 3) The performance of the TD group was better than ASD and the efficiency of TD group was proportional to age. While more research is needed to confirm its reliability and validity, the findings indicate that computer games have great potential in the field of special education as an evaluation tool to clarify difficulties associated with autism.
作者机构：
[Zhang, Kai] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.;[Zhang, Kai] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Hubei, Peoples R China.;[Zhang, Kai] Univ Regina, Dept Comp Sci, Regina, SK, Canada.
通讯机构：
[Zhang, Kai] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
摘要：
This paper proposes a Bayesian knowledge tracing model with three learning states by extending the original two learning states. We divide a learning process into three sections by using an evaluation function for three-way decisions. Advantages of such a trisection over traditional bisection are demonstrated by comparative experiments. We develop a three learning states model based on the trisection of the learning process. We apply the model to a series of comparative experiments with the original model. Qualitative and quantitative analyses of the experimental results indicate the superior performance of the proposed model over the original model in terms of prediction accuracies and related statistical measures. (C) 2018 Elsevier B.V. All rights reserved.
作者：
Zhang, Kun*;Suo, Jintao;Chen, Jingying;Liu, Xiaodi;Gao, Lei
期刊：
PROCEEDINGS OF THE 2017 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS),2017年:1297-1300 ISSN：2325-0348
通讯作者：
Zhang, Kun
作者机构：
[Gao, Lei; Liu, Xiaodi; Zhang, Kun; Suo, Jintao; Chen, Jingying] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
通讯机构：
[Zhang, Kun] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
会议名称：
2017 Federated Conference on Computer Science and Information Systems (FedCSIS)
会议时间：
September 2017
会议地点：
Prague, Czech Republic
会议主办单位：
[Zhang, Kun;Suo, Jintao;Chen, Jingying;Liu, Xiaodi;Gao, Lei] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
会议论文集名称：
2017 Federated Conference on Computer Science and Information Systems (FedCSIS)
摘要：
Fire safety education is essential to every student on campus. Fire safety knowledge learning and operational practice are both important. There is evidence that the virtual reality (VR) based educational method can be a novel and effective approach to learning and practice. However, the existing VR-based system for fire safety education has some shortcomings such as lack of interactivity and high equipment complexity, resulting in low practicability. In order to improve the effect of fire safety education on campus, this paper establishes the model and architecture of fire safety education system based on VR technology. The framework and various elements of fire safety education system are designed and implemented according to the combination of relevant fire safety education theory and VR technology. Finally the prototype version of fire safety education system based on VR technology is built on the HTC VIVE helmet equipment. Through the usability test and comparative analysis of the application experiment, the experiment results prove the feasibility and effectiveness of the proposed approach.
作者机构：
[Liu, Leyuan; Luo, Zhenzhen; Su, Zhiming; Luo, Nan; Zhang, Kun; Liu, Yuanyuan; Chen, Jingying] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Liu, Yuanyuan] Wenhua Coll, Wuhan, Peoples R China.
通讯机构：
[Chen, Jingying] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.
关键词：
Database systems;Decision trees;Forestry;Image resolution;Textures;Attention estimations;Geometric feature;Head Pose Estimation;Human Machine Interface;Probabilistic models;Unconstrained environments;Weighted voting;Weighted voting methods;Random forests;accuracy;Article;classification;classification algorithm;Dirichlet tree distribution enhanced random forest;facies;image analysis;intermethod comparison;mathematical analysis;mathematical model;noise;prediction;priority journal;probability;random forest
摘要：
Head pose estimation (HPE) is important in human-machine interfaces. However, various illumination, occlusion, low image resolution and wide scene make the estimation task difficult. Hence, a Dirichlet-tree distribution enhanced Random Forests approach (D-RF) is proposed in this paper to estimate head pose efficiently and robustly in unconstrained environment. First, positive/negative facial patch is classified to eliminate influence of noise and occlusion. Then, the D-RF is proposed to estimate the head pose in a coarse-to-fine way using more powerful combined texture and geometric features of the classified positive patches. Furthermore, multiple probabilistic models have been learned in the leaves of the D-RF and a composite weighted voting method is introduced to improve the discrimination capability of the approach. Experiments have been done on three standard databases including two public databases and our lab database with head pose spanning from -90 to 90 in vertical and horizontal directions under various conditions, the average accuracy rate reaches 76.2% with 25 classes. The proposed approach has also been evaluated with the low resolution database collected from an overhead camera in a classroom, the average accuracy rate reaches 80.5% with 15 classes. The encouraging results suggest a strong potential for head pose and attention estimation in unconstrained environment. Head pose estimation (HPE) is important in human-machine interfaces. However, various illumination, occlusion, low image resolution and wide scene make the estimation task difficult. Hence, a Dirichlet-tree distribution enhanced Random Forests approach (D-RF) is proposed in this paper to estimate head pose efficiently and robustly in unconstrained environment. First, positive/negative facial patch is classified to eliminate influence of noise and occlusion. Then, the D-RF is proposed to estimate the head pose in a coarse-to-fine way using more powerful combined texture and geometric features of the classified positive patches. Furthermore, multiple probabilistic models have been learned in the leaves of the D-RF and a composite weighted voting method is introduced to improve the discrimination capability of the approach. Experiments have been done on three standard databases including two public databases and our lab database with head pose spanning from -90 to 90 in vertical and horizontal directions under various conditions, the average accuracy rate reaches 76.2% with 25 classes. The proposed approach has also been evaluated with the low resolution database collected from an overhead camera in a classroom, the average accuracy rate reaches 80.5% with 15 classes. The encouraging results suggest a strong potential for head pose and attention estimation in unconstrained environment.
作者：
Chen, Jingying*;Chen, Dan;Li, Xiaoli;Zhang, Kun
期刊：
IEEE Transactions on Industrial Informatics,2014年10(1):323-330 ISSN：1551-3203
通讯作者：
Chen, Jingying
作者机构：
[Zhang, Kun; Chen, Jingying] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.;[Chen, Dan] China Univ Geosci, Sch Comp Sci, Wuhan 430074, Peoples R China.;[Li, Xiaoli] Beijing Normal Univ, Natl Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China.
通讯机构：
[Chen, Jingying] C;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
关键词：
Behavior detection;intelligent systems;multimodal sensory information;social communication skills
摘要：
How to improve social communication skills for children, especially those with social communication difficulties such as attention deficit/hyperactivity disorder, has long been a challenge faced by researchers and therapists. Recent research indicates that computer-assisted approaches may be effective in addressing this issue. This study aimed to understand children's behaviors and then provide appropriate support to improve their social communication skills. We have established an intelligent system, inside which a child can freely play interactive social skills games with virtual characters. The virtual characters can adjust their own behaviors by adapting to the child's cognitive state (e.g., focus of attention) and affective state (e.g., happiness or surprise). The child's behavior is identified in real-time by recognition of multimodal sensory information, which includes head pose and eye gaze estimation, gesture detection, and affective state detection supported by a series of algorithms proposed in this study. Furthermore, this intelligent system has been enabled in a nonintrusive manner using a novel approach of multicamera surveillance to provide the child with natural interaction with the system. Experimental results show the system can estimate a user's attention and affective states with correctness rates of 93% and 91.3%, respectively. The results obtained suggest that the methods have strong potential as alternative methods for sensing human behavior and providing appropriate support.
作者：
Kai Zhang;Ying Zhai;Hon Wai Leong;Shengming Wang
期刊：
ACM International Conference Proceeding Series,2012年:219-222
通讯作者：
Wang, S.(victor@mail.ccnu.edu.cn)
作者机构：
[Kai Zhang; Ying Zhai; Shengming Wang] National Engineering Research Center for E-Learning, Central China Normal University, 152 Luoyu Avenue, Wuhan, Hubei Province, 430079, China;[Hon Wai Leong] Dept of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543, Singapore
通讯机构：
National Engineering Research Center for E-Learning, Central China Normal University, 152 Luoyu Avenue, China
会议论文集名称：
ICIMCS '12: Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
期刊：
Journal of Computational Information Systems,2012年8(17):7317-7323 ISSN：1553-9105
通讯作者：
Zhang, K.(kaipresent@gmail.com)
作者机构：
[Liu, Sanya; Zhang, Kai; Yang, Zongkai; Wang, Shengming] 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, China
