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2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)最新文献

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Evaluation Model of Classroom Teaching Quality of Chinese as a Foreign Language Based on Deep Learning 基于深度学习的对外汉语课堂教学质量评价模型
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/icvris51417.2020.00220
Jie Gu
{"title":"Evaluation Model of Classroom Teaching Quality of Chinese as a Foreign Language Based on Deep Learning","authors":"Jie Gu","doi":"10.1109/icvris51417.2020.00220","DOIUrl":"https://doi.org/10.1109/icvris51417.2020.00220","url":null,"abstract":"In order to improve the classroom teaching quality of Chinese as a foreign language and attract more foreigners to participate in Chinese learning, a model for evaluating the quality of Chinese as a foreign language based on deep learning is proposed. Through the study of macro and micro indicators such as teaching methods, teaching tools, teaching content, curriculum relevance, teaching attitudes, etc., a classroom teaching quality evaluation index system is established to improve the coverage of quality evaluation. Based on the quantification of the processing qualitative indicators of deep learning, the deep learning data flow diagram is drawn according to the depth of different quality nodes in the teaching behavior, and the quality evaluation results is classified to complete the comprehensive evaluation of classroom teaching quality. In addition, by calculating the vector value of classroom teaching quality, planning experiment groups, and setting up comparative experiments, it is verified that the proposed model is more practical in the actual classroom teaching quality evaluation.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123593238","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
Design and Implementation of ShenTong Database Comparison Tool based on ODBC under Kylin Platform 麒麟平台下基于ODBC的神通数据库比对工具的设计与实现
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/ICVRIS51417.2020.00015
Guang Xiaoxia, Li Yonggang, Mao Wen, Hou Yawei, Zuo Yanqin
{"title":"Design and Implementation of ShenTong Database Comparison Tool based on ODBC under Kylin Platform","authors":"Guang Xiaoxia, Li Yonggang, Mao Wen, Hou Yawei, Zuo Yanqin","doi":"10.1109/ICVRIS51417.2020.00015","DOIUrl":"https://doi.org/10.1109/ICVRIS51417.2020.00015","url":null,"abstract":"At present, there is no effective ShenTong database comparison software under the domestic Kylin operating system platform. The database comparison is mainly performed manually, which may cause heavy workload and high error rate. This article mainly studies the ShenTong database content comparison method based on Unix ODBC interface under the Kylin operating system platform, designs a software-based comparison method using ODBC driver, and implements the ShenTong database comparison software by executing SQL scripts or statements, which can compare two database instances, show the difference of tables and records, edit and synchronize the instances. At present, the software has been successfully applied to the maritime tracking and control software system, which greatly improved the work efficiency.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125044746","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
Accounting Auditing And Evaluation Of Colleges And Universities Taking Account Of Operation Cost Accounting Matrix Algorithm 考虑运营成本会计矩阵算法的高校会计审计与评价
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/ICVRIS51417.2020.00217
Qiang Liu
{"title":"Accounting Auditing And Evaluation Of Colleges And Universities Taking Account Of Operation Cost Accounting Matrix Algorithm","authors":"Qiang Liu","doi":"10.1109/ICVRIS51417.2020.00217","DOIUrl":"https://doi.org/10.1109/ICVRIS51417.2020.00217","url":null,"abstract":"Various industries have begun to use this form of computerized accounting, and relatively speaking, they already have a specific field. For accounting work, the use of accounting computerization can greatly improve the quality and efficiency of work, and many companies begin to pay attention to this form of calculation. Based on the matrix algorithm of activity cost accounting, this paper makes a specific assessment of the risks of computerized accounting in colleges and universities, and sorts out the reasons for the formation of risks, and proposes solutions to them, which can effectively reduce the risk during actual operation and can reduce The workload is more important to be able to adapt to the requirements of the development of computerized accounting. The application of the matrix in the activity-based cost accounting method is used for the collection of manufacturing expenses, and for the distribution of operation costs among products.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128567400","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
Vehicle Detection Method Based on GhostNet-SSD 基于GhostNet-SSD的车辆检测方法
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/ICVRIS51417.2020.00053
Jing Liu, Wei Cong, Hongyan Li
{"title":"Vehicle Detection Method Based on GhostNet-SSD","authors":"Jing Liu, Wei Cong, Hongyan Li","doi":"10.1109/ICVRIS51417.2020.00053","DOIUrl":"https://doi.org/10.1109/ICVRIS51417.2020.00053","url":null,"abstract":"The traditional vehicle target detection algorithm needs to select appropriate features for different image scenes, resulting in poor generalization ability. In order to solve this problem, this paper proposes an image vehicle detection method based on SSD. This method combines GhostNet and SSD to extract feature maps from GhostNet for classified and location prediction. To some extent, the detection accuracy and speed of the vehicle are improved. Experimental results show that this method has a high recognition rate and is better than the traditional algorithm.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128186849","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: 3
Acquisition Technology for the Third Beidou Satellite Navigation Signal with Low Signal-to-Noise Ratio and High Dynamic 低信噪比、高动态的北斗第三卫星导航信号采集技术
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/ICVRIS51417.2020.00100
Yong Qin, Yucheng Zhang, Jianxin Guo, Bo Guo
{"title":"Acquisition Technology for the Third Beidou Satellite Navigation Signal with Low Signal-to-Noise Ratio and High Dynamic","authors":"Yong Qin, Yucheng Zhang, Jianxin Guo, Bo Guo","doi":"10.1109/ICVRIS51417.2020.00100","DOIUrl":"https://doi.org/10.1109/ICVRIS51417.2020.00100","url":null,"abstract":"In order to solve the problem of acquisition of the third generation Beidou satellite navigation signal with low SNR and high dynamic, a BOC (1,1) signal acquisition technology based on the non-coherent accumulation of BPSK-like PMF-FFT is proposed. The influence of carrier Doppler frequency offset and code Doppler on PN code acquisition is considered simultaneously in this algorithm, according to searching range for Doppler frequency offset, first-order Doppler frequency offset changing rate and code Doppler, the parameters of acquisition algorithm are determined, and the quantitative analysis results of detection value are given. The detection probability formula of the acquisition algorithm is derived, and its correctness is proved, Compared with the minimum carrier to noise ratio of Beidou system, the algorithm in this paper has a margin of 9.7db in the worst case. Finally, the scheme of carrier Doppler rate of change and code Doppler compensation for extremely low SNR and high dynamic signals is given.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128429416","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
Game theory Power control algorithm based on network connectivity 基于网络连通性的功率控制算法
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/ICVRIS51417.2020.00194
Yuanyuan Yang, Rui-xia Liu, Lipan Bian
{"title":"Game theory Power control algorithm based on network connectivity","authors":"Yuanyuan Yang, Rui-xia Liu, Lipan Bian","doi":"10.1109/ICVRIS51417.2020.00194","DOIUrl":"https://doi.org/10.1109/ICVRIS51417.2020.00194","url":null,"abstract":"Power control plays an important role in reducing interference and conflict between Wireless Body Area Networks (WBAN). The goal of power control is to send the collected data with as small and appropriate transmission power as possible, which largely depends on the network type or different application scenarios. In this paper, a utility function based on network connectivity is established based on the basic principle of non-cooperative game theory. The algorithm considers the cost function based on SINR and proves the existence and uniqueness of Nash equilibrium solution.The algorithm proves that the Nash equilibrium solution exists and is unique through the analysis of the utility function.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127369358","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
Development of wheel hub motor brake recovery control test bench 轮毂电机制动恢复控制试验台的研制
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/ICVRIS51417.2020.00166
Zhang Li, Zongmei Hu, Taiwei Zhang, Zhanxiang He, Tonglin Han
{"title":"Development of wheel hub motor brake recovery control test bench","authors":"Zhang Li, Zongmei Hu, Taiwei Zhang, Zhanxiang He, Tonglin Han","doi":"10.1109/ICVRIS51417.2020.00166","DOIUrl":"https://doi.org/10.1109/ICVRIS51417.2020.00166","url":null,"abstract":"Aiming at the electric vehicle driven by hub motor, a test bench was designed and developed in order to study the brake recovery of the electric vehicle driven by hub. It can provide experimental basis for the use of the hub-driven electric vehicle. The test bench adopts modular design, and many other test modules can be added on the basis of the mechanical part of the bench. For some major electric vehicle tests, the designed bench can well realize simulation and experiment.The test bench is equipped with road resistance simulation, weight simulation, lateral force simulation, other test functions and braking energy recovery, etc. It is a test bench for the comprehensive performance of electric vehicle driven by hub motor. The electric wheel module integrates various functions of vehicle driving, steering and braking. The maximum limit of the platform is simulated under real working conditions. Therefore, it can test these performances well. The test bench uses a hybrid battery and ultracapacitor, that is, a battery-ultracapacitor hybrid storage unit, to give play to the advantages of large specific energy of the battery and large specific power of the ultracapacitor. It can satisfy the dual requirements of the electric vehicle’s comparative energy and specific power and extend the driving range to the maximum extent, which provided a convenient for the research of wheel drive EV.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130078177","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
Feature Extraction of Face Image Based on Convolutional Neural Network 基于卷积神经网络的人脸图像特征提取
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/ICVRIS51417.2020.00107
Zhaofu Lin, Liu Lei
{"title":"Feature Extraction of Face Image Based on Convolutional Neural Network","authors":"Zhaofu Lin, Liu Lei","doi":"10.1109/ICVRIS51417.2020.00107","DOIUrl":"https://doi.org/10.1109/ICVRIS51417.2020.00107","url":null,"abstract":"In order to overcome the problem of inaccuracy in feature extraction when the corner features are not obvious in traditional corner detection methods, a face feature extraction method based on deep learning convolutional neural network is proposed in this paper. The key point of this method is the construction algorithm of convolution network with single image as input data. In this paper, the convolutional neural network implemented by Python code includes three convolution layers, three lower sampling layers and one full connection layer. The filter structure is designed and the characteristic image is obtained. The convolution layer uses the Reul function as the activation function, while the lower sampling layer uses the maximum pooling and ruul activation functions. The experimental results show that the method based on the different levels of image features extracted by deep learning network as the basis for image matching, and can still achieve good recognition effect when the traditional features such as corners are not clear.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128865059","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 on extraction method of flat gain characteristics of multi-channel radar antenna 多通道雷达天线平坦增益特性提取方法研究
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/ICVRIS51417.2020.00263
Jia-guo Lu, Zong'ang Liu, Zhen Dong
{"title":"Research on extraction method of flat gain characteristics of multi-channel radar antenna","authors":"Jia-guo Lu, Zong'ang Liu, Zhen Dong","doi":"10.1109/ICVRIS51417.2020.00263","DOIUrl":"https://doi.org/10.1109/ICVRIS51417.2020.00263","url":null,"abstract":"The beam flatness gain of multichannel radar antenna is an important auxiliary characteristic in the process of target detection and recognition. Active multi-target jamming is a typical method to extract flat beam gain of multi-channel radar antenna. It affects the detection, tracking and recognition ability of phased array radar, and also affects the judgment of phased array radar on the status. In order to improve the detection ability and networking ability of phased array radar, this paper optimizes the extraction method of beam flattening gain characteristics of multi-channel radar antenna under the background of accurate main lobe interference, so as to ensure the normal operation of radar antenna device. Finally, the numerical simulation is carried out. Experimental results show that this method can effectively suppress active multi-target interference. This conclusion is of great significance to improve the detection ability of radar in complex electromagnetic environment.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126742919","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 on Multi-feature Extraction Method in EEG Signal of Motor Imagination 运动想象脑电信号多特征提取方法研究
2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2020-07-01 DOI: 10.1109/ICVRIS51417.2020.00116
Li Dezhi, Zhang Xintong, Geng Xiaozhong
{"title":"Research on Multi-feature Extraction Method in EEG Signal of Motor Imagination","authors":"Li Dezhi, Zhang Xintong, Geng Xiaozhong","doi":"10.1109/ICVRIS51417.2020.00116","DOIUrl":"https://doi.org/10.1109/ICVRIS51417.2020.00116","url":null,"abstract":"The feature extraction of EEG signals of motor imaging is a very important step in the brain-computer interface system. We usually use the event-related synchronization/desynchronization (ERS/ERD) phenomenon of EEG signals, and use common motor imagination EEG signal’s feature extraction processing algorithms, including Common Spatial Pattern (CSP), Power Spectral Density (PSD), Autoregressive model (AR), Discrete Wavelet Transform DWT) method and other methods to extract features of EEG signals. This paper expounds the basic principle of the algorithm, and finally uses the support vector machine (SVM) to classify the left-hand and right-hand motor imagery patterns after processing the four methods. Comparative experiments show that the feature extraction method of multi-feature fusion better represents EEG features, and a better classification effect can be achieved by using SUM classification. This study can meet the requirements of BCI for high recognition rate.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121164549","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
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