Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00036
Shengce Zhang
With the rapid spread of COVID-19, many people in China are infected, so the government has taken some actions to prevent it from getting worse. However, one of these actions—controlling population flow (also called travel blocking)—has some negative impacts on the citizens’ daily life and China’s economy. Therefore, the balance between the two and the degree to control population flow should be discussed. This research uses SEIR model to simulate the flow between regions with input of the data from three regions, and each region has regional parametric variation. Next, the analysis of the situation of having no population flow, having regular population flow, and having population flow with control is made based on the parameters of the outcomes. After getting the result of the model, an effective way of control is proposed based on analysis and comparison of the cases. At last, test is made on new control strategy. It is concluded that travel blocking should be made between regions that have great infectious rate difference.
{"title":"Analysis of Blocking Population Flow to Control COVID-19 in Multi-regions Based on Discrete SEIR Epidemic Model","authors":"Shengce Zhang","doi":"10.1109/CISCE50729.2020.00036","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00036","url":null,"abstract":"With the rapid spread of COVID-19, many people in China are infected, so the government has taken some actions to prevent it from getting worse. However, one of these actions—controlling population flow (also called travel blocking)—has some negative impacts on the citizens’ daily life and China’s economy. Therefore, the balance between the two and the degree to control population flow should be discussed. This research uses SEIR model to simulate the flow between regions with input of the data from three regions, and each region has regional parametric variation. Next, the analysis of the situation of having no population flow, having regular population flow, and having population flow with control is made based on the parameters of the outcomes. After getting the result of the model, an effective way of control is proposed based on analysis and comparison of the cases. At last, test is made on new control strategy. It is concluded that travel blocking should be made between regions that have great infectious rate difference.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"7 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":"124283525","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}
Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00018
Zhiwei Li, Shuo Yang, Xincheng An, Zhuoyue Li, Xiyu Sun, Rui Zhu, Wenguang Lin
In order to solve the problem that high-order signal features need to be extracted manually and the recognition accuracy is not high in the process of signal modulation recognition, this paper applies the depth confidence network to the modulation recognition and studies the method of signal modulation recognition based on the Deep Belief Networks (DBN). In this paper, Restricted Boltzmann Machine (RBM) is used to build the network model of DBN, and then the simulation module of the data set needed by DBN is introduced. The DBN is trained by generating signal data, and the recognition of signal is realized. Simulation results show that the recognition accuracy of the method is higher than that of other machine learning algorithm.
{"title":"Research on Signal Modulation Recognition Method Based on Deep Belief Network","authors":"Zhiwei Li, Shuo Yang, Xincheng An, Zhuoyue Li, Xiyu Sun, Rui Zhu, Wenguang Lin","doi":"10.1109/CISCE50729.2020.00018","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00018","url":null,"abstract":"In order to solve the problem that high-order signal features need to be extracted manually and the recognition accuracy is not high in the process of signal modulation recognition, this paper applies the depth confidence network to the modulation recognition and studies the method of signal modulation recognition based on the Deep Belief Networks (DBN). In this paper, Restricted Boltzmann Machine (RBM) is used to build the network model of DBN, and then the simulation module of the data set needed by DBN is introduced. The DBN is trained by generating signal data, and the recognition of signal is realized. Simulation results show that the recognition accuracy of the method is higher than that of other machine learning algorithm.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"46 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":"115517379","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}
Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00056
Huibing Zhang, Fang Pan, Junchao Dong, Ya Zhou
Aspect-based sentiment analysis is different from document-level and sentence-level sentiment analysis, which aims to predict the sentiment polarity of a certain aspect in a sentence. The accuracy of the existing aspect-based sentiment analysis model still needs to be improved. A BERT-IAN sentiment analysis model that improves the Interactive Attention Networks (IAN) model is proposed to further improve the accuracy of the aspect-based sentiment analysis. First use the BERT pre-training model to encode aspects and context respectively. Then use a transformer encoder with interactive attention to interactively learn the attention of the aspect and context, and generate a final representation. Finally, through the sentiment classification layer, the aspect corresponding sentiment are analyzed. The experimental results on Restaurant and Laptop datasets show the effectiveness and superiority of the BERT-IAN model.
{"title":"BERT-IAN Model for Aspect-based Sentiment Analysis","authors":"Huibing Zhang, Fang Pan, Junchao Dong, Ya Zhou","doi":"10.1109/CISCE50729.2020.00056","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00056","url":null,"abstract":"Aspect-based sentiment analysis is different from document-level and sentence-level sentiment analysis, which aims to predict the sentiment polarity of a certain aspect in a sentence. The accuracy of the existing aspect-based sentiment analysis model still needs to be improved. A BERT-IAN sentiment analysis model that improves the Interactive Attention Networks (IAN) model is proposed to further improve the accuracy of the aspect-based sentiment analysis. First use the BERT pre-training model to encode aspects and context respectively. Then use a transformer encoder with interactive attention to interactively learn the attention of the aspect and context, and generate a final representation. Finally, through the sentiment classification layer, the aspect corresponding sentiment are analyzed. The experimental results on Restaurant and Laptop datasets show the effectiveness and superiority of the BERT-IAN model.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"111 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":"123447632","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}
Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00062
Qiliang Hu
With the progress of information technology, big data gradually shows its extraordinary value. Big data is used in all walks of life, including education and teaching. The big data on the vocational Skills Competition can analyze the students’ mastery of vocational ability. Through big data analysis, I was informed of the projects of China Vocational Skills Competition and the awards of various provinces and cities. It is concluded that the competition of vocational skills is difficult and can train students’ various abilities. Therefore, it is proposed to take the vocational skill contest as an opportunity to improve students’ vocational ability and teaching quality and promote the development of vocational education.
{"title":"The Vocational Skills Competition Based on Big Data Analysis Promotes the Research of Students' Vocational Ability","authors":"Qiliang Hu","doi":"10.1109/CISCE50729.2020.00062","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00062","url":null,"abstract":"With the progress of information technology, big data gradually shows its extraordinary value. Big data is used in all walks of life, including education and teaching. The big data on the vocational Skills Competition can analyze the students’ mastery of vocational ability. Through big data analysis, I was informed of the projects of China Vocational Skills Competition and the awards of various provinces and cities. It is concluded that the competition of vocational skills is difficult and can train students’ various abilities. Therefore, it is proposed to take the vocational skill contest as an opportunity to improve students’ vocational ability and teaching quality and promote the development of vocational education.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"89 6 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":"126000029","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}
Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00026
Qing Xin, Shixun Wang
With the development of artificial intelligence, particle filter algorithm has become a research hotspot of Chinese and foreign scholars. Since the particle filter algorithm has better performance in the non-linear Gaussian system, the particle filter is applied in the UAV positioning system. The Monte Carlo sampling method is used for the posterior distribution. In view of the particle degradation problem existing in the particle filter algorithm, the re-sampling of the particle filter method is improved. In order to verify the performance of the improved algorithm, experiments were carried out on a quadrotor UAV platform based on STM32. The results show that the improved positioning algorithm can effectively improve the positioning accuracy of the UAV, and has good practicability.
{"title":"GPS Positioning Method of UAV Based on Improved Particle Filter","authors":"Qing Xin, Shixun Wang","doi":"10.1109/CISCE50729.2020.00026","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00026","url":null,"abstract":"With the development of artificial intelligence, particle filter algorithm has become a research hotspot of Chinese and foreign scholars. Since the particle filter algorithm has better performance in the non-linear Gaussian system, the particle filter is applied in the UAV positioning system. The Monte Carlo sampling method is used for the posterior distribution. In view of the particle degradation problem existing in the particle filter algorithm, the re-sampling of the particle filter method is improved. In order to verify the performance of the improved algorithm, experiments were carried out on a quadrotor UAV platform based on STM32. The results show that the improved positioning algorithm can effectively improve the positioning accuracy of the UAV, and has good practicability.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"13 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":"126716800","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}
Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00013
Dong Xianguang, Dai Yanjie, Chen Zhiru, Liu Xiao, Li Yanxi, W. Tingting, Zhengxue, Yang Jie, Xu Ziqian
It is convenient for residents, industry and commerce with the extension of smart meters and the popularization rate of smart meter has reached 100%. However, it exposes many problems of smart meter in field application, such as display fault, communication failure, error out of tolerance, abnormal measurement data, clock abnormal. This paper just analyzes the problem of abnormal measurement data, the result shows that the reasons of the problem contain battery undervoltage, component failure and power failure, they cause the problem of abnormal measurement together. To avoid this problem in the future, it needs higher requirements of the hardware and software reliability, and the replaceable battery is necessary for smart meter.
{"title":"Analysis of Abnormal Measurement of Smart Meter","authors":"Dong Xianguang, Dai Yanjie, Chen Zhiru, Liu Xiao, Li Yanxi, W. Tingting, Zhengxue, Yang Jie, Xu Ziqian","doi":"10.1109/CISCE50729.2020.00013","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00013","url":null,"abstract":"It is convenient for residents, industry and commerce with the extension of smart meters and the popularization rate of smart meter has reached 100%. However, it exposes many problems of smart meter in field application, such as display fault, communication failure, error out of tolerance, abnormal measurement data, clock abnormal. This paper just analyzes the problem of abnormal measurement data, the result shows that the reasons of the problem contain battery undervoltage, component failure and power failure, they cause the problem of abnormal measurement together. To avoid this problem in the future, it needs higher requirements of the hardware and software reliability, and the replaceable battery is necessary for smart meter.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"263 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":"116037656","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}
Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00095
Fushan Li, Lan Luo
The rapid development of deep neural networks makes unmanned supermarket solutions based on computer vision possible. However, the computational complexity of convolutional neural networks is much higher than traditional algorithms, and the limitations of limited resources on embedded devices cannot meet real-time requirements. This article proposes an intelligent commodity settlement system based on embedded devices and deep learning. It uses CenterNet network and heterogeneous convolution filters to fuse. The initial layer convolution kernel is designed as a heterogeneous kernel to solve the detection of large differences in commodity scales. Experimental results show that the improved network structure has an average detection accuracy improvement of 3.2% compared to the original network structure, and the IoU index is increased by 3.1%, which can meet the real-time commodity recognition requirements of embedded devices.
{"title":"Intelligent Commodity Settlement System based on Embedded Equipment and Convolutional Neural Network","authors":"Fushan Li, Lan Luo","doi":"10.1109/CISCE50729.2020.00095","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00095","url":null,"abstract":"The rapid development of deep neural networks makes unmanned supermarket solutions based on computer vision possible. However, the computational complexity of convolutional neural networks is much higher than traditional algorithms, and the limitations of limited resources on embedded devices cannot meet real-time requirements. This article proposes an intelligent commodity settlement system based on embedded devices and deep learning. It uses CenterNet network and heterogeneous convolution filters to fuse. The initial layer convolution kernel is designed as a heterogeneous kernel to solve the detection of large differences in commodity scales. Experimental results show that the improved network structure has an average detection accuracy improvement of 3.2% compared to the original network structure, and the IoU index is increased by 3.1%, which can meet the real-time commodity recognition requirements of embedded devices.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"14 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":"131569671","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}
Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00077
Yongli Wang, Shuquan Li, Daomin Qu, Shaokun Jia, Xi Gan, Yuze Ma, Yaling Sun
In recent years, the frequent natural disasters worldwide and their effects have attracted great attention of the international community. In this context, the traditional reliability research is not enough to support the safe operation of the power grid, and the concept of toughness emerges as the times require. In this paper, the dynamic power flow model of natural gas network is adopted, and the coupling relationship between distribution network reconfiguration in physical layer and information layer is considered. Based on this, Q learning algorithm is introduced to solve the complex problem. The simulation results show that the Q learning algorithm can achieve better convergence while solving the problem. The improved initialization method and the adopted confidence interval upper bound algorithm can significantly improve the computational efficiency and make the results converge to a better solution. Compared with the conventional mixed integer linear programming model, Q learning algorithm has better optimization results.
{"title":"An Integrated Energy System Optimization Method Considering Q Learning Algorithm","authors":"Yongli Wang, Shuquan Li, Daomin Qu, Shaokun Jia, Xi Gan, Yuze Ma, Yaling Sun","doi":"10.1109/CISCE50729.2020.00077","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00077","url":null,"abstract":"In recent years, the frequent natural disasters worldwide and their effects have attracted great attention of the international community. In this context, the traditional reliability research is not enough to support the safe operation of the power grid, and the concept of toughness emerges as the times require. In this paper, the dynamic power flow model of natural gas network is adopted, and the coupling relationship between distribution network reconfiguration in physical layer and information layer is considered. Based on this, Q learning algorithm is introduced to solve the complex problem. The simulation results show that the Q learning algorithm can achieve better convergence while solving the problem. The improved initialization method and the adopted confidence interval upper bound algorithm can significantly improve the computational efficiency and make the results converge to a better solution. Compared with the conventional mixed integer linear programming model, Q learning algorithm has better optimization results.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"17 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":"134094089","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}
Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00055
Zhonghe Han, Zequn Zhang
The automatic dialogue system is an intelligent system built by combining various artificial intelligence technologies. In recent years, with the introduction of multi-turn dialogue generation systems, semantic relevance and topic consistency between different dialogue turns have become important evaluation criteria for the success of the model. However, these problems have not been resolved and still face many challenges. In this paper, we propose a sequence to sequence (seq2seq) model based on multi-encoder structure and theme-oriented decoder, and these innovations enable the proposed model to obtain semantic correlation between different turns of conversation and maintain the consistency of topics. Meanwhile, aiming at the disadvantages of the basic seq2seq model, BiLSTM cells, attention mechanism and beam search algorithm are adopted to solve the problem of long-distance dependence and obtain richer semantic information. Experiments show that the proposed model can generate coherent, appropriate and diverse replies on multi-turn dialogue datasets.
{"title":"Multi-turn Dialogue System Based on Improved Seq2Seq Model","authors":"Zhonghe Han, Zequn Zhang","doi":"10.1109/CISCE50729.2020.00055","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00055","url":null,"abstract":"The automatic dialogue system is an intelligent system built by combining various artificial intelligence technologies. In recent years, with the introduction of multi-turn dialogue generation systems, semantic relevance and topic consistency between different dialogue turns have become important evaluation criteria for the success of the model. However, these problems have not been resolved and still face many challenges. In this paper, we propose a sequence to sequence (seq2seq) model based on multi-encoder structure and theme-oriented decoder, and these innovations enable the proposed model to obtain semantic correlation between different turns of conversation and maintain the consistency of topics. Meanwhile, aiming at the disadvantages of the basic seq2seq model, BiLSTM cells, attention mechanism and beam search algorithm are adopted to solve the problem of long-distance dependence and obtain richer semantic information. Experiments show that the proposed model can generate coherent, appropriate and diverse replies on multi-turn dialogue datasets.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","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":"131439887","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}
Pub Date : 2020-07-01DOI: 10.1109/CISCE50729.2020.00030
Kuan Zhou, Ling Deng, Jun Zhang
In recent years, the field of communication technology has developed vigorously, the requirements for signal transmission quality have also gradually increased, covering a wide range, and high-quality transmission signals can better meet people’s daily lives and applications. Aiming at the problem that communication transmission is limited by distance in real life, weakening the quality of transmission signals, the repeater is implemented in the GNU Radio programming environment using a general software radio platform, at the same time, the relevant parameters of the repeater can be dynamically configured, the repeater signal can be observed in real time, which has high scalability. The actual test results show that the designed repeater realizes the forwarding of voice signals, increases the distance range of signal transmission of handheld stations, and improves the stability of data transmission, the repeater has certain application prospects in voice data communication, and provides a new idea for the design of the repeater.
{"title":"Research on Repeater Technology Based on Software Defined Radio","authors":"Kuan Zhou, Ling Deng, Jun Zhang","doi":"10.1109/CISCE50729.2020.00030","DOIUrl":"https://doi.org/10.1109/CISCE50729.2020.00030","url":null,"abstract":"In recent years, the field of communication technology has developed vigorously, the requirements for signal transmission quality have also gradually increased, covering a wide range, and high-quality transmission signals can better meet people’s daily lives and applications. Aiming at the problem that communication transmission is limited by distance in real life, weakening the quality of transmission signals, the repeater is implemented in the GNU Radio programming environment using a general software radio platform, at the same time, the relevant parameters of the repeater can be dynamically configured, the repeater signal can be observed in real time, which has high scalability. The actual test results show that the designed repeater realizes the forwarding of voice signals, increases the distance range of signal transmission of handheld stations, and improves the stability of data transmission, the repeater has certain application prospects in voice data communication, and provides a new idea for the design of the repeater.","PeriodicalId":101777,"journal":{"name":"2020 International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"93 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":"124618281","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}
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