In recent years, with the increasing number of Internet users and mobile phone users in China, various social contradictions have been discussed locally from the real world to the global discussion of the virtual world. In order to distinguish new media events in time and accurately, based on the analysis of common clustering algorithms, a hybrid K-means genetic algorithm suitable for clustering new media events is proposed by combining genetic algorithm with K-means algorithm. The algorithm uses the optimal preservation strategy, single-point crossover and single-point mutation to ensure the convergence of the hybrid K-means genetic algorithm to a greater extent. Multi-round merging based on dynamic weights is adopted to make segmentation results suitable for retrieval requirements, and the retrieval method of feature integration is improved. On the basis of the initial weights, the weight knowledge base can be stabilized through a certain number of user feedback training processes. Finally, according to the weights in the knowledge base, different features are integrated for retrieval. Experimental results show that the algorithm is effective.
{"title":"Research on Early Warning System of New Media Events Based on Model Segmentation and Feature Integration","authors":"Li Wen","doi":"10.1145/3510858.3511363","DOIUrl":"https://doi.org/10.1145/3510858.3511363","url":null,"abstract":"In recent years, with the increasing number of Internet users and mobile phone users in China, various social contradictions have been discussed locally from the real world to the global discussion of the virtual world. In order to distinguish new media events in time and accurately, based on the analysis of common clustering algorithms, a hybrid K-means genetic algorithm suitable for clustering new media events is proposed by combining genetic algorithm with K-means algorithm. The algorithm uses the optimal preservation strategy, single-point crossover and single-point mutation to ensure the convergence of the hybrid K-means genetic algorithm to a greater extent. Multi-round merging based on dynamic weights is adopted to make segmentation results suitable for retrieval requirements, and the retrieval method of feature integration is improved. On the basis of the initial weights, the weight knowledge base can be stabilized through a certain number of user feedback training processes. Finally, according to the weights in the knowledge base, different features are integrated for retrieval. Experimental results show that the algorithm is effective.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"72 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78671027","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}
Artificial intelligence is the study of the science of using computers to simulate certain human thought processes and intelligent behaviours, providing solutions for many domestic and international garbage classification applications. Based on artificial intelligence technology and software development technology, this paper analyses the garbage classification process, studies key garbage classification technologies and designs a system development framework. In particular, the garbage classification process follows the process of machine vision, item recognition and check classification. Key technologies for garbage classification include visual identity, convolutional neural network algorithm and Naive Bayes algorithm. The system development framework is a four-tier structure consisting of Struts2, Spring and Hibernate. The research results in this paper address key technical issues in the development of garbage classification systems, which can be selectively applied in the actual development process to improve the adaptability of the system.
{"title":"Design of Garbage Classification System Based on Artificial Intelligence Technology","authors":"He Bai","doi":"10.1145/3510858.3510920","DOIUrl":"https://doi.org/10.1145/3510858.3510920","url":null,"abstract":"Artificial intelligence is the study of the science of using computers to simulate certain human thought processes and intelligent behaviours, providing solutions for many domestic and international garbage classification applications. Based on artificial intelligence technology and software development technology, this paper analyses the garbage classification process, studies key garbage classification technologies and designs a system development framework. In particular, the garbage classification process follows the process of machine vision, item recognition and check classification. Key technologies for garbage classification include visual identity, convolutional neural network algorithm and Naive Bayes algorithm. The system development framework is a four-tier structure consisting of Struts2, Spring and Hibernate. The research results in this paper address key technical issues in the development of garbage classification systems, which can be selectively applied in the actual development process to improve the adaptability of the system.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82799393","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}
Due to its powerful data processing capabilities and data mining capabilities, machine learning has been widely used in various fields of research and has achieved breakthroughs. The use of machine learning methods to study sports injuries has great potential. BP neural network technology is one of the important contents of machine learning. Based on the basic model of neural network, this paper designs the training process of BP neural network and builds the sports injury prediction model based on neural network technology, including the input and output of neural network, and the layer selection and parameter selection, and strive to get the best training results through the least number of iterations. The research results are used to adjust the training intensity, strengthen the athlete's self-protection awareness, rationally plan training methods, avoid sports injury, and ensure the effective development of sports training.
{"title":"Research on Sports Injury Information Prediction Model Based on Neural Network Technology","authors":"Chunfeng Mao","doi":"10.1145/3510858.3510998","DOIUrl":"https://doi.org/10.1145/3510858.3510998","url":null,"abstract":"Due to its powerful data processing capabilities and data mining capabilities, machine learning has been widely used in various fields of research and has achieved breakthroughs. The use of machine learning methods to study sports injuries has great potential. BP neural network technology is one of the important contents of machine learning. Based on the basic model of neural network, this paper designs the training process of BP neural network and builds the sports injury prediction model based on neural network technology, including the input and output of neural network, and the layer selection and parameter selection, and strive to get the best training results through the least number of iterations. The research results are used to adjust the training intensity, strengthen the athlete's self-protection awareness, rationally plan training methods, avoid sports injury, and ensure the effective development of sports training.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90787280","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}
Flash is an animation technology combining control flow and graphic vector technology. This technology can organically and flexibly integrate audio, interactive actions, vector graphics, bitmaps, and animations. Multimedia in the form of Flash can produce strong animations with beautiful images. Flash animation has a series of characteristics such as good interactive performance, high transmission rate, simple and rich, streaming media playback, and low-cost production and so on. Because of these characteristics, web users love Flash very much. At present, there are a lot of resources on the Internet in the form of Flash. With the advent of the era of embedded applications, people’s daily lives are becoming more and more closely related to embedded systems, and the demand for multimedia applications in embedded systems is also getting stronger. In recent years, the embedded hardware has developed at a high speed, and the storage capacity and calculation speed of embedded systems have been continuously improved. It has become possible to develop vector graphics technology on embedded devices. After mobile portable devices and embedded platforms have network communication functions, people’s use of these devices has become increasingly normal, which makes the application of Flash technology on embedded platforms have great development prospects. The purpose of this article is to study the application of Flash playback technology in the WinCE environment. Based on the WinCE environment, an MFC dialog box is designed. ActiveX controls are inserted into the dialog box to implement a Flash playback area. The MFC dialog box is implemented on the WinCE simulator. Play Flash files in the specified area.
{"title":"Exploration on Flash Play Technology Based on Embedded WinCE Platform","authors":"Ying Deng, Yuanhui Yu","doi":"10.1145/3510858.3510958","DOIUrl":"https://doi.org/10.1145/3510858.3510958","url":null,"abstract":"Flash is an animation technology combining control flow and graphic vector technology. This technology can organically and flexibly integrate audio, interactive actions, vector graphics, bitmaps, and animations. Multimedia in the form of Flash can produce strong animations with beautiful images. Flash animation has a series of characteristics such as good interactive performance, high transmission rate, simple and rich, streaming media playback, and low-cost production and so on. Because of these characteristics, web users love Flash very much. At present, there are a lot of resources on the Internet in the form of Flash. With the advent of the era of embedded applications, people’s daily lives are becoming more and more closely related to embedded systems, and the demand for multimedia applications in embedded systems is also getting stronger. In recent years, the embedded hardware has developed at a high speed, and the storage capacity and calculation speed of embedded systems have been continuously improved. It has become possible to develop vector graphics technology on embedded devices. After mobile portable devices and embedded platforms have network communication functions, people’s use of these devices has become increasingly normal, which makes the application of Flash technology on embedded platforms have great development prospects. The purpose of this article is to study the application of Flash playback technology in the WinCE environment. Based on the WinCE environment, an MFC dialog box is designed. ActiveX controls are inserted into the dialog box to implement a Flash playback area. The MFC dialog box is implemented on the WinCE simulator. Play Flash files in the specified area.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86299919","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}
How to use big data technology to effectively excavate and identify data information contained in user behaviors and further innovate services has become a development trend of the Internet big data. With the further increase of the amount of data, the configuration parameters involved further increase, and the optimization of configuration parameters has become the main bottleneck limiting the performance of MapReduce. Hadoop configuration involves many parameters, which have a great impact on the running jobs. These parameters just determine the overall performance of the cluster. This paper uses Hadoop technology to the Internet big data combining the optimization model. The construction process of Hadoop cluster environment is described in detail. Hadoop is applied to a file publishing system. For files of different orders of magnitude, the time-consuming operation of file upload is compared when the number of clusters is different. The experimental results show that the larger the amount of data and the number of cluster nodes, the stronger the ability of Hadoop cluster to process data. The results prove that this method effectively can solve the problems of the complex information of big data and improve the service efficiency for big data processing.
{"title":"Application Analysis of Hadoop in Big Data Processing","authors":"Zhi Zheng","doi":"10.1145/3510858.3510975","DOIUrl":"https://doi.org/10.1145/3510858.3510975","url":null,"abstract":"How to use big data technology to effectively excavate and identify data information contained in user behaviors and further innovate services has become a development trend of the Internet big data. With the further increase of the amount of data, the configuration parameters involved further increase, and the optimization of configuration parameters has become the main bottleneck limiting the performance of MapReduce. Hadoop configuration involves many parameters, which have a great impact on the running jobs. These parameters just determine the overall performance of the cluster. This paper uses Hadoop technology to the Internet big data combining the optimization model. The construction process of Hadoop cluster environment is described in detail. Hadoop is applied to a file publishing system. For files of different orders of magnitude, the time-consuming operation of file upload is compared when the number of clusters is different. The experimental results show that the larger the amount of data and the number of cluster nodes, the stronger the ability of Hadoop cluster to process data. The results prove that this method effectively can solve the problems of the complex information of big data and improve the service efficiency for big data processing.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87505115","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}
Face recognition technology has its unique convenience and versatility in information security. This technology is also the product of social development. A face recognition access control system based on mathematical morphology was proposed. By pre-processing the original image, the binary image is obtained. Then the mathematical morphology of the image is used to integrate it into a face image that can locate the face. Finally, the face location is realized by extracting the eyes. Through the research, it can be found that it was convenient to realize and could be applied to the actual scene, which provided a feasible scheme for the access control system and a research basis for deep face recognition.
{"title":"Design of access control system using face recognition based on mathematical morphology","authors":"Xiaoqian Huang, Chao Chen, Chun Pan, Hui Liu","doi":"10.1145/3510858.3511009","DOIUrl":"https://doi.org/10.1145/3510858.3511009","url":null,"abstract":"Face recognition technology has its unique convenience and versatility in information security. This technology is also the product of social development. A face recognition access control system based on mathematical morphology was proposed. By pre-processing the original image, the binary image is obtained. Then the mathematical morphology of the image is used to integrate it into a face image that can locate the face. Finally, the face location is realized by extracting the eyes. Through the research, it can be found that it was convenient to realize and could be applied to the actual scene, which provided a feasible scheme for the access control system and a research basis for deep face recognition.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88337388","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}
The valuable information in the company's financial data is very important to evaluate the business situation of enterprises. Based on the five factors of cash flow, growth ability, operation ability, solvency and profitability, this paper determines the financial operation status of 27 enterprises, and proposes to use particle swarm optimization random forest algorithm to complete the classification and prediction of enterprise financial operation status. At the same time, the performance evaluation indexes of recall, accuracy, precision and F1 score algorithm are determined. Compared with other classification prediction methods. The accuracy, F1 value, precision, recall and AUC of PSO-RF algorithm are the best, which are 99.36%, 99.36%, 99.35%, 99.32% and 98.98% respectively. This study will help to realize the classification and prediction of enterprise financial operation.
{"title":"Enterprise Financial Management based on Random Forest Algorithm","authors":"Yunping Cao","doi":"10.1145/3510858.3510923","DOIUrl":"https://doi.org/10.1145/3510858.3510923","url":null,"abstract":"The valuable information in the company's financial data is very important to evaluate the business situation of enterprises. Based on the five factors of cash flow, growth ability, operation ability, solvency and profitability, this paper determines the financial operation status of 27 enterprises, and proposes to use particle swarm optimization random forest algorithm to complete the classification and prediction of enterprise financial operation status. At the same time, the performance evaluation indexes of recall, accuracy, precision and F1 score algorithm are determined. Compared with other classification prediction methods. The accuracy, F1 value, precision, recall and AUC of PSO-RF algorithm are the best, which are 99.36%, 99.36%, 99.35%, 99.32% and 98.98% respectively. This study will help to realize the classification and prediction of enterprise financial operation.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77172818","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}
With the rapid increase of domestic airport scale, passenger throughput and the change of international situation, the types and quantity of airport security inspection equipment have increased greatly, and centralized management will greatly improve its management efficiency. However, there are no related products or systems in China at present. This paper studies a distributed remote management system of airport security inspection equipment based on machine vision. The hardware system of acquisition terminal is designed and implemented, and the sensor network of security inspection equipment of single terminal building based on ZigBee technology is established. In this paper, aiming at machine vision and image processing technology, through effective image processing and pattern recognition methods, such as geometric transformation, filtering and denoising, threshold processing, etc., the image is converted into machine-readable form, and then the software program is used to process, analyze and read to obtain the corresponding information, so as to realize card and card reading. The embedded Web Server function is adopted to publish the monitoring platform to the work local area network, which realizes the remote monitoring of security inspection equipment by users in the local area network.
{"title":"Research and Design of Remote Management of Distributed Airport Security Inspection Equipment Based on Machine Vision","authors":"Ying Chen, Ruiqing Shi","doi":"10.1145/3510858.3511411","DOIUrl":"https://doi.org/10.1145/3510858.3511411","url":null,"abstract":"With the rapid increase of domestic airport scale, passenger throughput and the change of international situation, the types and quantity of airport security inspection equipment have increased greatly, and centralized management will greatly improve its management efficiency. However, there are no related products or systems in China at present. This paper studies a distributed remote management system of airport security inspection equipment based on machine vision. The hardware system of acquisition terminal is designed and implemented, and the sensor network of security inspection equipment of single terminal building based on ZigBee technology is established. In this paper, aiming at machine vision and image processing technology, through effective image processing and pattern recognition methods, such as geometric transformation, filtering and denoising, threshold processing, etc., the image is converted into machine-readable form, and then the software program is used to process, analyze and read to obtain the corresponding information, so as to realize card and card reading. The embedded Web Server function is adopted to publish the monitoring platform to the work local area network, which realizes the remote monitoring of security inspection equipment by users in the local area network.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"56 4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77551824","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}
Yuanke Zhou, Fan Yang, Xiao-Hu Shi, Yunyun Zhang, Shengyan Wang
Rural power grid is an important part of power grid construction. With the development of economic construction, users have higher and higher requirements for power supply reliability and power quality. In this paper, a q-type cluster analysis method based on entropy weight method and cluster analysis is proposed based on the statistical collation and analysis of sample data in a certain region of a province. Cluster analysis the villages belonging to each rural power grid in the province, find out the difference in the growth of power supply population and electricity sales among different villages. Finally, the villages in a certain region of a province are divided into three corresponding classification results: "growth type", "mature type" and "decline type", a more perfect model of site classification is established. It is of great significance for the government to set up investment strategy according to local conditions and promote the development of rural power grid.
{"title":"On Rural Power Grid Classification Method Based on Entropy Weight Method and Cluster Analysis","authors":"Yuanke Zhou, Fan Yang, Xiao-Hu Shi, Yunyun Zhang, Shengyan Wang","doi":"10.1145/3510858.3510941","DOIUrl":"https://doi.org/10.1145/3510858.3510941","url":null,"abstract":"Rural power grid is an important part of power grid construction. With the development of economic construction, users have higher and higher requirements for power supply reliability and power quality. In this paper, a q-type cluster analysis method based on entropy weight method and cluster analysis is proposed based on the statistical collation and analysis of sample data in a certain region of a province. Cluster analysis the villages belonging to each rural power grid in the province, find out the difference in the growth of power supply population and electricity sales among different villages. Finally, the villages in a certain region of a province are divided into three corresponding classification results: \"growth type\", \"mature type\" and \"decline type\", a more perfect model of site classification is established. It is of great significance for the government to set up investment strategy according to local conditions and promote the development of rural power grid.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"17 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91442002","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}
The development of computer technology promotes the widespread application of artificial intelligence. It has huge advantages in information processing. As big data and cloud computing take root in the hearts of the people, enterprises have put forward higher requirements for financial management models, and there are more and more technical requirements for the automated processing of financial information. Therefore, this article aims to design an automated information processing system by studying the characteristics of artificial intelligence technology and financial information, so as to facilitate the automatic financial analysis and bring efficiency to the enterprise. This article mainly applied analysis method, comparison method and experiment method to design, analyze and test the automated financial information processing system under artificial intelligence, and obtained relevant data. The experimental results show that the accuracy of the system designed in this paper is above 96%, which is in line with the financial needs of the enterprise.
{"title":"Design of Automated Financial Information Processing System under the Background of Artificial Intelligence","authors":"Songgui Zhu","doi":"10.1145/3510858.3510943","DOIUrl":"https://doi.org/10.1145/3510858.3510943","url":null,"abstract":"The development of computer technology promotes the widespread application of artificial intelligence. It has huge advantages in information processing. As big data and cloud computing take root in the hearts of the people, enterprises have put forward higher requirements for financial management models, and there are more and more technical requirements for the automated processing of financial information. Therefore, this article aims to design an automated information processing system by studying the characteristics of artificial intelligence technology and financial information, so as to facilitate the automatic financial analysis and bring efficiency to the enterprise. This article mainly applied analysis method, comparison method and experiment method to design, analyze and test the automated financial information processing system under artificial intelligence, and obtained relevant data. The experimental results show that the accuracy of the system designed in this paper is above 96%, which is in line with the financial needs of the enterprise.","PeriodicalId":6757,"journal":{"name":"2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT)","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87285944","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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