Aiming at the electromagnetic vibration and noise problem of power transformer body, the finite element analysis software ANSYS is used to establish the multi-field coupling calculation model including the electromagnetic field-structure field-sound field in power transformer, and the electromagnetic vibration and noise of power transformer body is numerically calculated and analyzed. Firstly, the magnetostrictive force of the core and the electromagnetic force of the winding are obtained through the electromagnetic field calculation. Then, it is applied to the structural field calculation model as an excitation to obtain the vibration displacement of the transformer body. Finally, the structure field calculation results are imported into the sound field calculation model, and the sound field distribution in the outer space of the transformer and the sound pressure value at the test point are obtained. By comparing with the test results, the effectiveness and accuracy of the method are proved. At the same time, the specific measures to reduce the vibration and noise of the transformer are given, which is of great significance to solve the vibration and noise problem of the transformer.
{"title":"Numerical Calculation of the Electromagnetic Vibration and Noise in Power Transformer Based on the Multi-Field Coupling Method","authors":"F. Han, Huan Wang, Xiuping Wang, Yongteng Jing","doi":"10.1145/3558819.3565083","DOIUrl":"https://doi.org/10.1145/3558819.3565083","url":null,"abstract":"Aiming at the electromagnetic vibration and noise problem of power transformer body, the finite element analysis software ANSYS is used to establish the multi-field coupling calculation model including the electromagnetic field-structure field-sound field in power transformer, and the electromagnetic vibration and noise of power transformer body is numerically calculated and analyzed. Firstly, the magnetostrictive force of the core and the electromagnetic force of the winding are obtained through the electromagnetic field calculation. Then, it is applied to the structural field calculation model as an excitation to obtain the vibration displacement of the transformer body. Finally, the structure field calculation results are imported into the sound field calculation model, and the sound field distribution in the outer space of the transformer and the sound pressure value at the test point are obtained. By comparing with the test results, the effectiveness and accuracy of the method are proved. At the same time, the specific measures to reduce the vibration and noise of the transformer are given, which is of great significance to solve the vibration and noise problem of the transformer.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129081266","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 continuous development of informatization, the network information center bears more and more heavy tasks, the maintenance pressure is increasing, for the management of a variety of hardware equipment and information system performance monitoring requirements are urgent. Zabbix as a distributed monitoring, control and management system, based on the mature distributed architecture design and development on market, can be all sorts the open source visual components, implementation of various monitoring data graphical display of mobile phones, state of early waring and analysis of the maintenance staff to have good support.
{"title":"The Application Research of Zabbix in Intelligent Network Information Center","authors":"Lisen Yue, Yongbin Bai, Haibo Liu, Z. Chen","doi":"10.1145/3558819.3565202","DOIUrl":"https://doi.org/10.1145/3558819.3565202","url":null,"abstract":"With the continuous development of informatization, the network information center bears more and more heavy tasks, the maintenance pressure is increasing, for the management of a variety of hardware equipment and information system performance monitoring requirements are urgent. Zabbix as a distributed monitoring, control and management system, based on the mature distributed architecture design and development on market, can be all sorts the open source visual components, implementation of various monitoring data graphical display of mobile phones, state of early waring and analysis of the maintenance staff to have good support.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128571348","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}
Synthetic Aperture Radar (SAR) is a microwave remote sensing imaging radar that reduces interference from imaging constraints such as climate. It has all-weather, all-weather imaging characteristics, and can obtain rich information representing the physical properties of real objects on the surface. Widely used in the field of modern economic development. With the rapid development of modern urbanization, the types and numbers of supporting roads and bridges are constantly increasing, and they are constantly developing and changing every year. Therefore, it is very important to detect highway bridges with high-resolution SAR images that can cover a large area. Development is of great significance and has broad prospects for development. In this paper, the detection of roads and bridges in single-polarization high-resolution SAR images and the connection of global road networks are studied. The scattering characteristics of urban roads, bridges and nearby objects under the condition of single polarization SAR imaging are analyzed, and the effects of different environments and materials on the results of the target appearing on the image are studied. According to the inherent properties of the road and bridge targets and the imaging features in the SAR image, the multi-angle feature extraction of the target to be detected is further carried out, which lays the foundation for the subsequent road and bridge detection.
{"title":"Research on road and bridge detection method in high resolution SAR image based on multi-feature fusion","authors":"J. Liu","doi":"10.1145/3558819.3565168","DOIUrl":"https://doi.org/10.1145/3558819.3565168","url":null,"abstract":"Synthetic Aperture Radar (SAR) is a microwave remote sensing imaging radar that reduces interference from imaging constraints such as climate. It has all-weather, all-weather imaging characteristics, and can obtain rich information representing the physical properties of real objects on the surface. Widely used in the field of modern economic development. With the rapid development of modern urbanization, the types and numbers of supporting roads and bridges are constantly increasing, and they are constantly developing and changing every year. Therefore, it is very important to detect highway bridges with high-resolution SAR images that can cover a large area. Development is of great significance and has broad prospects for development. In this paper, the detection of roads and bridges in single-polarization high-resolution SAR images and the connection of global road networks are studied. The scattering characteristics of urban roads, bridges and nearby objects under the condition of single polarization SAR imaging are analyzed, and the effects of different environments and materials on the results of the target appearing on the image are studied. According to the inherent properties of the road and bridge targets and the imaging features in the SAR image, the multi-angle feature extraction of the target to be detected is further carried out, which lays the foundation for the subsequent road and bridge detection.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128576598","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}
Haze affects the urban landscape, increases the cost of cleaning the city, and directly or indirectly causes respiratory diseases and affects the physical and mental health of citizens. In addition, the complex causes of haze, the difficulty of tracing the source leads to the current "wide net" type of treatment measures have limited effect, haze tracing work there are technical bottlenecks, poorly targeted treatment programs. Some economic and technological backwardness but also more serious pollution of the township, and even the use of "shock therapy" to manage the haze, although effective, but often cause economic decline. In this regard, the article proposes an accurate traceability method for haze, which achieves accurate traceability of haze through highly reductive haze collection, multi-angle morphological analysis and haze source database, and in addition applies remote sensing technology to obtain the real particle size parameters and temporal-spatial distribution of haze by inversion of AOD-PM2.5 mathematical model to check the obtained results from a macroscopic perspective, which ensures more The accuracy of the data is ensured. The results show that the pollution sources of typical haze in Xi'an are, in order of contribution, industrial coal combustion (35.1%), automobile exhaust (26.0%), industrial smelting (13.7%), soil sand (11.5%), and mineral extraction (1.9%). Among them, industrial coal combustion, automobile exhaust, and industrial smelting are the main sources of typical haze, with a combined contribution of more than 60%. To summarize the experience gained during the study, pollution prevention and control recommendations for industrial coal combustion, automobile exhaust and industrial smelting are proposed.
{"title":"A method and application of precise haze traceability based on image recognition","authors":"Zeyu Zhou, Jinhao Chen, Hao Jiang","doi":"10.1145/3558819.3565129","DOIUrl":"https://doi.org/10.1145/3558819.3565129","url":null,"abstract":"Haze affects the urban landscape, increases the cost of cleaning the city, and directly or indirectly causes respiratory diseases and affects the physical and mental health of citizens. In addition, the complex causes of haze, the difficulty of tracing the source leads to the current \"wide net\" type of treatment measures have limited effect, haze tracing work there are technical bottlenecks, poorly targeted treatment programs. Some economic and technological backwardness but also more serious pollution of the township, and even the use of \"shock therapy\" to manage the haze, although effective, but often cause economic decline. In this regard, the article proposes an accurate traceability method for haze, which achieves accurate traceability of haze through highly reductive haze collection, multi-angle morphological analysis and haze source database, and in addition applies remote sensing technology to obtain the real particle size parameters and temporal-spatial distribution of haze by inversion of AOD-PM2.5 mathematical model to check the obtained results from a macroscopic perspective, which ensures more The accuracy of the data is ensured. The results show that the pollution sources of typical haze in Xi'an are, in order of contribution, industrial coal combustion (35.1%), automobile exhaust (26.0%), industrial smelting (13.7%), soil sand (11.5%), and mineral extraction (1.9%). Among them, industrial coal combustion, automobile exhaust, and industrial smelting are the main sources of typical haze, with a combined contribution of more than 60%. To summarize the experience gained during the study, pollution prevention and control recommendations for industrial coal combustion, automobile exhaust and industrial smelting are proposed.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129389264","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}
Track and field short span is the basis of many competitive sports and is a typical periodic movement. The high-speed swing ability of athlete's limbs is an important special ability. This study explores the quantitative detection method of mechanical sensors for short-span athletes' swing training, and establishes the relationship between the specific ability and mechanical parameters of the training process. The system realizes quantitative evaluation of athletic ability and real-time feedback of training effect. We initially created a "signal-feedback" approach to assisted training.
{"title":"Research on Auxiliary Training System of Computer Virtual Reality Technology in Track and Field Sprint Hurdles","authors":"Ye He","doi":"10.1145/3558819.3565097","DOIUrl":"https://doi.org/10.1145/3558819.3565097","url":null,"abstract":"Track and field short span is the basis of many competitive sports and is a typical periodic movement. The high-speed swing ability of athlete's limbs is an important special ability. This study explores the quantitative detection method of mechanical sensors for short-span athletes' swing training, and establishes the relationship between the specific ability and mechanical parameters of the training process. The system realizes quantitative evaluation of athletic ability and real-time feedback of training effect. We initially created a \"signal-feedback\" approach to assisted training.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116881031","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 efforts of Terence Tao, David Donoho and many other scientists, using the prior knowledge of signal sparsity to obtain and reconstruct compressible signals has brought new vitality to information acquisition technology. The main advantage of compressive sensing technology over traditional Nyquist sampling law is that it can recover the original signal from fewer measurements. Naturally, compressive sensing technology can be innovatively used in a wide range of fields with its own advantages, such as space exploration, which is concerned in this paper: the measurement environment is more stringent, the original signal to noise ratio is lower, and the self-weight of detection equipment is more demanding. This paper will focus on the theory of compressive sensing, and discuss its application conditions and limitations. Finally, based on the theory, its application in multi-star imaging is discussed.
{"title":"Application of Compressive Sensing Technology and Image Processing in Space Exploration","authors":"Jiaming Jin","doi":"10.1145/3558819.3565086","DOIUrl":"https://doi.org/10.1145/3558819.3565086","url":null,"abstract":"With the efforts of Terence Tao, David Donoho and many other scientists, using the prior knowledge of signal sparsity to obtain and reconstruct compressible signals has brought new vitality to information acquisition technology. The main advantage of compressive sensing technology over traditional Nyquist sampling law is that it can recover the original signal from fewer measurements. Naturally, compressive sensing technology can be innovatively used in a wide range of fields with its own advantages, such as space exploration, which is concerned in this paper: the measurement environment is more stringent, the original signal to noise ratio is lower, and the self-weight of detection equipment is more demanding. This paper will focus on the theory of compressive sensing, and discuss its application conditions and limitations. Finally, based on the theory, its application in multi-star imaging is discussed.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114301067","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 differential protection method applied to high voltage transmission network introduces fault location of intelligent distribution network, and the improved differential current method can realize fast and accurate location of intelligent distribution network. Aiming at the disadvantage that traditional feeder automation is not suitable for intelligent distribution network, an intelligent feeder automation model for intelligent distribution network based on multi-agent is constructed. An improved differential current method based on multi-agent is proposed for feeder fault location. This method can realize intelligent feeder automation and high precision and high speed fault location. The system network loss and node minimum voltage after fault recovery using Agent algorithm are the same as those of genetic algorithm, but the fault recovery time is obviously shortened. Agent can quickly operate the corresponding switch equipment remotely, and restore the load power supply in non-failure area, so that users can hardly feel the occurrence of power failure.
{"title":"Research on Automatic Self-healing Control of Intelligent Feeder based on Multi-Agent Algorithm","authors":"Jiangang Lu, Ruifeng Zhao, Hai-cheng Liu, Wenxin Gou, Yong Zhao, Haiyong Wu, Hua Liu","doi":"10.1145/3558819.3565469","DOIUrl":"https://doi.org/10.1145/3558819.3565469","url":null,"abstract":"The differential protection method applied to high voltage transmission network introduces fault location of intelligent distribution network, and the improved differential current method can realize fast and accurate location of intelligent distribution network. Aiming at the disadvantage that traditional feeder automation is not suitable for intelligent distribution network, an intelligent feeder automation model for intelligent distribution network based on multi-agent is constructed. An improved differential current method based on multi-agent is proposed for feeder fault location. This method can realize intelligent feeder automation and high precision and high speed fault location. The system network loss and node minimum voltage after fault recovery using Agent algorithm are the same as those of genetic algorithm, but the fault recovery time is obviously shortened. Agent can quickly operate the corresponding switch equipment remotely, and restore the load power supply in non-failure area, so that users can hardly feel the occurrence of power failure.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114211715","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}
In recent decay, the house price prediction plays important role because of it's the volatile of house price which makes significant impact on property valuation and economic growth. It characterizes are attracted the numerous researchers, businessman and people who buy or sell house towards it. The volatile of house price is occurred based on various factors like location, facility, neighborhood, etc. In this way, researchers are evaluating the factors using machine and deep learning process to analysis the information. Although, regression-based analysis has problem due to its nonlinear and linear information in neural network. Thus, we have proposed a novel Bridge Memristors Recurrent Neural Network to forecast the house price prediction in this paper. In addition, RBP algorithm is used on Bridge Memristors RNN for train the neural network in efficient manner. Besides, our proposed model carried out outstanding performance than existing models to attain the high prediction rate by analyzing the correlation coefficient.
{"title":"House Price Prediction Model Using Bridge Memristors Recurrent Neural Network","authors":"Wenzhao Shi","doi":"10.1145/3558819.3565221","DOIUrl":"https://doi.org/10.1145/3558819.3565221","url":null,"abstract":"In recent decay, the house price prediction plays important role because of it's the volatile of house price which makes significant impact on property valuation and economic growth. It characterizes are attracted the numerous researchers, businessman and people who buy or sell house towards it. The volatile of house price is occurred based on various factors like location, facility, neighborhood, etc. In this way, researchers are evaluating the factors using machine and deep learning process to analysis the information. Although, regression-based analysis has problem due to its nonlinear and linear information in neural network. Thus, we have proposed a novel Bridge Memristors Recurrent Neural Network to forecast the house price prediction in this paper. In addition, RBP algorithm is used on Bridge Memristors RNN for train the neural network in efficient manner. Besides, our proposed model carried out outstanding performance than existing models to attain the high prediction rate by analyzing the correlation coefficient.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114360864","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 usage of amplifiers worldwide, many industries are using them to process the signal. With different designs and different types of amplifiers, they contribute to those areas a lot. The same trends happen to medical areas as well. They use it to enhance the signal from their research. The advantages of operational amplifiers (op-amp) of adjustable bandwidth could positively affect the area, especially for its signal process research, involving EEG, ECG, EMG, PCG, and Aps usage. This article will focus on designs of advanced amplifiers, especially op-amp for medical equipment and mainly discuss the drawbacks and advantages that different designs could bring to the equipment. This paper will lead to three main questions: why to use an op-amp, how to design them, and the advantages and disadvantages of different kinds of designs.
{"title":"Application of Advanced Operational Amplifiers in Biomedical Signal Systems","authors":"Xin Huo, Zhihao Liu","doi":"10.1145/3558819.3565137","DOIUrl":"https://doi.org/10.1145/3558819.3565137","url":null,"abstract":"With the usage of amplifiers worldwide, many industries are using them to process the signal. With different designs and different types of amplifiers, they contribute to those areas a lot. The same trends happen to medical areas as well. They use it to enhance the signal from their research. The advantages of operational amplifiers (op-amp) of adjustable bandwidth could positively affect the area, especially for its signal process research, involving EEG, ECG, EMG, PCG, and Aps usage. This article will focus on designs of advanced amplifiers, especially op-amp for medical equipment and mainly discuss the drawbacks and advantages that different designs could bring to the equipment. This paper will lead to three main questions: why to use an op-amp, how to design them, and the advantages and disadvantages of different kinds of designs.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126850859","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 increasing demand of bank loan businesses, the probability of non-performing loans, that is, loan default, has also increased sharply. We design machine learning algorithm to solve the problem, which can reduce the loan risk and improve service efficiency, especially when we face the data unbalanced issues. Firstly, we train the random forest model with the historical bank loan data and associated data from other financial institutions. Secondly, we revised the unbalanced data classification algorithm with random forest and tuned the data feature extraction methods. Thirdly, the results show that the machine learning risk predication algorithm outperforms traditional statistical algorithms. In addition, we use random forest algorithm to identify the impact of data feature, it is possible to obtain features that have a huge impact on the definition of the results, allowing for more accurate loan risk assessment in the financial sector.
{"title":"Prediction of Credit Risk based on Logistic Regression and Random Forest technique","authors":"Xin Yang","doi":"10.1145/3558819.3565138","DOIUrl":"https://doi.org/10.1145/3558819.3565138","url":null,"abstract":"With the increasing demand of bank loan businesses, the probability of non-performing loans, that is, loan default, has also increased sharply. We design machine learning algorithm to solve the problem, which can reduce the loan risk and improve service efficiency, especially when we face the data unbalanced issues. Firstly, we train the random forest model with the historical bank loan data and associated data from other financial institutions. Secondly, we revised the unbalanced data classification algorithm with random forest and tuned the data feature extraction methods. Thirdly, the results show that the machine learning risk predication algorithm outperforms traditional statistical algorithms. In addition, we use random forest algorithm to identify the impact of data feature, it is possible to obtain features that have a huge impact on the definition of the results, allowing for more accurate loan risk assessment in the financial sector.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"252 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122719978","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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