When using the CPU chip containing the debug module, the mechanism of secure debug is required to ensure the security of the internal data in the CPU chip. But, the specification of RISC-V instruction architecture set only describes the guideline of secure debug mechanism for hardware aspect. This paper presents a software solution for the RISC-V CPU secure debug mechanism, and the configuration program on the host computer first creates the black box area configuration data and secure authentication data, then passes the data through the debug channel to the firmware on the chip, then the firmware authenticates the security data and writes the configuration data of the black box area. The solution is combined with RISC-V CPU secure debug of hardware characteristics, and provides a comprehensive implementation reference for RISC-V CPU secure debug.
{"title":"Software Solution of Secure Debug Based on RISC-V CPU","authors":"Jun Liu, Ting Chong, Liangeng Liu, Xige Zhang","doi":"10.1145/3558819.3558823","DOIUrl":"https://doi.org/10.1145/3558819.3558823","url":null,"abstract":"When using the CPU chip containing the debug module, the mechanism of secure debug is required to ensure the security of the internal data in the CPU chip. But, the specification of RISC-V instruction architecture set only describes the guideline of secure debug mechanism for hardware aspect. This paper presents a software solution for the RISC-V CPU secure debug mechanism, and the configuration program on the host computer first creates the black box area configuration data and secure authentication data, then passes the data through the debug channel to the firmware on the chip, then the firmware authenticates the security data and writes the configuration data of the black box area. The solution is combined with RISC-V CPU secure debug of hardware characteristics, and provides a comprehensive implementation reference for RISC-V CPU secure debug.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"1 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":"128887029","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}
This paper proposes an animation dance movement creation detection method based on gesture recognition based on computer big data technology. This method combines the critical point information of bones to select fusion features such as relative positions of joint human points, joint point angles, and limb length ratios. This paper classifies actions in dance scenes and automatically detects actions through residual blocks. The system realizes the creation of dance movements of animated characters in complex dance scenes. The research results show that the construction method of the animation character dance action system is reasonable. It efficiently records and saves the dance moves of animated characters.
{"title":"Research on Computer Big Data Technology in the Creation of Virtual Reality Animation Character Dance Movement System","authors":"Zexin Huang","doi":"10.1145/3558819.3565099","DOIUrl":"https://doi.org/10.1145/3558819.3565099","url":null,"abstract":"This paper proposes an animation dance movement creation detection method based on gesture recognition based on computer big data technology. This method combines the critical point information of bones to select fusion features such as relative positions of joint human points, joint point angles, and limb length ratios. This paper classifies actions in dance scenes and automatically detects actions through residual blocks. The system realizes the creation of dance movements of animated characters in complex dance scenes. The research results show that the construction method of the animation character dance action system is reasonable. It efficiently records and saves the dance moves of animated characters.","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":"129589087","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}
Hand interaction is an important research content in computer image processing at present. In sign language recognition, social interaction, virtual reality and augmented reality, the hand is the main input device for human interaction.Aiming at the problem of low recognition rate of hand keypoint in video, this paper proposes a deep convolutional neural network to recognize hand keypoint in video. The neural network is divided into two parts, the first part is image super-resolution, the purpose is to improve the resolution of each frame in the video, so that the image of each frame is clear, to have a high-resolution input image; The second part is the detection model, in order to ensure the real-time performance of hand keypoint detection, the model adopts a lightweight network structure to detect hand keypoint. The results show that this method has a high accuracy rate for the hand keypoint in the video, and the model was tested on the test set. Experimental results show that after adding super-resolution, the hand keypoint detection in the video is significantly improved.
{"title":"Hand keypoint detection with super resolution","authors":"X. Jia, Jianqiang Feng, Baolin Liang","doi":"10.1145/3558819.3565114","DOIUrl":"https://doi.org/10.1145/3558819.3565114","url":null,"abstract":"Hand interaction is an important research content in computer image processing at present. In sign language recognition, social interaction, virtual reality and augmented reality, the hand is the main input device for human interaction.Aiming at the problem of low recognition rate of hand keypoint in video, this paper proposes a deep convolutional neural network to recognize hand keypoint in video. The neural network is divided into two parts, the first part is image super-resolution, the purpose is to improve the resolution of each frame in the video, so that the image of each frame is clear, to have a high-resolution input image; The second part is the detection model, in order to ensure the real-time performance of hand keypoint detection, the model adopts a lightweight network structure to detect hand keypoint. The results show that this method has a high accuracy rate for the hand keypoint in the video, and the model was tested on the test set. Experimental results show that after adding super-resolution, the hand keypoint detection in the video is significantly improved.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"77 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":"117195325","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}
Control theory of complex system is an important subject in the development of automatic control theory cntrol system simulation is one of its research directions. The results of this study have been implemented on DNNSS simulation subsystem of multi-model complex nonlinear network. In this paper, the multi-model method is introduced to make the concept of the discontinuous right end of the simulation complex nonlinear system clear intuitive analysis applicability and description ability. This paper studies a series of theories and knowledge about the modeling and switching simulation of oil and gas dual-power system based on the association algorithm, reveals the concept and definition of the algorithm based on the association, and carries out the disposal of application cases of the modeling and switching simulation of oil and gas dual-power system. By oil and gas field power supply system for analysis of effect of oil and gas dual power supply system based on correlation algorithm to study the modeling and simulation of switching, test result shows that oil and gas dual power supply system based on correlation algorithm modeling and simulation in oil and gas field double switching power supply system in the agility, practicability, intelligent and robust reached 82.41%, 90.01%, 94.65%, 98.28%.
{"title":"Modeling and Switching Simulation of Oil-gas Dual-power System on Account of Association Algorithm","authors":"Yinfeng Qiu, Guoxiang Li, Hao Tian, Che Wei, Guofeng Liu, Zhaoyun Wu","doi":"10.1145/3558819.3565161","DOIUrl":"https://doi.org/10.1145/3558819.3565161","url":null,"abstract":"Control theory of complex system is an important subject in the development of automatic control theory cntrol system simulation is one of its research directions. The results of this study have been implemented on DNNSS simulation subsystem of multi-model complex nonlinear network. In this paper, the multi-model method is introduced to make the concept of the discontinuous right end of the simulation complex nonlinear system clear intuitive analysis applicability and description ability. This paper studies a series of theories and knowledge about the modeling and switching simulation of oil and gas dual-power system based on the association algorithm, reveals the concept and definition of the algorithm based on the association, and carries out the disposal of application cases of the modeling and switching simulation of oil and gas dual-power system. By oil and gas field power supply system for analysis of effect of oil and gas dual power supply system based on correlation algorithm to study the modeling and simulation of switching, test result shows that oil and gas dual power supply system based on correlation algorithm modeling and simulation in oil and gas field double switching power supply system in the agility, practicability, intelligent and robust reached 82.41%, 90.01%, 94.65%, 98.28%.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"139-140 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":"121287259","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}
Aiming at the noise caused by missing marker data in optical human motion capture, an improved LSTNet neural network model was proposed in this paper, which decomposed the noise prediction into linear part and nonlinear part. In the nonlinear part, convolutional neural network and recurrent neural network are used to deal with periodic prediction, and LSTM is used to replace the gated recurrent unit GRU to enhance memory function. The linear part uses autoregressive models to deal with aperiodic predictions. Finally, the loss function based on the position of markers is constructed to improve the prediction accuracy. The simulation results show that the proposed denoising technique can obtain lower reconstruction error and strong robustness, and the reconstructed motion sequence is very close to the real motion sequence.
{"title":"Predicting missing markers in mocap data using LSTNet","authors":"Yongqiong Zhu, Yemin Cai","doi":"10.1145/3558819.3565222","DOIUrl":"https://doi.org/10.1145/3558819.3565222","url":null,"abstract":"Aiming at the noise caused by missing marker data in optical human motion capture, an improved LSTNet neural network model was proposed in this paper, which decomposed the noise prediction into linear part and nonlinear part. In the nonlinear part, convolutional neural network and recurrent neural network are used to deal with periodic prediction, and LSTM is used to replace the gated recurrent unit GRU to enhance memory function. The linear part uses autoregressive models to deal with aperiodic predictions. Finally, the loss function based on the position of markers is constructed to improve the prediction accuracy. The simulation results show that the proposed denoising technique can obtain lower reconstruction error and strong robustness, and the reconstructed motion sequence is very close to the real motion sequence.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"10 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":"122645935","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 order to solve the problem of crowd counting and crowd density statistics in the security intelligent video surveillance system, this paper adopts the method based on deep learning to optimize the algorithm. This method mainly uses the VGG16 backbone network with 1*1 and 3*3 small convolution Classification and feature extraction of people information in a crowd. In order to reduce the sharp reduction in the number of positive samples after increasing the threshold, and to avoid the situation where using different thresholds during training and testing will cause the performance of the detector to degrade, this paper draws on the cascade structure of the Cascade R-CNN network for input video. The frame images are analyzed and processed, and different IoU thresholds are set at different stages to obtain enough positive samples to reduce over-fitting, and use the multi-task loss function and the Hadamard product to obtain the pedestrian detection network, and output the final number of people. The improved pedestrian counting algorithm in this paper is tested in the public dataset WorldExpo'10 Crowd Counting, and compared with other algorithms to verify the feasibility and effectiveness of this method.
{"title":"A pedestrian detection algorithm based on deep learning","authors":"Jiangkun Lu, Hongyang Chen","doi":"10.1145/3558819.3565151","DOIUrl":"https://doi.org/10.1145/3558819.3565151","url":null,"abstract":"In order to solve the problem of crowd counting and crowd density statistics in the security intelligent video surveillance system, this paper adopts the method based on deep learning to optimize the algorithm. This method mainly uses the VGG16 backbone network with 1*1 and 3*3 small convolution Classification and feature extraction of people information in a crowd. In order to reduce the sharp reduction in the number of positive samples after increasing the threshold, and to avoid the situation where using different thresholds during training and testing will cause the performance of the detector to degrade, this paper draws on the cascade structure of the Cascade R-CNN network for input video. The frame images are analyzed and processed, and different IoU thresholds are set at different stages to obtain enough positive samples to reduce over-fitting, and use the multi-task loss function and the Hadamard product to obtain the pedestrian detection network, and output the final number of people. The improved pedestrian counting algorithm in this paper is tested in the public dataset WorldExpo'10 Crowd Counting, and compared with other algorithms to verify the feasibility and effectiveness of this method.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"49 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":"131888919","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}
Based on PyTorch development platform, this paper builds the Generative Adversarial Networks (GAN) model. Through the preprocessing, label making, network training and algorithm improvement of UAV aerial images, this paper completes the deep-learning of transmission line feature information, solidifies the Generation Network parameters, and realizes the goal of automatic extraction of transmission line information from UAV images. Based on the Deep Convolution Neural Network, a multi generator GAN model is proposed. The cooperative working mechanism is introduced between the generation networks to speed up the model to obtain information and reduce the amount of parameters. The Wasserstein distance is introduced into the loss function of the model to avoid the problems of gradient disappearance and training instability in the process of GAN training. Through experimental analysis, it is proved that this method has a good reference for extracting transmission line information from high-resolution UAV images.
{"title":"Transmission Line Information Extraction from Images Collected by UAV based on Generative Adversarial Networks","authors":"Zhiyang Liu, Hangxuan Song, Mingyu Xu, Yuanting Hu, Wenbo Hao, Zhi Song","doi":"10.1145/3558819.3565228","DOIUrl":"https://doi.org/10.1145/3558819.3565228","url":null,"abstract":"Based on PyTorch development platform, this paper builds the Generative Adversarial Networks (GAN) model. Through the preprocessing, label making, network training and algorithm improvement of UAV aerial images, this paper completes the deep-learning of transmission line feature information, solidifies the Generation Network parameters, and realizes the goal of automatic extraction of transmission line information from UAV images. Based on the Deep Convolution Neural Network, a multi generator GAN model is proposed. The cooperative working mechanism is introduced between the generation networks to speed up the model to obtain information and reduce the amount of parameters. The Wasserstein distance is introduced into the loss function of the model to avoid the problems of gradient disappearance and training instability in the process of GAN training. Through experimental analysis, it is proved that this method has a good reference for extracting transmission line information from high-resolution UAV images.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"34 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":"128140163","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}
For the need of power transmission and distribution line pole and tower tilt and vibration monitoring, a MEMS (inertial sensor) based line pole and tower real-time monitoring system is designed. Firstly, based on the application scenario, application scope and design index of power transmission pole and tower multi-characteristic monitoring system, the attitude acquisition circuit design of the pole and tower, MCU control circuit design, software and hardware design of the communication terminal are carried out, and finally, the MEMS based power transmission and distribution pole and tower attitude sensing model technology is proposed. Based on the improved attitude solving model, the sensing accuracy of the pole and tower attitude change is improved to ensure the high reliability and high precision real-time monitoring and transmission of the pole and tower state characteristic parameters.
{"title":"Research on MEMS-based Multi-characteristic Parameter Monitoring System for Power Transmission and Distribution Line Pole and Tower","authors":"Lei Gao, Hongming Bai, Zhenhua Yang","doi":"10.1145/3558819.3558827","DOIUrl":"https://doi.org/10.1145/3558819.3558827","url":null,"abstract":"For the need of power transmission and distribution line pole and tower tilt and vibration monitoring, a MEMS (inertial sensor) based line pole and tower real-time monitoring system is designed. Firstly, based on the application scenario, application scope and design index of power transmission pole and tower multi-characteristic monitoring system, the attitude acquisition circuit design of the pole and tower, MCU control circuit design, software and hardware design of the communication terminal are carried out, and finally, the MEMS based power transmission and distribution pole and tower attitude sensing model technology is proposed. Based on the improved attitude solving model, the sensing accuracy of the pole and tower attitude change is improved to ensure the high reliability and high precision real-time monitoring and transmission of the pole and tower state characteristic parameters.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"35 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":"124286128","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 development of computer networks, network information security has gradually been concerned. The research on covert channel has become one of a hot issue in information security. However, the secure communication with encryption may attract much attention of the adversaries due to the random cipher messages. Therefore, the covert communication technology becomes a hot issue, since the covert communication can escape the monitor of the manicous users. In this paper, we have proposed a novel covert communication system by using frequency modulation to transmit covert information. With the of orthogonal frequency division multiplexing (OFDM) scheme, we propose to embedded the covert bits with frequency hopping. Furthermore, in the covert communication system, we put forth that the frequency of random jitter is employed as the carrier of covert messages, and the spread spectrum is encoded to encrypt the covert information. Simulation results show that the proposed covert communication system can achieve a good performance on bit error ratio and reliable covert communication.
{"title":"On Design of Covert Communication System with Frequency Hopping by OFDM","authors":"Lu-Jing Jiang, Zhengrong Song, Yun Zhang, Yuwen Qian","doi":"10.1145/3558819.3558837","DOIUrl":"https://doi.org/10.1145/3558819.3558837","url":null,"abstract":"With the rapid development of computer networks, network information security has gradually been concerned. The research on covert channel has become one of a hot issue in information security. However, the secure communication with encryption may attract much attention of the adversaries due to the random cipher messages. Therefore, the covert communication technology becomes a hot issue, since the covert communication can escape the monitor of the manicous users. In this paper, we have proposed a novel covert communication system by using frequency modulation to transmit covert information. With the of orthogonal frequency division multiplexing (OFDM) scheme, we propose to embedded the covert bits with frequency hopping. Furthermore, in the covert communication system, we put forth that the frequency of random jitter is employed as the carrier of covert messages, and the spread spectrum is encoded to encrypt the covert information. Simulation results show that the proposed covert communication system can achieve a good performance on bit error ratio and reliable covert communication.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"35 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":"114484250","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}
Jinsong Huang, Yu-Qing Cai, Wu-chun Feng, Qin Li, Xin Wang
In the application of vertical well inclinometer, the erosion wear of pulser under various working conditions such as high displacement is the main factor leading to its failure. In this paper, based on the analysis of erosion factors and theoretical erosion rate, SolidWorks is used to restore the pulse structure with the same material and the same size. DPM multiphase flow model in Fluent and CFX numerical simulation is used to simulate the fluid/particle movement state and distribution law of the pulse under the downhole operation state. From the velocity, pressure, turbulence parameters, particle mass concentration and other body parts for key erosion, erosion mechanism and analysis, main show is to fluid cluster after local turbulence caused by the phenomenon, the upper fluid blocked reflection and original fluid phenomenon of turbulence in the collision, water hammer effect of instantaneous high pressure effect, local vortex caused by uneven pressure, The flow regime changes caused by Karman vortex street effect, the collision process caused by the accumulation and aggregation of particles, and the impact process caused by the fluid transport particles on the wall.
{"title":"Study on the Pulser Erosion Mechanism of Vertical Well Inclinometer through CFX Numerical Simulation","authors":"Jinsong Huang, Yu-Qing Cai, Wu-chun Feng, Qin Li, Xin Wang","doi":"10.1145/3558819.3565195","DOIUrl":"https://doi.org/10.1145/3558819.3565195","url":null,"abstract":"In the application of vertical well inclinometer, the erosion wear of pulser under various working conditions such as high displacement is the main factor leading to its failure. In this paper, based on the analysis of erosion factors and theoretical erosion rate, SolidWorks is used to restore the pulse structure with the same material and the same size. DPM multiphase flow model in Fluent and CFX numerical simulation is used to simulate the fluid/particle movement state and distribution law of the pulse under the downhole operation state. From the velocity, pressure, turbulence parameters, particle mass concentration and other body parts for key erosion, erosion mechanism and analysis, main show is to fluid cluster after local turbulence caused by the phenomenon, the upper fluid blocked reflection and original fluid phenomenon of turbulence in the collision, water hammer effect of instantaneous high pressure effect, local vortex caused by uneven pressure, The flow regime changes caused by Karman vortex street effect, the collision process caused by the accumulation and aggregation of particles, and the impact process caused by the fluid transport particles on the wall.","PeriodicalId":373484,"journal":{"name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","volume":"27 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":"114609962","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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