Pub Date : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345296
Yuhua Wang, Laixian Peng, Renhui Xu, Yaoqi Yang, Lin Ge
Battlefield information interaction has high requirements for its effectiveness, but traditional algorithms are still inadequate in this respect. In this paper, the neighbor discovery process in wireless Ad hoc networks with directional antennas is discussed and an efficient neighbor discovery algorithm based on Q-learning theory is proposed. This paper takes traditional blind algorithm of all sectors scanning as the basis, then a fast neighbor discovery algorithm with the use of Q-learning is analyzed, which divides the neighbor discovery process into three stages, the initial stage without prior location information, the reinforcement learning stage, and the completion stage for mutual discovery in the shortest time. Finally, OPNET Modeler 14.5 is used to simulate this model, and the result show that the algorithm can improve the efficiency of neighbor discovery by nearly 86%.
{"title":"A Fast Neighbor Discovery Algorithm Based on Q-learning in Wireless Ad Hoc Networks with Directional Antennas","authors":"Yuhua Wang, Laixian Peng, Renhui Xu, Yaoqi Yang, Lin Ge","doi":"10.1109/ICCC51575.2020.9345296","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345296","url":null,"abstract":"Battlefield information interaction has high requirements for its effectiveness, but traditional algorithms are still inadequate in this respect. In this paper, the neighbor discovery process in wireless Ad hoc networks with directional antennas is discussed and an efficient neighbor discovery algorithm based on Q-learning theory is proposed. This paper takes traditional blind algorithm of all sectors scanning as the basis, then a fast neighbor discovery algorithm with the use of Q-learning is analyzed, which divides the neighbor discovery process into three stages, the initial stage without prior location information, the reinforcement learning stage, and the completion stage for mutual discovery in the shortest time. Finally, OPNET Modeler 14.5 is used to simulate this model, and the result show that the algorithm can improve the efficiency of neighbor discovery by nearly 86%.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121574757","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345209
Feng Li, Haina Song, Jianfeng Li
Mobile crowdsensing is growing in popularity by collecting environmental information from participants' mobile phones. However, the sensing data may carry sensitive information of participants so as to violate their privacy. Thus, local differential privacy (LDP) is proposed to protect participants' privacy during data collection. But most recent studies only apply LDP to the data collection without considering the participant's personal privacy preservation requirement so as to reduce the data utility when aggregator tries to execute the frequency estimation. In this paper, a new LDP algorithm with the optimal privacy perturbation parameter based on Basic RAPPOR is proposed to improve data utility by minimizing the expected mean square error (EMSE). Then, a personalized data collection scheme based on the new LDP is elaborately presented to realize the fact that every participant can select his/her required privacy level to achieve personalized privacy preservation while guaranteeing higher data utility. Finally, the proposed personalized data collection scheme is simulated and verified on both synthetic and real datasets, which proves the feasibility and effectiveness of the proposed scheme in terms of the MSE.
{"title":"Personalized Data Collection Based on Local Differential Privacy in the Mobile Crowdsensing","authors":"Feng Li, Haina Song, Jianfeng Li","doi":"10.1109/ICCC51575.2020.9345209","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345209","url":null,"abstract":"Mobile crowdsensing is growing in popularity by collecting environmental information from participants' mobile phones. However, the sensing data may carry sensitive information of participants so as to violate their privacy. Thus, local differential privacy (LDP) is proposed to protect participants' privacy during data collection. But most recent studies only apply LDP to the data collection without considering the participant's personal privacy preservation requirement so as to reduce the data utility when aggregator tries to execute the frequency estimation. In this paper, a new LDP algorithm with the optimal privacy perturbation parameter based on Basic RAPPOR is proposed to improve data utility by minimizing the expected mean square error (EMSE). Then, a personalized data collection scheme based on the new LDP is elaborately presented to realize the fact that every participant can select his/her required privacy level to achieve personalized privacy preservation while guaranteeing higher data utility. Finally, the proposed personalized data collection scheme is simulated and verified on both synthetic and real datasets, which proves the feasibility and effectiveness of the proposed scheme in terms of the MSE.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125621746","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345177
Yu Hao, Jin Xin, Wang Tao, Song Tao, Lv Yu-xiang, Wu Hao
In this letter, a pilot allocation algorithm based on K-means clustering is proposed for the cell-free massive MIMO systems. Firstly, to avoid the communication between users and “invalid” access points (APs), a user-centered virtual cell division is adopted. Users select AP according to the large-scale factor of the channel to form a specific AP set which serves the specific users. Then, K value is determined by combining multiple features and the initial centroid is selected to cluster users. Finally, based on the results of user clustering, users in the internal cluster are assigned to orthogonal pilots, and users in different clusters are reused pilots, which can avoid pilot contamination (PC) caused by pilot reusing among users from the space perspective. Simulation results show that the proposed algorithm can reduce channel estimation error and enhance system throughput.
{"title":"Pilot Allocation Algorithm Based on K-means Clustering in Cell-Free Massive MIMO Systems","authors":"Yu Hao, Jin Xin, Wang Tao, Song Tao, Lv Yu-xiang, Wu Hao","doi":"10.1109/ICCC51575.2020.9345177","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345177","url":null,"abstract":"In this letter, a pilot allocation algorithm based on K-means clustering is proposed for the cell-free massive MIMO systems. Firstly, to avoid the communication between users and “invalid” access points (APs), a user-centered virtual cell division is adopted. Users select AP according to the large-scale factor of the channel to form a specific AP set which serves the specific users. Then, K value is determined by combining multiple features and the initial centroid is selected to cluster users. Finally, based on the results of user clustering, users in the internal cluster are assigned to orthogonal pilots, and users in different clusters are reused pilots, which can avoid pilot contamination (PC) caused by pilot reusing among users from the space perspective. Simulation results show that the proposed algorithm can reduce channel estimation error and enhance system throughput.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125062668","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9344909
Mingxin Liu, L. Zou, Xue-gang Wang
In space-time adaptive processing (STAP) of airborne radar, the mutual coupling among array elements can lead to inaccurate estimation of the clutter covariance matrix (CCM), which makes the radar performance degradation. To solve this problem, a new STAP algorithm based on the coprime structure is developed. The proposed method uses the coprime structure and difference operation to construct the virtual space-time snapshots. Thus, the CCM is computed by utilizing these virtual snapshots obtained by using the low-rank matrix recovery technology. Finally, the virtual weight vector is built. The simulation results verify the effectiveness and superiority of the proposed method. The proposed algorithm can reduce the mutual coupling effect, accurately estimate CCM, and improve degrees of freedom (DOF).
{"title":"Airborne STAP with Unknown Mutual Coupling for Coprime Sampling Structure","authors":"Mingxin Liu, L. Zou, Xue-gang Wang","doi":"10.1109/ICCC51575.2020.9344909","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9344909","url":null,"abstract":"In space-time adaptive processing (STAP) of airborne radar, the mutual coupling among array elements can lead to inaccurate estimation of the clutter covariance matrix (CCM), which makes the radar performance degradation. To solve this problem, a new STAP algorithm based on the coprime structure is developed. The proposed method uses the coprime structure and difference operation to construct the virtual space-time snapshots. Thus, the CCM is computed by utilizing these virtual snapshots obtained by using the low-rank matrix recovery technology. Finally, the virtual weight vector is built. The simulation results verify the effectiveness and superiority of the proposed method. The proposed algorithm can reduce the mutual coupling effect, accurately estimate CCM, and improve degrees of freedom (DOF).","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"202 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114009292","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345025
Gang Zheng, Xinzhong Xu, Chao Wang
In recent years, IPv6 and its application are more and more widely deployed. Most network devices support and open IPv6 protocol stack. The security of IPv6 network is also concerned. In the IPv6 network security technology, address scanning is a key and difficult point. This paper presents a TGAs-based IPv6 address scanning method. It takes the known alive IPv6 addresses as input, and then utilizes the information entropy and clustering technology to mine the distribution law of seed addresses. Then, the final optimized target address set can be obtained by expanding from the seed address set according to the distribution law. Experimental results show that it can effectively improve the efficiency of IPv6 address scanning.
{"title":"An Effective Target Address Generation Method for IPv6 Address Scan","authors":"Gang Zheng, Xinzhong Xu, Chao Wang","doi":"10.1109/ICCC51575.2020.9345025","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345025","url":null,"abstract":"In recent years, IPv6 and its application are more and more widely deployed. Most network devices support and open IPv6 protocol stack. The security of IPv6 network is also concerned. In the IPv6 network security technology, address scanning is a key and difficult point. This paper presents a TGAs-based IPv6 address scanning method. It takes the known alive IPv6 addresses as input, and then utilizes the information entropy and clustering technology to mine the distribution law of seed addresses. Then, the final optimized target address set can be obtained by expanding from the seed address set according to the distribution law. Experimental results show that it can effectively improve the efficiency of IPv6 address scanning.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122691947","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345294
Dexin Yin, Damin Zhang
To improve spectrum allocation optimization and optimal convergence accuracy in cognitive radio, a nonlinear spider monkey algorithm based on sine-cosine Algorithm (SCNWSMO) is proposed. In the decision-making stages of global leader and the local leader, the spider monkey individuals are optimized by sine-cosine Algorithm. Moreover, the nonlinear decreasing inertia weight factor is introduced to effectively control the global optimization and local optimization capabilities of the algorithm and improve the convergence speed. Finally, the performance of SCNWSMO is compared with various algorithms total system benefit, and average network benefit. Simulation results show that the SCNWSMO is advantageous over other algorithms with higher network efficiency.
{"title":"Spectrum Allocation Based on Spider Monkey Optimization Algorithm with Nonlinear Inertia Weight and Sine-Cosine Algorithm","authors":"Dexin Yin, Damin Zhang","doi":"10.1109/ICCC51575.2020.9345294","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345294","url":null,"abstract":"To improve spectrum allocation optimization and optimal convergence accuracy in cognitive radio, a nonlinear spider monkey algorithm based on sine-cosine Algorithm (SCNWSMO) is proposed. In the decision-making stages of global leader and the local leader, the spider monkey individuals are optimized by sine-cosine Algorithm. Moreover, the nonlinear decreasing inertia weight factor is introduced to effectively control the global optimization and local optimization capabilities of the algorithm and improve the convergence speed. Finally, the performance of SCNWSMO is compared with various algorithms total system benefit, and average network benefit. Simulation results show that the SCNWSMO is advantageous over other algorithms with higher network efficiency.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131112093","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9344946
Xiaomin Yang, Shuai Zhao, B. Cheng, Xu Wang, Jianchang Ao, Zhenzi Li, Zeyan Cao
A knowledge graph is a semantic network that reveals the relationships between entities. Domain knowledge graphs can assist practitioners in complex analysis applications and decision support, and build industry barriers. A good construction system can help companies construct domain knowledge graphs efficiently and quickly. However, due to the differences in data models and business requirements in different fields, there is no general method for constructing a domain knowledge graph. Moreover, the current construction methods require a lot of manpower investment, which is relatively inefficient. To solve the inefficiency and nonuniversal problems in the process of domain knowledge graph construction, in this paper, we study the automated construction mechanism of Chinese domain knowledge graphs and propose a general automatic construction solution. Experimental results show that our proposed solution is more effective in constructing a domain knowledge graph.
{"title":"A General Solution and Practice for Automatically Constructing Domain Knowledge Graph","authors":"Xiaomin Yang, Shuai Zhao, B. Cheng, Xu Wang, Jianchang Ao, Zhenzi Li, Zeyan Cao","doi":"10.1109/ICCC51575.2020.9344946","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9344946","url":null,"abstract":"A knowledge graph is a semantic network that reveals the relationships between entities. Domain knowledge graphs can assist practitioners in complex analysis applications and decision support, and build industry barriers. A good construction system can help companies construct domain knowledge graphs efficiently and quickly. However, due to the differences in data models and business requirements in different fields, there is no general method for constructing a domain knowledge graph. Moreover, the current construction methods require a lot of manpower investment, which is relatively inefficient. To solve the inefficiency and nonuniversal problems in the process of domain knowledge graph construction, in this paper, we study the automated construction mechanism of Chinese domain knowledge graphs and propose a general automatic construction solution. Experimental results show that our proposed solution is more effective in constructing a domain knowledge graph.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131374957","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345286
Louai Sheikhani, C. Gu
Cloud computing represents a new way to deploy computing technology to give users the ability to access, work on, share, and store information using the Internet. Developments in Cloud computing gain rapid attention of the researcher to maximize the utilization of computing resources such as storage, CPUs, and network bandwidth as service-by-service providers at less cost. The optimization models aims to optimize both resource centric such as utilization, availability, reliability and user centric like response time, budget spent fairness, and since the broker is responsible of route the user request to the most appropriate datacenter in the cloud system, choosing the right broker policy affect directly the optimization of the resources, in this paper we explore various number of existing broker policy and compare them in different scenarios in order to show the advantages and limitations of each one of them due there impact on the response time and the load distribution over the system.
{"title":"The Effect of Various Broker Policy Algorithms in Geo-distributed Datacenters on Response Time and Load Balance Review and analysis","authors":"Louai Sheikhani, C. Gu","doi":"10.1109/ICCC51575.2020.9345286","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345286","url":null,"abstract":"Cloud computing represents a new way to deploy computing technology to give users the ability to access, work on, share, and store information using the Internet. Developments in Cloud computing gain rapid attention of the researcher to maximize the utilization of computing resources such as storage, CPUs, and network bandwidth as service-by-service providers at less cost. The optimization models aims to optimize both resource centric such as utilization, availability, reliability and user centric like response time, budget spent fairness, and since the broker is responsible of route the user request to the most appropriate datacenter in the cloud system, choosing the right broker policy affect directly the optimization of the resources, in this paper we explore various number of existing broker policy and compare them in different scenarios in order to show the advantages and limitations of each one of them due there impact on the response time and the load distribution over the system.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121764791","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345081
R. Guo, Yuanjing Ma, Shuai Wang, Yiming Du, Shihai Wang
According to the existing air quality forecasting model, this paper proposed an air quality forecasting method based on deep learning. By analyzing forecasting data, monitoring data and meteorological data, a new air quality forecasting model in the region is established. The model fully takes into account the time variability and spatial distribution characteristics of air pollutant concentration, and introduces meteorological data as covariates to predict any location in the study area.
{"title":"Establishment of Air Quality Forecast Model Based on Deep Learning","authors":"R. Guo, Yuanjing Ma, Shuai Wang, Yiming Du, Shihai Wang","doi":"10.1109/ICCC51575.2020.9345081","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345081","url":null,"abstract":"According to the existing air quality forecasting model, this paper proposed an air quality forecasting method based on deep learning. By analyzing forecasting data, monitoring data and meteorological data, a new air quality forecasting model in the region is established. The model fully takes into account the time variability and spatial distribution characteristics of air pollutant concentration, and introduces meteorological data as covariates to predict any location in the study area.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127654650","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 : 2020-12-11DOI: 10.1109/ICCC51575.2020.9345032
Jing Li, L. Zou, Chuanchuan Pang, Xue-gang Wang
For MIMO cascaded sparse planar array radar, the angle resolution and precision are not high enough and the sidelobe is high if use zero-padding. This paper proposed an angle estimation method based on block spatial smoothing interpolation. This method combines spatial smoothing and interpolation. Firstly, segment and smooth the antenna array. By solving the interpolation function to find the relationship of actual and expected flow pattern matrixes, we can realize the interpolation of the received signal and figure out the angle information. According to the simulation result, under a certain SNR, the elevation resolution can be improved for 2–3 times with suitable interpolation antenna number, compared to traditional method. Meanwhile, the main / sidelobe ratio is improved about 11dB. The reduction of the high sidelobe and gatelobe is also good.
{"title":"2D Angle Estimation Based on Block Spatial Smoothing Interpolation Method","authors":"Jing Li, L. Zou, Chuanchuan Pang, Xue-gang Wang","doi":"10.1109/ICCC51575.2020.9345032","DOIUrl":"https://doi.org/10.1109/ICCC51575.2020.9345032","url":null,"abstract":"For MIMO cascaded sparse planar array radar, the angle resolution and precision are not high enough and the sidelobe is high if use zero-padding. This paper proposed an angle estimation method based on block spatial smoothing interpolation. This method combines spatial smoothing and interpolation. Firstly, segment and smooth the antenna array. By solving the interpolation function to find the relationship of actual and expected flow pattern matrixes, we can realize the interpolation of the received signal and figure out the angle information. According to the simulation result, under a certain SNR, the elevation resolution can be improved for 2–3 times with suitable interpolation antenna number, compared to traditional method. Meanwhile, the main / sidelobe ratio is improved about 11dB. The reduction of the high sidelobe and gatelobe is also good.","PeriodicalId":386048,"journal":{"name":"2020 IEEE 6th International Conference on Computer and Communications (ICCC)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128147622","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}