Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00044
Lei Shi, Li Hui, Jing Shi, Bin Zhao, Xiao Cui, Shibo Chu
The paper presented a new wave acquisition stereo system to estimate significant wave height based on stereo (binocular) vision. Using binocular vision, wave transformation in near shore water can be measured in wave altitude. The total measurement numbers are 1024 times. Wave vertical altitudes can be extracted from the datum according to binocular vision. With the help of 3D Fourier transform, the wave surface data can be turned into wave spectrum. By analyzing the wave spectrum, significant wave height can be estimated. Experimental results have shown that the method is effective.
{"title":"Using binocular vision to measure wave characteristic","authors":"Lei Shi, Li Hui, Jing Shi, Bin Zhao, Xiao Cui, Shibo Chu","doi":"10.1109/ICCEAI52939.2021.00044","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00044","url":null,"abstract":"The paper presented a new wave acquisition stereo system to estimate significant wave height based on stereo (binocular) vision. Using binocular vision, wave transformation in near shore water can be measured in wave altitude. The total measurement numbers are 1024 times. Wave vertical altitudes can be extracted from the datum according to binocular vision. With the help of 3D Fourier transform, the wave surface data can be turned into wave spectrum. By analyzing the wave spectrum, significant wave height can be estimated. Experimental results have shown that the method is effective.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115543115","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 : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00022
Zhaoyang Liu, Mingxi Ma, Zhaoming Wu
Hyperspectral images usually have higher spectral resolution but lower spatial resolution, compared with the multispectral images. Low spatial resolution brings difficulties to the practical applications of hyperspectral images. Therefore, to get high spatial resolution hyperspectral image, it is very important to fuse low spatial resolution hyperspectral image with the high spatial resolution multispectral image in the same scene. In this paper, we propose a hybrid regularization model by integrating sparse prior, local low-rank regularization and total variation based on l2 norm to reconstruct high spatial resolution hyperspectral images. In addition, we design an alternating direction method of multipliers (ADMM) to solve it. The experimental results show the superiority and competitiveness of our method over the state-of-the-art methods.
{"title":"Hyperspectral image fusion by hybrid regularizations with local low-rank","authors":"Zhaoyang Liu, Mingxi Ma, Zhaoming Wu","doi":"10.1109/ICCEAI52939.2021.00022","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00022","url":null,"abstract":"Hyperspectral images usually have higher spectral resolution but lower spatial resolution, compared with the multispectral images. Low spatial resolution brings difficulties to the practical applications of hyperspectral images. Therefore, to get high spatial resolution hyperspectral image, it is very important to fuse low spatial resolution hyperspectral image with the high spatial resolution multispectral image in the same scene. In this paper, we propose a hybrid regularization model by integrating sparse prior, local low-rank regularization and total variation based on l2 norm to reconstruct high spatial resolution hyperspectral images. In addition, we design an alternating direction method of multipliers (ADMM) to solve it. The experimental results show the superiority and competitiveness of our method over the state-of-the-art methods.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115682023","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 : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00010
S. Sun, Yatong Zhou, Haonuo He, Jingfei He, Yue Chi
With the development of power industry, electricity has become one of the most important energy sources in our country, related to the lifeline of the country's economy. The electricity system is becoming more and more mature, but abnormal electricity consumption behaviors are also emerging endlessly, causing potential safety hazards in the electricity industry and even the electricity supply system. Considering the lack of abnormal annotations in the electricity load data, this paper proposes a semi-supervised electricity load data anomaly detection method based on MixMatch. Firstly, data cleaning of electricity load data is used to remove incorrect data. Secondly, Convolutional Autoencoder (CAE) is used to extract its time-domain and frequency-domain features separately, and the features are combined through feature fusion. Thirdly, the Borderline Synthetic Minority Oversampling Technique (Borderline-SMOTE) is used to solve the problem of data imbalance. The MixMatch semi-supervised algorithm is used to label the abnormal data to realize the anomaly detection of the electricity load data. Finally, this paper uses the k-means clustering and T-Stochastic neighbour Embedding (T -SNE) to classify the abnormal data and visualize the data. The experimental results show that, compared with traditional machine learning methods, the proposed method has a significant improvement on AUC.
{"title":"Anomaly detection of electricity load data based on MixMatch","authors":"S. Sun, Yatong Zhou, Haonuo He, Jingfei He, Yue Chi","doi":"10.1109/ICCEAI52939.2021.00010","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00010","url":null,"abstract":"With the development of power industry, electricity has become one of the most important energy sources in our country, related to the lifeline of the country's economy. The electricity system is becoming more and more mature, but abnormal electricity consumption behaviors are also emerging endlessly, causing potential safety hazards in the electricity industry and even the electricity supply system. Considering the lack of abnormal annotations in the electricity load data, this paper proposes a semi-supervised electricity load data anomaly detection method based on MixMatch. Firstly, data cleaning of electricity load data is used to remove incorrect data. Secondly, Convolutional Autoencoder (CAE) is used to extract its time-domain and frequency-domain features separately, and the features are combined through feature fusion. Thirdly, the Borderline Synthetic Minority Oversampling Technique (Borderline-SMOTE) is used to solve the problem of data imbalance. The MixMatch semi-supervised algorithm is used to label the abnormal data to realize the anomaly detection of the electricity load data. Finally, this paper uses the k-means clustering and T-Stochastic neighbour Embedding (T -SNE) to classify the abnormal data and visualize the data. The experimental results show that, compared with traditional machine learning methods, the proposed method has a significant improvement on AUC.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114672067","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 : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00086
Li Wang, Siyu Tang, Jiageng Zhang, Heshan Wang, Jiawei Han, Jianxiang Cao
In the intensive computing scenario with the application of micro-service framework, it is too costly to allocate resources centrally to the micro-service instance on the server side, and it cannot adapt to the changes of the environment in real time. Therefore, allocating resource for micro-service instance distributed on the terminal becomes an effective way to solve the problem mentioned above. A client-based micro-service discovery algorithm with attractor selection model is proposed in this paper, which has the characters of simple and intelligent evolution. At first, this paper models micro-service discovery problem, defines optimization object and constraints; then, it re-defines the parameters of attractor selection and proposes the client-based micro-service discovery algorithm with attractor selection model; and at last, it analyzes the performance of the proposed algorithm with the compared ones in the really productive environment. The experiment results show that the proposed algorithm reduces almost 32 % resource fragments and 70% running time than the compared ones.
{"title":"Terminal Micro-service Discovery Algorithm based on attractor model","authors":"Li Wang, Siyu Tang, Jiageng Zhang, Heshan Wang, Jiawei Han, Jianxiang Cao","doi":"10.1109/ICCEAI52939.2021.00086","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00086","url":null,"abstract":"In the intensive computing scenario with the application of micro-service framework, it is too costly to allocate resources centrally to the micro-service instance on the server side, and it cannot adapt to the changes of the environment in real time. Therefore, allocating resource for micro-service instance distributed on the terminal becomes an effective way to solve the problem mentioned above. A client-based micro-service discovery algorithm with attractor selection model is proposed in this paper, which has the characters of simple and intelligent evolution. At first, this paper models micro-service discovery problem, defines optimization object and constraints; then, it re-defines the parameters of attractor selection and proposes the client-based micro-service discovery algorithm with attractor selection model; and at last, it analyzes the performance of the proposed algorithm with the compared ones in the really productive environment. The experiment results show that the proposed algorithm reduces almost 32 % resource fragments and 70% running time than the compared ones.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114936035","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 : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00036
Zhuo-Ya Pan
The new information technology revolution is subverting the traditional business model, and the challenges and opportunities of industrial innovation coexist. In order to enable the stadiums to achieve sustainable development under the new social development situation, Internet technology is gradually infiltrating the management of the stadiums. Large-scale sports events often require a lot of sports venues. For this reason, a large number of sports venues will be modified and built to provide comprehensive solutions for the systematic management of the stadiums and the use of them after the game. Integrate development of stadiums and stadiums through the Internet platform to improve the management level of stadiums and stadiums.
{"title":"Research on the integrated development of stadiums and stadiums under the background of “Internet +”","authors":"Zhuo-Ya Pan","doi":"10.1109/ICCEAI52939.2021.00036","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00036","url":null,"abstract":"The new information technology revolution is subverting the traditional business model, and the challenges and opportunities of industrial innovation coexist. In order to enable the stadiums to achieve sustainable development under the new social development situation, Internet technology is gradually infiltrating the management of the stadiums. Large-scale sports events often require a lot of sports venues. For this reason, a large number of sports venues will be modified and built to provide comprehensive solutions for the systematic management of the stadiums and the use of them after the game. Integrate development of stadiums and stadiums through the Internet platform to improve the management level of stadiums and stadiums.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115001402","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 : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00033
Lei Wang, Zhiyong Zhang, Xiaonan Li
As the self-occlusion or occluded 3D point clouds objects in complex scenes, which could affect the accuracy of objects classification, we propose Optimal Combination of Multidimensional Features based on deep learning for large-scene laser point clouds in classification. We construct the optimal combination matrix of multidimensional features by extracting the three-dimensional features of the three-dimensional point cloud and the two-dimensional features in multiple directions. The multidimensional optimal combination features are introduced into the convolutional network. The experimental results show that effectiveness of classification for large-scale point clouds, the effectiveness of 3D feature of point cloud is higher than that of 2D feature. The classification accuracy of our method can reach 98.8% on the Large-Scene Point Cloud Oakland data set, which obtains the better classification accuracy than other classification algorithms the paper mentioned.
针对复杂场景中自遮挡或遮挡的三维点云对象，影响目标分类精度的问题，提出了基于深度学习的大场景激光点云多维特征最优组合分类方法。通过在多个方向上提取三维点云的三维特征和二维特征，构建最优的多维特征组合矩阵。在卷积网络中引入了多维最优组合特征。实验结果表明，对大规模点云进行分类的有效性，点云的三维特征分类的有效性高于二维特征分类的有效性。本文方法在Large-Scene Point Cloud Oakland数据集上的分类准确率可达98.8%，获得了比本文提到的其他分类算法更好的分类准确率。
{"title":"Research on Deep Learning Based Optimal Combination of Multidimensional Features in Large-Scene Laser Point Clouds Classification","authors":"Lei Wang, Zhiyong Zhang, Xiaonan Li","doi":"10.1109/ICCEAI52939.2021.00033","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00033","url":null,"abstract":"As the self-occlusion or occluded 3D point clouds objects in complex scenes, which could affect the accuracy of objects classification, we propose Optimal Combination of Multidimensional Features based on deep learning for large-scene laser point clouds in classification. We construct the optimal combination matrix of multidimensional features by extracting the three-dimensional features of the three-dimensional point cloud and the two-dimensional features in multiple directions. The multidimensional optimal combination features are introduced into the convolutional network. The experimental results show that effectiveness of classification for large-scale point clouds, the effectiveness of 3D feature of point cloud is higher than that of 2D feature. The classification accuracy of our method can reach 98.8% on the Large-Scene Point Cloud Oakland data set, which obtains the better classification accuracy than other classification algorithms the paper mentioned.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128621306","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 : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00045
Zhu Zeng
One of the most commonly used natural language processing technologies is text classification. Spam detection, news text classification, information retrieval, emotion analysis, and intention judgment, among other applications, are all popular text classification applications [25]. Text classification is the process of assigning pre-defined class labels to text documents in order to shape semantic classes. Engineering, medical science, life science, social sciences and humanities, marketing, and government are only a few of the real-world applications. Machine learning and deep learning algorithms have recently become common and efficient methods for dealing with text classification problems involving labeled data [26]. The primary goal of text classification is to automatically assign texts to pre-defined categories based on their content. In this study, we will conduct a comparative study of the accuracies of different deep learning methods that include Bidirectional Encoder Representations from Transformers (BERT), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), and Region-based convolutional neural networks and compare the effectiveness of these deep-learning approaches in classifying Chinese news title text using the THUCNews dataset.
{"title":"A comparative study of deep learning approaches for Chinese Sentence Classification","authors":"Zhu Zeng","doi":"10.1109/ICCEAI52939.2021.00045","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00045","url":null,"abstract":"One of the most commonly used natural language processing technologies is text classification. Spam detection, news text classification, information retrieval, emotion analysis, and intention judgment, among other applications, are all popular text classification applications [25]. Text classification is the process of assigning pre-defined class labels to text documents in order to shape semantic classes. Engineering, medical science, life science, social sciences and humanities, marketing, and government are only a few of the real-world applications. Machine learning and deep learning algorithms have recently become common and efficient methods for dealing with text classification problems involving labeled data [26]. The primary goal of text classification is to automatically assign texts to pre-defined categories based on their content. In this study, we will conduct a comparative study of the accuracies of different deep learning methods that include Bidirectional Encoder Representations from Transformers (BERT), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), and Region-based convolutional neural networks and compare the effectiveness of these deep-learning approaches in classifying Chinese news title text using the THUCNews dataset.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133320948","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 : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00034
Lin Yuting, Wang Jianyao
Media integration is the future development trend. New media play a role in promoting the development of information visualization. Information visualization in the new media environment is undergoing media changes, and information carriers are developing diversified. By analyzing the relationship between video games and information visualization, explore the development trend of information visualization in the new media environment, and analyze the influence of video game media on information visualization.
{"title":"Research on Information Visualization of Electronic Games","authors":"Lin Yuting, Wang Jianyao","doi":"10.1109/ICCEAI52939.2021.00034","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00034","url":null,"abstract":"Media integration is the future development trend. New media play a role in promoting the development of information visualization. Information visualization in the new media environment is undergoing media changes, and information carriers are developing diversified. By analyzing the relationship between video games and information visualization, explore the development trend of information visualization in the new media environment, and analyze the influence of video game media on information visualization.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116289747","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 : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00015
Binbin Fan, Fengzeng Liu, Yuzhao Huang
With the normalization of requirement collection in the field of information and communication business, it is found that it is difficult to collect and manage requirement. In order to solve this problem, this paper analyzes the requirements of the collection system, designs the system architecture and functional modules, realizes the requirement collection system based on B / S architecture, and focuses on standardizing the requirement collection template and requirement data management, so as to improve the quality and efficiency of requirement collection as a whole.
{"title":"Design and Implementation of a Business Domain Requirement Collection System","authors":"Binbin Fan, Fengzeng Liu, Yuzhao Huang","doi":"10.1109/ICCEAI52939.2021.00015","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00015","url":null,"abstract":"With the normalization of requirement collection in the field of information and communication business, it is found that it is difficult to collect and manage requirement. In order to solve this problem, this paper analyzes the requirements of the collection system, designs the system architecture and functional modules, realizes the requirement collection system based on B / S architecture, and focuses on standardizing the requirement collection template and requirement data management, so as to improve the quality and efficiency of requirement collection as a whole.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122536440","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 switching control model of hybrid system, the stability of hybrid system is discussed. Combined with the typical switching control model, the sufficient conditions for the hybrid switching system to remain stable when the switching discrete state is changed and the system energy is increased are given. By dividing the switched system into a more reasonable area and adjusting the control law in time, the optimal control of the switched system is achieved. The stability condition of traffic signal switching control is verified by simulation with the traffic signal switching model of key traffic nodes (regions) in unbalanced road network based on hybrid system model. The experimental results show that the hybrid switched control system has more outstanding advantages than the discrete dynamic and continuous dynamic systems in urban traffic signal control.
{"title":"Stability Analysis and Application Research of Hybrid Dynamic System","authors":"Qianqian Wang, Minan Tang, Aimin An, Weili Liu, Kaiyue Zhang, Jiandong Qiu","doi":"10.1109/ICCEAI52939.2021.00082","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00082","url":null,"abstract":"Aiming at the switching control model of hybrid system, the stability of hybrid system is discussed. Combined with the typical switching control model, the sufficient conditions for the hybrid switching system to remain stable when the switching discrete state is changed and the system energy is increased are given. By dividing the switched system into a more reasonable area and adjusting the control law in time, the optimal control of the switched system is achieved. The stability condition of traffic signal switching control is verified by simulation with the traffic signal switching model of key traffic nodes (regions) in unbalanced road network based on hybrid system model. The experimental results show that the hybrid switched control system has more outstanding advantages than the discrete dynamic and continuous dynamic systems in urban traffic signal control.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116983811","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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