Pub Date : 2014-12-15DOI: 10.1109/SPAC.2014.6982695
Tao Zhou
We propose a novel approach for detecting keypoints invariant to scale changes based on M-wavelet theory. The theory description and detecting process of our approach are presented The comparative evaluation of different detectors shows our approach can provides a competent performance in rotation invariant, scale invariant, illumination invariant and noiseproof. In terms of scale changes, our proposed approach improves keypoint repeatability by 2%~10% compared with scale invariant feature transform (SIFT), speeded up robust features (SURF), Harris-Laplace, Hessian-Laplace.
{"title":"A scale invariant keypoints detector","authors":"Tao Zhou","doi":"10.1109/SPAC.2014.6982695","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982695","url":null,"abstract":"We propose a novel approach for detecting keypoints invariant to scale changes based on M-wavelet theory. The theory description and detecting process of our approach are presented The comparative evaluation of different detectors shows our approach can provides a competent performance in rotation invariant, scale invariant, illumination invariant and noiseproof. In terms of scale changes, our proposed approach improves keypoint repeatability by 2%~10% compared with scale invariant feature transform (SIFT), speeded up robust features (SURF), Harris-Laplace, Hessian-Laplace.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116418208","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 : 2014-12-15DOI: 10.1109/SPAC.2014.6982703
Chao Ma, Jihong Ouyang, J. Guan
In this paper, we hybridize the improved gravitational search algorithm (IGSA) with kernel based extreme learning machine (KELM) method. Based on this, a novel hybrid system IGSA-KELM is proposed to improve the generalization performance for classification problems. In this system, IGSA is designed by combining the search strategy of particle swarm optimization and GSA to effectively reduce the problem of slow convergence rate, moreover, the continuous-value IGSA and binary IGSA are integrated in one algorithm in order to optimize the KELM parameters and feature subset selection simultaneously. This proposed hybrid algorithm is evaluated on several well-known UCI machine learning datasets. The results indicate that the superiority of the proposed model in terms of classification accuracy. Our hybrid method not only can select the most relevant feature subset, but also achieves a high classification accuracy over other similar state-of-the-art classifier systems.
{"title":"Hybrid improved gravitional search algorithm and kernel based extreme learning machine method for classification problems","authors":"Chao Ma, Jihong Ouyang, J. Guan","doi":"10.1109/SPAC.2014.6982703","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982703","url":null,"abstract":"In this paper, we hybridize the improved gravitational search algorithm (IGSA) with kernel based extreme learning machine (KELM) method. Based on this, a novel hybrid system IGSA-KELM is proposed to improve the generalization performance for classification problems. In this system, IGSA is designed by combining the search strategy of particle swarm optimization and GSA to effectively reduce the problem of slow convergence rate, moreover, the continuous-value IGSA and binary IGSA are integrated in one algorithm in order to optimize the KELM parameters and feature subset selection simultaneously. This proposed hybrid algorithm is evaluated on several well-known UCI machine learning datasets. The results indicate that the superiority of the proposed model in terms of classification accuracy. Our hybrid method not only can select the most relevant feature subset, but also achieves a high classification accuracy over other similar state-of-the-art classifier systems.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122661683","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 : 2014-12-15DOI: 10.1109/SPAC.2014.6982668
Wen Liu, Zhijun Song
In this paper, an Internet Public Opinion Monitoring System based on Administration for Industry and Commerce is proposed. The paper first analyzes the design of the system. Then describes the system in detail as five modules, they are Internet Collection Module, Data Preprocessing Module, Public Opinion Analysis Module, Service Module and System Management Module.
{"title":"Design and implementation of an Internet Public Opinion Monitoring System","authors":"Wen Liu, Zhijun Song","doi":"10.1109/SPAC.2014.6982668","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982668","url":null,"abstract":"In this paper, an Internet Public Opinion Monitoring System based on Administration for Industry and Commerce is proposed. The paper first analyzes the design of the system. Then describes the system in detail as five modules, they are Internet Collection Module, Data Preprocessing Module, Public Opinion Analysis Module, Service Module and System Management Module.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"242 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120900211","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 : 2014-12-15DOI: 10.1109/SPAC.2014.6982719
Yubei Lin, Qinyi Chen, Xingming Zhang
The latest video coding standard HEVC (High Efficiency Video Coding) provides up to 35 intra prediction modes to achieve more accurate prediction. However, a larger number of prediction modes leads to higher encoding complexity. To accelerate the intra mode decision in HEVC, an improved algorithm based on numerical analysis of the neighboring reference samples of coding units is proposed. Four filters are designed to reduce the candidate modes. And an algorithm to seek the proper thresholds for the filters is developed. The experimental results show that when compared to the test model HM 12.0 of HEVC, the proposed method can save up to 28.40% of encoder time with slight increase of BD-rate and negligible loss of PSNR. Furthermore, it is easy to combine our approach with other fast algorithms to achieve more improvement.
最新的视频编码标准HEVC (High Efficiency video coding)提供多达35种帧内预测模式，以实现更准确的预测。但是，预测模式的数量越多，编码复杂度也就越高。为了加速HEVC中的模式内决策，提出了一种基于相邻编码单元参考样本数值分析的改进算法。设计了四个滤波器来减少候选模式。并提出了一种寻找滤波器合适阈值的算法。实验结果表明，与HEVC的测试模型HM 12.0相比，该方法可节省28.40%的编码器时间，且bd率略有提高，PSNR的损失可以忽略不计。此外，我们的方法很容易与其他快速算法相结合，以实现更多的改进。
{"title":"Numerical analysis based fast intra prediction algorithm in HEVC","authors":"Yubei Lin, Qinyi Chen, Xingming Zhang","doi":"10.1109/SPAC.2014.6982719","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982719","url":null,"abstract":"The latest video coding standard HEVC (High Efficiency Video Coding) provides up to 35 intra prediction modes to achieve more accurate prediction. However, a larger number of prediction modes leads to higher encoding complexity. To accelerate the intra mode decision in HEVC, an improved algorithm based on numerical analysis of the neighboring reference samples of coding units is proposed. Four filters are designed to reduce the candidate modes. And an algorithm to seek the proper thresholds for the filters is developed. The experimental results show that when compared to the test model HM 12.0 of HEVC, the proposed method can save up to 28.40% of encoder time with slight increase of BD-rate and negligible loss of PSNR. Furthermore, it is easy to combine our approach with other fast algorithms to achieve more improvement.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134461894","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 : 2014-12-15DOI: 10.1109/SPAC.2014.6982665
Qingyang Li, Yu Zhou, Anlong Ming
Action recognition has a long research history, despite several contributed approaches have been introduced, it remains a challenging task in computer vision. In this paper, we present a uniform fusion framework for action recognition, which integrates not only the local depth cues but also the global depth cues. Firstly, the action recognition task is formulated as the maximize the posterior probability, and then the observation for the original action is decomposed into the sub-observations for each individual feature representation strategy of the original action. For the local depth cues, the joints inside the human skeleton is employed to model the local variation of the human motion. In addition, the normal of the depth surface is utilized as the global cue to capture the holistic structure of the human motion. Rather than using the original feature directly, the support vector machine model learning both the discriminative local cue (i.e., the joint) and the discriminative global cue (i.e., the depth surface), respectively. The presented approach is validated on the famous MSR Daily Activity 3D Dataset. And the experimental results demonstrate that our fusion approach can outperform the baseline approaches.
{"title":"Integrating joint and surface for human action recognition in indoor environments","authors":"Qingyang Li, Yu Zhou, Anlong Ming","doi":"10.1109/SPAC.2014.6982665","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982665","url":null,"abstract":"Action recognition has a long research history, despite several contributed approaches have been introduced, it remains a challenging task in computer vision. In this paper, we present a uniform fusion framework for action recognition, which integrates not only the local depth cues but also the global depth cues. Firstly, the action recognition task is formulated as the maximize the posterior probability, and then the observation for the original action is decomposed into the sub-observations for each individual feature representation strategy of the original action. For the local depth cues, the joints inside the human skeleton is employed to model the local variation of the human motion. In addition, the normal of the depth surface is utilized as the global cue to capture the holistic structure of the human motion. Rather than using the original feature directly, the support vector machine model learning both the discriminative local cue (i.e., the joint) and the discriminative global cue (i.e., the depth surface), respectively. The presented approach is validated on the famous MSR Daily Activity 3D Dataset. And the experimental results demonstrate that our fusion approach can outperform the baseline approaches.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130495405","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 : 2014-12-15DOI: 10.1109/SPAC.2014.6982671
Guihua Liao, Jian Zhang
This paper presents an information query system for renting and returning public bicycles based on Android system. The system provides two parts of services: position locating and station query. Position locating is tackled by baidu API entirely, station query includes two sub parts: station marking and information updating. We use the latitude and longitude of the station to mark the station on the map, and query the station around current location. We use the station ID as the open API's parameter to query the station information, then analyze the returned JSON data with station information, and extract the remaining bicycles for renting and remaining seats for returning from the JSON data. At last, we update the station information on the map. This system aims to propose an integrated solution for public bicycle service. Experiments in 3 test cases demonstrate the effect of the proposed system, and indicate that the system can fully meet the requirement for public bicycle service.
{"title":"Information query for public bicycle service based on Andriod","authors":"Guihua Liao, Jian Zhang","doi":"10.1109/SPAC.2014.6982671","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982671","url":null,"abstract":"This paper presents an information query system for renting and returning public bicycles based on Android system. The system provides two parts of services: position locating and station query. Position locating is tackled by baidu API entirely, station query includes two sub parts: station marking and information updating. We use the latitude and longitude of the station to mark the station on the map, and query the station around current location. We use the station ID as the open API's parameter to query the station information, then analyze the returned JSON data with station information, and extract the remaining bicycles for renting and remaining seats for returning from the JSON data. At last, we update the station information on the map. This system aims to propose an integrated solution for public bicycle service. Experiments in 3 test cases demonstrate the effect of the proposed system, and indicate that the system can fully meet the requirement for public bicycle service.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124516458","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 : 2014-12-15DOI: 10.1109/SPAC.2014.6982727
R. Luo, Xuejia Lai, R. You
In this paper, we propose an improved table-based white-box implementation of AES which is able to resist different types of attack, including the BGE attack and De Mulder et al.'s cryptanalysis, to protect information under “white-box attack context”. The notion of white-box attack context, introduced by Chow et al., describes a general setting in which cryptographic algorithms are executed in untrusted environments. In this setting, adversaries have attained complete access to the implementations of cryptographic algorithms as well as the dynamic execution environments. The key strategy applied to our design is to compose different operations of the AES round function and convert the composition into encoded lookup tables. The new scheme exploits larger key-dependent tables, each of which contains two bytes of the round keys. We then analyze the security against different types of attack and measure two security metrics: the “white-box diversity” and “ambiguity”. The new scheme can withstand the BGE attack due to the utilization of larger mixing bijections and tabulated “ShiftRows” it can also resist the cryptanalysis of De Mulder et al. since the bindings between “nTMC” and “TSR” are irreducible and the non-linear encodings are introduced to all tables.
{"title":"A new attempt of white-box AES implementation","authors":"R. Luo, Xuejia Lai, R. You","doi":"10.1109/SPAC.2014.6982727","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982727","url":null,"abstract":"In this paper, we propose an improved table-based white-box implementation of AES which is able to resist different types of attack, including the BGE attack and De Mulder et al.'s cryptanalysis, to protect information under “white-box attack context”. The notion of white-box attack context, introduced by Chow et al., describes a general setting in which cryptographic algorithms are executed in untrusted environments. In this setting, adversaries have attained complete access to the implementations of cryptographic algorithms as well as the dynamic execution environments. The key strategy applied to our design is to compose different operations of the AES round function and convert the composition into encoded lookup tables. The new scheme exploits larger key-dependent tables, each of which contains two bytes of the round keys. We then analyze the security against different types of attack and measure two security metrics: the “white-box diversity” and “ambiguity”. The new scheme can withstand the BGE attack due to the utilization of larger mixing bijections and tabulated “ShiftRows” it can also resist the cryptanalysis of De Mulder et al. since the bindings between “nTMC” and “TSR” are irreducible and the non-linear encodings are introduced to all tables.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124602959","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 : 2014-12-15DOI: 10.1109/SPAC.2014.6982686
Haifeng Zhao, Wenbo Mao, Jiang-tao Wang
Multiple Instance Learning (MIL) has been an interesting topic in the machine learning community. Since proposed, it has been widely used in content-based image retrieval and classification. In the MIL setting, the samples are bags, which are made of instances. In positive bags, at least one instance is positive. Whereas negative bags have all negative instances. This makes it different from the supervised learning. In this paper, we propose an instance selection and optimization method by selecting the most/least positive/negative instances to form a new training set, and learning the optimal distance metric between instances. We evaluate the proposed method on two benchmark datasets, by comparing with representative MIL algorithms. The experimental results suggest the effectiveness of our algorithm.
{"title":"An instance selection and optimization method for multiple instance learning","authors":"Haifeng Zhao, Wenbo Mao, Jiang-tao Wang","doi":"10.1109/SPAC.2014.6982686","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982686","url":null,"abstract":"Multiple Instance Learning (MIL) has been an interesting topic in the machine learning community. Since proposed, it has been widely used in content-based image retrieval and classification. In the MIL setting, the samples are bags, which are made of instances. In positive bags, at least one instance is positive. Whereas negative bags have all negative instances. This makes it different from the supervised learning. In this paper, we propose an instance selection and optimization method by selecting the most/least positive/negative instances to form a new training set, and learning the optimal distance metric between instances. We evaluate the proposed method on two benchmark datasets, by comparing with representative MIL algorithms. The experimental results suggest the effectiveness of our algorithm.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114745193","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 a general solution for the multi-source high resolution real-time monitoring system. Our proposed system is realized on a PCI bus-based real-time image processing board, based on H.264 video compression standards. The main function of the system includes video decompression, image scaling, image stitching, as well as multi-mode real-time display in PC software. Unlike traditional multi-board based multi-source surveillance system, our solution focuses on single board system with synchronously processing and independently display of multi-source video, which is more resource-saving The main contributions of this paper are twofold: firstly, we propose a new logical control method of multi-thread to overcome the limitation of single-board bandwidth, and secondly we give a DirectDraw based display solution to avoid screen flicker caused by different frame rates of multi-source. In addition, we elaborate an approach on multi-thread control and synchronization to reduce CPU utility and monitor abnormal system condition.
{"title":"A general solution for multi-thread based multi-source compressed video surveillance system","authors":"Lu Han, Yixiao Zhao, Shujian Yu, Baojun Zhao, Jiatong Li, Jinghui Wu","doi":"10.1109/SPAC.2014.6982664","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982664","url":null,"abstract":"This paper proposes a general solution for the multi-source high resolution real-time monitoring system. Our proposed system is realized on a PCI bus-based real-time image processing board, based on H.264 video compression standards. The main function of the system includes video decompression, image scaling, image stitching, as well as multi-mode real-time display in PC software. Unlike traditional multi-board based multi-source surveillance system, our solution focuses on single board system with synchronously processing and independently display of multi-source video, which is more resource-saving The main contributions of this paper are twofold: firstly, we propose a new logical control method of multi-thread to overcome the limitation of single-board bandwidth, and secondly we give a DirectDraw based display solution to avoid screen flicker caused by different frame rates of multi-source. In addition, we elaborate an approach on multi-thread control and synchronization to reduce CPU utility and monitor abnormal system condition.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122592607","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 : 2014-12-15DOI: 10.1109/SPAC.2014.6982731
Jia Wang, Zhijun Song, Qian Li, Jun Yu, Fei Chen
In order to overcome the limitation of existing data cleansing methods working on massive data, in this paper, we propose a generic semantic-based framework using parallelized processing model for effective big data cleansing. We also use an improved Semantic-Based Keyword Matching Algorithm to deal with duplicate data. Experimental results show that this parallelized framework with improved Semantic-Based Keyword Matching Algorithm can identify duplicates with high recall and precision and have a good performance for big data cleansing.
{"title":"Semantic-based intelligent data clean framework for big data","authors":"Jia Wang, Zhijun Song, Qian Li, Jun Yu, Fei Chen","doi":"10.1109/SPAC.2014.6982731","DOIUrl":"https://doi.org/10.1109/SPAC.2014.6982731","url":null,"abstract":"In order to overcome the limitation of existing data cleansing methods working on massive data, in this paper, we propose a generic semantic-based framework using parallelized processing model for effective big data cleansing. We also use an improved Semantic-Based Keyword Matching Algorithm to deal with duplicate data. Experimental results show that this parallelized framework with improved Semantic-Based Keyword Matching Algorithm can identify duplicates with high recall and precision and have a good performance for big data cleansing.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117229988","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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