Pub Date : 2014-12-08DOI: 10.1109/ICNC.2014.6975976
Huanhuan He, Xingwei Wang, Min Huang
Spectrum shortage and low spectrum utilization have attracted much attention. In order to meet the communication demands of users, the dynamic and efficient spectrum management scheme with cognitive radio technology has been used. Spectrum share is the key component in the dynamic spectrum management. To enable cognitive user (CU) to share spectrum fairly, an evolutionary game-based spectrum sharing scheme is designed based on the results of spectrum sensing. The knowledge of fuzzy mathematic is introduced to characterize the parameters related to cognitive user satisfaction degree (CUSD). Gas Brownian motion optimization (GBMO) is used to solve the problem of spectrum access cost of CU, the fairness of spectrum sharing is considered in utility function, the dynamic equilibrium is solved according to replicator dynamic equation (RDE), finally, the detailed implementation steps of the scheme are given. Simulation results have shown that the proposed scheme is both feasible and effective.
{"title":"An evolutionary game-based spectrum sharing scheme","authors":"Huanhuan He, Xingwei Wang, Min Huang","doi":"10.1109/ICNC.2014.6975976","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975976","url":null,"abstract":"Spectrum shortage and low spectrum utilization have attracted much attention. In order to meet the communication demands of users, the dynamic and efficient spectrum management scheme with cognitive radio technology has been used. Spectrum share is the key component in the dynamic spectrum management. To enable cognitive user (CU) to share spectrum fairly, an evolutionary game-based spectrum sharing scheme is designed based on the results of spectrum sensing. The knowledge of fuzzy mathematic is introduced to characterize the parameters related to cognitive user satisfaction degree (CUSD). Gas Brownian motion optimization (GBMO) is used to solve the problem of spectrum access cost of CU, the fairness of spectrum sharing is considered in utility function, the dynamic equilibrium is solved according to replicator dynamic equation (RDE), finally, the detailed implementation steps of the scheme are given. Simulation results have shown that the proposed scheme is both feasible and effective.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129073535","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975963
Chengyun Liu, Zhenxue Chen, F. Chang, Kaifang Wang
Face recognition is one of typical biometric identification method, which has a great prospect in secure authentication system, file management, human-computer interaction and social security. This paper proposes gray-scale characteristics and creates facial templates to recognize faces method based on a given number of samples. Firstly, it selects the method of building template according to the number of samples to create the facial template image; then, it will compare the difference of first-order edge entropy between recognition image and the template image and find the best match result; finally, the recognition result is output. Experimental results show that the proposed algorithm has good recognition effect on face recognition under non-constraint conditions.
{"title":"Face recognition algorithm based on improved facial model","authors":"Chengyun Liu, Zhenxue Chen, F. Chang, Kaifang Wang","doi":"10.1109/ICNC.2014.6975963","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975963","url":null,"abstract":"Face recognition is one of typical biometric identification method, which has a great prospect in secure authentication system, file management, human-computer interaction and social security. This paper proposes gray-scale characteristics and creates facial templates to recognize faces method based on a given number of samples. Firstly, it selects the method of building template according to the number of samples to create the facial template image; then, it will compare the difference of first-order edge entropy between recognition image and the template image and find the best match result; finally, the recognition result is output. Experimental results show that the proposed algorithm has good recognition effect on face recognition under non-constraint conditions.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127645891","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975832
C. Fatichah, Abdullah M. Iliyasu, K. Abuhasel, N. Suciati, Mohammed A. Al-Qodah
A hybrid principal component analysis (PCA)-based neural network with fuzzy membership function (NEWFM) is proposed for epileptic seizure detection. By combining PCA and NEWFM, the proposed method improves the accuracy in epileptic seizure detection. The PCA is used for wavelet feature enhancement needed to eliminate the sensitivity of noise, electrode artifacts, or redundancy. NEWFM, a model of neural networks, is integrated to improve prediction results by updating weights of fuzzy membership functions. A dataset made up of 5 sets, each consisting 100 single EEGs segments, is employed to evaluate the proposed system's performance. Based on the experiments, the prediction results show an accuracy rate of 98.29% for epileptic seizure classification while in the best cases the accuracy reaches 99.5% for the `normal' (Z-S) seizure classification task.
{"title":"Principal component analysis-based neural network with fuzzy membership function for epileptic seizure detection","authors":"C. Fatichah, Abdullah M. Iliyasu, K. Abuhasel, N. Suciati, Mohammed A. Al-Qodah","doi":"10.1109/ICNC.2014.6975832","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975832","url":null,"abstract":"A hybrid principal component analysis (PCA)-based neural network with fuzzy membership function (NEWFM) is proposed for epileptic seizure detection. By combining PCA and NEWFM, the proposed method improves the accuracy in epileptic seizure detection. The PCA is used for wavelet feature enhancement needed to eliminate the sensitivity of noise, electrode artifacts, or redundancy. NEWFM, a model of neural networks, is integrated to improve prediction results by updating weights of fuzzy membership functions. A dataset made up of 5 sets, each consisting 100 single EEGs segments, is employed to evaluate the proposed system's performance. Based on the experiments, the prediction results show an accuracy rate of 98.29% for epileptic seizure classification while in the best cases the accuracy reaches 99.5% for the `normal' (Z-S) seizure classification task.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129058963","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6976001
Xiaoji Fu, Weihong Liao, X. Guo, Yunzhong Jiang, Mengtai Liu
A water balance model A water balance model is developed for arid regions in this study. The partition calibration strategy is also proposed for calibrating model parameters such as river loss coefficients and irrigation return water coefficients by adopting the method of the modified dynamically dimensioned search algorithm (MDDS). The conditional probability and Bayesian statistics are employed to demonstrate the theoretical rationality of partition calibration strategy. The case study in the Kaidu River Basin of Xinjiang Uyghur Autonomous Region has verified it in its application. According to the model results of Yanqi and Baolangsumu hydrological stations, the partition calibration strategy is superior to the whole regional calibration in terms of parameters number, computing time and Nash efficient coefficients. Therefore, the partition calibration strategy is suggested to be applied to these areas with the obvious advantages of sub-partition computing units and parameter distribution.
{"title":"Study on parameter calibration strategy for water balance model in arid areas","authors":"Xiaoji Fu, Weihong Liao, X. Guo, Yunzhong Jiang, Mengtai Liu","doi":"10.1109/ICNC.2014.6976001","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6976001","url":null,"abstract":"A water balance model A water balance model is developed for arid regions in this study. The partition calibration strategy is also proposed for calibrating model parameters such as river loss coefficients and irrigation return water coefficients by adopting the method of the modified dynamically dimensioned search algorithm (MDDS). The conditional probability and Bayesian statistics are employed to demonstrate the theoretical rationality of partition calibration strategy. The case study in the Kaidu River Basin of Xinjiang Uyghur Autonomous Region has verified it in its application. According to the model results of Yanqi and Baolangsumu hydrological stations, the partition calibration strategy is superior to the whole regional calibration in terms of parameters number, computing time and Nash efficient coefficients. Therefore, the partition calibration strategy is suggested to be applied to these areas with the obvious advantages of sub-partition computing units and parameter distribution.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127554709","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975921
Rong Jing-Shi, Pan Hai-Wei, Gao Lin-lin, Han Qi-long, Feng Xiao-Ning
CT imaging shows that it is approximately symmetrical about the perpendicular bisector. Based on this medical knowledge guidance, symmetry theory based classification algorithm in CT image database is presented in this paper. First of all, the definitions of the weak symmetry and strong symmetry were given. Then, the weak symmetry was applied to the first stage classification of the CT images. Secondly, we proposed the combination of weak symmetry and strong symmetry for the second stage classification. Finally, according to the tumor edge profile, tumors are divided into benign and malignant lesions by extracting some features of the tumor in the third stage classification. In this paper, sample size requirements of SVM (Support Vector Machine) classifier were selected to classify the CT images. Experimental results show that symmetry theory based classification algorithm in CT image database can increase the accuracy of the classification and reduce the time of the doctor's diagnosis.
{"title":"Symmetry theory based classification algorithm in CT image database","authors":"Rong Jing-Shi, Pan Hai-Wei, Gao Lin-lin, Han Qi-long, Feng Xiao-Ning","doi":"10.1109/ICNC.2014.6975921","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975921","url":null,"abstract":"CT imaging shows that it is approximately symmetrical about the perpendicular bisector. Based on this medical knowledge guidance, symmetry theory based classification algorithm in CT image database is presented in this paper. First of all, the definitions of the weak symmetry and strong symmetry were given. Then, the weak symmetry was applied to the first stage classification of the CT images. Secondly, we proposed the combination of weak symmetry and strong symmetry for the second stage classification. Finally, according to the tumor edge profile, tumors are divided into benign and malignant lesions by extracting some features of the tumor in the third stage classification. In this paper, sample size requirements of SVM (Support Vector Machine) classifier were selected to classify the CT images. Experimental results show that symmetry theory based classification algorithm in CT image database can increase the accuracy of the classification and reduce the time of the doctor's diagnosis.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"255 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121341255","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975989
A. Alkandari, I. A. Shaikhli, Ali Alhaddad
Traffic congestion is one of the most prevalent problems on the streets in urban areas, especially at intersections that are not properly controlled, so it causes problems in the flow of traffic and the disruption of the streets. Many new solutions has been proposed Which have been used intelligently and more dynamically than previous solutions. This paper proposes an intelligent control system, which uses a traffic light method called Dynamic Webster with Dynamic Cycle Time, which runs by software simulation of four-phase of the intersection. Emphasis was placed on the cycle time interval and the flow rate when compared (Dynamic Webster with Dynamic Cycle Time) with the rest of the previous methods. This paper concludes with what has been deduced and what can be improved in these methods.
{"title":"Optimization of traffic control methods comparing with dynamic webster with Dynamic Cycle Time (DWDC) using simulation software","authors":"A. Alkandari, I. A. Shaikhli, Ali Alhaddad","doi":"10.1109/ICNC.2014.6975989","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975989","url":null,"abstract":"Traffic congestion is one of the most prevalent problems on the streets in urban areas, especially at intersections that are not properly controlled, so it causes problems in the flow of traffic and the disruption of the streets. Many new solutions has been proposed Which have been used intelligently and more dynamically than previous solutions. This paper proposes an intelligent control system, which uses a traffic light method called Dynamic Webster with Dynamic Cycle Time, which runs by software simulation of four-phase of the intersection. Emphasis was placed on the cycle time interval and the flow rate when compared (Dynamic Webster with Dynamic Cycle Time) with the rest of the previous methods. This paper concludes with what has been deduced and what can be improved in these methods.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123110335","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975907
Yangyang Jia, Jianqun Wang, Qingyuan Xiao
In this paper, the particle swarm optimization algorithm (PSO) for reservoir optimal operation is studied. A new algorithm which is suitable for reservoir optimal operation called multiple groups of gradient particle swarm optimization algorithm (MGPSO) is proposed to avoid the shortcomings of PSO including premature convergence, poor search accuracy and easily falling into local optimal solution. The gradient searching strategy is introduced to improve the search accuracy of local optima. Grouping and randomly updating strategy are used to improve the searching ability of global optima. Simulation experiments and the example of reservoir optimal operation show that the new algorithm MGPSO obviously outperforms the standard PSO and shuffled frog leaping particle swarm optimization (SFLPSO), and is effective in solving the optimal operation of hydropower station reservoir.
{"title":"Multiple groups of gradient particle swarm optimization and its application in optimal operation of reservoir","authors":"Yangyang Jia, Jianqun Wang, Qingyuan Xiao","doi":"10.1109/ICNC.2014.6975907","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975907","url":null,"abstract":"In this paper, the particle swarm optimization algorithm (PSO) for reservoir optimal operation is studied. A new algorithm which is suitable for reservoir optimal operation called multiple groups of gradient particle swarm optimization algorithm (MGPSO) is proposed to avoid the shortcomings of PSO including premature convergence, poor search accuracy and easily falling into local optimal solution. The gradient searching strategy is introduced to improve the search accuracy of local optima. Grouping and randomly updating strategy are used to improve the searching ability of global optima. Simulation experiments and the example of reservoir optimal operation show that the new algorithm MGPSO obviously outperforms the standard PSO and shuffled frog leaping particle swarm optimization (SFLPSO), and is effective in solving the optimal operation of hydropower station reservoir.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115982619","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6976004
Wei-Kuo Tseng
This paper presents the simple and logical algorithms of piecewise rhumb-lines. Using the formulae of rhumb-line sailing and mathematical optimization may calculate the minimum overall distance for piecewise rhumb-lines. By constructing the piecewise rhumb-lines sailing, readers can quickly comprehend and grasp the meanings of equations. In the numerical test section, one specific example of one turning point is selected here which its results points out that the turning point with shortest overall distance is not the intersection of the great circle and the rhumb-line with initial course equal to the course of middle latitude along the great circle. The conclusion provided by this work is against the statement provided by Petrović (2014).
{"title":"The shortest overall distance of two piecewise rhumb-lines","authors":"Wei-Kuo Tseng","doi":"10.1109/ICNC.2014.6976004","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6976004","url":null,"abstract":"This paper presents the simple and logical algorithms of piecewise rhumb-lines. Using the formulae of rhumb-line sailing and mathematical optimization may calculate the minimum overall distance for piecewise rhumb-lines. By constructing the piecewise rhumb-lines sailing, readers can quickly comprehend and grasp the meanings of equations. In the numerical test section, one specific example of one turning point is selected here which its results points out that the turning point with shortest overall distance is not the intersection of the great circle and the rhumb-line with initial course equal to the course of middle latitude along the great circle. The conclusion provided by this work is against the statement provided by Petrović (2014).","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131404806","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975931
Xiao-yun Chen, Cairen Jian
An accurate tumor classification is important to diagnosis and treatment cancers. The conventional methods for tumor classification include training and testing phases, which may cause over fitting. Although this problem can be avoided by using sparse representation classification, the existing sparse representation methods for tumor classification are inefficient. In this paper, an efficient and robust classification model LSRC based on least square regression and nearest subspace rule is adopted for tumor classification. To investigate its performance, our proposed model LSRC is compared with 3 existing methods on 9 tumor datasets. The experimental results show that our proposed model can use less time to achieve higher classification accuracy.
{"title":"A tumor classification model using least square regression","authors":"Xiao-yun Chen, Cairen Jian","doi":"10.1109/ICNC.2014.6975931","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975931","url":null,"abstract":"An accurate tumor classification is important to diagnosis and treatment cancers. The conventional methods for tumor classification include training and testing phases, which may cause over fitting. Although this problem can be avoided by using sparse representation classification, the existing sparse representation methods for tumor classification are inefficient. In this paper, an efficient and robust classification model LSRC based on least square regression and nearest subspace rule is adopted for tumor classification. To investigate its performance, our proposed model LSRC is compared with 3 existing methods on 9 tumor datasets. The experimental results show that our proposed model can use less time to achieve higher classification accuracy.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116097162","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 : 2014-12-08DOI: 10.1109/ICNC.2014.6975925
Victor Y. Chen, Liquan Zhang, Jia Wang
The purpose of this paper is to analyze passengers' moving direction through the video shot in the entrances and exits of the subway stations. The results of the analysis will be helpful to relevant departments to manage the traffic condition, making a decision in the face of emergency. First of all, this paper adopts Haar features and Adaboost algorithm to implement the detection of human's head through OpenCV; Secondly, this paper uses color histogram in the head recognition and an improved algorithm that adds the step of comparing the pixel value of the location coordinates in consecutive frames is proposed; At last, the paper realizes the human tracking through the establishment of target tracking chain and puts forward to analyze passengers' moving direction through space coordinate information.
{"title":"Passenger detection for subway transportation based on video","authors":"Victor Y. Chen, Liquan Zhang, Jia Wang","doi":"10.1109/ICNC.2014.6975925","DOIUrl":"https://doi.org/10.1109/ICNC.2014.6975925","url":null,"abstract":"The purpose of this paper is to analyze passengers' moving direction through the video shot in the entrances and exits of the subway stations. The results of the analysis will be helpful to relevant departments to manage the traffic condition, making a decision in the face of emergency. First of all, this paper adopts Haar features and Adaboost algorithm to implement the detection of human's head through OpenCV; Secondly, this paper uses color histogram in the head recognition and an improved algorithm that adds the step of comparing the pixel value of the location coordinates in consecutive frames is proposed; At last, the paper realizes the human tracking through the establishment of target tracking chain and puts forward to analyze passengers' moving direction through space coordinate information.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124829037","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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