Pub Date : 2010-12-03DOI: 10.1109/ICOSP.2010.5655768
Zhan Xu, Fang Su, Jianwei Wan, Lizhi Cheng
The determination of backscattering coefficients is important to analyze echoes objective signals. To describe a rough sea surface naturally, a non-fully developed full-range sea spectrum (NDFSS) is reconstructed, and a fractal sea model based on NDFSS is presented. Based on the conventional two-scale model for backscattering coefficients, a complementary term is added for considering the skewness of sea waves. The additional part is proportional to the surface bispecctrum and it is a critical part in explaining the scattering difference between upwind and downwind observations. The numerical results show this modified model is consistent with the real radar data.
{"title":"A modified two-scale fractal sea model of the non-fully developed full-range sea spectrum","authors":"Zhan Xu, Fang Su, Jianwei Wan, Lizhi Cheng","doi":"10.1109/ICOSP.2010.5655768","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5655768","url":null,"abstract":"The determination of backscattering coefficients is important to analyze echoes objective signals. To describe a rough sea surface naturally, a non-fully developed full-range sea spectrum (NDFSS) is reconstructed, and a fractal sea model based on NDFSS is presented. Based on the conventional two-scale model for backscattering coefficients, a complementary term is added for considering the skewness of sea waves. The additional part is proportional to the surface bispecctrum and it is a critical part in explaining the scattering difference between upwind and downwind observations. The numerical results show this modified model is consistent with the real radar data.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126312610","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 : 2010-12-03DOI: 10.1109/ICOSP.2010.5656834
Kamal Nasrollahi, T. Moeslund
Reconstruction-based super-resolution algorithms are widely employed for enhancing the quality of low-resolution face images. However, these algorithms are very sensitive to the registration errors of their input images. The registration errors aggravate when working with face images coming from video sequences. The longer the video the bigger is the registration error (due to the motion of the subject). Furthermore, the improvement factor of these algorithms is limited by factors smaller than two. The proposed system in this paper deals with these two problems. In order to restrict the registration errors of the system a fuzzy-based face quality assessment is employed. To cope with the second problem, a hierarchy of different types of super-resolution algorithms is used to reach an improvement factor of four. The proposed system has been tested using real video sequences of different longs and the experimental results are promising.
{"title":"Hallucination of super-resolved face images","authors":"Kamal Nasrollahi, T. Moeslund","doi":"10.1109/ICOSP.2010.5656834","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5656834","url":null,"abstract":"Reconstruction-based super-resolution algorithms are widely employed for enhancing the quality of low-resolution face images. However, these algorithms are very sensitive to the registration errors of their input images. The registration errors aggravate when working with face images coming from video sequences. The longer the video the bigger is the registration error (due to the motion of the subject). Furthermore, the improvement factor of these algorithms is limited by factors smaller than two. The proposed system in this paper deals with these two problems. In order to restrict the registration errors of the system a fuzzy-based face quality assessment is employed. To cope with the second problem, a hierarchy of different types of super-resolution algorithms is used to reach an improvement factor of four. The proposed system has been tested using real video sequences of different longs and the experimental results are promising.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126209685","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 : 2010-12-03DOI: 10.1109/ICOSP.2010.5657034
H. Huang, G. Hu, Li Zhu
This paper proposes a novel and simple method that uses the randomness of random matrix and SVM ensemble learning to discriminate eight types of heartbeats. We use random matrices to generate 15 groups of random features. Then we construct one SVM classifier on each group of random features along with a RR interval. The type of heartbeat is determined using majority voting strategy to combine 15 SVM classifiers. 3062 heartbeats obtained from the MIH-BIH electrocardiogram (ECG) database are used for experiments. The results show that our proposed method has an accuracy of 98.65% and is an effective method for heartbeat classification.
{"title":"Ensemble of support vector machines for heartbeat classification","authors":"H. Huang, G. Hu, Li Zhu","doi":"10.1109/ICOSP.2010.5657034","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5657034","url":null,"abstract":"This paper proposes a novel and simple method that uses the randomness of random matrix and SVM ensemble learning to discriminate eight types of heartbeats. We use random matrices to generate 15 groups of random features. Then we construct one SVM classifier on each group of random features along with a RR interval. The type of heartbeat is determined using majority voting strategy to combine 15 SVM classifiers. 3062 heartbeats obtained from the MIH-BIH electrocardiogram (ECG) database are used for experiments. The results show that our proposed method has an accuracy of 98.65% and is an effective method for heartbeat classification.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126422057","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 : 2010-12-03DOI: 10.1109/ICOSP.2010.5657146
Hou Zhefei, Yang Jie, Jian Xiongjun, Chen De
A novel signal processing algorithm was proposed here for vibration signal analysis in condition monitoring and health diagnosis of rolling bearings. Such technique required an envelope being extracted from vibration signal with a complex analytical band-pass filter which was designed for better efficiency in processing than Morlet wavelet and Harmonic wavelet. The principal periodic component in the envelope was subsequently detected, enhanced and reconstructed with sweep frequency method based on singular value ratio (SVR) spectrum. Such signal processing approach was experimentally evaluated by using vibration signals measured on rolling element bearings that contained localized structural defects with proved validity and efficiency.
{"title":"Bearing defect diagnosis based on a complex filter and singular value ratio spectrum","authors":"Hou Zhefei, Yang Jie, Jian Xiongjun, Chen De","doi":"10.1109/ICOSP.2010.5657146","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5657146","url":null,"abstract":"A novel signal processing algorithm was proposed here for vibration signal analysis in condition monitoring and health diagnosis of rolling bearings. Such technique required an envelope being extracted from vibration signal with a complex analytical band-pass filter which was designed for better efficiency in processing than Morlet wavelet and Harmonic wavelet. The principal periodic component in the envelope was subsequently detected, enhanced and reconstructed with sweep frequency method based on singular value ratio (SVR) spectrum. Such signal processing approach was experimentally evaluated by using vibration signals measured on rolling element bearings that contained localized structural defects with proved validity and efficiency.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126532683","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 : 2010-12-03DOI: 10.1109/ICOSP.2010.5657124
Xia Chen, Hongwen Yang, W. Hu
The multipath propagation and low measurement precision in sky-wave Over-the-horizon Radar (OTHR) pose new challenges to data association. Aiming at the formation of ships, this paper presents a new method of data association. Firstly the plane measurement model is established, and the transformation between radar and ground coordinates is deduced according to the given ionospheres state, which leads to different propagation modes. Then measurements observed from radar are transformed to ground coordinates considering all possible propagation modes, and the transformed points in ground coordinates for each measurement are called hypothetic points. Max-min distance clustering method is adopted to divide these hypothetic points into multi-classes. The feasible classes are selected using the restriction of propagation modes, and the geometry center of clustering can be calculated by averaging the points of feasible class. Finally, the nearest neighbor method is used to associate the geometry centers of clustering among different scans and further find the correlation of measurements, propagation modes and targets. Simulation results indicate that the proposed algorithm can associate the tracks in the formation of ships effectively, and the influence of radar detection probability on the algorithm is also analyzed.
{"title":"Track clustering based data association for sky-wave Over-the-horizon Radar","authors":"Xia Chen, Hongwen Yang, W. Hu","doi":"10.1109/ICOSP.2010.5657124","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5657124","url":null,"abstract":"The multipath propagation and low measurement precision in sky-wave Over-the-horizon Radar (OTHR) pose new challenges to data association. Aiming at the formation of ships, this paper presents a new method of data association. Firstly the plane measurement model is established, and the transformation between radar and ground coordinates is deduced according to the given ionospheres state, which leads to different propagation modes. Then measurements observed from radar are transformed to ground coordinates considering all possible propagation modes, and the transformed points in ground coordinates for each measurement are called hypothetic points. Max-min distance clustering method is adopted to divide these hypothetic points into multi-classes. The feasible classes are selected using the restriction of propagation modes, and the geometry center of clustering can be calculated by averaging the points of feasible class. Finally, the nearest neighbor method is used to associate the geometry centers of clustering among different scans and further find the correlation of measurements, propagation modes and targets. Simulation results indicate that the proposed algorithm can associate the tracks in the formation of ships effectively, and the influence of radar detection probability on the algorithm is also analyzed.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126018686","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 : 2010-12-03DOI: 10.1109/ICOSP.2010.5656857
S. Yin
A new method is proposed for designing of two-channel filter banks (FBs) with causal-stable IIR filters having an approximate cosine-rolloff (CR) transition band. By using IIR filters with a CR transition band, the flatness condition required for two-channel NPR FB is automatically satisfied. The design problem of IIR FBs is reduced to the design of FIR fliers if we can propose locating the poles of IIR filters. Then the design problem can be formulated as a convex minimax optimization problem, and solved by second order core programming (SOCP). Moreover, tie polyphase components of tie analysis Alters are assumed to have an identical denominator in order to simplify the PR condition. The two-channel NPR IIR FB so obtained has a reasonably low reconstruction error and it can be employed as the initial guess to constrained nonlinear optimization software for designing the PR IIR FB.
{"title":"New method for designing of two-channel causal-stable IIR filter banks","authors":"S. Yin","doi":"10.1109/ICOSP.2010.5656857","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5656857","url":null,"abstract":"A new method is proposed for designing of two-channel filter banks (FBs) with causal-stable IIR filters having an approximate cosine-rolloff (CR) transition band. By using IIR filters with a CR transition band, the flatness condition required for two-channel NPR FB is automatically satisfied. The design problem of IIR FBs is reduced to the design of FIR fliers if we can propose locating the poles of IIR filters. Then the design problem can be formulated as a convex minimax optimization problem, and solved by second order core programming (SOCP). Moreover, tie polyphase components of tie analysis Alters are assumed to have an identical denominator in order to simplify the PR condition. The two-channel NPR IIR FB so obtained has a reasonably low reconstruction error and it can be employed as the initial guess to constrained nonlinear optimization software for designing the PR IIR FB.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121620513","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 : 2010-12-03DOI: 10.1109/ICOSP.2010.5656657
Marzieh Amini, H. Sadreazami
Binary images have only two distinct pixel color values so the capability of data hiding is very limited. To improve the robustness of watermarking algorithm, we proposed a novel ridgelet based watermarking for binary images. Ridgelet transform is efficient for representing images with line singularities. So, binary host image is partitioned into several non-overlapping blocks to make edges in each block similar to straight edges. Ridgelet transform is applied to each single block. To embed the watermark bits, directions with highest variance are selected in ridgelet coefficients matrix. To extract the watermark logo, detector response is computed for several sample watermarks and the maximum value is chosen as the extracted watermark. The proposed method has great robustness against different kinds of attacks.
{"title":"Binary image watermarking in ridgelet domain","authors":"Marzieh Amini, H. Sadreazami","doi":"10.1109/ICOSP.2010.5656657","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5656657","url":null,"abstract":"Binary images have only two distinct pixel color values so the capability of data hiding is very limited. To improve the robustness of watermarking algorithm, we proposed a novel ridgelet based watermarking for binary images. Ridgelet transform is efficient for representing images with line singularities. So, binary host image is partitioned into several non-overlapping blocks to make edges in each block similar to straight edges. Ridgelet transform is applied to each single block. To embed the watermark bits, directions with highest variance are selected in ridgelet coefficients matrix. To extract the watermark logo, detector response is computed for several sample watermarks and the maximum value is chosen as the extracted watermark. The proposed method has great robustness against different kinds of attacks.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115877783","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 : 2010-12-03DOI: 10.1109/ICOSP.2010.5656115
Zhixing Liu, Shaohai Hu, Yang Xiao, Guangzhi Qu, Kiseon Kim
This paper reveals that the classical R-D imaging algorithm can not remove the strong noise and extract the objects in R-D imaging image by their range and azimuth matching filters. Though 2-D DCT-DWT or 2-D DFT-DWT can be a 2-D filtering for the issue, while the algorithms need huge computation amount, they can not process SAR image real time. To solve the problem, this paper develops a new 2-D filtering algorithm based on 2-D leapfrog filter, which is good at extracting the SAR image target clearly. The 2-D recursive filter is of few multiplications for SAR image each pixel to realize fast and real-time image filtering. Practical experiments of SAR image processing have shown that the approach and algorithm are correct, effective and pragmatical.
{"title":"SAR image target extraction based on 2-D leapfrog filtering","authors":"Zhixing Liu, Shaohai Hu, Yang Xiao, Guangzhi Qu, Kiseon Kim","doi":"10.1109/ICOSP.2010.5656115","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5656115","url":null,"abstract":"This paper reveals that the classical R-D imaging algorithm can not remove the strong noise and extract the objects in R-D imaging image by their range and azimuth matching filters. Though 2-D DCT-DWT or 2-D DFT-DWT can be a 2-D filtering for the issue, while the algorithms need huge computation amount, they can not process SAR image real time. To solve the problem, this paper develops a new 2-D filtering algorithm based on 2-D leapfrog filter, which is good at extracting the SAR image target clearly. The 2-D recursive filter is of few multiplications for SAR image each pixel to realize fast and real-time image filtering. Practical experiments of SAR image processing have shown that the approach and algorithm are correct, effective and pragmatical.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"51 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115978054","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 : 2010-12-03DOI: 10.1109/ICOSP.2010.5656856
Wei Yan, Wen Yang, Y. Liu, Hong Sun
In this paper, we propose a new method for unsupervised classification of polarimetric synthetic aperture radar interferometry (PolInSAR) images based on Shannon Entropy Characterization. Firstly, we use polarimetric H (entropy) and a parameters to classify the image initially. Then, we reclassify the image according to the span of Shannon Entropy Characterization. Finally, we fuse the results of the two previous steps and merge them to the specified number of clusters. The effectiveness of this method is demonstrated on CETC38 PolInSAR data and E-SAR PolInSAR data.
{"title":"Unsupervised classification of PolInSAR image based on Shannon Entropy Characterization","authors":"Wei Yan, Wen Yang, Y. Liu, Hong Sun","doi":"10.1109/ICOSP.2010.5656856","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5656856","url":null,"abstract":"In this paper, we propose a new method for unsupervised classification of polarimetric synthetic aperture radar interferometry (PolInSAR) images based on Shannon Entropy Characterization. Firstly, we use polarimetric H (entropy) and a parameters to classify the image initially. Then, we reclassify the image according to the span of Shannon Entropy Characterization. Finally, we fuse the results of the two previous steps and merge them to the specified number of clusters. The effectiveness of this method is demonstrated on CETC38 PolInSAR data and E-SAR PolInSAR data.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132234248","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 : 2010-12-03DOI: 10.1109/ICOSP.2010.5656814
M. Tayel, Abdelmonem Mohsen
Many image processing techniques developed over the past two decades to help radiologists in diagnosing breast cancer. At the same time, many studies proven that an early diagnosis of breast cancer can increase five year survival rate from 60% to 80+% [1]. That made screening programs a mandatory step for females. Therefore, radiologists have to examine a large number of images, which may lead to missed breast lesions at early stage due to work load. Computer-Aided-Diagnosis (CAD) systems can be a powerful tool to overcome this problem by highlighting suspected lesions. However, this task is challenging also from CAD systems point of view due to difficulties in articulating and modeling patterns of abnormalities in a computational way as many pre-porcessing steps need to be done to identify region of interest before pattern recognition algorithms can be applied. In this paper a new proposed thresholding algorithm is introduced for breast boundaries and pectoral muscle determination in Mammograms using statistical properties.
{"title":"Breast boarder boundaries extraction using statistical properties of Mammogram","authors":"M. Tayel, Abdelmonem Mohsen","doi":"10.1109/ICOSP.2010.5656814","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5656814","url":null,"abstract":"Many image processing techniques developed over the past two decades to help radiologists in diagnosing breast cancer. At the same time, many studies proven that an early diagnosis of breast cancer can increase five year survival rate from 60% to 80+% [1]. That made screening programs a mandatory step for females. Therefore, radiologists have to examine a large number of images, which may lead to missed breast lesions at early stage due to work load. Computer-Aided-Diagnosis (CAD) systems can be a powerful tool to overcome this problem by highlighting suspected lesions. However, this task is challenging also from CAD systems point of view due to difficulties in articulating and modeling patterns of abnormalities in a computational way as many pre-porcessing steps need to be done to identify region of interest before pattern recognition algorithms can be applied. In this paper a new proposed thresholding algorithm is introduced for breast boundaries and pectoral muscle determination in Mammograms using statistical properties.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130147397","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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