Pub Date : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599323
Yang Liu, D. Hou, Pingjie Huang, Guangxin Zhang
With the help of statistical technology and artificial intelligence algorithms, online water quality monitoring and detecting have significant importance to national water security. This paper proposed amulti-scale and multivariate water quality event detection approach for detecting accidental or intentional water contamination events. The approach is based on the ensemble empirical mode decomposition (EEMD), which is a novel algorithm for the analysis of nonstationary and nonlinear data of the type used in this paper. With EEMD as a dyadic filter bank, original water quality time series are decomposed into a sequence of intrinsic mode functions (IMFs). The local time scale is an important feature for statistical analysis and multi-scale representation. In this paper, the fluctuation characteristic for newly available measurements is estimated dynamically, and the corresponding membership degree to the constructed time scale reference which depends on offline long-term normal data analysis is calculated with Gaussian fuzzy logic. Taking the various membership as weight values, the anomalous signal can be enhanced and sifted out by the selection and reconstruction of sensitive time scales. Compared with traditional water quality detection methods with receiver operating characteristic (ROC) curves, the proposed multi-scale method can improve the detection accuracy and reduce the false rate.
{"title":"Multiscale water quality contamination events detection based on sensitive time scales reconstruction","authors":"Yang Liu, D. Hou, Pingjie Huang, Guangxin Zhang","doi":"10.1109/ICWAPR.2013.6599323","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599323","url":null,"abstract":"With the help of statistical technology and artificial intelligence algorithms, online water quality monitoring and detecting have significant importance to national water security. This paper proposed amulti-scale and multivariate water quality event detection approach for detecting accidental or intentional water contamination events. The approach is based on the ensemble empirical mode decomposition (EEMD), which is a novel algorithm for the analysis of nonstationary and nonlinear data of the type used in this paper. With EEMD as a dyadic filter bank, original water quality time series are decomposed into a sequence of intrinsic mode functions (IMFs). The local time scale is an important feature for statistical analysis and multi-scale representation. In this paper, the fluctuation characteristic for newly available measurements is estimated dynamically, and the corresponding membership degree to the constructed time scale reference which depends on offline long-term normal data analysis is calculated with Gaussian fuzzy logic. Taking the various membership as weight values, the anomalous signal can be enhanced and sifted out by the selection and reconstruction of sensitive time scales. Compared with traditional water quality detection methods with receiver operating characteristic (ROC) curves, the proposed multi-scale method can improve the detection accuracy and reduce the false rate.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127712326","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 : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599297
Kai Zhou
The research of the human animation based on motion capture is very important in the research field of computer graphics and has been widely used in a lot of applications. The animation compressing is a desiderated problem among many human animation technologies. The present paper gives a method for animation compressing. First, model and represent the motion with representative data; second, compress the motion data using the clustering method and PCA method. Using the clustering method, similar motion clips are clustered into one cluster. The virtual human then could retrieve the motion clips based on the input of the client, after that, we will decompress the motion chips, and rebuild the skinning animation to realize the render of human animation in an effective manner.
{"title":"An effective method for human animation compression","authors":"Kai Zhou","doi":"10.1109/ICWAPR.2013.6599297","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599297","url":null,"abstract":"The research of the human animation based on motion capture is very important in the research field of computer graphics and has been widely used in a lot of applications. The animation compressing is a desiderated problem among many human animation technologies. The present paper gives a method for animation compressing. First, model and represent the motion with representative data; second, compress the motion data using the clustering method and PCA method. Using the clustering method, similar motion clips are clustered into one cluster. The virtual human then could retrieve the motion clips based on the input of the client, after that, we will decompress the motion chips, and rebuild the skinning animation to realize the render of human animation in an effective manner.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134154943","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 : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599315
Jian-Feng Zhu, Yong-dong Huang
In this paper, we construct a threshold function on the existing wavelet threshold functions. Compared with the traditional hard threshold, soft threshold, semi-soft threshold and some improved threshold functions, the proposed threshold function has the advantages of easy to calculate and mathematical properties. At the same time, the proposed threshold function also can overcome the drawbacks of hard threshold with discontinuous function and soft threshold function and other threshold functions with constant deviation in de-noising processing. By the Blocks, Bumps, HeaviSines and Doppler signal simulation experiment, the experimental results show that the proposed threshold function can remove the noise and suppress pseudo-Gibbs phenomena effectively. In visual effect, signal-to-noise ratio and mean square error (MSE) measure, the proposed threshold function is superior to the traditional threshold functions and has certain practical value.
{"title":"Improved threshold function of wavalet domain signal de-noising","authors":"Jian-Feng Zhu, Yong-dong Huang","doi":"10.1109/ICWAPR.2013.6599315","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599315","url":null,"abstract":"In this paper, we construct a threshold function on the existing wavelet threshold functions. Compared with the traditional hard threshold, soft threshold, semi-soft threshold and some improved threshold functions, the proposed threshold function has the advantages of easy to calculate and mathematical properties. At the same time, the proposed threshold function also can overcome the drawbacks of hard threshold with discontinuous function and soft threshold function and other threshold functions with constant deviation in de-noising processing. By the Blocks, Bumps, HeaviSines and Doppler signal simulation experiment, the experimental results show that the proposed threshold function can remove the noise and suppress pseudo-Gibbs phenomena effectively. In visual effect, signal-to-noise ratio and mean square error (MSE) measure, the proposed threshold function is superior to the traditional threshold functions and has certain practical value.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122047970","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 : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599320
Xiao-Wei Liu, Jinquan Xiong, Zhihua Xie
For single sample face recognition, the approaches based on statistical learning are always suffering from the generalizability problem because of small samples. This paper proposes a novel non-statistics features extraction approach based on fusion of global and local features. The global and low frequency features are obtained by low frequency coefficients of discrete cosine transform (DCT). The local and high frequency features are extracted by LGBPH. To integrate the global and local features, the final recognition can be achieved by parallel integration of classification results of the global and local features. The membership degree is defined to integrate local classifier and global classifier. The experimental results on ORL face databases show that the global face and local information can be integrated well after membership degree fusion by global and local features, and this improves the performance of single sample face recognition. Meanwhile, the proposed single sample face recognition method outperforms the methods based on DCT+LDA, LGBPH or traditional fusion.
{"title":"Membership degree fusion of DCT and LGBPH based face recognition approach for single sample problem","authors":"Xiao-Wei Liu, Jinquan Xiong, Zhihua Xie","doi":"10.1109/ICWAPR.2013.6599320","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599320","url":null,"abstract":"For single sample face recognition, the approaches based on statistical learning are always suffering from the generalizability problem because of small samples. This paper proposes a novel non-statistics features extraction approach based on fusion of global and local features. The global and low frequency features are obtained by low frequency coefficients of discrete cosine transform (DCT). The local and high frequency features are extracted by LGBPH. To integrate the global and local features, the final recognition can be achieved by parallel integration of classification results of the global and local features. The membership degree is defined to integrate local classifier and global classifier. The experimental results on ORL face databases show that the global face and local information can be integrated well after membership degree fusion by global and local features, and this improves the performance of single sample face recognition. Meanwhile, the proposed single sample face recognition method outperforms the methods based on DCT+LDA, LGBPH or traditional fusion.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127822215","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 : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599289
Hua Li, Genlong Wang, Min Gao
Collaborative filtering, one of the most successful technologies for automated product recommendation, is widely used in electronic commerce. One notable task in practical systems is to compute the similarities between users (items) which can be represented with rating vectors. There has been a variety of similarity methods according to distance and vector-based similarity computing. However, those methods, such as the Pearson correlation method and Cosine similarity method, have never been questioned about the rationality behind those original results. In this paper, we propose a new concept named fluctuation factor which refers to the count of the common rated items between two rating vectors. In addition, one feasible way is presented to remove the influence of different fluctuation factors by z-score method. Finally, 4 kinds of similarity measurements, in both user-based and item-based collaborative filtering algorithm, are combined with the concept to check the effect. After the comparison of the experiment, results demonstrate that those methods can lead to a better recommendation quality when the influence of different fluctuation factors is removed.
{"title":"A novel similarity calculation for collaborative filtering","authors":"Hua Li, Genlong Wang, Min Gao","doi":"10.1109/ICWAPR.2013.6599289","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599289","url":null,"abstract":"Collaborative filtering, one of the most successful technologies for automated product recommendation, is widely used in electronic commerce. One notable task in practical systems is to compute the similarities between users (items) which can be represented with rating vectors. There has been a variety of similarity methods according to distance and vector-based similarity computing. However, those methods, such as the Pearson correlation method and Cosine similarity method, have never been questioned about the rationality behind those original results. In this paper, we propose a new concept named fluctuation factor which refers to the count of the common rated items between two rating vectors. In addition, one feasible way is presented to remove the influence of different fluctuation factors by z-score method. Finally, 4 kinds of similarity measurements, in both user-based and item-based collaborative filtering algorithm, are combined with the concept to check the effect. After the comparison of the experiment, results demonstrate that those methods can lead to a better recommendation quality when the influence of different fluctuation factors is removed.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128650409","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 : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599293
Sansan Li, Yong-dong Huang, Jianwei Yang
The traditional affine-invariant Fourier descriptor is contour-based. It can not be applied to objects with several components. In this paper, a region-based Affine Invariant Ring Fourier Descriptor (AIRFD) is put forward to extract affine invariant features. A set of affine invariant closed curves is constructed from the object. Prior to the extraction of features, the derived closed curves are parameterized to establish a one-to-one correspondence between points on the original closed curves and points on the closed curves of their affine transformed version. Consequently, these closed curves are put on the image of the image, and pixels on these closed curves are derived. Finally, a Fourier transform is conducted on these pixel series. As a result, AIRFDs are derived. Experimental results show that the proposed method can be used for object classification.
{"title":"Affine Invariant Ring Fourier Descriptors","authors":"Sansan Li, Yong-dong Huang, Jianwei Yang","doi":"10.1109/ICWAPR.2013.6599293","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599293","url":null,"abstract":"The traditional affine-invariant Fourier descriptor is contour-based. It can not be applied to objects with several components. In this paper, a region-based Affine Invariant Ring Fourier Descriptor (AIRFD) is put forward to extract affine invariant features. A set of affine invariant closed curves is constructed from the object. Prior to the extraction of features, the derived closed curves are parameterized to establish a one-to-one correspondence between points on the original closed curves and points on the closed curves of their affine transformed version. Consequently, these closed curves are put on the image of the image, and pixels on these closed curves are derived. Finally, a Fourier transform is conducted on these pixel series. As a result, AIRFDs are derived. Experimental results show that the proposed method can be used for object classification.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129096319","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 : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599282
Yi Tang, Xue-Jun Zhou, Ting-ting Zhou
Example-based methods are popular in the single-image super-resolution technology. Among these methods, nearest neighbor-based algorithms are attractive for their simplicity and flexibility. These algorithms are mostly designed based on the nearest neighbor estimation, which has been shown very poor in generalization according to leaning theories. The weak generalization performance of nearest neighbor estimation lowers the performance of nearest neighbor-based algorithms, in both the visual experience and statistical index. To fix the problem, we introduce a local regression method where the local training sets are adaptively generated by applying the ℓ1-graph to the nearest neighbor-based algorithms. The ℓ1-graph based local regression method improves the generalization performance of nearest neighbor-based estimation, which further enhances the performance of nearest neighbor-based algorithms in super-resolution. The experimental results have shown that, the nearest neighbor-based algorithms are improved by our method.
{"title":"ℓ1-graph based local regression for super-resolution","authors":"Yi Tang, Xue-Jun Zhou, Ting-ting Zhou","doi":"10.1109/ICWAPR.2013.6599282","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599282","url":null,"abstract":"Example-based methods are popular in the single-image super-resolution technology. Among these methods, nearest neighbor-based algorithms are attractive for their simplicity and flexibility. These algorithms are mostly designed based on the nearest neighbor estimation, which has been shown very poor in generalization according to leaning theories. The weak generalization performance of nearest neighbor estimation lowers the performance of nearest neighbor-based algorithms, in both the visual experience and statistical index. To fix the problem, we introduce a local regression method where the local training sets are adaptively generated by applying the ℓ1-graph to the nearest neighbor-based algorithms. The ℓ1-graph based local regression method improves the generalization performance of nearest neighbor-based estimation, which further enhances the performance of nearest neighbor-based algorithms in super-resolution. The experimental results have shown that, the nearest neighbor-based algorithms are improved by our method.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115672931","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 : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599307
Zhao Pei-kun, Zhao Juan-juan, Wang Wu
In order to improve the personalized mobile network services, some researchers have employed the social relationship into the acquisition of mobile user's needs. But, when mobile users belong to different communities, their impacts on other mobile users are different. Therefore, in this paper, we propose an improved division of mobile social network based on the mobile user's behaviors. Firstly, we propose a computation of trust including the direct trust and indirect trust based on communications between mobile users. Then, we construct the mobile social network according to the obtained trusts. Afterward, we propose an improved method to divide the mobile social network based on cohesive subgroups. Finally, we perform experiments using the MIT real dataset. Experimental results show that we can get more accurate subgroup division.
{"title":"Division of mobile social network based on user behavior","authors":"Zhao Pei-kun, Zhao Juan-juan, Wang Wu","doi":"10.1109/ICWAPR.2013.6599307","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599307","url":null,"abstract":"In order to improve the personalized mobile network services, some researchers have employed the social relationship into the acquisition of mobile user's needs. But, when mobile users belong to different communities, their impacts on other mobile users are different. Therefore, in this paper, we propose an improved division of mobile social network based on the mobile user's behaviors. Firstly, we propose a computation of trust including the direct trust and indirect trust based on communications between mobile users. Then, we construct the mobile social network according to the obtained trusts. Afterward, we propose an improved method to divide the mobile social network based on cohesive subgroups. Finally, we perform experiments using the MIT real dataset. Experimental results show that we can get more accurate subgroup division.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124874606","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 : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599303
Haina Jiang, Xiangyu Yang, Li Zeng
To have higher resolution and precision, the amount of industrial computed tomography data has become larger and larger. Moreover, industrial computed tomography images are approximately piece-wise constant, which fits for encoding contour. Then, we develop an improved compression method based on wavelet contour coding Firstly, we merge Freeman encoding idea into our IMCE (an improved method for contours extraction based on stationary wavelet) to extract contours. Simultaneously, each contour point extracted by IMCE is directly stored by recording the relative coordinates not the actual ones through exploiting their continuity and logical linking. By that, the two steps of traditional contour-based compression method are simplified into only one. Lastly, Huffman coding is employed to further lossless compress them. Experimental results show that this method can gain good compression ratio as well as keeping ideal quality of decompressed image.
{"title":"Compressing industrial computed tomography images based on stationary wavelet","authors":"Haina Jiang, Xiangyu Yang, Li Zeng","doi":"10.1109/ICWAPR.2013.6599303","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599303","url":null,"abstract":"To have higher resolution and precision, the amount of industrial computed tomography data has become larger and larger. Moreover, industrial computed tomography images are approximately piece-wise constant, which fits for encoding contour. Then, we develop an improved compression method based on wavelet contour coding Firstly, we merge Freeman encoding idea into our IMCE (an improved method for contours extraction based on stationary wavelet) to extract contours. Simultaneously, each contour point extracted by IMCE is directly stored by recording the relative coordinates not the actual ones through exploiting their continuity and logical linking. By that, the two steps of traditional contour-based compression method are simplified into only one. Lastly, Huffman coding is employed to further lossless compress them. Experimental results show that this method can gain good compression ratio as well as keeping ideal quality of decompressed image.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116048305","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 : 2013-07-14DOI: 10.1109/ICWAPR.2013.6599329
Yulian Wu, Xiangchu Feng, Liang Luo
This paper describes an image inpainting algorithm based on two tight frame systems that can sparsely represent cartoons and textures respectively. The proposed minimization formulation adopts nonconvex approximation via balanced approach, and an iterative algorithm is derived to find its solution. Numerical simulations demonstrate that the proposed nonconvex algorithm can significantly improve the image inpainting quality over the usual l1 algorithm.
{"title":"Simultaneous cartoon and texture for nonconvex image inpainting via the balanced approach","authors":"Yulian Wu, Xiangchu Feng, Liang Luo","doi":"10.1109/ICWAPR.2013.6599329","DOIUrl":"https://doi.org/10.1109/ICWAPR.2013.6599329","url":null,"abstract":"This paper describes an image inpainting algorithm based on two tight frame systems that can sparsely represent cartoons and textures respectively. The proposed minimization formulation adopts nonconvex approximation via balanced approach, and an iterative algorithm is derived to find its solution. Numerical simulations demonstrate that the proposed nonconvex algorithm can significantly improve the image inpainting quality over the usual l1 algorithm.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129776852","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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