Pub Date : 2010-12-03DOI: 10.21437/Interspeech.2010-600
Miaomiao Wen, Miaomiao Wang, K. Hirose, N. Minematsu
Previous researches have indicated the relevance between segmental duration and syntax information, but the usefulness of syntax features have not been thoroughly studied for predicting segmental duration. In this paper, we design two sets of syntax features to improve Mandarin phone and pause duration prediction respectively. Instead of using manually extracted syntax information as previous researches do, we acquire these syntax features from an automatic Chinese syntax parser. Results show that even though the automatically extracted syntax information has limited precision; it could still improve Mandarin segmental duration prediction.
{"title":"Improved Mandarin segmental duration prediction with automatically extracted syntax features","authors":"Miaomiao Wen, Miaomiao Wang, K. Hirose, N. Minematsu","doi":"10.21437/Interspeech.2010-600","DOIUrl":"https://doi.org/10.21437/Interspeech.2010-600","url":null,"abstract":"Previous researches have indicated the relevance between segmental duration and syntax information, but the usefulness of syntax features have not been thoroughly studied for predicting segmental duration. In this paper, we design two sets of syntax features to improve Mandarin phone and pause duration prediction respectively. Instead of using manually extracted syntax information as previous researches do, we acquire these syntax features from an automatic Chinese syntax parser. Results show that even though the automatically extracted syntax information has limited precision; it could still improve Mandarin segmental duration prediction.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"14 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":"131606580","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.2010.5655905
Mengmeng Zhang, Xia Li, Zhihui Yang, Yang Yang
This paper aims to explore the zero-crossing edge detection method based on the scale-space theory. After the one-dimensional signal and two-dimensional image are convolved with the second derivation of the Gaussian kernel respectively, the zero-crossing method is applied to And the zero-crossings of the second derivation. These points are located and then construct the edge of the signal or the image based on multi-scale space. In this paper, we proposed a new zero-crossing edge detection method based on the LOG (Laplacian of Gaussian) algorithm and multi-scale space. And then the result is compared with the gradient method used to detect border, and it shows that this method is more precise than the gradient method and other detection methods because of the one pixel width image border. This method can come close to or achieve the best level of detecting the edge.
本文旨在探索基于尺度空间理论的过零边缘检测方法。将一维信号和二维图像分别与高斯核的二阶导数进行卷积后，对二阶导数的过零进行过零处理。对这些点进行定位，然后基于多尺度空间构造信号或图像的边缘。本文提出了一种基于LOG (laplace of Gaussian)算法和多尺度空间的过零边缘检测方法。然后将结果与用于边界检测的梯度方法进行比较，结果表明，由于该方法的图像边界宽度为1像素，因此比梯度方法和其他检测方法具有更高的精度。该方法可以接近或达到检测边缘的最佳水平。
{"title":"A novel zero-crossing edge detection method based on multi-scale space theory","authors":"Mengmeng Zhang, Xia Li, Zhihui Yang, Yang Yang","doi":"10.1109/ICOSP.2010.5655905","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5655905","url":null,"abstract":"This paper aims to explore the zero-crossing edge detection method based on the scale-space theory. After the one-dimensional signal and two-dimensional image are convolved with the second derivation of the Gaussian kernel respectively, the zero-crossing method is applied to And the zero-crossings of the second derivation. These points are located and then construct the edge of the signal or the image based on multi-scale space. In this paper, we proposed a new zero-crossing edge detection method based on the LOG (Laplacian of Gaussian) algorithm and multi-scale space. And then the result is compared with the gradient method used to detect border, and it shows that this method is more precise than the gradient method and other detection methods because of the one pixel width image border. This method can come close to or achieve the best level of detecting the edge.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"53 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":"128775632","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.2010.5655847
Ren Jiayuan, Wang Yigang, Deng Yun
To eliminate or reduce wrong pairs in SIFT(Scale Invariant Feature Trans for m)feature matching, this paper proposes an error canceling algorithm through computing match-base. First finding three match point pairs by considering minimal Euclidean distance; second take three match point pairs as match-base if these pairs satisfy with criterion, or finding another three match pairs. Finally checking all other match pairs and eliminating wrong match pairs. Experimental results show that the proposed algorithm consumes lower time than RANSAC with inheriting rotation invariance of SIFT. At the same time, it does not exclude the right match pairs, with strong robustness. As a result, precision of image mosaic has been improved.
为了消除或减少SIFT(Scale Invariant Feature Trans for m)特征匹配中的错误对，本文提出了一种通过计算匹配库来消除错误对的算法。首先考虑最小欧几里得距离，找到三个火柴点对;如果满足条件，则取三个赛点对作为匹配基础，或者再找三个赛点对。最后检查所有其他匹配对并消除错误匹配对。实验结果表明，该算法继承了SIFT的旋转不变性，比RANSAC算法耗时更短。同时，它不排除正确的匹配对，具有较强的鲁棒性。从而提高了图像拼接的精度。
{"title":"Study on eliminating wrong match pairs of SIFT","authors":"Ren Jiayuan, Wang Yigang, Deng Yun","doi":"10.1109/ICOSP.2010.5655847","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5655847","url":null,"abstract":"To eliminate or reduce wrong pairs in SIFT(Scale Invariant Feature Trans for m)feature matching, this paper proposes an error canceling algorithm through computing match-base. First finding three match point pairs by considering minimal Euclidean distance; second take three match point pairs as match-base if these pairs satisfy with criterion, or finding another three match pairs. Finally checking all other match pairs and eliminating wrong match pairs. Experimental results show that the proposed algorithm consumes lower time than RANSAC with inheriting rotation invariance of SIFT. At the same time, it does not exclude the right match pairs, with strong robustness. As a result, precision of image mosaic has been improved.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"3 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":"128778108","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}
In order to solve the problem of robustly classifying underwater multiple targets in shallow sea, a novel classification method based on Multidimensional Scaling (MDS) is proposed. This algorithm extracts the robust and distinct feature difference between targets by means of MDS, and optimizes the feature distance by combining with kernel function. A modified K-means classifier is utilized to cluster the extracted features without knowing the prior information of class number. Experiment results on real sonar detecting data indicate that the classifying probability increases by 13.4% compared with PCA, and the probability and robustness of underwater target classification are improved effectively.
{"title":"A novel method of underwater multitarget classification based on Multidimensional Scaling analysis","authors":"Ru-hang Wang, Jianguo Huang, Xiaodong Cui, Qunfei Zhang","doi":"10.1109/ICOSP.2010.5655129","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5655129","url":null,"abstract":"In order to solve the problem of robustly classifying underwater multiple targets in shallow sea, a novel classification method based on Multidimensional Scaling (MDS) is proposed. This algorithm extracts the robust and distinct feature difference between targets by means of MDS, and optimizes the feature distance by combining with kernel function. A modified K-means classifier is utilized to cluster the extracted features without knowing the prior information of class number. Experiment results on real sonar detecting data indicate that the classifying probability increases by 13.4% compared with PCA, and the probability and robustness of underwater target classification are improved effectively.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"25 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":"126635390","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.2010.5656663
Yu Wang, Lin Gao
Identifying modules in protein-protein interaction (PPI) networks is important to understand the organization of the cellular processes. In this paper, an improved algorithm based on affinity propagation (AP) is proposed. We embed AP in our algorithm by utilizing AP to find the candidate overlapping vertices and keep those satisfying our filter condition. We apply our algorithm to S. cerevisiae PPI networks. The experimental results show that compared with AP, MCL, MCODE and CPM, our algorithm can discover more functional modules with high matching rate. Our proposed method is validated as an effective algorithm in identifying overlapping functional modules and can provide more insights for future biological study.
{"title":"An improved AP algorithm for identifying overlapping functional modules in protein-protein interaction networks","authors":"Yu Wang, Lin Gao","doi":"10.1109/ICOSP.2010.5656663","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5656663","url":null,"abstract":"Identifying modules in protein-protein interaction (PPI) networks is important to understand the organization of the cellular processes. In this paper, an improved algorithm based on affinity propagation (AP) is proposed. We embed AP in our algorithm by utilizing AP to find the candidate overlapping vertices and keep those satisfying our filter condition. We apply our algorithm to S. cerevisiae PPI networks. The experimental results show that compared with AP, MCL, MCODE and CPM, our algorithm can discover more functional modules with high matching rate. Our proposed method is validated as an effective algorithm in identifying overlapping functional modules and can provide more insights for future biological study.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"22 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":"126762267","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.2010.5657089
Choi-Man Nam, Q. Ruan, Gaoyun An
We presents a color and heuristic-based face detection algorithm in order to detect faces in H.264/AVC compressed domain. Face detector is composed of preprocessing, selecting face candidate and face authentication. Firstly, video capturing conditions are removed by the modified Successive Mean Quantization Transform (m-SMQT). Secondly, face candidates are run by using skin color image segmentation, H.264/AVC DCT coefficients and well-kwon face features. Finally, face locations are confirmed by using frontal face template and geometric structure. In order to achieve correct and speed requirements, we introduced m-SMQT, high-speed rectangle region partitioning algorithm, 16 points up-sampled AC image and K-parameter-based face feature clustering technique. The proposed algorithm is not only affected less from the different of face poses, but also offers low computational cost solution to problem of detecting faces. The face detector achieved a high recall value of 81% in detecting faces of sizes more than 14×12 pixels in all I-frames of H.264/AVC QCIF video sequences.
{"title":"Color and heuristic-based face detection in H.264 video sequences","authors":"Choi-Man Nam, Q. Ruan, Gaoyun An","doi":"10.1109/ICOSP.2010.5657089","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5657089","url":null,"abstract":"We presents a color and heuristic-based face detection algorithm in order to detect faces in H.264/AVC compressed domain. Face detector is composed of preprocessing, selecting face candidate and face authentication. Firstly, video capturing conditions are removed by the modified Successive Mean Quantization Transform (m-SMQT). Secondly, face candidates are run by using skin color image segmentation, H.264/AVC DCT coefficients and well-kwon face features. Finally, face locations are confirmed by using frontal face template and geometric structure. In order to achieve correct and speed requirements, we introduced m-SMQT, high-speed rectangle region partitioning algorithm, 16 points up-sampled AC image and K-parameter-based face feature clustering technique. The proposed algorithm is not only affected less from the different of face poses, but also offers low computational cost solution to problem of detecting faces. The face detector achieved a high recall value of 81% in detecting faces of sizes more than 14×12 pixels in all I-frames of H.264/AVC QCIF video sequences.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"18 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":"126769040","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.2010.5657133
Yongxin Zhang, Lixian Chen, Xin Ran
The traditional Expectation-Maximization (EM) training of Gaussian Mixture Model (GMM) is essentially a batch mode procedure which requires the multiple data samples with the sufficient size to update the model parameters. This severely limits the deployment and adaptation of GMM in many real-time online systems since the newly observed data samples are expected to be incorporated into the system upon available via retraining the model. This paper presents a new online incremental EM training procedure of GMM, which aims to perform the EM training incrementally and so can adapt GMM online sample by sample. The proposed method is extended on two kinds of EM algorithms for GMM, namely, Split-and-Merge EM and the traditional EM. Experiments on both the synthetic data and a speech processing task show the advantages and efficiency of the new method.
{"title":"Online incremental EM training of GMM and its application to speech processing applications","authors":"Yongxin Zhang, Lixian Chen, Xin Ran","doi":"10.1109/ICOSP.2010.5657133","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5657133","url":null,"abstract":"The traditional Expectation-Maximization (EM) training of Gaussian Mixture Model (GMM) is essentially a batch mode procedure which requires the multiple data samples with the sufficient size to update the model parameters. This severely limits the deployment and adaptation of GMM in many real-time online systems since the newly observed data samples are expected to be incorporated into the system upon available via retraining the model. This paper presents a new online incremental EM training procedure of GMM, which aims to perform the EM training incrementally and so can adapt GMM online sample by sample. The proposed method is extended on two kinds of EM algorithms for GMM, namely, Split-and-Merge EM and the traditional EM. Experiments on both the synthetic data and a speech processing task show the advantages and efficiency of the new method.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"17 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":"126926162","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.2010.5654972
Chen Li-jun, Bai Xue-wei, Ren Wen-tao
A prerequisite for variable spray operations is to detect, identify and locate maize seedlings in the complex scenes of farmland rapidly and accurately. In this paper, Regular pattern in distribution and growth of the corn seedling by bunch planting but leaves of plant overlapped in field is carefully taken into account, with the image acquisition mode which the camera image plane parallelized to the ground, in order to obtain the center of maize seedling roots, over-segmentation block projection method based on position feature is employed to locate crown of maize seedlings with the image captured. So the coordinate of corn root can be indirectly obtained by means of principles of perspective in machine vision as well as growing characteristics of corn. Experiment shows that the positioning error by this method is less than 30mm, and the average time in processing an image with 640×512 pixels in MATLAB is less than 300ms.
{"title":"Identification and location of corn seedling based on computer vision","authors":"Chen Li-jun, Bai Xue-wei, Ren Wen-tao","doi":"10.1109/ICOSP.2010.5654972","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5654972","url":null,"abstract":"A prerequisite for variable spray operations is to detect, identify and locate maize seedlings in the complex scenes of farmland rapidly and accurately. In this paper, Regular pattern in distribution and growth of the corn seedling by bunch planting but leaves of plant overlapped in field is carefully taken into account, with the image acquisition mode which the camera image plane parallelized to the ground, in order to obtain the center of maize seedling roots, over-segmentation block projection method based on position feature is employed to locate crown of maize seedlings with the image captured. So the coordinate of corn root can be indirectly obtained by means of principles of perspective in machine vision as well as growing characteristics of corn. Experiment shows that the positioning error by this method is less than 30mm, and the average time in processing an image with 640×512 pixels in MATLAB is less than 300ms.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"5 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":"123201433","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.2010.5654822
H. A. Meziani, F. Soltani
In this paper, we analyze the decentralized CA-CFAR detector using fuzzy fusion rules in heavy tailed clutter modeled by a Pearson distribution. We generalize our study by considering a distributed detection system with "L" detectors and using the "Maximum", "Minimum", "Algebraic sum" and "Algebraic product" fuzzy rules at the data fusion centre. We derive the membership function which maps the decision to the false alarm space and compute the threshold at the fusion centre. From the Monte-Carlo simulations conducted to assess the detection performance in homogeneous Pearson distributed clutter, we observe that the probability of detection increases with the number of detectors. However, there a maximum number of detectors (L=ll) above which no improvement is obtained.
{"title":"Generalised decentralised fuzzy CA-CFAR detector in Pearson distributed clutter","authors":"H. A. Meziani, F. Soltani","doi":"10.1109/ICOSP.2010.5654822","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5654822","url":null,"abstract":"In this paper, we analyze the decentralized CA-CFAR detector using fuzzy fusion rules in heavy tailed clutter modeled by a Pearson distribution. We generalize our study by considering a distributed detection system with \"L\" detectors and using the \"Maximum\", \"Minimum\", \"Algebraic sum\" and \"Algebraic product\" fuzzy rules at the data fusion centre. We derive the membership function which maps the decision to the false alarm space and compute the threshold at the fusion centre. From the Monte-Carlo simulations conducted to assess the detection performance in homogeneous Pearson distributed clutter, we observe that the probability of detection increases with the number of detectors. However, there a maximum number of detectors (L=ll) above which no improvement is obtained.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"16 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":"123258115","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.2010.5656088
P. Ircing, J. Romportl, Zdenek Loose
Our paper introduces implementation details of the application that serves as an audiovisual interface to the automatic dialogue system. It comprises a state-of-the-art large vocabulary continuous speech recognition engine and a TTS system coupled with an embodied avatar that is able to some extent convey a range of emotions to the user. The interface was originally designed for the dialogue system that allows elderly users to reminiscence about their photographs. However, the modular architecture of the whole system and the flexibility of messages that are used for communication between the modules facilitate seamless transition of the application to any domain of the dialogue.
{"title":"Audiovisual interface for Czech spoken dialogue system","authors":"P. Ircing, J. Romportl, Zdenek Loose","doi":"10.1109/ICOSP.2010.5656088","DOIUrl":"https://doi.org/10.1109/ICOSP.2010.5656088","url":null,"abstract":"Our paper introduces implementation details of the application that serves as an audiovisual interface to the automatic dialogue system. It comprises a state-of-the-art large vocabulary continuous speech recognition engine and a TTS system coupled with an embodied avatar that is able to some extent convey a range of emotions to the user. The interface was originally designed for the dialogue system that allows elderly users to reminiscence about their photographs. However, the modular architecture of the whole system and the flexibility of messages that are used for communication between the modules facilitate seamless transition of the application to any domain of the dialogue.","PeriodicalId":281876,"journal":{"name":"IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS","volume":"90 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":"126525391","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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