Pub Date : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458146
Elham Shahinfard, Maher Sid-Ahmed, Majid Ahmadi
This paper describes an improved motion adaptive deinterlacing method which uses five consecutive fields for motion detection. The motion detection algorithm, searches for motion activity between the fields by a hierarchical block based structure so it reduces the computation amount considerably. This reduction depends on the level of motion activity between the fields and could be of the order of two for slow motion scenes. The motion detection algorithm applies the same motion detection structure to all three color components of the video sequence and the motion detection results of different colors are then compared to obtain more reliable motion detection results. Searching between five fields and also using color data in motion detection makes the motion detection step more accurate and robust to noise and consequently it improves the overall performance of the deinterlacing algorithm. Missing lines of interlaced video are then interpolated using the motion activity data of the interlaced video fields; by giving more weight to temporal (or interfield) interpolation in static parts of the video scene and more weight to spatial (or intrafield) interpolation in dynamic parts of the video scene. Experimental results show that the proposed deinterlacing method gives less interpolation errors than most available deinterlacing methods.
{"title":"An Improved Motion Adaptive Deinterlacing Method Using Variable Block-Size Motion Detection","authors":"Elham Shahinfard, Maher Sid-Ahmed, Majid Ahmadi","doi":"10.1109/ISSPIT.2007.4458146","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458146","url":null,"abstract":"This paper describes an improved motion adaptive deinterlacing method which uses five consecutive fields for motion detection. The motion detection algorithm, searches for motion activity between the fields by a hierarchical block based structure so it reduces the computation amount considerably. This reduction depends on the level of motion activity between the fields and could be of the order of two for slow motion scenes. The motion detection algorithm applies the same motion detection structure to all three color components of the video sequence and the motion detection results of different colors are then compared to obtain more reliable motion detection results. Searching between five fields and also using color data in motion detection makes the motion detection step more accurate and robust to noise and consequently it improves the overall performance of the deinterlacing algorithm. Missing lines of interlaced video are then interpolated using the motion activity data of the interlaced video fields; by giving more weight to temporal (or interfield) interpolation in static parts of the video scene and more weight to spatial (or intrafield) interpolation in dynamic parts of the video scene. Experimental results show that the proposed deinterlacing method gives less interpolation errors than most available deinterlacing methods.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130800897","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 : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458091
E. Piracci, N. Petrochilos, G. Galati
This paper presents an effective algorithm to discriminate and separate superimposed SSR (secondary surveillance radar) mode S signals. The algorithm is an adaptation of the PA (projection algorithm) [1,3,4] that perform a blind separation of the multiple SSR sources using a single channel receiver. As present-days SSR stations only have a single-channel receiver, the proposed algorithm is operatively useful, specially for multilateration and wide area multilateration applications, (M-LAT, WAM). The algorithm is evaluated with real recorded data and also simulated signals generated by a complete simulation of a typical MLAT Rx station, from the RF to the digital section. We discuss as well the estimation of the time of arrival for each overlapped signal, that is necessary for the timing. Finally we propose a possible architecture for the signals separation block of the digital processor of the receiving station.
{"title":"Super-imposed Mode S signals: Single-antenna Projection Algorithm and processing architecture","authors":"E. Piracci, N. Petrochilos, G. Galati","doi":"10.1109/ISSPIT.2007.4458091","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458091","url":null,"abstract":"This paper presents an effective algorithm to discriminate and separate superimposed SSR (secondary surveillance radar) mode S signals. The algorithm is an adaptation of the PA (projection algorithm) [1,3,4] that perform a blind separation of the multiple SSR sources using a single channel receiver. As present-days SSR stations only have a single-channel receiver, the proposed algorithm is operatively useful, specially for multilateration and wide area multilateration applications, (M-LAT, WAM). The algorithm is evaluated with real recorded data and also simulated signals generated by a complete simulation of a typical MLAT Rx station, from the RF to the digital section. We discuss as well the estimation of the time of arrival for each overlapped signal, that is necessary for the timing. Finally we propose a possible architecture for the signals separation block of the digital processor of the receiving station.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133381346","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 : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458028
Ashraf S Hussein, Amr H. Abdel-Aziz
This paper presents an integrated framework for surface reconstruction capable of handling large scale clouds of points. This framework is based on two proposed methods for implicit surface fitting and polygonization to convert a cloud of unorganized points into an optimized surface. The proposed fitting method employs the partition of unity (POU) method associated with the radial basis functions (RBF) over a distributed computing environment to facilitate and speedup fitting of large scale clouds without any data reduction to preserve all the surface details. Moreover, an innovative adaptive mesh refinement (AMR) based method is proposed for implicit surface polygonization. This method steers adaptive volume sampling via a series of optimization criteria to provide accurate and optimized surfaces with minimum number of polygons. The experimental results for the considered test models showed an average reduction of 60% in fitting time using 16 processing nodes and 90% in polygonization time on the master node only against other traditional methods with better performance.
{"title":"A Framework for Implicit Surfaces Reconstruction form Large Clouds of Points","authors":"Ashraf S Hussein, Amr H. Abdel-Aziz","doi":"10.1109/ISSPIT.2007.4458028","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458028","url":null,"abstract":"This paper presents an integrated framework for surface reconstruction capable of handling large scale clouds of points. This framework is based on two proposed methods for implicit surface fitting and polygonization to convert a cloud of unorganized points into an optimized surface. The proposed fitting method employs the partition of unity (POU) method associated with the radial basis functions (RBF) over a distributed computing environment to facilitate and speedup fitting of large scale clouds without any data reduction to preserve all the surface details. Moreover, an innovative adaptive mesh refinement (AMR) based method is proposed for implicit surface polygonization. This method steers adaptive volume sampling via a series of optimization criteria to provide accurate and optimized surfaces with minimum number of polygons. The experimental results for the considered test models showed an average reduction of 60% in fitting time using 16 processing nodes and 90% in polygonization time on the master node only against other traditional methods with better performance.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130131498","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 : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458115
Byong-Ok Kwun, A. El-Keyi, Benoit Champagne
We present a robust beamforming scheme for collaborative multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) wireless systems. Optimum collaborative transmit beamforming requires knowledge of channel state information (CSI) at the transmitters (collaborative nodes). In practice, however, exact knowledge of CSI is not available at the transmitters. To mitigate the effects of the channel mismatch, we consider a max- min beamforming design approach for collaborative transmission by maximizing the minimum (worst-case) received signal-to-noise ratio (SNR) within a predefined uncertainty region at each OFDM subcarrier. In addition, several subcarrier power allocation strategies are investigated to further improve the performance of collaborative systems.
{"title":"Robust Transmit Beamforming for Collaborative MIMO-OFDM Systems","authors":"Byong-Ok Kwun, A. El-Keyi, Benoit Champagne","doi":"10.1109/ISSPIT.2007.4458115","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458115","url":null,"abstract":"We present a robust beamforming scheme for collaborative multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) wireless systems. Optimum collaborative transmit beamforming requires knowledge of channel state information (CSI) at the transmitters (collaborative nodes). In practice, however, exact knowledge of CSI is not available at the transmitters. To mitigate the effects of the channel mismatch, we consider a max- min beamforming design approach for collaborative transmission by maximizing the minimum (worst-case) received signal-to-noise ratio (SNR) within a predefined uncertainty region at each OFDM subcarrier. In addition, several subcarrier power allocation strategies are investigated to further improve the performance of collaborative systems.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116726807","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 : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458166
H. J. Robertson, J. Soraghan, C. Idzikowski, Bernard A. Conway
A sleep apnoea episode prediction system is presented that is based exclusively on the airflow signal. Detection of obstructive sleep apnoea (OSA) is generally carried out using polysomnography, with the data being analysed and a diagnosis formed. Being able to predict when a sleep apnoea episode is going to occur will allow for treatment to be applied before the episode becomes detrimental to the patient. Airflow signals were extracted from polysomnographic data and processed using three techniques: epoching of the flow signal, principle component analysis (PCA) and empirical mode decomposition (EMD). These processed signals were then classified using three distance functions: Euclidean, Hamming and Spearman distance. Classification of the airflow signal preceding an apnoea by Hamming distance produced the best results, with sensitivity of 81% and specificity of 76%. Reliability statistics were increase when classifying apnoea and hypopnoea episodes, with sensitivity of 95% and specificity of 100%, using Hamming distance and the empirical mode decomposition. In conclusion, classification of inspiratory airflow signal before an apnoea and hypopnoea is possible with high reliability statistics.
{"title":"EMD and PCA for the Prediction of Sleep Apnoea: A Comparative Study","authors":"H. J. Robertson, J. Soraghan, C. Idzikowski, Bernard A. Conway","doi":"10.1109/ISSPIT.2007.4458166","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458166","url":null,"abstract":"A sleep apnoea episode prediction system is presented that is based exclusively on the airflow signal. Detection of obstructive sleep apnoea (OSA) is generally carried out using polysomnography, with the data being analysed and a diagnosis formed. Being able to predict when a sleep apnoea episode is going to occur will allow for treatment to be applied before the episode becomes detrimental to the patient. Airflow signals were extracted from polysomnographic data and processed using three techniques: epoching of the flow signal, principle component analysis (PCA) and empirical mode decomposition (EMD). These processed signals were then classified using three distance functions: Euclidean, Hamming and Spearman distance. Classification of the airflow signal preceding an apnoea by Hamming distance produced the best results, with sensitivity of 81% and specificity of 76%. Reliability statistics were increase when classifying apnoea and hypopnoea episodes, with sensitivity of 95% and specificity of 100%, using Hamming distance and the empirical mode decomposition. In conclusion, classification of inspiratory airflow signal before an apnoea and hypopnoea is possible with high reliability statistics.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133649493","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 : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458001
H.S. Wang, G. Zeng
In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analyzed by means of a statistical-mechanical approach. Replica analysis focus on analytically studying how the minimum mean square error (MMSE) channel estimation error appears in the multiuser channel capacity formula and mathematical expressions are derived. At the same time, numerical simulation results are demonstrated to validate the replica analysis. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, effect on the channel capacity.
{"title":"A statistical-mechanics approach to analyzing effect of imperfect channel state information on multiuser channel capacity","authors":"H.S. Wang, G. Zeng","doi":"10.1109/ISSPIT.2007.4458001","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458001","url":null,"abstract":"In this paper, the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analyzed by means of a statistical-mechanical approach. Replica analysis focus on analytically studying how the minimum mean square error (MMSE) channel estimation error appears in the multiuser channel capacity formula and mathematical expressions are derived. At the same time, numerical simulation results are demonstrated to validate the replica analysis. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, effect on the channel capacity.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126953720","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 : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458156
Atsunori Kanemura, S. Maeda, Shin Ishii
We develop an image superresolution method that can deal with spatially structured noise added to an original image. Such a structured noise process can be understood as a model for possible occlusions such as clouds in the sky or stains on the lens, and is modeled as spin glasses. The original high-resolution image underlying multiple low-resolution observed images and the hidden noise structure are estimated via a variational learning algorithm. Experiments show that our superresolution method can outperform other methods that do not assume structured noise.
{"title":"Image Superresolution under Spatially Structured Noise","authors":"Atsunori Kanemura, S. Maeda, Shin Ishii","doi":"10.1109/ISSPIT.2007.4458156","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458156","url":null,"abstract":"We develop an image superresolution method that can deal with spatially structured noise added to an original image. Such a structured noise process can be understood as a model for possible occlusions such as clouds in the sky or stains on the lens, and is modeled as spin glasses. The original high-resolution image underlying multiple low-resolution observed images and the hidden noise structure are estimated via a variational learning algorithm. Experiments show that our superresolution method can outperform other methods that do not assume structured noise.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121988229","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 : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458102
Adel Metref, D. Le Guennec, J. Palicot
In this paper, an optimized carrier recovery phase-error detector, based on hierarchical constellation concept is proposed in order to improve acquisition performances of the phase recovery loop. Theoretical and simulation results for quadrature amplitude modulation (16-QAM) signals and for a 5 dB signal-to-noise ratio per bit, show that a phase-error sensitivity gain of about 5 deg is obtained. Furthermore, this paper provides the analytical evaluation of the S-curve of a classical phase-error detector, selected in this study for being the most attractive for QAM constellations.
{"title":"S-curve Theoretical Analysis of a Classical and a Hierarchical Phase Detector for QAM Constellations","authors":"Adel Metref, D. Le Guennec, J. Palicot","doi":"10.1109/ISSPIT.2007.4458102","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458102","url":null,"abstract":"In this paper, an optimized carrier recovery phase-error detector, based on hierarchical constellation concept is proposed in order to improve acquisition performances of the phase recovery loop. Theoretical and simulation results for quadrature amplitude modulation (16-QAM) signals and for a 5 dB signal-to-noise ratio per bit, show that a phase-error sensitivity gain of about 5 deg is obtained. Furthermore, this paper provides the analytical evaluation of the S-curve of a classical phase-error detector, selected in this study for being the most attractive for QAM constellations.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122241863","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 : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458179
Ivo R. Draganov, A. Popova
In this paper an analysis is presented concerning the applicability of filters and edge/corner detectors using Smallest Univalue Segment Assimilating Nucleus (SUSAN) principle to preprocessing of images containing handwritten text. A new adaptive approach for estimating intensity threshold is given which proves filter and edge/corner efficiency. Different brightness similarity functions are tested for proper finding the Univalue Segment Assimilating Nucleus (USAN) area. A comparison is made with the averaging, Gaussian and median filters to reveal SUSAN filter superiority when filtering different kinds of noise and preserving the original structure of the handwriting.
{"title":"Handwritten Text Preprocessing Algorithm Applying SUSAN Principle","authors":"Ivo R. Draganov, A. Popova","doi":"10.1109/ISSPIT.2007.4458179","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458179","url":null,"abstract":"In this paper an analysis is presented concerning the applicability of filters and edge/corner detectors using Smallest Univalue Segment Assimilating Nucleus (SUSAN) principle to preprocessing of images containing handwritten text. A new adaptive approach for estimating intensity threshold is given which proves filter and edge/corner efficiency. Different brightness similarity functions are tested for proper finding the Univalue Segment Assimilating Nucleus (USAN) area. A comparison is made with the averaging, Gaussian and median filters to reveal SUSAN filter superiority when filtering different kinds of noise and preserving the original structure of the handwriting.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129974376","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 : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458103
S. Daumont, D. Le Guennec
We consider the problem of blind sources separation (BSS), i.e., without the use of training sequences, for a multiuser communication system using a linear multiple input multiple output (MIMO) system combined with an Alamouti or Tarokh space-time block coding scheme. In this coding scheme, each symbol is transmitted using several time slots and through a linear instantaneous mixing channel. In order to separate the sources, we use the multiuser kurtosis (MUK) algorithm, usually used in Bell layered space time (BLAST) scheme. This algorithm allows to separate the sources in spite to redundancy insert by Alamouti and Tarokh scheme. So, we propose a new method, applied after MUK algorithm, which raises the ambiguity of sources order inherent in BSS algorithm, thanks to redundancy. Furthermore, it is shown theoretically that using this method reduces the mean square error (MSE) of 3 dB compared with a method which doesn't exploit the redundancy.
{"title":"Blind source separation with order recovery for MIMO system and an Alamouti or Tarokh space-time block coding scheme","authors":"S. Daumont, D. Le Guennec","doi":"10.1109/ISSPIT.2007.4458103","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458103","url":null,"abstract":"We consider the problem of blind sources separation (BSS), i.e., without the use of training sequences, for a multiuser communication system using a linear multiple input multiple output (MIMO) system combined with an Alamouti or Tarokh space-time block coding scheme. In this coding scheme, each symbol is transmitted using several time slots and through a linear instantaneous mixing channel. In order to separate the sources, we use the multiuser kurtosis (MUK) algorithm, usually used in Bell layered space time (BLAST) scheme. This algorithm allows to separate the sources in spite to redundancy insert by Alamouti and Tarokh scheme. So, we propose a new method, applied after MUK algorithm, which raises the ambiguity of sources order inherent in BSS algorithm, thanks to redundancy. Furthermore, it is shown theoretically that using this method reduces the mean square error (MSE) of 3 dB compared with a method which doesn't exploit the redundancy.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129625824","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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