Pub Date : 2007-12-01DOI: 10.1109/ISSPIT.2007.4458076
Aboozar Taherkhani, Ali Seyyedsalehi, Arash Mohammadi, Mohammad Hasan, Moradi
Acoustic voice analysis is an effective, cheap and non-invasive tool that can be used to confirm the initial diagnosis and provides an objective determination of the impairment. The nonlinearities of the voice source mechanisms may cause the existence of chaos in human voice production. Voice pathology can cause to addition colored noise to voice wave. Added noise to a chaotic signal causes reduction of the deterministic property and therefore increases correlation dimension of signal. Surrogate data analysis can measure this deviation and give a criterion for amount of noise added to the chaotic signal. By using this criterion a threshold level is set to separate disordered voice from normal voice and 95% accuracy is achieved.
{"title":"Nonlinear Signal Processing for Voice Disorder Detection by Using Modified GP Algorithm and Surrogate Data Analysis","authors":"Aboozar Taherkhani, Ali Seyyedsalehi, Arash Mohammadi, Mohammad Hasan, Moradi","doi":"10.1109/ISSPIT.2007.4458076","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458076","url":null,"abstract":"Acoustic voice analysis is an effective, cheap and non-invasive tool that can be used to confirm the initial diagnosis and provides an objective determination of the impairment. The nonlinearities of the voice source mechanisms may cause the existence of chaos in human voice production. Voice pathology can cause to addition colored noise to voice wave. Added noise to a chaotic signal causes reduction of the deterministic property and therefore increases correlation dimension of signal. Surrogate data analysis can measure this deviation and give a criterion for amount of noise added to the chaotic signal. By using this criterion a threshold level is set to separate disordered voice from normal voice and 95% accuracy is achieved.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"101 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":"124628267","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.2007.4458141
Ata Abbasi, Farhad Pashakhanlou, B. Vahdat
The Block method approach to solve EIT problem leads to an exact solution if the measurements are done without error. Non-iterative method is a feasible approach on solving 3D EIT forward problem. However, the effect of the measurement error has not been considered in this method yet. In this article, the 3D model of EIT with block method has been considered. The required equations to solve the forward problem are then generated. To solve the forward problem, non-iterative method has been employed. Effect of the measurement error on forward problem for a 3D model of EIT are generated. It has been shown that for a sample 3D model, measurement error can propagate exponentially.
{"title":"Error Propagation in Non-Iterative EIT Block Method","authors":"Ata Abbasi, Farhad Pashakhanlou, B. Vahdat","doi":"10.1109/ISSPIT.2007.4458141","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458141","url":null,"abstract":"The Block method approach to solve EIT problem leads to an exact solution if the measurements are done without error. Non-iterative method is a feasible approach on solving 3D EIT forward problem. However, the effect of the measurement error has not been considered in this method yet. In this article, the 3D model of EIT with block method has been considered. The required equations to solve the forward problem are then generated. To solve the forward problem, non-iterative method has been employed. Effect of the measurement error on forward problem for a 3D model of EIT are generated. It has been shown that for a sample 3D model, measurement error can propagate exponentially.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"17 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":"130594235","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.2007.4458057
Yonghee Lee, Heejung Lee, Heonshik Shin
Video streams can be compressed to fit the available network by controlling three factors; temporal resolution, spatial resolution and picture quality. Controlling picture quality by modifying the quantization parameter (QP) is most widely used. But we demonstrate that reducing the spatial resolution is more effective in a low bit-rate environment, and we show how to find the optimal spatial resolution for the available bandwidth. Varying the spatial resolution is especially effective 1) when the bandwidth between the video encoder and the displaying device varies considerably with time, which is the case in wireless networks, and 2) when the display device is sensitive to energy saving. Both of these considerations are met by a portable media player which is displaying streaming video content transmitted by a remote video server through a wireless network. If the bit-rate is low, our technique can improve the picture quality by more than 1 db compared to adjustment of QP, accompanied by a halving of energy consumption.
{"title":"Adaptive Spatial Resolution Control Scheme for Mobile Video Applications","authors":"Yonghee Lee, Heejung Lee, Heonshik Shin","doi":"10.1109/ISSPIT.2007.4458057","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458057","url":null,"abstract":"Video streams can be compressed to fit the available network by controlling three factors; temporal resolution, spatial resolution and picture quality. Controlling picture quality by modifying the quantization parameter (QP) is most widely used. But we demonstrate that reducing the spatial resolution is more effective in a low bit-rate environment, and we show how to find the optimal spatial resolution for the available bandwidth. Varying the spatial resolution is especially effective 1) when the bandwidth between the video encoder and the displaying device varies considerably with time, which is the case in wireless networks, and 2) when the display device is sensitive to energy saving. Both of these considerations are met by a portable media player which is displaying streaming video content transmitted by a remote video server through a wireless network. If the bit-rate is low, our technique can improve the picture quality by more than 1 db compared to adjustment of QP, accompanied by a halving of energy consumption.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"13 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":"130082387","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.2007.4458023
Hongjie Liu, B. Feng, Jianjie Wei, Wenjie Li
In the oil-gas prediction of seismic reservoir, the traditional method directly classify by attribute. However, the dimension of input information is so large that the calculation is time-consuming, the storage capacity demanding and the network structure complex. Moreover it is easy to be caught in local minimum in the sample learning. Therefore, a method of oil-gas prediction in seismic reservoir based on rough set and PSO algorithm is presented. The main process is to reduce the seismic attributes by the method of attribute reduction in rough set, which can simplify the input structure and reduce the time needed to train those involved. The prediction system of neural network based on PSO algorithm can overcome many disadvantages in traditional BP network, and improve the training process. The simulation experiments and actual examples show the network structure constructed by attribute reduction not only can achieve the prediction precision, but also can save cost, improve process speed and have notable effect on oil-gas prediction.
{"title":"The Oil-Gas Prediction of Seismic Reservoir Based on Rough Set and PSO Algorithm","authors":"Hongjie Liu, B. Feng, Jianjie Wei, Wenjie Li","doi":"10.1109/ISSPIT.2007.4458023","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458023","url":null,"abstract":"In the oil-gas prediction of seismic reservoir, the traditional method directly classify by attribute. However, the dimension of input information is so large that the calculation is time-consuming, the storage capacity demanding and the network structure complex. Moreover it is easy to be caught in local minimum in the sample learning. Therefore, a method of oil-gas prediction in seismic reservoir based on rough set and PSO algorithm is presented. The main process is to reduce the seismic attributes by the method of attribute reduction in rough set, which can simplify the input structure and reduce the time needed to train those involved. The prediction system of neural network based on PSO algorithm can overcome many disadvantages in traditional BP network, and improve the training process. The simulation experiments and actual examples show the network structure constructed by attribute reduction not only can achieve the prediction precision, but also can save cost, improve process speed and have notable effect on oil-gas prediction.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"19 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":"123757459","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.2007.4458124
Saikat Chatterjee, T. Sreenivas
We address the issue of rate-distortion (R/D) performance optimality of the recently proposed switched split vector quantization (SSVQ) method. The distribution of the source is modeled using Gaussian mixture density and thus, the non-parametric SSVQ is analyzed in a parametric model based framework for achieving optimum R/D performance. Using high rate quantization theory, we derive the optimum bit allocation formulae for the intra-cluster split vector quantizer (SVQ) and the inter-cluster switching. For the wide-band speech line spectrum frequency (LSF) parameter quantization, it is shown that the Gaussian mixture model (GMM) based parametric SSVQ method provides 1 bit/vector advantage over the non-parametric SSVQ method.
{"title":"Gaussian Mixture Model Based Switched Split Vector Quantization of LSF Parameters","authors":"Saikat Chatterjee, T. Sreenivas","doi":"10.1109/ISSPIT.2007.4458124","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458124","url":null,"abstract":"We address the issue of rate-distortion (R/D) performance optimality of the recently proposed switched split vector quantization (SSVQ) method. The distribution of the source is modeled using Gaussian mixture density and thus, the non-parametric SSVQ is analyzed in a parametric model based framework for achieving optimum R/D performance. Using high rate quantization theory, we derive the optimum bit allocation formulae for the intra-cluster split vector quantizer (SVQ) and the inter-cluster switching. For the wide-band speech line spectrum frequency (LSF) parameter quantization, it is shown that the Gaussian mixture model (GMM) based parametric SSVQ method provides 1 bit/vector advantage over the non-parametric SSVQ method.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"83 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":"116445784","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.2007.4458214
A. Keshk
In this paper, we suggest a mechanism for implementing a distributed application using RMI based on JAVA threads. The application is parallel matrices multiplication depending on distributed the products of rows and columns on different machines. One server and three clients are run to find the product of matrix multiplication. The server distributes the determine blocks of rows and columns on the registered clients. The clients return their product blocks to a server, which calculate the final product of matrix multiplication. Applications of this type will allow loaded servers to transfer part of the load to clients to exploit the computing power available at client side. The time of matrix multiplication with size of 256 times 256 is reduced by 52.5 % by using 3-client and this time can be decreased more in the case of increasing the number of clients.
{"title":"Implementation of Distributed Application using RMI Java threads","authors":"A. Keshk","doi":"10.1109/ISSPIT.2007.4458214","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458214","url":null,"abstract":"In this paper, we suggest a mechanism for implementing a distributed application using RMI based on JAVA threads. The application is parallel matrices multiplication depending on distributed the products of rows and columns on different machines. One server and three clients are run to find the product of matrix multiplication. The server distributes the determine blocks of rows and columns on the registered clients. The clients return their product blocks to a server, which calculate the final product of matrix multiplication. Applications of this type will allow loaded servers to transfer part of the load to clients to exploit the computing power available at client side. The time of matrix multiplication with size of 256 times 256 is reduced by 52.5 % by using 3-client and this time can be decreased more in the case of increasing the number of clients.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"67 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":"125679976","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.2007.4458108
K. Suresh, T. Sreenivas
We extend the recently proposed spectral integration based psychoacoustic model for sinusoidal distortions to the MDCT domain. The estimated masking threshold additionally depends on the sub-band spectral flatness measure of the signal which accounts for the non- sinusoidal distortion introduced by masking. The expressions for masking threshold are derived and the validity of the proposed model is established through perceptual transparency test of audio clips. Test results indicate that we do achieve transparent quality reconstruction with the new model. Performance of the model is compared with MPEG psychoacoustic models with respect to the estimated perceptual entropy (PE). The results show that the proposed model predicts a lower PE than other models.
{"title":"Direct MDCT Domain Psychoacoustic Modeling","authors":"K. Suresh, T. Sreenivas","doi":"10.1109/ISSPIT.2007.4458108","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458108","url":null,"abstract":"We extend the recently proposed spectral integration based psychoacoustic model for sinusoidal distortions to the MDCT domain. The estimated masking threshold additionally depends on the sub-band spectral flatness measure of the signal which accounts for the non- sinusoidal distortion introduced by masking. The expressions for masking threshold are derived and the validity of the proposed model is established through perceptual transparency test of audio clips. Test results indicate that we do achieve transparent quality reconstruction with the new model. Performance of the model is compared with MPEG psychoacoustic models with respect to the estimated perceptual entropy (PE). The results show that the proposed model predicts a lower PE than other models.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"24 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":"125921285","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.2007.4458037
M. M. Tantawy, M. El-Yazeed, N.S. Abdel, M.M. El-Henawy
In this paper we propose a modification to a fast vector quantization algorithm based on nearest partition set search. The fast algorithm searches the codebook to find the nearest set of codevectors for each codevector in the codebook. The nearest set of codevectors is called nearest set partition (NPS) which calculated each iteration. During each iteration the fast algorithm searches the NPS instead of searching the codebook which save training time. The NPS algorithm does well but with large codebook the saved timed consumed in calculating the NPS. So we proposed a modified algorithm to overcome this problem. The experimental results indicate that variation of NPS is slow with iteration. According to our results the calculation of NPS in each iteration is not necessary which save more training time without affecting the codebook quality.
{"title":"A Modified Fast Vector Quantization Algorithm Based on Nearest Partition Set Search","authors":"M. M. Tantawy, M. El-Yazeed, N.S. Abdel, M.M. El-Henawy","doi":"10.1109/ISSPIT.2007.4458037","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458037","url":null,"abstract":"In this paper we propose a modification to a fast vector quantization algorithm based on nearest partition set search. The fast algorithm searches the codebook to find the nearest set of codevectors for each codevector in the codebook. The nearest set of codevectors is called nearest set partition (NPS) which calculated each iteration. During each iteration the fast algorithm searches the NPS instead of searching the codebook which save training time. The NPS algorithm does well but with large codebook the saved timed consumed in calculating the NPS. So we proposed a modified algorithm to overcome this problem. The experimental results indicate that variation of NPS is slow with iteration. According to our results the calculation of NPS in each iteration is not necessary which save more training time without affecting the codebook quality.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"14 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":"127898967","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.2007.4458099
S. Z. Mahmoodabadi, J. Alirezaie, P. Babyn
An application of wavelet packet is presented for electrocardiogram (ECG) and magnetic resonance spectroscopy (MRS) characteristics detection in this study. A fully automated system is developed to detect the "R" peaks which are beat designators and are used consequently to locate other ECG characteristics. They include "P", "Q", "S" and "T" waves along with "ST" segment shift. The peaks and the area under the peaks of MRS signals are also detected. The Daubechies wavelets are selected as base processing filters. Frequency ordered wavelet packets (FOWPT) is utilized to generate a time-frequency plot of the signal used for further processing. The algorithm is validated on MIT-BIH database. The proposed beat detector achieved sensitivity of 99.18%plusmn2.75 and a positive predictivity of 98.00%plusmn4.45. The "P" wave detector achieved sensitivity of 51.69% and a positive predictivity of 53.64%.
{"title":"Bio-signal Characteristics Detection Utilizing Frequency Ordered Wavelet Packets","authors":"S. Z. Mahmoodabadi, J. Alirezaie, P. Babyn","doi":"10.1109/ISSPIT.2007.4458099","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458099","url":null,"abstract":"An application of wavelet packet is presented for electrocardiogram (ECG) and magnetic resonance spectroscopy (MRS) characteristics detection in this study. A fully automated system is developed to detect the \"R\" peaks which are beat designators and are used consequently to locate other ECG characteristics. They include \"P\", \"Q\", \"S\" and \"T\" waves along with \"ST\" segment shift. The peaks and the area under the peaks of MRS signals are also detected. The Daubechies wavelets are selected as base processing filters. Frequency ordered wavelet packets (FOWPT) is utilized to generate a time-frequency plot of the signal used for further processing. The algorithm is validated on MIT-BIH database. The proposed beat detector achieved sensitivity of 99.18%plusmn2.75 and a positive predictivity of 98.00%plusmn4.45. The \"P\" wave detector achieved sensitivity of 51.69% and a positive predictivity of 53.64%.","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":"129052324","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.2007.4458062
Hoda S Abdel-Aty-Zohdyl, Hashem Mostafa, Adam Sherif, Jrl Smiarowski, B. Searing
Defect tracking is important in evaluating the reliability of the software used in telecommunication networks. Bio-inspired integrated approaches and embedded chips have been developed and implemented to track improvements in the software reliability. In this paper, the integrated model for the failure discovery during testing is combined with bio-inspired approaches using the recurrent dynamic neural network (RDNN) with parametric adjustments and wavelets as basis; and the adaptive parameters RDNN (ARDNN) where the criterion is to minimize the error in failure intensity estimation, subject to the model constraints. Simulation results favor our adaptive recurrent dynamic neural network, with reduced error from 88% to 1.25 -to- 8% based on the number of iterations in the training phase.. The ARDNN approach provides optimum solution to the dynamic problem at hand since it iterates on the shape of the wavelet basis and provide adequate recovery of the data in the form of piecewise linear differential.
{"title":"Bio-Inspired Integrated Chips for Telecommunications S/W Defect-Tracking","authors":"Hoda S Abdel-Aty-Zohdyl, Hashem Mostafa, Adam Sherif, Jrl Smiarowski, B. Searing","doi":"10.1109/ISSPIT.2007.4458062","DOIUrl":"https://doi.org/10.1109/ISSPIT.2007.4458062","url":null,"abstract":"Defect tracking is important in evaluating the reliability of the software used in telecommunication networks. Bio-inspired integrated approaches and embedded chips have been developed and implemented to track improvements in the software reliability. In this paper, the integrated model for the failure discovery during testing is combined with bio-inspired approaches using the recurrent dynamic neural network (RDNN) with parametric adjustments and wavelets as basis; and the adaptive parameters RDNN (ARDNN) where the criterion is to minimize the error in failure intensity estimation, subject to the model constraints. Simulation results favor our adaptive recurrent dynamic neural network, with reduced error from 88% to 1.25 -to- 8% based on the number of iterations in the training phase.. The ARDNN approach provides optimum solution to the dynamic problem at hand since it iterates on the shape of the wavelet basis and provide adequate recovery of the data in the form of piecewise linear differential.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"143 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":"132244808","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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