Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310490
Osama A S Alkishriwo, L. Chaparro
Compressive sensing attempts to simplify the frequency transformation and thresholding steps, commonly done in data compression, into one. Sparseness of the signal, in either time or frequency, is required for the convex optimization in compressive sensing to perform well. Although sparseness of certain signals, in either time or frequency, is guaranteed by the uncertainty principle signals composed of chirps are not however sparse in either domain. In this paper we propose an orthogonal linear-chirp transform, the discrete linear chirp transform (DLCT), to represent any signal in terms of linear chirps, with modulation and dual properties. Using the DLCT the sparseness of the signal in either time or frequency can be assessed, and if not sparse in neither of these domains, the modulation and dual properties of the DLCT provide a way to transform the signal into a sparse signal. The application of the proposed DLCT is in data compression. The transformation is illustrated by using sparse and not sparse test signals as well as actual signals.
{"title":"A discrete linear chirp transform (DLCT) for data compression","authors":"Osama A S Alkishriwo, L. Chaparro","doi":"10.1109/ISSPA.2012.6310490","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310490","url":null,"abstract":"Compressive sensing attempts to simplify the frequency transformation and thresholding steps, commonly done in data compression, into one. Sparseness of the signal, in either time or frequency, is required for the convex optimization in compressive sensing to perform well. Although sparseness of certain signals, in either time or frequency, is guaranteed by the uncertainty principle signals composed of chirps are not however sparse in either domain. In this paper we propose an orthogonal linear-chirp transform, the discrete linear chirp transform (DLCT), to represent any signal in terms of linear chirps, with modulation and dual properties. Using the DLCT the sparseness of the signal in either time or frequency can be assessed, and if not sparse in neither of these domains, the modulation and dual properties of the DLCT provide a way to transform the signal into a sparse signal. The application of the proposed DLCT is in data compression. The transformation is illustrated by using sparse and not sparse test signals as well as actual signals.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"1038 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131513220","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 : 2012-07-02DOI: 10.1109/ISSPA.2012.6310566
S. Miralavi, S. Ghorshi, Aidin Tahaei
A major problem in real-time packet-based communication systems, is misrouted or delayed packet which results in degraded perceived voice quality. If packets are not available on time, the packets are considered lost. The easiest solution in a network terminal receiver is to replace silence for the duration of lost speech segments. In a high quality communication system, to avoid degradation in speech quality due to packet loss, a suitable method or algorithm is needed to replace the missing segments of speech. In this paper, we introduce an adaptive filter for replacement of lost speech segment. In this method Kalman filter as a state-space based method will be used to predict the clean speech signal in presence of additive noise. The evaluation results show that Kalman filter has lower MSE compared to other methods in presence of White Gaussian Noise and background noise.
{"title":"A Kalman filter approach to packet loss replacement in presence of additive noise","authors":"S. Miralavi, S. Ghorshi, Aidin Tahaei","doi":"10.1109/ISSPA.2012.6310566","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310566","url":null,"abstract":"A major problem in real-time packet-based communication systems, is misrouted or delayed packet which results in degraded perceived voice quality. If packets are not available on time, the packets are considered lost. The easiest solution in a network terminal receiver is to replace silence for the duration of lost speech segments. In a high quality communication system, to avoid degradation in speech quality due to packet loss, a suitable method or algorithm is needed to replace the missing segments of speech. In this paper, we introduce an adaptive filter for replacement of lost speech segment. In this method Kalman filter as a state-space based method will be used to predict the clean speech signal in presence of additive noise. The evaluation results show that Kalman filter has lower MSE compared to other methods in presence of White Gaussian Noise and background noise.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"268 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132909200","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 : 2012-07-02DOI: 10.1109/ISSPA.2012.6310464
Marc-Antoine Rondeau, R. Rose
This paper addresses the problem of open vocabulary automatic speech recognition (ASR) using hybrid statistical language models (LMs). Hybrid LMs differ from closed vocabulary LMs in that the word level lexicon is augmented with an inventory of sub-lexical units (SLUs). The procedures used for selecting these SLUs and expanding out-of-vocabulary (OOV) words according to the SLUs is presented in the paper. The open-vocabulary ASR performance obtained using these techniques is presented for a lecture speech task domain.
{"title":"Developing a hybrid language model for open vocabulary automatic speech recognition in a lecture speech task","authors":"Marc-Antoine Rondeau, R. Rose","doi":"10.1109/ISSPA.2012.6310464","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310464","url":null,"abstract":"This paper addresses the problem of open vocabulary automatic speech recognition (ASR) using hybrid statistical language models (LMs). Hybrid LMs differ from closed vocabulary LMs in that the word level lexicon is augmented with an inventory of sub-lexical units (SLUs). The procedures used for selecting these SLUs and expanding out-of-vocabulary (OOV) words according to the SLUs is presented in the paper. The open-vocabulary ASR performance obtained using these techniques is presented for a lecture speech task domain.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122364027","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 : 2012-07-02DOI: 10.1109/ISSPA.2012.6310701
A. Serir, Youcef Bouhafsi
This paper deals with the micro-Doppler (m-D) phenomenon which is a frequency modulation induced on the returned radar signal due to micro-motion. Indeed, the micro-Doppler provides an additional information for target recognition that is complementary to existing recognition methods. In this paper we present a comparative study between feature extraction based on 2 types of analysis: time frequency (Instantaneous Frequency IF) analysis and time scale analysis (Wavelet Transform WT and Multiplicative Multiresolution Decomposition MMD), associated to SVM classifier to perform target identification. These approaches are tested on RadEch Database, containing radar echoes from various targets. The data has been collected in controlled test environments at the premises of Military Academy - Republic of Serbia. Thus, the results show that good performances are provided by the association of the instantaneous frequency with the MMD descriptor.
{"title":"Micro-doppler radar signature classification by time-frequency and time-scale analysis","authors":"A. Serir, Youcef Bouhafsi","doi":"10.1109/ISSPA.2012.6310701","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310701","url":null,"abstract":"This paper deals with the micro-Doppler (m-D) phenomenon which is a frequency modulation induced on the returned radar signal due to micro-motion. Indeed, the micro-Doppler provides an additional information for target recognition that is complementary to existing recognition methods. In this paper we present a comparative study between feature extraction based on 2 types of analysis: time frequency (Instantaneous Frequency IF) analysis and time scale analysis (Wavelet Transform WT and Multiplicative Multiresolution Decomposition MMD), associated to SVM classifier to perform target identification. These approaches are tested on RadEch Database, containing radar echoes from various targets. The data has been collected in controlled test environments at the premises of Military Academy - Republic of Serbia. Thus, the results show that good performances are provided by the association of the instantaneous frequency with the MMD descriptor.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122389154","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 : 2012-07-02DOI: 10.1109/ISSPA.2012.6310513
Ming Li, J. Azaña
An approach for programmable single-shot chirped microwave pulse compression is proposed and experimentally demonstrated based on an optical fiber-based microwave dispersive line. The microwave dispersive line is implemented based on a time-spectrum convolution system. This proposed technique has three key features. The first feature is that non-periodic input chirped microwave pulses can be single-shot compressed. The second one is that the compression system is programmable by shaping the spectrum of a broadband multi-wavelength laser or by tuning the first-order dispersion of a dispersive element. The last one is that microwave dispersive line provides an ultrahigh microwave dispersion approaching several ns2 over GHz bandwidths. The microwave dispersive line used to implement single-shot microwave pulse compression is theoretically analyzed and verified by a proof-of-concept experiment.
{"title":"Programmable and single-shot chirped microwave pulse compression using an optical fiber-based microwave dispersive line","authors":"Ming Li, J. Azaña","doi":"10.1109/ISSPA.2012.6310513","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310513","url":null,"abstract":"An approach for programmable single-shot chirped microwave pulse compression is proposed and experimentally demonstrated based on an optical fiber-based microwave dispersive line. The microwave dispersive line is implemented based on a time-spectrum convolution system. This proposed technique has three key features. The first feature is that non-periodic input chirped microwave pulses can be single-shot compressed. The second one is that the compression system is programmable by shaping the spectrum of a broadband multi-wavelength laser or by tuning the first-order dispersion of a dispersive element. The last one is that microwave dispersive line provides an ultrahigh microwave dispersion approaching several ns2 over GHz bandwidths. The microwave dispersive line used to implement single-shot microwave pulse compression is theoretically analyzed and verified by a proof-of-concept experiment.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127882137","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 : 2012-07-02DOI: 10.1109/ISSPA.2012.6310683
Reza Javanmard Alitappeh, Kossar Jeddi Saravi, F. Mahmoudi
The SIFT descriptor is one of the most widely used descriptors and is very stable in regard to changes in rotation, scale, affine, illumination, etc. This method is based on key points extracted from the image. If there are many such points, a lot of time will be needed in the matching and recognition phases. For this reason, we have tried in this article to use the clustering technique in order to reduce the number of key points by omitting similar points. In other words, subtractive clustering is used to select key points which are more distinct from and less similar to other points. In the section on conclusions, a successful implementation of this method is presented. The efficiencies of the proposed algorithm and of the base SIFT algorithm on the data set ALOI were investigated and it was observed that by adding this method to the base SIFT descriptor the rate of recognition increases by two percent and the time complexity decreases by 1.035728 seconds.
{"title":"Key point reduction in SIFT descriptor used by subtractive clustering","authors":"Reza Javanmard Alitappeh, Kossar Jeddi Saravi, F. Mahmoudi","doi":"10.1109/ISSPA.2012.6310683","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310683","url":null,"abstract":"The SIFT descriptor is one of the most widely used descriptors and is very stable in regard to changes in rotation, scale, affine, illumination, etc. This method is based on key points extracted from the image. If there are many such points, a lot of time will be needed in the matching and recognition phases. For this reason, we have tried in this article to use the clustering technique in order to reduce the number of key points by omitting similar points. In other words, subtractive clustering is used to select key points which are more distinct from and less similar to other points. In the section on conclusions, a successful implementation of this method is presented. The efficiencies of the proposed algorithm and of the base SIFT algorithm on the data set ALOI were investigated and it was observed that by adding this method to the base SIFT descriptor the rate of recognition increases by two percent and the time complexity decreases by 1.035728 seconds.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129195448","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 : 2012-07-02DOI: 10.1109/ISSPA.2012.6310574
B. Boashash, T. B. Jabeur
Prior to birth, fetus health can be monitored by the variety and scale of its movements. In addition, at birth, EEG signals are recorded from at-risk newborns. Studies have shown that both fetal movements and newborn EEGs are non-stationary signals. This paper aims to represent both newborn EEG and fetal movement signals in a time-frequency domain using a specifically designed time-frequency distribution (TFD) that is well adapted to these types of data for the purpose of analysis, detection and classification. The approach to design the quadratic TFDS is based on relating separable-kernel TFDS to DSP spectral window and digital filter design. To reach this goal, we compared recently proposed TFDs such as the Modified B distribution, a separable Gaussian distribution and the B distribution. Then, an extension of the modified B distribution (MBD) is proposed, referred to as the extended separable-kernel MBD. This new TFD uses a separable kernel based on an extension of the modified B kernel in both time and frequency domain with different windows for each domain. Simulation results are provided to compare the proposed Method with different TFDs and to assess its performance. The new TFD is then first applied to real fetal movement data recorded using accelerometers.
{"title":"Design of a high-resolution separable-kernel quadratic TFD for improving newborn health outcomes using fetal movement detection","authors":"B. Boashash, T. B. Jabeur","doi":"10.1109/ISSPA.2012.6310574","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310574","url":null,"abstract":"Prior to birth, fetus health can be monitored by the variety and scale of its movements. In addition, at birth, EEG signals are recorded from at-risk newborns. Studies have shown that both fetal movements and newborn EEGs are non-stationary signals. This paper aims to represent both newborn EEG and fetal movement signals in a time-frequency domain using a specifically designed time-frequency distribution (TFD) that is well adapted to these types of data for the purpose of analysis, detection and classification. The approach to design the quadratic TFDS is based on relating separable-kernel TFDS to DSP spectral window and digital filter design. To reach this goal, we compared recently proposed TFDs such as the Modified B distribution, a separable Gaussian distribution and the B distribution. Then, an extension of the modified B distribution (MBD) is proposed, referred to as the extended separable-kernel MBD. This new TFD uses a separable kernel based on an extension of the modified B kernel in both time and frequency domain with different windows for each domain. Simulation results are provided to compare the proposed Method with different TFDs and to assess its performance. The new TFD is then first applied to real fetal movement data recorded using accelerometers.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128480265","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 : 2012-07-02DOI: 10.1109/ISSPA.2012.6310622
Shou-Chun Yin, R. Rose, Yun Tang
This paper investigates a new approach for detecting phoneme level mispronunciations from utterances obtained from impaired children with neuromuscular disorders. This new pronunciation verification (PV) approach is obtained from the subspace based Gaussian mixture model (SGMM) based pronunciation model, where a set of state level projection vectors is applied for representing phonetic variability. SGMM models are trained from disabled speakers' utterances and PV scores are computed directly from distances between disabled and reference speaker projection vectors. An experimental study was performed to evaluate the performance of the SGMM based approach with respect to an approach based on the lattice posterior probabilities. A reduction in equal error rate (EER) of approximately 15% was obtained when the SGMM based scores were combined with lattice posterior probabilities.
{"title":"A study of applying subspace based pronunciation modeling in verifying pronunciation accuracy","authors":"Shou-Chun Yin, R. Rose, Yun Tang","doi":"10.1109/ISSPA.2012.6310622","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310622","url":null,"abstract":"This paper investigates a new approach for detecting phoneme level mispronunciations from utterances obtained from impaired children with neuromuscular disorders. This new pronunciation verification (PV) approach is obtained from the subspace based Gaussian mixture model (SGMM) based pronunciation model, where a set of state level projection vectors is applied for representing phonetic variability. SGMM models are trained from disabled speakers' utterances and PV scores are computed directly from distances between disabled and reference speaker projection vectors. An experimental study was performed to evaluate the performance of the SGMM based approach with respect to an approach based on the lattice posterior probabilities. A reduction in equal error rate (EER) of approximately 15% was obtained when the SGMM based scores were combined with lattice posterior probabilities.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128699517","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 : 2012-07-02DOI: 10.1109/ISSPA.2012.6310456
Luca Didaci, F. Roli
The co-training algorithm can be applied if a dataset admits a representation into two different feature sets (two views). However, its optimality is proved only under the conditions a) sufficiency of each view, and b) conditional independence given the class. We address the case where condition a) doesn't hold, as often happens in concrete applications. In such cases the co-training is unable to converge to the optimal Bayesian classifier, because samples added in the training set are not distributed according to the class-conditional distributions, even if their assigned label is correct. These results help to better understand the behavior of the co-training algorithm when the classes are only `statistically' separable.
{"title":"A Bayesian analysis of co-training algorithm with insufficient views","authors":"Luca Didaci, F. Roli","doi":"10.1109/ISSPA.2012.6310456","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310456","url":null,"abstract":"The co-training algorithm can be applied if a dataset admits a representation into two different feature sets (two views). However, its optimality is proved only under the conditions a) sufficiency of each view, and b) conditional independence given the class. We address the case where condition a) doesn't hold, as often happens in concrete applications. In such cases the co-training is unable to converge to the optimal Bayesian classifier, because samples added in the training set are not distributed according to the class-conditional distributions, even if their assigned label is correct. These results help to better understand the behavior of the co-training algorithm when the classes are only `statistically' separable.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115956866","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 : 2012-07-02DOI: 10.1109/ISSPA.2012.6310512
L. Potí
Digital processing role in the optical communications is analyzed together with its historical evolution and perspectives. If optical systems at their early stage included weak digital processing in the electrical domain, a fast evolution towards completely all-optical technologies arises due to the bottleneck caused by the electronics bandwidth limitation. With the return of coherent communications, digital processing migrated again back to the electronic domain. Nowadays, algorithm complexity capable of mitigating for linear and nonlinear fibre impairments is becoming unsustainable due to huge level of parallelization and power demand. For such a reason one possible evolution will include processing both in the electronic and optical domain.
{"title":"Digital processing in the optical communications","authors":"L. Potí","doi":"10.1109/ISSPA.2012.6310512","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310512","url":null,"abstract":"Digital processing role in the optical communications is analyzed together with its historical evolution and perspectives. If optical systems at their early stage included weak digital processing in the electrical domain, a fast evolution towards completely all-optical technologies arises due to the bottleneck caused by the electronics bandwidth limitation. With the return of coherent communications, digital processing migrated again back to the electronic domain. Nowadays, algorithm complexity capable of mitigating for linear and nonlinear fibre impairments is becoming unsustainable due to huge level of parallelization and power demand. For such a reason one possible evolution will include processing both in the electronic and optical domain.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"532 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116707988","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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