Pub Date : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553256
Pedro Suárez-Casal, Ó. Fresnedo, L. Castedo
Distributed Quantizer Linear Coding (DQLC) is a joint source-channel coding scheme that encodes and transmits distributed Gaussian sources over a MAC under severe delay constraints, providing significant gains when compared to uncoded transmissions. DQLC, however, relies on the appropriate optimization of its parameters depending on source correlation, channel state and noise variance. In this work, we propose a parameter optimization strategy that relies on the lattice structure of the mapping, reduces the number of parameters to estimate, and exhibits lower computational complexity.
{"title":"DQLC Optimization for Joint Source Channel Coding of Correlated Sources over Fading MAC","authors":"Pedro Suárez-Casal, Ó. Fresnedo, L. Castedo","doi":"10.23919/EUSIPCO.2018.8553256","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553256","url":null,"abstract":"Distributed Quantizer Linear Coding (DQLC) is a joint source-channel coding scheme that encodes and transmits distributed Gaussian sources over a MAC under severe delay constraints, providing significant gains when compared to uncoded transmissions. DQLC, however, relies on the appropriate optimization of its parameters depending on source correlation, channel state and noise variance. In this work, we propose a parameter optimization strategy that relies on the lattice structure of the mapping, reduces the number of parameters to estimate, and exhibits lower computational complexity.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122141704","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 : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553316
J. Leithon, Stefan Werner, V. Koivunen
We propose an energy cost minimization strategy for cooperating households equipped with renewable energy generation and storage capabilities. The participating households minimize their collective energy expenditure by sharing renewable energy through the grid. We assume location and time dependent electricity prices, as well as parametrized transfer fees. We then formulate an optimization problem to minimize the energy cost incurred by the participating households over any specified planning horizon. The proposed strategy serves as a performance benchmark for online energy management algorithms, and can be implemented in real time by incorporating adequate forecasting techniques. We solve the optimization problem through relaxation, and use simulations to illustrate the characteristics of the solution. These simulations show that energy sharing takes place when there are differences in the load/generation and price profiles across participants. We also show that no energy sharing takes place when the load is above the local generation at all times.
{"title":"Cooperative Renewable Energy Management with Distributed Generation","authors":"J. Leithon, Stefan Werner, V. Koivunen","doi":"10.23919/EUSIPCO.2018.8553316","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553316","url":null,"abstract":"We propose an energy cost minimization strategy for cooperating households equipped with renewable energy generation and storage capabilities. The participating households minimize their collective energy expenditure by sharing renewable energy through the grid. We assume location and time dependent electricity prices, as well as parametrized transfer fees. We then formulate an optimization problem to minimize the energy cost incurred by the participating households over any specified planning horizon. The proposed strategy serves as a performance benchmark for online energy management algorithms, and can be implemented in real time by incorporating adequate forecasting techniques. We solve the optimization problem through relaxation, and use simulations to illustrate the characteristics of the solution. These simulations show that energy sharing takes place when there are differences in the load/generation and price profiles across participants. We also show that no energy sharing takes place when the load is above the local generation at all times.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117297532","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 : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553450
Sun Hong Lim, J. Yoo, Sunwoo Kim, J. Choi
In this paper, we propose a low-complexity greedy recovery algorithm which can recover sparse signals with time-varying support. We consider the scenario where the support of the signal (i.e., the indices of nonzero elements) varies smoothly with certain temporal correlation. We model the indices of support as discrete-state Markov random process. Then, we formulate the signal recovery problem as joint estimation of the set of the support indices and the amplitude of nonzero entries based on the multiple measurement vectors. We successively identify the element of the support based on the maximum a posteriori (MAP) criteria and subtract the reconstructed signal component for detection of the next element of the support. Our numerical evaluation shows that the proposed algorithm achieves satisfactory recovery performance at low computational complexity.
{"title":"Greedy Recovery of Sparse Signals with Dynamically Varying Support","authors":"Sun Hong Lim, J. Yoo, Sunwoo Kim, J. Choi","doi":"10.23919/EUSIPCO.2018.8553450","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553450","url":null,"abstract":"In this paper, we propose a low-complexity greedy recovery algorithm which can recover sparse signals with time-varying support. We consider the scenario where the support of the signal (i.e., the indices of nonzero elements) varies smoothly with certain temporal correlation. We model the indices of support as discrete-state Markov random process. Then, we formulate the signal recovery problem as joint estimation of the set of the support indices and the amplitude of nonzero entries based on the multiple measurement vectors. We successively identify the element of the support based on the maximum a posteriori (MAP) criteria and subtract the reconstructed signal component for detection of the next element of the support. Our numerical evaluation shows that the proposed algorithm achieves satisfactory recovery performance at low computational complexity.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129563770","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 : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553541
H. Martinez, Mylène C. Q. Farias, Andrew Hines
Multimedia services play an important role in modern human communication. Understanding the impact of multisensory input (audio and video) on perceived quality is important for optimizing the delivery of these services. This work explores the impact of audio degradations on audio-visual quality. With this goal, we present a new dataset that contains audio-visual sequences with distortions only in the audio component (Im-AV-Exp2). The degradations in this new dataset correspond to commonly encountered streaming degradations, matching those found in the audio-only TCD-VoIP dataset. Using the Immersive Methodology, we perform a subjective experiment with the Im-AV-Exp2 dataset. We analyze the experimental data and compared the quality scores of the Im-AV-Exp2 and TCD-VoIP datasets. Results show that the video component act as a masking factor for certain classes of audio degradations (e.g. echo), showing that there is an interaction of video and audio quality that may depend on content.
{"title":"Perceived quality of audio-visual stimuli containing streaming audio degradations","authors":"H. Martinez, Mylène C. Q. Farias, Andrew Hines","doi":"10.23919/EUSIPCO.2018.8553541","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553541","url":null,"abstract":"Multimedia services play an important role in modern human communication. Understanding the impact of multisensory input (audio and video) on perceived quality is important for optimizing the delivery of these services. This work explores the impact of audio degradations on audio-visual quality. With this goal, we present a new dataset that contains audio-visual sequences with distortions only in the audio component (Im-AV-Exp2). The degradations in this new dataset correspond to commonly encountered streaming degradations, matching those found in the audio-only TCD-VoIP dataset. Using the Immersive Methodology, we perform a subjective experiment with the Im-AV-Exp2 dataset. We analyze the experimental data and compared the quality scores of the Im-AV-Exp2 and TCD-VoIP datasets. Results show that the video component act as a masking factor for certain classes of audio degradations (e.g. echo), showing that there is an interaction of video and audio quality that may depend on content.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129603662","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 : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553550
Abdelhamid Ladaycia, K. Abed-Meraim, Anissa Zergaïnoh-Mokraoui, A. Belouchrani
This paper deals with channel estimation for Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) wireless communications systems. Herein, we propose a semi-blind (SB) subspace channel estimation technique for which an identifiability result is first established for the subspace based criterion. Our algorithm adopts the MIMO-OFDM system model without cyclic prefix and takes advantage of the circulant property of the channel matrix to achieve lower computational complexity and to accelerate the algorithm's convergence by generating a group of sub vectors from each received OFDM symbol. Then, through simulations, we show that the proposed method leads to a significant performance gain as compared to the existing SB subspace methods as well as to the classical last-squares channel estimator.
{"title":"Efficient Semi-Blind Subspace Channel Estimation for MIMO-OFDM System","authors":"Abdelhamid Ladaycia, K. Abed-Meraim, Anissa Zergaïnoh-Mokraoui, A. Belouchrani","doi":"10.23919/EUSIPCO.2018.8553550","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553550","url":null,"abstract":"This paper deals with channel estimation for Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) wireless communications systems. Herein, we propose a semi-blind (SB) subspace channel estimation technique for which an identifiability result is first established for the subspace based criterion. Our algorithm adopts the MIMO-OFDM system model without cyclic prefix and takes advantage of the circulant property of the channel matrix to achieve lower computational complexity and to accelerate the algorithm's convergence by generating a group of sub vectors from each received OFDM symbol. Then, through simulations, we show that the proposed method leads to a significant performance gain as compared to the existing SB subspace methods as well as to the classical last-squares channel estimator.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128977110","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 : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553042
Tarek Gueham, Fatiha Merazka
This paper focuses on AMR WB G.722.2 speech codec, and discusses the unused bandwidth resources of the senders by using a Word16(16 bit) to encode the sent frames. A packet loss concealment (PLC) method for G.722.2 speech codec is proposed in order to overcome this problem and increases the efficiency of this codec by improving the quality of decoded speech under burst frame loss conditions over frame-switched networks. Objective and subjective experimental results confirm that our proposed algorithm could achieve better speech quality. Our proposed method achieves a PESQ value higher than 2 at 20% frame erasure rate and ensure the compatibility between our modified decoder and the non-modified G.722.2 coder.
{"title":"An Enhanced Interleaving Frame Loss Concealment Method for Voice Over IP Network Services","authors":"Tarek Gueham, Fatiha Merazka","doi":"10.23919/EUSIPCO.2018.8553042","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553042","url":null,"abstract":"This paper focuses on AMR WB G.722.2 speech codec, and discusses the unused bandwidth resources of the senders by using a Word16(16 bit) to encode the sent frames. A packet loss concealment (PLC) method for G.722.2 speech codec is proposed in order to overcome this problem and increases the efficiency of this codec by improving the quality of decoded speech under burst frame loss conditions over frame-switched networks. Objective and subjective experimental results confirm that our proposed algorithm could achieve better speech quality. Our proposed method achieves a PESQ value higher than 2 at 20% frame erasure rate and ensure the compatibility between our modified decoder and the non-modified G.722.2 coder.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129019528","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 : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553095
M. H. Jomaa, P. Bogaert, N. Jrad, M. A. Colominas, A. Humeau-Heurtier
In this paper, we propose a new algorithm to calculate sample entropy of multivariate data. Over the existing method, the one proposed here has the advantage of maintaining good results as the number of channels increases. The new and already-existing algorithms were applied on multivariate white Gaussian noise signals, pink noise signals, and mixtures of both. For high number of channels, the existing method failed to show that white noise is always the most irregular whereas the proposed method always had the entropy of white noise the highest. Application of both algorithms on MIX process signals also confirmed the ability of the proposed method to handle larger number of channels without risking erroneous results. We also applied the proposed algorithm on EEG data from epileptic patients before and after treatments. The results showed an increase in entropy values after treatment in the regions where the focus was localized. This goes in the same way as the medical point of view that indicated a better health state for these patients.
{"title":"A New Approach to Sample Entropy of Multi-channel Signals: Application to EEG Signals","authors":"M. H. Jomaa, P. Bogaert, N. Jrad, M. A. Colominas, A. Humeau-Heurtier","doi":"10.23919/EUSIPCO.2018.8553095","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553095","url":null,"abstract":"In this paper, we propose a new algorithm to calculate sample entropy of multivariate data. Over the existing method, the one proposed here has the advantage of maintaining good results as the number of channels increases. The new and already-existing algorithms were applied on multivariate white Gaussian noise signals, pink noise signals, and mixtures of both. For high number of channels, the existing method failed to show that white noise is always the most irregular whereas the proposed method always had the entropy of white noise the highest. Application of both algorithms on MIX process signals also confirmed the ability of the proposed method to handle larger number of channels without risking erroneous results. We also applied the proposed algorithm on EEG data from epileptic patients before and after treatments. The results showed an increase in entropy values after treatment in the regions where the focus was localized. This goes in the same way as the medical point of view that indicated a better health state for these patients.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129273391","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 : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553103
N. Stefanakis, Symeon Delikaris-Manias, A. Mouchtaris
In this paper, we consider the problem of beamforming with a planar microphone array placed in front of a wall of the room, so that the microphone array plane is perpendicular to that of the wall. While this situation is very likely to occur in a real life problem, the reflections introduced by the adjacent wall can be the cause of a serious mismatch between the actual acoustic paths and the traditionally employed free-field propagation model. We present an adaptation from the free-field to the so-called reflection-aware propagation model, that exploits an in-situ estimation of the complex and frequency-dependent wall reflectivity. Results presented in a real environment demonstrate that the proposed approach may bring significant improvements to the beamforming process compared to the free-field propagation model, as well as compared to other reflection-aware models that have been recently proposed.
{"title":"Acoustic Beamforming in Front of a Reflective Plane","authors":"N. Stefanakis, Symeon Delikaris-Manias, A. Mouchtaris","doi":"10.23919/EUSIPCO.2018.8553103","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553103","url":null,"abstract":"In this paper, we consider the problem of beamforming with a planar microphone array placed in front of a wall of the room, so that the microphone array plane is perpendicular to that of the wall. While this situation is very likely to occur in a real life problem, the reflections introduced by the adjacent wall can be the cause of a serious mismatch between the actual acoustic paths and the traditionally employed free-field propagation model. We present an adaptation from the free-field to the so-called reflection-aware propagation model, that exploits an in-situ estimation of the complex and frequency-dependent wall reflectivity. Results presented in a real environment demonstrate that the proposed approach may bring significant improvements to the beamforming process compared to the free-field propagation model, as well as compared to other reflection-aware models that have been recently proposed.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123943065","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 : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553101
Pauline Puteaux, W. Puech
Many techniques have been presented to protect image content confidentiality. The owner of an image encrypts it using a key and transmits the encrypted image across a network. If the recipient is authorized to access the original content of the image, he can reconstruct it losslessly. However, if during the transmission the encrypted image is noised, some parts of the image can not be deciphered. In order to localize and correct these errors, we propose an approach based on the local Shannon entropy measurement. We first analyze this measure as a function of the block-size. We provide then a full description of our blind error localization and removal process. Experimental results show that the proposed approach, based on local entropy, can be used in practice to correct noisy encrypted images, even with blocks of very small size.
{"title":"Noisy Encrypted Image Correction based on Shannon Entropy Measurement in Pixel Blocks of Very Small Size","authors":"Pauline Puteaux, W. Puech","doi":"10.23919/EUSIPCO.2018.8553101","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553101","url":null,"abstract":"Many techniques have been presented to protect image content confidentiality. The owner of an image encrypts it using a key and transmits the encrypted image across a network. If the recipient is authorized to access the original content of the image, he can reconstruct it losslessly. However, if during the transmission the encrypted image is noised, some parts of the image can not be deciphered. In order to localize and correct these errors, we propose an approach based on the local Shannon entropy measurement. We first analyze this measure as a function of the block-size. We provide then a full description of our blind error localization and removal process. Experimental results show that the proposed approach, based on local entropy, can be used in practice to correct noisy encrypted images, even with blocks of very small size.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123961085","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 : 2018-09-01DOI: 10.23919/EUSIPCO.2018.8553204
Maria Sandsten, Johan Brynolfsson, Isabella Reinhold
In this paper we calculate reassigned spectrograms using the envelope of an arbitrary signal as matched window. We show that the matched window then give the perfectly localized reassignment for any time-translated and frequency-modulated transient signal with corresponding envelope. The general expressions of the corresponding scaled reassignment vectors are derived and the matched window reassignment is evaluated for time-frequency localization as well as for classification. The results show that the accuracy in time- and frequency location is high also when the signal envelope deviates from the matched window and when the SNR is reasonable large. The classification performance based on the matched window reassignment and the Rényi entropy is robust to signal envelope deviations as well as to disturbing noise.
{"title":"The Matched Window Reassignment","authors":"Maria Sandsten, Johan Brynolfsson, Isabella Reinhold","doi":"10.23919/EUSIPCO.2018.8553204","DOIUrl":"https://doi.org/10.23919/EUSIPCO.2018.8553204","url":null,"abstract":"In this paper we calculate reassigned spectrograms using the envelope of an arbitrary signal as matched window. We show that the matched window then give the perfectly localized reassignment for any time-translated and frequency-modulated transient signal with corresponding envelope. The general expressions of the corresponding scaled reassignment vectors are derived and the matched window reassignment is evaluated for time-frequency localization as well as for classification. The results show that the accuracy in time- and frequency location is high also when the signal envelope deviates from the matched window and when the SNR is reasonable large. The classification performance based on the matched window reassignment and the Rényi entropy is robust to signal envelope deviations as well as to disturbing noise.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123623581","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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