Pub Date : 2006-07-09DOI: 10.1109/ICME.2006.262762
Chao-Yang Kao, Huang-Chih Kuo, Y. Lin
We propose a high performance architecture for fractional motion estimation and Lagrange mode decision in H.264/AVC. Instead of time-consuming fractional-pixel interpolation and secondary search, our fractional motion estimator employees a mathematical model to estimate SADs at quarter-pixel position. Both computation time and memory access requirements are greatly reduced without significant quality degradation. We propose a novel cost function for mode decision that leads to much better performance than traditional low complexity method. Synthesized into a TSMC 0.13 mum CMOS technology, our design takes 56 k gates at 100 MHz and is sufficient to process QUXGA (3200times2400) video sequences at 30 frames per second (fps). Compared with a state-of-the-art design operating under the same frequency, ours is 30% smaller and has 18 times more throughput at the expense of only 0.05 db in PSNR difference
提出了H.264/AVC中分数阶运动估计和拉格朗日模式判定的高性能体系结构。我们的分数运动估计器采用数学模型来估计四分之一像素位置的SADs，而不是耗时的分数像素插值和二次搜索。计算时间和内存访问需求都大大降低，而质量没有明显下降。我们提出了一种新的模式决策成本函数，它比传统的低复杂度方法具有更好的性能。我们的设计采用台积电0.13 mum CMOS技术合成，在100 MHz下使用56 k门，足以以每秒30帧(fps)的速度处理QUXGA(3200次2400)视频序列。与在相同频率下工作的最先进的设计相比，我们的设计体积缩小了30%，吞吐量提高了18倍，而PSNR差异仅为0.05 db
{"title":"High Performance Fractional Motion Estimation and Mode Decision for H.264/AVC","authors":"Chao-Yang Kao, Huang-Chih Kuo, Y. Lin","doi":"10.1109/ICME.2006.262762","DOIUrl":"https://doi.org/10.1109/ICME.2006.262762","url":null,"abstract":"We propose a high performance architecture for fractional motion estimation and Lagrange mode decision in H.264/AVC. Instead of time-consuming fractional-pixel interpolation and secondary search, our fractional motion estimator employees a mathematical model to estimate SADs at quarter-pixel position. Both computation time and memory access requirements are greatly reduced without significant quality degradation. We propose a novel cost function for mode decision that leads to much better performance than traditional low complexity method. Synthesized into a TSMC 0.13 mum CMOS technology, our design takes 56 k gates at 100 MHz and is sufficient to process QUXGA (3200times2400) video sequences at 30 frames per second (fps). Compared with a state-of-the-art design operating under the same frequency, ours is 30% smaller and has 18 times more throughput at the expense of only 0.05 db in PSNR difference","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132680272","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 : 2006-07-09DOI: 10.1109/ICME.2006.262468
Xiang Ma, F. Bashir, A. Khokhar, D. Schonfeld
This paper presents novel tensor-based object trajectory modelling techniques for simultaneous representation of multiple objects motion trajectories in a content based indexing and retrieval framework. Three different tensor decomposition techniques-PARAFAC, HOSVD and multiple-SVD-are explored to achieve this goal with the aim of using a minimum set of coefficients and data-dependant bases. These tensor decompositions have been applied to represent full as well as segmented trajectories. Our simulation results show that the PARAFAC-based representation provides higher compression ratio, superior precision-recall metrics, and smaller query processing time compared to the other tensor-based approaches
{"title":"Tensor-Based Multiple Object Trajectory Indexing and Retrieval","authors":"Xiang Ma, F. Bashir, A. Khokhar, D. Schonfeld","doi":"10.1109/ICME.2006.262468","DOIUrl":"https://doi.org/10.1109/ICME.2006.262468","url":null,"abstract":"This paper presents novel tensor-based object trajectory modelling techniques for simultaneous representation of multiple objects motion trajectories in a content based indexing and retrieval framework. Three different tensor decomposition techniques-PARAFAC, HOSVD and multiple-SVD-are explored to achieve this goal with the aim of using a minimum set of coefficients and data-dependant bases. These tensor decompositions have been applied to represent full as well as segmented trajectories. Our simulation results show that the PARAFAC-based representation provides higher compression ratio, superior precision-recall metrics, and smaller query processing time compared to the other tensor-based approaches","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123161332","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 : 2006-07-09DOI: 10.1109/ICME.2006.262953
Oge Marques, Liam M. Mayron, G. Borba, H. Gamba
Content-based image retrieval (CBIR) systems have been actively investigated over the past decade. Several existing CBIR prototypes claim to be designed based on perceptual characteristics of the human visual system, but even those who do are far from recognizing that they could benefit further by incorporating ongoing research in vision science. This paper explores the inclusion of human visual perception knowledge into the design and implementation of CBIR systems. Particularly, it addresses the latest developments in computational modeling of human visual attention. This fresh way of revisiting concepts in CBIR based on the latest findings and open questions in vision science research has the potential to overcome some of the challenges faced by CBIR systems
{"title":"On the Potential of Incorporating Knowledge of Human Visual Attention into Cbir Systems","authors":"Oge Marques, Liam M. Mayron, G. Borba, H. Gamba","doi":"10.1109/ICME.2006.262953","DOIUrl":"https://doi.org/10.1109/ICME.2006.262953","url":null,"abstract":"Content-based image retrieval (CBIR) systems have been actively investigated over the past decade. Several existing CBIR prototypes claim to be designed based on perceptual characteristics of the human visual system, but even those who do are far from recognizing that they could benefit further by incorporating ongoing research in vision science. This paper explores the inclusion of human visual perception knowledge into the design and implementation of CBIR systems. Particularly, it addresses the latest developments in computational modeling of human visual attention. This fresh way of revisiting concepts in CBIR based on the latest findings and open questions in vision science research has the potential to overcome some of the challenges faced by CBIR systems","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131422303","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 : 2006-07-09DOI: 10.1109/ICME.2006.262713
B. Qiu, Chang Xu, Q. Tian
In this paper, a multi-class classification system is developed for medical images. We have mainly explored ways to use different image features, and compared two classifiers: principle component analysis (PCA) and supporting vector machines (SVM) with RBF (radial basis functions) kernels. Experimental results showed that SVM with a combination of the middle-level blob feature and low-level features (down-scaled images and their texture maps) achieved the highest recognition accuracy. Using the 9000 given training images from ImageCLEFOS, our proposed method has achieved a recognition rate of 88.9% in a simulation experiment. And according to the evaluation result from the ImageCLEFOS organizer, our method has achieved a recognition rate of 82% over its 1000 testing images
{"title":"An Automatic Classification System Applied in Medical Images","authors":"B. Qiu, Chang Xu, Q. Tian","doi":"10.1109/ICME.2006.262713","DOIUrl":"https://doi.org/10.1109/ICME.2006.262713","url":null,"abstract":"In this paper, a multi-class classification system is developed for medical images. We have mainly explored ways to use different image features, and compared two classifiers: principle component analysis (PCA) and supporting vector machines (SVM) with RBF (radial basis functions) kernels. Experimental results showed that SVM with a combination of the middle-level blob feature and low-level features (down-scaled images and their texture maps) achieved the highest recognition accuracy. Using the 9000 given training images from ImageCLEFOS, our proposed method has achieved a recognition rate of 88.9% in a simulation experiment. And according to the evaluation result from the ImageCLEFOS organizer, our method has achieved a recognition rate of 82% over its 1000 testing images","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127400596","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 : 2006-07-09DOI: 10.1109/ICME.2006.262908
Aijuan Dong, Honglin Li
Many documentary videos use background music to help structure the content and communicate the semantic. In this paper, we investigate semantic segmentation of documentary video using music breaks. We first define video semantic units based on the speech text that a video/audio contains, and then propose a three-step procedure for semantic video segmentation using music breaks. Since the music breaks of a documentary video are of different semantic levels, we also study how different speech/music segment lengths correlate with the semantic level of a music break. Our experimental results show that music breaks can effectively segment a continuous documentary video stream into semantic units with an average F-score of 0.91 and the lengths of combined segments (speech segment plus the music segment that follows) strongly correlate with the semantic levels of music breaks
{"title":"Semantic Segmentation of Documentary Video using Music Breaks","authors":"Aijuan Dong, Honglin Li","doi":"10.1109/ICME.2006.262908","DOIUrl":"https://doi.org/10.1109/ICME.2006.262908","url":null,"abstract":"Many documentary videos use background music to help structure the content and communicate the semantic. In this paper, we investigate semantic segmentation of documentary video using music breaks. We first define video semantic units based on the speech text that a video/audio contains, and then propose a three-step procedure for semantic video segmentation using music breaks. Since the music breaks of a documentary video are of different semantic levels, we also study how different speech/music segment lengths correlate with the semantic level of a music break. Our experimental results show that music breaks can effectively segment a continuous documentary video stream into semantic units with an average F-score of 0.91 and the lengths of combined segments (speech segment plus the music segment that follows) strongly correlate with the semantic levels of music breaks","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124339961","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 : 2006-07-09DOI: 10.1109/ICME.2006.262892
A. Haubold, A. Natsev, M. Naphade
We present methods for improving text search retrieval of visual multimedia content by applying a set of visual models of semantic concepts from a lexicon of concepts deemed relevant for the collection. Text search is performed via queries of words or fully qualified sentences, and results are returned in the form of ranked video clips. Our approach involves a query expansion stage, in which query terms are compared to the visual concepts for which we independently build classifier models. We leverage a synonym dictionary and WordNet similarities during expansion. Results over each query are aggregated across the expanded terms and ranked. We validate our approach on the TRECVID 2005 broadcast news data with 39 concepts specifically designed for this genre of video. We observe that concept models improve search results by nearly 50% after model-based re-ranking of text-only search. We also observe that purely model-based retrieval significantly outperforms text-based retrieval on non-named entity queries
{"title":"Semantic Multimedia Retrieval using Lexical Query Expansion and Model-Based Reranking","authors":"A. Haubold, A. Natsev, M. Naphade","doi":"10.1109/ICME.2006.262892","DOIUrl":"https://doi.org/10.1109/ICME.2006.262892","url":null,"abstract":"We present methods for improving text search retrieval of visual multimedia content by applying a set of visual models of semantic concepts from a lexicon of concepts deemed relevant for the collection. Text search is performed via queries of words or fully qualified sentences, and results are returned in the form of ranked video clips. Our approach involves a query expansion stage, in which query terms are compared to the visual concepts for which we independently build classifier models. We leverage a synonym dictionary and WordNet similarities during expansion. Results over each query are aggregated across the expanded terms and ranked. We validate our approach on the TRECVID 2005 broadcast news data with 39 concepts specifically designed for this genre of video. We observe that concept models improve search results by nearly 50% after model-based re-ranking of text-only search. We also observe that purely model-based retrieval significantly outperforms text-based retrieval on non-named entity queries","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114833969","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 : 2006-07-09DOI: 10.1109/ICME.2006.262869
Yu Wang, Lap-Pui Chau, Kim-Hui Yap
A scalable video coder generates scalable compressed bit-stream, which can provide different types of scalability depend on different requirements. This paper proposes a novel resynchronization method for the scalable video with combined temporal and quality (SNR) scalability. The main purpose is to improve the robustness of the transmitted video. In the proposed scheme, the video is encoded into scalable compressed bit-stream with combined temporal and quality scalability. The significance of each enhancement layer unit is estimated properly. A novel resynchronization method is proposed where joint group of picture (GOP) level and picture level insertion of resynchronization marker approach is applied to insert different amount of resynchronization markers in different enhancement layer units for reliable transmission of the video over error-prone channels. It is demonstrated from the experimental results that the proposed method can perform graceful degradation under a variety of error conditions and the improvement can be up to 1 dB compared with the conventional method
可伸缩的视频编码器生成可伸缩的压缩比特流，可以根据不同的需求提供不同类型的可扩展性。提出了一种具有时间和质量(信噪比)相结合可扩展性的视频重同步方法。其主要目的是提高传输视频的鲁棒性。在该方案中，视频被编码成可伸缩的压缩比特流，具有时间和质量的可扩展性。适当地估计了各增强层单元的重要性。提出了一种新的重同步方法，该方法采用图像级联合组(GOP)和图像级插入重同步标记的方法，在不同的增强层单元中插入不同数量的重同步标记，以保证视频在易出错信道上的可靠传输。实验结果表明，该方法在各种误差条件下都能实现优雅的退化，与传统方法相比，改进幅度可达1 dB
{"title":"A Novel Resynchronization Method for Scalable Video Over Wireless Channel","authors":"Yu Wang, Lap-Pui Chau, Kim-Hui Yap","doi":"10.1109/ICME.2006.262869","DOIUrl":"https://doi.org/10.1109/ICME.2006.262869","url":null,"abstract":"A scalable video coder generates scalable compressed bit-stream, which can provide different types of scalability depend on different requirements. This paper proposes a novel resynchronization method for the scalable video with combined temporal and quality (SNR) scalability. The main purpose is to improve the robustness of the transmitted video. In the proposed scheme, the video is encoded into scalable compressed bit-stream with combined temporal and quality scalability. The significance of each enhancement layer unit is estimated properly. A novel resynchronization method is proposed where joint group of picture (GOP) level and picture level insertion of resynchronization marker approach is applied to insert different amount of resynchronization markers in different enhancement layer units for reliable transmission of the video over error-prone channels. It is demonstrated from the experimental results that the proposed method can perform graceful degradation under a variety of error conditions and the improvement can be up to 1 dB compared with the conventional method","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"564 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116285907","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 : 2006-07-09DOI: 10.1109/ICME.2006.262554
Xiaorong Li, T. Hung, B. Veeravalli
In this paper, we proposed to setup a distributed multimedia system which aggregates the capacity of multiple servers to provide customized multimedia services in a cost-effective way. Such a system enables clients to customize their services by specifying the service delay or the viewing times. We developed an experimental prototype in which media servers can cooperate in streams caching, replication and distribution. We applied a variety of stream distribution algorithms to the system and studied their performance under the real-life situations with limited network resources and varying request arrival pattern. The results show such a system can provide cost-effective services and be applied to practical environments
{"title":"Design and Implementation of a Multimedia Personalized Service Over Large Scale Networks","authors":"Xiaorong Li, T. Hung, B. Veeravalli","doi":"10.1109/ICME.2006.262554","DOIUrl":"https://doi.org/10.1109/ICME.2006.262554","url":null,"abstract":"In this paper, we proposed to setup a distributed multimedia system which aggregates the capacity of multiple servers to provide customized multimedia services in a cost-effective way. Such a system enables clients to customize their services by specifying the service delay or the viewing times. We developed an experimental prototype in which media servers can cooperate in streams caching, replication and distribution. We applied a variety of stream distribution algorithms to the system and studied their performance under the real-life situations with limited network resources and varying request arrival pattern. The results show such a system can provide cost-effective services and be applied to practical environments","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116353231","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 : 2006-07-09DOI: 10.1109/ICME.2006.262677
K. Otsuka, Junji Yamato, Y. Takemae, H. Murase
A novel method based on a probabilistic model for conversation scene analysis is proposed that can infer conversation structure from video sequences of face-to-face communication. Conversation structure represents the type of conversation such as monologue or dialogue, and can indicate who is talking/listening to whom. This study assumes that the gaze directions of participants provide cues for discerning the conversation structure, and can be identified from head directions. For measuring head directions, the proposed method newly employs a visual head tracker based on sparse-template condensation. The conversation model is built on a dynamic Bayesian network and is used to estimate the conversation structure and gaze directions from observed head directions and utterances. Visual tracking is conventionally thought to be less reliable than contact sensors, but experiments confirm that the proposed method achieves almost comparable performance in estimating gaze directions and conversation structure to a conventional sensor-based method
{"title":"Conversation Scene Analysis with Dynamic Bayesian Network Basedon Visual Head Tracking","authors":"K. Otsuka, Junji Yamato, Y. Takemae, H. Murase","doi":"10.1109/ICME.2006.262677","DOIUrl":"https://doi.org/10.1109/ICME.2006.262677","url":null,"abstract":"A novel method based on a probabilistic model for conversation scene analysis is proposed that can infer conversation structure from video sequences of face-to-face communication. Conversation structure represents the type of conversation such as monologue or dialogue, and can indicate who is talking/listening to whom. This study assumes that the gaze directions of participants provide cues for discerning the conversation structure, and can be identified from head directions. For measuring head directions, the proposed method newly employs a visual head tracker based on sparse-template condensation. The conversation model is built on a dynamic Bayesian network and is used to estimate the conversation structure and gaze directions from observed head directions and utterances. Visual tracking is conventionally thought to be less reliable than contact sensors, but experiments confirm that the proposed method achieves almost comparable performance in estimating gaze directions and conversation structure to a conventional sensor-based method","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123445965","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 : 2006-07-09DOI: 10.1109/ICME.2006.262847
P. Martins, P. Carvalho
A robust image watermarking scheme relying on an affine invariant embedding domain is presented. The invariant space is obtained by triangulating the image using affine invariant interest points as vertices and performing an invariant triangle representation with respect to affine transformations based on the barycentric coordinates system. The watermark is encoded via quantization index modulation with an adaptive quantization step
{"title":"A Robust Imagewatermarking Scheme Based on the Alpha-Beta Space","authors":"P. Martins, P. Carvalho","doi":"10.1109/ICME.2006.262847","DOIUrl":"https://doi.org/10.1109/ICME.2006.262847","url":null,"abstract":"A robust image watermarking scheme relying on an affine invariant embedding domain is presented. The invariant space is obtained by triangulating the image using affine invariant interest points as vertices and performing an invariant triangle representation with respect to affine transformations based on the barycentric coordinates system. The watermark is encoded via quantization index modulation with an adaptive quantization step","PeriodicalId":339258,"journal":{"name":"2006 IEEE International Conference on Multimedia and Expo","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122041362","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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