Pub Date : 2012-12-13DOI: 10.1109/RSP.2012.6380686
V. Fresse, Zhiwei Ge, Junyan Tan, F. Rousseau
The evaluation of Network-On-Chip (NoC) architectures is an up to date problem in the design of System-on-Chip. Emulation on FPGA (Field Programmable Gate Array) is used to cover all possible NoC solutions in a reduced exploration time. Emulation requires multi-FPGA platform as the resources for large NoC is important and cannot be handling by one FPGA. In the same time, SoC community is exploring 3D technology for the next generation of large SoC with 3D NoC, making emulation more complex. This paper presents a case study of the deployment of the 2D NoC structure to 3D. A design flow is proposed for the automatic generation of a NoC targeting 3D on multi-FPGAs. The flow integrates emulation blocks used for the validation and exploration on the NoC. With this automatic aided tool, the designer can evaluate and explore the NoC architecture and extract performances of the NoC regardless of the multi-component platform. One may expect a communication performance improvement using an adapted partitioning of the NoC, as highlighted by the results given in this paper.
{"title":"Case study: Deployment of the 2D NoC on 3D for the generation of large emulation platforms","authors":"V. Fresse, Zhiwei Ge, Junyan Tan, F. Rousseau","doi":"10.1109/RSP.2012.6380686","DOIUrl":"https://doi.org/10.1109/RSP.2012.6380686","url":null,"abstract":"The evaluation of Network-On-Chip (NoC) architectures is an up to date problem in the design of System-on-Chip. Emulation on FPGA (Field Programmable Gate Array) is used to cover all possible NoC solutions in a reduced exploration time. Emulation requires multi-FPGA platform as the resources for large NoC is important and cannot be handling by one FPGA. In the same time, SoC community is exploring 3D technology for the next generation of large SoC with 3D NoC, making emulation more complex. This paper presents a case study of the deployment of the 2D NoC structure to 3D. A design flow is proposed for the automatic generation of a NoC targeting 3D on multi-FPGAs. The flow integrates emulation blocks used for the validation and exploration on the NoC. With this automatic aided tool, the designer can evaluate and explore the NoC architecture and extract performances of the NoC regardless of the multi-component platform. One may expect a communication performance improvement using an adapted partitioning of the NoC, as highlighted by the results given in this paper.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130835441","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 : 2012-10-15DOI: 10.1109/IPTA.2012.6469529
V. Amarger, D. Ramík, C. Sabourin, K. Madani, Ramón Moreno, L. Rossi, M. Graña
Wildland fires represent a major risk for many countries over the world. For efficient fire fighting, the modeling and prediction of fire front propagation is a curial need. However, wildland fires' involves complex dynamics and mathematical modelling of such complex systems needs reliable information extraction from real situations, which is far from being a trivial task. Artificial Vision and Image Processing offer appealing potential toward reliable extraction of required information. In this paper we focus on flames' and fires' segmentation, dealing with the above-stated already open problem. The segmentation approach that we propose is based on dichromatic reflection model reformulated on a spherical interpretation of the RGB color space.
{"title":"Spherical coordinates framed RGB color space dichromatic reflection model based image segmentation: Application to wildland fires' outlines extraction","authors":"V. Amarger, D. Ramík, C. Sabourin, K. Madani, Ramón Moreno, L. Rossi, M. Graña","doi":"10.1109/IPTA.2012.6469529","DOIUrl":"https://doi.org/10.1109/IPTA.2012.6469529","url":null,"abstract":"Wildland fires represent a major risk for many countries over the world. For efficient fire fighting, the modeling and prediction of fire front propagation is a curial need. However, wildland fires' involves complex dynamics and mathematical modelling of such complex systems needs reliable information extraction from real situations, which is far from being a trivial task. Artificial Vision and Image Processing offer appealing potential toward reliable extraction of required information. In this paper we focus on flames' and fires' segmentation, dealing with the above-stated already open problem. The segmentation approach that we propose is based on dichromatic reflection model reformulated on a spherical interpretation of the RGB color space.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"224 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124454346","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 : 2012-10-15DOI: 10.1109/IPTA.2012.6469512
L. Rossi, M. Akhloufi, A. Pieri, Jean-Louis Rossi, T. Molinier
This paper presents a work conducted in the field of image processing and computer vision in order to measure geometrical characteristics of spreading fires; this allows understanding the phenomenon occurring during the propagation and improving and/or validating mathematical models by comparing experimental data with numerical ones. In order to develop a metrological system based on vision for wildland fires, it is necessary to solve scientific locks that are also presented in this paper.
{"title":"Image processing and vision for the study and the modeling of spreading fires","authors":"L. Rossi, M. Akhloufi, A. Pieri, Jean-Louis Rossi, T. Molinier","doi":"10.1109/IPTA.2012.6469512","DOIUrl":"https://doi.org/10.1109/IPTA.2012.6469512","url":null,"abstract":"This paper presents a work conducted in the field of image processing and computer vision in order to measure geometrical characteristics of spreading fires; this allows understanding the phenomenon occurring during the propagation and improving and/or validating mathematical models by comparing experimental data with numerical ones. In order to develop a metrological system based on vision for wildland fires, it is necessary to solve scientific locks that are also presented in this paper.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124709617","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 : 2012-10-15DOI: 10.1109/IPTA.2012.6469507
Nefissa Khiari Hili, S. Lelandais, Christophe Montagne, K. Hamrouni
It is often difficult to deal with the problem of 2D-face recognition under unconstrained conditions. The objective of this study is to develop an original method that overcomes such obstructions. The proposed approach combines a holistic method, the Principal Component Analysis (PCA) to a local method, the Steerable Pyramid (SP). All tests were run on IV2 database, with challenging variability and including 3500 to 5000 comparisons by experiment from 315 different people. The followed protocol was established in the first evaluation campaign on 2D-face images using the multimodal IV2 database. Comparison with five submitted algorithms as PCA, LDA and LDA/Gabor provides satisfying results.
{"title":"A combining approach for 2D face recognition application on IV2 database","authors":"Nefissa Khiari Hili, S. Lelandais, Christophe Montagne, K. Hamrouni","doi":"10.1109/IPTA.2012.6469507","DOIUrl":"https://doi.org/10.1109/IPTA.2012.6469507","url":null,"abstract":"It is often difficult to deal with the problem of 2D-face recognition under unconstrained conditions. The objective of this study is to develop an original method that overcomes such obstructions. The proposed approach combines a holistic method, the Principal Component Analysis (PCA) to a local method, the Steerable Pyramid (SP). All tests were run on IV2 database, with challenging variability and including 3500 to 5000 comparisons by experiment from 315 different people. The followed protocol was established in the first evaluation campaign on 2D-face images using the multimodal IV2 database. Comparison with five submitted algorithms as PCA, LDA and LDA/Gabor provides satisfying results.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115422021","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 : 2012-10-01DOI: 10.1109/IPTA.2012.6469516
F. Tavard, A. Simon, Alfredo I. Hernández, J. Betancur, E. Donal, M. Garreau
Cardiac Resynchronization Therapy (CRT) can be optimized by the fusion of anatomical, functional and electrical information in a unified framework in order to identify the most effective pacing sites. The aim of this work is to perform a registration between dynamic CT and ultrasound (US) images (2D speckle tracking mode). The proposed registration approach is based on a contour to surface scheme, decomposed in four steps: (1) the temporal synchronization of data; (2) the segmentation of the left ventricle endocardial surface from the 3D+t CT data; (3) the segmentation and tracking of the myocardium from the 2D+t US data; (4) the registration of US contour with the CT surface. The originality of the method relies on the use of Fourier descriptors and Dynamic Time Warping (DTW) to handle different spatial and temporal resolutions as well as dissimilar cardiac rhythms between CT and US data. An evaluation on simulated data is described as well as results obtained on three patient databases.
{"title":"Dynamic registration of cardiac US and CT data using Fourier descriptors and Dynamic Time Warping","authors":"F. Tavard, A. Simon, Alfredo I. Hernández, J. Betancur, E. Donal, M. Garreau","doi":"10.1109/IPTA.2012.6469516","DOIUrl":"https://doi.org/10.1109/IPTA.2012.6469516","url":null,"abstract":"Cardiac Resynchronization Therapy (CRT) can be optimized by the fusion of anatomical, functional and electrical information in a unified framework in order to identify the most effective pacing sites. The aim of this work is to perform a registration between dynamic CT and ultrasound (US) images (2D speckle tracking mode). The proposed registration approach is based on a contour to surface scheme, decomposed in four steps: (1) the temporal synchronization of data; (2) the segmentation of the left ventricle endocardial surface from the 3D+t CT data; (3) the segmentation and tracking of the myocardium from the 2D+t US data; (4) the registration of US contour with the CT surface. The originality of the method relies on the use of Fourier descriptors and Dynamic Time Warping (DTW) to handle different spatial and temporal resolutions as well as dissimilar cardiac rhythms between CT and US data. An evaluation on simulated data is described as well as results obtained on three patient databases.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"268 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122984635","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 : 2012-10-01DOI: 10.1109/IPTA.2012.6469572
Ali Musa Kazmi, N. I. Rao, Fawad Fazal, Muhammad Faisal Khan
The problem of depth estimation from one or more image(s) is most frequently discussed in computer vision using binocular cues, motion parallax or monocular cues. In this paper, we exploited a scene calibration mechanism for estimating depth from a single image, with emphasis on motorways. The approach incorporates linear perspective depth cue to restore distance information of vehicle(s) from a given image. Based upon the assumption that linear perspective is available in ample amount in structured environments, proposed approach computes 1D projective transformation across ground plane which maps imaged distances to the corresponding real-world distances. Once the homography matrix for 1D projective transformation is available, it can be applied to any point to compute its straight line distance from the reference point. Experimental results show that the proposed approach is computationally efficient and delivers desirably accurate depth estimates; thus, it has been applied to identify over-speedings.
{"title":"Exploiting a scene calibration mechanism for depth estimation","authors":"Ali Musa Kazmi, N. I. Rao, Fawad Fazal, Muhammad Faisal Khan","doi":"10.1109/IPTA.2012.6469572","DOIUrl":"https://doi.org/10.1109/IPTA.2012.6469572","url":null,"abstract":"The problem of depth estimation from one or more image(s) is most frequently discussed in computer vision using binocular cues, motion parallax or monocular cues. In this paper, we exploited a scene calibration mechanism for estimating depth from a single image, with emphasis on motorways. The approach incorporates linear perspective depth cue to restore distance information of vehicle(s) from a given image. Based upon the assumption that linear perspective is available in ample amount in structured environments, proposed approach computes 1D projective transformation across ground plane which maps imaged distances to the corresponding real-world distances. Once the homography matrix for 1D projective transformation is available, it can be applied to any point to compute its straight line distance from the reference point. Experimental results show that the proposed approach is computationally efficient and delivers desirably accurate depth estimates; thus, it has been applied to identify over-speedings.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129078955","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 : 2012-10-01DOI: 10.1109/IPTA.2012.6469542
M. Caon, J. Tscherrig, Yong Yue, Omar Abou Khaled, E. Mugellini
This paper presents a non-intrusive approach for view-invariant hand gesture recognition. In fact, the representation of gestures changes dynamically depending on camera viewpoints. Therefore, the different positions of the user between the training phase and the evaluation phase can severely compromise the recognition process. The proposed approach involves the calibration of two Microsoft Kinect depth cameras to allow the 3D modeling of the dynamic hands movements. The gestures are modeled as 3D trajectories and the classification is based on Hidden Markov Models. The approach is trained on data from one viewpoint and tested on data from other very different viewpoints with an angular variation of 180°. The average recognition rate is always higher than 94%. Since it is similar to the recognition rate when training and testing on gestures from the same viewpoint, hence the approach is indeed view-invariant. Comparing these results with those deriving from the test of a one depth camera approach demonstrates that the adoption of two calibrated cameras is crucial.
{"title":"Extending the interaction area for view-invariant 3D gesture recognition","authors":"M. Caon, J. Tscherrig, Yong Yue, Omar Abou Khaled, E. Mugellini","doi":"10.1109/IPTA.2012.6469542","DOIUrl":"https://doi.org/10.1109/IPTA.2012.6469542","url":null,"abstract":"This paper presents a non-intrusive approach for view-invariant hand gesture recognition. In fact, the representation of gestures changes dynamically depending on camera viewpoints. Therefore, the different positions of the user between the training phase and the evaluation phase can severely compromise the recognition process. The proposed approach involves the calibration of two Microsoft Kinect depth cameras to allow the 3D modeling of the dynamic hands movements. The gestures are modeled as 3D trajectories and the classification is based on Hidden Markov Models. The approach is trained on data from one viewpoint and tested on data from other very different viewpoints with an angular variation of 180°. The average recognition rate is always higher than 94%. Since it is similar to the recognition rate when training and testing on gestures from the same viewpoint, hence the approach is indeed view-invariant. Comparing these results with those deriving from the test of a one depth camera approach demonstrates that the adoption of two calibrated cameras is crucial.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115369399","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 : 2012-10-01DOI: 10.1109/IPTA.2012.6469513
M. Gaata, W. Puech, Sattar Sadkhn, Saad Hasson
In this paper, a new no-reference image quality metric is proposed to estimate the quality of watermarked images automatically based on combining objective metrics using neural network. The aim is to predict the subjective quality scores, known as the mean opinion score (MOS) obtained from human observers. In practice, our metric consists of three stages: first, filtering process is applied to watermarked image in order to generate its filtered image. Second, we use watermarked image and its filtered image in the calculation of the objective metrics as input to a neural network. Third; these metrics are combined using neural network model. The output of this neural network is a single value corresponding to the MOS scores. Experimental results show that combination of objective metrics through the neural network, indeed is able to accurately predict perceived quality of watermarked images.
{"title":"No-reference quality metric for watermarked images based on combining of objective metrics using neural network","authors":"M. Gaata, W. Puech, Sattar Sadkhn, Saad Hasson","doi":"10.1109/IPTA.2012.6469513","DOIUrl":"https://doi.org/10.1109/IPTA.2012.6469513","url":null,"abstract":"In this paper, a new no-reference image quality metric is proposed to estimate the quality of watermarked images automatically based on combining objective metrics using neural network. The aim is to predict the subjective quality scores, known as the mean opinion score (MOS) obtained from human observers. In practice, our metric consists of three stages: first, filtering process is applied to watermarked image in order to generate its filtered image. Second, we use watermarked image and its filtered image in the calculation of the objective metrics as input to a neural network. Third; these metrics are combined using neural network model. The output of this neural network is a single value corresponding to the MOS scores. Experimental results show that combination of objective metrics through the neural network, indeed is able to accurately predict perceived quality of watermarked images.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116399345","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 : 2012-10-01DOI: 10.1109/IPTA.2012.6469522
P. Holtzhausen, V. Crnojevic, B. Herbst
The detection of naval vessels in open water is a difficult challenge, with many applications from harbor monitoring to proximity security systems for ocean-faring ships. Background modelling is an effective method of detecting candidate targets, and we describe a framework that improves the operational robustness by the interaction of two different Mixture of Gaussian (MoG) models. These results are then processed by a tracking system that accurately detects moving vessels. The algorithm performs well in varying environmental conditions with good real-time performance characteristics.
{"title":"The detection of naval vessels by fusion of edge and color background models","authors":"P. Holtzhausen, V. Crnojevic, B. Herbst","doi":"10.1109/IPTA.2012.6469522","DOIUrl":"https://doi.org/10.1109/IPTA.2012.6469522","url":null,"abstract":"The detection of naval vessels in open water is a difficult challenge, with many applications from harbor monitoring to proximity security systems for ocean-faring ships. Background modelling is an effective method of detecting candidate targets, and we describe a framework that improves the operational robustness by the interaction of two different Mixture of Gaussian (MoG) models. These results are then processed by a tracking system that accurately detects moving vessels. The algorithm performs well in varying environmental conditions with good real-time performance characteristics.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130703034","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 : 2012-10-01DOI: 10.1109/IPTA.2012.6469568
A. Faro, D. Giordano, S. Palazzo
Aim of the paper is to demonstrate how by integrating unsupervised and supervised parallel neural clustering methods in a GPU platform we may carry out a fast image segmentation with a satisfactory compromise between the topological preservation of the original image and the minimization of the quantization error, also known as clustering accuracy. For this reason, an unsupervised parallel clustering method inspired by the Extended SOM (ESOM) powered by a Learning Vector Quantization (LVQ) like algorithm is proposed. Then, its parallel supervised versions is presented to further minimize the quantization error in case proper prototypes of the desired clusters are known. Finally, the GPU implementation of both these methods are illustrated to show how we may support time critical tasks such as real time surveillance, interactive medical diagnosis, and control of dynamical systems. The performance of the GPU implementation is discussed with the help of small examples and realistic processing tasks.
{"title":"Integrating unsupervised and supervised clustering methods on a GPU platform for fast image segmentation","authors":"A. Faro, D. Giordano, S. Palazzo","doi":"10.1109/IPTA.2012.6469568","DOIUrl":"https://doi.org/10.1109/IPTA.2012.6469568","url":null,"abstract":"Aim of the paper is to demonstrate how by integrating unsupervised and supervised parallel neural clustering methods in a GPU platform we may carry out a fast image segmentation with a satisfactory compromise between the topological preservation of the original image and the minimization of the quantization error, also known as clustering accuracy. For this reason, an unsupervised parallel clustering method inspired by the Extended SOM (ESOM) powered by a Learning Vector Quantization (LVQ) like algorithm is proposed. Then, its parallel supervised versions is presented to further minimize the quantization error in case proper prototypes of the desired clusters are known. Finally, the GPU implementation of both these methods are illustrated to show how we may support time critical tasks such as real time surveillance, interactive medical diagnosis, and control of dynamical systems. The performance of the GPU implementation is discussed with the help of small examples and realistic processing tasks.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132658887","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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