Pub Date : 2017-05-22DOI: 10.1109/ATSIP.2017.8075589
Kalthoum Ouerghi, A. Smida, R. Ghayoula, N. Boulejfen
Breast cancer affects many women all over the globe and means for early detection are necessary for fast and effective treatment. Mammography, which is currently the most popular method of breast screening, has some limitations and microwave imaging seems to offer a good alternative. In this paper, a study of patch antenna array for breast cancer detection is presented. The results show that the proposed antenna's design is capable of detecting the breast tumor with much improved characteristics compared to the other designs available in the literature. The capabilities and limitations of this antenna for detecting tumor models are investigated through simulations and its potential for detecting tumors in the breast is highlighted.
{"title":"Design and analysis of a microstrip antenna array for biomedical applications","authors":"Kalthoum Ouerghi, A. Smida, R. Ghayoula, N. Boulejfen","doi":"10.1109/ATSIP.2017.8075589","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075589","url":null,"abstract":"Breast cancer affects many women all over the globe and means for early detection are necessary for fast and effective treatment. Mammography, which is currently the most popular method of breast screening, has some limitations and microwave imaging seems to offer a good alternative. In this paper, a study of patch antenna array for breast cancer detection is presented. The results show that the proposed antenna's design is capable of detecting the breast tumor with much improved characteristics compared to the other designs available in the literature. The capabilities and limitations of this antenna for detecting tumor models are investigated through simulations and its potential for detecting tumors in the breast is highlighted.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"134 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120871340","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 : 2017-05-22DOI: 10.1109/ATSIP.2017.8075555
Marwa Chaabane, M. Mansouri, H. Nounou, M. Nounou, M. Slima, A. Hamida
The objective of this paper is to extend the applicability of the GLR method to a wide range of practical systems. Most real systems are nonlinear, multivariate, and are best represented by input-output type of models. Kernel partial least squares (KPLS) models have been widely used to represent such systems. Therefore, in this paper, kernel PLS-based GLR method will be utilized in practice to improve damage detection in Structural Health Monitoring (SHM). The developed kernel PLS-based GLR technique combines the benefits of the multivariate input-output kernel PLS model and the statistical fault detection GLR statistic which showed performance in the cases where process models are not available. GLR is a well-known statistical detection method that relies on maximizing the detection probability for a given false alarm rate. To calculate the kernel PLS model, we use the data collected from the complex 3DOF spring-mass-dashpot system. The simulation results show improved performance of kernel PLS-based GLR in damage detection compared to the classical kernel PLS method.
{"title":"Damage detection in structural health monitoring using kernel PLS based GLR","authors":"Marwa Chaabane, M. Mansouri, H. Nounou, M. Nounou, M. Slima, A. Hamida","doi":"10.1109/ATSIP.2017.8075555","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075555","url":null,"abstract":"The objective of this paper is to extend the applicability of the GLR method to a wide range of practical systems. Most real systems are nonlinear, multivariate, and are best represented by input-output type of models. Kernel partial least squares (KPLS) models have been widely used to represent such systems. Therefore, in this paper, kernel PLS-based GLR method will be utilized in practice to improve damage detection in Structural Health Monitoring (SHM). The developed kernel PLS-based GLR technique combines the benefits of the multivariate input-output kernel PLS model and the statistical fault detection GLR statistic which showed performance in the cases where process models are not available. GLR is a well-known statistical detection method that relies on maximizing the detection probability for a given false alarm rate. To calculate the kernel PLS model, we use the data collected from the complex 3DOF spring-mass-dashpot system. The simulation results show improved performance of kernel PLS-based GLR in damage detection compared to the classical kernel PLS method.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117089322","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 : 2017-05-22DOI: 10.1109/ATSIP.2017.8075590
Said Charfi, Mohamed El Ansari
In this paper, we present a new feature descriptor for automatic recognition of frames with ulcer in Wireless Capsule Endoscopy (WCE) images. The new approach is based on the fact that the ulcer disease exhibits various features that can not be detected with a single descriptor. Hence, we have combined two stages of the art descriptors in order to get more powerful one. Complete Local Binary Pattern (CLBP) descriptor is used to detect the texture information in the image. In parallel, the Global Local Oriented Edge Magnitude Pattern (Global LOEMP) descriptor is employed to extract the color features. Finally, we combine the feature vectors to get a more discriminating one. Experiments were conducted and the results are satisfactory.
{"title":"Computer-aided diagnosis system for ulcer detection in wireless capsule endoscopy videos","authors":"Said Charfi, Mohamed El Ansari","doi":"10.1109/ATSIP.2017.8075590","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075590","url":null,"abstract":"In this paper, we present a new feature descriptor for automatic recognition of frames with ulcer in Wireless Capsule Endoscopy (WCE) images. The new approach is based on the fact that the ulcer disease exhibits various features that can not be detected with a single descriptor. Hence, we have combined two stages of the art descriptors in order to get more powerful one. Complete Local Binary Pattern (CLBP) descriptor is used to detect the texture information in the image. In parallel, the Global Local Oriented Edge Magnitude Pattern (Global LOEMP) descriptor is employed to extract the color features. Finally, we combine the feature vectors to get a more discriminating one. Experiments were conducted and the results are satisfactory.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127312221","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 : 2017-05-22DOI: 10.1109/ATSIP.2017.8075581
H. Karmouni, Tarik Jahid, Imad El Affar, M. Sayyouri, A. Hmimid, H. Qjidaa, A. Rezzouk
In this paper, we will present a new method of image reconstruction using a new type of separable discrete orthogonal moments called the Krawtchouk-Tchebichef moments. The latter are based on the bivariate discrete orthogonal polynomials defined from the product of Krawtchouk and Tchebichef of discrete orthogonal polynomials with a variable. The new method of image reconstruction is made from the blocks of each slice of the image using the Krawtchouk-Tchebichef moments for small orders. By experiments we show the effectiveness of our method with respect to the global approach of image reconstruction and the possibility of reconstructing the image by the Krawtchouk-Tchebichef moments is compared to the classical moments of Tchebichef and Krawtchouk.
{"title":"Image analysis using separable Krawtchouk-Tchebichef's moments","authors":"H. Karmouni, Tarik Jahid, Imad El Affar, M. Sayyouri, A. Hmimid, H. Qjidaa, A. Rezzouk","doi":"10.1109/ATSIP.2017.8075581","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075581","url":null,"abstract":"In this paper, we will present a new method of image reconstruction using a new type of separable discrete orthogonal moments called the Krawtchouk-Tchebichef moments. The latter are based on the bivariate discrete orthogonal polynomials defined from the product of Krawtchouk and Tchebichef of discrete orthogonal polynomials with a variable. The new method of image reconstruction is made from the blocks of each slice of the image using the Krawtchouk-Tchebichef moments for small orders. By experiments we show the effectiveness of our method with respect to the global approach of image reconstruction and the possibility of reconstructing the image by the Krawtchouk-Tchebichef moments is compared to the classical moments of Tchebichef and Krawtchouk.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131515922","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 : 2017-05-22DOI: 10.1109/ATSIP.2017.8075538
Wafae Mrabti, Driss Moujahid, B. Bellach, H. Tairi
Tracking a moving object in image sequences from a stationary video camera is a crucial task for surveillance applications. This paper proposes a hybrid technique that combines Kalman Filter (KF) and the Support Vector Machines (SVM). First, the moving target is determined according to the user's interest, and then the system state model of the KF algorithm is constructed. Second, a set of patterns are generated around the target's position. For every pattern, the Histogram of Oriented Object (HOG) is calculated to be classified into positive (humans) and negative patterns (other object) by the SVM algorithm. Finally, the selected pattern is the one that minimizes the Euclidean distance between the prediction and the positive patterns. This selected pattern is considered as a measurement for the correction step of the KF algorithm. The experiment results prove that the proposed method has the robust ability to track the moving human being across the image sequences with different challenging situations such as occlusion, deformation, rotation and the scale variation.
从静止摄像机的图像序列中跟踪运动物体是监控应用的关键任务。本文提出了一种将卡尔曼滤波(KF)和支持向量机(SVM)相结合的混合技术。首先根据用户兴趣确定运动目标，然后构建KF算法的系统状态模型。其次，在目标位置周围生成一组图案。对于每种模式，计算出面向对象直方图(Histogram of Oriented Object, HOG)，通过SVM算法将其分类为正面(人类)和负面(其他对象)模式。最后，选择的模式是预测和正模式之间的欧几里得距离最小的模式。这种选择的模式被认为是KF算法的校正步骤的测量。实验结果表明，该方法具有较强的鲁棒性，能够在图像序列中实现遮挡、变形、旋转和尺度变化等不同挑战情况下的人体运动跟踪。
{"title":"Approach for tracking human being in surveillance videos","authors":"Wafae Mrabti, Driss Moujahid, B. Bellach, H. Tairi","doi":"10.1109/ATSIP.2017.8075538","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075538","url":null,"abstract":"Tracking a moving object in image sequences from a stationary video camera is a crucial task for surveillance applications. This paper proposes a hybrid technique that combines Kalman Filter (KF) and the Support Vector Machines (SVM). First, the moving target is determined according to the user's interest, and then the system state model of the KF algorithm is constructed. Second, a set of patterns are generated around the target's position. For every pattern, the Histogram of Oriented Object (HOG) is calculated to be classified into positive (humans) and negative patterns (other object) by the SVM algorithm. Finally, the selected pattern is the one that minimizes the Euclidean distance between the prediction and the positive patterns. This selected pattern is considered as a measurement for the correction step of the KF algorithm. The experiment results prove that the proposed method has the robust ability to track the moving human being across the image sequences with different challenging situations such as occlusion, deformation, rotation and the scale variation.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123849746","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 : 2017-05-22DOI: 10.1109/ATSIP.2017.8075534
A. Hanafi, M. Karim, El-Kaber Hachem, T. Rachidi, M. Sahmoudi
The main objective of this paper is to evaluate the perturbations in CubeSat's orbital elements in low Earth orbits (LEO) using the Cowell's method. The disturbing forces are driving the satellite (the satellite's trajectory) away from Keplerian orbit, therefore produce a change in Keplerian orbital elements over time. In this paper, after introducing the perturbing forces acting on a satellite in LEO, the methods of converting the orbital elements into state vector and the opposite are being presented, and in the end, the perturbations in orbital elements of CubeSats in LEO are evaluated.
{"title":"Perturbation effects in orbital elements of CubeSats","authors":"A. Hanafi, M. Karim, El-Kaber Hachem, T. Rachidi, M. Sahmoudi","doi":"10.1109/ATSIP.2017.8075534","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075534","url":null,"abstract":"The main objective of this paper is to evaluate the perturbations in CubeSat's orbital elements in low Earth orbits (LEO) using the Cowell's method. The disturbing forces are driving the satellite (the satellite's trajectory) away from Keplerian orbit, therefore produce a change in Keplerian orbital elements over time. In this paper, after introducing the perturbing forces acting on a satellite in LEO, the methods of converting the orbital elements into state vector and the opposite are being presented, and in the end, the perturbations in orbital elements of CubeSats in LEO are evaluated.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126004016","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 : 2017-05-22DOI: 10.1109/ATSIP.2017.8075544
R. Khemakhem, I. Kammoun, K. Chtourou, J. Boughariou, M. Ghorbel, A. Hamida
The study of the cerebral electric activity in the brain, requires estimation of the EEG inverse problem. Several methods of the inverse problem solution are studied in the literature. In this paper we propose a comparative study of the localization error based on distance between active sources, using WMN-FOCUSS, LORETA-FOCUSS, and Shrinking sLORETA-FOCUSS as inverse problem solution. So, we consider the presence of two active sources whose distance intervals range from 1cm to 10cm. This study is made in a first case using electrode configuration on the entire brain, and in a second case on each lobe separately. The presented results show that the new approach for the separately lobes gives a good localization of the active sources in the brain.
{"title":"EEG localization error exploration vs distance between sources","authors":"R. Khemakhem, I. Kammoun, K. Chtourou, J. Boughariou, M. Ghorbel, A. Hamida","doi":"10.1109/ATSIP.2017.8075544","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075544","url":null,"abstract":"The study of the cerebral electric activity in the brain, requires estimation of the EEG inverse problem. Several methods of the inverse problem solution are studied in the literature. In this paper we propose a comparative study of the localization error based on distance between active sources, using WMN-FOCUSS, LORETA-FOCUSS, and Shrinking sLORETA-FOCUSS as inverse problem solution. So, we consider the presence of two active sources whose distance intervals range from 1cm to 10cm. This study is made in a first case using electrode configuration on the entire brain, and in a second case on each lobe separately. The presented results show that the new approach for the separately lobes gives a good localization of the active sources in the brain.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127708927","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 : 2017-05-22DOI: 10.1109/ATSIP.2017.8075524
Ghofrane Souaki, Kacem Halim
Wireless sensor communication is managing critical applications that require serious security and privacy concerns to decrease hacking attacks. As a solution, most cryptographic algorithms include secure encoding and decoding which are based on random number generator (RNG), This paper suggests an efficient solution for the generation of low cost and low power random number for Internet of Things’ Application based on analog and digital sources of the Microcontroller Unit (MCU) with external sensing resources. The design detail and the validation of the quality of the solution outputs, were identified based on a couple of test suites standardized by the U.S. National Institute of Standards and Technology, both achieved in the ideal case and assuming implementation.
{"title":"Random number generation based on MCU sources for IoT application","authors":"Ghofrane Souaki, Kacem Halim","doi":"10.1109/ATSIP.2017.8075524","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075524","url":null,"abstract":"Wireless sensor communication is managing critical applications that require serious security and privacy concerns to decrease hacking attacks. As a solution, most cryptographic algorithms include secure encoding and decoding which are based on random number generator (RNG), This paper suggests an efficient solution for the generation of low cost and low power random number for Internet of Things’ Application based on analog and digital sources of the Microcontroller Unit (MCU) with external sensing resources. The design detail and the validation of the quality of the solution outputs, were identified based on a couple of test suites standardized by the U.S. National Institute of Standards and Technology, both achieved in the ideal case and assuming implementation.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127930294","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 : 2017-05-22DOI: 10.1109/ATSIP.2017.8075517
Khadija Lekdioui, Y. Ruichek, R. Messoussi, Youness Chaabi, R. Touahni
This paper proposes a facial expression recognition method based on a novel facial decomposition. First, seven regions of interest (ROI), representing the main components of face (left eyebrow, right eyebrow, left eye, right eye, between eyebrows, nose and mouth), are extracted using facial landmarks detected by IntraFace algorithm. Then, different local descriptors, such as LBP, CLBP, LTP and Dynamic LTP, are used to extract features. Finally, feature vector, representing face image, is fed into a multiclass support vector machine to achieve the recognition task. Experimental results on two public datasets show that the proposed method outperforms state of the art methods based on other facial decompositions.
{"title":"Facial expression recognition using face-regions","authors":"Khadija Lekdioui, Y. Ruichek, R. Messoussi, Youness Chaabi, R. Touahni","doi":"10.1109/ATSIP.2017.8075517","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075517","url":null,"abstract":"This paper proposes a facial expression recognition method based on a novel facial decomposition. First, seven regions of interest (ROI), representing the main components of face (left eyebrow, right eyebrow, left eye, right eye, between eyebrows, nose and mouth), are extracted using facial landmarks detected by IntraFace algorithm. Then, different local descriptors, such as LBP, CLBP, LTP and Dynamic LTP, are used to extract features. Finally, feature vector, representing face image, is fed into a multiclass support vector machine to achieve the recognition task. Experimental results on two public datasets show that the proposed method outperforms state of the art methods based on other facial decompositions.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130113015","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 : 2017-05-22DOI: 10.1109/ATSIP.2017.8075576
A. Habib, K. Labbassi, J. M. D. Blasco, F. J. Leijen, L. Iannini, M. Menenti
Even if land deformation in Sahel-Doukkala may not directly threaten human life, it could lead to serious economic losses. Therefore, the monitoring of this deformation becomes a priority. In this study, PS-InSAR technique was applied in order to extract information regarding land deformation. This method was successful in detecting a considerable amount of PS targets from which the land deformation was estimated. The deformation rate was between −2.4 mm/year and 1.9 mm/year showing an alternation between uplift and subsidence. The origin of this deformation is suggested to be related to tectonic and climatological origins.
{"title":"Land deformation monitoring using PS-InSAR technique over Sahel-Doukkala (Morocco)","authors":"A. Habib, K. Labbassi, J. M. D. Blasco, F. J. Leijen, L. Iannini, M. Menenti","doi":"10.1109/ATSIP.2017.8075576","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075576","url":null,"abstract":"Even if land deformation in Sahel-Doukkala may not directly threaten human life, it could lead to serious economic losses. Therefore, the monitoring of this deformation becomes a priority. In this study, PS-InSAR technique was applied in order to extract information regarding land deformation. This method was successful in detecting a considerable amount of PS targets from which the land deformation was estimated. The deformation rate was between −2.4 mm/year and 1.9 mm/year showing an alternation between uplift and subsidence. The origin of this deformation is suggested to be related to tectonic and climatological origins.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127448267","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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