Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204188
Houda Sekkal, Naila Amrous, S. Bennani
There is knowledge in user generated content that can be extracted and mined to be reused. Our work is focusing on knowledge extraction from user-generated content present in online communities. In this article, we propose an approach to extract elements of knowledge from user-generated content using ATM (Automatic terms recognition). The obtained results show the effectiveness of the process in extracting useful solutions to problems discussed by the online community members.
{"title":"Knowledge components detection in User-Generated Content","authors":"Houda Sekkal, Naila Amrous, S. Bennani","doi":"10.1109/ISCV49265.2020.9204188","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204188","url":null,"abstract":"There is knowledge in user generated content that can be extracted and mined to be reused. Our work is focusing on knowledge extraction from user-generated content present in online communities. In this article, we propose an approach to extract elements of knowledge from user-generated content using ATM (Automatic terms recognition). The obtained results show the effectiveness of the process in extracting useful solutions to problems discussed by the online community members.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115656187","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204303
Ouarda Lamrabet, E. Tissir, F. E. Haoussi
In this paper, the problem of controller design is studied for a class of delta operator systems subject actuator saturation and time-varying state delay. Our main attention is to approximate the time-varying delay by using the three term approximation method. On the basis of the scaled small gain (SSG) theorem, input-output (IO) approach, Lyapunov-Krasovskii functional and Wirtinger-based inequality, a new set of sufficient conditions in terms of linear matrix inequalities is obtained to not only ensure the existence of the desired state feedback control law, but also cover the issues of actuator saturation and performance constraints. Finally, the advantages and the feasibility of the proposed method are demonstrated by the numerical examples.
{"title":"Controller design for delta operator time-delay systems subject to actuator saturation","authors":"Ouarda Lamrabet, E. Tissir, F. E. Haoussi","doi":"10.1109/ISCV49265.2020.9204303","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204303","url":null,"abstract":"In this paper, the problem of controller design is studied for a class of delta operator systems subject actuator saturation and time-varying state delay. Our main attention is to approximate the time-varying delay by using the three term approximation method. On the basis of the scaled small gain (SSG) theorem, input-output (IO) approach, Lyapunov-Krasovskii functional and Wirtinger-based inequality, a new set of sufficient conditions in terms of linear matrix inequalities is obtained to not only ensure the existence of the desired state feedback control law, but also cover the issues of actuator saturation and performance constraints. Finally, the advantages and the feasibility of the proposed method are demonstrated by the numerical examples.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126200815","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204041
Brahim Dib, Fahd Kalloubi, E. Nfaoui, Abdelhak Boulaalam
With the fast growth of the Twitter network, users are overwhelmed by the huge amount of information, which is shared via the follower/followee social network, to overcome this problem, finding like-minded users becomes a very important task. Thus, a system to assist users in such a task is recommended. In this paper, we propose a followee recommendation system by leveraging the topic feature, for topic modeling, and the follower/followee topology, searching for similar users to recommend, based on topic similarities. To show the effectiveness of our approach, we evaluate it using a dataset ingathered from the Twitter platform. The experiment results indicate that our model outperforms the lexical-based [reference?] approach and semantic-based approach [reference?], achieving a recall value of more than 23% on recommending 10 followees, proving that dealing with users’ topics of interest in microblogging websites content is more efficient than semantic and lexical features.
{"title":"Leveraging topic feature for followee recommendation on Twitter network","authors":"Brahim Dib, Fahd Kalloubi, E. Nfaoui, Abdelhak Boulaalam","doi":"10.1109/ISCV49265.2020.9204041","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204041","url":null,"abstract":"With the fast growth of the Twitter network, users are overwhelmed by the huge amount of information, which is shared via the follower/followee social network, to overcome this problem, finding like-minded users becomes a very important task. Thus, a system to assist users in such a task is recommended. In this paper, we propose a followee recommendation system by leveraging the topic feature, for topic modeling, and the follower/followee topology, searching for similar users to recommend, based on topic similarities. To show the effectiveness of our approach, we evaluate it using a dataset ingathered from the Twitter platform. The experiment results indicate that our model outperforms the lexical-based [reference?] approach and semantic-based approach [reference?], achieving a recall value of more than 23% on recommending 10 followees, proving that dealing with users’ topics of interest in microblogging websites content is more efficient than semantic and lexical features.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129059753","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204071
M. Yamni, H. Karmouni, A. Daoui, O. El Ogri, M. Sayyouri, H. Qjidaa
Image watermarking systems are frequently used tools for copyright protection against unauthorized use of images in unsecured spaces. The conventional method is to embed a copyright mark (watermark) in the original image. However, this strategy is not suitable for sensitive images such as medical, satellite, texture and remote sensing images, etc., because the integrated watermark strongly affects the results of its application tasks. For copyright protection of this type of images, this paper proposes a robust blind zero-watermarking algorithm based on Krawtchouk Radial Moments and a chaotic system. This algorithm does not integrate any information into the original image and satisfactorily ensures robustness against various common image processing attacks and geometric distortions. The experimental study uses different categories of images to evaluate and compare the proposed algorithm with other watermarking and zero-watermarking algorithms in terms of robustness against various image attacks.
{"title":"Blind Image Zero-Watermarking Algorithm Based on Radial Krawtchouk Moments and Chaotic System","authors":"M. Yamni, H. Karmouni, A. Daoui, O. El Ogri, M. Sayyouri, H. Qjidaa","doi":"10.1109/ISCV49265.2020.9204071","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204071","url":null,"abstract":"Image watermarking systems are frequently used tools for copyright protection against unauthorized use of images in unsecured spaces. The conventional method is to embed a copyright mark (watermark) in the original image. However, this strategy is not suitable for sensitive images such as medical, satellite, texture and remote sensing images, etc., because the integrated watermark strongly affects the results of its application tasks. For copyright protection of this type of images, this paper proposes a robust blind zero-watermarking algorithm based on Krawtchouk Radial Moments and a chaotic system. This algorithm does not integrate any information into the original image and satisfactorily ensures robustness against various common image processing attacks and geometric distortions. The experimental study uses different categories of images to evaluate and compare the proposed algorithm with other watermarking and zero-watermarking algorithms in terms of robustness against various image attacks.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127953553","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204261
Yassine El Hasnaoui, T. Mazri
Patch array antennas are widely used in various applications, namely, wireless communications networks, satellite telecommunications, radar systems, global positioning systems, and telemedicine applications. The purpose of this article is to design and simulate, using the simulation software ADS (Advanced Design System), so we designed a rectangular 1 patch antenna powered by a microstrip line with notch, the results obtained were transformed to a 2 patches array and then to 4 patches powered first in parallel using a power divider. The objective is to achieve: a high directivity of the antenna with better gain and reduced losses by reflection, we analyzed the results for the three coil arrays (1 patch, 2 patch, and 4 patch coil), found that the 4 patch array provides better results than the 1 and 2 patch array, because they show an increase in directivity and gain with a very large bandwidth.
{"title":"Study, Design and Simulation of an Array Antenna for Base Station 5G","authors":"Yassine El Hasnaoui, T. Mazri","doi":"10.1109/ISCV49265.2020.9204261","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204261","url":null,"abstract":"Patch array antennas are widely used in various applications, namely, wireless communications networks, satellite telecommunications, radar systems, global positioning systems, and telemedicine applications. The purpose of this article is to design and simulate, using the simulation software ADS (Advanced Design System), so we designed a rectangular 1 patch antenna powered by a microstrip line with notch, the results obtained were transformed to a 2 patches array and then to 4 patches powered first in parallel using a power divider. The objective is to achieve: a high directivity of the antenna with better gain and reduced losses by reflection, we analyzed the results for the three coil arrays (1 patch, 2 patch, and 4 patch coil), found that the 4 patch array provides better results than the 1 and 2 patch array, because they show an increase in directivity and gain with a very large bandwidth.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128330062","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204333
Ilham Hmaiddouch, M. Essabre, A. Assoudi, J. Soulami, E. Yaagoubi
A new fuzzy observer design for a class of discrete-time Takagi-Sugeno models (DTSMs) when the premise variables are not accessible is proposed in this paper. Using the Lyapunov theory, convergence conditions of this observer design are obtained and expressed in term of linear matrix inequalities (LMIs). Finally, an application to a DTSM of an asynchronous motor is given to illustrate the effectiveness of the proposed fuzzy observer design.
{"title":"Observer Design for a Class of Discrete-Time Takagi-Sugeno Models with Unmeasurable Premise Variables: Application to an Asynchronous Motor","authors":"Ilham Hmaiddouch, M. Essabre, A. Assoudi, J. Soulami, E. Yaagoubi","doi":"10.1109/ISCV49265.2020.9204333","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204333","url":null,"abstract":"A new fuzzy observer design for a class of discrete-time Takagi-Sugeno models (DTSMs) when the premise variables are not accessible is proposed in this paper. Using the Lyapunov theory, convergence conditions of this observer design are obtained and expressed in term of linear matrix inequalities (LMIs). Finally, an application to a DTSM of an asynchronous motor is given to illustrate the effectiveness of the proposed fuzzy observer design.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131377571","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204154
A. E. Bakri, S. Sefriti, I. Boumhidi
The reliability of the wind turbine doubly-fed induction generator (DFIG) is of paramount concern for adequate power production. This paper investigates an effective fault detection scheme for DFIG using the deep auto-encoder (DAE) structure. The methods contain three main steps: first, the measurement of the stator currents and voltages directly presented to the DAE to capture the characteristics of the signals effectively. Second, using those features, a neural network model is used to detect faults affecting the stator immediately. Then, a binary decision logic proposed for isolation. The results confirm the method efficiency, rapidity, robustness against the occurrence of multiple faults in the presence of measurement noise and unknown inputs.
{"title":"A sensor fault detection scheme of DFIG-based wind turbine using deep auto-encoder approach","authors":"A. E. Bakri, S. Sefriti, I. Boumhidi","doi":"10.1109/ISCV49265.2020.9204154","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204154","url":null,"abstract":"The reliability of the wind turbine doubly-fed induction generator (DFIG) is of paramount concern for adequate power production. This paper investigates an effective fault detection scheme for DFIG using the deep auto-encoder (DAE) structure. The methods contain three main steps: first, the measurement of the stator currents and voltages directly presented to the DAE to capture the characteristics of the signals effectively. Second, using those features, a neural network model is used to detect faults affecting the stator immediately. Then, a binary decision logic proposed for isolation. The results confirm the method efficiency, rapidity, robustness against the occurrence of multiple faults in the presence of measurement noise and unknown inputs.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134576744","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204319
Soukaina El Idrissi El kaitouni, H. Tairi
Malignant brain tumors are one of the leading causes of death in adults and children. To identify a brain tumor, an MRI image is acquired and analyzed manually by an expert to find lesions. This procedure takes time and the intra and inter expert variations for the same case vary a lot. To overcome these problems, many automatic and semi-automatic methods have been proposed in recent years to help practitioners make decisions. The advent of Deep Learning methods and their success in many applications such as image classification has helped to promote Deep Learning in the analysis of medical images. In this paper, we will present two methods for the detection of brain tumors in medical images. The first is based on Deep Learning through the U-net architecture that has proven its robustness vis-vis the segmentation of images, especially medical images. The results obtained will be compared by a second method that we have published in another article [1], which uses LBP and k-means techniques. The classes found are improved using the Markov method, by calculating the class correlation. The comparison was made on the same BraTS2019 dataset [2], which will give us an idea of the performance of each.
{"title":"Segmentation of medical images for the extraction of brain tumors: A comparative study between the Hidden Markov and Deep Learning approaches","authors":"Soukaina El Idrissi El kaitouni, H. Tairi","doi":"10.1109/ISCV49265.2020.9204319","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204319","url":null,"abstract":"Malignant brain tumors are one of the leading causes of death in adults and children. To identify a brain tumor, an MRI image is acquired and analyzed manually by an expert to find lesions. This procedure takes time and the intra and inter expert variations for the same case vary a lot. To overcome these problems, many automatic and semi-automatic methods have been proposed in recent years to help practitioners make decisions. The advent of Deep Learning methods and their success in many applications such as image classification has helped to promote Deep Learning in the analysis of medical images. In this paper, we will present two methods for the detection of brain tumors in medical images. The first is based on Deep Learning through the U-net architecture that has proven its robustness vis-vis the segmentation of images, especially medical images. The results obtained will be compared by a second method that we have published in another article [1], which uses LBP and k-means techniques. The classes found are improved using the Markov method, by calculating the class correlation. The comparison was made on the same BraTS2019 dataset [2], which will give us an idea of the performance of each.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128785597","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204305
Marouan Elmansouri, Noureddine El Makhfi, Badraddine Aghoutane
Deep learning is an area that has seen many developments in recent years. One of these algorithms that have provided good results is Deep Convolutional Neural Networks (DCNN). It is proven to be effective in various fields such as natural language processing, pattern recognition, computer vision, object detection in images, etc. Despite the development of these technologies, Arabic manuscripts in digital libraries still use traditional indexing methods based on metadata, annotation or transcription. In this article, we propose two methods of word classification based on deep learning, the first one uses a simple Neural Network (DNN) and the last one uses a Convolutional Neural Network (DCNN). The idea is to segment words of Arabic manuscripts images and predict the class of each word. The experimental results show the efficient of this classification system based on the DCNN. By comparing the results obtained, we can observe that the DCNN method provides excellent results than those obtained with the DNN method.
{"title":"Toward Classification of Arabic Manuscripts Words Based on the Deep Convolutional Neural Networks","authors":"Marouan Elmansouri, Noureddine El Makhfi, Badraddine Aghoutane","doi":"10.1109/ISCV49265.2020.9204305","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204305","url":null,"abstract":"Deep learning is an area that has seen many developments in recent years. One of these algorithms that have provided good results is Deep Convolutional Neural Networks (DCNN). It is proven to be effective in various fields such as natural language processing, pattern recognition, computer vision, object detection in images, etc. Despite the development of these technologies, Arabic manuscripts in digital libraries still use traditional indexing methods based on metadata, annotation or transcription. In this article, we propose two methods of word classification based on deep learning, the first one uses a simple Neural Network (DNN) and the last one uses a Convolutional Neural Network (DCNN). The idea is to segment words of Arabic manuscripts images and predict the class of each word. The experimental results show the efficient of this classification system based on the DCNN. By comparing the results obtained, we can observe that the DCNN method provides excellent results than those obtained with the DNN method.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114282744","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204094
K. Slimani, S. Bourekkadi, R. Messoussi, Y. Ruichek, R. Touahni
Learning nowadays is fast, modern, and very connected but this might yield a short attention span and lack of focus. On the other hand, emotions are a fundamental partner of the human’s cognition, creativity, and decision-making. For instance, neuroscience and brain imaging confirm that the absence of normal emotional responses could affect one’s critical decisions in life though this person has complete cognitive abilities. Meanwhile, due to the importance of emotions, the aim of this study was to examine the attitudes of students toward the reception of their teammates’ emotions during a distance collaborative work. A total of 244 university students participated in this study representing various Moroccan universities. A mixed methods design was used to collect data, which were analyzed using the SPSS software. The results confirmed that participants have a positive attitude toward sharing their emotions. Moreover, the findings displayed the significance of sharing emotions because this might help enriching communication, ensuring quality work, and generating participants’ satisfaction.
{"title":"Sharing Emotions in the Distance Education Experience: Attitudes and Motivation of University Students","authors":"K. Slimani, S. Bourekkadi, R. Messoussi, Y. Ruichek, R. Touahni","doi":"10.1109/ISCV49265.2020.9204094","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204094","url":null,"abstract":"Learning nowadays is fast, modern, and very connected but this might yield a short attention span and lack of focus. On the other hand, emotions are a fundamental partner of the human’s cognition, creativity, and decision-making. For instance, neuroscience and brain imaging confirm that the absence of normal emotional responses could affect one’s critical decisions in life though this person has complete cognitive abilities. Meanwhile, due to the importance of emotions, the aim of this study was to examine the attitudes of students toward the reception of their teammates’ emotions during a distance collaborative work. A total of 244 university students participated in this study representing various Moroccan universities. A mixed methods design was used to collect data, which were analyzed using the SPSS software. The results confirmed that participants have a positive attitude toward sharing their emotions. Moreover, the findings displayed the significance of sharing emotions because this might help enriching communication, ensuring quality work, and generating participants’ satisfaction.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114285877","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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