Pub Date : 2019-03-01DOI: 10.1109/icscan.2019.8878678
{"title":"ICSCAN 2019 Preface","authors":"","doi":"10.1109/icscan.2019.8878678","DOIUrl":"https://doi.org/10.1109/icscan.2019.8878678","url":null,"abstract":"","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124158831","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878791
R. Rajesh, R. Kanimozhi
At the present time evaluating an exam papers and declaring end result in a restricted period of time is a difficult task for educational schools, colleges, institutions, departments and Universities. Thus manual exam paper correction becomes more difficult and many fraudulent activities are happened today. To make it easier and more accurate the proposed aim is to develop a software for automatic exam paper evaluation and grading system, the system works by scanning the handwritten written exam papers then the scanned image be improved into an editable text using OCR tool and the evaluation will perform by matching the key terms which is maintained in the template. It is entirely integrated approach upon dissimilar level of knowledge by the method of examination, evaluation, result and formulation of subject papers. In a field of education though teaching, evaluation and the performance method many organizations initiated with the use of advanced technologies. The approach of evaluating the examination papers is evolved although use of computer wherever the utilization of computer is obligatory in every varied techniques for analysis. This paper structured in different patterns such as offline, online and the manual exam paper evaluation with different analysis and techniques.
{"title":"Digitized Exam Paper Evaluation","authors":"R. Rajesh, R. Kanimozhi","doi":"10.1109/ICSCAN.2019.8878791","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878791","url":null,"abstract":"At the present time evaluating an exam papers and declaring end result in a restricted period of time is a difficult task for educational schools, colleges, institutions, departments and Universities. Thus manual exam paper correction becomes more difficult and many fraudulent activities are happened today. To make it easier and more accurate the proposed aim is to develop a software for automatic exam paper evaluation and grading system, the system works by scanning the handwritten written exam papers then the scanned image be improved into an editable text using OCR tool and the evaluation will perform by matching the key terms which is maintained in the template. It is entirely integrated approach upon dissimilar level of knowledge by the method of examination, evaluation, result and formulation of subject papers. In a field of education though teaching, evaluation and the performance method many organizations initiated with the use of advanced technologies. The approach of evaluating the examination papers is evolved although use of computer wherever the utilization of computer is obligatory in every varied techniques for analysis. This paper structured in different patterns such as offline, online and the manual exam paper evaluation with different analysis and techniques.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125462416","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878812
V. Janani, Lubin Balasubramanian, G. Sasikala, G. Vidhya, T. Kowsalya
Right now, location recommendation plays a vital role in searching attractive places. Such recommendation places are identified by social network. The social networks are FourSquare, yelp, Jiepang, Uber etc., Ongoing analysis, based on user feedback finding a best restaurant, hotels etc., Users regularly leave reviews about the site on (LBSN) after visiting. This reviews differs from low level to high level. In this paper, recommending hotels to a user based on user inputs such as kind of outing Leisure or business, sort of movement Solo or family, sort of room, number of long periods of remain. Prescribe inns to a user based on client surveys. Hotels which are most similar in terms of reviews to the particular hotel specified by the user and recommend it to them. The main aim of this paper is to suggest the voyagers the tag of the inn dependent on their wish, by inspecting the further voyagers comments/feedbacks jointly with the rating an incentive to upgrade the recommendation. The new user cold start problem is a major concern in recommender system, because of the absence of accuracy in the recommendation. To fix this complication the resulting commitment will be made in this paper, 1. Regression model 2. Correlation 3. Classification tree analysis. Finally, we evaluate user reviews and also enhancing the accuracy of recommendation.
{"title":"A Location Recommendation Based On User Reviews Using Cart","authors":"V. Janani, Lubin Balasubramanian, G. Sasikala, G. Vidhya, T. Kowsalya","doi":"10.1109/ICSCAN.2019.8878812","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878812","url":null,"abstract":"Right now, location recommendation plays a vital role in searching attractive places. Such recommendation places are identified by social network. The social networks are FourSquare, yelp, Jiepang, Uber etc., Ongoing analysis, based on user feedback finding a best restaurant, hotels etc., Users regularly leave reviews about the site on (LBSN) after visiting. This reviews differs from low level to high level. In this paper, recommending hotels to a user based on user inputs such as kind of outing Leisure or business, sort of movement Solo or family, sort of room, number of long periods of remain. Prescribe inns to a user based on client surveys. Hotels which are most similar in terms of reviews to the particular hotel specified by the user and recommend it to them. The main aim of this paper is to suggest the voyagers the tag of the inn dependent on their wish, by inspecting the further voyagers comments/feedbacks jointly with the rating an incentive to upgrade the recommendation. The new user cold start problem is a major concern in recommender system, because of the absence of accuracy in the recommendation. To fix this complication the resulting commitment will be made in this paper, 1. Regression model 2. Correlation 3. Classification tree analysis. Finally, we evaluate user reviews and also enhancing the accuracy of recommendation.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131918783","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878858
Surender Ragunathan, P. Dananjayan
Fifth generation wireless communication aims at providing high data rate for long range signal transmission consuming high power in the network. The increase of power must be proficient considering the limitation of the interference without demolishing the quality of service in the network. This work can be analyzed by densifying the network using Massive MIMO with small cell access where maximum sum rate can be achieved. The work in this paper aims at providing better QoS by minimizing the total power and maximizing the sum rate in the heterogeneous network deployed with maximal ratio transmission beamforming technique. The simulation results of maximal ratio transmission prove that better sum rate can be achieved at the penalty of power consumption and it is compared with that of existing regularized zero forcing.
{"title":"QoS and Sum Rate Maximization in Heterogeneous Massive MIMO Network","authors":"Surender Ragunathan, P. Dananjayan","doi":"10.1109/ICSCAN.2019.8878858","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878858","url":null,"abstract":"Fifth generation wireless communication aims at providing high data rate for long range signal transmission consuming high power in the network. The increase of power must be proficient considering the limitation of the interference without demolishing the quality of service in the network. This work can be analyzed by densifying the network using Massive MIMO with small cell access where maximum sum rate can be achieved. The work in this paper aims at providing better QoS by minimizing the total power and maximizing the sum rate in the heterogeneous network deployed with maximal ratio transmission beamforming technique. The simulation results of maximal ratio transmission prove that better sum rate can be achieved at the penalty of power consumption and it is compared with that of existing regularized zero forcing.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133564043","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878695
M. Ramadevi, M. Sakthisri, N. Sri Madhaava Raja
In this work, multifractal method is used to segment and analyze human retinal fundus images. Both in normal and abnormal cases, the retinal images acquired under standard protocols undergoes segmentation process for extraction of retinal vasculature. From the segmented vessels, different performance measures are obtained by comparing the segmented image with ground truth images. Using Support Vector Machines (SVM), these significant performance measures along with the derived parameter of Vessel to Vessel Free (VVF) area ratio are further subjected to classification. By using this method normal and abnormal images can be differentiated. When compared to other kernels SVM classifier with order 3 polynomial kernel gives better performance. The proposed study seems to be useful in assisting clinical interventions related to retinal disorders.
{"title":"Feature Based Classification of Retinal Blood Vessels Using Multifractal Technique","authors":"M. Ramadevi, M. Sakthisri, N. Sri Madhaava Raja","doi":"10.1109/ICSCAN.2019.8878695","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878695","url":null,"abstract":"In this work, multifractal method is used to segment and analyze human retinal fundus images. Both in normal and abnormal cases, the retinal images acquired under standard protocols undergoes segmentation process for extraction of retinal vasculature. From the segmented vessels, different performance measures are obtained by comparing the segmented image with ground truth images. Using Support Vector Machines (SVM), these significant performance measures along with the derived parameter of Vessel to Vessel Free (VVF) area ratio are further subjected to classification. By using this method normal and abnormal images can be differentiated. When compared to other kernels SVM classifier with order 3 polynomial kernel gives better performance. The proposed study seems to be useful in assisting clinical interventions related to retinal disorders.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133477001","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878780
A. Divya, R. Kiruthika, D. Gayathri
In developing nations, the extended station of metropolitan air pollutants is a first-degree environmental question. In developing nations, the expanded stages of city air pollutants are a first-rate environmental problem. Air pollutants has emerged as a tremendous subject rely of discussion the least bit stages in India due to the improved anthropogenic sports activities. The external of this scheme is to project and exhibit a wireless system for supervise the temper of gas in WSN encompassment. The WSN concept endows formation of the smart environments associating with the citizens and arrange the cities around the world by providing a row of dandy services with aim to lengthen the property of life in the cities. This machine-driven air quality overseeing stations record the hourly, monthly or annually averaged data using the sensors. The sensors are worked to discover the events or diversity in the surrounding. Data gathered from these stations are available almost in actual time. Air Pollution may be expounded as any atmospherically state in which some substances are propitious in such concentrations that they can show off undesirable accomplishment on folks and his surroundings. Hence, it is requisite to promote tools for real-time air quality overseeing, so as to admit attribute and opportunely decisions. Aim of this project is to spotlight the technology which is worked for air quality overseeing in WSN surrounding and how forcible of this technology is and identify the essential scrutiny in this necessary region. In this system, portative sensors are gather the air quality data early, which is transmitted through a burn spirit wide area network. All air quality data are produced and analyzed in the WSN base situation. The realized air quality overseeing system, contain both hardware and software, is improved and unfolded satisfyingly in urban environments.
{"title":"Detecting And Analysing The Quality Of Air Using Low Cost Sensors To Reduce Air Pollution In Urban Areas","authors":"A. Divya, R. Kiruthika, D. Gayathri","doi":"10.1109/ICSCAN.2019.8878780","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878780","url":null,"abstract":"In developing nations, the extended station of metropolitan air pollutants is a first-degree environmental question. In developing nations, the expanded stages of city air pollutants are a first-rate environmental problem. Air pollutants has emerged as a tremendous subject rely of discussion the least bit stages in India due to the improved anthropogenic sports activities. The external of this scheme is to project and exhibit a wireless system for supervise the temper of gas in WSN encompassment. The WSN concept endows formation of the smart environments associating with the citizens and arrange the cities around the world by providing a row of dandy services with aim to lengthen the property of life in the cities. This machine-driven air quality overseeing stations record the hourly, monthly or annually averaged data using the sensors. The sensors are worked to discover the events or diversity in the surrounding. Data gathered from these stations are available almost in actual time. Air Pollution may be expounded as any atmospherically state in which some substances are propitious in such concentrations that they can show off undesirable accomplishment on folks and his surroundings. Hence, it is requisite to promote tools for real-time air quality overseeing, so as to admit attribute and opportunely decisions. Aim of this project is to spotlight the technology which is worked for air quality overseeing in WSN surrounding and how forcible of this technology is and identify the essential scrutiny in this necessary region. In this system, portative sensors are gather the air quality data early, which is transmitted through a burn spirit wide area network. All air quality data are produced and analyzed in the WSN base situation. The realized air quality overseeing system, contain both hardware and software, is improved and unfolded satisfyingly in urban environments.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128829869","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878786
D. Palani, K. Venkatalakshmi, A. Jabeen, V. M. A. B. Ram
Diabetic Retinopathy is an eye disease caused in patients with diabetic which leads to blindness. So, detection of Diabetic retinopathy at early stage prevents loss of vision. In this paper, we proposed an effective segmentation method that combines modified Fuzzy C Means (FCM) clustering with spatial features and Inertia Weight Particle Swarm optimization (IWPSO) for detection of Diabetic Retinopathy. The input human retinal fundus images are filtered by a median filter to reduce speckle noise and then contrast enhancement is done by Adaptive Histogram Equalization. Then segmented by various methods like Chaotic Particle Swarm optimization (CPSO), Inertia Weight Particle Swarm optimization (IWPSO) and our proposed method. The performance of these methods is analyzed using the metrics Accuracy, True Positive Rate (Sensitivity), True Negative Rate (Specificity), False Positive Rate and False Negative Rate. A comparative analysis has been made for the above said segmentation algorithms and the results proved that our proposed method achieved the best than the other methods.
{"title":"Effective Detection of Diabetic Retinopathy From Human Retinal Fundus Images Using Modified FCM and IWPSO","authors":"D. Palani, K. Venkatalakshmi, A. Jabeen, V. M. A. B. Ram","doi":"10.1109/ICSCAN.2019.8878786","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878786","url":null,"abstract":"Diabetic Retinopathy is an eye disease caused in patients with diabetic which leads to blindness. So, detection of Diabetic retinopathy at early stage prevents loss of vision. In this paper, we proposed an effective segmentation method that combines modified Fuzzy C Means (FCM) clustering with spatial features and Inertia Weight Particle Swarm optimization (IWPSO) for detection of Diabetic Retinopathy. The input human retinal fundus images are filtered by a median filter to reduce speckle noise and then contrast enhancement is done by Adaptive Histogram Equalization. Then segmented by various methods like Chaotic Particle Swarm optimization (CPSO), Inertia Weight Particle Swarm optimization (IWPSO) and our proposed method. The performance of these methods is analyzed using the metrics Accuracy, True Positive Rate (Sensitivity), True Negative Rate (Specificity), False Positive Rate and False Negative Rate. A comparative analysis has been made for the above said segmentation algorithms and the results proved that our proposed method achieved the best than the other methods.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128833887","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878828
K. Vijiya Kumar, R. Kowsalya, V. Prithebha, S. Rajeswari, G. Shruthee
At present, breast cancer in women is most is the prominently discovered life-threatening cancer in women and took over too many life’s of women all around the world. This project deals with the Breast Cancer Wisconsin dataset to compare the accuracy of various machine learning algorithm in predicting the breast cancer in women. The various classification model are built and trained with the Wisconsin dataset. The different classifiers that are used to construct the model are Naive Bayes, Support Vector Machine, Regression Tree, Random Forest and K-Nearest Neighbor. The efficient working of these model are assessed by estimating the accuracy score of each model with the usage of unstandardized and standardized dataset. Once the performance of the model are evaluated, the optimal working algorithm are used to identify the type of breast cancer in the patient entry.
{"title":"Compare the accuracy of different classfiers using Breast Cancer in Big Data","authors":"K. Vijiya Kumar, R. Kowsalya, V. Prithebha, S. Rajeswari, G. Shruthee","doi":"10.1109/ICSCAN.2019.8878828","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878828","url":null,"abstract":"At present, breast cancer in women is most is the prominently discovered life-threatening cancer in women and took over too many life’s of women all around the world. This project deals with the Breast Cancer Wisconsin dataset to compare the accuracy of various machine learning algorithm in predicting the breast cancer in women. The various classification model are built and trained with the Wisconsin dataset. The different classifiers that are used to construct the model are Naive Bayes, Support Vector Machine, Regression Tree, Random Forest and K-Nearest Neighbor. The efficient working of these model are assessed by estimating the accuracy score of each model with the usage of unstandardized and standardized dataset. Once the performance of the model are evaluated, the optimal working algorithm are used to identify the type of breast cancer in the patient entry.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127419016","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878685
Ms T Yathavi, Akshaya B, A. S., G. Kumaran, Meshach G, Shruthi A
In the current scenario where the world is moving towards modernization and automation, personal cars have become an integral part of people’s lives. This project focuses on improving a car from ordinary to smart by constantly monitoring parameters such as pressure of the car tyre and fuel level. The prototype also communicates to the owner of the car through SMS alerts and audio output to intimate reduced fuel levels, nearby gas stations and low car tyre pressure. This project is also incorporated with features like rain sensing wipers and theft alert at reduced costs. In addition to these, in situations where the owner loses his car keys or the keys are accidentally locked inside the car, the owner can unlock the car using his smart phone through a Bluetooth module and the output is shown using a gear motor. Raspberry Pi controller coordinates with different sensors like rain drop sensor, water level sensor, pressure sensor and vibration sensor to facilitate the features included in this project. To enhance the security of the car, a vibration sensor is included in the prototype and abnormal vibrations from the car door will be recorded as a robbery or a force open and alert is sent to the owner through a GSM module as SMS alert.
{"title":"Parameter Monitoring and Functionality Control in Automobiles Using Raspberry pi","authors":"Ms T Yathavi, Akshaya B, A. S., G. Kumaran, Meshach G, Shruthi A","doi":"10.1109/ICSCAN.2019.8878685","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878685","url":null,"abstract":"In the current scenario where the world is moving towards modernization and automation, personal cars have become an integral part of people’s lives. This project focuses on improving a car from ordinary to smart by constantly monitoring parameters such as pressure of the car tyre and fuel level. The prototype also communicates to the owner of the car through SMS alerts and audio output to intimate reduced fuel levels, nearby gas stations and low car tyre pressure. This project is also incorporated with features like rain sensing wipers and theft alert at reduced costs. In addition to these, in situations where the owner loses his car keys or the keys are accidentally locked inside the car, the owner can unlock the car using his smart phone through a Bluetooth module and the output is shown using a gear motor. Raspberry Pi controller coordinates with different sensors like rain drop sensor, water level sensor, pressure sensor and vibration sensor to facilitate the features included in this project. To enhance the security of the car, a vibration sensor is included in the prototype and abnormal vibrations from the car door will be recorded as a robbery or a force open and alert is sent to the owner through a GSM module as SMS alert.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115849118","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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