Pub Date : 2019-06-01DOI: 10.1109/ECAI46879.2019.9042086
A. Bărar, Alina Elena Marcu, P. Schiopu, M. Vlădescu
This paper presents the design considerations for a special solar spectrum simulator, based on LED technology, specifically conceived for the characterization of porphyrin-based dye-sensitized solar cells.
{"title":"Design of an LED-based solar spectrum simulator for porphyrin dye-sensitized solar cell characterization","authors":"A. Bărar, Alina Elena Marcu, P. Schiopu, M. Vlădescu","doi":"10.1109/ECAI46879.2019.9042086","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9042086","url":null,"abstract":"This paper presents the design considerations for a special solar spectrum simulator, based on LED technology, specifically conceived for the characterization of porphyrin-based dye-sensitized solar cells.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115124349","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 : 2019-06-01DOI: 10.1109/ECAI46879.2019.9042099
M. C. Arva, N. Bizon, Mirel Stanica, E. Diaconescu
The precise and efficient estimation of the DC component of the discrete periodic signals is required and used in many engineering and scientific fields of signal processing. In this paper there are presented several methods of estimating the DC component for discrete periodic signals. The main purpose of this paper is to show the influence of using a method of estimating DC offset on the precision of measurements and the present a comparison between several estimation methods. The estimation methods include the arithmetic mean method, the method using the Discreet Fourier Transform (DFT), the linear regression scattering method and the least squares method using high order interpolation. There are presented both theory elements and modeling and simulation elements specific to each method. An evaluation of the accuracy of the methods in which both the true error and the standard deviation are presented for each method is also performed.
{"title":"A Review of Different Estimation Methods of DC Offset Voltage For Periodic-Discrete Signals","authors":"M. C. Arva, N. Bizon, Mirel Stanica, E. Diaconescu","doi":"10.1109/ECAI46879.2019.9042099","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9042099","url":null,"abstract":"The precise and efficient estimation of the DC component of the discrete periodic signals is required and used in many engineering and scientific fields of signal processing. In this paper there are presented several methods of estimating the DC component for discrete periodic signals. The main purpose of this paper is to show the influence of using a method of estimating DC offset on the precision of measurements and the present a comparison between several estimation methods. The estimation methods include the arithmetic mean method, the method using the Discreet Fourier Transform (DFT), the linear regression scattering method and the least squares method using high order interpolation. There are presented both theory elements and modeling and simulation elements specific to each method. An evaluation of the accuracy of the methods in which both the true error and the standard deviation are presented for each method is also performed.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126767624","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 : 2019-06-01DOI: 10.1109/ECAI46879.2019.9042098
M. Muntean
In car park occupancy problem, large amounts of data are collected from sensors and stored in databases. In order to discover useful information from such data, data mining techniques are applied. In this paper I propose to find alternative solutions for Birmingham car park occupancy issue. Our approach consist in clustering first the dataset in order to obtain relevant periods of time within a day and then forecast data within these clusters. Our experiments show that splitting data into six clusters and predict car park occupancy with k-Nearest Neighbor technique lead to the highest forecast rates.
{"title":"Car Park Occupancy Rates Forecasting based on Cluster Analysis and kNN in Smart Cities","authors":"M. Muntean","doi":"10.1109/ECAI46879.2019.9042098","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9042098","url":null,"abstract":"In car park occupancy problem, large amounts of data are collected from sensors and stored in databases. In order to discover useful information from such data, data mining techniques are applied. In this paper I propose to find alternative solutions for Birmingham car park occupancy issue. Our approach consist in clustering first the dataset in order to obtain relevant periods of time within a day and then forecast data within these clusters. Our experiments show that splitting data into six clusters and predict car park occupancy with k-Nearest Neighbor technique lead to the highest forecast rates.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122880775","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 : 2019-06-01DOI: 10.1109/ECAI46879.2019.9041978
S. Tudor
This paper presents an analysis of the need to correlate the professional competences offered by the university studies programs in relation to the employability requirements of the graduates on the labor market. The study analyzes the concepts of competence versus transversal competences versus new competences required on the labor market; the applied part of the study focuses on the analysis of the students' perceptions from 4 university specializations (education sciences, psychology, sociology, communication sciences) on the competence of learning to learn from the perspective of fulfilling its performance descriptors during university studies. The conclusion of the study reflects the fulfillment of cognitive indicators (the ability to carry out various projects, initiative, entrepreneurship, digital culture), but the failure to fulfill the indicators of the social-emotional and motivational sphere.
{"title":"The Competence of Learning to Learn–An Indicator of Employability in the Labor Market","authors":"S. Tudor","doi":"10.1109/ECAI46879.2019.9041978","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9041978","url":null,"abstract":"This paper presents an analysis of the need to correlate the professional competences offered by the university studies programs in relation to the employability requirements of the graduates on the labor market. The study analyzes the concepts of competence versus transversal competences versus new competences required on the labor market; the applied part of the study focuses on the analysis of the students' perceptions from 4 university specializations (education sciences, psychology, sociology, communication sciences) on the competence of learning to learn from the perspective of fulfilling its performance descriptors during university studies. The conclusion of the study reflects the fulfillment of cognitive indicators (the ability to carry out various projects, initiative, entrepreneurship, digital culture), but the failure to fulfill the indicators of the social-emotional and motivational sphere.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129569489","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 : 2019-06-01DOI: 10.1109/ECAI46879.2019.9042052
A. Ene, C. Stirbu
Java is an objected oriented language that is platform independent. That is why it is widely used for Internet programming. A beginner that starts to study Java language has firstly to learn how an object is instantiated based on its constructor, how a public method is called from another class based on its signature and on class constructor, how a public and static method is called, based on its signature and on class name, how a public instance variable can be used in a method defined in a different class and how to access a constant defined in class in another class. In this paper it is presented an automatic way of generating random questions concerning these basic issues. These questions are presented to the student and he has to edit his answers. The paper also presents an automatic way of verifying the correctitude of the answers.
{"title":"Automatic generation of quizzes for Java programming language","authors":"A. Ene, C. Stirbu","doi":"10.1109/ECAI46879.2019.9042052","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9042052","url":null,"abstract":"Java is an objected oriented language that is platform independent. That is why it is widely used for Internet programming. A beginner that starts to study Java language has firstly to learn how an object is instantiated based on its constructor, how a public method is called from another class based on its signature and on class constructor, how a public and static method is called, based on its signature and on class name, how a public instance variable can be used in a method defined in a different class and how to access a constant defined in class in another class. In this paper it is presented an automatic way of generating random questions concerning these basic issues. These questions are presented to the student and he has to edit his answers. The paper also presents an automatic way of verifying the correctitude of the answers.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129875156","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 : 2019-06-01DOI: 10.1109/ECAI46879.2019.9041953
M. Ianculescu, Ovidiu Bîcă, A. Balog, Irina Cristescu
The smart citizen is a citizen not only accustomed with the daily use of digital technology, but one who feels empowered and entitled to actively participate at designing and improving the online public services in his direct benefit and also for his city advantage. Smart technologies have become a compulsory driver for establishing a proper foundation inside a smart city. This paper focuses on presenting the smart citizen as an enabler of better online public services in the context of a smart city. For illustrating his participative role, a proposed functional architecture for enhancing online public services is put in.
{"title":"Smart citizen - a participatory co-creator for enhancing online public services","authors":"M. Ianculescu, Ovidiu Bîcă, A. Balog, Irina Cristescu","doi":"10.1109/ECAI46879.2019.9041953","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9041953","url":null,"abstract":"The smart citizen is a citizen not only accustomed with the daily use of digital technology, but one who feels empowered and entitled to actively participate at designing and improving the online public services in his direct benefit and also for his city advantage. Smart technologies have become a compulsory driver for establishing a proper foundation inside a smart city. This paper focuses on presenting the smart citizen as an enabler of better online public services in the context of a smart city. For illustrating his participative role, a proposed functional architecture for enhancing online public services is put in.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129910208","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 : 2019-06-01DOI: 10.1109/ECAI46879.2019.9042080
Soraya Chalard, S. Sinthupinyo
Social network visualization has been extensively studied in research in diffusion of information. This paper focuses on extracting propagated Facebook posts from keywords created by users and visualizing important information diffusion path in social network graph. Furthermore, some interesting propagation patterns of user behavior in online social network were discovered. Our research contributions could be summarized as follow: 1) A novel method was proposed to determine the keyword occurrence in online social network, 2) This research constructed the map of keyword propagation and visualized the propagation patterns among different groups of people and 3) a case study of social phenomena was shown. In sum, our work eventually could be applied to improve the performance of tracking keyword spread in social media and would be beneficial for greater understanding about user behavior.
{"title":"Constructing Keyword Propagation Map of Facebook Pages","authors":"Soraya Chalard, S. Sinthupinyo","doi":"10.1109/ECAI46879.2019.9042080","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9042080","url":null,"abstract":"Social network visualization has been extensively studied in research in diffusion of information. This paper focuses on extracting propagated Facebook posts from keywords created by users and visualizing important information diffusion path in social network graph. Furthermore, some interesting propagation patterns of user behavior in online social network were discovered. Our research contributions could be summarized as follow: 1) A novel method was proposed to determine the keyword occurrence in online social network, 2) This research constructed the map of keyword propagation and visualized the propagation patterns among different groups of people and 3) a case study of social phenomena was shown. In sum, our work eventually could be applied to improve the performance of tracking keyword spread in social media and would be beneficial for greater understanding about user behavior.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"229 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120889640","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 : 2019-06-01DOI: 10.1109/ECAI46879.2019.9042118
Delia Duminică
The aim of this study is to reveal the consequences, both positive and negative, of applying the GROW method for professional training of staff from Generali Company of Insurance. The human resource is one of the most important resources for organizations, regardless of the type of activity, which provides the organizations with the source of performance, profitability and market positioning. This the reason why companies must invest all kind of resources (time, money, specialists) into staff training. From all professional training of staff methods, we have chosen the GROW method, a well-known process for goal setting and problem solving. The conclusions of this study show that the GROW method is efficient if properly applied. However, for the efficiency of the method, the manager's working method, the way of application, the need to adapt to the person with whom he works are very well understood. Of course, the manager's experience influences the effectiveness of the method.
{"title":"Professional Training of Staff from Organizations through the GROW Method","authors":"Delia Duminică","doi":"10.1109/ECAI46879.2019.9042118","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9042118","url":null,"abstract":"The aim of this study is to reveal the consequences, both positive and negative, of applying the GROW method for professional training of staff from Generali Company of Insurance. The human resource is one of the most important resources for organizations, regardless of the type of activity, which provides the organizations with the source of performance, profitability and market positioning. This the reason why companies must invest all kind of resources (time, money, specialists) into staff training. From all professional training of staff methods, we have chosen the GROW method, a well-known process for goal setting and problem solving. The conclusions of this study show that the GROW method is efficient if properly applied. However, for the efficiency of the method, the manager's working method, the way of application, the need to adapt to the person with whom he works are very well understood. Of course, the manager's experience influences the effectiveness of the method.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127740718","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 : 2019-06-01DOI: 10.1109/ECAI46879.2019.9042120
R. Radescu, M. Dragu
This paper is motivated by the possibility of developing a wide variety of applications and domains in which Unmanned Aerial Vehicles (UAVs) can be used globally for various purposes. UAVs are currently used by public administrations and security forces such as police, fire brigades, civil protection, research institutions, construction, and agriculture entities. The purpose of this paper is to facilitate the handling of UAVs to retrieve various data from the environment. The drone (UAV) visits some points to collect data (image and/or video input) from sensors like GPS, camera, gyroscope, and accelerometer. GPS sensor coordinates are used to compare the data taken with subsequent results through processing with specialized software. The drone is used as an access gate with built-in sensors. Certain hazard events (fires, floods, avalanches, landslides) are not limited to narrow geographical areas, but can impact the environment by triggering negative chain events. 3D modeling offers a wide range of possibilities to prevent potential hazard events, or, if such an event has occurred, makes it possible to monitor the affected area and assess the damage by comparing the area in the pre-event configuration with the after-event one. After image processing and data acquisition, a report is generated that includes the map and the 3D model of the analyzed object. A hazard is an agent that has the potential to cause damage to a particular target. Terms such as risk or danger can be used in similar contexts. TensorFlow is an open source software library in high-performance computing. Flexible architecture allows easy deployment of computing on a variety of platforms (CPU, GPU, TPU), from desktop to server or mobile devices. We used the learning transfer: at first we used a model that was already prepared for another problem, and then we re-qualified it on a similar problem. Deep learning from scratch can take several days, but learning transfer can be done shortly. We applied Python along with TensorFlow to train an image classifier and classify images with it. We formed a consistent set of training pictures, using three labels: fire, flood (detectable hazards) and nature (non-hazard images). We then re-qualified an efficient, small-sized neural network by (re)training the image set in order to get the best results in the hazards prediction selection process with a progressive higher accuracy as (re) training evolves at optimal rating. With Python and OpenCV technologies, we used four decision algorithms to generate prediction of hazard: Support Vector Machine, Naive Bayes, Logistic Regression, and Decision Tree Classifier. Each generated report includes precision, recall, f1-score, and support indices, depending on the class and intervals used. We also used the confusion matrix as an alternative method to evaluate the classification accuracy. Analyzing the 4 algorithms we noticed that they behave differently. Training using TensorFlow generated better resu
{"title":"Automatic Analysis of Potential Hazard Events Using Unmanned Aerial Vehicles","authors":"R. Radescu, M. Dragu","doi":"10.1109/ECAI46879.2019.9042120","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9042120","url":null,"abstract":"This paper is motivated by the possibility of developing a wide variety of applications and domains in which Unmanned Aerial Vehicles (UAVs) can be used globally for various purposes. UAVs are currently used by public administrations and security forces such as police, fire brigades, civil protection, research institutions, construction, and agriculture entities. The purpose of this paper is to facilitate the handling of UAVs to retrieve various data from the environment. The drone (UAV) visits some points to collect data (image and/or video input) from sensors like GPS, camera, gyroscope, and accelerometer. GPS sensor coordinates are used to compare the data taken with subsequent results through processing with specialized software. The drone is used as an access gate with built-in sensors. Certain hazard events (fires, floods, avalanches, landslides) are not limited to narrow geographical areas, but can impact the environment by triggering negative chain events. 3D modeling offers a wide range of possibilities to prevent potential hazard events, or, if such an event has occurred, makes it possible to monitor the affected area and assess the damage by comparing the area in the pre-event configuration with the after-event one. After image processing and data acquisition, a report is generated that includes the map and the 3D model of the analyzed object. A hazard is an agent that has the potential to cause damage to a particular target. Terms such as risk or danger can be used in similar contexts. TensorFlow is an open source software library in high-performance computing. Flexible architecture allows easy deployment of computing on a variety of platforms (CPU, GPU, TPU), from desktop to server or mobile devices. We used the learning transfer: at first we used a model that was already prepared for another problem, and then we re-qualified it on a similar problem. Deep learning from scratch can take several days, but learning transfer can be done shortly. We applied Python along with TensorFlow to train an image classifier and classify images with it. We formed a consistent set of training pictures, using three labels: fire, flood (detectable hazards) and nature (non-hazard images). We then re-qualified an efficient, small-sized neural network by (re)training the image set in order to get the best results in the hazards prediction selection process with a progressive higher accuracy as (re) training evolves at optimal rating. With Python and OpenCV technologies, we used four decision algorithms to generate prediction of hazard: Support Vector Machine, Naive Bayes, Logistic Regression, and Decision Tree Classifier. Each generated report includes precision, recall, f1-score, and support indices, depending on the class and intervals used. We also used the confusion matrix as an alternative method to evaluate the classification accuracy. Analyzing the 4 algorithms we noticed that they behave differently. Training using TensorFlow generated better resu","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"20 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125841481","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 : 2019-06-01DOI: 10.1109/ECAI46879.2019.9041999
Jianu Eugenia, M. Oproescu, Dumitru Tudosoiu
This paper presents an image of the pre-university education seen through the eyes of the school manager. Management is a conscious process of managing and coordinating individual and group actions and activities, as well as mobilizing and allocating the organization's resources to meet its objectives in accordance with its mission, goals and economic and social responsibilities. Educational management is a methodology of a global - optimal - strategic approach to education, but not a model for the management of the basic unit of the education system applicable to the complex school organization.
{"title":"Romanian pre-university education from the perspective of school management","authors":"Jianu Eugenia, M. Oproescu, Dumitru Tudosoiu","doi":"10.1109/ECAI46879.2019.9041999","DOIUrl":"https://doi.org/10.1109/ECAI46879.2019.9041999","url":null,"abstract":"This paper presents an image of the pre-university education seen through the eyes of the school manager. Management is a conscious process of managing and coordinating individual and group actions and activities, as well as mobilizing and allocating the organization's resources to meet its objectives in accordance with its mission, goals and economic and social responsibilities. Educational management is a methodology of a global - optimal - strategic approach to education, but not a model for the management of the basic unit of the education system applicable to the complex school organization.","PeriodicalId":285780,"journal":{"name":"2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134207781","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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