Pub Date : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464143
Rino Kaburagi, Yudai Ishimaru, W. Chin, Akihiro Yorita, N. Kubota, S. Egerton
As the importance of lifelong learning and recurrent education has been emphasized in recent years, it can be argued that people must study for the rest of their lives. Many people, however, find it difficult to engage in and maintain learning behavior, and adequate learning support is required for people to participate in and maintain learning. We developed a learning support system based on the learner’s self-efficacy by the robot partner and explored its utility in this study to create an efficient learning support system by a robot partner. As a result, the proposed method’s effectiveness was demonstrated by the fact that the proposed learning support system increased the learner’s self-efficacy.
{"title":"Lifelong Robot Edutainment based on Self-Efficacy","authors":"Rino Kaburagi, Yudai Ishimaru, W. Chin, Akihiro Yorita, N. Kubota, S. Egerton","doi":"10.1109/CYBCONF51991.2021.9464143","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464143","url":null,"abstract":"As the importance of lifelong learning and recurrent education has been emphasized in recent years, it can be argued that people must study for the rest of their lives. Many people, however, find it difficult to engage in and maintain learning behavior, and adequate learning support is required for people to participate in and maintain learning. We developed a learning support system based on the learner’s self-efficacy by the robot partner and explored its utility in this study to create an efficient learning support system by a robot partner. As a result, the proposed method’s effectiveness was demonstrated by the fact that the proposed learning support system increased the learner’s self-efficacy.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134592195","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 : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464135
T. Murata, A. Fukushima, Takuya Harada, Mie Sasaki
In this paper, we conduct an investigation of available time for automated external defibrillators (AED) in a Japanese city. In Japan, there are about 600,000 AEDs available in cities or towns, but only 4.9% of AEDs are used by bystanders when citizens suffer a sudden cardiac arrest. One reason of such low usage rate comes from their available time. Since many AEDs are installed by business owners, they are not available when their business is closed. We investigate the available time of AEDs in a Japanese city, Takatsuki, Osaka Japan. The number of AEDs that are available 24 hours can be increased by installing new AEDs in 24-hour convenience stores and a koban that is a small police station with policemen.
{"title":"Social Awareness from Analysis of Available Time for Automated External Defibrillators in a City","authors":"T. Murata, A. Fukushima, Takuya Harada, Mie Sasaki","doi":"10.1109/CYBCONF51991.2021.9464135","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464135","url":null,"abstract":"In this paper, we conduct an investigation of available time for automated external defibrillators (AED) in a Japanese city. In Japan, there are about 600,000 AEDs available in cities or towns, but only 4.9% of AEDs are used by bystanders when citizens suffer a sudden cardiac arrest. One reason of such low usage rate comes from their available time. Since many AEDs are installed by business owners, they are not available when their business is closed. We investigate the available time of AEDs in a Japanese city, Takatsuki, Osaka Japan. The number of AEDs that are available 24 hours can be increased by installing new AEDs in 24-hour convenience stores and a koban that is a small police station with policemen.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132085667","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 : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464139
Kazunori Oka, Takumi Hirahara, Yasunobu Nohara, Sozo Inoue, K. Arimura, Syoji Kobashi, K. Iihara
Intracerebral hematoma (ICH) is the cause of intracerebral hemorrhage. Acute enlargement of the ICH is high risk, and emergency surgical treatment is required. Therefore, prediction of ICH enlargement is essential to improve a survival rate and outcome. The purpose of this study is to find factors to predict the ICH enlargement with thick slice head CT images. We propose three kinds of feature extraction methods, (1) shape and texture features, (2) layered texture features, and (3) anatomical location features. In addition, we introduce an ICH enlargement prediction method using support vector machine (SVM) and feature selection. The experimental results showed that the angular second order moment of the texture feature was the most effective in predicting the ICH enlargement. By using this feature, we were able to predict the ICH enlargement with an accuracy of 75.7%. In addition, we found that normalization of the location and posture improved the prediction accuracy by 2.7% compared to that without normalization.
{"title":"Predictors of Intracerebral Hematoma Enlargement Using Brain CT Images in Emergency Medical Care","authors":"Kazunori Oka, Takumi Hirahara, Yasunobu Nohara, Sozo Inoue, K. Arimura, Syoji Kobashi, K. Iihara","doi":"10.1109/CYBCONF51991.2021.9464139","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464139","url":null,"abstract":"Intracerebral hematoma (ICH) is the cause of intracerebral hemorrhage. Acute enlargement of the ICH is high risk, and emergency surgical treatment is required. Therefore, prediction of ICH enlargement is essential to improve a survival rate and outcome. The purpose of this study is to find factors to predict the ICH enlargement with thick slice head CT images. We propose three kinds of feature extraction methods, (1) shape and texture features, (2) layered texture features, and (3) anatomical location features. In addition, we introduce an ICH enlargement prediction method using support vector machine (SVM) and feature selection. The experimental results showed that the angular second order moment of the texture feature was the most effective in predicting the ICH enlargement. By using this feature, we were able to predict the ICH enlargement with an accuracy of 75.7%. In addition, we found that normalization of the location and posture improved the prediction accuracy by 2.7% compared to that without normalization.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127199524","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 : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464150
T. Murata, Kohei Totsuka
In this paper, we develop an agent-based simulation model to avoid tourist concentration in a sightseeing area. Among main tourist destinations, the tourist concentration called "overtourism" becomes an issue for both of tourists and residents in the destinations. While spreading COVID-19 among sightseeing areas, tourist concentration should be avoided from the standpoint of the public health. We develop an agent-based simulation model to estimate the effectiveness of "congestion information at the destination" among tourists. The simulation results show that the congestion information is effective when only 30% of tourists follow the information to avoid the concentration in the major attractions in a sightseeing area.
{"title":"Agent-Based Simulation for Avoiding the Congestions of Tourists","authors":"T. Murata, Kohei Totsuka","doi":"10.1109/CYBCONF51991.2021.9464150","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464150","url":null,"abstract":"In this paper, we develop an agent-based simulation model to avoid tourist concentration in a sightseeing area. Among main tourist destinations, the tourist concentration called \"overtourism\" becomes an issue for both of tourists and residents in the destinations. While spreading COVID-19 among sightseeing areas, tourist concentration should be avoided from the standpoint of the public health. We develop an agent-based simulation model to estimate the effectiveness of \"congestion information at the destination\" among tourists. The simulation results show that the congestion information is effective when only 30% of tourists follow the information to avoid the concentration in the major attractions in a sightseeing area.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"IM-36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126639661","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 : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464133
Shuri Nakamura, Y. Hata, N. Yagi, Naoko Kawamura, H. Kashioka, T. Yanagida, Masayuki Hirata, Hitoshi Maezawa, Y. Sakai
This paper describes a relationship between singing experience and laryngeal movement obtained by DeepLabCut software to investigate whether singing improves swallowing function. First, we track the coordinates of the laryngeal region in videos captured swallowing movements by using DeepLabCut. Second, we remove the unusual outliers, and perform linear interpolation and the normalization for the obtained coordinates. Third, we extracted the features such as RMS, peak width and swallowing time. Finally, we did Welch's test to them against two groups: one with singing experience and the other without singing experience. As a result, we found the feature with a significant difference, and that the singing experience affected the swallowing time.
{"title":"Relationship between Singing Experience and Laryngeal Movement Obtained by DeepLabCut","authors":"Shuri Nakamura, Y. Hata, N. Yagi, Naoko Kawamura, H. Kashioka, T. Yanagida, Masayuki Hirata, Hitoshi Maezawa, Y. Sakai","doi":"10.1109/CYBCONF51991.2021.9464133","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464133","url":null,"abstract":"This paper describes a relationship between singing experience and laryngeal movement obtained by DeepLabCut software to investigate whether singing improves swallowing function. First, we track the coordinates of the laryngeal region in videos captured swallowing movements by using DeepLabCut. Second, we remove the unusual outliers, and perform linear interpolation and the normalization for the obtained coordinates. Third, we extracted the features such as RMS, peak width and swallowing time. Finally, we did Welch's test to them against two groups: one with singing experience and the other without singing experience. As a result, we found the feature with a significant difference, and that the singing experience affected the swallowing time.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114253632","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 : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464134
Shoya Kusunose, Yuki Shinomiya, Takashi Ushiwaka, N. Maeda, Y. Hoshino
This paper focuses on the analysis of behavior of immune cells for supporting diagnosis. The previous work has proposed to detect immune cells from medical images by recognition frequency space. However, the work has a problem that selects a region including multiple cells as a single cell. This paper aims to relax the problem by focusing the locality of cell shapes. Our proposal uses gradient-weighted class activation mapping (GradCAM) to capture locality characteristics of immune cells. The results shows that the densely inhabited immune cells are correctly selected. Our proposal has some issues that a cell is occasionally detected as multiple ones. We consider that this issue is can be solved by image processing techniques such as non-maximum suppression.
{"title":"Improving Individually Selectness for Immune Cells using GradCAM","authors":"Shoya Kusunose, Yuki Shinomiya, Takashi Ushiwaka, N. Maeda, Y. Hoshino","doi":"10.1109/CYBCONF51991.2021.9464134","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464134","url":null,"abstract":"This paper focuses on the analysis of behavior of immune cells for supporting diagnosis. The previous work has proposed to detect immune cells from medical images by recognition frequency space. However, the work has a problem that selects a region including multiple cells as a single cell. This paper aims to relax the problem by focusing the locality of cell shapes. Our proposal uses gradient-weighted class activation mapping (GradCAM) to capture locality characteristics of immune cells. The results shows that the densely inhabited immune cells are correctly selected. Our proposal has some issues that a cell is occasionally detected as multiple ones. We consider that this issue is can be solved by image processing techniques such as non-maximum suppression.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"11 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133664088","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 : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464144
Fengkai Guo, Yan Pei
In this paper, we attempt to use a method of estimating a convergence point of the population to accelerate the search of the multi-objective chaotic evolution optimization. The movement vectors between generations have powerful information for inducing the search direction of the global optimum solution. We use these movement vectors that are composed of the non-dominated Pareto solutions to estimate a convergence point in which is the first Pareto front solution to enhance the search of multi-objective chaotic evolution algorithm. The estimated point is constricted by the movement vectors, and we use the estimated point to replace the population’s dominated solution to achieve the objective of enhancing the multi-objective chaotic evolution algorithm. We use hypervolume, generational distance, and inverted generational distance to evaluate our proposal. The result indicates that using an estimated point can accelerate the search of the multi-objective chaotic evolution algorithm.
{"title":"Enhancing multi-objective chaotic evolution algorithm using an estimated convergence point","authors":"Fengkai Guo, Yan Pei","doi":"10.1109/CYBCONF51991.2021.9464144","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464144","url":null,"abstract":"In this paper, we attempt to use a method of estimating a convergence point of the population to accelerate the search of the multi-objective chaotic evolution optimization. The movement vectors between generations have powerful information for inducing the search direction of the global optimum solution. We use these movement vectors that are composed of the non-dominated Pareto solutions to estimate a convergence point in which is the first Pareto front solution to enhance the search of multi-objective chaotic evolution algorithm. The estimated point is constricted by the movement vectors, and we use the estimated point to replace the population’s dominated solution to achieve the objective of enhancing the multi-objective chaotic evolution algorithm. We use hypervolume, generational distance, and inverted generational distance to evaluate our proposal. The result indicates that using an estimated point can accelerate the search of the multi-objective chaotic evolution algorithm.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114484002","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 : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464151
M. Ohsaki, Hayato Sasaki, Naoya Kishimoto, S. Katagiri, K. Ohnishi, Yakub Sebastian, P. Then
It is desired in a variety of fields to identify which variables are dependent, and variable dependence measures have been studied. The majority of such measures detect a linear or a certain range of nonlinear dependence between paired variables. To go beyond them, a method based on Neural Network Regression, Group Lasso, and Information Aggregation has been proposed in our past study. It can detect a wide range of nonlinear dependences among multi variables and discover the sets and representatives of the detected dependences. Its fundamental effectiveness has already been examined using synthesized artificial datasets containing a single dependence. For further evaluation in the present study, we conducted an experiment using those containing multi dependences. The proposed method succeeded in discovering the sets and representatives, and its performance was robust to data size and noise rate. The experimental results suggested that the proposed method works well for difficult tasks to handle multi dependences.
{"title":"Evaluation of the Neural-network-based Method to Discover Sets and Representatives of Nonlinearly Dependent Variables","authors":"M. Ohsaki, Hayato Sasaki, Naoya Kishimoto, S. Katagiri, K. Ohnishi, Yakub Sebastian, P. Then","doi":"10.1109/CYBCONF51991.2021.9464151","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464151","url":null,"abstract":"It is desired in a variety of fields to identify which variables are dependent, and variable dependence measures have been studied. The majority of such measures detect a linear or a certain range of nonlinear dependence between paired variables. To go beyond them, a method based on Neural Network Regression, Group Lasso, and Information Aggregation has been proposed in our past study. It can detect a wide range of nonlinear dependences among multi variables and discover the sets and representatives of the detected dependences. Its fundamental effectiveness has already been examined using synthesized artificial datasets containing a single dependence. For further evaluation in the present study, we conducted an experiment using those containing multi dependences. The proposed method succeeded in discovering the sets and representatives, and its performance was robust to data size and noise rate. The experimental results suggested that the proposed method works well for difficult tasks to handle multi dependences.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122725584","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 : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464148
Xiaosong Zhao, Qiangfu Zhao
The application of machine learning in stock market prediction has generated widespread attention. This paper proposes a new method for short-term stock investment using optimized LightGBM based on cost awareness. By cost awareness here we define that the decision process is more aware of the false-positive errors, or is more aware of ‘fake chances’, and the cost for investment can be reduced. The main contribution of the research is to design an investment method for stock price prediction. Based on the principles of short-term investment and current quantitative investment research, we select a series of technical indicators that meet the requirements of this research to improve the reliability of the prediction results. We propose the concept of cost awareness to improve the accuracy of prediction. By comparing with the previous results, we demonstrated that the performance of the optimized model based on cost awareness could be improved significantly. we eventually examined and compared results with XGBoost and Random Forest, and found that LightGBM provides better performances in prediction accuracy, profitability, and risk control ability.
{"title":"Stock Prediction Using Optimized LightGBM Based on Cost Awareness","authors":"Xiaosong Zhao, Qiangfu Zhao","doi":"10.1109/CYBCONF51991.2021.9464148","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464148","url":null,"abstract":"The application of machine learning in stock market prediction has generated widespread attention. This paper proposes a new method for short-term stock investment using optimized LightGBM based on cost awareness. By cost awareness here we define that the decision process is more aware of the false-positive errors, or is more aware of ‘fake chances’, and the cost for investment can be reduced. The main contribution of the research is to design an investment method for stock price prediction. Based on the principles of short-term investment and current quantitative investment research, we select a series of technical indicators that meet the requirements of this research to improve the reliability of the prediction results. We propose the concept of cost awareness to improve the accuracy of prediction. By comparing with the previous results, we demonstrated that the performance of the optimized model based on cost awareness could be improved significantly. we eventually examined and compared results with XGBoost and Random Forest, and found that LightGBM provides better performances in prediction accuracy, profitability, and risk control ability.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114159692","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 : 2021-06-08DOI: 10.1109/CYBCONF51991.2021.9464146
Hideaki Hoshino, Kento Morita, D. Takeda, T. Hasegawa, T. Wakabayashi
In recent years, osteotomy has been used as a treatment for osteomyelitis of the jaw. However, the extent of osteomyelitis that can be determined from preoperative images is ambiguous, which causes problems such as lengthy surgery. Therefore, it is necessary to estimate the resection area with high accuracy. In this study, we proposed a method that combines deep metric learning and anomaly detection to estimate the area of osteomyelitis before surgery. As a result of experiments, we were able to estimate the presence or absence of osteomyelitis with F value of 0.85.
{"title":"Automatic osteomyelitis area estimation in head CT using anomaly detection","authors":"Hideaki Hoshino, Kento Morita, D. Takeda, T. Hasegawa, T. Wakabayashi","doi":"10.1109/CYBCONF51991.2021.9464146","DOIUrl":"https://doi.org/10.1109/CYBCONF51991.2021.9464146","url":null,"abstract":"In recent years, osteotomy has been used as a treatment for osteomyelitis of the jaw. However, the extent of osteomyelitis that can be determined from preoperative images is ambiguous, which causes problems such as lengthy surgery. Therefore, it is necessary to estimate the resection area with high accuracy. In this study, we proposed a method that combines deep metric learning and anomaly detection to estimate the area of osteomyelitis before surgery. As a result of experiments, we were able to estimate the presence or absence of osteomyelitis with F value of 0.85.","PeriodicalId":231194,"journal":{"name":"2021 5th IEEE International Conference on Cybernetics (CYBCONF)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115602862","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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