Pub Date : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00152
Yusuke Sato, Nobuyuki Kobayashi, S. Shirasaka
Rapid economic changes have recently been requesting human resource departments in Japanese firms to transform their roles and services. [1] No paper refers a method to map the themes they talk about and to discuss these issues explicitly by using the Harvard Model and Organization Strategy and Management Type. In this paper, we propose a method using the Harvard Model and Organization Strategy and Management Type. The method is divided into Visualization Map of HR Systems based on Life Cycle and Organization Strategy and Management Type. We asked employees of Human Resource Departments to use worksheets of "visualization map of HR systems based on life cycle" and "Organization Strategy and Management Type". Then, we evaluated the two points on whether they thought the HR System of their company was appropriate and whether they could write down and explain the HR System to other people. As a result, we confirmed that we achieved the goal of identifying issues of the firm and facilitating discussions with management and HR employees of other companies. In addition, this method could play a role in a training program for people who have a little experience as employees of Human Resource Departments.
{"title":"A Proposal of HR System's Visualization Based on Harvard Model, Life Cycle, and Organization Strategy and Management Type","authors":"Yusuke Sato, Nobuyuki Kobayashi, S. Shirasaka","doi":"10.1109/IIAI-AAI.2019.00152","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00152","url":null,"abstract":"Rapid economic changes have recently been requesting human resource departments in Japanese firms to transform their roles and services. [1] No paper refers a method to map the themes they talk about and to discuss these issues explicitly by using the Harvard Model and Organization Strategy and Management Type. In this paper, we propose a method using the Harvard Model and Organization Strategy and Management Type. The method is divided into Visualization Map of HR Systems based on Life Cycle and Organization Strategy and Management Type. We asked employees of Human Resource Departments to use worksheets of \"visualization map of HR systems based on life cycle\" and \"Organization Strategy and Management Type\". Then, we evaluated the two points on whether they thought the HR System of their company was appropriate and whether they could write down and explain the HR System to other people. As a result, we confirmed that we achieved the goal of identifying issues of the firm and facilitating discussions with management and HR employees of other companies. In addition, this method could play a role in a training program for people who have a little experience as employees of Human Resource Departments.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132125852","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 : 2019-07-01DOI: 10.1109/iiai-aai.2019.00011
{"title":"Keynote: Ford Gaol, Ph.D.","authors":"","doi":"10.1109/iiai-aai.2019.00011","DOIUrl":"https://doi.org/10.1109/iiai-aai.2019.00011","url":null,"abstract":"","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115519420","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 : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00020
Genkou Ou, Kei Wakabayashi, T. Satoh
With the spread of the internet as social infrastructure, more and more people are shopping online. Online sites that formerly dealt with such specific products as books and clothing have also expanded to mall-type shopping sites by incorporating various kinds of stores. As a result, searching for products has become more complicated and prolonged. In this paper, we propose a method that models product-searching behavior based on the transition of the search words input by users. Since a query is generally composed of one or more search words, their information content is calculated in advance from query logs. Thus, varying the information content of the user's query sequences can be classified as a model of user searching behaviors. From analysis results using actual data, we confirmed that our proposed method effectively models product-searching behavior.
{"title":"Searching Behavior Analysis of Online Shopping Based on Information Content of Query Words","authors":"Genkou Ou, Kei Wakabayashi, T. Satoh","doi":"10.1109/IIAI-AAI.2019.00020","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00020","url":null,"abstract":"With the spread of the internet as social infrastructure, more and more people are shopping online. Online sites that formerly dealt with such specific products as books and clothing have also expanded to mall-type shopping sites by incorporating various kinds of stores. As a result, searching for products has become more complicated and prolonged. In this paper, we propose a method that models product-searching behavior based on the transition of the search words input by users. Since a query is generally composed of one or more search words, their information content is calculated in advance from query logs. Thus, varying the information content of the user's query sequences can be classified as a model of user searching behaviors. From analysis results using actual data, we confirmed that our proposed method effectively models product-searching behavior.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115332565","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 : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00235
J. Lo, Hui-Ying Lin
Recently, it is more and more difficult to make a decision because we receive a large amount of information through the Internet every day. Therefore, the recommender system becomes more and more popular. It can help users making decisions effectively by providing suitable suggestions to users, and those suggestions were processed according to users' browsing history and transaction. Therefore, the development of the recommender system in this research is based on cloud platform and focuses on providing location-based search and intelligent recommendation for resource objects. First, we will automatically through the pre-processing process, crawler technology and APIs provided by social networking sites, and use these data descriptions to enhance data search with correctness. Moreover, we design and build an integrated tourism augmented reality navigation system with recommendation technology and dynamic route planning which covers all tourism activities. The service also provided various valued-added services, such as wikitude Augmented Reality, subject guidance including POI, LOI and SOI, and stored trajectory path of users. Therefore, the user may have a story-based touring guidance while surfing the cultural and historic contents in advance.
{"title":"An Intelligent Touring Recommendation System Using the Deep Learning and Augmented Reality Technology-Case Study of Toucheng Historic Street","authors":"J. Lo, Hui-Ying Lin","doi":"10.1109/IIAI-AAI.2019.00235","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00235","url":null,"abstract":"Recently, it is more and more difficult to make a decision because we receive a large amount of information through the Internet every day. Therefore, the recommender system becomes more and more popular. It can help users making decisions effectively by providing suitable suggestions to users, and those suggestions were processed according to users' browsing history and transaction. Therefore, the development of the recommender system in this research is based on cloud platform and focuses on providing location-based search and intelligent recommendation for resource objects. First, we will automatically through the pre-processing process, crawler technology and APIs provided by social networking sites, and use these data descriptions to enhance data search with correctness. Moreover, we design and build an integrated tourism augmented reality navigation system with recommendation technology and dynamic route planning which covers all tourism activities. The service also provided various valued-added services, such as wikitude Augmented Reality, subject guidance including POI, LOI and SOI, and stored trajectory path of users. Therefore, the user may have a story-based touring guidance while surfing the cultural and historic contents in advance.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114554595","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 : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00028
Ya-Chu Chuang, Yung-Ming Li
With the rapid development of technology, the business model of the tourism industry has changed. More and more people need to rent the houses, and it is easier for customers to use and get information on the Internet. In the era of Web 2.0, consumers can leave rating scores and write reviews on the online social platforms to share their experience with others. Nonetheless, there may exist some spam reviews. In this paper, we propose a novel approach to detect user profiles and spam reviews so as to generate a rental house recommendation. With this new mechanism, consumers can receive an appropriate recommendation from their own basic information, preference, and their close friends or family who are with powerful influence on them. Also, with the support of the proposed mechanism, less fake or useless reviews influence them.
{"title":"Detecting Spam Reviews for Improving House Sharing Recommendation","authors":"Ya-Chu Chuang, Yung-Ming Li","doi":"10.1109/IIAI-AAI.2019.00028","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00028","url":null,"abstract":"With the rapid development of technology, the business model of the tourism industry has changed. More and more people need to rent the houses, and it is easier for customers to use and get information on the Internet. In the era of Web 2.0, consumers can leave rating scores and write reviews on the online social platforms to share their experience with others. Nonetheless, there may exist some spam reviews. In this paper, we propose a novel approach to detect user profiles and spam reviews so as to generate a rental house recommendation. With this new mechanism, consumers can receive an appropriate recommendation from their own basic information, preference, and their close friends or family who are with powerful influence on them. Also, with the support of the proposed mechanism, less fake or useless reviews influence them.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123195972","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 : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00135
Yoshiyuki Suimon, Hiroki Sakaji, T. Shimada, K. Izumi, Hiroyasu Matsushima
In recent years, overseas financial system crises (e.g., Lehman shock and European debt crisis) and the effects of monetary policy changes by US and European central banks exerted major influence on the Japanese interest rates market. In this research, we developed a forecasting model of Japanese interest rate based on a variety of machine learning methods, by considering the information obtained from overseas rates markets and currency markets. Finally, we confirmed that the prediction accuracy of Japanese long-term interest rate improved by using the US interest rates data in addition to the Japanese interest rates data for machine learning. Furthermore, we confirmed that the prediction accuracy increased by using US and Japanese rates markets data in recent years, particularly after 2006. This result suggests that information of overseas interest rates can be used to forecast Japanese rates market nowadays.
{"title":"Extraction of Relationship between Japanese and US Interest Rates using Machine Learning Methods","authors":"Yoshiyuki Suimon, Hiroki Sakaji, T. Shimada, K. Izumi, Hiroyasu Matsushima","doi":"10.1109/IIAI-AAI.2019.00135","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00135","url":null,"abstract":"In recent years, overseas financial system crises (e.g., Lehman shock and European debt crisis) and the effects of monetary policy changes by US and European central banks exerted major influence on the Japanese interest rates market. In this research, we developed a forecasting model of Japanese interest rate based on a variety of machine learning methods, by considering the information obtained from overseas rates markets and currency markets. Finally, we confirmed that the prediction accuracy of Japanese long-term interest rate improved by using the US interest rates data in addition to the Japanese interest rates data for machine learning. Furthermore, we confirmed that the prediction accuracy increased by using US and Japanese rates markets data in recent years, particularly after 2006. This result suggests that information of overseas interest rates can be used to forecast Japanese rates market nowadays.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122174303","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 : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00175
Elisa Indriasari, F. Gaol, T. Matsuo
Discussions related to the Digital Banking (DB) transformation has become the main issues in the industry nowadays. Digital disruption has changed the way peoples do business and perform transactions. However, the bankers still found many problems when performing DB transformation. Main issues on DB transformation are that many banks still assume that digital transformation is about workflows and systems rather than focus on customer experience. Nowadays, Artificial Intelligence (AI) and Big Data Analytics (BDA) have risen and played as an important role in the new banking era. The recent trend of AI and BDA enable banking to be more customer-centric based on data driven. Personalization service becoming an important strategy for leveraging the existing customer engagement, and attracting potential customer become new customers. This study explores the application of AI and BDA in banking for leveraging customer experience. This study used literature review and interviews to gather the data. We interview more than some persons in Indonesia banking industry to get the insight on the implementation of AI and BDA in Indonesia. The paper reveals best practices of the global banking and Indonesian banking, in the implementation of AI & BDA. The contributions of this study are proposed enterprise architecture and recommended digital innovation in AI and BDA that enables banking institutions to leverage customer experiences.
{"title":"Digital Banking Transformation: Application of Artificial Intelligence and Big Data Analytics for Leveraging Customer Experience in the Indonesia Banking Sector","authors":"Elisa Indriasari, F. Gaol, T. Matsuo","doi":"10.1109/IIAI-AAI.2019.00175","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00175","url":null,"abstract":"Discussions related to the Digital Banking (DB) transformation has become the main issues in the industry nowadays. Digital disruption has changed the way peoples do business and perform transactions. However, the bankers still found many problems when performing DB transformation. Main issues on DB transformation are that many banks still assume that digital transformation is about workflows and systems rather than focus on customer experience. Nowadays, Artificial Intelligence (AI) and Big Data Analytics (BDA) have risen and played as an important role in the new banking era. The recent trend of AI and BDA enable banking to be more customer-centric based on data driven. Personalization service becoming an important strategy for leveraging the existing customer engagement, and attracting potential customer become new customers. This study explores the application of AI and BDA in banking for leveraging customer experience. This study used literature review and interviews to gather the data. We interview more than some persons in Indonesia banking industry to get the insight on the implementation of AI and BDA in Indonesia. The paper reveals best practices of the global banking and Indonesian banking, in the implementation of AI & BDA. The contributions of this study are proposed enterprise architecture and recommended digital innovation in AI and BDA that enables banking institutions to leverage customer experiences.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130108868","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 : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00035
Ryosuke Suzuki, Tadachika Ozono, T. Shintani
The diffusion of the Augmented Reality framework has facilitated the implementation of a support system for a real world task. This paper introduces a system that supports the Mahjong game for beginners. However, it is difficult to calculate the score for beginners in the real Mahjong game. We develop an offline system to get the score by recognizing the Mahjong tiles. This is a difficult task because Mahjong tiles have classes and attributes that are the context of their positions. The system needs context-aware image recognition. The system detected tiles using OpenCV and Convolutional Neural Network to classify them and self-localization indirectly found in attributes. The experimental results show that the system can be used effectively.
{"title":"An Offline Mahjong Support System Based on Augmented Reality with Context-aware Image Recognition","authors":"Ryosuke Suzuki, Tadachika Ozono, T. Shintani","doi":"10.1109/IIAI-AAI.2019.00035","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00035","url":null,"abstract":"The diffusion of the Augmented Reality framework has facilitated the implementation of a support system for a real world task. This paper introduces a system that supports the Mahjong game for beginners. However, it is difficult to calculate the score for beginners in the real Mahjong game. We develop an offline system to get the score by recognizing the Mahjong tiles. This is a difficult task because Mahjong tiles have classes and attributes that are the context of their positions. The system needs context-aware image recognition. The system detected tiles using OpenCV and Convolutional Neural Network to classify them and self-localization indirectly found in attributes. The experimental results show that the system can be used effectively.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127284710","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 : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00127
Johannes Lindén, Xutao Wang, Stefan Forsström, Tingting Zhang
Multi linguistic problems such as auto-categorization is not an easy task. It is possible to train different models for each language, another way to do auto-categorization is to build the model in one base language and use automatic translation from other languages to that base language. Different languages have a bias to a language specific grammar and syntax and will therefore pose problems to be expressed in other languages. Translating from one language into a non-verbal language could potentially have a positive impact of the categorization results. A non-verbal language could for example be pure information in form of a knowledge graph relation extraction from the text. In this article a comparison is conducted between Chinese and Swedish languages. Two categorization models are developed and validated on each dataset. The purpose is to make an auto-categorization model that works for n'importe quel langage. One model is built upon LSTM and optimized for Swedish and the other is an improved Bidirectional-LSTM Convolution model optimized for Chinese. The improved algorithm is trained on both languages and compared with the LSTM algorithm. The Bidirectional-LSTM algorithm performs approximately 20% units better than the LSTM algorithm, which is significant.
{"title":"Bilingual Auto-Categorization Comparison of Two LSTM Text Classifiers","authors":"Johannes Lindén, Xutao Wang, Stefan Forsström, Tingting Zhang","doi":"10.1109/IIAI-AAI.2019.00127","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00127","url":null,"abstract":"Multi linguistic problems such as auto-categorization is not an easy task. It is possible to train different models for each language, another way to do auto-categorization is to build the model in one base language and use automatic translation from other languages to that base language. Different languages have a bias to a language specific grammar and syntax and will therefore pose problems to be expressed in other languages. Translating from one language into a non-verbal language could potentially have a positive impact of the categorization results. A non-verbal language could for example be pure information in form of a knowledge graph relation extraction from the text. In this article a comparison is conducted between Chinese and Swedish languages. Two categorization models are developed and validated on each dataset. The purpose is to make an auto-categorization model that works for n'importe quel langage. One model is built upon LSTM and optimized for Swedish and the other is an improved Bidirectional-LSTM Convolution model optimized for Chinese. The improved algorithm is trained on both languages and compared with the LSTM algorithm. The Bidirectional-LSTM algorithm performs approximately 20% units better than the LSTM algorithm, which is significant.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127689979","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 : 2019-07-01DOI: 10.1109/IIAI-AAI.2019.00231
Wei-Jen Lin, Mu-Chun Su, Wei-Yin Cheng, Wen-Yu Cheng
For the visually impaired, "independent living" is the key to rebuild the dignity and self-confidence. In addition to mobility skill, visually impaired memorize where the furniture is in homes. Therefore, moving the furniture or items (e.g. keys, remote control, etc.) around could be confusing and possibly unsafe. This article describes a system that combines deep learning with a camera for visually impaired to identify objects in the space whether it has been moved, such as furniture, important daily necessities, etc. The smart phone app is used to inform the visually impaired about the current location and movement location of all objects. We hope to re-establish a safe, convenient and comfortable indoor environment for the visually impaired through our system.
{"title":"An Assist System for Visually Impaired at Indoor Residential Environment using Faster-RCNN","authors":"Wei-Jen Lin, Mu-Chun Su, Wei-Yin Cheng, Wen-Yu Cheng","doi":"10.1109/IIAI-AAI.2019.00231","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2019.00231","url":null,"abstract":"For the visually impaired, \"independent living\" is the key to rebuild the dignity and self-confidence. In addition to mobility skill, visually impaired memorize where the furniture is in homes. Therefore, moving the furniture or items (e.g. keys, remote control, etc.) around could be confusing and possibly unsafe. This article describes a system that combines deep learning with a camera for visually impaired to identify objects in the space whether it has been moved, such as furniture, important daily necessities, etc. The smart phone app is used to inform the visually impaired about the current location and movement location of all objects. We hope to re-establish a safe, convenient and comfortable indoor environment for the visually impaired through our system.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121836634","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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