On-line selling website is currently famous and popular. There are several websites selling products and/or services including on-line book-selling websites. At present, the current book-selling websites usually apply recommender systems to recommend a book or a set of books to customers. However, the recommender systems mostly focus on recommending books that users usually view or buy together and also on books having high review rates. This may cause failure to recommend books that cover most required contents, for example, books related to a course description of a course students have registered. To address on this issue, we here introduce an alternative recommender system called Supplementary Books Suggestion system (SBS system) to create a list of supplementary books related/relevance to a course description of a course in computer science domain by regarding relevance between a book and a course description. This can help students easily find supplementary books to read and also may help to encourage the students doing self-learning. Experiments on real course descriptions were conducted to investigate the effectiveness of the SBS system in the terms of precision, recall, F-measure and average (also total) coverage/uncoverage of contents between a list of supplementary books and a course description.
{"title":"Supplementary Book Suggestion for Computer Science Courses","authors":"Benchamawan Chaisoongnoen, Komate Amphawan, Aekapop Bunpeng","doi":"10.1109/ICAICTA.2018.8541347","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541347","url":null,"abstract":"On-line selling website is currently famous and popular. There are several websites selling products and/or services including on-line book-selling websites. At present, the current book-selling websites usually apply recommender systems to recommend a book or a set of books to customers. However, the recommender systems mostly focus on recommending books that users usually view or buy together and also on books having high review rates. This may cause failure to recommend books that cover most required contents, for example, books related to a course description of a course students have registered. To address on this issue, we here introduce an alternative recommender system called Supplementary Books Suggestion system (SBS system) to create a list of supplementary books related/relevance to a course description of a course in computer science domain by regarding relevance between a book and a course description. This can help students easily find supplementary books to read and also may help to encourage the students doing self-learning. Experiments on real course descriptions were conducted to investigate the effectiveness of the SBS system in the terms of precision, recall, F-measure and average (also total) coverage/uncoverage of contents between a list of supplementary books and a course description.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114707509","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 : 2018-08-01DOI: 10.1109/ICAICTA.2018.8541318
Kyoji Umemura, Yuto Kohara, Nudtawon Yusuk, Ayaka Takamoto, Mitsuo Yoshida
There are two counting methods of "aa" in "aaa". The first method is overlapping count and this method count two "aa" in "aaa". The overlapping count uses the middle "a" twice. The other method is non-overlapping count which can count only one "aa" in "aaa". Non-overlapping counting uses each character once; therefore, there is only one "aa" in "aaa". In this paper, we provide the formulas to compute non-overlapping count of a string from the overlapping count of the related strings. Because a suffix array is known to be an efficient data structure, to obtain overlapping count of any string we can use suffix array to obtain the non-overlapping count of the given string by the formula which is presented in this paper.
{"title":"Non-overlapping Counting of String Using Suffix Array","authors":"Kyoji Umemura, Yuto Kohara, Nudtawon Yusuk, Ayaka Takamoto, Mitsuo Yoshida","doi":"10.1109/ICAICTA.2018.8541318","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541318","url":null,"abstract":"There are two counting methods of \"aa\" in \"aaa\". The first method is overlapping count and this method count two \"aa\" in \"aaa\". The overlapping count uses the middle \"a\" twice. The other method is non-overlapping count which can count only one \"aa\" in \"aaa\". Non-overlapping counting uses each character once; therefore, there is only one \"aa\" in \"aaa\". In this paper, we provide the formulas to compute non-overlapping count of a string from the overlapping count of the related strings. Because a suffix array is known to be an efficient data structure, to obtain overlapping count of any string we can use suffix array to obtain the non-overlapping count of the given string by the formula which is presented in this paper.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121335028","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}
The flipped classroom has become famous as an effective educational method that flips the purpose of classroom study and homework. In this paper, we propose a video learning system for flipped classrooms, called Response Collector, which enables students to record their responses to preparation videos. Our system provides response visualization for teachers and students to understand what they have acquired and questioned. We performed a practical user study of our system in a flipped classroom setup. The results show that students preferred to use the proposed method as the inputting method, rather than naive methods. Moreover, sharing responses among students was helpful for resolving individual students' questions, and students were satisfied with the use of our system.
{"title":"Response Collector: A Video Learning System for Flipped Classrooms","authors":"Hayato Okumoto, Mitsuo Yoshida, Kyoji Umemura, Yuko Ichikawa","doi":"10.1109/ICAICTA.2018.8541338","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541338","url":null,"abstract":"The flipped classroom has become famous as an effective educational method that flips the purpose of classroom study and homework. In this paper, we propose a video learning system for flipped classrooms, called Response Collector, which enables students to record their responses to preparation videos. Our system provides response visualization for teachers and students to understand what they have acquired and questioned. We performed a practical user study of our system in a flipped classroom setup. The results show that students preferred to use the proposed method as the inputting method, rather than naive methods. Moreover, sharing responses among students was helpful for resolving individual students' questions, and students were satisfied with the use of our system.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130669487","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 : 2018-08-01DOI: 10.1109/ICAICTA.2018.8541274
Sasiporn Tongman, N. Wattanakitrungroj
The contents in website and social networks are rapidly generated. The opinions and reviews can be analyzed and classified into two classes, positive or negative opinions, by machine learning methods. However, the main issue is how to representing each text as a proper set of variables, a p-feature vector, so that the successful classifiers can be obtained by one of the supervised learning approaches with its suitable parameter setting. In this study, a two-feature vector representing positive and negative moods in each text was prepared by using lists of positive and negative words, and then combined with term frequency - inverse document frequency (TF-IDF) features. kNN and SVM classifiers were comparatively built by this set and also other baseline set to predict each test vector and measure their effectiveness. Data of text Reviews from Yelp, Amazon and IMDB, were experimented with 10-fold cross validation in parameter variation and feature set reduction using PCA. The best Accuracy results across these three datasets, ~0.81-0.87, were yielded by SVM classifiers with each size of the reduced feature sets that is very smaller than the original size.
{"title":"Classifying Positive or Negative Text Using Features Based on Opinion Words and Term Frequency - Inverse Document Frequency","authors":"Sasiporn Tongman, N. Wattanakitrungroj","doi":"10.1109/ICAICTA.2018.8541274","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541274","url":null,"abstract":"The contents in website and social networks are rapidly generated. The opinions and reviews can be analyzed and classified into two classes, positive or negative opinions, by machine learning methods. However, the main issue is how to representing each text as a proper set of variables, a p-feature vector, so that the successful classifiers can be obtained by one of the supervised learning approaches with its suitable parameter setting. In this study, a two-feature vector representing positive and negative moods in each text was prepared by using lists of positive and negative words, and then combined with term frequency - inverse document frequency (TF-IDF) features. kNN and SVM classifiers were comparatively built by this set and also other baseline set to predict each test vector and measure their effectiveness. Data of text Reviews from Yelp, Amazon and IMDB, were experimented with 10-fold cross validation in parameter variation and feature set reduction using PCA. The best Accuracy results across these three datasets, ~0.81-0.87, were yielded by SVM classifiers with each size of the reduced feature sets that is very smaller than the original size.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130395162","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 : 2018-08-01DOI: 10.1109/ICAICTA.2018.8541319
Anocha Yaemjaem, N. Sutthisangiam, Amnat Sompan, Nattakit Sa-ngiam, Pongsak Jindasee
This paper is the develop of a high-definition 3D mapping system for use in topographic surveys and management of water resources by using MMS technology (Mobile mapping System) as a tool survey information on the topography, such as canal width, water level, bank level, road height and water regulating building structure. This information is the important in analyzing water situation and finding solutions for water resources management. This research uses 4 part type of devices: GPS, IMU, camera and 3D laser scanner. All devices are designed to be mounted on vehicles. The results of the test run of land vehicles in the area frequently flooded are Chai Nat and Nakhon Sawan Thailand and provide high-definition 3D maps from system. The system can generate high-definition 3D maps, measuring 9 centimeters in horizontal accuracy and 20 centimeters in vertical accuracy.
{"title":"Development of High-Definition 3D Mapping System for Water Resources Management","authors":"Anocha Yaemjaem, N. Sutthisangiam, Amnat Sompan, Nattakit Sa-ngiam, Pongsak Jindasee","doi":"10.1109/ICAICTA.2018.8541319","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541319","url":null,"abstract":"This paper is the develop of a high-definition 3D mapping system for use in topographic surveys and management of water resources by using MMS technology (Mobile mapping System) as a tool survey information on the topography, such as canal width, water level, bank level, road height and water regulating building structure. This information is the important in analyzing water situation and finding solutions for water resources management. This research uses 4 part type of devices: GPS, IMU, camera and 3D laser scanner. All devices are designed to be mounted on vehicles. The results of the test run of land vehicles in the area frequently flooded are Chai Nat and Nakhon Sawan Thailand and provide high-definition 3D maps from system. The system can generate high-definition 3D maps, measuring 9 centimeters in horizontal accuracy and 20 centimeters in vertical accuracy.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122649229","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 : 2018-08-01DOI: 10.1109/ICAICTA.2018.8541284
Vosco Pereira, S. Tamura, S. Hayamizu, Hidekazu Fukai
Image processing techniques have been actively used for research on road condition inspection and achieving high detection accuracies. Many studies focus on the detection of cracks and potholes of the road. However, in some least developed countries, there are some distances of roads are still unpaved and it escaped the attention of the researchers. Inspired by penetration and success in applying deep learning technic to computer vision and to any other fields and by the existence of the various type of smartphone devices, we proposed a low - cost method for paved and unpaved road images classification using convolutional neural network (CNN). Our model is trained with 13.186 images and validate with 3.186 images which collected using smartphone device in various conditions of roads such as wet, muddy, dry, dusty and shady conditions and with different types of road surface such as ground, rocks and sands. The experiment using 500 new testing images showed that our model can achieve high Precision (98.0%), Recall (98.4%) and F1 -Score (98.2%) simultaneously.
{"title":"Classification of Paved and Unpaved Road Image Using Convolutional Neural Network for Road Condition Inspection System","authors":"Vosco Pereira, S. Tamura, S. Hayamizu, Hidekazu Fukai","doi":"10.1109/ICAICTA.2018.8541284","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541284","url":null,"abstract":"Image processing techniques have been actively used for research on road condition inspection and achieving high detection accuracies. Many studies focus on the detection of cracks and potholes of the road. However, in some least developed countries, there are some distances of roads are still unpaved and it escaped the attention of the researchers. Inspired by penetration and success in applying deep learning technic to computer vision and to any other fields and by the existence of the various type of smartphone devices, we proposed a low - cost method for paved and unpaved road images classification using convolutional neural network (CNN). Our model is trained with 13.186 images and validate with 3.186 images which collected using smartphone device in various conditions of roads such as wet, muddy, dry, dusty and shady conditions and with different types of road surface such as ground, rocks and sands. The experiment using 500 new testing images showed that our model can achieve high Precision (98.0%), Recall (98.4%) and F1 -Score (98.2%) simultaneously.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121582081","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 : 2018-08-01DOI: 10.1109/ICAICTA.2018.8541337
Steffi Indrayani, M. L. Khodra
In order to fulfill the needs of journalistic automation, we develop automatic news generator that accepts structured data and user query and generates Indonesian news article. This paper employs template-based natural language generation in generating Indonesian municipal elections. Based on evaluation using Indonesian news characteristics as the evaluation metric by 15 linguistic experts and 25 active news readers, the average score of the generated news was 3.292 out of 4.
{"title":"Data-Driven News Generation for Indonesian Municipal Election","authors":"Steffi Indrayani, M. L. Khodra","doi":"10.1109/ICAICTA.2018.8541337","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541337","url":null,"abstract":"In order to fulfill the needs of journalistic automation, we develop automatic news generator that accepts structured data and user query and generates Indonesian news article. This paper employs template-based natural language generation in generating Indonesian municipal elections. Based on evaluation using Indonesian news characteristics as the evaluation metric by 15 linguistic experts and 25 active news readers, the average score of the generated news was 3.292 out of 4.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127960610","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 : 2018-08-01DOI: 10.1109/ICAICTA.2018.8541320
Catherine Pricilla, D. Lestari, Dody Dharma
Chatbot-based conversational commerce which allows buyers to do online shopping by conversing with chatbot through messaging application has been growing in the e-commerce industry. However, based on studies conducted in this paper, findings show that interaction design of the existing conversational commerce are still lacking in various areas. Therefore, an interaction and interface design for chatbot-based conversational commerce are developed in this study using user-centered design. The outcome of this study is a prototype that fulfills the usability goal and the user experience goal defined for chatbot-based conversational commerce on mobile platform especially for Indonesian users. We conduct usability testing to evaluate the prototype. The results show that the prototype fulfills the defined usability goals and user experience goals as 100% users agree that the prototype is effective to use, efficient to use, easy to learn, enjoyable and helpful, although only 83.3% users agree that the prototype is safe to use.
{"title":"Designing Interaction for Chatbot-Based Conversational Commerce with User-Centered Design","authors":"Catherine Pricilla, D. Lestari, Dody Dharma","doi":"10.1109/ICAICTA.2018.8541320","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541320","url":null,"abstract":"Chatbot-based conversational commerce which allows buyers to do online shopping by conversing with chatbot through messaging application has been growing in the e-commerce industry. However, based on studies conducted in this paper, findings show that interaction design of the existing conversational commerce are still lacking in various areas. Therefore, an interaction and interface design for chatbot-based conversational commerce are developed in this study using user-centered design. The outcome of this study is a prototype that fulfills the usability goal and the user experience goal defined for chatbot-based conversational commerce on mobile platform especially for Indonesian users. We conduct usability testing to evaluate the prototype. The results show that the prototype fulfills the defined usability goals and user experience goals as 100% users agree that the prototype is effective to use, efficient to use, easy to learn, enjoyable and helpful, although only 83.3% users agree that the prototype is safe to use.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117349698","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 : 2018-08-01DOI: 10.1109/ICAICTA.2018.8541301
P. Bamrungthai, Prasatporn Wongkamchang
The development of an image fusion system is described in this paper. The system consists of thermal and visible (color) cameras. Image alignment between two camera views is performed by using homography. The homography was estimated from four pairs of corresponding points on a planar object in the captured images that was manually selected by the user. Then, the user-defined region of interest (ROI) is used to adjust scale and position of the two images. Finally, the image fusion algorithm is applied to create the fused image. By thresholding the thermal image at a specified intensity level, the pixel values in the color image will be replaced with a predefined color if the corresponding pixels in the thermal image exceed the threshold value. This technique can provide thermal information of possible targets to be fused with original color image. This makes the system suitable for situation awareness. The experimental results show that the system can operate in real-time with satisfactory results.
{"title":"Development of a Thermal/Visible Image Fusion System for Situation Awareness","authors":"P. Bamrungthai, Prasatporn Wongkamchang","doi":"10.1109/ICAICTA.2018.8541301","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541301","url":null,"abstract":"The development of an image fusion system is described in this paper. The system consists of thermal and visible (color) cameras. Image alignment between two camera views is performed by using homography. The homography was estimated from four pairs of corresponding points on a planar object in the captured images that was manually selected by the user. Then, the user-defined region of interest (ROI) is used to adjust scale and position of the two images. Finally, the image fusion algorithm is applied to create the fused image. By thresholding the thermal image at a specified intensity level, the pixel values in the color image will be replaced with a predefined color if the corresponding pixels in the thermal image exceed the threshold value. This technique can provide thermal information of possible targets to be fused with original color image. This makes the system suitable for situation awareness. The experimental results show that the system can operate in real-time with satisfactory results.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125913231","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 : 2018-08-01DOI: 10.1109/ICAICTA.2018.8541335
Supaporn Erjongmanee, Navatasn Kongsamutr
Air passenger estimation is essential since air-travel demand continuously grows. This work proposes to derive an air-passenger estimation model using three forms of gravity model and two machine learning approaches, regression and neural network. Data used in this work are Thailand’s domestic air-passengers and affecting factors on air-travel demand collected from publicly available sources. The results show that both regression and neural network with one hidden layer provide low error. Gross domestic product and number of tourists change in the same direction with air-passenger demand. The outcomes of this work give more understandings in employing machine learning to estimate air passengers in Thailand and can be developed for more complex forecast models in the future.
{"title":"Air Passenger Estimation Using Gravity Model and Learning Approaches: Case Study of Thailand","authors":"Supaporn Erjongmanee, Navatasn Kongsamutr","doi":"10.1109/ICAICTA.2018.8541335","DOIUrl":"https://doi.org/10.1109/ICAICTA.2018.8541335","url":null,"abstract":"Air passenger estimation is essential since air-travel demand continuously grows. This work proposes to derive an air-passenger estimation model using three forms of gravity model and two machine learning approaches, regression and neural network. Data used in this work are Thailand’s domestic air-passengers and affecting factors on air-travel demand collected from publicly available sources. The results show that both regression and neural network with one hidden layer provide low error. Gross domestic product and number of tourists change in the same direction with air-passenger demand. The outcomes of this work give more understandings in employing machine learning to estimate air passengers in Thailand and can be developed for more complex forecast models in the future.","PeriodicalId":184882,"journal":{"name":"2018 5th International Conference on Advanced Informatics: Concept Theory and Applications (ICAICTA)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124261971","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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