Pub Date : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.124
Kumiko Kanekawa, Tetsuya Nakatoh, Takahiko Suzuki, S. Hirokawa
Evaluation of researchers is a big issue in institutional research. We propose a method for quantitatively evaluating the stage of young, middle and senior researchers focusing on the role of the last author in co-authored papers. We trace the two time series of the number of published papers and the ratio of the last authored papers among them of each researcher. We conducted experiments on 84 researchers of ICT related graduate school of a university in Japan, and on 50 researchers who published papers in 15 highly evaluated international conferences and 5 international journals. We analyzed 3360 articles in the first case and 13138 articles in the second case. We test three different approaches: cross tables, portfolios and bar graphs.
{"title":"Who is the Last Author of Your Paper?","authors":"Kumiko Kanekawa, Tetsuya Nakatoh, Takahiko Suzuki, S. Hirokawa","doi":"10.1109/IIAI-AAI.2017.124","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.124","url":null,"abstract":"Evaluation of researchers is a big issue in institutional research. We propose a method for quantitatively evaluating the stage of young, middle and senior researchers focusing on the role of the last author in co-authored papers. We trace the two time series of the number of published papers and the ratio of the last authored papers among them of each researcher. We conducted experiments on 84 researchers of ICT related graduate school of a university in Japan, and on 50 researchers who published papers in 15 highly evaluated international conferences and 5 international journals. We analyzed 3360 articles in the first case and 13138 articles in the second case. We test three different approaches: cross tables, portfolios and bar graphs.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115630311","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 : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.88
T. Hasuike, T. Kashima, S. Matsumoto
This paper proposes a robust model of multiperiod agricultural supply chain to consider both maximizing the total profit and minimizing the environmental load with random and fuzzy parameters. Our proposed model is formulated as a fuzzy and stochastic, multiobjective and multiperiod programming problem, and hence, it is hard to solve the formulated problem directly without setting a specific random distribution and a specific membership function. Therefore, a distribution-free approach based on sample mean and variance derived from received data, which does not assume any specific random distributions and membership functions, is introduced to apply our proposed model to various uncertain conditions. In addition, deterministic equivalent transformations are also introduced to obtain the optimal solution efficiently using the scenario-based approach.
{"title":"Robust Agricultural Supply Chain Management with Various Random and Fuzzy Parameters","authors":"T. Hasuike, T. Kashima, S. Matsumoto","doi":"10.1109/IIAI-AAI.2017.88","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.88","url":null,"abstract":"This paper proposes a robust model of multiperiod agricultural supply chain to consider both maximizing the total profit and minimizing the environmental load with random and fuzzy parameters. Our proposed model is formulated as a fuzzy and stochastic, multiobjective and multiperiod programming problem, and hence, it is hard to solve the formulated problem directly without setting a specific random distribution and a specific membership function. Therefore, a distribution-free approach based on sample mean and variance derived from received data, which does not assume any specific random distributions and membership functions, is introduced to apply our proposed model to various uncertain conditions. In addition, deterministic equivalent transformations are also introduced to obtain the optimal solution efficiently using the scenario-based approach.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115943873","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 : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.215
Toru Sugihara, Soichiro Aihara, S. Hirokawa, Takashi Nara
What sort of care should a university take for student-athletes? To answer the question and to consider the future educational strategy are one of big issues for many universities. The authors created a questionnaire which consists of 77 questions with multiple choice form. We collected the responses from 100 student-athletes and 141 other students. The present paper analyzed the characteristic features of student-athletes. We considered 312 kinds of combination of question items and the response choices as words and the questionnaire record of a student as a document written in those words. Then we applied the text mining method SVM (support vector machine) and feature selection. As the result, we confirmed that we can distinguish student-athletes from other students with 90% accuracy based on 16 characteristic features such as (a) they spend much time on athlete club and not on study, (b) they want to work for economically rich life, (c) they think that it is advantageous to job hunting or graduate school if they have good grades and (d) they have less interests on international perspective in campus life.
{"title":"An Analysis of Characteristics of Student-Athletes from Questionnaire by SVM","authors":"Toru Sugihara, Soichiro Aihara, S. Hirokawa, Takashi Nara","doi":"10.1109/IIAI-AAI.2017.215","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.215","url":null,"abstract":"What sort of care should a university take for student-athletes? To answer the question and to consider the future educational strategy are one of big issues for many universities. The authors created a questionnaire which consists of 77 questions with multiple choice form. We collected the responses from 100 student-athletes and 141 other students. The present paper analyzed the characteristic features of student-athletes. We considered 312 kinds of combination of question items and the response choices as words and the questionnaire record of a student as a document written in those words. Then we applied the text mining method SVM (support vector machine) and feature selection. As the result, we confirmed that we can distinguish student-athletes from other students with 90% accuracy based on 16 characteristic features such as (a) they spend much time on athlete club and not on study, (b) they want to work for economically rich life, (c) they think that it is advantageous to job hunting or graduate school if they have good grades and (d) they have less interests on international perspective in campus life.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125227822","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 : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.44
Ming-Puu Chen, Jih-Wei Hsu
The purpose of this study was to explore whether employing a learning cycle model helps students science exploration within an AR-based environment. Two types of guiding strategies were implemented within the learning cycle, including the procedural guidance and the question guidance. A pilot test was conducted to examine the design of AR-based science exploration using a learning cycle framework and the effect of type of guidance on participants learning performance and attitudes. The results revealed that when learning from the augmented-reality environment, the question-guidance group achieved better knowledge application performance than the procedural-guidance group and learners of both groups showed positive attitudes toward the employed learning activity.
{"title":"Enhancing AR-based Science Exploration through Learning Cycle","authors":"Ming-Puu Chen, Jih-Wei Hsu","doi":"10.1109/IIAI-AAI.2017.44","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.44","url":null,"abstract":"The purpose of this study was to explore whether employing a learning cycle model helps students science exploration within an AR-based environment. Two types of guiding strategies were implemented within the learning cycle, including the procedural guidance and the question guidance. A pilot test was conducted to examine the design of AR-based science exploration using a learning cycle framework and the effect of type of guidance on participants learning performance and attitudes. The results revealed that when learning from the augmented-reality environment, the question-guidance group achieved better knowledge application performance than the procedural-guidance group and learners of both groups showed positive attitudes toward the employed learning activity.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132729375","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 : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.122
Jun Zeng, Yinghua Li, Feng Li, Junhao Wen, S. Hirokawa
POI recommendation aims to recommend places which users have not visited before. In this paper, we proposed a POI recommendation method using location similarity, which assumes that people may be interested in the places that are similar with the places that they have been to before. In order to calculate the similarity of locations, we proposed a novel method using time slots. Every two hours can be considered as a time slot. In other words, one day can be segmented into 12 time slots. For each location, the check-in times in each time slot can be collected. These check-in times can form a vector, which can be used to calculate the similarity of two locations. According to the similarity, the score of each unvisited locations can be calculated and sorted. Finally, the POI recommendation can be generated from the top-n unvisited locations. The experiment results show that the proposed method is effective.
{"title":"A Point-of-Interest Recommendation Method Using Location Similarity","authors":"Jun Zeng, Yinghua Li, Feng Li, Junhao Wen, S. Hirokawa","doi":"10.1109/IIAI-AAI.2017.122","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.122","url":null,"abstract":"POI recommendation aims to recommend places which users have not visited before. In this paper, we proposed a POI recommendation method using location similarity, which assumes that people may be interested in the places that are similar with the places that they have been to before. In order to calculate the similarity of locations, we proposed a novel method using time slots. Every two hours can be considered as a time slot. In other words, one day can be segmented into 12 time slots. For each location, the check-in times in each time slot can be collected. These check-in times can form a vector, which can be used to calculate the similarity of two locations. According to the similarity, the score of each unvisited locations can be calculated and sorted. Finally, the POI recommendation can be generated from the top-n unvisited locations. The experiment results show that the proposed method is effective.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130897689","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 : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.15
T. H. Chiang, Stephen J. H. Yang
The research focus on The motivation of Ubiquitous Mobile learning and gender, it took sport literacy as courses, a research use flipped classroom concept to develop a learning method suitable for basketball advanced student as well as learning by doing model to teach student about the sport literacy concept.332 University students from Central Taiwan participate in the experiment, the tablet was provided as tools during lesson before and after class, research period takes one semester, the research team observed in the classroom every week, we use empirical evidence from group discussion, questionnaire survey method to analyze the student behavior. The result shows the combination of cloud services and mobile carrier enhance student motivation during lesson, contribute to flipped educational teaching methodology, and enhance the interaction between peer and teacher.
{"title":"Investigating the Motivation between Ubiquitous Learning Strategy and Gender for Basketball Sport Literacy","authors":"T. H. Chiang, Stephen J. H. Yang","doi":"10.1109/IIAI-AAI.2017.15","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.15","url":null,"abstract":"The research focus on The motivation of Ubiquitous Mobile learning and gender, it took sport literacy as courses, a research use flipped classroom concept to develop a learning method suitable for basketball advanced student as well as learning by doing model to teach student about the sport literacy concept.332 University students from Central Taiwan participate in the experiment, the tablet was provided as tools during lesson before and after class, research period takes one semester, the research team observed in the classroom every week, we use empirical evidence from group discussion, questionnaire survey method to analyze the student behavior. The result shows the combination of cloud services and mobile carrier enhance student motivation during lesson, contribute to flipped educational teaching methodology, and enhance the interaction between peer and teacher.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130197953","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 : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.177
Tomoyuki Okuda, Kouyu Suzuki, N. Kohtake
This paper describes a method of predicting the rutting depth by introducing Adam and dropout into MLP of neural network and GRU of recurrent neural net that can handle time series data. We built a model to predict the current rutting depth from the past rutting 3 years ago. We compared RMSE with the multiple regression model (MLR), which is most frequently used as a regression problem for the time variation of rutting depth. As a result, RMSE decreased in the order of MLR, MLP, GRU. The difference between GRU and RMSE of MLR was about 10%.
{"title":"Proposal and Evaluation of Prediction of Pavement Rutting Depth by Recurrent Neural Network","authors":"Tomoyuki Okuda, Kouyu Suzuki, N. Kohtake","doi":"10.1109/IIAI-AAI.2017.177","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.177","url":null,"abstract":"This paper describes a method of predicting the rutting depth by introducing Adam and dropout into MLP of neural network and GRU of recurrent neural net that can handle time series data. We built a model to predict the current rutting depth from the past rutting 3 years ago. We compared RMSE with the multiple regression model (MLR), which is most frequently used as a regression problem for the time variation of rutting depth. As a result, RMSE decreased in the order of MLR, MLP, GRU. The difference between GRU and RMSE of MLR was about 10%.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129418544","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 : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.28
Cheng-Han Wu
In this paper, we consider that consumers have memory about their previous purchases, and thus consumers switching behavior is associated with the gap of consumer perception. In such an environment, we investigate the interaction of the periodically pricing strategies between a brand manufacturer and a generic manufacturer, who sell homogeneous consumable products in the market, in a two-period supply chain. We formulate consumers Markovian switching behavior by using utility functions to obtain market demand for each manufacturer. Subsequently, we derive the manufacturers equilibrium pricing decisions and profits. Then, we resort to the numerical analysis to explore the parametric effects on the equilibrium results in order to provide the managerial insights.
{"title":"Pricing Strategies and Decisions in a Bertrand Competition with Markov Process","authors":"Cheng-Han Wu","doi":"10.1109/IIAI-AAI.2017.28","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.28","url":null,"abstract":"In this paper, we consider that consumers have memory about their previous purchases, and thus consumers switching behavior is associated with the gap of consumer perception. In such an environment, we investigate the interaction of the periodically pricing strategies between a brand manufacturer and a generic manufacturer, who sell homogeneous consumable products in the market, in a two-period supply chain. We formulate consumers Markovian switching behavior by using utility functions to obtain market demand for each manufacturer. Subsequently, we derive the manufacturers equilibrium pricing decisions and profits. Then, we resort to the numerical analysis to explore the parametric effects on the equilibrium results in order to provide the managerial insights.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121125547","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 : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.181
Shao-Yu Wang, Owen H. T. Lu, Wen-Long Lee, T. H. Chiang, Wang-sheng Su, Ming-Chao Lin, Stephen J. H. Yang
Scientific exhibition in Taiwan has been held by National Taiwan Science Education Center for more than 55 years, more than 15,000 works has been accumulated. It also becomes a famous competition for K-12 students. In order to provide recommendation of research topic to the participating students, domain experts require the growth topic and related industry from the past works. However, with the long history of the scientific exhibition, the domain experts cannot interpret all of the works in the short term. Therefore, through the computer to explore and summarize a large number of works becomes an emerging technology. In this study, we applied text-mining technology, and designed an expert rules as a computer-enabled methodology to explore the correlation between scientific exhibition and industry in the earth science and physics category. In the result, you can observe the computer programming and real estate development industries were the most growing research topic in scientific exhibition.
{"title":"Examining the Trend of Taiwan Primary and High School Scientific Exhibition by Using Text Mining Technique","authors":"Shao-Yu Wang, Owen H. T. Lu, Wen-Long Lee, T. H. Chiang, Wang-sheng Su, Ming-Chao Lin, Stephen J. H. Yang","doi":"10.1109/IIAI-AAI.2017.181","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.181","url":null,"abstract":"Scientific exhibition in Taiwan has been held by National Taiwan Science Education Center for more than 55 years, more than 15,000 works has been accumulated. It also becomes a famous competition for K-12 students. In order to provide recommendation of research topic to the participating students, domain experts require the growth topic and related industry from the past works. However, with the long history of the scientific exhibition, the domain experts cannot interpret all of the works in the short term. Therefore, through the computer to explore and summarize a large number of works becomes an emerging technology. In this study, we applied text-mining technology, and designed an expert rules as a computer-enabled methodology to explore the correlation between scientific exhibition and industry in the earth science and physics category. In the result, you can observe the computer programming and real estate development industries were the most growing research topic in scientific exhibition.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115529187","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 : 2017-11-15DOI: 10.1109/IIAI-AAI.2017.136
C. Yen, Tzone-I Wang
To help programmer gaining sound concepts of a programming language and boost their problem solving ability, this study constructs a programming environment, which, based on the self-explanation strategy, gives proper feedbacks for the programmers of C++language. The embedded self-explanation strategy guides the environment which, when programmers gets compilation errors, gives extended examples for the programmers and ask them for self-explanations on the inference of the error after they study the examples. An algorithm developed in this study compares the self-explanation sentence from a programmer with base strings, established and organized into an ontology by programing experts, and finds possible errors on the explanation, which lead to his/her possible misconceptions. Based on the results, the environment manages to feedback proper learning material and extended examples for programmers to correct their possible misconceptions. This study builds an ontology of C++ concepts class hierarchy with class properties and instances being possible misconceptions and the learning material feedbacks. The possible misconceptions are collected from actual programming practices in several pilot experiments joined by programmers of college students. The final experiment involves 13 college students who use the system for actual programming. The environment records students programming activities, analyzes their self-explanations on errors, and gives proper feedbacks, which, after verified by programming experts, reaches an average accuracy of 84.7%. The distinctive feature of this study is the open question style self-explanation sentence requirement, a rare research of its kind. All the schemes and algorithms developed in this study can be used as a methodology for establishing system with self-explanation learning strategy in other fields.
{"title":"Using Self-Explanation and Ontology for Providing Proper Feedbacks in a Programming Environment","authors":"C. Yen, Tzone-I Wang","doi":"10.1109/IIAI-AAI.2017.136","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2017.136","url":null,"abstract":"To help programmer gaining sound concepts of a programming language and boost their problem solving ability, this study constructs a programming environment, which, based on the self-explanation strategy, gives proper feedbacks for the programmers of C++language. The embedded self-explanation strategy guides the environment which, when programmers gets compilation errors, gives extended examples for the programmers and ask them for self-explanations on the inference of the error after they study the examples. An algorithm developed in this study compares the self-explanation sentence from a programmer with base strings, established and organized into an ontology by programing experts, and finds possible errors on the explanation, which lead to his/her possible misconceptions. Based on the results, the environment manages to feedback proper learning material and extended examples for programmers to correct their possible misconceptions. This study builds an ontology of C++ concepts class hierarchy with class properties and instances being possible misconceptions and the learning material feedbacks. The possible misconceptions are collected from actual programming practices in several pilot experiments joined by programmers of college students. The final experiment involves 13 college students who use the system for actual programming. The environment records students programming activities, analyzes their self-explanations on errors, and gives proper feedbacks, which, after verified by programming experts, reaches an average accuracy of 84.7%. The distinctive feature of this study is the open question style self-explanation sentence requirement, a rare research of its kind. All the schemes and algorithms developed in this study can be used as a methodology for establishing system with self-explanation learning strategy in other fields.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115599401","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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