Pub Date : 2018-07-01DOI: 10.1109/iiai-aai.2018.00003
{"title":"[Copyright notice]","authors":"","doi":"10.1109/iiai-aai.2018.00003","DOIUrl":"https://doi.org/10.1109/iiai-aai.2018.00003","url":null,"abstract":"","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133771321","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 : 2018-07-01DOI: 10.1109/IIAI-AAI.2018.00206
Chih-Fong Tsai
Image feature representation by bag-of-visual words (BOVW) has been widely considered in the image classification related problems. The feature extraction step is usually based on tokenizing the detected keypoints as the visual words. As a result, the visual-word vector of an image represents how often the visual words occur in an image. To train and test an image classifier, the BOVW features of the training and testing images can be extracted by either at the same time or separately. Therefore, the aim of this paper is to examine the classification performance of using these two different feature extraction strategies. We show that there is no significant difference between these two strategies, but extracting the BOVW features from the training and testing images at the same time requires much longer time. Therefore, the key criterion of choosing the right strategy of BOVW feature extraction is based on the dataset size.
{"title":"Two Strategies for Bag-of-Visual Words Feature Extraction","authors":"Chih-Fong Tsai","doi":"10.1109/IIAI-AAI.2018.00206","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2018.00206","url":null,"abstract":"Image feature representation by bag-of-visual words (BOVW) has been widely considered in the image classification related problems. The feature extraction step is usually based on tokenizing the detected keypoints as the visual words. As a result, the visual-word vector of an image represents how often the visual words occur in an image. To train and test an image classifier, the BOVW features of the training and testing images can be extracted by either at the same time or separately. Therefore, the aim of this paper is to examine the classification performance of using these two different feature extraction strategies. We show that there is no significant difference between these two strategies, but extracting the BOVW features from the training and testing images at the same time requires much longer time. Therefore, the key criterion of choosing the right strategy of BOVW feature extraction is based on the dataset size.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133904491","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 : 2018-07-01DOI: 10.1109/IIAI-AAI.2018.00041
Chih-Hung Chang, Chih-Ming Chen, Rong-Hua Zhao
Many studies have confirmed that the collaborative problem-based learning (CPBL) mode is an increasingly popular educational paradigm that has highly potential to cultivate learners' collaborative learning and problem solving abilities. However, how to effectively promote positive group members' interaction and group accountability is a critical issue in the CPBL mode. This work thus presents a group incentive mechanism (GIM) based on considering several important factors affecting peers' interaction and group accountability in collaborative learning theories to promote the learning performance learners in a CPBL system. To evaluate the effectiveness of the proposed GIM, this work recruited 48 Grade 4 students from an elementary school to participate in the instruction experiment. The quasi-experimental design was adopted to assess the differences in learning performance, interaction relationship, group efficacy, and group cohesiveness between the experimental group learners using the proposed GIM and control group learners using the individual incentive mechanism (IIM) under using the CPBL system to collaboratively solve a target problem. Analytical results show that although the control group learners using the IIM had higher social network interaction than the experimental group learners using the proposed GIM, the experimental group learners presents better learning performance and group efficacy than the control group.
{"title":"An Effective Group Incentive Mechanism in a Collaborative Problem-Based Learning System for Enhancing Positive Peer Interaction and Learning Performance","authors":"Chih-Hung Chang, Chih-Ming Chen, Rong-Hua Zhao","doi":"10.1109/IIAI-AAI.2018.00041","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2018.00041","url":null,"abstract":"Many studies have confirmed that the collaborative problem-based learning (CPBL) mode is an increasingly popular educational paradigm that has highly potential to cultivate learners' collaborative learning and problem solving abilities. However, how to effectively promote positive group members' interaction and group accountability is a critical issue in the CPBL mode. This work thus presents a group incentive mechanism (GIM) based on considering several important factors affecting peers' interaction and group accountability in collaborative learning theories to promote the learning performance learners in a CPBL system. To evaluate the effectiveness of the proposed GIM, this work recruited 48 Grade 4 students from an elementary school to participate in the instruction experiment. The quasi-experimental design was adopted to assess the differences in learning performance, interaction relationship, group efficacy, and group cohesiveness between the experimental group learners using the proposed GIM and control group learners using the individual incentive mechanism (IIM) under using the CPBL system to collaboratively solve a target problem. Analytical results show that although the control group learners using the IIM had higher social network interaction than the experimental group learners using the proposed GIM, the experimental group learners presents better learning performance and group efficacy than the control group.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134369901","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 : 2018-07-01DOI: 10.1109/IIAI-AAI.2018.00120
Phasit Charoenkwan
Thailand has a huge number of Facebook user. Most company has their own public page to communicate with their customers. Thus, it's desirable to perform sentimental analysis on Facebook post messages to understand customer's reaction of specific promotion, event or news. This work aims to propose a novel method to perform sentimental analysis on Thai Facebook data by combining information generated from a classical Bag-Of-Words features and advance deep learning approaches called ThaiFBDeep. Remarkably, according to Thai people usually conduct new words every year, the proposed data preprocessing techniques should be able to handle this kind of words. The experiment results show that ThaiFBDeep achieved a 91.75% of train accuracy and an 83.36% of independent test accuracy which is better than other well-known methods i.e. Naïve Bayes, Support Vector Machine, Multi-Layers Perceptron, Long Short-Term Memory and Convolution Neural Networks. These results also show that the including of Bag-Of-Words features can improve efficiency of Deep Learning based approach for sentimental analysis.
{"title":"ThaiFBDeep: A Sentimental Analysis Using Deep Learning Combined with Bag-of-Words Features on Thai Facebook Data","authors":"Phasit Charoenkwan","doi":"10.1109/IIAI-AAI.2018.00120","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2018.00120","url":null,"abstract":"Thailand has a huge number of Facebook user. Most company has their own public page to communicate with their customers. Thus, it's desirable to perform sentimental analysis on Facebook post messages to understand customer's reaction of specific promotion, event or news. This work aims to propose a novel method to perform sentimental analysis on Thai Facebook data by combining information generated from a classical Bag-Of-Words features and advance deep learning approaches called ThaiFBDeep. Remarkably, according to Thai people usually conduct new words every year, the proposed data preprocessing techniques should be able to handle this kind of words. The experiment results show that ThaiFBDeep achieved a 91.75% of train accuracy and an 83.36% of independent test accuracy which is better than other well-known methods i.e. Naïve Bayes, Support Vector Machine, Multi-Layers Perceptron, Long Short-Term Memory and Convolution Neural Networks. These results also show that the including of Bag-Of-Words features can improve efficiency of Deep Learning based approach for sentimental analysis.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134521382","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}
Hokkaido University has launched the special graduate education program "Nitobe School" in 2015 to develop students' high-level transferable skills as well as to enhance their advanced specialty. The program adopts Student Emotional Intelligent Quotient (SEQ), which measures student's behavior traits based on emotional intelligent theory, as a supportive system of the assessment of educational quality. Students take the SEQ test at the time of enrollment, one year passed and completion of the program to aware the changes of behavior. This paper reports the preliminary result of SEQ score for the Japanese students in academic year 2015 as a first study. The results show the effect of a team-based learning style class in Nitobe School such as improvement of relationship to others. Furthermore, we focus on the similarly of the tendency of between the students who withdraw from the program and who complete.
{"title":"Measurement of Educational Effect Based on Behavioral Change in a Trans-Graduate Educational Program","authors":"Shotaro Imai, Michiyo Shimamura, Kazuhiko Terasawa","doi":"10.1109/IIAI-AAI.2018.00085","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2018.00085","url":null,"abstract":"Hokkaido University has launched the special graduate education program \"Nitobe School\" in 2015 to develop students' high-level transferable skills as well as to enhance their advanced specialty. The program adopts Student Emotional Intelligent Quotient (SEQ), which measures student's behavior traits based on emotional intelligent theory, as a supportive system of the assessment of educational quality. Students take the SEQ test at the time of enrollment, one year passed and completion of the program to aware the changes of behavior. This paper reports the preliminary result of SEQ score for the Japanese students in academic year 2015 as a first study. The results show the effect of a team-based learning style class in Nitobe School such as improvement of relationship to others. Furthermore, we focus on the similarly of the tendency of between the students who withdraw from the program and who complete.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"92 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125699141","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 : 2018-07-01DOI: 10.1109/IIAI-AAI.2018.00039
Chih-Ming Chen, Zong-Lin You
With web-based collaborative problem-based learning, learners could more conveniently cultivate their problem-solving capabilities through autonomous learning. Nevertheless, learners are often guided to solve a target problem by the messages announced by teachers during the collaborative problem-based learning (CPBL) processes. Individual learners often could not effectively absorb such standard messages, thus ignoring the important messages from teachers. This study thus employs the modularity Q function as the fitness function of genetic algorithm (GA) to optimally detect communities and uses PageRank measure to accurately find out community opinion leaders according to the social network interaction data of learners in the CPBL process. Based on quasi-experimental design, this study examines whether learners in the experimental group using the two-step flow of communication through opinion leaders to convey messages for solving a target CPBL mission could more significantly enhance web-based CPBL performance, social network interaction, and group cohesion than learners in the control group using the one-step flow of communication through teachers' messages. Analytical results show learners in the experimental group remarkably outperform those in the control group on learning performance and peer interaction under a CPBL environment. Learners in the experimental group present significantly higher group cohesion than those in the control group.
{"title":"Community Detection with Opinion Leaders' Identification for Promoting Collaborative Problem-Based Learning Performance","authors":"Chih-Ming Chen, Zong-Lin You","doi":"10.1109/IIAI-AAI.2018.00039","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2018.00039","url":null,"abstract":"With web-based collaborative problem-based learning, learners could more conveniently cultivate their problem-solving capabilities through autonomous learning. Nevertheless, learners are often guided to solve a target problem by the messages announced by teachers during the collaborative problem-based learning (CPBL) processes. Individual learners often could not effectively absorb such standard messages, thus ignoring the important messages from teachers. This study thus employs the modularity Q function as the fitness function of genetic algorithm (GA) to optimally detect communities and uses PageRank measure to accurately find out community opinion leaders according to the social network interaction data of learners in the CPBL process. Based on quasi-experimental design, this study examines whether learners in the experimental group using the two-step flow of communication through opinion leaders to convey messages for solving a target CPBL mission could more significantly enhance web-based CPBL performance, social network interaction, and group cohesion than learners in the control group using the one-step flow of communication through teachers' messages. Analytical results show learners in the experimental group remarkably outperform those in the control group on learning performance and peer interaction under a CPBL environment. Learners in the experimental group present significantly higher group cohesion than those in the control group.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124222263","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 : 2018-07-01DOI: 10.1109/IIAI-AAI.2018.00163
Tsui-Min Chen, Chiu-Chi Wei, Hui-Chung Che
With the powerful implementation of national intellectual property strategy, China became the country with the most patent applications around the world in previous five years. There are more than 3,200 A-share listed companies in China, the daily transaction volume exceeded RMB 1 trillion Yuan, ranking it as the second largest stock market in the world. Patents are the concrete manifestations of scientific and technological innovation achievements, this study intended to discover how patents impact stock prices on technology-based companies listed on China's Shanghai A-share market from 2011-2017. It was found that specific patent indicators significantly lead the stock prices more than one year; a patent leading equation for predicting stock price was proposed. It also showed that the specific stocks extracted by the proposed patent leading equation had better performance than that of Shanghai stock index.
{"title":"Contribution of Patent Indicators to China Stock Performance","authors":"Tsui-Min Chen, Chiu-Chi Wei, Hui-Chung Che","doi":"10.1109/IIAI-AAI.2018.00163","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2018.00163","url":null,"abstract":"With the powerful implementation of national intellectual property strategy, China became the country with the most patent applications around the world in previous five years. There are more than 3,200 A-share listed companies in China, the daily transaction volume exceeded RMB 1 trillion Yuan, ranking it as the second largest stock market in the world. Patents are the concrete manifestations of scientific and technological innovation achievements, this study intended to discover how patents impact stock prices on technology-based companies listed on China's Shanghai A-share market from 2011-2017. It was found that specific patent indicators significantly lead the stock prices more than one year; a patent leading equation for predicting stock price was proposed. It also showed that the specific stocks extracted by the proposed patent leading equation had better performance than that of Shanghai stock index.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131563598","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 : 2018-07-01DOI: 10.1109/IIAI-AAI.2018.00093
Tomohiko Sato, M. Mitachi, Tetsutaro Okada
Although active learning (AL) strategies have been introduced in multiple contexts, application of the strategies in large-enrollment class still leaves much room for improvement. The purpose of this study was to describe how to apply AL strategies in a large economics class at a university. A total of 297 students on economics course at Kagawa University in fiscal year 2017 were enrolled. Designation of the course consisted of multi-step instructive techniques such as instructor-oriented seating system, multiple times of group discussions, immediate feedback from the instructor, and selection of excellent worksheets and reaction papers. At a practice level, well-designed questions at different levels, and appropriate choice of these questions for group discussions could facilitate instructor-students interactions even in the large class. Students appeared anxious about AL style class at the beginning of the course, but they gradually got used to the style, possibly due to multiple times of group discussions and immediate and meaningful feedbacks from the instructor in class. Text analysis of reaction papers from students revealed that students were impressed by both AL style lessons and the course contents. This study highlights the importance of instructors' active teaching for AL of students in a large-enrollment class.
{"title":"Implementation of Active Learning Strategies in a Large-Enrollment Economics Class at a University","authors":"Tomohiko Sato, M. Mitachi, Tetsutaro Okada","doi":"10.1109/IIAI-AAI.2018.00093","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2018.00093","url":null,"abstract":"Although active learning (AL) strategies have been introduced in multiple contexts, application of the strategies in large-enrollment class still leaves much room for improvement. The purpose of this study was to describe how to apply AL strategies in a large economics class at a university. A total of 297 students on economics course at Kagawa University in fiscal year 2017 were enrolled. Designation of the course consisted of multi-step instructive techniques such as instructor-oriented seating system, multiple times of group discussions, immediate feedback from the instructor, and selection of excellent worksheets and reaction papers. At a practice level, well-designed questions at different levels, and appropriate choice of these questions for group discussions could facilitate instructor-students interactions even in the large class. Students appeared anxious about AL style class at the beginning of the course, but they gradually got used to the style, possibly due to multiple times of group discussions and immediate and meaningful feedbacks from the instructor in class. Text analysis of reaction papers from students revealed that students were impressed by both AL style lessons and the course contents. This study highlights the importance of instructors' active teaching for AL of students in a large-enrollment class.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133958203","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 : 2018-07-01DOI: 10.1109/IIAI-AAI.2018.00145
Kento Igarashi, Tetsuo Yamada, N. Itsubo, M. Inoue
Recently, to prevent environmental issues such as natural resource depletion and global warming, recycling for assembly products is expected to promote both material recovery from End-of-Life products and reduction of CO_2 volumes in new production. In order to realize economical recycling, recycling factories select to disassemble or dispose each part depending on the recycling rate and cost. Furthermore, it is necessary for disassembly lines to allocate all disassembly tasks to each disassembly work station in order to minimize the number of disassembly work stations. Igarashi et al. (2015) proposed a modeling and design of multi-objective optimization of disassembly systems for minimization of disassembly costs and maximization of recycling rate and maximization of CO_2 saving rate in the case of cleaners. However, different trends may appear in the disassembly system design when other types of assembly products are recycled. This study adopts the disassembly system design by multi-objective optimization for lower disassembly cost, higher recycling and CO_2 saving rates with the environmental and economic parts selection to the cell phone case. In addition, the influence on the disassembly system design by the difference of product type is discussed.
最近，为了防止自然资源枯竭和全球变暖等环境问题，组装产品的回收利用有望促进报废产品的材料回收和减少新产品的二氧化碳量。为了实现经济回收，回收工厂根据回收率和成本选择对每个部件进行拆解或处理。此外，为了使拆卸工位的数量最小化，拆卸线有必要将所有的拆卸任务分配到每个拆卸工位。Igarashi et al.(2015)以清洁器为例，提出了一种多目标优化拆卸系统的建模和设计，以实现拆卸成本最小化、回收率最大化和CO_2节约率最大化。然而，当其他类型的装配产品被回收时，拆卸系统设计可能会出现不同的趋势。本研究采用多目标优化的拆卸系统设计，以降低拆卸成本，提高回收利用率和节省二氧化碳，并选择环保经济的零部件。此外，还讨论了产品类型的不同对拆卸系统设计的影响。
{"title":"Comparison between Different Products by Disassembly System Design with Parts Selection for Cost, Recycling and CO2 Saving Rates Using Multi-objective Optimization","authors":"Kento Igarashi, Tetsuo Yamada, N. Itsubo, M. Inoue","doi":"10.1109/IIAI-AAI.2018.00145","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2018.00145","url":null,"abstract":"Recently, to prevent environmental issues such as natural resource depletion and global warming, recycling for assembly products is expected to promote both material recovery from End-of-Life products and reduction of CO_2 volumes in new production. In order to realize economical recycling, recycling factories select to disassemble or dispose each part depending on the recycling rate and cost. Furthermore, it is necessary for disassembly lines to allocate all disassembly tasks to each disassembly work station in order to minimize the number of disassembly work stations. Igarashi et al. (2015) proposed a modeling and design of multi-objective optimization of disassembly systems for minimization of disassembly costs and maximization of recycling rate and maximization of CO_2 saving rate in the case of cleaners. However, different trends may appear in the disassembly system design when other types of assembly products are recycled. This study adopts the disassembly system design by multi-objective optimization for lower disassembly cost, higher recycling and CO_2 saving rates with the environmental and economic parts selection to the cell phone case. In addition, the influence on the disassembly system design by the difference of product type is discussed.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134635118","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 : 2018-07-01DOI: 10.1109/IIAI-AAI.2018.00098
Yuko Ikkatai, Eiri Ono
Academic crowdfunding, one of the concepts of open science, is a funding system in which a research candidate proposes a project online and asks for financial support from other citizens. Recently, researchers of universities and research institutions have begun using academic crowdfunding in addition to public research funding. However, there are few researches on academic crowdfunding in Japan. This study examined the characteristics of funded projects on four Japanese platforms that facilitate academic crowdfunding (Readyfor, CAMPFIRE, academist, and OTSUCLE). The results showed a significant correlation between the number of backers and amount raised, but not between the number of backers and achievement rate. The number of projects was large in biology, art and design, and physics. Such information will be useful not only for future research candidates but also for universities and research institutions to design their financial supports for researchers.
{"title":"Exploring Characteristics of Academic Crowdfunding in Japan","authors":"Yuko Ikkatai, Eiri Ono","doi":"10.1109/IIAI-AAI.2018.00098","DOIUrl":"https://doi.org/10.1109/IIAI-AAI.2018.00098","url":null,"abstract":"Academic crowdfunding, one of the concepts of open science, is a funding system in which a research candidate proposes a project online and asks for financial support from other citizens. Recently, researchers of universities and research institutions have begun using academic crowdfunding in addition to public research funding. However, there are few researches on academic crowdfunding in Japan. This study examined the characteristics of funded projects on four Japanese platforms that facilitate academic crowdfunding (Readyfor, CAMPFIRE, academist, and OTSUCLE). The results showed a significant correlation between the number of backers and amount raised, but not between the number of backers and achievement rate. The number of projects was large in biology, art and design, and physics. Such information will be useful not only for future research candidates but also for universities and research institutions to design their financial supports for researchers.","PeriodicalId":309975,"journal":{"name":"2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133880799","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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