• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.312-320
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• 2023

Recently, there has been an increasing attempt to replace defect detection inspections in the manufacturing industry using deep learning techniques. However, obtaining substantial high-quality labeled data to enhance the performance of deep learning models entails economic and temporal constraints. As a solution for this problem, semi-supervised learning, using a limited amount of labeled data, has been gaining traction. This study assesses the effectiveness of semi-supervised learning in the defect detection process of manufacturing using the MixMatch algorithm. The MixMatch algorithm incorporates three dominant paradigms in the semi-supervised field: Consistency regularization, Entropy minimization, and Generic regularization. The performance of semi-supervised learning based on the MixMatch algorithm was compared with that of supervised learning using defect image data from the metal casting process. For the experiments, the ratio of labeled data was adjusted to 5%, 10%, 25%, and 50% of the total data. At a labeled data ratio of 5%, semi-supervised learning achieved a classification accuracy of 90.19%, outperforming supervised learning by approximately 22%p. At a 10% ratio, it surpassed supervised learning by around 8%p, achieving a 92.89% accuracy. These results demonstrate that semi-supervised learning can achieve significant outcomes even with a very limited amount of labeled data, suggesting its invaluable application in real-world research and industrial settings where labeled data is limited.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.115-136
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• 2014

The game industry has grown steadily and the online game has become one of the most attractive game segments for its remarkable growth. Customer management in the online game industry, however, has received little attention from the academic field. The purpose of this study is to analyze the drivers of customer defection in the online game setting and suggest not only theoretical but also managerial insights into increasing customer retention rates. Prior to empirical analysis, the authors hypothesized that 3 variables of interests (Learning, Playing, Achievement) would explain the customer defection according to preceeding researches. To demonstrate these hypotheses, the authors obtained data from one of the biggest game publishers in Korea, and the empirical analysis model was developed considering context of research settings. The results of analyses provide the following insights. First, the key behavioral variables of Learning, Playing, and Achievement play substantial roles in explaining the customer defection. Next, the effects of these variables vary between customer types: novice and experienced customers. The defection decisions by novice customers are predicted by all key behavioral variables and Playing serves as the most influential indicator of the defection decisions. However, experienced customers are influenced by Playing and Achievement, while Learning has no impact on the defection decisions. Finally, the authors investigated hypothetical customer retention strategies, using the empirical results. The market outcomes indicate that the customer retention strategies work well with novice customers and it is hard-to-impossible to prevent experienced customers from defection using their behavioral data. These findings together deliver several meaningful insights to management as follow. First, the management should support customers to get involved in Learning activities at the very first stage. Second, customer's Achievement and appropriate compensation for it would work as defection barriers. Last, to optimize the outcomes of firm's marketing investments, it is better to focus on retention of novice users not experienced ones.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.196-202
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• 2020

This study explores conceptions of learning management and examines the effects on study approach and critical thinking. Undergraduates majoring or minoring in management were gathered through convenient sampling and participated in the online survey. A total of 88 responses were analyzed. The results reveal that there is no significant gender or grade difference on conceptions of learning management. Conceptions of "test" and "seeing in a new way" are associated with deep study approach, whereas conceptions of 'test' is associated with surface study approach. Conceptions of "seeing in a new way" has a significant effect on critical thinking. The findings may inform redesign of instruction or curriculum especially focusing on improving high-quality thinking skills as the learning outcomes.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.289-297
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• 2020

The purpose of this study is to examine the college life adaptation that is affected by major satisfaction, learning commitment, and time management behavior of the college of Health students. The data were collected from 482 College of Health students at U city and analyzed using descriptive statistics, t-test, ANOVA, Scheffe test, Pearson's correlation analysis, and multiple regression. As a result of this study, major satisfaction, learning commitment, and time management behavior of College of Health students showed a positive relation with college life adaptation, and those factors affected college life adaptation. Therefore, it is necessary to make and apply the programs to enhance the college life adaptation for the college of Health students, and the supports such as environmental improvement and teaching methods are required to increase the learning commitment.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.1
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• pp.35-43
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• 2020

Turbidity has various effects on the water quality and ecosystem of a river. High turbidity during floods increases the operation cost of a drinking water supply system. Thus, the management of turbidity is essential for providing safe water to the public. There have been various efforts to estimate turbidity in river systems for proper management and early warning of high turbidity in the water supply process. Advanced data analysis technology using machine learning has been increasingly used in water quality management processes. Artificial neural networks(ANNs) is one of the first algorithms applied, where the overfitting of a model to observed data and vanishing gradient in the backpropagation process limit the wide application of ANNs in practice. In recent years, deep learning, which overcomes the limitations of ANNs, has been applied in water quality management. LSTM(Long-Short Term Memory) is one of novel deep learning algorithms that is widely used in the analysis of time series data. In this study, LSTM is used for the prediction of high turbidity(>30 NTU) in a river from the relationship of turbidity to discharge, which enables early warning of high turbidity in a drinking water supply system. The model showed 0.98, 0.99, 0.98 and 0.99 for precision, recall, F1-score and accuracy respectively, for the prediction of high turbidity in a river with 2 hour frequency data. The sensitivity of the model to the observation intervals of data is also compared with time periods of 2 hour, 8 hour, 1 day and 2 days. The model shows higher precision with shorter observation intervals, which underscores the importance of collecting high frequency data for better management of water resources in the future.

• Journal of Digital Convergence
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• v.6 no.2
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• pp.135-143
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• 2008

The remarkable growth of the Internet since mid-l990s has expanded the e-learning market and brought the transformation of educational environments and methodology. It can be said that the e-learning has changed the educational paradigm. Korean government is firmly determined to support the diffusion of e-learning because of the benefits of e-learning. People seem to accept the e-learning when its contents have high quality. A lot of research have been conducted on e-learning, however, it was mostly about user's usage intention, satisfaction and educational effect. It can't seem that sufficient research efforts have been put into figuring out the role of e-learning contents quality in the expansion of e-learning. In this paper, we present the empirical study on the influence of e-learning contents quality on user's satisfaction and educational effect. We conducted an questionnaire survey on college students to collect data and found that the quality of e-learning contents has significant influence on the users' satisfaction.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.640-650
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• 2016

This study was conducted in order to develop an education program based on simulation with problem-based learning, to apply it to nursing students, and to examine its effects on the students' learning motivation, learning strategy, and academic achievement. The subjects of this study were 69 seniors majoring in nursing. Education based on simulation with problem-based learning was applied to the students from September to October in 2015, and then a questionnaire survey was conducted on their learning motivation, learning strategy, and academic achievement. According to the results of this study, the education based on simulation with problem-based learning reduced the nursing students' other-directed motivation (external motivation), increased their self-regulation motivation (identified motivation, intrinsic motivation), and improved their use of resource management strategies. In addition, academic achievement (academic performance, and educational satisfaction) was in a positive correlation with identified motivation and learning strategies (cognitive strategy, meta cognitive strategy, and resource management strategy). In conclusion, education based on simulation with problem-based learning was found to be an effective education strategy for enhancing nursing students' autonomous motivation and improving their use of resource management strategies. Thus, it is necessary to promote the application of simulation with problem-based learning in various care situations and to study factors and parameters influencing learning related variables.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.559-570
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• 2005

This paper presents how to establish an efficient e-Learning environment using open source software. A LMS with additional functionalities on the top of dotLRN. which is a open source project for LMS, is presented. Additional functionalities include modification of the language for Korean, adoption of SCORM educational standard, and management of learning outcome. This system had been serviced for Kongju cyber university for one year on stable basis. The scope of this paper covers introduction, characteristics review, and the learner's learning outcome analysis.

• The Journal of Korean Association of Computer Education
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• v.6 no.3
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• pp.99-108
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• 2003

This paper indicates limitations of the existing VOD(Video on Demand)-based on-line education systems and presents the design and implementation of Education on Demand (EOD) system as an alternative. EOD system is based on meta information expressed in XML and component technology. Overall system consists of authoring tool. contents server, learning policy system and contents viewer. which are utilized throughout the learning contents life-cycle. EOD system enables automated contents management using meta information exchange methodology that is conformant to the SCORM meta data presentation scheme. In addition, integrated management of interaction and feedback information along with the learning policy system provides customized learning guide for each individual learner. With the development of EOD system, this paper discusses about advanced on-line education system which surpasses existing content-providing-only systems.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.61-70
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• 2003

Currently many companies and cyber-universities are investing large amount of time and efforts to develop a standard for Web-based learning contents. Among various standards proposed, SCORM(Sharable Content Object Reference Model) has been especially interested regarding web contents and LCMS(Learning Content Management System), In contrast with corporate and adult education, many seem to be skeptical that SCORM could be applied to K-12 education. In the study, opportunities and limitations of the concept for the learning object in 'SCORM' are examined through analyzing relevant studies and cases. In addition, this study examines the learning object in the pedagogical Perspective, and derives suggestions for applying them to K-12 education.