• Journal of Digital Contents Society
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• v.15 no.1
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• pp.101-112
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• 2014

Existing tools using in the standard e-learning contents authoring were used a method to provide users contents template produced in advance. In order to use resources of the template in a common web-based authoring tool, there is problem to overcome. If the resource of template is inserted within the contents on the authoring tool, the deformation of the template by the user's input that may occur during the edit process cannot be controlled. In this paper, we propose an effective maintenance method to prevent deformation of the resource of template inserted into any WYSIWYG-based HTML authoring tool by user's discretion. We added a template plug-in that can create the IMS-QTI standard resource in tynyMCE the web-based open source editor of representative examples. And the plug-in for tinyMCE was realized as a module of directly respond to the action of limited user input. So, in response to the action of user's input, the structure of the template can be sustained possibly.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.65-76
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• 2022

Recently, not only traditional statistical techniques but also machine learning algorithms have been used to make more accurate bankruptcy predictions. But the insolvency rate of companies dealing with financial institutions is very low, resulting in a data imbalance problem. In particular, since data imbalance negatively affects the performance of artificial intelligence models, it is necessary to first perform the data imbalance process. In additional, as artificial intelligence algorithms are advanced for precise decision-making, regulatory pressure related to securing transparency of Artificial Intelligence models is gradually increasing, such as mandating the installation of explanation functions for Artificial Intelligence models. Therefore, this study aims to present guidelines for eXplainable Artificial Intelligence-based corporate bankruptcy prediction methodology applying SMOTE techniques and LIME algorithms to solve a data imbalance problem and model transparency problem in predicting corporate bankruptcy. The implications of this study are as follows. First, it was confirmed that SMOTE can effectively solve the data imbalance issue, a problem that can be easily overlooked in predicting corporate bankruptcy. Second, through the LIME algorithm, the basis for predicting bankruptcy of the machine learning model was visualized, and derive improvement priorities of financial variables that increase the possibility of bankruptcy of companies. Third, the scope of application of the algorithm in future research was expanded by confirming the possibility of using SMOTE and LIME through case application.

• Journal of Korean Society for Quality Management
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• v.51 no.1
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• pp.55-65
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• 2023

Purpose: The purpose of this study is to propose an optimization process to improve product yield in the process using process data. Recently, research for low-cost and high-efficiency production in the manufacturing process using machine learning or deep learning has continued. Therefore, this study derives major variables that affect product defects in the manufacturing process using eXplainable Artificial Intelligence(XAI) method. After that, the optimal range of the variables is presented to propose a methodology for improving product yield. Methods: This study is conducted using the injection molding machine AI dataset released on the Korea AI Manufacturing Platform(KAMP) organized by KAIST. Using the XAI-based SHAP method, major variables affecting product defects are extracted from each process data. XGBoost and LightGBM were used as learning algorithms, 5-6 variables are extracted as the main process variables for the injection process. Subsequently, the optimal control range of each process variable is presented using the ICE method. Finally, the product yield improvement methodology of this study is proposed through a validation process using Test Data. Results: The results of this study are as follows. In the injection process data, it was confirmed that XGBoost had an improvement defect rate of 0.21% and LightGBM had an improvement defect rate of 0.29%, which were improved by 0.79%p and 0.71%p, respectively, compared to the existing defect rate of 1.00%. Conclusion: This study is a case study. A research methodology was proposed in the injection process, and it was confirmed that the product yield was improved through verification.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.85-94
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• 2009

It is becoming increasingly difficult for learners to find the lectures they are looking for. In turn, the ability to find the particular lecture sought by the learner in an accurate and prompt manner has become an important issue in e-Learning. To deal this issue, in this paper. we present a collaborative approach to provide personalized recommendations of online video lectures. The proposed approach first identifies candidated video lectures that will be of interest to a certain user. Partitioned collaborative filtering is employed as an approach in order to generate neighbor learners and predict learners'preferences for the lectures. Thereafter, Attribute-based filtering is employed to recommend a final list of video lectures that the target user will like the most.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.329-332
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.280-283
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.238-244
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• 2020

The development and distribution rate of smartphones have progressed so rapidly that it is safe for the entire nation to use them in the smart age, and the use of smartphones has become an essential medium for the use of domestic media content, and many people are using various contents regardless of gender, age, or region. Recently, various media outlets have been consuming video content for online learning, indicating that learners utilize video content online for learning. In the previous research, satisfaction studies were conducted according to the type of content, and the improvement plan was necessary because no research was conducted on how to evaluate the learning content itself and provide it to learners. In this paper, we would like to propose a system through evaluation and review of learning content itself as a way to improve the way of providing video content for learning and quality learning content.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.517-525
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• 2015

The purpose of this research was to perform a comparison of face-to-face and blended learning of TOEIC to see if there is a difference in their learning effectiveness. The research compared the improvement rate of the students' academic achievement, their self-evaluation results, and their participation rate and results of the online assignment by using t-test, pearson correlation analysis, and regression analysis. The research results demonstrated that the blended learning is pedagogically more effective than the face-to-face although the difference is not large. It was analyzed that the results were largely thanks to the following facts: In the blended learning, the students could interact with their instructors face-to-face in the off-line class, they got the weekly text message to encourage them to participate in the online class, and their routine online class attendance could cause their more positive participation in the online assignment.

• Korea Journal of Hospital Management
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• v.14 no.4
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• pp.1-24
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• 2009

The purpose of this study was to find out the differences and relationships among balanced strategy, coordinating and learning mechanism, and perceived performance of hospitals in Korea, and provide some directions to establish effective strategic management of hospital. Measure items on balanced strategy, coordinating and learning mechanism, and perceived performance were developed from previous studies. Questionnaire was sent and received through Internet site and e-mail during May, 2008. Data were collected from key informant in each institutions, and analyzed using frequency analysis, T-test, ANOVA, correlation and regression analysis. The major findings of this study were as follows: 1. The level of strategic selection and external learning mechanism of private hospital was lower than that of medical corporation, and others corporation hospital. 2. There was little difference between hospitals in metropolitan and those in small cities. 3. Hospitals that have under 100 beds were statistically lower level in strategic selection and external learning mechanism than hospitals has over 100 beds. 4. Formal coordinating and external learning mechanism, and foundation form(medical corporation) were significantly influenced on profitability from specialized field. 5. Strategic selection and adaptation mechanism were significantly affected on total profitability. 6. Strategic selection and external learning mechanism were significantly influenced on competitive power around its local market. Hospitals that are to be competitive by specialization should have to establish mechanism for management such as balanced strategy, coordinating and learning mechanism.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.24-32
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• 2011

In ubiquitous environment, the analysis for student's learning behaviour is essential to provide students with personalized education. SCORM(Sharable Contents Object Reference Model), IMS LD (Instructional Management System Learning Design) standards provide the support function of learning design such as checking the progress. However, in case of applying these standards contain many problem to add or modify the contents. In this paper, We implement the system that manages the learner behaviour by hooking the event of web browser. Through all of this, HTML-based content can be recycled without any additional works and the problems by applying the standard can be improved because the store and analysis of the learning result is possible. It also supports the ubiquitous learning environment because of keeping track of the learning result in case of network disconnected.