• Educational Technology International
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• v.6 no.1
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• pp.41-63
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• 2005

E-Learning is widely introduced with cyber universities in Korea from 2001 whencyber universities were first authorized by the Ministry of Education and Human Resource Development. E-learning amplified by cyber university gave a big impact in the campus based university which became the cause for the educational paradigm shift. The changes of status of cyber university shows important trend in college education which was analyzed by enrollment rate, types of cyber university, demography, and study areas. The enrollment rate of cyber universities is ever since 2001 and variety of study areas gives popularity to students. The demography of students is as expected older than traditional students. Female students at the cyber university outnumbered that at campus based university in Korea. For analyzing the trend of e-learning in Korea, there were studies twice in 2001 May-June from 213 faculty members and staff, 630 students and in 2004 May-June with 401 students. Most of e-learning students tent to spend less time yet, students feel more burden with e-learning. Professors tend to load more materials for the e-learning in 2001but in 2004 study, the difference no longer exists. Professors and students feel the academic achievement through e-learning is not as good as from the traditional classes. Difficulties for e-learning in 2001 were the lack of administrative information but in 2004, boring contents and lack of instructional strategies for e-learning. Technical problems still do exist but less serious. Suggestions for e-learning are blended learning, online students prefer video streaming with their own lecturer, new definition of instructor is needed, professional development for content development and online instruction is needed, success story of online learning should be encouraged, guidance for online students needed. The cyber university experiencegave a positive impact on the traditional universities such as rethinking the roles of universities, the quality control of classes, professional development, student oriented educational service of e-learning pedagogy.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.6
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• pp.535-545
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• 2013

The goal of stock investment is earning high rate or return with stability. To accomplish this goal, using a portfolio that distributes stocks with high rate of return with less variability and a stock price prediction model with high accuracy is required. In this paper, three methods are suggested to require these conditions. First of all, in portfolio re-balance part, Max-Return and Min-Risk (MRMR) model is suggested to earn the largest rate of return with stability. Secondly, Entering/Leaving Rule (E/L) is suggested to upgrade portfolio when particular stock's rate of return is low. Finally, to use outstanding stock price prediction model, a model based on Semi-Supervised Learning (SSL) which was suggested in last research was applied. The suggested methods were validated and applied on stocks which are listed in KOSPI200 from January 2007 to August 2008.

• Journal of Information Technology Services
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• v.17 no.1
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• pp.121-134
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• 2018

Massive Open Online Course (MOOC) is online education that anyone can register for free and has internet access. MOOC is also called Education Revolution and is spreading rapidly all over the world. Although recent MOOC high-quality classes may enhance the value of MOOC, MOOC learning still needs much research. Since MOOC has low learning completion rate and continuous use rate, various studies on the reasons that learners give up at the beginning of learning have not been tried yet This research is studied for the continuous intention of use of MOOC applying self-determination theory and learning flow theory based on technology acceptance model. In particular, the research are conducted for cultural difference in continuous usage of MOOC between Korean and Chinese. The research results show that self-determination theory applying perceived autonomy, perceived competence, and perceived relatedness and learning flow is useful to explain continuous use of MOOC. The research also shows that Hofstede theory works well in explaining the cultural difference between Korea and China in continuous usage of MOOC. The result shows that korean is more influenced by perceived external motivation like perceived usefulness and chinese is more influenced by internal motivation like learning flow in continuous use of MOOC.

• Journal of Korea Game Society
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• v.20 no.6
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• pp.23-30
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• 2020

There are many cases in the game. So, Game have to learn a lot. This paper uses reinforcement learning to improve the learning speed. However, because reinforcement learning has many cases, it slows down early in learning. So, the speed of learning was improved by using the minimax algorithm. In order to compare the improved performance, a Gonu game was produced and tested. As for the experimental results, the win rate was high, but the result of a tie occurred. The game tree was further explored using progressive deepening to reduce tie cases and win rate has improved by about 75%.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.56-63
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• 2021

As the use of robots in service area increases, research has been conducted to replace human tasks in daily life with robots. Among them, this study focuses on the tidy-up task on a desk using a robot arm. The order in which tidy-up motions are carried out has a great impact on the success rate of the task. Therefore, in this study, a neural network-based method for determining the priority of the tidy-up motions from the input image is proposed. Reinforcement learning, which shows good performance in the sequential decision-making process, is used to train such a task planner. The training process is conducted in a virtual tidy-up environment that is configured the same as the actual tidy-up environment. To transfer the learning results in the virtual environment to the actual environment, the input image is preprocessed into a segmented image. In addition, the use of a neural network that excludes unnecessary tidy-up motions from the priority during the tidy-up operation increases the success rate of the task planner. Experiments were conducted in the real world to verify the proposed task planning method.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.41-47
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• 2022

A reliable prediction model of national occupational accident fatality rate can be used to evaluate level of safety and health protection for workers in a country. Moreover, the socio-economic aspects of occupational accidents can be identified through interpretation of a well-organized prediction model. In this paper, we propose a machine learning based relative comparison methods to predict and interpret a national occupational accident fatality rate based on socio-economic indicators. First, we collected 29 years of the relevant data from 11 developed countries. Second, we applied 4 types of machine learning regression models and evaluate their performance. Third, we interpret the contribution of each input variable using Shapley Additive Explanations(SHAP). As a result, Gradient Boosting Regressor showed the best predictive performance. We found that different patterns exist across countries in accordance with different socio-economic variables and occupational accident fatality rate.

• Journal of ILASS-Korea
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• v.29 no.3
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• pp.147-154
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• 2024

This study explores the rate of injection (ROI) and injection quantities of a solenoid-type high-pressure injector under varying conditions by integrating experimental methods with machine learning (ML) techniques. Experimental data for fuel injection were obtained using a Zeuch-based HDA Moehwald injection rate measurement system, which served as the foundation for developing a machine learning model. An artificial neural network (ANN) was employed to predict the ROI, ensuring accurate representation of injection behaviors and patterns. The present study examines the impact of ambient conditions, including chamber temperature, chamber pressure, and injection pressure, on the transient profiles of the ROI, quasi-steady ROI, and injection duration. Results indicate that increasing the injection pressure significantly increases ROI, with chamber pressure affecting its initial rising peak. However, the chamber temperature effect on ROI is minimal. The trained ANN model, incorporating three input conditions, accurately reflected experimental measurements and demonstrated expected trends and patterns. This model facilitates the prediction of various ROI profiles without the need for additional experiments, significantly reducing the cost and time required for developing injection control systems in next-generation aero-engine combustors.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.3
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• pp.17-24
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• 2004

We present a P-type iterative learning control(ILC) scheme for uncertain robotic systems that perform the same tasks repetitively. The proposed ILC scheme comprises a linear feedback controller consisting of position error, and a feedforward and feedback teaming controller updated by current velocity error. As the learning iteration proceeds, the joint position and velocity mrs converge uniformly to zero. By adopting the learning gain dependent on the iteration number, we present joint position and velocity error bounds which converge at the arbitrarily tuned rate, and the joint position and velocity errors converge to zero in the iteration domain within the adopted error bounds. In contrast to other existing P-type ILC schemes, the proposed ILC scheme enables analysis and tuning of the convergence rate in the iteration domain by designing properly the learning gain.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.57-63
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• 2010

The damping parameter of Levenberg-Marquardt algorithm switches between error backpropagation and Gauss-Newton learning and affects learning speed. Fixing the damping parameter induces some oscillation of error and decreases learning speed. Therefore, we propose the way of a variable damping parameter with referring to the alternation of error. The proposed method makes the damping parameter increase if error rate is large and makes it decrease if error rate is small. This method so plays the role of momentum that it can improve learning speed. We tested both iris recognition and wine recognition for this paper. We found out that this method improved learning speed in 67% cases on iris recognition and in 78% cases on wine recognition. It was also showed that the oscillation of error by the proposed way was less than those of other algorithms.

• Human Ecology Research
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• v.59 no.3
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• pp.341-351
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• 2021

The purpose of this study was to examine the longitudinal relationships between Korean adolescents'mobile phone dependency, trajectories of depression, and self-regulated learning abilities. To achieve these goals, structural equation modeling analysis was conducted, using the 3rd, 5th and 7th wave of the data on 4th graders taken from the Korean Children and Youth Panel Survey. The results can be summarized as follows. First, growth-curve longitudinal analysis indicates that depression in 6th through 10th grade has increased. Second, mobile phone dependency among adolescents at 6th grade has a significant effect on both the initial value and the rate of change in depression. Also, the initial value and the rate of change in depression have significant relationships with mobile phone dependency at 10th grade. Moreover, both increased levels of mobile phone dependency and the rate of change in depression significantly influence adolescents'self-regulated learning abilities at 10th grade. Based on a longitudinal data set, these findings demonstrate the causal relationships between Korean adolescents'trajectories of depression and their mobile phone dependency. The findings also provide a comprehensive framework with implications for adolescents'development through an understanding of the relationships between adolescents'depression and mobile phone dependency, which impact their self-regulated learning abilities.