• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• Journal of Science Education
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• v.44 no.2
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• pp.240-258
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• 2020

The advances in science technology brought about a new form of learning called flipped-learning: a combination of on-line and off-line learning. A flipped learning is a form of blended learning which has become quite popular, nowadays, in the field of education. Despite the emphasis on the importance of medical humanities in medical education program, there are no effective teaching and learning models to realize the purpose of medical humanities education. This study explores the possibility of flipped-learning to apply medical humanities classes. The class was designed based on the ADDIE model consisting of five stages, analysis - design - development - execution - evaluation. In order to do 'flipped-learning,' the instructor reconstructs the purpose of medical humanities education, instructional purpose and content, and analyzed learner. The contents of the medical humanities class were structured considering the purpose of the introduction to the medical humanities in the medical education program and the competencies that medical personnel should have in the developed health care environment. The instructor produces a video of the lecture and makes it possible to use LMS (Learning Management System) before and after classes, and conducts discussion activities so that learner-learner and learner-teacher interaction could actively occur during the class. The result of applying medical humanities lesson as flipped learning is as follows: First, it can realize the essence of medical humanities education. Second, it contributes to strengthening the competencies of health care provider. Third, flip learning can be used as a new teaching strategy for medical humanities education. The result of this study is expected to suggest new ways of introduction to teaching method in the traditional medical humanities class and contribute to the practice of designing and doing flipped learning of medical humanities class in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.105-111
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• 1999

This Paper is about how to deside the best parameter of PID controller, using Genetic Algorithms and Neural Networks. Control by Genetic Algorithms, which is off-line pass, has weakness for disturbance. So we want to improve like followings by adding Neural Network to controller and putting it on line. First we find PID parameter by Genetic Algorithms in forward pass of Neural Network and set the best output condition according to the increasing number of generation. Second, we explain the adaptability for disturbance with simulation by correcting parameter by backpropagation learning rule by using the learning ability of Neural Network.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.62-66
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the learning control field was learning in robots doing repetitive tasks such as an assembly line works. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown for the iterative precision of each link.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.46.3-47
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• 2021

Recently a multilayer spectral inversion (MLSI) model has been proposed to infer the physical parameters of plasmas in the solar chromosphere. The inversion solves a three-layer radiative transfer model using the strong absorption line profiles, H alpha and Ca II 8542 Å, taken by the Fast Imaging Solar Spectrograph (FISS). The model successfully provides the physical plasma parameters, such as source functions, Doppler velocities, and Doppler widths in the layers of the photosphere to the chromosphere. However, it is quite expensive to apply the MLSI to a huge number of line profiles. For example, the calculating time is an hour to several hours depending on the size of the scan raster. We apply deep neural network (DNN) to the inversion code to reduce the cost of calculating the physical parameters. We train the models using pairs of absorption line profiles from FISS and their 13 physical parameters (source functions, Doppler velocities, Doppler widths in the chromosphere, and the pre-determined parameters for the photosphere) calculated from the spectral inversion code for 49 scan rasters (~2,000,000 dataset) including quiet and active regions. We use fully connected dense layers for training the model. In addition, we utilize a skip connection to avoid a problem of vanishing gradients. We evaluate the model by comparing the pairs of absorption line profiles and their inverted physical parameters from other quiet and active regions. Our result shows that the deep learning model successfully reproduces physical parameter maps of a scan raster observation per second within 15% of mean absolute percentage error and the mean squared error of 0.3 to 0.003 depending on the parameters. Taking this advantage of high performance of the deep learning model, we plan to provide the physical parameter maps from the FISS observations to understand the chromospheric plasma conditions in various solar features.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.709-713
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• 2004

This Paper Presents an Internet-based Java self-learning educational system which consists of a management system named Java Web Player (JWP) and creative multimedia contents fer Java language. The JWP Is a Java application program free from security problems by the Java Web Start technologies that supports an Integrated learning environment including three Important learning Procedures: Java concept learning Process, Programming practice process and assessment process. This JWP enables the learners to achieve efficient and Interesting self-learning since the learning process is designed to enhance the multimedia capabilities on the basis of various educational technologies. On-line voice presentation and its related texts together with moving images are synchronized for efficiently conveying creative contents to learners. Furthermore, a simple and useful compiler is included in the JWP fur providing user-friendly language practice environment enabling such as coding, editing, executing and debugging Java source files on the Web. The assessment process with various items helps the learners not only to increase their academic capability but also to appreciate their current degree of understanding. Finally, simple multiple choices are given suddenly to the learners while they are studying through the JWP and the test results are displayed on the message box. The proposed system can be used for an efficient tool for learning system on the Web.

• Journal of Practical Engineering Education
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• v.5 no.2
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• pp.163-168
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• 2013

The vicious cycle of over-education has been made. That is, higher education enrollment rate is high, but university graduate employment rate is low. To eliminate this cycle and relieve youth unemployment and young people to enter the labor market early, dual education and training system is needed. This dual system can support working and learning in parallel. So, worker can get the opportunity pre-employment and post-learning and improve his/her job skills. Recent MOOC (Massive Open On-line Course), a new form of online education system, has emerged. MOOC combines education, entertainment and social networking, and emphasize the interaction between faculty and student and between students. The educational contents of MOOC are available free of charge. Using newly changed online education environments we can effectively provide knowledge and skills. In technology and engineering education hands-on training is necessary. In order to support work based learning dual system for worker to work and learn in parallel, we should build the multi-learning system to combine the online education and campus hands-on practice.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.51-60
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• 2014

Modern society is rapidly changing by the Internet, and it is getting influential on the field of education. Learners can learn what they want to learn actively and freely at their desired level at anywhere in their free time by using the internet. The purpose of this study, therefore, is to find out the methods for improving writing ability through e-learning. The results of the study are as follows: First, learners can attend a lecture to improve their writing ability and can get learning materials from on-line course sites, internet websites, communities and blogs. Second, e-learning is learner-centered education, so it stimulates learners learning motivation and interest. Third, learners have an opportunity to express their ideas freely, and they can gain cultural comprehension while they communicate with people in the world by e-mail and chatting.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.157-162
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• 2010

The cart-pole balancing problem is a pseudo-standard benchmark problem from the field of control methods including genetic algorithms, artificial neural networks, and reinforcement learning. In this paper, we propose a novel approach by using online reinforcement learning(OREL) to solve this cart-pole balancing problem. The objective is to analyze the learning method of the OREL learning system in the cart-pole balancing problem. Through experiment, we can see that approximate faster the optimal value-function than Q-learning.

• Management & Information Systems Review
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• v.14
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• pp.79-99
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• 2004

Cyber education system service is in the field of software service which is highlighted after the latter half of 1990'. But the progress of this service is impeded by the lack of back office which contributes to the evaluation of learning achievement and the management of learning progress. This article points out the problem of current back office which is the most important in the cyber education system, and focuses on the new intelligent learning achievement evaluation module. First, we define the cause and effect between the learning stages using by fuzzy implication which is the important part of fuzzy theory. Next, we suggest the model which generates the results of the learning achievement evaluation. This model, suggested by this article, may contribute to the development of the cyber education system by improving the current on-line education service.