• Information Systems Review
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• v.8 no.1
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• pp.287-303
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• 2006

Recently, Investment on HRM, particularly, on training and development, in companies has been increased. Therefore, HR managers pay attention to action learning that has the practical effect on performance. The purpose of this study is to introduce action learning as an efficient training method and simultaneously to raise operational issues from the case study. This study analyses a training and development program applying action learning for team manager candidates in corporate Hyosung from September, 2005 to January, 2006. The findings are as follows: First, inefficient processes are thrown out by the process reengineering applying action learning. Second, the training and development activity is maximized by the integrated use of internal and external facilitators. Third, the steady support of executives and the driving force of HRD managers are considered as main success factors.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.31-36
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• 2020

Virtual simulation education, which is one of the methods of executing engineering education, is spreading. In general online education, only theoretical learning-centered lessons and practical training of simple small projects are conducted remotely, and it is necessary to disseminate various educational contents. Due to the spread of smart factories these days, most producers use automatic control to produce, inspect and package their products. The operation of automation equipment is controlled by using electricity, and electricity-related learning is operated in various departments. Due to the characteristics of electricity, it is difficult to learn online due to safety issues and high cost of practical equipment. In this paper, we provide a simulation-based electrical control panel distance learning model to improve the sense of accomplishment of education related to electrical training. Through the experiment of the proposed model, it was confirmed that the learning was more satisfied with the virtual simulation education than the online education using the existing equipment. It is expected that it can be used as a basic course for automation equipment education in the future.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.483-490
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• 2019

In the Network Intrusion Detection System (NIDS), the function of classification is very important, and detection performance depends on various features. Recently, a lot of research has been carried out on deep learning, but network intrusion detection system experience slowing down problems due to the large volume of traffic and a high dimensional features. Therefore, we do not use deep learning as a classification, but as a preprocessing process for feature extraction and propose a research method from which classifications can be made based on extracted features. A stacked AutoEncoder, which is a representative unsupervised learning of deep learning, is used to extract features and classifications using the Random Forest classification algorithm. Using the data collected in the IOT environment, the performance was more than 99% when normal and attack traffic are classified into multiclass, and the performance and detection rate were superior even when compared with other models such as AE-RF and Single-RF.

• International Commerce and Information Review
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• v.15 no.2
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• pp.109-128
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• 2013

With the growth of contents business, the expansion of domestic culture contents into global market became active. However, while some field such as game, music and movie have made fine results, education contents has failed to make significant success in global market. Therefore, this study intends to look into a case of Contents Management Institute(CMI), which spread G-Learning into La Ballona Elementary School located in LA. In this case, CMI successfully dealt with diverse difficulties to conduct a G-Learning class in the school and helped to increase students' achievement. Based on analyzing this case, this study suggests three reasons behind the success. First, by separating platform and learning contents in development process, CMI could save the cost in contents development and handle problems swiftly. Second, it could be possible to use human resources efficiently by constucting a support organization. Third, by sharing information and doing persuasion CMI could lead to chain persuasion process among local decision makers.

• Journal of The Korean Association of Information Education
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• v.8 no.4
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• pp.537-545
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• 2004

In spite of the fact that project-based learning has had positive effects on improvement of creation power and expansion of the spirit of inquiry, the project-based learning lesson was difficult to carry out in the classroom. The web overcomes time and space limitations in traditional schools. This study has developed and implemented an online project-based website of children's education, based upon the extensive classroom use of multimedia materials to further students participation and interest in projects of discovery. The developed website shows the entire process used through out the project. This paper presents the project's activities and students' learning, using multimedia and web. This study was conducted in fourth grade of an elementary school for a month. The results of this study suggest that the effects of using the project-based website were improved self-directed learning and generation of new ideas.

• Journal of The Korean Association of Information Education
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• v.12 no.2
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• pp.223-234
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• 2008

Educating qualified elementary school teachers depends on excellent pre-service education. The high quality of education is accomplished by various interactions between teachers and learners, as well as active participation by students. In the present study, online problem-based learning and an e-portfolio were used to examine the effect on the computer-curriculum education to reflect social and individual needs, and to enhance the quality of instruction at universities. Students (n=105) participated in six different problem-based learning sessions. At the same time, they developed Blog e-portfolios as individual and group products, and wrote reflective journals that focused on their learning processes and results. A qualitative analysis method was employed to analyze the reflective journals. The results of the analyses showed the following: 1) Increasing the understanding of the computer-curriculum education, 2) enhancing students' competence in using ICT potentially, 3) cultivating student-centered teaching and learning strategies on ICT, and 4) enhancing competence of future teaching activities through experiencing e-portfolio as a performance-assessment tool.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.993-1000
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• 2016

Semi-supervised learning makes it easy to use an unlabeled data in the supervised learning such as classification. Applying the semi-supervised learning on the regression analysis, we propose two methods for a better regression function estimation. The proposed methods have been assumed different marginal densities of independent variables and different smoothing parameters in unlabeled and labeled data. We shows that the overfitted pilot estimator should be used to achieve the fastest convergence rate and unlabeled data may help to improve the convergence rate with well estimated smoothing parameters. We also find the conditions of smoothing parameters to achieve optimal convergence rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.555-561
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• 2018

It is the Korean language textbook of elementary school 1~2 grade that forms the basis of the textbook to nurture the creative convergence talent with the core competence required by the future society. In order to increase the learning effect based on the textbooks, the interest inducing factors were derived on the basis of the learning interest, and the textbook design was analyzed by the in - depth interviews and discussions of the expert group. As a result, Graphic elements using bright and soft colors, illustrations of peer groups related to learning contents, and resilient use of sans serifs. However, issues such as lack of proper mixing of photos and illustrations, further development of learning helper characters, configuration of spare margins, graphic image design, and lack of a structured layout that utilizes color and visual images were cited as problems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.14-21
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• 2021

Green networking has become a issue to reduce energy wastes and CO2 emission by adding energy managing mechanism to wired data networks. Energy consumption of the overall wired data networks is driven by access networks, expect for end devices. However, on a global scale, it is more difficult to manage centrally energy, measure and model the real energy use and energy savings potential of the access networks. This paper presented the multiple linear regression model to predict energy consumption of wired access networks using supervised learning of machine learning with data collected by existing investigated materials, actual measured values and results of many models. In addition, this work optimized the performance of it by various experiments and predict energy consumption of wired access networks. The performance evaluation of the regression model was achieved by well-knowned evaluation metrics.