• Proceedings of the KSME Conference
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• 2004.04a
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• pp.822-827
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• 2004

In this paper, an intelligent fault diagnosis system is proposed for induction motors through the combination of feature extraction, genetic algorithm (GA) and neural network (ANN) techniques. Features are extracted from motor vibration signals, while reducing data transfers and making on-line application available. GA is used to select most significant features from whole feature database and optimize the ANN structure parameter. Optimized ANN diagnoses the condition of induction motors online after trained by the selected features. The combination of advanced techniques reduces the learning time and increases the diagnosis accuracy. The efficiency of the proposed system is demonstrated through motor faults of electrical and mechanical origin on the induction motors. The results of the test indicate that the proposed system is promising for real time application.

• Journal of Multimedia Information System
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• v.5 no.2
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• pp.99-104
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences

• The Journal of Korean Association of Computer Education
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• v.11 no.4
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• pp.13-21
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• 2008

Although education on information technology ethics is increasingly being reinforced in elementary and middle schools, immoral and illegal behaviors online are not showing any sign of decrease. Because cognition- based education fails to lead students' practice on what they learned. Therefore, this study proposes a teaching- learning model integrating cognitive, affective and conative dimensions which had been developed on the elementary students' practice of information technology ethics. We verified the effect of achievement and practice through application this model to the school. To raise reliability we analysed the result of learning such as observation, analysis video data, homepage etc., and interview.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.19-36
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• 2016

The purpose of this study was to analyze domestic and overseas cases of flipped learning instructional design model and actual classes in K-12 Education, and find out educational implications in order to design effective flipped learning. Papers, 14 articles in domestic and international journals, were collected. As results of the analysis, first, flipped learning instructional model was presented as flipped learning that applied to ADDIE model and 8C model etc. Second, 'Activities before classroom' consisted of watching lecture videos, lecture notes etc. 'Activities during classroom' was checking prior learning in early stage, individual activities and cooperative activities in middle stage, and solving quizzes, reviewing in later stage. After class, students performed tasks and questions&answers. Third, in case of creating lecture video, they used application such as Screencast-o-matic, Explain Everything; In contrast, some cases utilized online web-sites such as YouTube or Phet. Fourth, positive results were shown in learners' academic achievement, motivation and learning attitude etc. This research has a significance in terms of analyzing the flipped learning instructional model and flipped learning activities, and providing the preliminary data to facilitate the design for the effective flipped learning.

• Knowledge Management Research
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• v.20 no.3
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• pp.119-137
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• 2019

With the recent spread of digital content, more people have been watching the digital content of TV programs on their PCs or mobile devices, rather than on TVs. With the change in such media use pattern, genres(types) of broadcast programs change in the flow of the times and viewers' trends. The programs that were broadcast on TVs have been released in digital content, and thereby people watching such content change their perception. For this reason, it is necessary to newly and differently classify genres(types) of broadcast programs on the basis of digital content, from the conventional classification of program genres(types) in broadcasting companies or relevant industries. Therefore, this study suggests a plan for newly classifying broadcast programs through using machine learning with the log data of people watching the programs in online media and for applying the new classification. This study is academically meaningful in the point that it analyzes and classifies program types on the basis of digital content. In addition, it is meaningful in the point that it makes use of the program classification algorithm developed in relevant industries, and especially suggests the strategy and plan for applying it.

• Journal of Korean Elementary Science Education
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• v.40 no.4
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• pp.433-442
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• 2021

The purpose of this study is to develop an artificial-intelligence STEAM program for real-time interactive online class for elementary science and to analyze its effect on science academic achievement and creative problem-solving ability. The applied unit was 'Life of plant', a 4th grade science subject with high difficulty in teaching and learning mainly by memorization. The theme of the program is 'Creating a doctor of plant artificial intelligence chatbot'. The results of this study were as follows: The program developed in this study had a positive effect on elementary school students' science academic achievement and creative problem-solving ability. Therefore, the artificial intelligence STEAM program for elementary science interactive online class is effective in improving students' scientific academic achievement and creative problem-solving ability, and further research on artificial intelligence STEAM education theory, method, and practice is required.

• Journal of Korean Clinical Nursing Research
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• v.17 no.3
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• pp.411-420
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• 2011

Purpose: The purpose of this study was to develop and evaluate a new-nurse education program utilizing both e-learning and instructor demonstration. Methods: From August to December in 2009, the e-learning education program about insulin injection was developed. The control (C) group was educated via instructor demonstration from April 15 to October 6 in 2009, and the experimental (E) group was educated via both e-learning and instructor demonstration from January 5 to October 13 in 2010. After each education, knowledge and educational effectiveness were checked. Results: Satisfaction with the education contents in the E group was significantly higher than those of the C group (Z=-3.72, p<.001), and satisfaction with the education method in the E group was higher than those of the C group (Z=-2.98, p=.003). Usefulness (Z=-3.33, p=.001), application (Z=-2.62, p=.009), and confidence (Z=-2.61, p=.009) in the E group were all higher than those of the C group. 78.9% in the E group reused the e-learning program after the experimental education. Conclusion: Combined educational program with e-learning and instructor demonstration had both merits of online efficiency and face-to-face education. It would be useful especially for new-nurses to improve their nursing skills in accomplishing their roles.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.107-123
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• 2021

Recently, there have been a number of researchers in the field of education who are actively exploring the educational applications of Blockchain technology, even though it is still in its infancy. Some researchers have been investigating its application in educational administration to issue academic credentials' or maintain student records with distributed ledger, which is the basis of Blockchain technology. Whereas, others have been examining its application in redesigning learning systems that are being used in various contexts, including online learning and lifelong education. In that vein, this paper aims to discuss a liberal arts education system which will be supported by Blockchain-based 'smart contracts'. At present, active efforts are being made to innovate liberal arts education in Korea, centered around government-funded university innovation projects and there have been reports of great achievements. However, if the Blockchain technology is applied to innovating the liberal arts education, we will innovate not only the liberal arts education but also university education as a whole. In this paper, there are suggestions on how to build a learner-centered educational environment where a liberal arts education system is supported by Blockchain-based smart contracts. First of all, the current innovation in liberal arts education and its limitations are discussed, followed by ways in which Blockchain-based smart contracts can reframe the liberal arts education system. Last but not least, the paper addresses implications of the Blockchain technology applications in liberal arts education, along with their future prospects.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.37-45
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• 2022

As of 2020, about 500 hours of videos are uploaded to YouTube, a representative online video platform, per minute. As the number of users acquiring information through various uploaded videos is increasing, online video platforms are making efforts to provide better recommendation services. The currently used recommendation service recommends videos to users based on the user's viewing history, which is not a good way to recommend videos that deal with specific purposes and interests, such as educational videos. The recent recommendation system utilizes not only the user's viewing history but also the content features of the item. In this paper, we extract the content features of educational video for educational video recommendation based on YouTube, design a recommendation system using it, and implement it as a web application. By examining the satisfaction of users, recommendataion performance and convenience performance are shown as 85.36% and 87.80%.