• Journal of Information Technology Services
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• v.9 no.4
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• pp.109-121
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• 2010

Most organizations adopt their own performance measurement systems. Those organizations select performance measures to meet their goals. Organizations can give only limited description of what performance measures are. Kaplan and Norton suggest that the Balanced Scorecard (BSC) to complement the conventional performance measures. The BSC can provide management system with a comprehensive strategic vision and integrates non-financial measures with financial measures. The BSC is widely used for measuring corporate performance. This paper investigates how the BSC-based performance measures can be applied to Learning City. The Learning City's performance measures and strategy map on the basis of the BSC are suggested in this research. This paper adopt the AR(assurance region)-DEA model which could limit the range of weight on performance measures to prevent each viewpoint of BSC from having unlimited elasticity. The proposed model is based on CCR model including a property of unit invariance to use the data without normalization process.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.399-404
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• 2020

There are many attempts to apply AI technology to diagnose facilities or improve the work efficiency of the power industry. The emergence of new machine learning technologies, such as deep learning, is accelerating the digital transformation of the power sector. The problem is that traditional power systems face security risks when adopting state-of-the-art AI systems. This adoption has convergence characteristics and reveals new cybersecurity threats and vulnerabilities to the power system. This paper deals with the security measures and implementations of the power system using machine learning. Through building a commercial facility operations forecasting system using machine learning technology utilizing power big data, this paper identifies and addresses security vulnerabilities that must compensated to protect customer information and power system safety. Furthermore, it provides security guidelines by generalizing security measures to be considered when applying AI.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.239-246
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• 2003

Statisticians, or data miners, are often requested to assess the importances of input variables in the given supervised learning model. For the purpose, one may rely on separate ad hoc measures depending on modeling types, such as linear regressions, the neural networks or trees. Consequently, the conceptual consistency in input variable importance measures is lacking, so that the measures cannot be directly used in comparing different types of models, which is often done in data mining processes, In this short communication, we propose a unified approach to the importance measurement of input variables. Our method uses sensitivity analysis which begins by perturbing the values of input variables and monitors the output change. Research scope is limited to the models for continuous output, although it is not difficult to extend the method to supervised learning models for categorical outcomes.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.2
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• pp.34-43
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• 2022

In Efforts to prevent CFIT accidents so far, have been emphasizing various education measures to minimize the occurrence of human errors, as well as enforcement measures. However, current engineering measures remain in a system (TAWS) that gives warnings before colliding with ground or obstacles, and even actual automatic avoidance maneuvers are not implemented, which has limitations that cannot prevent accidents caused by human error. Currently, various attempts are being made to apply machine learning-based artificial intelligence agent technologies to the aviation safety field. In this paper, we propose a deep reinforcement learning-based artificial intelligence agent that can recognize CFIT situations and control aircraft to avoid them in the simulation environment. It also describes the composition of the learning environment, process, and results, and finally the experimental results using the learned agent. In the future, if the results of this study are expanded to learn the horizontal and vertical terrain radar detection information and camera image information of radar in addition to the terrain database, it is expected that it will become an agent capable of performing more robust CFIT autonomous avoidance.

• Journal of Korean language education
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• v.29 no.2
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• pp.49-72
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• 2018

The purpose of this study is to introduce an efficient measure in Korean language education for learners of Korean by applying shadowing techniques which focus on improving not only listening and speaking skills but also reading and writing skills. First of all, the study discusses about the definition of shadowing along with the effect of shadowing. The second part will be about examining the proposed method related to shadowing technique which is comprised of original shadowing techniques and other techniques transformed from the original. Thirdly, the paper will be discussing background information of the shadowing technique in previous researches and experiments using shadowing techniques in Korean language education. Finally, there will be an introduction of learning measures that apply to skill unification. Most of the previous researches of the shadowing technique were limited to a few students with only mid-to-high level learners while this method could cover up to a wide range of learners. The most effective way of learning a foreign language would firstly be the suggested method and the focus should be on repetition and practice of the learners.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.4
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• pp.162-172
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• 2021

This paper proposes stochastic methods to find an approximate solution for the L²-Wasserstein least squares problem of Gaussian measures. The variable for the problem is in a set of positive definite matrices. The first proposed stochastic method is a type of classical stochastic gradient methods combined with projection and the second one is a type of variance reduced methods with projection. Their global convergence are analyzed by using the framework of proximal stochastic gradient methods. The convergence of the classical stochastic gradient method combined with projection is established by using diminishing learning rate rule in which the learning rate decreases as the epoch increases but that of the variance reduced method with projection can be established by using constant learning rate. The numerical results show that the present algorithms with a proper learning rate outperforms a gradient projection method.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.73-81
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• 2022

This study is a descriptive research study to analyze the relationship between learning motivation, learning immersion, and self-directed learning. For this study, data were collected from August 1 to 30, 2021. The collected data were analyzed using the IBM SPSS/WIN 22.0 program. The learning motivation was positively correlated with learning immersion and self-directed learning. In analysis results, the factors affecting learning immersion are learning motivation and self-directed learning. And it was confirmed that self-direction was a partial mediating factor in the relationship between learning motivation and learning immersion. Learning motivation is an important factor for nursing students' learning immersion and self-directed learning. Therefore, specific measures to improve self-directed learning should be prepared for learning immersion. Therefore, nursing students' self-directed learning is an important factor for learning motivation and learning immersion, and specific measures to improve that should be prepared.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.141-157
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• 2023

The present work aimed to present the development of 'Funt', the augmented reality-based digital app as an educational tool for foreign language learning. Our work further evaluated the learning efficacy of the tool by the assessment of the three dependent measures including learning motivation, learning satisfaction, and learning involvement. With a learning app of 'Funt', students can use AR app to access recognition-based or location-based experiences such that any objects, artifacts, or media appear to be in the app. Students are then able to interact with the digital content by manipulating it to learn more about it. Students's engagement should also increase when they create their own experience in AR to demonstrate their understanding of a particular concept or words. Learning effects were evaluated on survey data collected from a hundred respondents aging six to nine years. One-group design for pre-test and post-test was utilized to examine the differences of learning efficacy by comparing the non-'Funt' group and the Funt group scores. A pairwise t-Test was performed for pairwise comparisons between two learning groups. The results indicate that the 'Funt' group scored significantly higher than the non-'Funt' group in the measures of learning motivation, learning satisfaction, and learning involvement. Overall, our results suggest that 'Funt' attracted the students' attention, provided them with a fun context to learn English vocabulary, and develop positive motivation and satisfaction towards vocabulary learning through AR technology.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.161-168
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• 2013

For the successful implementation of IT projects, individual consultant's competency in the project is very important. Especially, learning processes are required for solving various critical issues which can be occurred during implementing IT project. The objective of this research is to develop the measures for learning processes. Prior to setup the learning processes, we conducted 3 times in-depth interviews with IT consultants who have over 20 years IT project experiences. Through interviews with IT project expert, we tried to validate our research mode and develop survey questionnaires.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.3
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• pp.59-68
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• 2021

Purpose : The purpose of this study was to investigate the lecture method and physical activity level of Korean university students during the COVID-19 pandemic to determine their effect on the students' mental health, self-efficacy, and learning motivation. Methods : A total of 203 participants (53 male, 150 female) completed the study. An online survey was distributed through a social media platform between March 24 and April 7, 2021. Participants completed the international physical activity questionnaire-short form (IPAQ-SF), COVID-19 stress scale for Korean people (CSSK), the Korean version of the general health questionnaire (KGHQ-30), and self-efficacy and learning motivation scales. Results : Among the general characteristics of the study subjects, there were statistically significant differences in the IPAQ-SF, CSSK, KGHQ, self-efficacy, and learning motivation measures by sex. There were no significant differences in the degree of IPAQ-SF, CSSK, KGHQ, self-efficacy, and learning motivation among any of the lecture method and university area groups. The level of physical activity corresponded with significant differences in KGHQ, self-efficacy, and learning motivation, excluding CSSK. There was a statistically significant positive correlation between IPAQ and self-efficacy (r=.273, p<.001), IPAQ-SF and learning motivation (r=.201, p<.01), CSSK and KGHQ (r=.271, p<.001), self-efficacy and learning motivation measures (r=.506, p<.001). There was a statistically significant negative correlation between IPAQ-SF and KGHQ (r=-.203, p<.01) and between KGHQ and self-efficacy (r=-.558, p<.001). Conclusion : CSSK and KGHQ measures were significantly higher in female students than in male students. Therefore, it is important to consider sex as a protective factor in the mental health management of university students in the context of an infectious disease pandemic. The results of this study suggest that university students should continue to engage in physical activities, even during a pandemic, and that it is necessary to prepare health management to improve mental health in such situations.