• Journal of Information Technology Services
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• v.20 no.1
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• pp.55-65
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• 2021

For smart defense innovation, the key is to apply state-of-the-art technologies of the Fourth Industrial Revolution to national defense. In order to apply state-of-the-art technology to the defense sector, we need to apply and develop technologies to analyze and respond to uncertain future operational environments. To this end, our military is investing a lot of time and effort. To understand future operational environment analysis and to apply and develop our military, we explored the perspectives of operational environment analysis in major countries and studied specific cases of U.S. troops with systematic analysis functions. The U.S. Army has established a cooperative system to analyze future operational environment under the leadership of the Education Command and operates the organization organically. It also utilizes the collective intelligence of expert groups in various fields by utilizing the MSC, and it is time for the Korean military to take the lead in keeping with the era of transformation. To that end, the organization of the U.S. Education Command should be benchmarked and the Korean Future Operation Environment Analysis Organization should be established and operated. Through this study, we have developed an understanding of the future operational environment analysis system of the U.S. Army and presented a plan to apply the ROK MND.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.359-361
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• 2022

최근 현대인의 영양불균형이 점점 심화됨에 따라 영양결핍과 비만의 위험도가 점점 증가하고 있다. 이에 따라 건강기능식품에 대한 관심이 증가하여 일반인들의 건강기능식품 소비가 증가하고 있지만, 적정섭취량에 비해 영양소를 과도하게 섭취 중이거나 영양제를 먹지만 정작 필요한 영양소를 섭취하지 못하는 경우가 빈번히 나타나고 있다. 이러한 문제를 해소하고자 본 논문에서는 7 일간 사용자가 섭취한 식단을 기반으로 부족한 영양소를 수치상으로 계산하여 개인 맞춤 영양제를 추천하는 시스템을 제안한다.

• Korean Association of Arts Management
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• no.58
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• pp.89-119
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• 2021

This study empirically analyzes the factors that affect the people's enjoyment of pure culture and arts, especially art exhibitions. We use 56,588 sample data from the "The Survey of Cultural Enjoyment" collected by the Ministry of Cultrure, Sports and Tourism over the last 10 years and perform multiple regression and Multi-Way ANOVA to analyze the effect of individual's cultural experience on art exhibit visits. The results of the analysis show that the experience of participating in culture and arts events, culture and arts education, and participation in culture and arts clubs have a positive effect on the art exhibition visits. We also identify the positive interaction effects between the three independent variables. In other words, it was found that the average number of visits to art exhibitions was higher for groups who had experience of participating in culture and arts events, culture and arts education, and culture and arts clubs. This study provides a first empirical analysis on personal factors influencing art exhibition visits in Korea and lays the groundwork for future studies in developing a comprehensive predictive model for cultural art visits. In addition, we give policy implications and suggestions specifically, mid-term policies related to promoting art exhibition visits as an extension of individual's engagement with pure culture and arts through big data analysis.

• Management & Information Systems Review
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• v.37 no.1
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• pp.139-154
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• 2018

R programming is free and open source system associated with a rich and ever-growing set of libraries of functions developed and submitted by independent end-users. It is recognized as a popular tool for handling big data sets and analyzing them. Reflecting these characteristics, R has been gaining popularity from data analysts. However, the antecedents of R technology acceptance has not been studied yet. In this study we identify and investigates cognitive factors contributing to build user acceptance toward R in education environment. We extend the existing technology acceptance model by incorporating social norms and software capability. It was found that the factors of subjective norm, perceived usefulness, ease of use affect positively on the intention of acceptance R programming. In addition, perceived usefulness is related to subjective norms, perceived ease of use, and software capability. The main difference of this research from the previous ones is that the target system is not a stand-alone. In addition, the system is not static in the sense that the system is not a final version. Instead, R system is evolving and open source system. We applied the Technology Acceptance Model (TAM) to the target system which is a platform where diverse applications such as statistical, big data analyses, and visual rendering can be performed. The model presented in this work can be useful for both colleges that plan to invest in new statistical software and for companies that need to pursue future installations of new technologies. In addition, we identified a modified version of the TAM model which is extended by the constructs such as subjective norm and software capability to the original TAM model. However one of the weak aspects that might inhibit the reliability and validity of the model is that small number of sample size.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.406-415
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• 2018

Educational satisfaction is an important indicator of the educational field but the existing customer satisfaction index mainly focused on partial area because measurements could not reflect the alteration of university environment. The purpose of this research is to develop a new UCSI for university to improve the quality of university education. This research demonstrates validity and reliability of UCSI. This research uses the second-order confirmatory factor analysis. The results indicate that the reliability and validity of UCSI is verified. Education condition, education course, university development and student support are clarified to be appropriate components of the satisfaction survey. This research develops UCSI and applies it in a university. University managers can be used to measure the satisfaction level of university education and to improve the quality of university education.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.95-104
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• 2020

In this paper, we propose the real time indoor air quality monitoring and controlling platform on cloud using IoT sensor data such as PM10, PM2.5, CO2, VOCs, temperature, and humidity which has direct or indirect impact to indoor air quality. The system is connected to air ventilator to manage and optimize the indoor air quality. The proposed system has three main parts; First, IoT data collection service to measure, and collect indoor air quality in real time from IoT sensor network, Second, Big data processing pipeline to process and store the collected data on cloud platform and Finally, Big data analysis and visualization service to give real time insight of indoor air quality on mobile and web application. For the implication of the proposed system, IoT sensor kits are installed on three different public day care center where the indoor pollution can cause serious impact to the health and education of growing kids. Analyzed results are visualized on mobile and web application. The impact of ventilation system to indoor air quality is tested statistically and the result shows the proper optimization of indoor air quality.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.243-250
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• 2020

In this paper, we propose an effective software education scheme for universities. The key idea of this software education scheme is to analyze software curriculum of QS world university rankings Top 10, SW-oriented university, and regional main national university. And based on the results, we propose five improvements for the effective SW education method of universities. The first is to enhance the adaptability of the industry by developing courses based on the SW developer's job analysis in the curriculum development process. Second, it is necessary to strengthen the curriculum of the 4th industrial revolution core technologies(cloud computing, big data, virtual/augmented reality, Internet of things, etc.) and integrate them with various fields such as medical, bio, sensor, human, and cognitive science. Third, programming language education should be included in software convergence course after basic syntax education to implement projects in various fields. In addition, the curriculum for developing system programming developers and back-end developers should be strengthened rather than application program developers. Fourth, it offers opportunities to participate in industrial projects by reinforcing courses such as capstone design and comprehensive design, which enables product-based self-directed learning. Fifth, it is necessary to develop university-specific curriculum based on local industry by reinforcing internship or industry-academic program that can acquire skills in local industry field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.208-214
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• 2016

With the rising interest in intelligence information technology built on artificial intelligence and big data technologies, all countries in the world including advanced countries such as the United States, the United Kingdom, Japan and so on, have launched national investment programs in preparation for the fourth industrial revolution centered on the software industry. Our country belatedly recognized the importance of software and initiated the 2015 revised educational curriculum for elementary and secondary informatics subjects. This paper thoroughly analyzes the new educational curriculum for information science in high schools and, then, suggests improvements in the areas of information ethics and multimedia. The analysis of the information science curriculum is applied to over twenty science high schools and schools for gifted children, which are expected to play a leading role in scientific research in our country. In the future artificial intelligence era, in which our dependence on information technology will be further increased, information ethics education for talented students who will play the leading role in making and utilizing artificial intelligence systems should be strongly emphasized, and the focus of their education should be different from that of the existing system. Also, it is necessary that multimedia education centered on digital principles and compression techniques for images, sound, videos, etc., which are commonly used in real life, should be included in the 2015 revised educational curriculum. In this way, the goal of the 2015 revised educational curriculum can be achieved, which is to encourage innovation and the efficient resolution of problems in real life and diverse academic fields based on the fundamental concepts, principles and technology of computer science.

• Journal of The Korean Association For Science Education
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• v.42 no.6
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• pp.611-619
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• 2022

The purpose of this study is to explore the possibility of applying big data analysis to provide appropriate feedback to students using evaluation data in science education at a time when interest in educational data mining has recently increased in education. In this study, we use the evaluation data of 2,576 students who took 24 questions of the national assessment of educational achievement. And we use K-means cluster analysis as a method of unsupervised machine learning for clustering. As a result of clustering, students were divided into six clusters. The middle-ranking students are divided into various clusters when compared to upper or lower ranks. According to the results of the cluster analysis, the most important factor influencing clusterization is academic achievement, and each cluster shows different characteristics in terms of content domains, subject competencies, and affective characteristics. Learning motivation is important among the affective domains in the lower-ranking achievement cluster, and scientific inquiry and problem-solving competency, as well as scientific communication competency have a major influence in terms of subject competencies. In the content domain, achievement of motion and energy and matter are important factors to distinguish the characteristics of the cluster. As a result, we can provide students with customized feedback for learning based on the characteristics of each cluster. We discuss implications of these results for science education, such as the possibility of using this study results, balanced learning by content domains, enhancement of subject competency, and improvement of scientific attitude.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.595-600
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• 2024

As the use of artificial intelligence technologies such as machine learning increases in research fields that predict learning outcomes or optimize learning pathways, the use of artificial intelligence in education is gradually making progress. This research is gradually evolving into more advanced artificial intelligence methods such as deep learning and reinforcement learning. This study aims to improve the method of predicting future learning performance based on the learner's past learning performance-history data. Therefore, to improve prediction performance, we propose conditional probability applying the Markov Chain method. This method is used to improve the prediction performance of the classifier by allowing the learner to add learning history data to the classification prediction in addition to classification prediction by machine learning. In order to confirm the effectiveness of the proposed method, a total of more than 30 experiments were conducted per algorithm and indicator using empirical data, 'Teaching aid-based early childhood education learning performance data'. As a result of the experiment, higher performance indicators were confirmed in cases using the proposed method than in cases where only the classification algorithm was used in all cases.