• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.27-35
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• 2021

With the development of the Internet, various IT technologies such as IoT, Cloud, etc. have been developed, and various systems have been built in countries and companies. Because these systems generate and share vast amounts of data, they needed a variety of systems that could detect threats to protect the critical data contained in the system, which has been actively studied to date. Typical techniques include anomaly detection and misuse detection, and these techniques detect threats that are known or exhibit behavior different from normal. However, as IT technology advances, so do technologies that threaten systems, and these methods of detection. Advanced Persistent Threat (APT) attacks national or companies systems to steal important information and perform attacks such as system down. These threats apply previously unknown malware and attack technologies. Therefore, in this paper, we propose a hybrid intrusion detection system that combines anomaly detection and misuse detection to detect unknown threats. Two detection techniques have been applied to enable the detection of known and unknown threats, and by applying machine learning, more accurate threat detection is possible. In misuse detection, we applied Classification based on Association Rule(CBA) to generate rules for known threats, and in anomaly detection, we used One-Class SVM(OCSVM) to detect unknown threats. Experiments show that unknown threat detection accuracy is about 94%, and we confirm that unknown threats can be detected.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.336-344
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• 2021

The purpose of this study was to identify the self-awareness of smartphone dependence among undergraduate students and their response to the same. The data was drawn from a survey on smartphone overdependence conducted by the Ministry of Science and information and communications technology (ICT) and the National Information Society Agency in 2017. The responses of 1,735 undergraduate students were analyzed by frequency, percentage, mean, standard deviation, minimum-maximum value, ��2-test, independent t-test, Pearson's correlation coefficient, and stepwise multiple regression analysis. The results indicated that 22.3% of participants were at risk of smartphone dependence, and 63.6% of them were unaware of their dependence on smartphones. The perception of smartphone dependence was significantly associated with a higher risk of smartphone dependence (��=.35, p=.000) and the increasing use of applications such as games (��=.19, p=.000), television/video (��=.11, p=.000), and learning (��=.11, p=.000). Of the participants with dependence awareness, only a few knew about the existence of centers to prevent smartphone and internet dependence. Moreover, they rarely utilized these centers. However, the participants felt the need for more counseling agencies (26.8%), programs for dealing with oneself (23.2%), information about smartphone dependence (14.9%), and help to overcome dependence (10.9%). These findings show the need to establish public services so that students can easily access correct information on smartphone dependence and address this problem.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.734-751
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• 2021

The purpose of this study is to prepare basic data to reflect polar literacy education in the school curriculum. The perception about the polar regions, teaching experience, and polar-related cognitive and affective characteristics of teachers were investigated. The survey was conducted among 56 elementary, middle, and high school teachers from schools from 10 major cities and surrounding regions, based on their perceptions of the polar region, current teaching status, polar knowledge, and beliefs and attitudes toward polar region and climate change. Results showed that although teachers' polar information efficacy was low, they positively evaluated the status of educators in resolving polar and climate change problems, and prioritized global citizenship values over practical purposes. The experience of teaching polar region and climate change issues at schools varied across subjects and non-subjects, but showed a passive aspect in teaching development, such as wanting to be provided with consolidated learning materials. On the cognitive aspect, teachers revealed an ambiguous understanding of the mechanisms and processes by which polar change and climate influence each other. On the affective aspect, most teachers showed strong beliefs and attitudes for polar-related issues beyond the school level, but their behavior choices were relatively lower. Based on the results, we propose the following as recommendations: providing opportunities and materials to promote polar knowledge, discovering educational materials in various contexts to form values and attitudes, developing educational materials from polar research materials, identifying misconceptions about polar knowledge among students and teachers, strengthening elementary school teachers' polar literacy, and cultivating positive attitudes and values toward polar issues.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.29-41
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• 2022

As one of the alternatives to solve the problem of unstable food supply and demand imbalance caused by abnormal climate change, the need for plant factories is increasing. Airflow in plant factory is recognized as one of important factor of plant which influence transpiration and heat transfer. On the other hand, Digital Twin (DT) is getting attention as a means of providing various services that are impossible only with the real system by replicating the real system in the virtual world. This study aimed to develop a digital twin model for airflow prediction that can predict airflow in various situations by applying the concept of digital twin to a plant factory in operation. To this end, first, the mathematical formalism of the digital twin model for airflow analysis in plant factories is presented, and based on this, the information necessary for airflow prediction modeling of a plant factory in operation is specified. Then, the shape of the plant factory is implemented in CAD and the DT model is developed by combining the computational fluid dynamics (CFD) components for airflow behavior analysis. Finally, the DT model for high-accuracy airflow prediction is completed through the validation of the model and the machine learning-based calibration process by comparing the simulation analysis result of the DT model with the actual airflow value collected from the plant factory.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.161-183
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• 2022

Opinion polls have become a powerful means for election campaigns and one of the most important subjects in the media in that they predict the actual election results and influence people's voting behavior. However, the more active the polls, the more often they fail to properly reflect the voters' minds in measuring the effectiveness of election campaigns, such as repeatedly conducting polls on the likelihood of winning or support rather than verifying the pledges and policies of candidates. Even if the poor predictions of the election results of the polls have undermined the authority of the press, people cannot easily let go of their interest in polls because there is no clear alternative to answer the instinctive question of which candidate will ultimately win. In this regard, we attempt to retrospectively grasp public opinion on the 20th presidential election by applying the 'YouTube Analysis' function of Sometrend, which provides an environment for discovering insights through online big data. Through this study, it is confirmed that a result close to the actual public opinion (or opinion poll results) can be easily derived with simple YouTube data results, and a high-performance public opinion prediction model can be built.

• Journal of The Korean Association For Science Education
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• v.42 no.6
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• pp.579-595
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• 2022

This study is a qualitative case study of secondary science teachers who are doing educational activities in YouTube. In particular, this study attempts to interpret this case based on Foucault's concept of 'Heterotopia', which means a space that allows for private freedom or deviance by reflecting various utopias without the norms and constraints from every day or real space. Five secondary science teachers who voluntarily opened a personal channel on the YouTube platform and actively uploaded their own videos related to science education participated in the study. In order to understand the experiences of five secondary science teachers, data were individually collected through semi-structured in-depth interviews, and the collected data were analyzed using qualitative case study method. For valid interpretation of the study, we also referred to the video contents, teacher training materials, and teaching and learning materials produced by the participants. As a result of the study, seven themes were revealed: 'Desire for one's own unique educational activities,' 'Youtube as an extended classroom space,' 'Expanded network of relationships beyond the classroom barrier,' 'Satisfaction of desire for recognition and experience of identity as a YouTuber,' 'Tension between the educational space and the YouTube,' 'Space to be reborn as a craftsman,' and 'Finding one's own direction as a Teacher-YouTuber.' Given those findings, we found that the identity and desire of secondary science teachers, which were limited in the existing secondary schools and classrooms, was expanded in a new space called YouTube. In addition, we suggested that YouTube could be a space where science teachers can realize their own ideals and feel the joy. And simple regulating teacher's behavior in Youtube space only based on norms and standards shared in traditional educational space would rather hinder their healthy construction of identity and growth.

• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.1-13
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• 2021

The purpose of this study is to identify trends and potential themes of research on consumption of children and adolescents for 20 years by analyzing keywords. The keywords of 869 studies on consumption of children and adolescents published in journals listed in Korean Citation Index were analyzed using text mining techniques. The most frequent keywords were found in the order of youth, youth consumers, consumer education, conspicuous consumption, consumption behavior, and character. As a result of analyzing the frequency of keywords by dividing into five-year periods, it was confirmed that the frequency of consumer education was significantly higher betwn 2006 and 2010. Research on ethical consumption has been active since 2011, and research has been conducted on various topics instead of without a prominent keyword during the most recent 5-year period. Looking at the keywords based on the TF-IDF, the keywords related to the environment and the Internet were the main keywords between 2001 and 2005. From 2006 to 2010, the TF-IDF values of media use, advertisement education, and Internet items were high. From 2011 to 2015, fair trade, green growth, green consumption, North Korean defector youths, social media, and from 2016 to 2020, text mining, sustainable development education, maker education, and the 2015 revised curriculum appeared as important themes. As a result of topic modeling, eight topics were derived: consumer education, mass media/peer culture, rational consumption, Hallyu/cultural industry, consumer competency, economic education, teaching and learning method, and eco-friendly/ethical consumption. As a result of network analysis, it was found that conspicuous consumption and consumer education are important topics in consumption research of children and adolescents.

• Knowledge Management Research
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• v.23 no.1
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• pp.89-109
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• 2022

Due to COVID-19 and soaring participation of individual investors, large-scale transactions exceeding system capacity limits have been reported frequently in the capital market. The capital market IT systems, which the impact of system failure is very critical, have encountered unexpectedly tremendous transactions in 2020, resulting in a sharp increase in system failures. Despite the fact that many companies maintained large-scale system capacity planning policies, recent transaction influx suggests that a new approach to capacity planning is required. Therefore, this study developed capital market IT system capacity planning models using machine learning techniques and analyzed those performances. In addition, the performance of the best proposed model was improved by using sentiment index that can promptly reflect the behavior of investors. The model uses empirical data including the COVID-19 period, and has high performance and stability that can be used in practice. In practical significance, this study maximizes the cost-efficiency of a company, but also presents optimal parameters in consideration of the practical constraints involved in changing the system. Additionally, by proving that the sentiment index can be used as a major variable in system capacity planning, it shows that the sentiment index can be actively used for various other forecasting demands.

• Journal of Music and Human Behavior
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• v.20 no.1
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• pp.47-74
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• 2023

The purpose of this study was to develop a music teacher training program for global citizenship education and explore its effects on the participants' capacity for global citizenship. The program focused on multicultural education, including diversity and tolerance, among various topics in global citizenship education and consisted of practice to develop lesson plans for middle school music classes as well as theory about music in diverse sociocultural environments. The results showed that this program positively affected the participants' attitudes about a music teacher's role in the multicultural classroom. This program enabled participants to identify and reflect on any prejudice they may have against diversity and multiculturalism and to consider the role of music teachers in multicultural learning environments. The program also helped the participants develop greater self-efficacy as music teachers in multicultural environments and see music as a symbolic expression and a social and cultural product. Finally, the participants showed their positive attitude toward transformative pedagogy and considered various topics in global citizenship education beyond diversity and multiculturalism through multilateral understanding and exploration about music based on theory and practice in global citizenship education.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.178-193
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• 2023

The aim of this study was to investigate differences in the achievement standards from the 2015 to the 2022 revised national science curriculum and to present the implications for science teaching under the revised curriculum. Achievement standards relevant to primary science education were therefore extracted from the national curriculum documents; conceptual domains in the two curricula were analyzed for differences; various kinds of centrality were computed; and the Louvain algorithm was used to identify clusters. These methods revealed that, in the revised compared with the preceding curriculum, the total number of nodes and links had increased, while the number of achievement standards had decreased by 10 percent. In the revised curriculum, keywords relevant to procedural skills and behavior received more emphasis and were connected to collaborative learning and digital literacy. Observation, survey, and explanation remained important, but varied in application across the fields of science. Clustering revealed that the number of categories in each field of science remained mostly unchanged in the revised compared with the previous curriculum, but that each category highlighted different skills or behaviors. Based on those findings, some implications for science instruction in the classroom are discussed.