• Journal of Korean Home Economics Education Association
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• v.35 no.2
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• pp.1-20
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• 2023

The purpose of this study is to extract and analyze ecological citizenship elements in the middle school home economics textbook used in the 2015 national curriculum for the introduction of ecological transformation education in the 2022 national curriculum. As a result of the analysis, the content analysis of the ecological citizenship factor was validated by six experts who are incumbent middle school home economics teachers, and the S-CVI value was 0.97, ensuring the validity of the ecological citizenship factor analysis. The results of analyzing 242 ecological citizenship factors extracted from home economics textbooks are as follows. According to the content area of the 2015 national home economics curriculum, the 'human development and family' area had the highest presence of ecological citizenship factors followed by the 'resource management and self-reliance' area and the 'home life and safety' area. Among the categories of ecological citizenship factors, 'value⋅attitude' was the most frequent, followed by 'process⋅function' and 'knowledge⋅understanding'. For each textbook composition system, ecological citizenship elements were extracted in the order of pictures, text, activities, and supplementary materials. There was a significant variation in the number of ecological citizenship factors among publishers, indicating the importance of the textbook writers' perception, interpretation, and direction of writing. Based on these analysis results, ecological citizenship teaching and learning activities applicable to home economics education were presented. This study highlights the potential for practicing ecological citizenship education in line with the new orientation of the curriculum on ecological transformation education through home economics education. Furthermore, it provides valuable baseline data for the development and implementation of textbooks for the 2022 national curriculum.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.19-26
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• 2023

In this study, the public sensitivity of the 'MZ generation' was examined through the social media big data sensitivity analysis method. For the analysis, the consumer account SNS text was examined, and positive and negative emotional factors were presented by classifying external sensibilities and emotions of the MZ generation. In conclusion, the positive emotions of liking and interest in relation to the "MZ generation" were 72.1%, higher than the negative emotional ratio of 27.9%. In positive sensitivity, the older generation showed 'a favorable feeling for the individuality and dignifiedness of the MZ generation' and 'interest in the MZ generation with new values'. In contrast, the MZ generation has a favorable feeling for 'the fact that they are a generation of their own boldness, youthfulness and individuality' and 'small growthism'. Negative sensitivity outside the MZ generation was found to be 'A concern about the marriage avoidance, employment difficulties, debt investment, and resignation trends of the MZ generation', 'Hate the MZ generation who treats Kkondae' and 'Difficult to talk to the MZ generation'. On the other hand, the negative emotions felt by the MZ generation itself were 'Rejection of generalization', 'Rejection of generation and gender conflicts', 'Rejection of competition worse than the older generation', 'Relative failure of the rich era', and 'Sadness to live in a predicted climate disaster'. Therefore, the older generation should not look at the MZ generation in general, but as individuals, and should alleviate conflicts with intergenerational understanding and empathy. there is a need for community consideration to solve generational conflicts, gender conflicts, and environmental problems.

• Informatization Policy
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• v.30 no.1
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• pp.41-66
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• 2023

This study aims to reveal the direction of municipal ordinances for smart cities, while focusing on 74 municipal ordinances from 72 municipal governments through topic modeling. As a result, the main keywords that show a high frequency belong to establishment and operations of the Smart City Committee. From the result of topic modeling Latent Dirichlet Allocation(LDA), it classifies municipal ordinances for smart cities into eight topics as follows: Topic 1(security for process of smart cities), Topic 2(promotion of smart city industry), Topic 3(composition of a smart city consultative body for local residents), Topic 4(support system for smart cities), Topic 5(management for personal information), Topic 6(use of smart city data), Topic 7(implementation for intelligent public administration), and Topic 8(smart city promotion). As for topic categorization by region, Topics 5, 6, and 8 which are mostly related to the practical operation of smart cities have a significant portion of municipal ordinances for smart cities in the Seoul metropolitan area. Then, Topics 2, 3, and 4 which are mostly related to the initial implementation of smart cities have a significant portion of municipal ordinances for smart cities in provincial areas.

• Journal of Science Education
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• v.46 no.2
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• pp.178-194
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• 2022

This study analyzes the trend of domestic research related to science writing education. The subjects of analysis were 152 research papers related to science writing education in Korea from 2004 to 2021. The analysis criteria were set as the research problem, research subject, research method and research application etc. Result of the analysis shows a steady increase until 2014, but decreased afterwards. In the result of the research problems, it was found that most studies were about finding out the effects of scientific writing activities. The research subjects were mostly elementary, middle, and high school students. Qualitative research occupied a large proportion in the results of the research method analysis, and there were many mixed studies that combined quantitative and qualitative research. As for the research application method, the most applied research in regular classes. As a result of analyzing the effect of application, most of the studies were on science concepts, attitudes towards science, thinking skills, and creative problem-solving skills. Writing education such as experimental and observational writing in science classes has been steadily conducted since before the introduction of the 2007 revised curriculum. In particular, the importance of scientific writing as a text-based education is being emphasized from the 2007 revised curriculum to the 2022 revised curriculum overview. Writing is an important learning strategy in science education for students to generate, share, explain, and expand their ideas. Therefore, examining domestic research trends related to science writing education can provide important basic data for setting the future direction of science writing education.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.197-216
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• 2022

With the development of Internet and mobile technology and the spread of social media, a large amount of information is being generated and distributed online. Some of them are useful information for the public, but others are misleading information. The misleading information, so-called 'fake news', has been causing great harm to our society in recent years. Since the global spread of COVID-19 in 2020, much of fake news has been distributed online. Unlike other fake news, fake news related to COVID-19 can threaten people's health and even their lives. Therefore, intelligent technology that automatically detects and prevents fake news related to COVID-19 is a meaningful research topic to improve social health. Fake news related to COVID-19 has spread rapidly through social media, however, there have been few studies in Korea that proposed intelligent fake news detection using the information about how the fake news spreads through social media. Under this background, we propose a novel model that uses Graph2vec, one of the graph embedding methods, to effectively detect fake news related to COVID-19. The mainstream approaches of fake news detection have focused on news content, i.e., characteristics of the text, but the proposed model in this study can exploit information transmission relationships in social engagement networks when detecting fake news related to COVID-19. Experiments using a real-world data set have shown that our proposed model outperforms traditional models from the perspectives of prediction accuracy.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.97-103
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• 2022

An aircraft component can only be mounted on an aircraft if it has been certified to have a structural robustness under flight load conditions. Among the major components of the aircraft, a pylon is a structure that connects external equipment such as an engine, and external attachments with the main wing of an aircraft and transmits the loads acting on it to the main structure of the aircraft. In civil aircraft, when there is an incident of fire in the engine area, the pylon prevents the fire from spreading to the wings. This study presents the results of structural static tests performed to verify the structural robustness of a fuel pylon used to mount external fuel tank in an aircraft. In the main text, we present the test set-up diagram consisting of test fixture, hydraulic pressure unit, load control system, and data acquisition equipment used in the structure static test of the fuel pylon. In addition, we introduce the software that controls the load actuator, and provide a test profile for each test load condition. As a result of the structural static test, it was found that the load actuator was properly controlled within the allowable error range in each test, and the reliability of the numerical analysis was verified by comparing the numerical analysis results and the strain obtained from the structural test at the main positions of the test specimen. In conclusion, it was proved that the fuel pylon covered in this study has sufficient structural strength for the required load conditions through structural static tests.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.299-314
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• 2017

Technological advances in media have expanded users' consciousness. At the same time, users have changed from passive into active voice by interacting media. The emergence of mobile made different structures and contents compared to the past. Especially, Korean culture of mobile converted original media channels to contents in a category. Plus, the usage structure of internet of this time converges in massive portal sites. It is because that the structure has aspect of emitting through remediation in the sites. Also, Korean massive portal sites have provided specific service named 'real-time issues'. This is not only the unique way of offering information that exists in Korea but also high usability of getting issues. We therefore considered the meaning of durability of real-time issues in the view of journalism, compared original media channels. Then, this paper identified the user attributes for acquisition of information following ways using informal and formal data from Korean massive portal sites named 'Daum' and 'Naver'.

• 한국체육학회지인문사회과학편
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• v.57 no.3
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• pp.117-133
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• 2018

The purpose of this study was to explore integrated approaches to physical education in general education by examining methodology of physical education aiming for convergence education. This case study was conducted, using a qualitative approach during March, 2017 to November, 2017. Data were collected through non-participant observation, in-depth interviews, field-notes, students' journal, syllabus and lecture materials. The key findings are as follows: First, "Emotion Coaching through Movement" is a course of 'understanding of body' approaching integrated humanities science and natural science. Second, it is a convergence education, conducting 'text to daily practice' by approaching positive psychology and neurophysiology. Third, it is a physical education with 'integrated theory and practice' in higher education. These results indicate that students can understand their own body, observe their daily and fixed movement or reaction pattern, and enhance the ability of understanding others through a physical education in general education.

• The Journal of Bigdata
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• v.6 no.2
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• pp.151-159
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• 2021

Construction of a blockchain network needs a cumbersome and time consuming activity. To overcome these limitations, global IT companies such as Microsoft are providing cloud-based blockchain services. In this paper, we propose a blockchain-based construction and management tool that enables blockchain developers, blockchain operators, and enterprises to deploy blockchain more comfortably in their infrastructure. This tool is implemented using Hyperledger Fabric, one of the famous private blockchain platforms, and Ansible, an open-source IT automation engine that supports network-wide deployment. Instead of complex and repetitive text commands, the tool provides a user-friendly web dashboard interface that allows users to seamlessly set up, deploy and interact with a blockchain network. With this proposed solution, blockchain developers, operators, and blockchain researchers can more easily build blockchain infrastructure, saving time and cost. To verify the usefulness and convenience of the proposed tool, a blockchain network that conducts electronic voting was built and tested. The construction of a blockchain network, which consists of writing more than 10 setting files and executing commands over hundreds of lines, can be replaced with simple input and click operations in the graphical user interface, saving user convenience and time. The proposed blockchain tool will be used to build trust data infrastructure in various fields such as food safety supply chain construction in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.166-178
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• 2023

This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.