• Journal of Korean Dental Hygiene Science
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• v.6 no.1
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• pp.13-25
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• 2023

Background: This study was conducted to confirm the service quality management of care workers, who are direct service personnel of long-term care insurance for the elderly, using unstructured big data. Methods: Using a textome, this study collected and analyzed unstructured social data related to care workers' service quality. Frequency, TF-IDF, centrality, semantic network, and CONCOR analyses were conducted on the top 50 keywords collected by crawling the data. Results: As a result of frequency analysis, the top-ranked keywords were 'Long-term care services,' 'Care workers,' 'Quality of care services,' 'Long term care,' 'Long term care facilities,' 'Enhancement,' 'Elderly,' 'Treatment,' 'Improvement,' and 'Necessity.' The results of degree centrality and eigenvector centrality were almost the same as those of the frequency analysis. As a result of the CONCOR analysis, it was found that the improvement in the quality of long-term care services, the operation of the long-term care services, the long-term care services system, and the perception of the psychological aspects of the care workers were of high concern. Conclusion: This study contributes to setting various directions for improving the service quality of care workers by presenting perceptions related to the service quality of care workers as a meaningful group.

• 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 Industrial Convergence
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• v.21 no.5
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• pp.1-13
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• 2023

Carbon neutrality is the concept of reducing greenhouse gases emitted by human activities and making actual emissions zero through removal of remaining gases. It is also called "Net-Zero" and "carbon zero". Korea has declared a "2050 Carbon Neutrality policy" to cope with the climate change crisis. Various carbon reduction legislative processes are underway. Since carbon neutrality requires changes in industrial technology, it is important to prepare a system for carbon zero. This paper aims to understand the status and trends of global carbon neutrality technology. Therefore, ROK's web platform "www.naver.com." was selected as the data collection scope. Korean online articles related to carbon neutrality were collected. Carbon neutrality technology trends were analyzed by future signal methodology and Word2Vec algorithm which is a neural network deep learning technology. As a result, technology advancement in the steel and petrochemical sectors, which are carbon over-release industries, was required. Investment feasibility in the electric vehicle sector and technology advancement were on the rise. It seems that the government's support for carbon neutrality and the creation of global technology infrastructure should be supported. In addition, it is urgent to cultivate human resources, and possible to confirm the need to prepare support policies for carbon neutrality.

• Journal of Industrial Convergence
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• v.21 no.3
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• pp.1-15
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• 2023

Expectations for wireless communication technology are rising as a base technology that promotes innovation in various industries in line with the paradigm of digital transformation in the 21st century beyond the stage of being used only for communication service itself. In this study, in order to compare 6G technological competitiveness between Korea and leading countries, technological competitiveness was confirmed through PFS, CPP, and network analysis based on GaN Integrated Circuit patent data. Korea's 6G technological competitiveness was 0.62 in PFS and 3.93 in CPP, which were 32.8% and 19.9%, respectively, compared to leading countries. In addition, as a result of network analysis, the collaboration rate in the 6G field was 7.2%, and the collaboration ecosystem was very insufficient in most countries. In contrast, it was confirmed that Korea, unlike leading countries, has established a small-scale collaboration ecosystem linked by industry and academia. Thus, it is necessary to establish a strategy for 6G communication technology at the national level so that communication technology can be advanced based on a relatively well-established collaborative ecosystem.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.36-49
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• 2022

The purpose of this study was to analyze domestic research trends related to the Baekdudaegan Mountains in the last two decades. In total, 551 academic papers and keyword data related to the Baekdudaegan Mountains were collected using the "Research and Information Service Section" and analyzed using "big data" analysis programs, such as Textom and UCINET. Papers related to the Baekdudaegan Mountains were published in 177 academic journals, and 229 papers (41.6% of all published papers) were published between 2011 and 2015. According to word frequency data (N-gram analyses), the major research topic over the past 20 years was "species diversity." According to CONCOR analysis results, the main research could be divided into 15 areas, the most important of which was "species diversity," followed by "vegetation restoration and management," and "culture." Ecological research comprised 12 groups with a frequency of 78.8%; humanities and social research comprised 2 groups with a frequency of 15.6%. Overall, our study of research areas and quantitative data analyses provides valuable information that could help establish policy formulation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.259-268
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• 2023

The purpose of this study was to verify the effectiveness of mental simulation practice training using standardized patients for nursing students. This study is a single-group pre- and post-design study, and for data collection, a structured questionnaire was provided to 95 nursing students from a university located in J. The collected data was analyzed using the SPSS/WIN 27.0 program. Results of the study The mental simulation practice training program using standardized patients improved the subject's learning motivation (t=-2.011, p=.046), learning self-efficacy (t=-2.225, p=.027), and learning satisfaction (t=-). 3.428, p=.001) and transfer motivation (t=-2.628, p=.009). In addition, as a result of analyzing the self-assessment contents by text mining, words related to mental simulation practice education using standardized patients included situation, experience, acting, communication, scenario, and mental nursing clinical practice, and words related to satisfaction were actual, There was help, response, understanding, variety, etc. As a result of this study, an environment similar to the actual situation was implemented, and the mental simulation training program applying various cases was found to be effective in practical education of nursing students, so it is necessary to actively utilize it to improve the ability to adapt to the field in the future.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.167-181
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• 2023

This study utilized TEXTOM, a social network analysis program to analyze changes in current tourism behavior after travel restrictions were eased after the outbreak of COVID-19. Data on the keywords 'domestic travel' and 'overseas travel' were collected from blogs, cafes, and news provided by Naver, Google, and Daum. The collection period was set from April to December 2022 when social distancing was lifted, and 2019 and 2020 were each set as one year and compared and analyzed with 2022. A total of 80 key words were extracted through text mining and centrality analysis was performed using NetDraw. Finally, through the CONCOR, the correlated keywords were clustered into 4. As a result of the study, tourism behavior in 2022 shows tourism recovery before the outbreak of COVID-19, segmentation of travel based on each person's preferred theme, prioritization of each country's corona mitigation policy, and then selecting a tourist destination. It is expected to provide basic data for the development of tourism marketing strategies and tourism products for the newly emerging tourism ecosystem after COVID-19.

• 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.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.95-106
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• 2023

Korean healing research has developed over the past 20 years along with the growing social interest in healing. The field of healing research is diverse and includes legislated natural-based healing. In this study, abstracts of 2,202 academic journals, master's, and doctoral dissertations published in KCI and RISS were collected and analyzed. As for the research method, LDA topic modeling used to classify research topics, and time-series publication trends were examined. As a result of the study, it identified that the topic of Korean healing research was connected with 5 types and 4 mediators. The five were "Healing Tourism," "Mind and Art Healing," "Forest Therapy," "Healing Space," and "Youth Restoration and Healing," and the four mediators were "Forest," "Nature," "Culture", and "Education". In addition, only legalized healing studies extracted from Korean healing research and the topics were analyzed. As a result, legalized healing research classified into four. The four types were "Healing Spatial Environment Plan", "Healing Therapy Experiment", "Agricultural Education Experiential Healing", and "Healing Tourism Factor". Forest Therapy, which has the largest amount of research in legalized healing, Agro Healing and Garden Healing which operate similar programs through plants, and Marine Healing using marine resources also analyzed. As a result, topics that show the unique characteristics of individual healing studies and topics that are considered universal in all healing studies derived. This study is significant in that it identified the overall trend of research on Korean healing facilities and programs by utilizing LDA topic modeling.

• Journal of Industrial Convergence
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• v.21 no.8
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• pp.23-33
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• 2023

Consumer review analysis is important for product development, customer satisfaction, competitive advantage, and effective marketing. Increased use of wireless earphones is expected to reach $45.7 billion by 2026 with growth in lifestyle. Therefore, in consideration of the growth and importance of the market, consumer reviews of wireless earphones from Apple and Samsung were analyzed. In this study, 11,320 wireless earphone reviews from Apple and Samsung sold on Coupang were collected to analyze consumers' purchase intentions and analyze consumer satisfaction through analysis of the frequency, sensitivity, and LDA topic model of text mining. As a result of topic modeling, 16 topics were derived and classified into sound quality, connection, shopping mall service, purchase intention, battery, delivery, and price. As a result of brand comparison, Samsung purchased a lot for gift purposes, had a high positive sentiment for price, and Apple had a high positive sentiment for battery, sound quality, connection, service, and delivery. The results of this study can be used as data for related industries as a result of research that can obtain improvements and insights on customer satisfaction, quality and market trends, including manufacturing, retail, marketers, and consumers.