• Journal of the Korean earth science society
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• v.43 no.1
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• pp.224-235
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• 2022

This study aimed to confirm the status of media reports on space hazards using topic modeling analysis of media articles that are related to space hazards for the past 12 years. Therefore, Latent Dirichlet Allocation (LDA) analysis was performed by collecting over 1200 space hazards articles between 2010 and 2021 on solar storm, artificial space objects, and natural space objects from BIGKins news platform. The articles related to solar storm focused on three topics: the effect of solar explosion on satellites; effect of solar explosion on radio communication in Korea, centered on the Korean Space Weather Center; and relationship between aircrew and space radiation. The articles related to artificial space objects focused on three topics: the threat of space garbage to satellite and space stations and the transition of useful objects into space junk; the relationship between space garbage and humanity as shown in movies; and the effort of developed countries for tracking, monitoring, and disposing of space garbage. The articles related to natural space objects focused on two topics: International Space Agency's tracking and monitoring of near-Earth asteroids and the countermeasures of collisions, and the evolution and extinction of dinosaurs and mammals, with a focus on the collisions of asteroids or comets. Therefore, this study confirmed that domestic media play a role in conveying dangers of space hazards and arousing the attention of public using a total of eight themes in various fields such as society and culture, and derived education method and policy on space hazards.

• Journal of Korean Home Economics Education Association
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• v.34 no.2
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• pp.1-19
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• 2022

The purpose of this study is to analyze the keywords of the middle school textbooks based on the 2015 revision of the technology and home economics curriculum to understand the core concepts and contents composition of the 'housing' unit. Using TEXTOM and UCINET programs, the frequencies and centralities of the keywords were analyzed, and CONCOR analysis was performed. The results are as follows. First, the content system of the 'housing' unit is divided into 'life culture' and 'safety' in the 'family life and safety' area. Second, in the 'safety' section, the frequencies of occurrence of the words were high in the order of indoor, occurrence, use, noise, and safety accidents, in the order of frequency of occurrence. It was confirmed that words related to daily life, safety accidents, and prevention were closely connected to each other. In the 'life culture' section, the frequencies of occurrence were high in the order of space, housing, family, and residential space, and the correlations between these keywords were also high. Third, the most influential core keywords were, indoor and occurrence in the 'safety' section, and space, family, and housing, in the 'life culture' section. Fourth, the 'safety' section were divided into two subunits, 'safe living environment' and 'comfortable living environment', and the 'life culture' section were divided into four subunits, 'living space composition', 'space utilization', 'housing value and lifestyle', and 'housing culture'.

• Journal of The Korean Association For Science Education
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• v.42 no.4
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• pp.429-438
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• 2022

In this study, we propose a way to improve science teacher expertise through infographics creation teacher training program by analyzing the infographics types focusing on the Earth Science subject of the 2015 revised curriculum, and inspecting the teachers' utilization of graphic tools. The data visualization characteristics of Earth Science textbooks were analyzed, the execution results of the infographics creation teacher training program were presented, and a survey on science teachers' change in perception and competency of infographics. As a result of the Earth Science textbook analysis, diagram-type, map-type, and comparative analysis-type infographics were frequently used, and were mainly presented as text-assisted-type infographics. The infographics creation teacher training program was conducted five times for 112 science teachers to create the complete, text-assisted, incomplete, and gradient-type infographics. Incomplete infographics for development of evaluation questions were most needed. Although many science teachers recognize the importance of infographics, they lacked the competency to create high-quality infographics because there were no training opportunities for infographics creation. After completing the training, 74.1% of teachers felt that the quality of developments of supplementary textbooks and evaluation questions had improved, and answered that it was helpful in re-educating knowledge and improving teaching-learning methods. Based on the research results, ways to improve science teacher expertise through infographics creation teacher training program were suggested.

• Journal of Korean Library and Information Science Society
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• v.54 no.1
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• pp.143-165
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• 2023

This study aims to propose a scaffolding strategy that can be applied to the information search process by using Kuhlthau's ISP model, which presented a design and implementation strategy for the mediation role in the learning process. To this end, the relevant literature was reviewed to categorize scaffolding strategies, and impressions were collected from the students surveys after providing 150 middle school students in the Daejeon area with the project class to which the scaffolding strategy based on the ISP model was applied. The collected data were processed into a form suitable for analysis through data preprocessing for word frequencies to be extracted, and topic analysis was performed using STM (Structural Topic Modeling). First, after determining the optimal number of topics and extracting topics for each stage of the ISP model, the extracted topics were classified into three types: cognitive domain-macro perspective, cognitive domain-micro perspective, and emotional domain perspective. In this process, we focused on cognitive verbs and emotional verbs among words extracted through text mining, and presented a scaffolding strategy model related to each topic by reviewing representative document cases. Based on the results of this study, if an appropriate scaffolding strategy is provided at the ISP model stage, a positive effect on learners' self-directed task solving can be expected.

• Journal of Korean Library and Information Science Society
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• v.53 no.4
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• pp.233-266
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• 2022

The purpose of this study is to derive and propose agenda to improve the quality of minority services provided by regional cental libraries at the present time when information gap is deepening. First, text mining and topic modeling were conducted on 144 studies in the field of library and information science that dealt with minorities, and the discussions surrounding minorities in the domestic library world were examined in detail. Next, the current status of services for minorities in Regional central libraries were examined in detail, and tasks requiring discussion were sought in planning and operation of services for minorities in Regional central libraries. To this end, interviews were conducted with practitioners, in charge of services for minorities at Regional central libraries. Specifically, 1) awareness of minorities by practitioners, 2) current status of minority services, and 3) responsibility and role of Regional central libraries for planning and operating minority services and necessary support were analyzed. Based on the analysis results, the following tasks were derived. 1) Recategorization of minority groups, 2) Establishment of reference resource, 3) Reinforcement of education, and 4) Cooperation support between regional representative libraries and local public libraries were derived and suggested.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.21-30
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• 2023

The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.425-433
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• 2023

In this study, we developed a virtual artist play lesson model using gamification concepts and AI-generated art programs to foster creative thinking in freshman art majors. Targeting first-year students in the Digital Media Art Department at Sichuan Film & Television University in China, this course aims to alleviate fear of artistic creation and enhance problem-solving abilities. The educational model consists of four stages: persona creation, creative writing, text visualization, and virtual exhibitions. Through persona creation, students established their artist identities, and by introducing game-like elements into writing experiences, they discovered their latent creativity. Using AI-generated art programs for text visualization, students gained confidence in their creations, and in the virtual exhibitions, they were able to enhance their self-esteem as artists by appreciating and evaluating each other's works. This educational model offers a new approach to promoting creative thinking and problem-solving skills while increasing learner engagement and interest. Based on these research findings, we expect that by developing and implementing educational strategies that cultivate creative thinking, more students will grow their artistic capacities and creativity, benefiting not only art majors but also students from various fields.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.261-282
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• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.97-109
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• 2024

In the field of domestic tourism, tourism trend analysis of tourism consumers, both international tourists and domestic tourists, is essential not only for the Korean tourism market but also for local and governmental tourism policy makers. e will explore the keywords and sentiment analysis on social media to establish a marketing strategy plan and revitalize the domestic tourism industry through communication and information from tourism consumers. This study utilized TEXTOM 6.0 to analyze recent trends in Korean tourism. Data was collected from September 31, 2022, to August 31, 2023, using 'Korean tourism' and 'domestic tourism' as keywords, targeting blogs, cafes, and news provided by Naver, Daum, and Google. Through text mining, 100 key words and TF-IDF were extracted in order of frequency, and then CONCOR analysis and sentiment analysis were conducted. For Korean tourism keywords, words related to tourist destinations, travel companions and behaviors, tourism motivations and experiences, accommodation types, tourist information, and emotional connections ranked high. The results of the CONCOR analysis were categorized into five clusters related to tourist destinations, tourist information, tourist activities/experiences, tourism motivation/content, and inbound related. Finally, the sentiment analysis showed a high level of positive documents and vocabulary. This study analyzes the rapidly changing trends of Korean tourism through text mining on Korean tourism and is expected to provide meaningful data to promote domestic tourism not only for Koreans but also for foreigners visiting Korea.

• Journal of the Korean Society of Radiology
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• v.84 no.3
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• pp.653-662
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• 2023

Purpose This study aimed to determine the incremental value of using a structured report (SR) for US examinations of the pediatric appendix. Materials and Methods Between January 2009 and June 2016, 1150 pediatric patients with suspected appendicitis who underwent US examinations of the appendix were included retrospectively. In November 2012, we developed a five-point scale SR for appendix US examinations. The patients were divided into two groups according to the form of the US report: free-text or SR. The primary clinical outcomes were compared between the two groups, including the rate of CT imaging following US examinations, the negative appendectomy rate (NAR), and the appendiceal perforation rate (PR). Results In total, 550 patients were included in the free-text group and 600 patients in the SR group. The rate of additional CT examinations decreased by 5.3% in the SR group (8.2%, p = 0.003), and the NAR decreased by 8.4% in the SR group (7.8%, p = 0.028). There was no statistical difference in the appendiceal PR (37.6% vs. 48.0%, p = 0.078). Conclusion The use of an SR to evaluate US examinations for suspected pediatric appendicitis results in lower CT use and fewer negative appendectomies without an increase in appendiceal PR.