• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.301-313
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• 2021

This study was conducted on 253 artists for a month from April 19, 2020 to study the influence and countermeasures of COVID-19. The analysis results are as follows. First, as a result of frequency analysis, the timing of the occurrence of COVID-19 and the period of the decrease in artist's artistic activities were consistent, and the subjective socioeconomic level perceived by the artist was degraded from COVID-19. Second, as a result of the multivariate variance analysis, the income level and employment environment of artists affected the variables associated with COVID-19. Third, as a result of the hierarchical analysis analysis, the income level and the socioeconomic level changes due to COVID-19, and concerns about COVID-19 infections, have been shown to have had a significant impact on the level of stress felt by artists. Fourth, as a result of qualitative research, the artist reported that he was experiencing economic and psychological difficulties due to the influence of COVID-19, and emphasized the need for policy support as a way to cope with them. We hope that the results of this study will be used as empirical data in the process of developing support systems and programs for artists experiencing economic constraints and social alienation due to COVID-19.

• Journal of the Korean Society for information Management
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• v.38 no.1
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• pp.53-69
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• 2021

This study aims to understand the research landscape of South Korea using the data of 2020 Google Scholar Metrics. To achieve the goal, we constructed and analyzed four types of networks including the university collaboration network, the keyword co-occurrence network, the journal citation network, and the discipline citation network. Through the analysis of the university collaboration network, we found major universities such as Seoul National University, Keimyung University, and Sungkyunkwan University that have led collaborative research. Job related keywords such as job change intention and job satisfaction have been frequently studied with other keywords. Through the analysis of the journal citation network, we found multiple journals such as The Journal of the Korea Contents Association, Korean Journal of Sociology, and Korean Journal of Culture and Social Issues that have been widely cited by the other journals and influenced them. Finally, Education, Business administration, and Social welfare were identified as the top influential disciplines that have influenced other disciplines through the knowledge diffusion. The study is the first of its kind to use the data of Google Scholar Metrics and conduct a stepwise network analysis (e.g., keyword, journal, and discipline) to broadly understand the research landscape of South Korea. Our results can be used by government agencies and universities to develop effective strategies of promoting university collaboration and interdisciplinary research.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.22-28
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• 2021

This is a basic study on the development of deep learning-based algorithms to detect smoke before the smoke detector operates in the event of a ship fire, analyze and utilize the detected data, and support fire suppression and evacuation activities by predicting the spread of smoke before it spreads to remote areas. Proposed algorithms were reviewed in accordance with the following procedures. As a first step, smoke images obtained through fire simulation were applied to the YOLO (You Only Look Once) model, which is a deep learning-based object detection algorithm. The mean average precision (mAP) of the trained YOLO model was measured to be 98.71%, and smoke was detected at a processing speed of 9 frames per second (FPS). The second step was to estimate the spread of smoke using the coordinates of the boundary box, from which was utilized to extract the smoke geometry from YOLO. This smoke geometry was then applied to the time series prediction algorithm, long short-term memory (LSTM). As a result, smoke spread data obtained from the coordinates of the boundary box between the estimated fire occurrence and 30 s were entered into the LSTM learning model to predict smoke spread data from 31 s to 90 s in the smoke image of a fast fire obtained from fire simulation. The average square root error between the estimated spread of smoke and its predicted value was 2.74.

• Atmosphere
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• v.31 no.5
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• pp.577-592
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• 2021

This study evaluates the predictability of the number of days of heat and cold damages by growth stages of rice in South Korea using the hindcast data (1986~2020) produced by Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF) model chain. The predictability is accessed in terms of Root Mean Square Error (RMSE), Normalized Standardized Deviations (NSD), Hit Rate (HR) and Heidke Skill Score (HSS). For the purpose, the model predictability to produce the daily maximum and minimum temperatures, which are the variables used to define heat and cold damages for rice, are evaluated first. The result shows that most of the predictions starting the initial conditions from January to May (01RUN to 05RUN) have reasonable predictability, although it varies to some extent depending on the month at which integration starts. In particular, the ensemble average of 01RUN to 05RUN with equal weighting (ENS) has more reasonable predictability (RMSE is in the range of 1.2~2.6℃ and NSD is about 1.0) than individual RUNs. Accordingly, the regional patterns and characteristics of the predicted damages for rice due to excessive high- and low-temperatures are well captured by the model chain when compared with observation, particularly in regions where the damages occur frequently, in spite that hindcasted data somewhat overestimate the damages in terms of number of occurrence days. In ENS, the HR and HSS for heat (cold) damages in rice is in the ranges of 0.44~0.84 and 0.05~0.13 (0.58~0.81 and -0.01~0.10) by growth stage. Overall, it is concluded that the PNU CGCM-WRF chain of 01RUN~05RUN and ENS has reasonable capability to predict the heat and cold damages for rice in South Korea.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.41-48
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• 2022

This study tried to empirically explore which issues related to the social service agency for public(as below SSA), that is, social perceptions were formed, by using mess media related to the SSA. This study is meaningful in that it identifies the overall social perception and trend of SSA through public opinion. In order to extract media trend data, the search used the big data analysis system, Textom, to collect data from the representative portals Naver News and Daum News. The collected texts were 1,299 in 2020 and 1,410 in 2021, for a total of 2,709. As a result of the analysis, first, the most derived words in relation to the frequency of text appearance were 'SSA', 'establishment', and 'operation'. Second, as a result of the N-gram analysis, the pairs of words directly related to the SSA 'SSA and public', 'SSA and opening', 'SSA and launch', and 'SSA and Department Director', 'SSA and Staff', 'SSA and Caregiver' etc. Third, in the results of TF-IDF analysis and word network analysis, similar to the word occurrence frequency and N-gram results, 'establishment', 'operation', 'public', 'launch', 'provided', 'opened', ' 'Holding' and 'Care' were derived. Based on the above analysis results, it was suggested to strengthen the emergency care support group, to commercialize it in detail, and to stabilize jobs.

• Research in Plant Disease
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• v.27 no.4
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• pp.180-186
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• 2021

Typical bacterial symptoms, water-soaking brown and black leaf spots with yellow halo, were observed on watermelon seedlings in nursery and field of Gyeongnam and Jeonnam provinces. Bacterial isolates from the lesion showed strong pathogenicity on watermelon and zucchini. One of them was rod-shaped with 4 polar flagella by observation of transmission electron microscopy. They belonged to LOPAT group 1. The phylogenical trees with nucleotide sequences of 16S rRNA and multi-locus sequencing typing with the 4 house-keeping genes (gapA, gltA, gyrB, and rpoD) of the isolates showed they were highly homologous to Pseudomonas syringae pv. syringae and grouped together with them, indicating that they were appeared as P. syringae genomospecies group 1. Morphological, physiological, and genetical characteristics of the isolates suggested they are P. syringae pv. syringae. We believe this is the first report that P. syringae pv. syringae caused leaf spot disease on watermelon in the Republic of Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.549-566
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• 2022

Recently, artificial intelligence (AI) technology has progressed rapidly, and industries using this technology are significantly increasing. Further, analysis research using text mining, which is an application of artificial intelligence, is being actively developed in the field of social science research. About 125 laws, including joint laws, have been enacted under the Ministry of Oceans and Fisheries in various sectors including marine environment, fisheries, ships, fishing villages, ports, etc. Research on the laws under the Ministry of Oceans and Fisheries has been progressively conducted, and is steadily increasing quantitatively. In this study, the domestic research trends were analyzed through text mining, targeting the research papers related to laws of the Ministry of Oceans and Fisheries. As part of this research method, first, topic modeling which is a type of text mining was performed to identify potential topics. Second, co-occurrence network analysis was performed, focusing on the keywords in the research papers dealing with specific laws to derive the key themes covered. Finally, author network analysis was performed to explore social networks among authors. The results showed that key topics have been changed by period, and subjects were explored by targeting Ship Safety Law, Marine Environment Management Law, Fisheries Law, etc. Furthermore, in this study, core researchers were selected based on author network analysis, and the tendency for joint research performed by authors was identified. Through this study, changes in the topics for research related to the laws of the Ministry of Oceans and Fisheries were identified up to date, and it is expected that future research topics will be further diversified, and there will be growth of quantitative and qualitative research in the field of oceans and fisheries.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.115-124
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• 2022

The purpose of this study is to analyze and present keywords, trends, and language networks of keywords for each year of the pedagogical exam of the secondary teacher's employment exam for the 2019~2022 school year. The main research methods were text mining technique and language network analysis method, and analysis programs were KrKwic, Wordcloud Maker, Ucinet6, NetDraw, etc. The research results are as follows; First, keywords such as teacher, student, curriculum, class, and evaluation appeared in the top rankings, and keywords (online, wiki, discussion ceremony, information, etc.) that reflect the recent online class progress in the current COVID-19 situation also tended to appear. The keywords with high frequency of occurrence in the four-year integrated text were student(44), teacher(39), class(27), school(18), curriculum(16), online(10), and discussion method(8). Second, the overall language network of the keywords with high frequency of 4 years showed a significant level of density(0.566), total number of links(492), and average degree of links(16.4). The degree centrality was found in the order of teacher(199.0), class(197.0), student(185.0), and school(150.0). Betweenness centrality was found in the order of teacher(30.859), class(18.956), student(16.054), and school (15.745). It is expected that the results of this study will serve as data to be considered for preparatory teachers, institutions and related persons, and teachers and administrators of secondary school teacher training institutions.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.11-20
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• 2021

The purpose of this study is to propose a documentary plan for the 7th Gyeongbuk Intangible Cultural Property, Andong-Notdaribapgi. Most of the records of Andong-Notdaribapgi. are produced centering on play. Thus this study aims to the method of recording it so that it can be accessed and utilized in the long term. This is a study at the beginning stage for documenting the Andong-Notdaribapgi. First of all, at the stage of the basic framework, the concept and characteristics of the recording of the Andong-Notdaribapgi were derived, and the meaning and necessity of recording was raised. In addition, the entire category of records was set through the analysis of the behavior process of Andong-Notdaribapgi, and the occurrence records and the contents of the records were organized focusing on the behavior processes occurring in various forms through the analysis of the recording target. In addition, materials that can be used are organized by focusing on the details and contents, including related records, and records that can be produced in the course of action are organized by type characteristics. Lastly, record analysis was based on performance behavior, and management functions were organized based on producers. The management of the records is to make it easier for users with various purposes to access the Intangible Cultural Property, the Andong-Notdaribapgi, and it is expected that it will provide directions and guidelines that can be applied to the recording plan in fields with similar characteristics.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1805-1815
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• 2022

In 2022, wildfires broke out in Uljin-gun and Samcheok-si, which set the record for the longest forest fire in Korea, but there were no casualties. To protect local residents from wildfires, they must evacuate. Predicting the demand for evacuation in the event of wildfires is essential for the efficiency of disaster management. The purpose of this study is to analyze the human mobility patterns according to the occurrence of Uljin-gun and Samcheok-si wildfires. SKT floating population data was used in this study to analyze the human mobility patterns in Uljin-gun and Samcheok-si. The main findings are as follows. First, while the movement of the resident and visiting population decreased, the movement of the worker population was found to be similar to normal. Second, the resident population of Buk-myeon, Uljin-gun moved to the surrounding area to avoid the wildfires. Third, the region is an area judged to be safe from wildfires, and this mobility patterns are related to emergency disaster text messages. This study confirmed human mobility patterns of the population in the area where the wildfires through the floating population data, which is quantitative data. This suggests that it is important to guide residents to shelters through emergency text messages to minimize damage in the event of wildfires.