• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.289-307
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• 2016

Infectious diseases such as Ebola virus disease become a social issue and draw public attention to be a major topic on news or research. As a result, there have been a lot of studies on infectious diseases using text-mining techniques. However, there is no research on content analysis of two media channels that have distinct characteristics. Accordingly, in this study, we conduct topic analysis between news (representing a social perspective) and academic research paper (representing perspectives of bio-professionals). As text-mining techniques, topic modeling is applied to extract various topics according to the materials, and the word co-occurrence map based on selected bio entities is used to compare the perspectives of the materials specifically. For network analysis, topic map is built by using Gephi. Aforementioned approaches uncovered the difference of topics between two materials and the characteristics of the two materials. In terms of the word co-occurrence map, however, most of entities are shared in both materials. These results indicate that there are differences and commonalties between social and academic materials.

• The Journal of Korean Academic Society of Nursing Education
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• v.28 no.4
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• pp.444-455
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• 2022

Purpose: This study explored the meaning of the social perceptions of nurses in online news articles during the coronavirus disease 2019 (COVID-19) pandemic. Methods: A total of 339 nurse-related articles published in Korean online newspapers from January 1 to December 31, 2020, were extracted by entering various combinations of OR and AND with the four words "Corona," "COVID," "Nursing," and "Nurse" as search keywords using BIGKinds, a news database provided by the Korea Press Foundation. The collected data were analyzed with a keyword network analysis and topic modeling using NetMiner 4. Results: The top keywords extracted from the nurse-related news articles were, in the following order, "metropolitan area," "protective clothing," "government," "task," and "admission." Four topics representing keywords were identified: "encouragement for dedicated nurses," "poor work environment," "front-line nurses working with obligation during the COVID-19 pandemic," and "nurses' efforts to prevent the spread of COVID-19." Conclusion: The media's attention to the dedication of nurses, the shortage of nursing resources, and the need for government support is encouraging in that it forms the public opinion necessary to lead to substantial improvements in treating nurses. The nursing community should actively promote policy proposals to improve treatment toward nurses by utilizing the net function of the media and proactively seek and apply strategies to improve the image of nurses working in various fields.

• Korean Journal Plant Pathology
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• v.11 no.3
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• pp.271-277
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• 1995

The RNA nucleotide sequences of the 3/-noncoding regions (3'-NCRs) of two Korean strains of turnip mosaic virus (TuMV), Ca and cqs, have been determined from their cDNA clones that encompassed the 3'-terminal regions of the viral genomic RNAs. The 3'-NCRs of both strains were 209 nucleotides long, terminated with GAC residues and poly (A) tails. The potential polyadenylational signal motif, UAUGU, was located 140 nucleotides upstream from the poly (A) tail in each of the virus. A highly conserved hexanucleotide sequence [A G U G A/U G/C], which was common in the 3'-NCRs of the potyvirus RNAs, was also found at the regions of 119 bases upstream from the 3'-end. Comparison of the 3'-NCRs of the two Korean isolates with those of four strains from Canada, China and Japan showed significantly identical genotypes (94.3∼99.5%). The secondary structure of three loops with long stems was found within the 3'-NCRs by sequence analysis. The substituted bases in the region among the six TuMV strains did not alter their secondary structures. Length of the 3'-NCRs of the know 11 potyviral RNAs and TuMV RNAs was different from one another and their nucleotide sequences showed 55.7% to 24.0% of homology. The 3'-NCR, therefore, is considered to be useful for phylogenetic studies in potyviruses.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.119-124
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• 2003

In this paper, we modeled positive selection and negative selection that is developing process of cytotoxic T-cell that plays important role in biological immune system. Also, we developed change detection algorithm, which is very Important part in detecting data change by intrusion and data infection by computer virus. Proposed method is the algorithm that produces MHC receptor lot recognizing self and antigen detector for recognizing non-self. Therefore, proposed method detects self and intruder by two type of detectors like real immune system. We show the effectiveness and characteristics of proposed change detection algorithm by simulation about point and block change of self file.

• Journal of muscle and joint health
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• v.27 no.3
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• pp.255-267
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• 2020

Purpose: The purpose of this study is to compare topics through keywords related to nurses in internet portals and social media Pre coronavirus disease (COVID-19) era and during the COVID-19 era. Methods: For six months before and during the outbreak of COVID-19 in Korea, "nurse" was searched on the internet. For data collection, we implemented web crawlers in programming languages such as Python and collected keywords. The keywords collected were classified into three domains of topic Modeling. Results: The keyword 'nurse' increased by 15% during COVID-19 era. Keywords that ranked high in Term Frequency - Inverse Document Frequency (TF-IDF) values were before COVID-19, such as "nurse" and "C-section". during COVID-19, however, they were not only "nurse" but also "emergency" and "gown" related to pandemics. Conclusion: Various topics were being uploaded into the internet media. Nursing professionals should be interested in the text that is revealed in the internet media and try to continuously identify and improve problems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.10 no.4
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• pp.95-105
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• 2000

The Firewall is needed in order to protect communication networks from ill effects of informatization such as information leakage, destruction, forgery and virus. To take an advantage of the firewall, the security manager must understand the effects that it can have on the network. There airs, however, no tools available to evaluate the performance of the firewall. In this paper, we study the effect of the firewall by putting various kinds of traffic into the actual network. Also, using COMNET- III, we model two networks with and without the firewall. And we analyze the effects under the various network envion-ments.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.218-227
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• 2021

The purpose was to examine what kind of discourse about foreigners in the media in a situation where hatred toward foreigners prevailed in a pandemic situation. News data related to Chinese international students(CIS) was collected for 2020, The 11 optimal topics were selected derived through LDA analysis. They were analyzed in an exploratory level, focusing on the relationship with major events per year. The news about CIS in 2020 was intensively linked to reports on the COVID19 situation. There was a tendency to report in response to the presupposes CIS as potential confirmed patients.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.109-117
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• 2020

An edutainment system aims to help learners to recognize problems effectively, grasp and classify important information needed to solve the problems and convey the contents of what they have learned. Edutainment contents can be usefully applied to education and training in the both scientific and industrial areas. Our present work proposes an edutainment system that can be applied to a drug discovery process including virtual screening by using intuitive multi-modal interfaces. In this system, a stereoscopic monitor is used to make three-dimensional (3D) macro-molecular images, with supporting multi-modal interfaces to manipulate 3D models of molecular structures effectively. In this paper, our system can easily solve a docking simulation function, which is one of important virtual drug screening methods, by applying gaming factors. The level-up concept is implemented to realize a bio-game approach, in which the gaming factor depends on number of objects and users. The quality of the proposed system is evaluated with performance comparison in terms of a finishing time of a drug docking process to screen new inhibitors against target proteins of human immunodeficiency virus (HIV) in an e-drug discovery process.

• Knowledge Management Research
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• v.22 no.2
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• pp.145-165
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• 2021

As of late December 2019, the spread of COVID-19 pandemic began which put the entire world in panic. In order to overcome the crisis and minimize any subsequent damage, the government as well as its affiliated institutions must maximize effects of pre-existing policy support and introduce a holistic response plan that can reflect this changing situation- which is why it is crucial to analyze social topics and people's interests. This study investigates people's major thoughts, attitudes and topics surrounding COVID-19 pandemic through the use of social media and big data. In order to collect public opinion, this study segmented time period according to government countermeasures. All data were collected through NAVER blog from 31 December 2019 to 12 December 2020. This research applied TF-IDF keyword extraction and LDA topic modeling as text-mining techniques. As a result, eight major issues related to COVID-19 have been derived, and based on these keywords, this research presented policy strategies. The significance of this study is that it provides a baseline data for Korean government authorities in providing appropriate countermeasures that can satisfy needs of people in the midst of COVID-19 pandemic.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.135-161
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• 2023

This study analyzed the research trends of COVID-19 research papers published in medical journals of Korea. Data were collected from 25 MEDLINE journals in 'Medicine and Pharmacy' studies and a total of 800 were selected. As a result of the study, authors from domestic affiliations made up 76.96% of the total, and the proportion of authors from foreign institutions decreased without significant change. The authors' majors were 'Internal Medicine' (32.85%), 'Preventive Medicine/Occupational and Environmental Medicine' (16.23%), 'Radiology' (5.74%), and 'Pediatrics' (5.50%), and 435 (54.38%) papers were collaborative research. As for author keywords, 'COVID19' (674), 'SARSCoV2' (245), 'Coronavirus' (81), and 'Vaccine' (80) were derived as top keywords. There were six words that appeared throughout the entire period: 'COVID19,' 'SARSCoV2,' 'Coronavirus,' 'Korea,' 'Pandemic,' and 'Mortality.' Co-occurrence network analysis was conducted on MeSH terms and author keywords, and common keywords such as 'covid-19,' 'sars-cov-2,' and 'public health' were derived. In topic modeling, five topics were identified, including 'Vaccination,' 'COVID-19 outbreak status,' 'Omicron variant,' 'Mental health, control measures,' and 'Transmission and control in Korea.' Through this study, it was possible to identify the research areas and major keywords by year of COVID-19 research papers published during the 'Public Health Emergency of International Concern (PHEIC).'