• Journal of Korean Home Economics Education Association
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• v.19 no.4
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• pp.37-56
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• 2007

The purpose of this study is to provide basic resources to the first-grade Home Economics Regular Teacher Qualification Program (FGHERTQP) in order to improve its operation plans. For the study, the three methods were carried out: an analysis on the curricula of FGHERTQP over six years since 2000, a questionnaire asking their satisfaction degrees and needs on the programs which was answered by the home economics teachers who were the participants of FGHERTQP, and several statistical analyses such as a descriptive-test, a $X^2$-test, a t-test, and one way ANOVA by using SPSS Win ver 10.0. The results of the study were as follows; Firstly, FGHERTQP has been operated ten times by five training centers during resent six years. Subject matters ($1{\sim}7$), whole numbers of lectures ($11{\sim}29$), and their allotted working hours ($111{\sim}136$) vary with individual training centers and operation years. Secondly, when using 5 point likert scales, Contents and Methods of evaluation marked 3.08 which were the lowest scores, and Qualification Training in General marked 3.72 which was the highest score among five fields of Qualification Training in General, Contents, Organizations, Methods and Evaluation. The overall scores were low. Thirdly, in needs analysis on offering subject matters, the participants wanted to study the field of home economics education more than that of subject contents. Looking about the highest needs classified by domains, Food Principles & Meal Management showed the highest in Foods. And Consumer Issues in Clothing & Textiles in Textiles, Upcoming Housing Cultures in Housing, Family Relationship in Child Development & Family Relationship, Juveniles and their daily life as a consumer in Family & Consumer Resources Management. Fourthly, training centers' lectures available had a significant influence on the satisfaction degrees according to general characteristic variations of the participants. That is, as a training center offers more lectures in the field of subject education than those of subject contents, the participants showed higher satisfaction degrees (p<.05).

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1296-1307
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• 1997

Background : Erdosteine is a thiol derivative developed for the treatement of chronic obstructive bronchitis, including acute infective exacerbation of chronic bronchitis. Erdosteine has mucomodulating and antioxidant properties and especially exhibits excellent gastrointestinal tolerability. Methods : The study was conducted as a prospective evaluation, with 2 comparative groups orally treated with erdosteine 300mg (bid.) or ambroxol 30mg (b.i.d.) for 7 days and the design of trial was double-blind. The treatments have been assigned randomly to patients (n=80) with acute or chronic bronchitis. The primary end-point used to determine efficacy in this study was subjective symptoms including expectorating frequence, expectoration volume, expectorating difficulty, expectoration viscosity, cough intensity and dyspnea. The secondary end-points of efficacy was the result of arterial blood gas analysis and pulmonary function test. Safety was evaluated with adverse drug reactions and laboratory tests monitoring. 61 patients was included in the efficacy analysis, due to the fact that 19 patients drop-out for different reasons. The obtained values have been analyzed with paired Hest., ANOVA test., multivariate $t^2$-test, repeated measures analysis of covariance, two sample t-test, loglinear-logit model analysis, Fisher's exact test. Results : 1) There was no significant difference on demographic data and vital signs between erdosteine and ambroxol treated groups. 2) The comparison between erdosteine and ambroxol treated groups showed no significant difference in improvement of each symptom in spite of the more favorable efficacy obtained with erdosteine. No difference on the contrary was observed for arterial blood gas analysis and pulmonary function test. 3) As safety is concerned, no clinical significant changes in laboratory test and symptom were induced in erdosteine and ambroxol treated group and two patients in ambroxol treated group drop-out for adverse reactions in symptom. 4) In the evaluation of final clinical efficacy, erdosteine improved more effectively patient's overall symptoms {very good effect (11/31), good effect (12/31), moderate effect (6/31), no effect (2/31), aggravation (0/31)} than ambroxol {very good effect (6/30), good effect (14/30), moderate effect (5/30), no effect (4/30), aggravation (2/30)}. And the probability of symptomatic improvement by erdosteine compared to ambroxol was 2.5 times. (p<0.05). Conclusion : This study showed that erdosteine was clinically effective and safe drug for treatment of acute and chronic bronchitis.

• Asian Journal of Turfgrass Science
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• v.18 no.4
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• pp.179-191
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• 2004

This study was conducted to find out the effect of sodding and seeding time and rate of seed mixtures on the establishment of cool-season turfgrasses by evaluating the turf coverage rates for two years. In fall planting, the required establishment period of full coverage($100\%$) was 1.5 months with a rolled turf sodding(Kentucky bluegrass $100\%$, Kentucky bluegrass $80\%$+perennial ryegrass $20\%$). The $100\%$ turf establishment was achieved in 7 months with Perennial ryegrass $100\%$, and 7.5 months by seeding with Kentucky bluegrass $100\%$(KB 100), Kentucky bluegrass $80\%$+perennial ryegrass $20\%$(KB80+PR20), Kentucky bluegrass $70\%$+perennial ryegrass $30\%$(KB70+PR30). In spring planting, the establishment periods far sod with KB 100 or KB80+PR20 were taken one month. However, in the case of seeding, the establishment periods were 3 months, 3.5 months, 3.5 months and 4 months with PR100, KB80+PR20, KB70+PR30, and KB 100, respectively Comparing the turf establishment vigor between fall and spring planting, the vigor was higher In spring planting than in fall planting in both sodding and . seeding. In the case of spring planting, the most proper time for turf establishment was tested on April, May, and June trials. The effect was significant in establishment vigor. The result showed highest on April planting. On May and June trials, establishment vigors were decreased gradually As the mixture rate of PR increased, ryegrass, establishment vigor was decreased with the rates. These results indicated that perennial ryegrass has relatively less tolerant to summer heat than Kentucky bluegrass. Number of shoots in 95 days after seeding was higher in KB100 by 16,600 per $m^2$ than in PR100 by 12,400 per $m^2$, while the lowest number showed in KB50+PR50 by 3,300 per $m^2$. Those in KB80:PR20, KB70:PR30 were 6,700 and 4,900 per $m^2$, respectively. The ratios of tillers according to mixture rates between Kentucky bluegrass and perennial ryegrass were KB80:PR20=87:13, KB70:PR30=78:22, and KB50:PR50=48:52. According to results in this study, Ideal seeding time might be spring (April) than in fall (September), and proper mixture rate was $80\%$ of Kentucky bluegrass with $20\%$ of perennial ryegrass.

• The Korean Journal of Nuclear Medicine
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• v.37 no.4
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• pp.219-228
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• 2003

Purpose: The amount of salvaged myocardium is an important prognostic factor in patients with acute myocardial infarction (MI). We investigated if early Tl-201 SPECT imaging could be used to predict the salvaged myocardium and functional recovery in acute MI after primary PTCA. Materials and Methods: In 36 patients with first acute MI treated with primary PTCA, serial echocardiography and Tl-201 SPECT imaging ($5.8{\pm}2.1$ days after PTDA) were performed. Regional wall motion and perfusion were quantified with on 16-segment myocardial model with 5-point and 4-point scaling system, respectively. Results: Wall motion was improved in 78 of the 212 dyssynergic segments on 1 month follow-up echocardiography and 97 on 7 months follow-up echocardiography, which were proved to be salvaged myocardium. The areas under receiver operating characteristic curves of Tl-201 perfusion score for detecting salvaged myocardial segments were 0.79 for 1 month follow-up and 0.83 for 7 months follow-up. The sensitivity and specificity of Tl-201 redistribution images with optimum cutoff of 40% of peak thallium activity for detecting salvaged myocardium were 84.6% and 55.2% for 1 month follow-up, and 87.6% and 64.3% for 7 months follow-up, respectively. There was a linear relationship between the percentage of peak thallium activity on early redistribution imaging and the likelihood of segmental functional improvement 7 months after reperfusion. Conclusion: Tl-201 myocardial perfusion SPECT imaging performed early within 10 days after reperfusion can be used to predict the salvaged myocardium and functional recovery with high sensitivity during the 7 months following primary PTCA in patients with acute MI.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• The Korean Journal of Nuclear Medicine
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• v.39 no.1
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• pp.34-43
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• 2005

Purpose: $^{99m}Tc$-sestamibi(MIBI) and $^{99m}Tc$-tetrofosmin have been used as substrates for P-glycoprotein (Pgp) and multidrug resistance associated protein (MRP), which are closely associated with multidrug resistance of the tumors. To understand different handling of radiotracers in cancer cell lines expressing Pgp and MRP, we compared cellular uptakes of $^{99m}Tc$-MIBI and $^{99m}Tc$-tetrofosmin. The effects of cyclosporin A (CsA), well-known multidrug resistant reversing agent, on the uptake of both tracers were also compared. Materials and Methods: HCT15/CL02 human colorectal cancer cells for Pgp expressing cells, and human non-small cell lung cancer A549 cells for MRP expressing cells, were used for in vitro and in vivo studies. RT-PCR, western blot analysis and immunohistochemistry were used for detection of Pgp and MRP. MDR-reversal effect with CsA was evaluated at different drug concentrations after incubation with MIBI or tetrofosmin. Radioactivities of supernatant and pellet were measured with gamma well counter. Tumoral uptake of the tracers were measured from tumor bearing nude mice treated with or without CsA. Results: RT-PCR, western blot analysis of the cells and irnrnunochemical staining revealed selective expression of Pgp and MRP for HCY15/CL02 and A549 cells, respectively. There were no significant difference in cellular uptakes of both tracers in HCT15/CL02 cells, but MIBI uptake was slightly higher than that of tetrofosmin in A549 cells. Co-incubation with CsA resulted in a increase in cellular uptakes of MIBI and tetrofosmin. Uptake of MIBI or tetrofosmin in HCT15/CL02 cells was increased by 10- and 2.4-fold, and by 7.5 and 6.3-fold in A549 cells, respectively. Percentage increase of MIBI was higher than that of tetrofosmin with CsA for both cells (p<0.05). In vivo biodistribution study showed that MIBI (114% at 10 min, 257% at 60 min, 396% at 240 min) and tetrofosmin uptake (110% at 10 min, 205% at 60 min, 410% at 240 min) were progressively increased by the time, up to 240 min with CsA. But increases in tumoral uptake were not significantly different between MIBI and tetrofosmin for both tumors. Conclusion: MIBI seems to be a better tracer than tetrofosmin for evaluating MDR reversal effect of the modulators in vitro, but these differences were not evident in vivo tumoral uptake. Both MIBI and tetrofosmin seem to be suitable tracers for imaging Pgp- and MRP-mediated drug resistance in tumors.

• Journal of Korean Historical Folklife
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• no.52
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• pp.7-46
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• 2017

The elderly in the Joseon Dynasty consistently attracted attention from the national herb as objects of social respect. Based on the Confucian ideology, the old man was considered to be a receiving body, since he was a person with complete character as a man. The elderly, who have the character of being a slave, transcended their status, and both the souls and the people were transcended beyond their identities and attributes and became objects of respect. The perception of the elderly is divided by age. The persons who are 50 years old and start to be in physical decline were regarded as senior citizens. However, this was just mentioned as an inflection point between the prime of manhood and senior citizens and was not defined as the elderly. As a public duty called a national work ends when they are 60 years old, the age is truly the lowest limit of senior citizens who are applicable to all the social beings. However, because their public duties end when they are 60 years old and they were regarded as general members of society, special benefits were not granted to them. In the caste system and bureaucratic society, senior citizens' treatment were differently done by age. For the senior citizens who are 70 years old, various benefits were just granted to high government officials. Bokho(復戶) and Seojeong were first given to them. And the retirement age of government officials was not specially set. It was done in the way to treat Jonno with exceptional respect by Chisa(致仕: regular retirement). It is the most respectful treatment given to high government officials and ministers. For the senior citizens who are 80 years old, Yangnoyeon(養老宴) was held for both of Yangmin and Cheonmin as an measure to treat them considerately. In addition, official ranks(官品) with social value were allowed by giving them Noinjik (老人職). Official ranks given to Seoin and Cheonin were the best Jonno(尊老) policy. However, the Jonno policy related to senior citizens was different according to position and official ranks as follows: Kings were subjected to social treatment when they were 60 years old. High government officials and royal relatives of the senior grade of the second court rank were subjected to social treatment when they were 70 years old. And general Seoin and slaves were subjected to social treatment when they were respectively 80 and 90 years old. Senior citizens were individually supported. However, social value was granted because the nation supervised it. As Bokho and Sijeong were assigned according to position and official ranks and kinds of things were different, the social limit was clearly shown. Social order was put above the ideology called Jonno thought. However, Jonno acts by age and position did not stay at the individual level and the nation took care of the senior citizens who are the members of society in various ways based on Jonno thought. Society tried to take care of the senior citizens who had difficulties in their activities because of being in physical decline. The nation increased the existence value of the senior citizens by giving things(賜物) including chairs, rice, meat, and ice economically, exoneration(免罪), the reduction system, and wergild legally, and Noinjik called Gaja(加資) socially to them and changing them to the members of society. Yangnoyeon and Gaja held targeting people of every class by transcending position and official ranks make the point that the senior citizens who are more than 80 years old are subject to social jonno clear. That is, the senior citizens were subject to respect for the elderly as the persons who were socially respected transcending their position when they got to be 80 years old.

• The Korean Society of Law and Medicine
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• v.23 no.4
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• pp.29-74
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• 2022

As social disasters occur under the Disaster Management Act, which can damage the people's "life, body, and property" due to the rapid spread and spread of unexpected COVID-19 infectious diseases in 2020, information collected through inspection and reporting of infectious disease pathogens (Article 11), epidemiological investigation (Article 18), epidemiological investigation for vaccination (Article 29), artificial technology, and prevention policy Decision), (3) It was used as an important basis for decision-making in the context of an infectious disease crisis, such as promoting vaccination and understanding the current status of damage. In addition, medical policy decisions using infectious disease data contribute to quarantine policy decisions, information provision, drug development, and research technology development, and interest in the legal scope and limitations of using infectious disease data has increased worldwide. The use of infectious disease data can be classified for the purpose of spreading and blocking infectious diseases, prevention, management, and treatment of infectious diseases, and the use of information will be more widely made in the context of an infectious disease crisis. In particular, as the serious stage of the Disaster Management Act continues, the processing of personal identification information and sensitive information becomes an important issue. Information on "medical records, vaccination drugs, vaccination, underlying diseases, health rankings, long-term care recognition grades, pregnancy, etc." needs to be interpreted. In the case of "prevention, management, and treatment of infectious diseases", it is difficult to clearly define the concept of medical practicesThe types of actions are judged based on "legislative purposes, academic principles, expertise, and social norms," but the balance of legal interests should be based on the need for data use in quarantine policies and urgent judgment in public health crises. Specifically, the speed and degree of transmission of infectious diseases in a crisis, whether the purpose can be achieved without processing sensitive information, whether it unfairly violates the interests of third parties or information subjects, and the effectiveness of introducing quarantine policies through processing sensitive information can be used as major evaluation factors. On the other hand, the collection, provision, and use of infectious disease data for research purposes will be used through pseudonym processing under the Personal Information Protection Act, consent under the Bioethics Act and deliberation by the Institutional Bioethics Committee, and data provision deliberation committee. Therefore, the use of research purposes is recognized as long as procedural validity is secured as it is reviewed by the pseudonym processing and data review committee, the consent of the information subject, and the institutional bioethics review committee. However, the burden on research managers should be reduced by clarifying the pseudonymization or anonymization procedures, the introduction or consent procedures of the comprehensive consent system and the opt-out system should be clearly prepared, and the procedure for re-identifying or securing security that may arise from technological development should be clearly defined.