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A Convergence Study on Feasibility of Expanding Establishment of Public Postpartum Care Centers: Benefit-Cost Analysis (공공산후조리원 확대의 타당성에 관한 융합 연구: 편익-비용 분석을 중심으로)

  • Bae, Hyun-Ji;Kim, Jin-Hyun
    • Journal of the Korea Convergence Society
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    • v.11 no.12
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    • pp.409-418
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    • 2020
  • The purpose of this study is to analyze the economic feasibility of public postpartum care centers established for health care of low-income postpartum mothers. 6 of 8 public postpartum care centers were used to verify the economic feasibility and research data were collected through the centers. A sensitivity analysis was performed with the bed turnover rate, assuming that users in a postpartum care center will be decreased. As a result, B/C ratio was estimated to be 1.50 and the net benefit was estimated to be KRW 186,557 in million. A sensitivity analysis showed that B/C was 1.42 at 17.4 of bed turnover rate and 1.26 at 15.4 which indicates the lowest bed turnover rate among subjects. A public postpartum care center was evaluated as economically feasible as public works. Therefore it is necessary that the public postpartum care centers operated by local governments should be expanded through legal amendment.

Exploring Issues Related to the Metaverse from the Educational Perspective Using Text Mining Techniques - Focusing on News Big Data (텍스트마이닝 기법을 활용한 교육관점에서의 메타버스 관련 이슈 탐색 - 뉴스 빅데이터를 중심으로)

  • Park, Ju-Yeon;Jeong, Do-Heon
    • Journal of Industrial Convergence
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    • v.20 no.6
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    • pp.27-35
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    • 2022
  • The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

Design of Knowledge-based Spatial Querying System Using Labeled Property Graph and GraphQL (속성 그래프 및 GraphQL을 활용한 지식기반 공간 쿼리 시스템 설계)

  • Jang, Hanme;Kim, Dong Hyeon;Yu, Kiyun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.5
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    • pp.429-437
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    • 2022
  • Recently, the demand for a QA (Question Answering) system for human-machine communication has increased. Among the QA systems, a closed domain QA system that can handle spatial-related questions is called GeoQA. In this study, a new type of graph database, LPG (Labeled Property Graph) was used to overcome the limitations of the RDF (Resource Description Framework) based database, which was mainly used in the GeoQA field. In addition, GraphQL (Graph Query Language), an API-type query language, is introduced to address the fact that the LPG query language is not standardized and the GeoQA system may depend on specific products. In this study, database was built so that answers could be retrieved when spatial-related questions were entered. Each data was obtained from the national spatial information portal and local data open service. The spatial relationships between each spatial objects were calculated in advance and stored in edge form. The user's questions were first converted to GraphQL through FOL (First Order Logic) format and delivered to the database through the GraphQL server. The LPG used in the experiment is Neo4j, the graph database that currently has the highest market share, and some of the built-in functions and QGIS were used for spatial calculations. As a result of building the system, it was confirmed that the user's question could be transformed, processed through the Apollo GraphQL server, and an appropriate answer could be obtained from the database.

An Analysis on the Factors Affecting University Startups (대학 창업 성과에 미치는 영향 요인)

  • Kim, Jongwoon
    • Korean small business review
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    • v.42 no.4
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    • pp.285-308
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    • 2020
  • This paper analyzes the factors which affect University professors and students on their startup activities, such as (a) University factors: their industrial cooperation organization and systems, their resources for startup support, their knowledge assets, and (b) socioeconomic characteristics in which Universities are located. We used the data and information from the University Information System and the National Statistical Office Publication to analyze 157 4-year Universities in Korea who uploaded their startup-related information on the system. Our analysis shows that Universities' systems, such as the term for Professors' leave of absence for startup activities, and their amount of knowledge assets affect the number of Professor startups significantly positively, while there is no significant effect on their performance, in terms of sales, from those factors, except for the amount of patents that the University has. In the meantime, the number of practical startup courses, the number of startup clubs, and the number of professor startups in the University affect the number of student startups, while the size of industrial cooperation body, the amount of knowledge asset, the area's socioeconomic characteristics didn't affect their performance. The result implies that we need to take different approaches to boost University professor startups and their student startups: better system and more knowledge for the former, more practical courses and programs for the latter. Further study is needed to get a more robust result because this analysis used only one year data, and personal trait data was not included in the analysis. A panel data analysis for several years is recommended for further research.

An Exploratory Study on the Learning Community: Focusing on the Covid19 Untact Era (배움공동체에 대한 탐색적 연구 : covid19 언택트시대를 중심으로)

  • Jeong, Su-Jeong;Im, Hong-Nam;Park, Hong-Jae
    • Journal of Convergence for Information Technology
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    • v.12 no.5
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    • pp.237-245
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    • 2022
  • This study examines the social discourse on the characteristics of the learning community in the untact era, and discusses the directions that learning communities for children could explore and consider in the pandemic situation and beyond. For this purpose, big data for one year, from January 20, 2020 to January 20, 2021, were collected through internet portal sites (includingincluding Google News, Daum, Naver and other News surfaces), using two keywords "untact" and "learning community", and analyzed by employing a word frequency and network analysis method. The analysis results show that several important terms, such as 'village education community', 'operation', 'activity', 'corona 19', 'support', and 'online' are closely related to the learning community in the untact era. The findings from this study also have implications for developing the learning community as an alternative model to fill the existing gaps in public care and education for children during the prolonged pandemic and afterwards. In conclusion, the study findings highlight that it is meaningful to identify key terms and concepts through word frequency analysis in order to examine social trends and issues related to the learning community.

Comparison of Micro Mobility Patterns of Public Bicycles Before and After the Pandemic: A Case Study in Seoul (팬데믹 전후 공공자전거의 마이크로 모빌리티 패턴 비교: 서울시 사례 연구)

  • Jae-Hee Cho;Ga-Eun Baek;Il-Jung Seo
    • The Journal of Bigdata
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    • v.7 no.2
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    • pp.235-244
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    • 2022
  • The rental history data of public bicycles in Seoul were analyzed to examine how pandemic phenomena such as COVID-19 caused changes in people's micro mobility. Data for 2019 and 2021 were compared and analyzed by dividing them before and after COVID-19. Data were collected from public data portal sites, and data marts were created for in-depth analysis. In order to compare the changes in the two periods, the riding direction type dimension and the rental station type dimension were added, and the derived variables (rotation rate per unit, riding speed) were newly created. There is no significant difference in the average rental time before and after COVID-19, but the average rental distance and average usage speed decreased. Even in the mobility of Ttareungi, you can see the slow rhythm of daily life. On weekdays, the usage rate was the highest during commuting hours even before COVID-19, but it increased rapidly after COVID-19. It can be interpreted that people who are concerned about infection prefer Ttareungi to village buses as a means of micro-mobility. The results of data mart-based visualization and analysis proposed in this study will be able to provide insight into public bicycle operation and policy development. In future studies, it is necessary to combine SNS data such as Twitter and Instagram with public bicycle rental history data. It is expected that the value of related research can be improved by examining the behavior of bike users in various places.

Moderating Effect of Population Drop in the Relationship Between Demographic Changes and Crime Decline (인구통계학적 구조 변화와 범죄 감소 간의 관계에 있어서 인구 감소의 조절 효과 검증)

  • Soo-Chang Lee;Dae-Chan, Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.95-102
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    • 2023
  • This study aims to empirically verify the moderating effect of population drop on the relationship between demographic changes and crime decline in local cities facing population decline in Korea. The study employs changes in the population of young adults, men, elderly, foreign residents, and population movement as factors of demographic changes, including types of the city as a control variable in the research model. The rate of change in population drop is used as a moderator variable and the rate of change in crime decline as a dependent variable. Data are collected from 155 cities with declining populations from 2010 to 2022 through KOSIS, the National Statistics Portal, and information disclosure requests. Data collected are analyzed using moderated regression analysis. In the first and second stages of the analysis, they show that changes in the population of young adults, population movement, foreign people, population drop, and the type of city affect the change in crime. Moderated regression analysis shows that only the interaction terms among changes in the population of young adults, changes in population movement, and changes in the population of foreigners and the population drop affects change in crime significantly.

Assessment of climate disaster vulnerability of Gangwon-do based on RCP 8.5 climate change scenario (RCP 8.5 기후변화시나리오 기반 강원도 기후 재난취약성 평가)

  • Lee, Hyeon Ji;Jeung, Se Jin;Kim, Byung Sik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.335-335
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    • 2022
  • 남한상세 기후변화 전망보고서(2021)는 2100년대 강원도 강수량이 현재보다 19% 증가하고, 평균기온이 현재보다 6.5℃ 상승할 것으로 공표했다. 강원도는 영동지역과 영서지역으로 분리돼 기후 차이가 분명하다. 기상청 ASOS 데이터(1986~2020)를 이용해 기후 특성을 확인한 결과 영동지역 강수량은 1,463mm, 평균기온은 10.5℃, 상대습도는 66%로 분석됐고, 영서지역 강수량은 1,307mm, 평균기온은 11℃, 상대습도는 68%로 분석됐다. 영동지역 강수량이 영서지역 강수량보다 약 156mm 더 많으며, 이는 영동지역에서 큰 규모의 우심 피해가 발생할 가능성이 존재함을 의미한다. 강원도 평년 우심 피해 현황을 살펴본 결과 영동지역은 5회(피해액: 62억 원), 영서지역은 24회(피해액: 62억원)가 발생했다. 이는 미래로 갈수록 더 심해질 것으로 판단되며, 이런 기상 재난을 객관적으로 판단할 수 있는 기준이 필요하다. 이에 본 연구에서는 기후변화에 따른 강원도 기후 재난취약성을 평가했다. 이를 위해 기후변화 위험성, 기후변화 민감도, 기후변화 적응능력 지표를 활용해 기후변화 취약성 지표를 선정했다. 기후변화 위험성 지표는 홍수(CWD, Rx5day, R30mm), 가뭄(CDD, SU, TX90p), 폭염(SU, TR, TN90p), 한파(ID, TX10p, FD)로 RCP 8.5 기후변화시나리오를 ETCCDI 지수에 적용했다. 기후변화 민감도와 기후변화 적응능력 지표는 국가통계포털, 강원통계정보, WAMIS에서 자료를 수집해 선정했다. 또한 재난취약성 지표를 4단계(Very Low, Low, High, Very High)로 구분했다. 홍수 취약성 평가 결과 2090년대 원주시, 춘천시, 횡성군이 Low에서 Very High로 단계가 격상됐다. 가뭄 취약성 평가 결과 2090년대 양양군, 영월군, 정선군이 Very Low에서 Very High로 단계가 격상됐다. 폭염 취약성 평가 결과 2090년대 삼척시, 태백시, 영월군이 Very Low에서 Very High로 단계가 격상됐다. 한파 취약성 평가 결과 삼척시, 태백시, 영월군이 High에서 Very Low로 단계가 격하됐다. 고로 강원도는 기후 재난취약성 평가 결과에 따른 미래 기후변화를 대비하고, 각 지역 특성에 맞는 복원력 관점 기후 재난 관리가 필요하다고 사료된다.

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Establishing meteorological drought severity considering the level of emergency water supply (비상급수의 규모를 고려한 기상학적 가뭄 강도 수립)

  • Lee, Seungmin;Wang, Wonjoon;Kim, Donghyun;Han, Heechan;Kim, Soojun;Kim, Hung Soo
    • Journal of Korea Water Resources Association
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    • v.56 no.10
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    • pp.619-629
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    • 2023
  • Recent intensification of climate change has led to an increase in damages caused by droughts. Currently, in Korea, the Standardized Precipitation Index (SPI) is used as a criterion to classify the intensity of droughts. Based on the accumulated precipitation over the past six months (SPI-6), meteorological drought intensities are classified into four categories: concern, caution, alert, and severe. However, there is a limitation in classifying drought intensity solely based on precipitation. To overcome the limitations of the meteorological drought warning criteria based on SPI, this study collected emergency water supply damage data from the National Drought Information Portal (NDIP) to classify drought intensity. Factors of SPI, such as precipitation, and factors used to calculate evapotranspiration, such as temperature and humidity, were indexed using min-max normalization. Coefficients for each factor were determined based on the Genetic Algorithm (GA). The drought intensity based on emergency water supply was used as the dependent variable, and the coefficients of each meteorological factor determined by GA were used as coefficients to derive a new Drought Severity Classification Index (DSCI). After deriving the DSCI, cumulative distribution functions were used to present intensity stage classification boundaries. It is anticipated that using the proposed DSCI in this study will allow for more accurate drought intensity classification than the traditional SPI, supporting decision-making for disaster management personnel.

A Study on the Social Perception of Jiu-Jitsu Using Big data Analysis (빅데이터 분석을 활용한 주짓수의 사회적 인식 연구)

  • Kun-hee Kim
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.3
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    • pp.209-217
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    • 2024
  • The purpose of this study is to explore development plans by analyzing social interests and perceptions of jiu-jitsu using big data analysis. Network analysis, centrality analysis, and CONCOR analysis were conducted by collecting data for the last 10 years of major domestic portal sites. First, 'judo' was found to be the most important related word in network analysis, and 'judo' was also an important word in the analysis of dgree centrality. In the closeness centrality analysis, "defender" was the most important word, and "sports" was the most important word in betweenness centrality. Finally, as a result of CONCOR analysis, four clusters (related sports and marketing, jiu-jitsu competitions, belt test, supplies and expenses) were formed. As a conclusion of the study, first, words such as 'judo', 'exercise', 'competition', 'dobok', 'gym', and 'graduation' should be actively used to promote jiu-jitsu.As a conclusion of the study, first, words such as 'judo', 'exercise', 'contest', 'dobok', 'gym', and 'graduation' should be actively used to promote jiu-jitsu. Second, it is necessary to share information on training costs through various routes, to make awareness of the graduation process or method common, and to develop safety products and create a safe training culture. Third, it is necessary to find ways to continuously increase the influx of new trainees by attracting steady competitions.