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임준범 ( Joon Bum Lim ),이수범 ( Soo Beom Lee ),성정곤 ( Jung Gon Sung ),박준태 ( Jun Tae Park ) 한국안전학회(구 한국산업안전학회) 2012 한국안전학회지 Vol.27 No.4
This research has analyzed factors affecting customers` satisfaction when they use parking lots of big retailers so that, in case of constructing, operating or managing such retailers, proper measures can be come up with. The analysis has been implemented on the basis of survey, and influence factors including entry/exit lamp, parking cars`` traffic flow, parking type, pedestrians`` movement after parking and safety. Parking lot users`` satisfaction has been analyzed by using the Structural Equation Modelling and, as a result of it, in case of a detached or single building, pedestrians movement flow after parking contributed the most to the users`` satisfaction, while, in case of multipurpose complex, parking cars traffic flow has the most influential factor. It is interpreted that users of a single building put a bigger emphasis on entry to the shop and their way back to the parked area after their shopping while customers of multipurpose complex might have various purposes of visiting the place and there are relatively more cars so that they put more emphasis on traffic counterflow, other cars and pedestrians.
도시부 신호교차로 안전성 향상을 위한 사고예측모형 개발
박준태(Park, Jun-Tae),이수범(Soo Beom Lee),김장욱(Kim, Jang-Uk),이동민(Dong min Lee) 대한교통학회 2008 대한교통학회 학술대회지 Vol.58 No.-
국가적 문제점으로 대두되고 있는 교통사고는 물적 손실 뿐만아니라 국민의 인명과 고통이라는 피해를 발생시키며 꾸준히 증가하고 있는 추세이다. 발생지점별로 교차로에서의 사고는 2002년 21.1%, 2003년 25.9%, 2004년 26.0%로 교통사고 발생비율이 증가 양상을 보이고 있으며 이러한 교통사고는 차량간의 상충이나 차량과 보행자간의 상충이 자주 발생하므로 정밀분석을 통한 교통사고 원인 및 문제점에 대한 안전대책이 필요하고 시설투자의 우선순위의 대안제시가 필요한 실정이다. OECD회원국중에서 우리나라의 교통사고율이 매우 높은 것으로 나타나 아직까지도 교통사고 다발국, 교통후진국이라는 오명을 벗지 못하고 있다. 도로에서의 교통사고를 완전히 없애고자 하는 목표는 현재로서는 달성하기 힘들겠지만 도로를 좀 더 안전하게 만들고 사고감소의 목표치를 설정하는 노력은 계속되고 있다.
소셜 빅데이터 기법을 활용한 초등학생 스포츠맨십에 대한 인식 분석
박준태 ( Park Jun Tae ) 국제뇌교육종합대학원 인성교육연구원 2023 인성교육연구 Vol.8 No.1
본 연구의 목적은 소셜 빅데이터 기법을 활용하여 초등학생 스포츠맨십에 대한 사람들의 인식을 알아보는 것이다. 이 연구 문제를 해결하기 위해 네이버, 구글, 다음 3곳 주요 포털사이트에서 “초등학생 스포츠맨십”이라는 키워드로 2018년 1월 1일부터 2022년 10월 31일까지 게시된 데이터를 수집하였다. 전처리 과정을 거친 후 텍스톰(Textom)과 Ucinet6을 통해 주요 키워드 및 TF-IDF 분석, 중심성 분석, 군집분석(CONCOR) 실시하여 다음과 같은 결론을 도출하였다. 첫째, 스포츠맨십에 대한 키워드 빈도와 TF-IDF 분석한 결과, 「선수, 초등학교, 경기, 배움, 학년, 올림픽, 쇼트트랙, 재학」과 같은 상위 키워드가 도출되었다. 둘째, 스포츠맨십에 대한 중심성 분석한 결과, 「선수, 초등학교, 쇼트트랙, 학년, 올림픽, 경기, 배움, 전국, 재학」 등의 키워드가 연결중심성이 높은 것으로 나타났다. 셋째, 스포츠맨십에 대한 CONCOR 분석한 결과, 「스포츠맨십 대상, 스포츠맨십 종목, 학교의 스포츠맨십, 스포츠맨십 모델링」으로 4개의 군집이 형성되었다. 본 연구는 스포츠맨십에 대한 숨겨진 인사이트를 발견하고 그로 인해 초등학생의 스포츠맨십 형성에 도움이 되는 정보를 제공하였다는 점에 의의가 있다. The purpose of this study is to find out people's perceptions of elementary school students' sportsmanship using novel big-data analysis. To solve this research problem, data posted from January 1, 2018 to October 31, 2022 with the keyword Elementary school students' sportsmanship were collected from three major portal sites: Naver, Google, and Daum. After the preprocessing process, the main keywords and TF-IDF analysis, centrality analysis, and cluster analysis (CONCOR) were conducted through Textom and Ucinet6. The following conclusions were drawn. First, as a result of keyword frequency and TF-IDF analysis of sportsmanship, top keywords such as an 「athlete, elementary school, game, learning, grade, Olympics, short track, and school」 were derived. Second, as a result of the centrality analysis of sportsmanship, keywords such as 「athlete, elementary school, short track, grade, Olympics, game, learning, nationwide, and school attendance」 showed high connection centrality. Third, as a result of the CONCOR analysis on sportsmanship, four clusters were formed: sportsmanship target, sportsmanship event, school sportsmanship, and sportsmanship modeling. This study is significant in that it discovered hidden insights on sportsmanship and provided information helpful for the formation of sportsmanship in elementary school students.
박준태 ( Jun Tae Park ),이수범 ( Soo Beom Lee ),이수일 ( Soo Il Lee ) 한국안전학회(구 한국산업안전학회) 2011 한국안전학회지 Vol.26 No.4
A traffic accident which happens in Expressway during dense fog is more likely to cause the sequential accidents and high death rate. So, the preventive measures shall be taken at dangerous areas to enhance the efficiency of roads and minimize the accidents and the resultant damages. So, it is necessary to find out the characteristics of freeway zone which has high risk of fog occurrence and to establish the comprehensive safety strategy on installation and operation of the safety equipment. In this study, I developed a fog forecasting model by using the freeway fog data. This model can be used as the fog forecasting model in dealing with fog problems when new road is planned. The model was developed by using a statistical analysis technique or the regression analysis, focusing on the variables such as geographical features and regional conditions, distances to water sources and the area of water source. I have segmented the models by classifying the area into inland area and coastal area. The distance to water source and area of the water source located around the freeway were found to be main factors causing fog.
박준태 ( Jun Tae Park ),강팔문 ( Pal Moon Kang ),박성호 ( Sung Ho Park ) 한국안전학회(구 한국산업안전학회) 2014 한국안전학회지 Vol.29 No.2
Railroad traffic accident consists of train accident, level-crossing accident, traffic death and injury accident caused by train or vehicle, and it is showing a continuous downward trend over a long period of time. As a result of the frequency comparison of train accidents and level-crossing accidents using the railway accident statistics data of Railway Industry Information Center, the share of train accident is over 90% in the 1990s and 80% in the 2000s more than the one of level-crossing accidents. In this study, we investigated time series characteristic and short-term prediction of railroad crossing, as well as seasonal characteristic. The analysis data has been accumulated over the past 20 years by using the frequency data of level-crossing accident, and was used as a frequency data per month and year. As a result of the analysis, the frequency of accident has the characteristics of the seasonal occurrence, and it doesn’t show the significant decreasing trend in a short-term