http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
곽호찬(Ho Chan Kwak),정윤영(Youn Young Jung),김종철(Jong Chul Kim),방승기(Seung Ki Pang),손종렬(Jong Ryeul Sohn) 한국생활환경학회 2009 한국생활환경학회지 Vol.16 No.6
In this study, evaluated removal efficiency of indoor air pollutants such as PM₁? (particulate matter), TBC (total bacteria colony), HCHO (formaldehyde), TVOC (total volatile organic compound) by using air cleaner in smallsized crowd facilities. As the results, the removal efficiency of PM₁? and TBC were shown as 58% and 70%. And also HCHO and TVOC were shown as 60%, 70%. The statistic result of correlation analysis between incipient PM₁? concentration (no-air cleaner) and after 3 days (apllied air cleaner) PM₁? concentrations were significantly shown as correlated. And the result of correlation analysis between incipient TBC, HCHO, TVOC concentrations (no-air cleaner) and after 3 days TBC, HCHO, TVOC concentrations (appllied air cleaner) were significant shown as correlated. In these results, we suggest that air cleaners applied on small-sized crowd facilities can help to reduce of indoor air pollutants as effectively
이동통신 자료를 활용한 거시적 교통사고 예측 모형 개발
곽호찬 ( Ho-chan Kwak ),송지영 ( Ji Young Song ),이인묵 ( In Mook Lee ),이준 ( Jun Lee ) 한국안전학회(구 한국산업안전학회) 2018 한국안전학회지 Vol.33 No.4
Macroscopic accident analyses have been conducted to incorporate transportation safety into long-term transportation planning. In macro-level accident prediction model, exposure variable(e.g. a settled population) have been used as fundamental explanatory variable under the concept that each trip will be subjected to a probable risk of accident. However, a settled population may be embedded error by exclusion of active population concept. The objective of this research study is to develop macro-level accident prediction model using floating population variable(concept of including a settled population and active population) collected from mobile phone data. The concept of accident prediction models is introduced utilizing exposure variable as explanatory variable in a generalized linear regression with assumption of a negative binomial error structure. The goodness of fit of model using floating population variable is compared with that of the each models using population and the number of household variables. Also, log transformation models are additionally developed to improve the goodness of fit. The results show that the log transformation model using floating population variable is useful for capturing the relationships between accident and exposure variable and generally perform better than the models using other existing exposure variables. The developed model using floating population variable can be used to guide transportation safety policy decision makers to allocate resources more efficiently for the regions(or zones) with higher risk and improve urban transportation safety in transportation planning step.
송지영(Jiyoung Song),곽호찬(Ho-Chan Kwak) 한국도시철도학회 2020 한국도시철도학회논문집 Vol.8 No.2
유동인구는 실제 사람들의 이동을 파악할 수 있는 자료로, 도시철도 건설 및 운영 계획 수립에 중요한 기초자료로 활용될 수 있다. 하지만 현재 유동인구 자료는 사후 구득만이 가능해 장래 개발계획 등에는 활용도가 낮은 실정이다. 이에 본 연구에서는 도시 및 인구 특성을 나타내는 사회경제지표를 활용하여 이동통신 자료 기반의 유동인구를 예측하기 위한 모형을 구축하였다. 모형 구축을 위해 2013년 12월 서울시 6개 구를 대상으로 수집된 유동인구 자료를 활용하여 회귀모형을 구축하였으며, 모형 구축 결과 사회경제지표 중 세대수와 종사자수 변수가 유동인구 예측에 통계적으로 유의성이 높은 것으로 나타났다. 또한 최종 모형의 적합도 분석 결과, R2이 0.97로 나타나해당 모형은 유동인구 예측에 활용도가 높을 것으로 사료된다. The floating population that is index to figure out urban mobility will be important in urban railway planning and operation. This study aims to estimate the model to predict floating population based on mobile phone data using socio-economic index. The floating population data that was collected at 6 districts in Seoul in December 2013 is used as dependent variable, and the linear regression analysis is used in modelling. The final model using the number of households and the number of employees showed good performance in urban floating population prediction as R2=0.97.