• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.107-114
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• 2009

Human walking is essential and important mean of transportation. Pedestrian safety is recently important because accidents often happen while walking. This research is showing that Walking-environmental factors have effect on safety while walking. At first, exact 15 factors and conduct survey in the preceding research. After that, exact 4 important factors through factor analysis. At result of Multiple regression analysis, null hypothesis has proved to be true by satisfying therms which is F-value 9.211 and P-value 0.000. and come to the conclusion that walking-environmental factors influence pedestrian safety. 4 important factors can be listed by below. Pedestrian-road characteristic, landscape characteristic, commercial characteristic, walking characteristics by following influence. Especially, landscape characteristic and pedestrian-road characteristic can be vital factors.

• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.418-430
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• 2017

The quality of surface water is a very important issue to use various demands like as drinking water, industrial, agricultural and recreational usages. There has been an increasing demand for monitoring water quality of many rivers by regular measurements of various water quality variables. However precise and effective monitoring is not enough, if the acquired dataset is not analyzed thoroughly. Therefore, the aim of this study was to estimate differences of seasonal and regional water quality using multivariate data analysis for each investing tributaries in Han River. Statistical analysis was applied to the data concerning 11 mainly parameters (flow, water temperature, pH, EC, DO, BOD, COD, SS, TN, TP and TOC) for the time period 2012~2016 from 12 sampling sites. The seasonal water quality variations showed that each of BOD, TN, TP and TOC average concentration in spring and winter was higher than that of summer and fall, respectively. In summer each flow rate and average concentration of SS was higher than any other seasons, respectively. The correlation analysis were explained that EC had a strong relationship with BOD (r=0.857), COD (r=0.854), TN (r=0.899) and TOC (r=0.910). According to principal component analysis, five principal components (Eigenvalue > 1) are controlled 98.0% of variations in water quality. The first component included TP, DO, pH. The second component included EC, TN. The third component included SS. The fourth component included flow. The last component included Temp. Cluster analysis classified that spring is similar to fall and winter with water quality parameters. AnyA, WangsA, JungrA and TancA were identified as affected by organic pollution. Cluster analysis derived seasonal differences with investigating sites and better explained the principal component analysis results.

• Journal of the Korean Society for Marine Environment & Energy
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• v.3 no.4
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• pp.3-22
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• 2000

To know characteristics of water quality in coastal sea around the Keum river estuary in summer, we studied the water quality of surface, middle and bottom level during Jun e～september, 1998. The mean concentrations of COD, DIN, DIP & chlorophyll-a were 1.36mg/L, 28.60㎍-at/L, 0.48㎍-at/L and 4.14㎍/L, respectively, which were over eutrophication criteria in sea water. After the Keum river dyke was constructed, seasonal freshwater discharge was largely changed. About 80% of total annual freshwater discharge was concentrated in summer as rainy season from July to September. The correlation coefficient of DIN versus salinity was shown to be high, and thus the concentration of DIN was closely related to freshwater discharge. Maximum Chlorophyll-a concentration was occurred in September, due to increased DIP concentration, high water temperature and low salinity after heavy rainfall in August. The results of Principal Component Analysis showed that the first factor represented a series of eutrophication factors, the second factor w3s a valiance of seasonal fluctuation, and the third was a variance of progress of mass change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.223-233
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• 2014

This study empirically analyzes the relationships among the road and traffic experts' personal characteristics, the driving behavior and factors being expected to have an effect on the satisfaction about roundabout operation. The factors are drawn and grouped through the principle component analysis to clarify driving environment satisfaction on roundabout operation. Each group is named as personal attribute, driving behavior attribute, and satisfaction. After the variables are refined by confirmatory factor analysis, satisfaction model is developed with personal attribute and driving behavior attributes as exogenous variables and roundabout driving awareness and emotion attributes as endogenous variables. As a result, driving satisfaction of roundabout operation is directly influenced by delay reduction, safety improvement, capacity increase, sight improvement, severity accident reduction, and bicycle convenience and indirectly gender, age, driving time, and driving experience. Law obeyance, driving concession, traffic sign obeyance, and interposition do not statistically shows significant on satisfaction. As a result of Analytical Hierarchy Process (AHP), the turning radius of geometry and the driving behavior are important elements for roundabout safety.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1568-1572
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• 2007

지역빈도해석은 우리나라와 같이 자료 기간이 짧은 경우 지점빈도해석보다 더 정확한 확률강우량을 산정할 수 있는 기법이다. 지역빈도해석을 통한 확률강우량 산정 결과는 수문학적으로 동질한 지역의 구분 결과에 따라 달라진다. 지역을 구분할 때에는 강우에 영향을 미치는 다양한 변수들이 사용될 수 있다. 변수의 유형과 개수가 지역 구분의 효율성을 좌우하기 때문에 활용 가능한 모든 변수들의 정보를 요약할 수 있는 변수들을 선택하는 것이 지역 구분의 효율성 면에서 유리하다고 할 수 있다. 이런 면에서 지역 구분의 효율성을 증대시킬 목적으로 다변량 분석 기법이 활용될 수 있다. 본 연구에서는 주성분 분석, 요인 분석, Procrustes analysis와 같은 다변량 분석 기법을 활용하여 42개의 강우 관련 변수들을 33개의 변수로 줄일 수 있었다. 분석 결과 변수 개수 감소로 인한 정보 손실은 크지 않은 것으로 나타났다. 따라서 이러한 기법에 의한 변수 차원의 축소는 지역 구분의 효율성 향상에 기여할 수 있는 것으로 판단된다. 선정된 변수들을 바탕으로 군집해석을 수행하여 지역을 구분하였고, L-모멘트에 근거한 이질성척도(H)를 활용하여 구분된 지역의 동질성을 검토하였다. 또한 L-모멘트에 근거한 적합성 척도(Z)를 적용하여 구분된 지역에 적합한 확률분포형을 선정하였고, 선정된 적정 확률분포형을 바탕으로 각 지역에 대한 성장 곡선(growth curve)을 유도하였다.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.53-66
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• 2008

This research is to the establishment of a conceptual framework that supports road characteristic classification from a new point of view in order to complement of the existing road functional classification and examine of traffic pattern. The road characteristic classification(RCC) is expected to use important performance criteria that produced a policy guidelines for transportation planning and operational management. For this study, the traffic data used the permanent traffic counters(PTCs) located within the national highway between 2002 and 2006. The research has described for a systematic review and assessment of how exploratory factor analysis should be applied from 12 explanatory variables. The optimal number of components and clusters are determined by interpretation of the factor analysis results. As a result, the scenario including all 12 explanatory variables is better than other scenarios. The four components is produced the optimal number of factors. This research made contributions to the understanding of the exploratory factor analysis for the road characteristic classification, further applying the objective input data for various analysis method, such as cluster analysis, regression analysis and discriminant analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.71-82
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• 2020

The existing transportation system, which is based on internal combustion engines, is rapidly being converted to electrification. Thus, eco-friendly public transportation with high transportation efficiency will continue to spread throughout the market in the near future. The purpose of this study is to compare and analyze the cognitive characteristics of passengers redgarding the technical and social factors of various public transportation means to help a successful introduction of eco-friendly public transit. Through a survey questionnaire (N=485), seven factors of seven transportation modes were evaluated and analyzed using principal component analysis. As a result, it is confirmed that potential passengers have high expectations for the eco-friendliness and city image of the eco-friendly buses. Also, it is confirmed that eco-friendly buses are superior in cleanliness and ride comfort than diesel buses. Given the study's results, this study identifies the cognitive characteristics of passengers regarding eco-friendly public transportation. We hope that these results will be used as basic information for image positioning and improved service with the use of eco-friendly transportation.

• The Journal of Engineering Geology
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• v.23 no.2
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• pp.105-115
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• 2013

Increasing the river cross-section by barrage construction causes rises in the average river water levels and discharge rates in the rainy season. The time series patterns for groundwater levels measured at 23 riverside monitoring wells along the lower Nakdong River are compared for two cases: before and after water-filling at the Changnyeong-Haman Barrage. Monthly average groundwater levels indicate a distinct increase in groundwater levels in the upstream riverside close to the barrage. River-water level management by barrage gate control in August, during the rainy season, resulted in a 0.1 m decrease in groundwater levels, while water-filling at the barrage in December caused a 1.3 m increase in groundwater levels. The results of hierarchical cluster analysis indicate that seven groundwater monitoring wells and river water levels were in the same group before barrage construction, but that this number increased to 14 after barrage construction. Principal component analysis revealed that the explanation power of two principal components corresponding to river fluctuation, PC1 and PC2, was approximately 82% before barrage construction but decreased to 45% after construction. This finding indicates that the effect of the river level component that contributes to change in groundwater level, decreases after barrage construction; consequently, other factors, including groundwater pumping, become more important. Continuous surveying and monitoring is essential for understanding change in the hydrological environment. Water policy that takes groundwater-surface water interaction into consideration should be established for riverside areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.34-34
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• 2016

강우는 우리의 일상생활뿐만 아니라 각종 산업 활동 및 레저스포츠 등 많은 분야에 영향을 주는 중요한 기상 현상이다. 최근 들어 우리나라는 기후변화로 인해 과거 장마기간에 발생하였던 강우집중 현상이 장마기간 전후되어 발생하는 게릴라성 집중호우나 급작스런 이상강우의 형태를 보이고 있으며 그로 인해 홍수 예 경보체계 구축에 대한 중요성이 높아지고 있다. 하지만 우리나라의 경우 홍수 예 경보 체계 및 수공구조물 건설 등이 국가하천 위주로 운영되어 소하천에 대한 연구와 대책이 부족한 실정이다. 최근 이상호우에 의한 홍수피해 사례를 보면 지방하천 혹은 소하천으로부터 발생한 재산 및 인명피해가 크다는 것을 알 수 있으며 이를 관리하기 위한 시스템 구축이 절실한 상황이다. 특히 도시하천의 홍수방재를 위해서는 안정적이고 체계적인 도시하천관리가 필요한데 이를 위해서는 도시하천의 특성을 정확히 파악하는 것이 매우 중요하다. 국내에서 하천의 특성에 관한 연구동향을 살펴보면 대부분의 연구가 하천수질 관점에서 하천특성을 규명하는 목적으로 수행 되었고 홍수 방재를 위한 수문학적인 관점에서의 하천 특성을 도출하는 연구는 미비한 실정이다. 수문학적 관점에서의 하천특성은 유역면적, 도달시간, 형상계수 등 유역특성인자를 말하며 국내 하천에 적용 할 수 있는 대표 유역특성인자를 도출을 위해서는 통계학적인 방법이 필수적이다. 그 중에서도 요인분석, 주성분분석, 군집분석 등 다변량 통계기법을 이용한 분석 필요하다. 본 연구에서는 GIS분석과 지자체에서 제공하는 소하천정비기본계획을 통해 도시하천의 유역특성인자를 선정하고, 수문분야에서의 적용성이 높은 다변량 통계분석기법을 이용하여 우리나라를 대표할 수 있는 도시하천의 특성 및 권역별 도시하천의 특성을 도출하였다. 또한 대조군에 적용하여 도출된 특성의 적정성을 평가하였고 이를 통해 도시하천 관리에 이용될 수 있는 도시하천의 특성을 제시하고자 한다.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.201-211
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• 2013

This study compares Customer Satisfaction Index(CSI) and the weight for each dimension by applying various methods of weight calculation and attempts to suggest some implications. For the purpose, the study classified the methods of weight calculation into the subjective method and the statistical method. Constant sum scale was used for the subjective method, and the statistical method was again segmented into correlation analysis, principal component analysis, factor analysis, structural equation model. The findings showed that there is difference between the weights from the subjective method and the statistical method. The order of the weights by the analysis methods were classified with similar patterns. Besides, the weight for each dimension by different methods of weight calculation showed considerable deviation and revealed the difference of discrimination and stability among the dimensions. Lastly, the CSI calculated by various methods of weight calculation showed to be the highest in structural equation model, followed by in the order of regression analysis, correlation analysis, arithmetic mean, principal component analysis, constant sum scale and factor analysis. The CSI calculated by each method showed to have statistically significant difference.