• 산업경영시스템학회지
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• 제22권49호
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• pp.125-133
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• 1999

Nonrecurring congestions are generally caused by random or less predictable events, such as accidents, spilled loads stalled or broken-down vehicles that, temporarily reduce the capacity of the freeway. The purpose of this paper is to present the effect of incidents on the traffic congestion on the urban freeway by simulation method. The simulation scenario is composed of two level traffic conditions, two level incident severities, and eight level incident durations. After incident, the recovering duration to the normal traffic flow, increased by linear of incident duration. Total vehicles travel time increased and average travel speed decreased by squares curve of incident duration. Considering incident impacts, incident management system is evaluated the major function of the urban freeway traffic management system. Also, necessary the related research to detect, verify, and develop effective response strategies for traffic incidents.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.34-39
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• 2002

Road information is very important for topographic mapping, transportation application, urban planning and other related application fields. Therefore, automatic detection of road networks from spatial imagery, such as aerial photos and satellite imagery can play a central role in road information acquisition. In this paper, we use least squares correlation matching alone for road center tracking and show that it works. We assumed that (bright) road centerlines would be visible in the image. We further assumed that within a same road segment, there would be only small differences in brightness values. This algorithm works by defining a template around a user-given input point, which shall lie on a road centerline, and then by matching the template against the image along the orientation of the road under consideration. Once matching succeeds, new match proceeds by shifting a matched target window further along road orientation at the target window. By repeating the process above, we obtain a series of points, which lie on a road centerline successively. A 1m resolution IKONOS images over Seoul and Daejeon were used for tests. The results showed that this algorithm could extract road centerlines in any orientation and help in fast and exact he ad-up digitization/vectorization of cartographic images.

• 가정과삶의질연구
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• 제10권2호
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• pp.19-36
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• 1992

The purpose of this paper is to analyze empirically the tendency of household consumption expenditure according to the change of social and economical condition, and the factor which influences consumption expenditure of urban household. The data used in analysis are time-series. The data are statistic form Urban Household Economy Survey published by the Economic Planning Board, dating form the first quarter of 1970 to the fourth quarter of 1989. The income of household and consumption expenditure materials were deflated as consumer price index to exclude the influence of prices and the influence of household composition are considered to deflated as the size of the household under assumption of homogeneity. The consumption expenditure items were categorized to 12 relatively large range items. The time-series data were analyzed by using the Two Stage Least Squares and the Ordinary Least Squares. The following is the result of analysis. 1) Rather than the income increase of previous years. the average income increase for two years influences more significantly on consumption expenditure of household. In the case of influence on consumption expenditure for each item by increase in disposable income, such categories as furniture and utensils. clothing and footwear, housing, medical care, culture and recreation, and transportation and communication have significant influence. 2) Among consumption expenditure categories, the increasing factors were furniture and utensils, and clothing and footwear. And the decreasing factors were housing, medical care, culture and recreation ,and transportation and communication. The relative prices, however, had significant influence on categories such as housing, furniture and utensils, medical care , culture and recreation, and transportation and communication and all of them were the decreation factors. 3) Among with changes of social and economical conditions, miscellaneous showed the highest increase in marginal propensity to consume and foods was the lowest. Also culture and recreation and housing brought up a great change of the income elasticity of demand.

• 한국안전학회지
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• 제37권4호
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• pp.80-91
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• 2022

The purpose of this study is to contribute to strengthening the response of local governments to the emergence of new infectious diseases by identifying the urban characteristics affecting their spread. To this end, the urban characteristics influencing the spread of infectious diseases were identified from previous studies. Moreover, the variations in the impact of urban characteristics that affected the number of confirmed COVID-19 patients was spatially analyzed using geographically weighted regression (GWR). The analysis indicated that the explanatory power of the GWR was approximately 12.4% higher than that of the ordinary least squares method. Moreover, the explanatory power of the model in the northern regions, such as Seoul, Gyeonggi, and Gangwon, was particularly high, indicating that the urban characteristics affecting the spread of COVID-19 vary by region. The results of this study can be used as a basis for suggesting the formulation of customized policies reflecting the characteristics of each local government rather than a uniform spread reduction policy.

• 한국산림과학회지
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• 제95권5호
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• pp.591-594
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• 2006

To have better urban forests in future we are focusing on two major issues like other countries. How we could have more urban forest-quantitative approach-against the expanding of urbanization, and how we could produce better urban forest-qualitative approach-to give a chance in contact with better nature for urban people. Prime surveys on urban forests have been carried out in 6 major cities since 1991, and the city of Daegu which is located on the east southern area of Korea have been case studied for qualitative approaches during last 3 years. Major species of the remnant forests were Pinus densiflora, Pinus rigida, Pinus thunbergii and Robinia pseudoacacia. Approximately 20% of the surveyed forests were lost their structure as forests caused by illegal farming, facilities and as the bare ground by excessive visitors. Generally speaking the condition of forests for biotope was very poor in overall. From two years data of monitoring of birds, we found that wooded parkways and woodland squares had more species than street tree areas. Nests were found mainly on the branch of Zelkova serrata, Pinus densiflora and Quercus myrsinaefolia. The size of urban forests mainly determined the species richness of birds. According to the oxygen output and carbon input by photosynthesis measurement, the capability was in order of Platanus occidentalis, Zelkova serrata and Ginko biloba. Air conditioning effects of trees through transpiration measurement was found and the quality of forests also related to the reducing of urban heat-island.

• Spatial Information Research
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• 제20권4호
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• pp.1-16
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• 2012

도시열섬 현상은 도심지의 가장 큰 환경문제로 대두되고 있으며, 이는 온도상승, 대기오염, 에너지 수요에 영향을 준다. 이러한 열섬현상에 대하여 많은 건물과 복잡한 공간적/입체적 패턴을 가진 지역의 경우에는 3차원 분석이 전적으로 수행되어야 한다. 본 연구는 2차원자료와 3차원 공간자료를 이용하여 도시열섬 인자를 파악함에 있다. 또한 공간 통계기법을 이용하여 열섬인자들의 공간적 영향력을 추출한다. 따라서, 도시온도의 예측, 3차원 모델의 생성, 도시인자의 추출, 일반회귀모형과 공간회귀모형의 구축을 통하여 본 연구를 수행한다. 결과적으로 3차원 도시인자와 인접한 공간영향력들이 도시열섬 현상에 미치는 효과는 크다는 것을 확인할 수 있다. 이를 바탕으로 도시온도 저감을 위한 정책수립에 방향을 효과적으로 제시할 수 있을 것이다.

• 한국측량학회지
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• 제35권1호
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• pp.31-39
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• 2017

The goal of this study was to efficiently analyze the relationships of the number of thefts with related factors, considering the spatial patterns of theft crimes. Theft crime data for a 5-year period (2009-2013) were collected from Haeundae Police Station. A logarithmic transformation was performed to ensure an effective statistical analysis and the number of theft crimes was used as the dependent variable. Related factors were selected through a literature review and divided into social, environmental, and defensive factors. Seven factors, were selected as independent variables: the numbers of foreigners, aged persons, single households, companies, entertainment venues, community security centers, and CCTV (Closed-Circuit Television) systems. OLS (Ordinary Least Squares) and GWR (Geographically Weighted Regression) were used to analyze the relationship between the dependent variable and independent variables. In the GWR results, each independent variable had regression coefficients that differed by location over the study area. The GWR model calculated local values for, and could explain the relationships between, variables more efficiently than the OLS model. Additionally, the adjusted R square value of the GWR model was 10% higher than that of the OLS model, and the GWR model produced a AICc (Corrected Akaike Information Criterion) value that was lower by 230, as well as lower Moran's I values. From these results, it was concluded that the GWR model was more robust in explaining the relationship between the number of thefts and the factors related to theft crime.

• 지역연구
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• 제8권1호
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• pp.31-50
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• 1992

The aim of this paper is to define major factors influencing land development of each of major uses (residential, commercial, industrial) in the process of rapid urban expansion. The main hypothesis of this study is that land use changing patterns are directed by supply side of land managed to public policies rather than demand side. The graphic analysis is applied to relationships between urban growth and land development process of each use and between land development project managed to public policies and land development process. Public and land development projects and zonning protection seem to be major roles of land supply and main determinants of urban spatial structure. Location factors for land development of each uses are selected in 23 variables. Factor analysis is applied to test correlation between variables in 1971 and 1981. Factor structure between two years is similar, but progressive processing of functional separation is derived such as intensive land use is grouped, different location between residential and industrial use is deep. Dependent variables are standardized to logarithm of land development of each use per unit vacant land in two periods, between 1971 and 1980 year and between 1981 year. Correlation analysis between 6 dependent variables and 23 location factors in each years are applied. Major factors of each use are selected in criteria such as high correlation with dependent variables, low correlation between independent variables and common application in two periods. As the result, major factors for residential land development are Land Readjustment Project (LRP), percent of total zoned area in residential zone, residential floor space density per available area, percent of total area in industrial use; for commercial development is distance to CBD, percent of total area in commercial use, residential floor space density per available area in each year, and volumn rate of industrial use; for industrial use is percent of total area of industrial use is percent of total area of industrial use, Industrial Estate Project (IES), LRP, and distance from CBD. Land development pattern of each use between two periods are slightly different. So 6 equation is derived from appling backward method of regession. Adjusted multiple R squares of all is more than 0.5 and those equation is statistically significant and valuable to assist urban land use forecasting.

• 한국지능시스템학회논문지
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• 제22권3호
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• pp.300-304
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• 2012

본 논문은 리튬 폴리머 배터리 셀의 잔존충전용량을 추정하기 위한 비선형 관측기의 설계방법을 제시한다. 배터리 셀의 동적방정식은 비선형 전압원을 갖는 간단한 RC 전기회로로 모델하고 파라메터는 비선형 최적화기법을 이용하여 구한다. 관측기 이득은 제곱합 분해기법을 사용하여 오차의 동적방정식이 점근적으로 안정하고 추정오차 감소율이 설계자가 지정한 값 이하가 되도록 설계한다. 관측기의 성능을 입증하기 위하여 UDDS 전류 프로파일을 사용한 실험 데이터를 이용하여 모의실험을 수행하였다.

• Smart Structures and Systems
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• 제31권5호
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• pp.501-516
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• 2023

Dynamic irregularity and acceleration of bridges subjected to high-speed trains provide crucial information for comprehensive evaluation of the health state of under-track structures. This paper proposes a novel approach for real-time estimation of vertical track dynamic irregularity and bridge acceleration using deep generative adversarial network (GAN) and vibration data from in-service train. The vehicle-body and bogie acceleration responses are correlated with the two target variables by modeling train-bridge interaction (TBI) through least squares generative adversarial network (LSGAN). To realize supervised learning required in the present task, the conventional LSGAN is modified by implementing new loss function and linear activation function. The proposed approach can offer pointwise and accurate estimates of track dynamic irregularity and bridge acceleration, allowing frequent inspection of high-speed railway (HSR) bridges in an economical way. Thanks to its applicability in scenarios of high noise level and critical resonance condition, the proposed approach has a promising prospect in engineering applications.