• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.47-55
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• 2005

In recent years, the rapid growth of vehicles have increased traffic crashes. Since they can cause the economic losses and have put the life qualify in danger, there should be numerous efforts to reduce traffic crashes. To reduce traffic crashes, this research seeks to improve the safety of intersections by analysing causations of injury severity with Ordered Probability Model. This research applied the Ordered Probit Model, which assumes that ${\epsilon}_i$(random error) is normally distributed, for model calibration and used $p^2$ (likelihood ratio) and $x^2$ (Chi-square) for model selection. The results show that minor road traffic, heavy vehicle rates, major and minor right-turn rates, presence of lightings, speed limits, instructive line for left-turn traffic are significant factors affecting crash severities at signalized intersections.

• Journal of Biomedical Engineering Research
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• v.24 no.3
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• pp.233-239
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• 2003

Falling related injuries are categorized as the most serious and common medical problems experienced by the elderly, hip joint fracture, one of the most serious consequences of falling in the elderly, occurs in only about 1% of falling. Nevertheless, hip fracture accounts for a considerable part of the disability, death, and medical costs associated with falling. In this study, we considered the impact angle and displacement rate in falling as another factor affecting femoral strength. Using a fresh-frozen human femur, we developed system to simulate the falling condition and then conducted the experiments changing the impact angle (0$^{\circ}$, 15$^{\circ}$, 30$^{\circ}$) of proximal femur. Also, in order to analyze the relative risk due to falling to normal situation in proximal femur, we did the static test simulating the two-legged stance condition. The results showed that the change in impact angle affected the strain distribution in proximal femur, and that a large deformation in femoral neck than in other sites. Furthermore despite low impact velocity, a large deformation in proximal femur occurred in the impact test and different strain distribution was observed compare to the static case.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.156-156
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• 2020

가뭄은 다른 자연재해에 비해 진행 속도가 느리고 발생 시작 시기가 명확하지 않다. 또한 피해지역이 광범위하다는 점에서 사회, 경제적 피해와 농업 생산 시스템 및 수확량 등 농업 전반에 걸쳐 직접적인 영향을 미치고 있다. 전지구적 기후변화로 인해 국내의 가뭄 발생빈도는 2000년 이후 증가하고 있으며, 가뭄의 정량적 분석은 선제적 가뭄 대응을 위해 필요하다. 현재 국내에서는 여러 유관기관에서 지상 관측 데이터를 활용하여 가뭄을 모니터링하고, 가뭄 공간 분포 지도를 제공하고 있다. 하지만 지상 관측 데이터를 통한 가뭄 분포 지도는 미계측 지역에 대한 데이터 취득이 어렵고, 지형학적 특성을 고려하지 못하는 한계점이 있다. 이러한 한계점을 보완하기 위해 수자원 및 재해 분야에서 위성영상이 활용되고 있다. 위성영상을 활용한 가뭄 판단 및 예측에는 정규식생지수 (Normalized Difference Vegetation Index, NDVI)가 사용되고 있으며, 식생지수는 가뭄 발생, 진행 등에 있어 즉각적인 반응이 어렵다는 단점이 있다. 본 연구에서는 잠재 증발산과 실제 증발산의 비를 이용해 산정된 위성영상 기반 가뭄 지수인 Evaporative Stress Index (ESI)를 활용하였다. NASA (National Aeronautics and Space Administration)에서 제공하는 ESI는 전지구를 대상으로 5km 해상도로 제공하고 있다. 하지만 국내 가뭄 판단을 위해서는 높은 해상도의 영상이 필요하며, 본 연구에서는 MODIS (Moderate Resolution Imaging Spectroradiometer) 영상을 활용한 ESI의 산정을 통해 해상도의 문제를 개선하고자 한다. 산정한 500m 해상도의 ESI는 기존 5km 해상도의 ESI와 비교 검증하였으며, SPI 및 과거 가뭄 발생 현황 자료를 근거로 ROC (Receiver Operating Characteristics) 분석을 통해 시군 단위 농업가뭄평가의 적용성을 확인하고 한다.

• Journal of the Korean association of regional geographers
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• v.17 no.4
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• pp.432-442
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• 2011

Climatic variables such as temperature and precipitation tend to vary both in space and in time simultaneously. Thus, it is necessary to include space-time autocorrelation into conventional spatial interpolation methods for reliable time-series mapping. This paper introduces and applies space-time variogram modeling and space-time kriging to generate time-series temperature maps using hourly Automatic Weather System(AWS) temperature observation data for a one-month period. First, temperature observation data are decomposed into deterministic trend and stochastic residual components. For trend component modeling, elevation data which have reasonable correlation with temperature are used as secondary information to generate trend component with topographic effects. Then, space-time variograms of residual components are estimated and modelled by using a product-sum space-time variogram model to account for not only autocorrelation both in space and in time, but also their interactions. From a case study, space-time kriging outperforms both conventional space only ordinary kriging and regression-kriging, which indicates the importance of using space-time autocorrelation information as well as elevation data. It is expected that space-time kriging would be a useful tool when a space-poor but time-rich dataset is analyzed.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.63-76
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• 2009

On the basis of a Stochastic Frontier Approach (SFA), this paper analyses revenue efficiencies for the same sample of Korean and Japanese railways in the papers which analyze cost efficiencies using a generalized translog functional form. The paper also compares the results of revenue efficiencies with cost efficiencies and evaluates the effects of managerial autonomy and privatization on the firm-specific efficiencies. The results show that the average estimate of revenue inefficiency is 7.02% when the term of inefficiency is assumed to be distributed as a half-normal and 6.98% as a exponential for the total sample. Also, standardized inefficiencies in revenues (7.5%) are greater than those in costs (2.1%). JR East and JR West are found to be most efficient on the revenue side and on the cost side respectively while JNR and JR Kyushu are worst efficient on the both sides. Finally, the correlations between efficiencies in revenues and costs also between efficiencies and privatization are positively correlated. The results suggest that the most independent companies, with increased managerial autonomy via privatization, are the most efficient in both revenues and costs.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.228-237
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• 2013

In this paper, we propose a normalized cross correlation(NCC)-based multiview background subtraction method which is robust when an object and background have similar color. When the background of the capturing environment is not artificially composed, the regions in the background images which would be occluded by an object tends to have difference colors. The colors of those regions, however, becomes similar when an object enters the capturing environment. Based on this assumption, this paper proposes a concept of GoNCC(Graph of Normalized Cross Correlation). GoNCC is the distribution of NCC between a pixel in an image and pixels related by epipolar constraints with the pixel. The proposed multiview background subtraction method is performed by comparing GoNCC of the current images with the background images. To reduce computational complexity, we perform multiview background subtraction only to the pixels undetermined by single view background subtraction. Experimental results show that the proposed method is more robust to color similarity between an object and background than a single-view background subtraction method and a previous multiview background subtraction method.

• International Area Studies Review
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• v.13 no.3
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• pp.287-308
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• 2009

This article examines the distributional characteristics of the return of Chinese stock market indices. The majority of previous empirical researches have tended to focus upon the simple stock market index. However, this study focuses on the four indices which represent the characteristics of each stock market index. The empirical findings indicate that the returns of the four chinese indices are not normally distributed at conventional levels. The Ljimg-Box -statistics indicate the returns of the index of A shares are not serially autocorrelated. However, the returns of the index of B shares are serially autocorrelated. The empirical findings also indicate returns of the four chinese indices are not serially autocorrelated. The statistics of Regression Specification Error Test and ARCH indicate the returns of all four indices are not serially linear. The findings also indicate that E- GARCH model is the most fittest model for the returns of the four chinese indices and the forecast error can be reduced by using student t distribution rather normal distribution.

• Journal of Life Science
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• v.17 no.9 s.89
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• pp.1217-1223
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• 2007

I investigated the reproduction system of nine natural populations of P. discolor in Korea and two Mongolian P. conferta populations. The measurements of 19 quantitative or qualitative morphological characters were taken on each of total individuals directly from their natural habitats. Multivariate principal component analyses (PCA) were conducted to detect differences among populations consid-ering several characters simultaneously of variances using the statistical analysis system. 19 morpho-logical characteristics between Korean Potentilla species and Mongolian Potentilla species showed a slight heterogeneity of variance. The length of internodes (LFL and LSI) and characteristics of root (LLR and NOR) were shown a significant difference between two species (P<0.05). The number of ra-mets in P. conferta decreased with increasing geographic distance from viviparity. However, P. discolor has most ramets at distance intervals $60{\sim}80$ cm. In light conditions, P. discolor was significantly less resilience than P. conferta. In drought conditions, although there was not shown significant difference, P. conferta was less resilience than P. discolor. The core analysis indicates that P. conferta is the more resistant species than P. discolor and usually propagates by clonal growth during several strong envi-ronmental disadvantages such as drought events.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1692-1700
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• 2009

This paper proposes the direction distribution of surface normal vectors as a feature descriptor of three-dimensional models. Proposed the feature descriptor handles rotation invariance using a principal component analysis(PCA) method, and performs mesh simplification to make it robust and nonsensitive against noise addition. Our method picks samples for the distribution of normal vectors to be proportional to the area of each polygon, applies weight to the normal vectors, and applies interpolation to enhance discrimination so that the information on the surface with less area may be less reflected on composing a feature descriptor. This research measures similarity between models with a L1-norm in the probability density histogram where the distances of feature descriptors are normalized. Experimental results have shown that the proposed method has improved the retrieval performance described in an average normalized modified retrieval rank(ANMRR) by about 17.2% and the retrieval performance described in a quantitative discrimination scale by 9.6%~17.5% as compared to the existing method.

• Journal of Korean Tunnelling and Underground Space Association
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• v.15 no.3
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• pp.253-270
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• 2013

This paper concerns the effect of orientation and geometric characteristics of a fracture zone on the tunnel behavior using a numerical investigation. A parametric study was executed on a number of drill and blast tunnelling cases representing different fracture and tunnelling conditions using two and three dimensional finite element analyses. The variables considered include the strike and dip angle of fracture zone relative to the longitudinal tunnel axis, the width and the clearance of the fracture zone, the tunnel depth, and the initial lateral stress coefficient. The results of the analyses were examined in terms of the tunnel deformation including crown settlement, convergence, and invert heave as well as shotcrete lining stresses. The results indicate that the tunnel deformation as well as the shotcrete lining stress are strongly influenced by the orientation of the fracture zone, and that such a trend becomes more pronounced for tunnels with greater depths.