• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.479-487
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• 1998

현재 도로화물운송을 분석하는데 가장 많이 사용되는 지표는 수송톤(ton)과 톤-키로(ton-km)이다. 하지만 이러한 두 지표는 도로화물운송체계를 설명하기보다는 단순히 운송실적을 나타내는 통계지표이다. 따라서 본 연구에서는 한국의 도로화물운송체계를 설명할 수 있는 운송단계, 총 운송거리, 순물동량, 평균운송거리 등의 4개 요소를 추정하였다. 그리고 한국의 도로화물 운송체계의 문제점을 진단하기 위하여 외국이 도로화물운송체계와 비교분석하였다. 본 연구에서 발견된 주요결과는 (1) 한국과 대만은 운송단계와 총 운송거리가 증가하고 평균운송거리는 감소하는 추세를 보였고, (2) 한국과는 대조적으로, 미국, 일본, 네덜란드는 운송단계와 총 운송거리는 감소하고 평균운송거리는 증가하는 변화추세를 보였으며, (3) 시계열 분석결과, 운송단계의 증가는 GDP대비 물류비와 운송비를 증가시키고 운송단계의 감소는 GDP대비 물류비와 운송비를 감소시키는 것으로 나타났다. 본 연구결과, 한국의 도로화물운송체계는 운송단계를 증가시키는 비효율적인 방향으로 진행되어왔고 이러한 운송단계의 증가는 GDP대비 물류비를 증가시키는 주요 원인임을 알 수 있었다. 따라서 한국의 도로화물운송체계를 개선시키기 위해서는 지능형 화물운송체계의 구축, 복합기능의 화물거점시설 확충, 화물자동차 운송업의 규제완화, 기업물류관리의 선진화 등의 정책을 통하여 불필요한 운송단계의 단축이 필요하다.

• Journal of Korean Society of Forest Science
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• v.97 no.6
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• pp.611-616
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• 2008

The investigation was accomplished on the test area in Forest Practice Research Center in order to compare Point Grid method with Bufferring method in process of the calculation of the Actual Mean Skidding Distance with the GIS aided harvesting method. the investigation site amounted to 264.9 ha in area and 32.67 m in the road density, 306.1 m in road spacing. the Net Correction Factor (Kn) was 1.53 in both sides skidding. the theoretical mean skidding distance was 72.52 m. the shortest mean skidding distance amounted to 149.57 m with point grid method and 139.68 m with Buffering methode. skidding distance correction factor (Kr) was 2.15. actual mean skidding distance amounted to 251.51 m and factor of wood assortment skidding (Kg) was 3.29. when the tractor (Dongyang) and tower yader (Koller 303) are used on investigation site, the logging cost is calculated 11,808 Won with Tractor below 25% slope and 12,336 won with Tractor between 25~55% slope, 10,020 won with Tower Yarder more than 55% slope.

• Korean Journal of Environment and Ecology
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• v.15 no.2
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• pp.99-102
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• 2001

본 연구는 번식기와 비번식기에 있어서 까치의 행동변화를 파악하기 위해 강원도 춘천시 동면 감정리에 위치한 강원도 산림개발연구원 시험림 및 부근지역에서 2000년 3월부터 2001년 2월까지의 기간동안 실시되었다. 조사지 내 전체 면척은 5.6$\textrm{km}^2$였으며, 전체 지역에서 까치의 둥지는 모두 49개가 발견되었다. 이중 2000년 봄철의 번식기동안에는 24개의 둥지에서 까치가 번식을 한 것으로 나타났다. 까치의 번식밀도는 4.3쌍/$\textrm{km}^2$였으며, 둥지의 평균거리는 평균 357.5m 인 것으로 나타났다. 까치에 부착한 전파발신기에서 발신되는 전파를 추적하여 번식기와 비번식기에 둥지로부터 이동한 거리는 큰 차이를 보였다.(t-test, t= 2.98, P<0.01). 번식기에는 평균 133.5m의 거리를 둥지로부터 이동하였으며, 최대 184m 이동한 것으로 나타났다. 그 결과 세력권의 크기는 약 5.6ha인 것으로 추정되었다. 또한 비번식이에 있어서는 둥지로부터의 이동거리 평균 384.2m 였으며, 최대 457m 까지 이동하였다. 6월에서 8월 까지는 보통 2~3개체 정도가 무리를 형성하였고, 12월에 가장 많은 12개체 정도가 하나의 무리를 이루었다. 번식기에 암컷과 수컷을 행동은 매우 다른 것으로 나타났으나(t=2.89, P<0.05)비번식기에는 큰 차이가 없었다(t=1.03, P>0.05).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.137-143
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• 1999

The straight spatial distance or geodesic distance on WGS84 ellipsoid measured by GPS should be reduced on geoid to be used in Korean Geodetic System. The factors for this reduction are geoidal height and mean radius of the earth. On this study the effects of these factors on reducing distance were analyzed and the result showed that mean geoidal height should be multiplied by $1.6\times{10}^{-7}$ per unit distance for reducing geodesic distance on reference ellipsoid to that on geoid. Condsidering that the geoidal height on Bessel ellipsoid in Korea is -45 m in northeast and -75 m in middle west. It also showed that the difference of geodesic distance between on reference ellipsoid and on geoid is about 7-12 mm per km.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.3011-3016
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• 2015

Representing protein three-dimensional structure by concatenating a sequence of protein fragments gives an efficient application in analysis, modeling, search, and prediction of protein structures. This paper investigated the effective combination of distance measures, which can exploit large protein structure database, in order to construct a protein fragment library representing native protein structures accurately. Clustering method was used to construct a protein fragment library. Initial clustering stage used inter alpha-carbon distance having low time complexity, and cluster extension stage used the combination of inter alpha-carbon distance, Binet-Cauchy distance, and root mean square deviation. Protein fragment library was constructed by leveraging large protein structure database using the proposed combination of distance measures. This library gives low root mean square deviation in the experiments representing protein structures with protein fragments.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.137-145
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• 2014

This paper suggests an LDA-based long distance face recognition algorithm for intelligent surveillance system. The existing face recognition algorithm using single distance face image as training images caused a problem that face recognition rate is decreased with increasing distance. The face recognition algorithm using face images by actual distance as training images showed good performance. However, this also causes user inconvenience as it requires the user to move one to five meters in person to acquire face images for initial user registration. In this paper, proposed method is used for training images by using single distance face image to automatically create face images by various distances. The test result showed that the proposed face recognition technique generated better performance by average 16.3% in short distance and 18.0% in long distance than the technique using the existing single distance face image as training. When it was compared with the technique that used face images by distance as training, the performance fell 4.3% on average at a close distance and remained the same at a long distance.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.94-103
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• 2008

In this paper, we adapt the $\kappa$-means clustering technique to segmenting a given 3D mesh. In order to avoid the locally minimal convergence and speed up the computing time, first we extract sharp vertices from the mesh by analysing its curvature and convexity that respectively reflect the local and global geometric characteristics from the viewpoint of cognitive science. Next the sharp vertices are partitioned into $\kappa$ clusters by iterated converging with the $\kappa$-means clustering method based on the geodesic distance instead of the Euclidean distance between each pair of the sharp vertices. For obtaining the effective result of $\kappa$-means clustering method, it is crucial to assign an initial value to $\kappa$ appropriately. Hence, we automatically compute a reasonable number of clusters as an initial value of $\kappa$. Finally the mesh segmentation is completed by merging other vertices except the sharp vertices into the nearest cluster by geodesic distance.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.443-446
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• 2000

본 연구는 과학적이고 실험적인 접근을 통하여 공간의 비례와 실내음향과의 상관관계를 규명하기 위하여 체적과 마감재료가 같고 비슷한 기본축척의 모델을 중심으로 가로, 세로, 높이의 비율이 다른 4개의 모델에서 각각 SPL, EDT, C, RT, LEF, IACC 등을 측정하여 각 형태의 모델의 값을 비교 분석하였다. 실험결과 잔향은 동일한 체적인 경우 음원으로부터 평균거리가 멀리 위치한 장방형의 형태가 양쪽 측벽 사이의 거리가 넓은 장방형보다 잔향시간이 긴 것으로 나타났다. 음압은 실의 체적이 작고 음원으로부터의 평균거리가 짧은 순서로 큰 반면, 명료도는 잔향의 크기순서에 반대로 분석되었으며 특히 음원으로부터의 직선거리가 짧은 순서로 명료도가 좋게 나타났다. IACC는 양쪽 측벽의 거리가 가장 긴 모델에서 가장 작게 나타났다 그러나, 초기 음장에서는 그 변화가 작게 나타났는데 이것은 IACC가 실의 형태에 장시간 관여하는 지수라는 것을 의미한다.

• Current Research on Agriculture and Life Sciences
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• v.19
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• pp.45-54
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• 2001

This study was carried out to provide fundamental data for prospective forest-road project and forest-road network arrangement through appraising existing forest-road network with density, extension distance, maximum yarding distance and yarding area, position of forest-road line considered above foundation of two theories, one is "theory of optimal forest-road density" which has expense for yarding cost and constructing forest-road minimized, the other is "theory of optimal forest-road arrangement" which has investment effect maximized. The results are as follows. 1. In density and extension distance of the forest-road by site, it was showed up that density of existing forest-road is lower than that of calculated forest-road. So, it is thought that some additional forest-roads have to be constructed. 2. In the arrangement of the forest-road network by site, it was showed up that the arrangement of calculated forest-road is higher than that of existing forest-road arrangement for the forestry and yarding function. So, it is thought that the arrangement of forest-road network have to be considered to maximize the investment effect. 3. In "mean maximum distance for yarding" and "mean area which yarding can be done" by horizontal and inclined distance, the existing forest-road networks were different from those of calculated forest-road network. So, calculated forest-road network making investment effect maximize is more effective than existing forest-road network. Hence, in prospective forest-road project, it is needed that forest-road network having "area which yarding can be done" maximized through considering function for yarding have to be constructed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.595-605
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• 2012

DV-Hop is one of the well known range-free localization algorithms. The algorithm works well in case of isotropic network since the sensor and anchor nodes are placed in the entire area. However, it results in large errors in case of anisotropic networks where the hop count between nodes is not linearly proportional to the Euclidean distance between them. Hence, we proposed a novel range-free algorithm for anisotropic networks to improve the localization accuracy. In the paper, the Euclidean distance between anchor node and unknown node is estimated by the average hop distance calculated at each hop count with hop count and distance information between anchor nodes. By estimating the unknown location of nodes with the estimated distance estimated by the average hop distance calculated at each hop, the localization accuracy is improved. Simulation results show that the proposed algorithm has more accuracy than DV-Hop.