• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.178-182
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• 2007

In this study, we evaluated current raingauge network of Soyanggang dam region applying spatial-correlation analysis and Entropy theory to recommend an optimized raingauge network. In the process of analysis, correlation distance of raingauge stations is estimated and evaluated via spatial-correlation method and entropy method. From this correlation distances, respective influencing radii of each dataset and each methods is assessed. The result of correlation and entropy analysis has estimated correlation distance of 25.546km and influence radius of 7.206km, deducing a decrease of network density from $224.53km^2$ to $122.47km^2$ which satisfy the recommended minimum densities of $250km^2$ in mountainous regions(WMO, 1994) and an increase of basin coverage from 59.3% to 86.8%. As for the elevation analysis the relative evaluation ratio increased from 0.59(current) to 0.92(optimized) resulting an obvious improvement.

• 조명전기설비학회논문지
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• 제20권9호
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• pp.45-53
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• 2006

This paper proposes a method for an effective intelligent route decision for automatic moving robots(AMR) using a 2D spatial map of a stereo camera system. In this method, information about depth and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle is detected, and a 2D spatial map is obtained from the location coordinates. Then the relative distances between the obstacle and other objects are deduced. The robot move automatically by effective and intelligent route decision using the obtained 2D spatial map. From experiments on robot driving with 240 frames of stereo images, it was found that the error ratio of the calculated distance to the measured distance between objects was very low, 1.52[%] on average.

• International Journal of Internet, Broadcasting and Communication
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• 제8권4호
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• pp.54-57
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• 2016

In this paper, the method for an effective and intelligent route decision of the automatic ground vehicle (AGV) using a 2D spatial map of the stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle detected and the 2D spatial map obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The AGV moves automatically by effective and intelligent route decision using the obtained 2D spatial map. From some experiments on robot driving with 480 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 1.57% on average, respectably.

• 정보처리학회논문지B
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• 제10B권4호
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• pp.411-418
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• 2003

본 논문에서는 모바일 단말기에 부착되어 있는 카메라를 통하여 입력되는 차량의 전, 후면의 번호판을 자동으로 인식, 검증하는 기술을 바탕으로 차량 번호를 검출하고 무선 통신망을 통해 원격 서버에 차량 번호와 모바일 단말기의 위치 정보를 함께 전송함으로써 어디에서든지 차량 조회 및 차량 위치 추적을 위한 시스템을 제안한다. 모바일 단말기에서 획득된 차량의 정보는 부호화되어 무선 통신망을 통하여 원격지의 서버로 전송된다. 원격지의 서버는 복호화 과정을 거쳐 전송된 텍스트 형식의 차량 번호와 위치 정보는 실시간 추정한 공간상관거리를 통하여 가용자의 위치를 측정하기 위해 공간정보와 속성 정보를 갖는 수치 값들 가운데 원하는 데이터 값에 가장 우선하는 특성 정보를 통해 적합한 위치를 추적이 가능한 임베디드형 이동 가능한 차량 번호판 인식 시스템을 구현한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2737-2753
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• 2013

In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

• 방송공학회논문지
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• 제27권7호
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• pp.974-984
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• 2022

In this paper, we introduce the minimum and maximum distance setting methods used in geometric distance attenuation processing, which is one of spatial sound reproduction methods. In general, sound attenuation by distance is inversely proportional to distance, that is 1/r law, but when the relative distance between the user and the audio object is very short or long, exceptional processing might be performed by setting the minimum distance or the maximum distance. While MPEG-I Immersive Audio's RM0 uses fixed values for the minimum and maximum distances, this study proposes effective methods for setting the distances considering the signal gain of an audio object. Proposed methods were verified through simulation of the proposed methods and experiments using RM0 renderer.

• 대기
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• 제30권2호
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• pp.169-181
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• 2020

We conducted a study on the impact of observation station density; this was done in order to enable the accurate estimation of spatial meteorological variables. The purpose of this study is to help operate an efficient observation network by examining distributions of temperature, relative humidity, and wind speed in a test area of a three-dimensional meteorological observation project in the Yeongdong region in 2019. For our analysis, we grouped the observation stations as follows: 41 stations (for Step 4), 34 stations (for Step 3), 17 stations (for Step 2), and 10 stations (for Step 1). Grid values were interpolated using the kriging method. We compared the spatial accuracy of the estimated meteorological grid by using station density. The effect of increased observation network density varied and was dependent on meteorological variables and weather conditions. The temperature is sufficient for the current weather observation network (featuring an average distance about 9.30 km between stations), and the relative humidity is sufficient when the average distance between stations is about 5.04 km. However, it is recommended that all observation networks, with an average distance of approximately 4.59 km between stations, be utilized for monitoring wind speed. In addition, this also enables the operation of an effective observation network through the classification of outliers.

• 인지과학
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• 제25권2호
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• pp.109-133
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• 2014

관찰자가 대상이나 상황에 관해 느끼는 주관적인 간극을 심리적 거리라고 한다. 심리적 거리는 개인이 그 대상과 상황에 대해 취하는 의사결정과 행위에 영향을 끼친다. 본 연구는 친숙감의 수준이 심리적 거리의 형성에 끼치는 효과를 탐색하였다. 친숙한 자극이 덜 친숙한 자극에 비해 심리적으로 더 가깝게 느껴진다면, 자극이 유발하는 친숙감 수준이 자극의 지각된 공간적 거리와 상호작용할 것으로 예상하였다. 각 실험에서 참가자들은 먼저 사전 노출 단계에서 세 개의 무의미 단어를 경험하였다. 선행연구들에 따르면 친숙감은 자극의 노출 횟수와 지각적 유창성(perceptual fluency)의 영향을 받는다. 따라서 참가자들이 단어 판단 과제를 수행하는 동안, 무의미 단어들은 각기 다른 수준의 빈도(실험 1)와 선명도(실험 2)로 제시되었다. 그 다음 단계에서 참가자들은 가장 친숙한 무의미 단어와 가장 덜 친숙한 무의미 단어를 가지고 거리 스트룹 과제를 수행하였다. 각각의 단어들은 깊이 단서가 분명한 장면 사진들 속에서 지각적으로 가깝거나 먼 장소에 출현하였다. 그 결과, 두 실험 모두에서 단어의 친숙감과 공간적 거리 간 상호작용이 유의미하였다. 친숙한 단어는 가까운 위치에서 제시되었을 때 빠른 판단반응을 유발하였고 상대적으로 덜 친숙한 단어는 먼 위치에서 제시되었을 때 빠른 판단 반응을 유발하였다. 이러한 결과는 친숙감에 대한 상위인지적 평가(metacognitive evaluation)가 심리적 거리의 형성을 뒷받침하는 주요 요인임을 의미한다.

• 환경영향평가
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• 제19권3호
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• pp.223-230
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• 2010

Trajectory dispersion models are used for the dispersion calculations in air quality assessments, Yellow-sand modeling, environmental planning and the emergency response. Meso-scale forcing and coastal circulations are calculated by trajectory model in the East Asia region. In this study the meteorological fields (GDAS and MM5) coupled to the trajectory model (HY-SPLIT) are applied to simulate the transport and the dispersion. Seoul is selected as a starting point of the HY-SPLIT. The sensitivity studies are performed by conducting an ensemble of simulations using the GDAS and the MM5 model for the same dispersion cases. The results in this study show a significant difference depending on the resolution of meteorological models. Additionally, in most cases of the compared tionally,results from MM5 and GDAS, the absolute and relative distance, shows significant difference and the difference increased with the increasing distance of HY-SPLIT. Therefore, for the case of small domai for twi d field distefbution over complex terrai, should be used only high model temporal or spatial resolution to improve the HY-SPLIT model results.

• 한국멀티미디어학회논문지
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• 제6권3호
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• pp.375-383
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• 2003

공간 마이닝에서 클러스터링은 오브젝트간의 거리나 연결 상태, 또는 공간상에서의 상대적인 밀도를 기반으로 서로 비슷한 오브젝트들을 하나의 그룹으로 묶는 과정이다. 실세계에서 공간 상에 분포하는 강이나 호수, 고속도로와 같은 장애물들은 클러스터링의 결과에 영향을 줄 수 있다. 본 논문은 장애물을 고려한 오브젝트 사이의 거리를 정의하고, 이를 이용하여 공간 오브젝트들을 밀도를 기반으로 클러스터링 하면서 동시에 공간상에 존재하는 장애물을 고려하는 새로운 공간 클러스터링 알고리즘(DBSCAN-O)을 제안한다. 또한 실험을 통해 DBSCAN-O가 기존의 밀도 기반 알고리즘인 DBSCAN에서 찾아내지 못한 새로운 형태의 클러스터링 결과를 도출하는 것을 보인다.