• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.133-139
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• 2011

Estimation of biomass carbon stock is an important research for estimation of public benefit of forest. Previous studies about biomass carbon stock estimation have limitations, which come from the used deterministic models. The most serious problem of deterministic models is that deterministic models do not provide any explanation about the relevant effects of errors. In this study, the effects of location errors were analyzed in order to estimation of biomass carbon stock of Danyang area using Monte Carlo simulation method. More specifically, the k-Nearest Neighbor(kNN) algorithm was used for basic estimation. In this procedure, random and systematic errors were added on the location of Sample plot, and effects on estimation error were analyzed by checking the changes of RMSE. As a result of random error simulation, mean RMSE of estimation was increased from 24.8 tonC/ha to 26 tonC/ha when 0.5~1 pixel location errors were added. However, mean RMSE was converged after the location errors were added 0.8 pixel, because of characteristic of study site. In case of the systematic error simulation, any significant trends of RMSE were not detected in the test data.

• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.218-227
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• 2017

In this paper, an algorithm to calculate both bearing and distance error for target detection and localization is proposed using the Cramer Rao lower bound to estimate the minium variance of their error in DOA (Direction Of Arrival) estimation. The performance of arrays in detection and localization depends on the accuracy of DOA, which is affected by a variation of SNR (Signal to Noise Ratio). The SNR is determined by sonar parameters such as a SL (Source Level), TL (Transmission Loss), NL (Noise Level), array shape and beam steering angle. For verification of the suggested method, a Monte Carlo simulation was performed to probabilistically calculate the bearing and distance error according to the SNR which varies with the relative position of the target in space and noise level.

• Journal of the Society of Naval Architects of Korea
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• v.33 no.1
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• pp.90-97
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• 1996

The optimal mesh refinement has a meaning that error of the every element is within an allowable level and in uniformly distributed. The adaptive mesh generation may be required to achieve the optimal mesh generation. For the purpose of optimal mesh generation, an error estimation and an adaptive mesh refinement are required. Using the adaptive mesh generation the second finite element analysis is performed with the result of the first analysis. In the process the error estimation is required. In this study the adaptive mesh generation program for triangular element is developed, and for a posteriori error estimation the stress projection approach is considered. It has been found the multigrid technique, where the error estimation and the mesh generation are combined in multi-step of analysis, may be used efficiently in the finite element analysis.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.1-14
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• 2003

In this study, we suggest the method of small area estimation based on the Economically Active Population Survey (EAPS) data in producing unemployment statistics for the local self-government areas (LSGAs) within large areas. The small area estimators considered are design-based indirect estimators such as the synthetic and composite estimators. The jackknife mean square error was used as a measure of accuracy of such small area estimators. The total unemployed and jackknife mean square errors of the 10 LSGAs within the large area of ChoongBuk region are derived from the estimation procedure suggested in this study, using EAPS data of December 2000. The reliability of small area estimators was assessed using the relative bias values and relative root mean square errors of these estimators. We find that under the current Korean EAPS system, the composite estimator turns out to be much more stable than other estimators.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.683-686
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• 1999

이동로봇은 주행성을 가지며 설정된 이동 경로에 따라 목적지까지 자율적으로 이동하기 위해서는 이동로봇의 실제 위치에 대한 정확한 정보가 확보되어야 한다. 정보확보를 위해서 보통 엔코더, 자이로센서, 비젼센서, 레이저 거리등의 센서를 주로 사용한다. 본 연구에서 주행중인 이동로봇의 위치는 상대센서인 엔코더를 통해 측정된 운동변화량과 출발점에서 이동로봇의 위치로부터 자기유도 주행방법에 의해 계산된다. 이들 상대센서는 이동로봇의 실제 이동에 따라 주행거리 및 주행 방향 변화를 항상 측정할 수 있으므로, 전체 주행구간에 걸쳐 이동로봇의 위치를 연속적으로 측정할 수 있다는 장점이 있으나, 상대센서 측정값에 발생된 오차가 위치 평가값이 연속적으로 누적되므로 실제 위치에 대한 오차가 발생하는 단점이 있다. 즉, 바닥의 미끄럼, 요철, 로봇의 요동(Vibration)등 큰 오차의 요인이 된다. 본 연구에서는 위치를 직접 추정하지 않고 엔코드에서 나온 위치오차, Heading 오차, 자체 엔코드오차 그리고, 자이로 오차와 지자기 센서 오차를 Extended Kalman Filter를 통해 추정하여 이 오차를 다시 위치 계산과 Heading에 되돌려 줌으로서 오차를 보정하는 방법을 제시한다.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.55-70
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• 2000

본 논문에서는 내포오차성분을 가지는 패널회귀모형에서 회귀계수에 대하여 다양한 추정량들을 유도하고, 추정량들의 효율성을 모의실험을 통하여 평균제곱오차의 기준에서 비교하였다. 모의실험 결과, 제안된 FGLS 추정량들은 GLS추정량과 효율성에서 서로 큰 차이를 보이지 않았으며, 계산상 더욱 복잡한 ML, REML 추정량 및 MIVQUE와 거의 비슷한 효율성을 보여주었다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06a
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• pp.193-196
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• 1998

본 논문에서는 동영상 부호화에 있어서의 영상 간 중복성을 제거하기 위한 수단으로 사용되는 움직임 추정 방식에 관련된 내용으로 특히 밝기가 변하는 영상에 대해 부호화 성능을 높여 주는 움직임 추정방식에 대해 부호화 제안하였다. 제안한 움직임 추정은 기존의 평균 절대 오차나 평균 제곱 오차를 기반으로 하는 기존의 움직임 추정에 의한 움직임 벡터와 매크로블록 간 오차의 최소 분산을 가지는 움직임 벡터 중 부호화 시 적은 비트를 필요로 하는 움직임 벡터를 이용함으로써 일반 영상에는 기존의 방법과 유사한 부호화 성능을 나타내고, 화면의 밝기가 급격하게 변하는 영상에서는 기존의 방법보다 우수한 부호화 성능을 나타내도록 하는 방법이다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.87-94
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• 2007

Imbalances in focus, luminance and color between stereo Pairs could cause disparity vector estimation error and increment of transmission data. If the distribution of errors in residual image is large, it may influence to lowering of compression performance. Therefore, in this paper, we propose an efficient balancing method between stereo pairs to reduce the effect. For this, we registrated stereo images using a FFT based method to consider the pixels in the occluded region, we eliminated the pixels of blocks which has large error of disparity vector estimation in balancing function estimation. The balancing function has estimated using histogram specification, local information of target image and residual image between stereo images. Experiments show that the proposed method is effective in error distribution, PSNR and disparity vector estimation. We expect that our method can be improving compression efficiency in stereo coding system.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.685-694
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• 1998

임상실험이나 신뢰성공학 분야에서 임의 중단자료를 이용한 비모수적 신뢰도 추정량으로 Kaplan-Meier 추정량과 Nelson형 추정량이 많이 사용되고 있다. 그러나 Nelson형 추정량은 평균제곱오차의 관점에서 Kaplan-Meier 추정량보다 추정능력이 우수한 반면 편의는 신뢰도가 감소함에 따라 양의 방향으로 점증하는 소표본 특성을 갖는다. Nelson형 추정량의 이러한 특성 때문에 신뢰도의 함수로 표현되는 잔여수명 분위수함수 등의 추정시에는 평균제곱오차의 관점에서 Kaplan-Meier 추정량보다 추정능력이 떨어짐을 볼 수 있다. 이러한 점을 고려하여 이 두 추정량을 가중평균으로 통합한 새로운 비모수적 신뢰도 추정량을 제안하고 추정량의 특성을 비교 분석하였다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.155-162
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• 2011

It is using to incident angle estimation technique in order to target estimation in radar. This paper was estimated incident angle estimation for target using adaptive array incident angle and single look error incident angle estimation technique. We estimated signal incident angle of target to removal main lobe and side lobe to adaptive array incident angle technique. It is difficult to correctly target estimation because single look technique increase direction error of signal incident angle. In order to receive a desired target signal must be not almost look error between signal incident angle and look angle. we had decreased to occur a look error using delay time and single look condition to calculation a covariance when incident angle estimate. Through simulation, we show that the proposed incident angle estimation technique improves the performance of target estimation compared to previous method.