• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1495-1498
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• 2002

The constrained average method is one of dither methods which combines edge emphasis and grayscale rendition to provide legibility of textual region and proper quality of continuous tone region. How-ever, image quality of continuous tone region is insufficient compared to other dither methods, such as ordered dither methods or the error diffusion method. The constrained average method uses a uniform distribution function to decide number of lit pixels related to the average intensity in a picture area. However, actual distribution of continuous tone region is closer to the Laplacian distribution or triangle distribution. In this paper, we introduce various probability distributions and the actual luminance distribution to decide the threshold value of the constrained average method in order to improve image quality of dithered image.

• 대한전자공학회논문지
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• 제21권3호
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• pp.66-72
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• 1984

본 논문에서는 동일 채널 간섭과 잡음 환경하에서의 L레벨 ASK 및 다상 PSK, APK 시스템의 성능을 오율의 관점에서 구명하였다. ASK 신호와 PSK 신호에 대한 오율식을 이용하여 반송파대 잡음 전력비, 반송파대 간섭파 전력비 및 간섭파의 포락선 분포의 함수로서 APK 시스템의 오율 특성을 밝히고 PSK시스템 및 ASK 시스템, QAM 시스템, APK시스템의 성능을 비교 검토하였다.

• Asian-Australasian Journal of Animal Sciences
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• 제14권7호
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• pp.910-914
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• 2001

The teat number of a sow plays an important role for weaning pigs and has been utilized in selection of swine breeding stock. Various linear models have been employed for genetic analyses of teat number although the teat number can be considered as a count trait. Theoretically, Poisson error mixed models are more appropriate for count traits than Normal error mixed models. In this study, the two models were compared by analyzing data simulated with Poisson error. Considering the mean square errors and correlation coefficients between observed and fitted values, the Poisson generalized linear mixed model (PGLMM) fit the data better than the Normal error mixed model. Also these two models were applied to analyzing teat numbers in four breeds of swine (Landrace, Yorkshire, crossbred of Landrace and Yorkshire, crossbred of Landrace, Yorkshire, and Chinese indigenous Min pig) collected in China. However, when analyzed with the field data, the Normal error mixed model, on the contrary, fit better for all the breeds than the PGLMM. The results from both simulated and field data indicate that teat numbers of swine might not have variance equal to mean and thus not have a Poisson distribution.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 추계학술대회논문집
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• pp.75-78
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• 2004

A mesh generation algorithm adapted to the mesh density map using the Delaunay mesh generation technique is developed. In the finite element analyses of the forging processes, the numerical error increases as the process goes on because of discrete property of the finite elements or severe distortion of elements. Especially, in the region where stresses and strains are concentrated, the numerical discretization error will be highly increased. However, it is too time consuming to use a uniformly fine mesh in the whole domain to reduce the expected numerical error. Therefore, it is necessary to construct locally refined mesh at the region where the error is concentrated such as at the die corner. In this study, the point insertion algorithm is used and the mesh size is controlled by moving nodes to optimized positions according to a mesh density map constructed with a posteriori error estimation. An optimization technique is adopted to obtain a good position of nodes. And optimized smoothing techniques are also adopted to have smooth distribution of the mesh and improve the mesh element quality.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 춘계학술대회 논문집
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• pp.27-31
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• 2003

Underwater acoustic navigation systems are classified into three systems: ultra-short baseline (USBL), short baseline (SBL), and long baseline (LBL). Because the USBL system estimates the angle of a submersible, the estimation error becomes large if the submersible is far from the USBL transducer array mounted under a support vessel. SBL and LBL systems estimate submersible's location more accurately because they have wider distribution of measuring sensors. Especially LBL systems are widely used as a navigation system for deep ocean applications. Although it is most accurate system it still has estimation errors because of noise, measurement error, refraction and multi-path of acoustic signal, or wrong information of the distributed transponders. In this paper the estimation error of the LBL system are analyzed from a point of sensitivity. It is assumed that the error exists only in the distance between a submersible and the transponders. For this purpose sensitivity of the estimated position with respect to relative distances between them is analyzed. The result says that estimation error is small if the submersible is close to transponders but not near the ocean bottom.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.25-25
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• 2023

The ensemble optimal interpolation (EnOI) scheme is a sub-optimal alternative to the ensemble Kalman filter (EnKF) with a reduced computational demand making it potentially more suitable for operational applications. Since only one model is integrated forward instead of an ensemble of model realizations, online estimation of the background error covariance matrix is not possible in the EnOI scheme. In this study, we investigate two Gaussian noise based ensemble generation strategies to produce dynamic covariance matrices for assimilation of water level observations into a distributed hydrological model. In the first approach, spatially correlated noise, sampled from a normal distribution with a fixed fractional error parameter (which controls its standard deviation), is added to the model forecast state vector to prepare the ensembles. In the second method, we use an adaptive error estimation technique based on the innovation diagnostics to estimate this error parameter within the assimilation framework. The results from a real and a set of synthetic experiments indicate that the EnOI scheme can provide better results when an optimal EnKF is not identified, but performs worse than the ensemble filter when the true error characteristics are known. Furthermore, while the adaptive approach is able to reduce the sensitivity to the fractional error parameter affecting the first (non-adaptive) approach, results are usually worse at ungauged locations with the former.

• 대기
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• 제26권3호
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• pp.483-492
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• 2016

We have examined the random error of eddy covariance (EC) measurements on the basis of two-tower approach during daytime. Two EC towers were placed on the grassland with different vegetation density near Gumi-weir. We calculated the random error using three different methods. The first method (M1) is two-tower method suggested by Hollinger and Richardson (2005) where random error is based on differences between simultaneous flux measurements from two towers in very similar environmental conditions. The second one (M2) is suggested by Kessomkiat et al. (2013), which is extended procedure to estimate random error of EC data for two towers in more heterogeneous environmental conditions. They removed systematic flux difference due to the energy balance deficit and evaporative fraction difference between two sites before determining the random error of fluxes using M1 method. Here, we introduce the third method (M3) where we additionally removed systematic flux difference due to available energy difference between two sites. Compared to M1 and M2 methods, application of M3 method results in more symmetric random error distribution. The magnitude of estimated random error is smallest when using M3 method because application of M3 method results in the least systematic flux difference between two sites among three methods. An empirical formula of random error is developed as a function of flux magnitude, wind speed and measurement height for use in single tower sites near Nakdong River. This study suggests that correcting available energy difference between two sites is also required for calculating the random error of EC data from two towers at heterogeneous site where vegetation density is low.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 춘계 학술발표회 논문집
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• pp.1-5
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• 2002

We consider the problem of optimal bandwidth choice for nonparametric classification, based on kernel density estimators, where the problem of interest is distinguishing between two univariate distributions. When the densities intersect at a single point, optimal bandwidth choice depends on curvatures of the densities at that point. The problem of empirical bandwidth selection and classifying data in the tails of a distribution are also addressed.

• Korean Journal of Mathematics
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• 제13권1호
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• pp.113-122
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• 2005

We consider the iterative schemes for the large sparse linear system to solve partial differential equations. Using spectral radius of iteration matrices, the optimal relaxation parameters and good parameters can be obtained. With those parameters we compare the effectiveness of the SOR and SSOR algorithms. Applying Crank-Nicolson approximation, we observe the error distribution according to domain decomposition. The number of processors due to domain decomposition affects time and error. Numerical experiments show that effectiveness of SOR and SSOR can be reversed as time size varies, which is not the usual case. Finally, these phenomena suggest conjectures about equilibrium time grid for SOR and SSOR.

• 대한의용생체공학회:의공학회지
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• 제12권1호
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• pp.43-48
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• 1991

As the computerized methods and equipments In nuclear medicine imaging increases, quantitative information is needed on the single photon emission computed tomographic Images as well as on the conventional nuclear medicine images. In this paper, the authors investigated the effect of several clinician - friendly reconstrution filters on the resultant transverse slices of backprojected Profiles of radioisotope distribution from the Quantitative point of view, and reduced the filter parameters such as cutoff frequency and order of filter which are neces mary to minimize the quantification error using computer-generated phantoms.