• The Korean Journal of Applied Statistics
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• v.1 no.1
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• pp.57-67
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• 1987

In time series analysis, we usually require the assumption that time series are stationary. But we may often encounter time series whose parameter values subject to change. Inthis paper w propose a method which can detect the variance change point in anAR(1) model which is subjct to changesat non-predictable time points. Proposed method is compared with other methods using the simulated and real data.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.149-157
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• 2006

Turbo code, a kind of error correction coding technique, has been used in the field of digital mobile communication system. As the number of iterations increases, it can achieves remarkable BER performance over AWGN channel environment. However, if the number of iterations is increased in the several channel environments, any further iteration results in very little improvement, and requires much delay and computation in proportion to the number of iterations. To solve this problems, it is necessary to device an efficient criterion to stop the iteration process and prevent unnecessary delay and computation. In this paper, it proposes an efficient and simple criterion for stopping the iteration process in turbo decoding. By using variance values of LLR in turbo decoder, the proposed algerian can largely reduce the average number of iterations without BER performance degradation in all SNR regions. As a result of simulation, the average number of iterations in the upper SNR region is reduced by about $34.66%{\sim}41.33%$ compared to method using variance values of extrinsic information. the average number of iterations in the lower SNR region is reduced by about $13.93%{\sim}14.45%$ compared to CE algorithm and about $13.23%{\sim}14.26%$ compared to SDR algorithm.

• Journal of the Korean housing association
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• v.14 no.3
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• pp.9-18
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• 2003

This study is designed to explore the relationship between the level of housing satisfaction and housing values, as well as family characteristics and characteristics of residence. Questionnaires are administered to 526 adolescents from the four residential areas in Kwangju. Most of the adolescents are satisfied with their housing environment, especially indoors, however, they show a lower level of satisfaction toward the appearance and organization of the unit plan. It is found that the level of the safety, comfortability and social values predicted a meaningful variance in the level of housing satisfaction. Those with a higher degree of safety and social values tend to be associated with stronger housing satisfaction, whereas those with lower comfortability values are more associated with stronger housing satisfaction. Groups with higher household incomes are more likely to be satisfied with their housing environment. Groups living within a younger and larger house are more likely to be satisfied with their housing environment. Also, owners tend to show a stronger degree of housing satisfaction than renters.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.649-653
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• 2005

To estimate for an error signal with sigmoid nonlinearity what reduced constellation applies closed eye pattern in the initial equalization, there can be improves problems of previous soft decision-directed algorithm that increasing estimate complexity and decreasing of convergence speed when substitute high-order constellation. The characteristic of sigmoid function is adjusted by a mean and a variance parameter, so it depends on adjustment of variance that what reduced constellation $values(\gamma)$ can have ranges between + $\gamma$ and - $\gamma$. In this paper, we proposed Variable Modulus Algorithm (VMA) that can be improving a performance of steady-state by adjustment of variance when equalization works normally and each cluster of constellation decrease.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1835-1838
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• 2003

Texts in natural images contain significant and detailed informations about the images. Thus, to extract those texts correctly, we suggest a text extraction method using color variance feature. Generally, the texts in images have color variations with the backgrounds. Thus, if we express those variations in 3 dimensional RGB color space, we can emphasize the text regions that can be hard to be captured with a method using intensity variations in the gray-level images. We can even make robust extraction results with the images contaminated by light variations. The color variations are measured by color variance in this paper. First, horizontal and vertical variance images are obtained independently, and we can fine that the text regions have high values of the variances in both directions. Then, the two images are logically ANDed to remove the non-text components with only one directional high variance. We have applied the proposed method to the multiple kinds of the natural images, and we confirmed that the proposed feature can help to find the text regions that can he missed with the following features - intensity variations in the gray-level images and/or color continuity in the color images.

• Journal of Ginseng Research
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• v.9 no.1
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• pp.9-14
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• 1985

The aerial parts, stem diameter, stem length, Petiole length, leaf length and leaf width were investigated to estimate coefficient of variability in ginseng at 2 to 4 years grown under the conventional and improved shadings. C.V values of characters such as stem length, petiole length, leaf length and leaf width were decreased with increasing the plant age, while that of steam diameter was increased. C.V. values of aerial part characters were higher in conventional shading than in improved shading, and the variance of c.v. was not significant when above 20 plants were investigated.

• International Journal of Reliability and Applications
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• v.8 no.1
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• pp.1-16
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• 2007

In this paper, we derive exact explicit expressions for the triple and quadruple moments of the lower record values from inverse the Weibull (IW) distribution. Next, we present and calculate the coefficients of the best linear unbiased estimates of the location and scale parameters of IW distribution (BLUEs) for different choices of the shape parameter and records size. We then use the higher order moments and the calculated BLUEs to compute the mean, variance, and the coefficients of skewness and kurtosis of certain linear functions of lower record values. By using the coefficients of the skewness and kurtosis, we develop approximate confidence intervals for the location and scale parameters of the IW distribution using Edgeworth approximate values and then compare them with the corresponding intervals constructed through Monte Carlo simulations. Finally, we apply the findings of the paper to some simulated data.

• Journal of the Korean Statistical Society
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• v.10
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• pp.91-96
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• 1981

The development of Minimum Norm Quadratic Unbiased Estimation (MINQUE) has introduced a unified approach for the estimation of variance components in general linear models. The computational problem has been studied by Liu and Senturia (1977) and Goodnight (1978, setting a-priori values to 0). This paper further simplifies the computation and gives efficient and compact computational algorithm for the MINQUE and dispersion matrix in general linear random model.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.735-742
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• 2023

Non-alcoholic fatty liver disease is an independent risk factor for the development of cardiovascular disease, diabetes, hypertension, and kidney disease, and the clinical importance of non-alcoholic fatty liver disease has recently been increasing. In this study, we aim to extract feature values by applying GLCM, a texture analysis method, to ultrasound images of patients with non-alcoholic fatty liver disease. By applying an artificial neural network model using extracted feature values, we would like to classify the degree of fat deposition in non-alcoholic fatty liver into normal liver, mild fatty liver, moderate fatty liver, and severe fatty liver. As a result of applying the GLCM algorithm, the parameters Autocorrelation, Sum of squares, Sum average, and sum variance showed a tendency for the average value of the feature values to increase as it progressed from mild fatty liver to moderate fatty liver to severe fatty liver. The four parameters of Autocorrelation, Sum of squares, Sum average, and sum variance extracted by applying the GLCM algorithm to ultrasound images of non-alcoholic fatty liver disease were applied as inputs to the artificial neural network model. The classification accuracy was evaluated by applying the GLCM algorithm to the ultrasound images of non-alcoholic fatty liver disease and applying the extracted images to an artificial neural network, showing a high accuracy of 92.5%. Through these results, we would like to present the results of this study as basic data when conducting a texture analysis GLCM study on ultrasound images of patients with non-alcoholic fatty liver disease.

• Journal of Korean Society for Atmospheric Environment
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• v.3 no.2
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• pp.53-61
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• 1987

Automatic and manual rain smaplers wre installed at the roof of National Institute of Environmental Research (NIER), and the rain sampling and measurement were conducted during the period April to August 31, 1987. The rain sampling and measurement were carried out in the following manners: The 1st : Acidity and conductivity were measured entirely by automatic rain sampler (continuous measurement) The 2nd : Acidity and conductivity wrer measured in the laboratory with the sample that was taken out of automatic rain sampler. The 3rd : Acidity and conductivity were measured in the laboratory with the sample that was taken out of manual rain sampler. Afterwards, those different measurement values were compared each other and the following conclusions were obtained: 1) The pH of the continous measurement by the automatic sampler was lower than that of the laboratory measurement, and it was reversed in case of the conductivity. 2) The significance was recognized at 5% risk ratio for the population mean of difference of the measurement values of the pH and conductivity from both samples. 3) The significance was not recognized at 5% risk ratio by the analysis of variance by one way layout for the pH and conductivity. 4) The significance was recognized at 5% risk ratio by the analysis of variance by two way layouts for the pH conductivity. 5) The significance was recognized at 5% rrisk ratio for the differences of the pH values obtained by oboth samplers, and no significance was recognized for conductivity. 6) In comparison of the measurement values from the two samplers were shown a good correlation for pH; correlation coefficient (r) = 0.63, and regression equation Y = 0.53X + 2.78. For conductivity, the correlation was also excellent; correlation coefficient (r) = 0.53 and regression equation Y = 0.63X + 5.65.