• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.473-495
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• 2019

In this paper, a new extension of Lindley distribution has been introduced. Certain characterizations based on truncated moments, hazard and reverse hazard function, conditional expectation of the proposed distribution are presented. Besides, these characterizations, other statistical/mathematical properties of the proposed model are also discussed. The estimation of the parameters is performed through different classical methods of estimation. Bayes estimation is computed under gamma informative prior under the squared error loss function. The performances of all estimation methods are studied via Monte Carlo simulations in mean square error sense. The potential of the proposed model is analyzed through two data sets. A modified goodness-of-fit test using the Nikulin-Rao-Robson statistic test is investigated via two examples and is observed that the new extension might be used as an alternative lifetime model.

• Journal of Korean Society for Quality Management
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• v.25 no.4
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• pp.206-212
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• 1997

This paper considers the problem of estimating parameters and reliability of shared parallel system with two identical components using type II censored system life data. Likelihood functions are derived and maximum likelihood estimates of parameters and reliability are discussed numerically.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.21-32
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• 2008

Flood forecasting is a very important tool as one of nonstructural measures for reduction of flood damages in life and property and its accuracy is also an important factor. However, when we apply the Storage Function Model(SFM) which is mainly used for the flood forecasting system in Korea, the determination of the parameters is very important but it is difficult. So, the parameters have been calibrated by using an empirical formulas and judgement of hydrologist. Hence, in this study we perform the sensitivity analysis to understand the parameter characteristics and establish the ranges of parameters of the SFM. Also we do the parameter calibration by using the optimization techniques and objective functions, and evaluate their performances. Especially, we suggest a method to determine proper parameters by using a objective function which can be obtained from flood events. So, we use the suggested method for parameter estimation and compare the estimated parameters with the previously reported parameters. As a result of the application, the estimated parameters by the suggested method showed better than them from the previously reported parameters.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.1-11
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• 1998

We present somple block methods for blind maximal ratio combining (MRC) based on a maximum likelihood (ML) principle and finite alphabet properties (FAP) inherent in digital communication systems. The methods can provide accurate estimates of channel parameters even with a small subset of data, thus realizing nearly perfect combining. The channel parameters of diversity branches and the data sequence are estimated simultaneously by using an alternating projection technique. Two different methods, that is, (1) Joint combining and data sequence estimation(JC-DSE) method and (2) Pre-combining and blind phase estimation (PC-BPE) method are presented. Efficient initiallization schemes that can assure the convergence to the global optimum are also presented. Simulation results demonstrate the performance of two methods on the symbol error rate (SER) and the estimated accuracy of the channel parameters.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.823-832
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• 2007

In this study, the separation of short and long durations for estimation the parameters of IDF curve is suggested by using Multi-Objective Genetic Algorithm (MOGA). Objective functions are to minimize root mean squared error (RMSE) and relative RMSE between observed and computed values. The criteria for separation are two; the first one is to estimate more precisely the parameters of IDF curve and the second is to make a single IDF curve without non-continuous duration point. For this purpose 22 rainfall recording gauges operated by Korea Meteorological Administration are selected and three IDF curves that are used generally in South Korea are tested. The result shows that the IDF curve developed by Heo et al. (1999) would be the best of three tested IDF curves, and the suggested parameter estimation method using MOGA can compute more reliable parameters compared with empirical regression analysis.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.183-190
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• 2015

Invasive blood pressure (IBP) is measured for the patient's real time arterial pressure (ABP) to monitor the critical abrupt disorders of the cardiovascular system. It can be used for the estimation of cardiac output and the opening and closing time detection of the aortic valve. Although the unexplained inflections on ABP make it difficult to find the mathematical relations with other cardiovascular parameters, the estimations based on ABP for other data have been accepted as useful methods as they had been verified with the statistical results among vast patient data. Previous windkessel models were composed with systemic resistance and vascular compliance and they were successful at explaining the average systolic and diastolic values of ABP simply. Although it is well-known that the blood pressure reflection from peripheral arteries causes complex inflection on ABP, previous models do not contain any elements of the reflections because of the complexity of peripheral arteries' shapes. In this study, to simulate a reflection wave of blood pressure, a new mathematical model was designed with four elements that were the impedance of aorta, the compliance of aortic arch, the peripheral resistance, and the compliance of peripheral arteries. The parameters of the new model were adjusted to have three types of arterial blood pressure waveform that were measured from a patient. It was used to find the relations between the inflections and other cardiovascular parameters such as the opening-closing time of aortic valve and the cardiac output. It showed that the blood pressure reflection can bring wide range errors to the closing time of aortic valve and cardiac output with the conventional estimation based on ABP and that the changes of one-stroke volumes can be easily detected with previous estimation while the changes of heart rate can bring some error caused by unexpected reflections.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.2
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• pp.10-16
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• 2012

Currently, the majority of systems which are non-linear are in need of the correct system equations for controlling and monitoring. Therefore, the correct estimation of parameters is crucial. Generally, parameters are changed due to system deterioration or sudden environmental alterations. Given the limitations of system monitoring unstable controls can arise. In the following paper, the parameter estimation method is proposed using software filters to combat these system instabilities. For dynamic instances, a powerful particle filter is used to control the nonlinear and noisy environments in which they take place. Using a setup simulation comprised of a slider and pendulum, the state variable of noise is obtained. After collecting the data, the proposed algorithm is used to estimate both the state variable and its parameters. Finally, these results are checked with correct parameter estimations to evaluate and verify the algorithms performance.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.856-864
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• 2006

For estimating the minimum discharge to maintain a river, low flow analysis is required and long term runoff records are needed for the analysis. However, runoff data should be estimated to run a hydrologic model for ungaged river basin. For the reason, parameter estimation is crucial to simulate rainfall-runoff events for those basins using Tank model. In this study, only runoff data recorded for dry season are used for parameter estimation, which is different to other methods based on runoff data recorded for wet and dry seasons. The Harmony Search algorithm is used to determine the optimum parameters for Tank model. The coefficient of determination ($R^2$) is served as the objective function in the Harmony Search. In cases that recorded data are insufficient, the recording interval is changed and Empirical CDF is adopted to analyze the estimated parameters. The suggested method is applied to Yongdam dam, Soyanggang dam, Chungju dam and Seomjingang dam basins. As results, the higher $R^2s$ are obtained when the shorter recording interval, the better recorded data quality, and the more rainfall events recorded along with certain rainfall amount is. Moreover, when the total rainfall is higher than the certain amount, $R^2$ is high. Considering the facts found from this study for the low flow analysis, it is possible to estimate the parameters for Tank model properly with the desired confidence level.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.7
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• pp.267-274
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• 2018

This paper describes a head pose estimation method using PTZ(Pan-Tilt-Zoom) camera. When the external parameters of a camera is changed by rotation and translation, the estimated face pose for the same head also varies. In this paper, we propose a new method to estimate the head pose independently on varying the parameters of PTZ camera. The proposed method consists of 3 steps: face detection, feature extraction, and pose estimation. For each step, we respectively use MCT(Modified Census Transform) feature, the facial regression tree method, and the POSIT(Pose from Orthography and Scaling with ITeration) algorithm. The existing POSIT algorithm does not consider the rotation of a camera, but this paper improves the POSIT based on perspective projection in order to estimate the head pose robustly even when the external parameters of a camera are changed. Through experiments, we confirmed that RMSE(Root Mean Square Error) of the proposed method improve $0.6^{\circ}$ less then the conventional method.

• Journal of the Korea Computer Graphics Society
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• v.2 no.2
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• pp.21-28
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• 1996

The nature of complexity of medical images makes them difficult to segment using standard techniques. Therefore the usual approaches to segment images continue to predominantly involve manual interaction. But it tediously consumes a good deal of time and efforts of the experts. Hereby a nonmanual parameters estimation which can replace the manual interaction is needed to solve the problem of redundant manual works for an image segmentation. This paper attempts to estimate parameters for an image region segmentation using Scale Space Filtering. This attempt results in estimating the number of regions, their boundary and each representatives to be segmented 2-dimensionally and 3-dimensionally. Using this algorithm, we may diminish the problem of wasted time and efforts for finding prerequisite segmentation parameters, and lead the relatively reasonable result of region segmentation.