• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.9-18
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• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.75-80
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• 2002

Putnam develops SLIM (Software LIfecycle Management) model based upon the assumption that the manpower utilization during software project development is followed by a Rayleigh distribution. To obtain the manpower distribution, we have to be estimate the total development effort and difficulty ratio parameter. We need a way to accurately estimate these parameters early in the requirements and specification phase before investment decisions have to be made. Statistical tests show that system attributes are highly correlation (redundant) so that Putnam discards one and get a parameter estimator from the other attributes. But, different statistical method has different system attributes and presents different performance. To select the principle system attributes, this paper uses the principle component analysis (PCA) instead of Putnam's method. The PCA's results improve a 9.85 percent performance more than the Putnam's result. Also, this model seems to be simple and easily realize.

• The Journal of the Acoustical Society of Korea
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• v.27 no.7
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• pp.386-393
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• 2008

This paper proposes a new approach for speech enhancement in highly nonstationary noisy environments. The spectral subtraction (SS) is a well known technique for speech enhancement in stationary noisy environments. However, in real world, noise is mostly nonstationary. The proposed method uses an auto control parameter for an adaptive threshold to work well in highly nonstationary noisy environments. Especially, the auto control parameter is affected by a linear function associated with an a posteriori signal to noise ratio (SNR) according to the increase or the decrease of the noise level. The proposed algorithm is combined with spectral subtraction (SS) using a hangover scheme (HO) for speech enhancement. The performances of the proposed method are evaluated ITU-T P.835 signal distortion (SIG) and the segment signal to-noise ratio (SNR) in various and highly nonstationary noisy environments and is superior to that of conventional spectral subtraction (SS) using a hangover (HO) and SS using a minimum statistics (MS) methods.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.129-135
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• 2011

An algorithm is presented for estimating the 3-D location (i.e., azimuth angle, elevation angle, and range) of multiple sources with a uniform circular array (UCA) consisting of an even number of sensors. Recently the rank reduction (RARE) algorithm for partly-calibrated sensor arrays was developed. This algorithm is applicable to sensor arrays consisting of several identically oriented and calibrated linear subarrays. Assuming that a UCA consists of M sensors, it can be divided into M/2 identical linear subarrays composed of two facing sensors. Based on the structure of the subarrays, the steering vectors are decomposed into two parts: range-independent 2-D direction-of-arrival (DOA) parameters, and range-relevant 3-D location parameters. Using this property we can estimate range-independent 2-D DOAs by using the RARE algorithm. Once the 2-D DOAs are available, range estimation can be obtained for each source by defining the 1-D MUSIC spectrum. Despite its low computational complexity, the proposed algorithm can provide an estimation performance almost comparable to that of the 3-D MUSIC benchmark estimator.

• Geotechnical Engineering
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• v.4 no.3
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• pp.19-26
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• 1988

A stochastic numerical model for predictions of differential settlement of foundation Eoils is developed in this Paper. The differential settlement is highly dependent on the spatial variability of elastic modulus of soil. The Kriging method is used to account for the spatial variability of the elastic modulus. This technique provides the best linear unbiased estimator of a parameter and its minimum variance from a limited number of measured data. The stochastic finite element method, employing the first-order second-moment analysis for computations of error Propagation, is used to obtain the means, ariances, and covariances of nodal displacements. Finally, a reliability model of differential settlement is proposed by using the results of the stochastic FEM analysis. It is found that maximum differential settlement occurs when the distance between two foundations is approximately same It with the scale of fluctuation in horizontal direction, and the probability that differential settlement exceeds the allot.able vague might be significant.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.305-317
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• 2006

Outliers adversely affect model identification, parameter estimation, and forecast in time series data. In particular, when outliers consist of a patch of additive outliers, the current outlier detection procedures suffer from the masking and swamping effects which make them inefficient. In this paper, we propose new outlier detection procedure based on high breakdown estimators, called as the dual robust filtering. Empirical and simulation studies in the autoregressive model with orders p show that the proposed procedure is effective.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.493-505
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• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• Journal of Korean Society on Water Environment
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• v.28 no.4
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• pp.538-550
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• 2012

This study suggests a general methodology which is designed for assessing RDOC behavior at the catchment scale by coupling properly a series of steam flow and water quality simulation models and actual monitoring data set. The modified TANK model in which a river routing function is incorporated to the conventional one is applied to simulate the long-term daily stream flow data, and the simulated stream flow data is combined with the 7-parameter log-linear model coupled to the minimum variance unbiased estimator to simulate the long-term daily water quality (BOD, COD and TOC) loads. Finally, the regression analysis between the usually monitored water quality data (BOD, COD and TOC) and RDOC is combined with the simulated water quality data to manifest the spatio-temporal variability of RDOC flux behavior at the Korean TMDL catchment scale.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.1
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• pp.74-82
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• 2011

The Bass model is a cornerstone in diffusion theory which is used for forecasting demand of durables or new services. Three well-known estimation methods for parameters of the Bass model are Ordinary Least Square (OLS), Maximum Likelihood Estimator (MLE), Nonlinear Least Square (NLS). In this paper, a hybrid method incorporating OLS and NLS is presented and it's performance is analyzed and compared with OLS and NLS by using simulation data and empirical data. The results show that NLS has the best performance in terms of accuracy and our hybrid method has the best performance in terms of stability. Specifically, hybrid method has better performance with less data. This result means much in practical aspect because the avaliable data is little when a diffusion model is used for forecasting demand of a new product.

• Journal of Power Electronics
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• v.10 no.5
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• pp.485-490
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• 2010

Sensorless control methods are generally used in motor control for home-appliances because of the material cost and manufactureing standard restrictions. The current model-based control algorithm is mainly used for PMSM sensorless control in the home-appliance industry. In this control method, the rotor position is estimated by using the d-axis and q-axis current errors between the real system and a motor model of the position estimator. As a result, the accuracy of the motor model parameters are critical in this control method. A mismatch of the PMSM parameters affects the speed and torque in low speed, steadystate responses. Rotor position errors are mainly caused by a mismatch of the stator resistance. In this paper, a stator resistance compensation algorithm is proposed to improve sensorless control performance. This algorithm is easy to implement and does not require a modification of the motor model or any special interruptions of the controller. The effectiveness of the proposed algorithm is verified through experimental results.