• Journal of Korean Ophthalmic Optics Society
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• v.1 no.1
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• pp.29-39
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• 1996

We studied the method which would determine the appropriate additive damping factor for the damped least sequres(DLS) optimization. We calculated eigenvalues of the product of the Jacobian matrix of error function by using the singular value decomposition(SVD) method. While suitable damping factor was appiled to the additive DLS by using SVD and Gaussian elimination method, the convergence and stability of the optimization process were examined in a triplet-type camera lens-system where the condition number is well conditioned. We compared the convergence and stability of merit function when median, maximum and minimum of eigenvalues were used as a damping factor in the optimization process. When damping factor is median of eigenvalue, the convergence and stability of merit function are more excellent than in the case of two other eigenvalues. Thus, we adopt the median of eigenvalues as an appropriate damping factor. Next, by using SVD and Gaussian elimination method, we compound the convergence and stability of optimization process for triplet-type camera lens-system design. In these two method; triplet-type camera lens-system in which condition number is well conditioned, has little improvement with the combination of DLS and SVD.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.118-128
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• 2016

As the rural areas have experienced the population reduction and the aging, the service level of public transit decreases. This study analyzes the effecting factor to user satisfaction of demand response transport(DRT) as alternative to rural public transit by the quantile regression that aims at estimating either the conditional median or other quantiles of the response variable. Jeonbuk Province tested DRT operations in Dongsang of Wanju County and Sannae of Jeongup City each in 2015. The user DRT satisfaction of Wanju was higher than one of Jeongup in basic statistics analysis. The difference in satisfaction between higher quantile and lower quntile of Wanju is smaller than one of Jeongupy as a result of quantile regression analysis. Also, Wanju DRT continues the second test operation of DRT as satisfaction from Ordinary Least Squares(OLS) close to higher satisfaction quantile.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.337-346
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• 2001

In this paper we consider the problem of identifying and testing the outliers in linear regression. first we consider the problem for testing the null hypothesis of no outliers. The test based on the ratio of two scale estimates is proposed. We show the asymptotic distribution of the test statistic by Monte Carlo simulation and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure based on the suggested test is proposed and shown to perform fairly well. The forward sequential procedure is unaffected by masking and swamping effects because the test statistic is based on robust estimate.

• Korean Journal of Optics and Photonics
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• v.6 no.3
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• pp.178-187
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• 1995

The method that determines the appropriate damping factor is studied for a lens design. When suitable damping factor is applied to the additive damped least-squares (DLS) method, the convergence and the stability of the optimization process are examined in a triplet-type photographic lens design. We calculate eigenvalues of the product of the Jacobian matrix of error functions by using the singular value decomposition (SVD) method. We adopt the median of eigenvalues as an appropriate damping factor. The convergence and the stability of the optimization process are improved by choosing the adequate damping factor for the optimization of a photographic lens. It is known that the numerical inaccuracy in the calculation of normal equation is overcome by using the orthogonal transformations of the Jacobian matrix. Therefore, a combination of the method for setting a proper damping factor and the orthogonal transformations of the Jacobian matrix is good for application to the design of an aspheric lens with high-order terms. terms.

• Smart Structures and Systems
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• v.31 no.2
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• pp.101-111
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• 2023

Structural health monitoring (SHM) covers a range of damage detection strategies for buildings. In real-time, SHM provides a basis for rapid decision making to optimise the speed and economic efficiency of post-event response. Previous work introduced an SHM method based on identifying structural nonlinear hysteretic parameters and their evolution from structural force-deformation hysteresis loops in real-time. This research extends and generalises this method to investigate the impact of a wide range of flag-shaped or pinching shape nonlinear hysteretic response and its impact on the SHM accuracy. A particular focus is plastic stiffness (K_p), where accurate identification of this parameter enables accurate identification of net and total plastic deformation and plastic energy dissipated, all of which are directly related to damage and infrequently assessed in SHM. A sensitivity study using a realistic seismic case study with known ground truth values investigates the impact of hysteresis loop shape, as well as added noise, on SHM accuracy using a suite of 20 ground motions from the PEER database. Monte Carlo analysis over 22,000 simulations with different hysteresis loops and added noise resulted in absolute percentage identification error (median, (IQR)) in K_p of 1.88% (0.79, 4.94)%. Errors were larger where five events (Earthquakes #1, 6, 9, 14) have very large errors over 100% for resulted K_p as an almost entirely linear response yielded only negligible plastic response, increasing identification error. The sensitivity analysis shows accuracy is reduces to within 3% when plastic drift is induced. This method shows clear potential to provide accurate, real-time metrics of non-linear stiffness and deformation to assist rapid damage assessment and decision making, utilising algorithms significantly simpler than previous non-linear structural model-based parameter identification SHM methods.

• Journal of Energy Engineering
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• v.22 no.3
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• pp.245-249
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• 2013

This paper attempts to estimate the kerosene demand function in Korea over the period 1981-2012. As the kerosene demand function provides us information on the pattern of consumer's kerosene consumption, it can be usefully utilized in predicting the impact of policy variables such as kerosene price and forecasting the demand for kerosene. We apply least absolute deviations and least median squares estimation methods as a robust approach to estimating the parameters of the kerosene demand function. The results show that short-run price and income elasticities of the kerosene demand are estimated to be -0.468 and 0.409, respectively. They are statisitically significant at the 1% level. The short-run price and income elasticities portray that demand for kerosene is price- and income-inelastic. This implies that the kerosene is indispensable goods to human-being's life, thus the kerosene demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for kerosene is price- and income-elastic in the long-run.

• Ocean and Polar Research
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• v.35 no.1
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• pp.1-14
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• 2013

Shoreline data of the barrier islands in Nakdong River Estuary for the last three decades were assembled using six sets of aerial photographs and seven sets of satellite images. Canny Algorithm was applied to untreated data in order to obtain a wet-dry boundary as a proxy shoreline. Digital Shoreline Analysis System (DSAS 4.0) was used to estimate the rate of shoreline changes in terms of five statistical variables; SCE (Shoreline Change Envelope), NSM (Net Shoreline Movement), EPR(End Point Rate), LRR (Linear Regression Rate), and LMS (Least Median of Squares). The shoreline in Jinwoodo varied differently from one place to another during the last three decades; the west tail has advanced (i.e., seaward or southward), the west part has regressed, the south part has advanced, and the east part has regressed. After the 2000s, the rate of shoreline changes (-2.5~6.7 m/yr) increased and the east advanced. The shoreline in Shinjado shows a counterclockwise movement; the west part has advanced, but the east part has retreated. Since Shinjado was built in its present form, the west part became stable, but the east part has regressed faster. The rate of shoreline changes (-16.0~12.0 m/yr) in Shinjado is greater than that of Jinwoodo. The shoreline in Doyodeung has advanced at a rate of 31.5 m/yr. Since Doyodeung was built in its present form, the south part has regressed at the rate of -18.2 m/yr, but the east and west parts have advanced at the rate of 13.5~14.3 m/yr. Based on Digital Shoreline Analysis, shoreline changes in the barrier islands in the Nakdong River Estuary have varied both temporally and spatially, although the exact reason for the shoreline changes requires more investigation.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.815-826
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• 2012

The underestimating trend using existing ordinary regression (OR) based trend analysis has been a well-known problem. The existing OR method based on least squares approximate the conditional mean of the response variable given certain values of the time t, and the usual assumption of the OR method is normality, that is the distribution of data are not dissimilar form a normal distribution. In this regard, this study proposed a quantile regression that aims at estimating either the conditional median or other quantiles of the response variable. This study assess trend in annual daily maximum rainfall series over 64 weather stations through both in OR and QR approach. The QR method indicates that 47 stations out of 67 weather stations are a strong upward trend at 5% significance level while OR method identifies a significant trend only at 13 stations. This is mainly because the OR method is estimating the condition mean of the response variable. Unlike the OR method, the QR method allows us flexibly to detect the trends since the OR is designed to estimate conditional quantiles of the response variable. The proposed QR method can be effectively applied to estimate hydrologic trend for either non-normal data or skewed data.