• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.161-175
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• 2001

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. Hierarchical models including selection models are introduced and shown to be useful in such Bayesian meta-analysis. Semiparametric hierarchical models are proposed using the Dirichlet process prior. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierachical selection model with including unknown weight function and use Markov chain Monte Carlo methods to develop inference for the parameters of interest. Using Bayesian method, this model is used on a meta-analysis of twelve studies comparing the effectiveness of two different types of flouride, in preventing cavities. Clinical informative prior is assumed. Summaries and plots of model parameters are analyzed to address questions of interest.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.957-963
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• 2015

The autocorrelation of an alternative binary offset carrier (AltBOC) signal provides an improved positioning accuracy because of its narrow main-peak. However, The AltBOC signal has a disadvantage that the autocorrelation of the AltBOC signal has multiple side-peaks which incur a severe positioning error. In this paper, we propose a generating method of an unambiguous correlation function for AltBOC signal tracking. Specifically, we first obtain symmetric partial correlation functions, and subsequently, we obtain an unambiguous correlation function by combining them. In numerical results, it is confirmed that the proposed correlation function provides better tracking error standard devation (TESD) performances comparing with the conventional correlation functions.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.11
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• pp.549-557
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• 2000

This study proposes a new numerical analysis method for assessing the outage cost of the composite power system with considering transmission system at load points. The proposed method comes from combination of the expected energy not served curve(EENSC) with the marginal outage cost function obtained at load points. Uncertainty of the outages of the generation and transmission systems was also included in this study. This study can be categorized into three processing parts as like as follows. Firstly, EENSC at load points was developed newly from the composite power system effective load duration curve which has been proposed by the authors. Secondly, this study proposes a new technical method for determining the coefficients of the marginal outage cost functions at load points in the composite power system(Generation and Transmission systems). It is a main key point that the mathematical expression for the marginal outage cost function at a load point is formulated and evaluated using relations between the GNP (or GDP) and the electrical energy demand at the load pint. Finally, the outage cost was calculated in this paper by combining the proposed EENSC with the marginal outage cost function evaluated at each load point. It is another important feature that the average costs for future at load points can be forescasted using the proposed approach. The effectiveness of the proposed new approach is demonstrated by the case studies with the IEEE-RTS.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.3 s.303
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• pp.63-72
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• 2005

In this paper, we propose a deformation technique based on Radial Basis Function (RBF) and a blending technique combining the deformed facial component with the original face for a Virtual Aesthetic Surgery (VAS) system. The deformation technique needs the smoothness and the accuracy to deform the fluid facial components and also needs the locality not to affect or distort the rest of the facial components besides the deformation region. To satisfy these deformation characteristics, The VAS System computes the degree of deformation of lattice cells using RBF based on a Free-Form Deformation (FFD) model. The deformation error is compensated by the coefficients of mapping function, which is recursively solved by the Singular Value Decomposition (SVD) technique using SSE (Sum of Squared Error) between the deformed control points and target control points on base curves. The deformed facial component is blended with an original face using a blending ratio that is computed by the Euclidean distance transform. An experimental result shows that the proposed deformation and blending techniques are very efficient in terms of accuracy and distortion.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.1
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• pp.1-13
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• 2022

A weighted linear combination of seismic fragility models previously developed for cut-and-cover railway tunnels was presented and the appropriateness of the combined model was evaluated. The seismic fragility function is expressed in the form of a cumulative probability function of the lognormal distribution based on the peak ground acceleration. The model uncertainty can be reduced by combining models independently developed. Equal weight is applied to four models. The new seismic fragility function was developed for each damage level by determining the median and standard deviation, which are model metrics. Comparing fragility curves developed for other bored tunnels, cut-and-cover tunnels for high-speed railway system have a similar level of fragility. We postulated that this is due to the high seismic design standard for high-speed railway tunnel.

• Structural Engineering and Mechanics
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• v.32 no.5
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• pp.667-683
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• 2009

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

• The Journal of Fisheries Business Administration
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• v.45 no.1
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• pp.63-77
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• 2014

This study is to estimate the recent changes in total factor productivity of 15 Korean adjacent water fisheries based on Malmquist productivity indices. The study adopted both input and output oriented productivity measures utilizing a hyperbola distance function. In addition to this point, the study also calculated the 95% confidence interval for the various components of the productivities in order to access the statistical significance of estimates using 2000 times of re-sampling process through the smoothed bootstraping. The results of the study showed us that there was 18% reduction in the overall total factor productivity during the study period from 2007 to 2011, which turned out to be 5% of annual decrease in productivity. The study found that the main reason of this decrease in total productivity is about 22% downward shift of a fisheries production function due to recent conditions of a devastated fishing ground. When we evaluated the statistical significance of changes in technical efficiency combining both pure technical and scale efficiency based on the 95% confidence intervals, we could not find any evidence of changes in those components of total factor productivity. When we accessed the productivity of the each of 15 adjacent water fisheries methods, only the large danish seine fisheries showed us about 7% increase in productivity. Even though the large trawling and the large tow-boat trawling revealed no changes in productivity, all of the other 12 fisheries suffered the decreases in productivities.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.39-49
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• 2013

This paper presents a method of improving the performance of a day-ahead 24-h load curve and peak load forecasting. The next-day load curve is forecasted using radial basis function (RBF) neural network models built using the best design parameters. To improve the forecasting accuracy, the load curve forecasted using the RBF network models is corrected by the weighted sum of both the error of the current prediction and the change in the errors between the current and the previous prediction. The optimal weights (called "gains" in the error correction) are identified by differential evolution. The peak load forecasted by the RBF network models is also corrected by combining the load curve outputs of the RBF models by linear addition with 24 coefficients. The optimal coefficients for reducing both the forecasting mean absolute percent error (MAPE) and the sum of errors are also identified using differential evolution. The proposed models are trained and tested using four years of hourly load data obtained from the Korea Power Exchange. Simulation results reveal satisfactory forecasts: 1.230% MAPE for daily peak load and 1.128% MAPE for daily load curve.

• Journal of Environmental Policy
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• v.7 no.2
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• pp.49-66
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• 2008

The goal of current study is to carry out comparative analysis on the relationship between nature perspectives and their corresponding utilities by taking integrated approach combining economic values with environmental ones. The results are as follows. First, empirical evidence shows that the structures of happiness function differ according to nature perspectives. The anthropocentric-nature perspective is centered on economic value. Whilst, environment and social trust play an statistically insignificant role in deciding happiness levels. Secondly, the eco-centric perspective possesses a multi-facted structure of happiness function composing of income, environment, and social trust. In this vein, it is no reasonable behavior, from happiness maximization view, to focus on economic value vis-a-vis use value.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.6 no.2
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• pp.59-66
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• 2007

Voice coil actuator is used linear motion system that requires precision positioning control. In order to control precision positioning of voice coil actuator, relation model between duty ratio and moving displacement of voice coil actuator is needed. This paper present a duty ratio - displacement model in PWM control of voice coil actuator. Transfer function of voice coil actuator is obtained by combining voice coil motor's equation of motion with the equation of circuit and characteristic of voice coil motor. Consider to initial condition of velocity and current, transfer function is transformed mathematical model. The induced model can predict output displacement, velocity and current according to duty ratio and amplitude. The model is verified by experimental tests such as velocity and displacement response of voice coil motor. Simulated results have tracking errors of less than 10 percent of experimental results.