• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.379-393
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• 2020

A terminal event such as death may censor an intermediate event such as relapse, but not vice versa in semi-competing risks data, which is often seen in medicine, public health, and epidemiology. We propose a Weibull regression model with a normal frailty to analyze semi-competing risks data when all three transition times of the illness-death model are possibly interval-censored. We construct the conditional likelihood separately depending on the types of subjects: still alive with or without the intermediate event, dead with or without the intermediate event, and dead with the intermediate event missing. Optimal parameter estimates are obtained from the iterative quasi-Newton algorithm after the marginalization of the full likelihood using the adaptive importance sampling. We illustrate the proposed method with extensive simulation studies and PAQUID (Personnes Agées Quid) data.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.1
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• pp.106-115
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• 1988

A numerical procedure for determining the airfoil shape that maximizes the lift is presented. The structure of the flow field is calculated by iteratively coupling potential flow and boundary analysis using the viscous-inviscid interaction method. The potential flow field is obtained by the vortex panel method and boundary layer flow is analyzed by means of integral approximation method which is capable of handling the laminar, transition and turbulent flow regimes. As the result of this study, it is found that the calculated flow regimes have good agreement with the existing experimented data. Davidon-Fletcher-Powell method and Augmented Lagrange Multiplier method are used for the optimal techniques. NACA 23012, NACA 65-3-21, NACA 64-2-415, NACA 64-2-A215 airfoils are used for determining the optimal airfoil shapes as a basic and compensate airfoils. Optimal design showed that the lift coefficients are increased by 17.4% at M$_{0}$=0.2 and 29% at M$_{0}$=0.3, compared with those of basic airfoil.oil.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.129-138
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• 2003

A new methodology for selecting spatially variable model control parameter values through consideration of inference models within a Hydroinformatic system has been developed to overcome problems associated with determination of spatially variable control parameter values for both ungauged and gauged catchment. The adopted Hydroinformatic tools for determination of control parameter values were a GIS(Arc/Info) to handle spatial and non-spatial attribute information, the SWMM(stormwater management model) to simulate catchment response to hydrologic events, and lastly, L_BFGS_B(a limited memory quasi-Newton algorithm) to assist in the calibration process. As a result, high accuracy of control parameter estimation was obtained by considering the spatial variations of the control parameters based on landuse characteristics. Also, considerable time and effort necessary for estimating a large number of control parameters were reduced from the new calibration approach.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.661-669
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• 2007

Eyer since the Prandtl's experiment in 1934 and X-21 airjet test in 1950 both attempting to reduce drag, it was found that controlling the velocities of surface for extremely fast-moving object in the air through suction or injection was highly effective and active method. To obtain the right amount of suction or injection, however, repetitive trial-and error parameter test has been still used up to now. This study started from an attempt to decide optimal amount of suction and injection of incompressible Navier-Stokes by employing optimization techniques. However, optimization with traditional methods are very limited, especially when Reynolds number gets high and many unexpected variables emerges. In earlier study, we have proposed an algorithm to solve this problem by using step by step method in analysis and introducing SQP method in optimization. In this study, we propose more effective and robust algorithm and techniques in solving flow optimization problem.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.539-553
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• 2017

We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).