• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.309-327
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• 2021

Dynamic treatment regimes (DTRs) are decision-making rules designed to provide personalized treatment to individuals in multi-stage randomized trials. Unlike classical methods, in which all individuals are prescribed the same type of treatment, DTRs prescribe patient-tailored treatments which take into account individual characteristics that may change over time. The Q-learning method, one of regression-based algorithms to figure out optimal treatment rules, becomes more popular as it can be easily implemented. However, the performance of the Q-learning algorithm heavily relies on the correct specification of the Q-function for response, especially in observational studies. In this article, we examine a number of double-robust weighted least-squares estimating methods for Q-learning in high-dimensional settings, where treatment models for propensity score and penalization for sparse estimation are also investigated. We further consider flexible ensemble machine learning methods for the treatment model to achieve double-robustness, so that optimal decision rule can be correctly estimated as long as at least one of the outcome model or treatment model is correct. Extensive simulation studies show that the proposed methods work well with practical sample sizes. The practical utility of the proposed methods is proven with real data example.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1485-1492
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• 2015

This paper proposes a double frequency method using FTP(Fourier Transform Profilometry) in fringe projection techniques for 3D measurement systems. In fringe projection techniques, fringe pattern images are projected and captured, and then object is measured by analysing phase. PMP(Phase Measuring Profilometry) for analysing phase provides high-resolution and is robust to object's reflection and background intensities. However, the measurement range is narrow due to 2π ambiguity. In order to overcome this problem, a double frequency method is often used. This method can widen the range of measurement while maintaining the high-resolution, but the measurement time is taken about twice due to grab 2 times number of images. The proposed double frequency method using FTP requires an additional image for resolving 2π ambiguity. The proposed method effectively reduces the measurement time while maintaining the same accuracy.

• Journal of Labour Economics
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• v.43 no.4
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• pp.35-86
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• 2020

We estimate the effects of marriage on women's labor market outcomes and subject well-being. To resolve the endogeneity problem of marital status and timing of marriage, we use the difference-in-differences event study method which compares the trends of the outcome before and after the event between treatment and control groups. For robustness, we use four different control groups. The results show that the probability of working drops significantly by about 10%p in the first year of marriage and the effect becomes as large as 46%p by the 5th year of marriage. Also monthly earnings decrease substantially. We find that marriage increases subjective well-being, while the effect is not persistent.

• Journal of Auto-vehicle Safety Association
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• v.13 no.3
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• pp.32-40
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• 2021

Composite material is very attractive because it has excellent mechanical property and is possible to lightweight due to the low density. However, composite material is less used compared to other systems in the chassis system because it is very hard to solve NVH problem when composite material is applied to vehicle. Especially, reducing squeal noise of composite brake system is essential to apply it to vehicle successfully. In this paper, we present a new solution to reduce squeal noise of composite brake system. To achieve this goal, we analyze main causes of noise using RCA (Root Cause Analysis), CA (Contradiction Analysis) and sequentially get IFR (Ideal Final Result) to solve the problem. Next, we define the function of composite brake system and derive control factors and noise factors. A variety of tests for factors like chamfer, slot, damping shim, underlayer of brake pad are done. In addition, we analyze level of contribution for control factors theoretically. Finally, we get the effective solution for reducing squeal noise.

• Environmental and Resource Economics Review
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• v.25 no.1
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• pp.1-25
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• 2016

This study investigated the variability of WTP estimates(i.e. mean or median) with ad hoc assumptions of specific parametric probability distributions(i.e. normal, logistic, lognormal, and exponential distribution) to estimate WTP function using dichotomous choice CV data on mortality risk reduction. From the perspective of policy decision, the variability of these WTP estimates are intolerable in comparison with those of Turnbull nonparametric estimation method which is free from ad hoc distribution assumptions. The Turnbull nonparametric estimation can avoid a kind of misspecification bias due to ad hoc assumption of specific parametric distributions. Furthermore, the WTP estimates by Turnbull nonparametric estimation are robust because the similar estimates are elicited from a dichotomous choice or double dichotomous choice CV data, and the statistically significant WTP estimates can be obtained even though it is not possible by parametric estimation methods. If there are considerable variability among those WTP estimates by parametric estimation methods in condition with no criteria of model adequacy, the mean WTPs from Turnbull nonparametric estimation can be the robust estimates without ad hoc assumptions, which can avoid controversial issues in the perspective of policy decisions.

• Journal of IKEEE
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• v.20 no.2
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• pp.152-162
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• 2016

Electrical resistivity tomography (ERT) is a technique to reconstruct the internal resistivity distribution using the measured voltages on the surface electrodes. ERT inverse problem suffers from ill-posedness nature, so regularization methods are used to mitigate ill-posedness. The reconstruction performance varies depending on the type of regularization method. In this paper, an interacting dual-mode regularization method is proposed with two different regularization methods, L1-norm regularization and total variation (TV) regularization, to achieve robust reconstruction performance. The interacting dual-mode regularization method selects the suitable regularization method and combines the regularization methods based on computed mode probabilities depending on the actual conditions. The proposed method is tested with numerical simulations and the results demonstrate an improved reconstruction performance.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.293-300
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• 2012

In this study, the delamination analysis has been implemented to investigate the initiation and propagation of crack in composite laminates composed of orthotropic materials. A simple modeling was achieved by moving nodal technique without re-meshing work when crack propagation occurred. This paper aims at achieving two specific objectives. The first is to suggest a very simple modeling scheme compared with those applied to conventional h-FEM based models. To verify the performance of the proposed model, analysis of double cantilever beams with composite materials was implemented and then the results were compared with reference values in literatures. The second one is to investigate the behavior of interior delamination problems using the proposed model. To complete these objectives, the full-discrete-layer model based on Lobatto shape functions was considered and energy release rates were calculated using three-dimensional VCCT(virtual crack closure technique) based on linear elastic fracture mechanics.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.157-158
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• 1995

• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.25-35
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• 2014

This paper proposes a method of boosting-based classification for the purpose of real-time face detection. The proposed method uses depth images to ensure strong performance of face detection in response to changes in lighting and face size, and uses the depth difference feature to conduct learning and recognition through the I-MCTBoost classifier. I-MCTBoost performs recognition by connecting the strong classifiers that are constituted from weak classifiers. The learning process for the weak classifiers is as follows: first, depth difference features are generated, and eight of these features are combined to form the weak classifier, and each feature is expressed as a binary bit. Strong classifiers undergo learning through the process of repeatedly selecting a specified number of weak classifiers, and become capable of strong classification through a learning process in which the weight of the learning samples are renewed and learning data is added. This paper explains depth difference features and proposes a learning method for the weak classifiers and strong classifiers of I-MCTBoost. Lastly, the paper presents comparisons of the proposed classifiers and the classifiers using conventional MCT through qualitative and quantitative analyses to establish the feasibility and efficiency of the proposed classifiers.

• KDI Journal of Economic Policy
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• v.36 no.4
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• pp.135-169
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• 2014

This study empirically analyzes changes in production patterns of farmers by agricultural disaster insurance. The aim of this project is to achieve stability of farm management by paying insurance in case of a natural disaster. However, it causes farmers to change production patterns in the direction of increasing production, and leads the crop price to drop. This can be explained by producers' risk reduction through the disaster insurance. The empirical analysis is based on IV approach with using two stage least squares method. The first stage estimates by difference-in-differences methodology indicate that the production of insurable crops increases more about 80,000ton on average than that of non-insurable crops. In addition, to solve the endogeneity problem caused by general supply and demand model, I use the first stage estimates and find that the price index of the crops drops about 2.3% according to the production increase by 10,000ton. The credibility of these results is also attained by various robustness checks. These findings suggest that it is necessary for government to analyze the whole economy which consists of producer and consumer welfare when it determines the policy. Besides, it implies that it is essential to develop a new market to cope with the unintended effect.