• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1121-1131
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• 2015

Logistic models with a random intercept are useful to analyze longitudinal binary data. Traditionally, the random intercept of the logistic model is assumed to be parametric (such as normal distribution) and is also assumed to be independent to variables. Such assumptions are very strong and restricted for application to real data. Recently, Garcia and Ma (2015) derived semiparametric efficient estimators for logistic model with a random intercept without these assumptions. Their estimator shows the consistency where we do not assume any parametric form for the random intercept. In addition, the method is computationally simple. In this paper, we apply this method to analyze toenail infection data. We compare the semiparametric estimator with maximum likelihood estimator, penalized quasi-likelihood estimator and hierarchical generalized linear estimator.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.11
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• pp.999-1011
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• 2015

In modern electronic warfare, RADAR is under constant threat of ECM(Electronic Counter Measures) signals from nearby jammers. The conventional linear frequency modulated(Linear-FM) waveform is easy to be intercepted to estimate its signal parameters due to its periodical phase transition. Recently, APCN(Advanced Pulse Compression Noise) waveform using random amplitude and phase transition was proposed for LPI(Low probability of Intercept). But random phase code signals such as APCN waveform tend to be sensitive to Doppler frequency shift and result in performance degradation during moving target detection. In this paper, random phase and code rate transition based radar waveform(RPCR) is proposed for Doppler tolerance improvement. Time frequency analysis is carried out through ambiguity analysis to validate the improved Doppler tolerance of RPCR waveform. As a means to measure the vulnerability of the proposed RPCR waveform against LPI, WHT(Wigner-Hough Transform) is adopted to analyze and estimate signal parameters for ECCM(Electronic Counter Counter Measures) application.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.729-739
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• 2017

The objective of this study was to optimize minimum-energy impulsive spacecraft intercept using genetic algorithms. A mathematical model was established on two-body system based on f and g solution and universal variable to address spacecraft intercept problem for non-coplanar elliptical orbits. This nonlinear problem includes many local optima due to discontinuity and strong nonlinearity. In addition, since it does not provide a closed-form solution, it must be solved using a numerical method. Therefore, the initial guess is that a very sensitive factor is needed to obtain globally optimal values. Genetic algorithms are effective for solving these kinds of optimization problems due to inherent properties of random search algorithms. The main goal of this paper was to find minimum energy solution for orbit transfer problem. The numerical solution using initial values evaluated by the genetic algorithm matched with results of Hohmann transfer. Such optimal solution for unrestricted arbitrary elliptic orbits using universal variables provides flexibility to solve orbit transfer problems.

• Journal of Urban Science
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• v.9 no.2
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• pp.63-68
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• 2020

In recent years, the planning of livable communities has emerged as a new paradigm. The concept of livable communities is related to both the spatial balance of working, playing, and living and the promotion of green modes of transportation, such as walking and biking. This study uses a disaggregate travel survey conducted by the Seoul Metropolitan Area in 2006. I applied a multi-level random intercept logit model to estimate the effects of land-use characteristics on the choice of green modes, holding a traveler's socio-demographic characteristics constant. The empirical results show that higher density and more mixed land-use development encourages people to walk and bike even when individuals have the same socio-economic characteristics. This paper demonstrates that land-use planning by itself can play a role in the creation of livable cities and the decline of greenhouse gas production.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.84-86
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• 2001

A new navigation method is developed and implemented for mobile robot. The mobile robot navigation problem has traditionally been decomposed into the path planning and path following. Unlike tracking-based system, which minimize intercept time and moved mobile robot distance for optimal rendezvous point selection. To research of random moving object uses algorithm of Adaptive Control using Auto-regressive Model. A fine motion tracking object's trajectory is predicted of Auto-regressive Algorithm. Thus, the mobile robot can travel faster than the target wi thin the robot's workspace. The can select optimal rendezvous point of various intercept time.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.10
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• pp.1542-1549
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• 2018

Objective: Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a RR model. Methods: We analyzed test-day milk records from 85,690 Holstein cows in their first lactations and 131,727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. Results: The first-order Legendre polynomials were practical covariates of RR for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Conclusion: Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.597-602
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• 1988

In this paper, we consider conventional and modified proportional navigation guidance(PNG) laws for a random maneuvering target. By means of Lyapunov function approach, we show that an ideal missile guided by the conventional PNG law can always intercept a random maneuvering target if some specified initial conditions are satisfied and the navigation constant is chosen sufficiently high. In addition, we propose a modified PNG law. At the final phase of pursuit, the proposed guidance law has a better acceleration profile than the conventional PNG law.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.413-420
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• 2022

In this study we adapt discrete weibull regression model for clustered count data. Discrete weibull regression model has an attractive feature that it can handle both under and over dispersion data. We analyzed the eighth Korean National Health and Nutrition Examination Survey (KNHANES VIII) from 2019 to assess the factors influencing the 1 month outpatient stay in 17 different regions. We compared the results using clustered discrete Weibull regression model with those of Poisson, negative binomial, generalized Poisson and Conway-maxwell Poisson regression models, which are widely used in count data analyses. The results show that the clustered discrete Weibull regression model using random intercept model gives the best fit. Simulation study is also held to investigate the performance of the clustered discrete weibull model under various dispersion setting and zero inflated probabilities. In this paper it is shown that using a random effect with discrete Weibull regression can flexibly model count data with various dispersion without the risk of making wrong assumptions about the data dispersion.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.677-683
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• 1997

For an AR(1) model with intercept $y_t=\mu+\rho{y_{t-1}}+e_t$, a test for random walk hypothesis $H_0:(\mu, \rho)=(0, 1)$is proposed, which is based on the symmetric estimator. In the vicinity of the null, the test in shown to be more powerful than the test of Dickey and Fuller(1981) based on the ordinary least squares estimator.

• Korean Medical Education Review
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• v.12 no.1
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• pp.3-8
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• 2010

This study is designed to evaluate the effectiveness of teaching or studying programs, and thus to overcome the selectionbias in studies. Selection-bias derived from unobservable characteristics in the course of participants selection of the teaching or studying programs, in the case of cross-section data instrumental variable(IV) method and two stage least square estimation were suggested as an analysis tool. Panel data were analyzed by using both fixed effect in which individual effects are captured by intercept terms and random effect estimation where an unobserved effect can be characterized as being randomly drawn from a given distribution.