• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1093-1101
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• 2015

This paper discusses nested design models when nesting occurs in treatment structure and design structure. Some are fixed and others are random; subsequently, the fixed factors having a nested design structure are assumed to be nested in the random factors. The treatment structure can involve random and fixed effects as well as a design structure that can involve several sizes of experimental units. This shows how to use projections for sums of squares by fitting the model in a stepwise procedure. Expectations of sums of squares are obtained via synthesis. Variance components of the nested design model are estimated by the method of moments.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.589-603
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• 2014

When consecutive data follows different distributions(depending on the time interval) change-point detection infers where the changes occur first and then finds further inferences for each sub-interval. In this paper, we investigate the Bayesian detection of multiple change points. Utilizing the reversible jump MCMC, we can explore parameter spaces with unknown dimensions. In particular, we consider a model where the signal is a piecewise linear function. For the Bayesian inference, we propose a new Bayesian structure and build our own MCMC algorithm. Through the simulation study and the real data analysis, we verified the performance of our method.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.399-408
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• 2016

There is a need to detect heteroscedasticity in a regression analysis; however, it invalidates the standard inference procedure. The diagnostics on heteroscedasticity may be distorted when both outliers and heteroscedasticity exist. Available heteroscedasticity detection methods in the presence of outliers usually use robust estimators or separating outliers from the data. Several approaches have been suggested to identify outliers in the heteroscedasticity problem. In this article conventional tests on heteroscedasticity are modified by using a sequential outlier detection methods to separate outliers from contaminated data. The performance of the proposed method is compared with original tests by a Monte Carlo study and examples.

• The Korean Journal of Rheology
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• v.9 no.3
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• pp.89-96
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• 1997

PS/PPO 블렌등의 동적 탄성율 E*($\omega$)와 동적 스트레인-광학계수 O*($\omega$)을 유리전이 영역에서 동시에 측정하여, PS/PPO 3종류조성블렌드의 E*($\omega$)와 O*($\omega$)완화거동을 조성 단 일 중합체와 비교고찰하였다. PS/PPO 블렌드의 $\alpha$-분산 점탄성 거동은 조성에 관계없이 거 의 유사하여 조성 고분자가 상호 협동적으로 완화하는 것을 알수 있었다. 그러나 광학적 완 화 스펙트럼 O*($\omega$)는 정성적으로 명확히 다른 거동을 보였다. 단일 PS와 PPO의 O*($\omega$)는 전 영역에 걸쳐 상반된 부로를 나타냈으며 두 고분자의 블렌드는 조성고분자의 반대부호를 상호보상으로 인하여 복굴절이 감소하였다. 3종류블렌드는 PPO의 조성이 증가함에 따라 상 호보상에 의해 O*($\omega$)의부호가 순차적으로 변하여 반전하였으며, 저 복굴절 PS/PPO 블렌드 의 PS조성이 65-80wt% 범위내에 있음을 추정할수 있었다. 상이한 부호를 갖는 복굴절 특 성으로 인하여 블렌드 내에서 각 성분 고분자의 완화 기여를 다순 가성법칙에 의해 정량적 으로 계산하는 것이 가능하였다. 또한 PS/PPO 블렌드의 상용성을 광학적 부분 기여 파라메 터를 사용하여 고찰하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.7-13
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• 2015

Unmanned air vehicles (UAVs) are getting popular not only as a private usage for the aerial photograph but military usage for the surveillance, reconnaissance and supply missions. For an UAV to successfully achieve these kind of missions, geolocation (localization) must be implied to track an interested target or fly by reference. In this research, we adopted multi-sensor fusion (MSF) algorithm to increase the accuracy of the geolocation and verified the algorithm using two multicopter UAVs. One UAV is equipped with an optical camera, and another UAV is equipped with an optical camera and a laser range finder. Throughout the experiment, we have obtained measurements about a fixed ground target and estimated the target position by a series of coordinate transformations and sequential Kalman filter. The result showed that the MSF has better performance in estimating target location than the case of using single sensor. Moreover, the experimental result implied that multi-sensor geolocation algorithm is able to have further improvements in localization accuracy and feasibility of other complicated applications such as moving target tracking and multiple target tracking.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.55-64
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• 2011

This study aims to analyze of the impact of converged information with tourism and Bus Information on recreational bus travel. The research has conducted as the following process : A survey was implemented that the user preference behavior as if they were provided a converged information with tourism and bus information on bus usage. As a result, we found that able to using mobile media, having a experience visiting the tourism site, evaluate willingness to pay of the information highly, the 20s age, increasing income variables are concerned with positive relation, and the factors which are using the main mode by auto and having a auto are negative relation on bus usage actively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.2
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• pp.172-180
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• 2013

In this paper, we propose an energy-efficient camera operating scheme to save energy which can be used for mass surveillance cameras. This technique determines how many cameras should be turned on in the consideration of the velocity vector of monitoring targets, which is acquired by DSRC object tracking, the model of the specification of installed cameras, and the road model of installed sites. Also, we address other techniques used to save energy for the surveillance system as well. Throughout performance evaluation, we demonstrate the excellence of our proposed scheme compared with previous approaches.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.512-519
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• 2003

In this paper, we propose a neuro-fuzzy modeling to improve the performance using the hierarchical clustering and Gaussian Mixture Model(GMM). The hierarchical clustering algorithm has a property of producing unique parameters for the given data because it does not use the object function to perform the clustering. After optimizing the obtained parameters using the GMM, we apply them as initial parameters for Adaptive Network-based Fuzzy Inference System. Here, the number of fuzzy rules becomes to the cluster numbers. From this, we can improve the performance index and reduce the number of rules simultaneously. The proposed method is verified by applying to a neuro-fuzzy modeling for Box-Jenkins s gas furnace data and Sugeno's nonlinear system, which yields better results than previous oiles.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.72-85
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• 1998

In this paper, we propose a new method that sequentially estimates TDOA(Time Delay Of Arrival) and FDOA(Frequency Delay Of Arrival) for extracting the information about the bearing and relative velocity of a target in passive radar or sonar arrays. The objective is to efficiently estimate the TDOA and FDOA between two sensor signal measurements, corrupted by correlated Gaussian noise sources in an unknown way. The proposed method utilizes the one dimensional slice function of the third order cumulants between the two sensor measurements, by which the effect of correlated Gaussian measurement noises can be significantly suppressed for the estimation of TDOA. Because the proposed sequential algoritjhm uses the one dimensional complex ambiguity function based on the TDOA estimate from the first step, the amount of computations needed for accurate estimationof FDOA can be dramatically reduced, especially for the cases where high frequency resolution is required. It is demonstrated that the proposed algorithm outperforms existing TDOA/FDOA estimation algorithms based on the ML(maximum likelihood) criterionandthe complex ambiguity function of the third order cumulant as well, in the MSE(mean squared error) sense and computational burden. Various numerical resutls on the detection probability, MSE and the floatingpoint computational burden are presented via Monte-Carlo simulations for different types of noises, different lengths of data, and different signal-to-noise ratios.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.2
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• pp.67-70
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• 2016

This paper discusses a graphic user interface(GUI) for the concealed target segmentation. The human subject hiding a metal gun is captured by the passive millimeter wave(MMW) imaging system. The imaging system operates on the regime of 8 mm wavelength. The MMW image is analyzed by the multi-level segmentation to segment and identify a concealed weapon under clothing. The histogram of the passive MMW image is modeled with the Gaussian mixture distribution. LBG vector quantization(VQ) and expectation and maximization(EM) algorithms are sequentially applied to segment the body and the object area. In the experiment, the GUI is implemented by the MFC(Microsoft Foundation Class) and the OpenCV(Computer Vision) libraries and tested in real-time showing the efficiency of the system.