• ETRI Journal
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• v.42 no.6
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• pp.932-942
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• 2020

To recover the neural activity from Magnetoencephalography (MEG) and Electroencephalography (EEG) measurements, we need to solve the inverse problem by utilizing the relation between dipole sources and the data generated by dipolar sources. In this study, we propose a new approach based on the implementation of a particle filter (PF) that uses minimum sampling variance resampling methodology to track the neural dipole sources of cerebral activity. We use this approach for the EEG data and demonstrate that it can naturally estimate the sources more precisely than the traditional systematic resampling scheme in PFs.

• Journal of the Korean Mathematical Society
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• v.59 no.6
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• pp.1153-1170
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• 2022

In this paper, we investigate the portfolio optimization problem under the SVCEV model, which is a hybrid model of constant elasticity of variance (CEV) and stochastic volatility, by taking into account of minimum-entropy robustness. The Hamilton-Jacobi-Bellman (HJB) equation is derived and the first two orders of optimal strategies are obtained by utilizing an asymptotic approximation approach. We also derive the first two orders of practical optimal strategies by knowing that the underlying Ornstein-Uhlenbeck process is not observable. Finally, we conduct numerical experiments and sensitivity analysis on the leading optimal strategy and the first correction term with respect to various values of the model parameters.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.2
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• pp.151-161
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• 2007

Statistical characteristic analysis was carried out using the non-tidal components computed by the harmonic analysis of the tidal elevation data in East coast. The tide gauging stations included in this study are the Sokcho, Mukho, Hupo, Pohang, Ulsan and Ulreungdo stations. In this study, the variance and skewness coefficient (SC) information changes, i.e., the max. value, min. value, mean and standard deviation of the variance and SC, are compared and analysed in detail by the various analysis periods increased from one year to the maximum available period. Based on the result of the statistical information (SI) range analysis, the minimum analysis period required in order to satisfy the confidence interval of the ${\pm}5%$ range of the variance and the ${\pm}0.1$ range of the SC is suggested as the 12 years, except the Ulreungdo stations. The auto-correlation and spectral density change patterns show the very similar shapes in every stations even though the absolute values are a little bit different each other.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.175-181
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• 2014

Korean government proposed a new initiative 'government 3.0' with which the administration will open its dataset to the public before requests. City of Seoul is the front runner in disclosure of government data. If we know what kind of attributes are governing factors for any given segmentation, these outcomes can be applied to real world problems of marketing and business strategy, and administrative decision makings. However, with respect to city of Seoul, selection of optimal variables from the open dataset up to several thousands of attributes would require a humongous amount of computation time because it might require a combinatorial optimization while maximizing dissimilarity measures between clusters. In this study, we acquired 718 attribute dataset from Statistics Korea and conducted an analysis to select the most suitable variables, which differentiate Gangnam from other districts, using the Genetic algorithm and Dunn's index. Also, we utilized the Microsoft Azure cloud computing system to speed up the process time. As the result, the optimal 28 variables were finally selected, and the validation result showed that those 28 variables effectively group the Gangnam from other districts using the Ward's minimum variance and K-means algorithm.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.809-817
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• 2002

This paper describes a new face detection method that is a pre-processing algorithm for on-line face recognition. To complement the weakness of using only edge or rotor features from previous face detection method, we propose the two types of face detection method. The one is a combined method with edge and color features and the other is a center area color sampling method. To prevent connecting the people's face area and the background area, which have same colors, we propose a new adaptive edge detection algorithm firstly. The adaptive edge detection algorithm is robust to illumination variance so that it extracts lots of edges and breakouts edges steadily in border between background and face areas. Because of strong edge detection, face area appears one or multi regions. We can merge these isolated regions using color information and get the final face area as a MBR (Minimum Bounding Rectangle) form. If the size of final face area is under or upper threshold, color sampling method in center area from input image is used to detect new face area. To evaluate the proposed method, we have experimented with 2,100 face images. A high face detection rate of 96.3% has been obtained.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.2
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• pp.32-45
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• 2000

This paper presents the analytic derivation of the SINR, when a linear array antenna is accommodated into the cellular CDMA basestation receiver, in relation to the two major performance effecting factors in beamforming(BF) applications, i. e., the direction selectivity, which refers to the narrowness of the mainbeam width, and the direction-of-arrival(DOA) estimation accuracy. The analytically derived results are compared with the operation simulation of the receiver realized with the several BF algorithms and their agreements are confirmed, consequently verifying the correctness of the analysis and the operation simulation. In order to investigate separately the effects of the errors occurring in the direction estimation and in the interference suppression, which are the two major functional components of general BF algorithms, both the algorithms of steering BF and the minimum- variance- distortionless-response(MVDR) BF are applied to the analysis. A signal model to reflect the spatially scattering phenomenon of the RF waves entering into the .:nay antenna, which directly affects on the accuracy of the BF algorithm's direction estimation, is also suggested in this paper and applied to the analysis and the operation simulation. It is confirmed from the results that the enhancement of the direction selectivity of the away antenna is not desirable in view of both the implementation economy and the BF algorithm's robustness to the erroneous factors. Such a trade-off characteristics is significant in the sense that it can be capitalized to obtain an economic means of BF implementation that does not severely deteriorate its performance while ensuring the robustness to the erroneous effects, consequently manifesting the significance of the analysis results of this paper that can be used as a design reference in developing BF algorithms to the cellular CDMA system.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.384-390
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• 2018

This paper introduces a MATLAB graphical user interface (GUI) based software for analysis of korea augmentation satellite system (KASS) availability performance. This software uses minimum variance (MV) estimator and Kriging algorithm to generate integrity information such as user differential range error (UDRE) and grid ionospheric vertical error (GIVE). The information is offered to ground and aviation users in Korean region. The software also gives accuracy data, protection level data and availability map about each user position by using the integrity information. In particular the software calculates the protection level along a path of aircraft. We verified the result of protection level of aviation user by comparing them with the results of SBASimulator#2, which is a simulation tool of european geostationary navigation overlay service (EGNOS). As a result, the protection level error between the result of our software and the SBASimulator#2 was about 2% which means that the result of our software is accurate.

• Korean Journal of Environment and Ecology
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• v.25 no.4
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• pp.470-478
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• 2011

Aster altaicus var. uchiyamae is on the list of endangered species in Korea. Using amplified fragment length polymorphism (AFLP) markers, we investigated the genetic diversity within and among four populations (Guram, Dori Island, Samhap, and Danyang) of A. altaicus var. uchiyamae. We also present the collecting strategies that most efficiently capture the genetic diversity of A. altaicus var. uchiyamae. Four AFLP primer combinations produced a total of 936 bands, of which 934 (99.8%) were polymorphic. A high level of genetic diversity (PPB = 45.3%, h = 0.104, I = 0.168, hs = 0.108) was recognized within the populations of A. altaicus var. uchiyamae. A low degree of genetic differentiation ($G_{ST}$ = 0.075, ${\theta}^B$ = 0.079) was detected among the populations. In addition, analysis of molecular variance (AMOVA) showed that genetic variation was greater within populations (91%) than among populations (9%). These results indicate that the high rate of gene flow has played an important role in forming the present populations of A. altaicus var. uchiyamae. According to maximization strategy, 17, 16, and 11 individuals captured all of the genetic variation in Dori Island, Samhap, and Guram population, respectively. The determination the minimum population size of A. altaicus var. uchiyamae in terms of the genetic information is critical and thereby gain reliable decision support for ex situ conservation of the endangered species, A. altaicus var. uchiyamae.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.591-598
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• 2021

The digital phase-locked loops(DPLL) is a circuit used for phase synchronization and has been generally used in various fields such as communication and circuit fields. State estimators are used to design digital phase-locked loops, and infinite impulse response state estimators such as the well-known Kalman filter have been used. In general, the performance of the infinite impulse response state estimator-based digital phase-locked loop is excellent, but a sudden performance degradation may occur in unexpected situations such as inaccuracy of initial value, model error, and disturbance. In this paper, we propose a minimum variance finite impulse response filter with optimal horizon for designing a new digital phase-locked loop. A numerical method is introduced to obtain the measured value interval length, which is an important parameter of the proposed finite impulse response filter, and to obtain a gain, the covariance matrix of the error is set as a cost function, and a linear matrix inequality is used to minimize it. In order to verify the superiority and robustness of the proposed digital phase-locked loop, a simulation was performed for comparison and analysis with the existing method in a situation where noise information was inaccurate.