• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.634-643
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• 2006

This study was intended to develop a high reliable technique by statistically processing on-site data with a general linear model, providing the basic data for construction, analysis of stability and establishment of maintenance measures for tunnel portal slopes in the future. This study evaluated the stability of a tunnel portal slope using a quantified technique, which is based on a general linear model. The important scores of each independent variable were allocated by using the ranges of the quantified values, based on the predicted coefficient of regression and the scores for categories of each independent variable were allocated so that those are equally spaced. The quantification model obtained from the results of evaluating the total data used for the quantification process provided precise results. In addition, it is expected that a more detail subdivision of response variables and sufficient data would produce a better stability evaluation standard.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.98-103
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• 1997

Given the small bit allocation for motion information in very low bit-rate coding, motion estimation using the block matching algorithm(BMA) fails to maintain an acceptable level of prediction errors. The reson is that the motion model, or spatial transformation, assumed in block matching cannot approximate the motion in the real world precisely with a small number of parameters. In order to overcome the drawback of the conventional block matching algorithm, several triangle-based methods which utilize triangular patches insead of blocks have been proposed. To estimate the motions of image sequences, these methods usually have been based on the combination of optical flow equation, affine transform, and iteration. But the compuataional cost of these methods is expensive. This paper presents a fast motion estimation algorithm using a multiple linear regression model to solve the defects of the BMA and the triange-based methods. After describing the basic 2-D triangle-based method, the details of the proposed multiple linear regression model are presented along with the motion estimation results from one standard video sequence, representative of MPEG-4 class A data. The simulationresuls show that in the proposed method, the average PSNR is improved about 1.24 dB in comparison with the BMA method, and the computational cost is reduced about 25% in comparison with the 2-D triangle-based method.

• Journal of Biosystems Engineering
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• v.23 no.1
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• pp.49-56
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• 1998

The objectives of this study were to develop models to predict the contents of moisture and protein of single kernel of brown rice based on visible/NIR (near-infrared) spectroscopic technique. The reflectance spectra of rice were obtained in the range of the wavelength 400 to 2,500 nm with 2 nm intervals. Multiple linear regression(MLR) and partial least squares (PLS) were used to develop the models. The MLR model using the first derivative spectra(10 nm of gap) with Standard Normal Variate and Detrending (SNV and Drt.) preprocessing showed the best results to predict moisture content of the sin린e kernel brown rice. To predict the protein content of a single kernel of brown ricer the PLS model used the raw spectra with multiplicative scatter correction(MSC) preprocessing over the wavelength of 1,100~1,500 nm.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.270-272
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• 2006

In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs) using symbolic coding for non-linear data. One of the major subject of genetic algorithms is representation of chromosomes. The proposed model optimized by the means genetic algorithms which used symbolic code to represent chromosomes. The proposed gFPNN used a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.

• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.347-358
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• 1996

A new test for goodness-of-fit is presented. It is a modification of a test of LaRiccia (1991). These tests are applicable to continuous lo-cation/scale models. The new test statistic is based on a few selected order statistics taken from the sample, while the LaRiccia test is based directly on the full sample. Each test embeds the hypothesized model in a larger linear model and proceeds to test the goodness-of-fit hy-pothesis by testing the coefficients of this linear model appropriately. The general theory is presented. The tests are compared via computer simulation to a related test of Ali and Umbach (1989) for distributions that could be used as lifetime models. An important aspect of all these tests is that only standard $X_2$ tables are used. Selection of the spacings of the order statistics is discussed.

• Journal of Animal Science and Technology
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• v.52 no.6
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• pp.459-466
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• 2010

In this study, we suggest an objective standard in selection of candidate horse mates. Korea Racing Authority provided racing records and pedigree information of 44 sires and 954 dams. The datasets were used to predict Racing Indices represented by the averages of earnings earned by offspring for each dam and sire that indicate the racing performance of its domestic progeny. Proportion of wins and second places to the number of taken races and the mean of distances for the won races of a sire were significant factors in linear model with minimum prediction errors. For dam, those factors were the average of earned money per race, number of outstanding broodmares in pedigree, and the comparable index which indicates the relative affinity with its mate. We can use the resultant model for a horse mate by choosing one of the candidates with the largest predicted value for hypothetical offspring.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.95-99
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• 1985

In this paper, Bayesian analysiss of the general linear econometric model is carried out by using a multinomal prior for the vector of unknown regression coefficents and a half-normal prior for the standard deviation of the disturbances.

• Journal of Environmental Health Sciences
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• v.32 no.2 s.89
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• pp.132-139
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• 2006

Number of aerosol, CO, $CO_2$ and TVOC after one-, two-, three-cigarettes smoking were monitored with time every 10 minute for 180 minutes in the seminar room (volume $51.1m^3$) when poorly-ventilated. IAQ monitor (IAQRAE, model PGM-5210) and PortCount (TSI, model 8020) were used for monitoring. Aerosol was decreased with exponential decay equation and it was estimated that number of aerosol would be long suspended (one cigarette 75/cc. two cigarettes 66/cc, three cigarettes 141/cc by 8hrs after smoking). While CO was also decreased with exponential or linear decay equation and correlated with number of aerosol strongly, TVOC and $CO_2$ were increased with linear equation in accordance with time lag. Most of TVOC and $CO_2$ were above standard levels of Korean Indoor Air Quality (Ministry of Environment) without regarding number of cigarettes. When naturally ventilated, all of CO, $CO_2$ and TVOC concentrations were dramatically decreased below standard levels of Korean Indoor Air Quality.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1847-1852
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• 2004

This article provides the connection between feedback stabilization and interpolation conditions for n-D linear systems (n > 1). In addition to internal stability, if one demands performance as a design goal, then there results an n-D matrix Nevanlinna-Pick interpolation problem. Application of recent work on Nevanlinna-Pick interpolation on the polydisk yields a solution of the problem for the 2-D case. The same analysis applies in the n-D case (n > 2), but leads to solutions which are contractive in a norm (the "Schur-Agler norm") somewhat stronger than the $H^{\infty}$ norm. This is an analogous version of the connection between the standard $H^{\infty}$ control problem and an interpolation problem of Nevanlinna-Pick type in the classical 1-D linear time-invariant systems.

• Environmental Analysis Health and Toxicology
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• v.15 no.1_2
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• pp.39-43
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• 2000

Linear alkyl sulfonates (LAS) constitute a large fraction of the surfactants used in cleaning processes in households, trade and industry Despite the industrial significance and the possible environmental impact of these compounds, the fast and inexpensive determination of LAS concentrations is still a difficult task. In this study, near infrared (NIR) spectroscopy which is a rapid spectroscopic analysis method compared with a traditional analytical method for the measurement of LAS concentration such as HPLC, GC and standard wet chemistry method. NIR spectra of LAS between 0.313 and 25.0% (w/v) in water were utilized to develop a calibration model. The best results (R ＝ 0.998, SEP ＝ 0.244% (w/v)) obtained by using partial least-squares regression with spectral data treatment and 2nd derivatization were comparable to the results (SEC ＝ 0.186% (w/v), SEP ＝ 0.206% (w/v)) obtained by using multiple linear least-squares regression (MLR). However, models based on derivative spectra have no significant advantage with MLR.