• Journal of the Korea Computer Graphics Society
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• v.28 no.4
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• pp.1-11
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• 2022

The Skinned Multi-Person Linear Model (SMPL) is the most widely used parametric 3D Human Model optimized and learned from CAESAR, a 3D human scanned database created with measurements from 3,800 people living in United States in the 1990s. We point out the lack of racial diversity of body types in SMPL and propose K-SMPL that better represents Korean 3D body shapes. To this end, we develop a fitting algorithm to estimate 2,773 Korean 3D body shapes from Korean body measurement data. By conducting principle component analysis to the estimated Korean body shapes, we construct K-SMPL model that can generate various Korean body shape in 3D. K-SMPL model allows to improve the fitting accuracy over SMPL with respect to the Korean body measurement data. K-SMPL model can be widely used for avatar generation and human shape fitting for Korean.

• Journal of the Chungcheong Mathematical Society
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• v.22 no.4
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• pp.777-787
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• 2009

In this paper we investigate the upper bound on the Castelnuovo-Mumford regularity of a graded module with linear free presentation. Let M be a finitely generated graded module over a polynomial ring R with zero dimensional support. We prove that if M is generated by elements of degree $d{\geq}0$ with a linear free presentation $$\bigoplus^p{R}(-d-1)\longrightarrow^{\phi}\bigoplus^q{R}(-d){\longrightarrow}M{\longrightarrow}0$$, then the Castelnuovo-Mumford regularity of M is at most d+q-1. As an important application, we can prove vector bundle technique, which was used in [11], [13], [17] as a tool for obtaining several remarkable results.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.51-56
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• 2000

This paper presents the characteristics of the dynamic response and calibration technique on a linear variable differential transformer(LVDT). The linear error of the LVDT was proven $\pm$1% in the static calibration and $\pm$0.5% in the dynamic calibration. In this paper, the linearity error generated in the static and dynamic state of the core movement can be eliminated using the correction algorithem of the static and dynamic state derived from the least square linear approximation for the nonlinearity of the curves of direct data fitting and Lagrange polynomials. With the static and dynamic calibration method, the calibration accuracy of the LVDT can be reduced to within $\pm{0.5%.}$.

• ETRI Journal
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• v.46 no.3
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• pp.461-472
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• 2024

We propose a network traffic prediction model based on linear and nonlinear model combination. Network traffic is modeled by an autoregressive moving average model, and the error between the measured and predicted network traffic values is obtained. Then, an echo state network is used to fit the prediction error with nonlinear components. In addition, an improved slime mold algorithm is proposed for reservoir parameter optimization of the echo state network, further improving the regression performance. The predictions of the linear (autoregressive moving average) and nonlinear (echo state network) models are added to obtain the final prediction. Compared with other prediction models, test results on two network traffic datasets from mobile and fixed networks show that the proposed prediction model has a smaller error and difference measures. In addition, the coefficient of determination and index of agreement is close to 1, indicating a better data fitting performance. Although the proposed prediction model has a slight increase in time complexity for training and prediction compared with some models, it shows practical applicability.

• The Korean Journal of Nuclear Medicine
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• v.39 no.4
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• pp.257-262
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• 2005

Purpose: Gastric emptying scan (GES) is usually acquired up to 2 hours. Our study investigated whether a fraction of meal-retention in the stomach at 120 minutes (FR120) was predicted from the data measured for 90 minutes by using non-linear curve fitting. We aimed at saving the delayed imaging by utilizing mathematical models. Materials and Methods: Ninety-six patients underwent GES immediately after taking a boiled egg with 74 MBq (2 mCi) Tc-99m DTPA. The patients were divided into Group I ($T_{1/2}\;{\leq}90\;min$) and Group II ($90\;min). Group I (n=51) had 21 men and 30 women, and Group II (n=45) 15 men and 30 women. There was no significant difference in age and sex between the two groups. Simple exponential, power exponential, and modified power exponential curves were acquired from the measured fraction of meal-retention at each time (0, 15, 30, 45, 60, 75, and 90 min) by non-linear curve fitting ($MATLAB^{\circledR}$ 5.3) and another simple exponential fitting was performed on the fractions at late times (60, 75, and 90 min). A predicted FR120 was calculated from the acquired functional formulas. A correlation coefficient between the measured FR120 and the predicted FR120 was computed ($MedCalc^{\circledR}$ 6.0). Results: Correlation coefficients(r) between the measured FR120 and the predicted FR120 of each mathematical functions were as follows: simple exponential function (Group I: 0.8558, Group II: 0.5982, p<0.0001), power exponential function (Group I: 0.8755, Group II: 0.6008, p<0.0001), modified power exponential function (Group I: 0.8892, Group II: 0.5882, p<0.0001), and simple exponential function at the late times(Group I: 0.9085, Group II: 0.6832, p<0.0001). In all the fitting models, the predicted FR120 were significantly correlated with the measured FR120 in Group I but not in Group II. There was no statistically significant difference in correlation among the 4 mathematical models. Conclusion: In the cases with $T_{1/2}\;{\leq}90\;min$, the predicted FR120 is significantly correlated with the measured FR120. Therefore, FR120 can be predicted from the data measured for 90 minutes by using non-linear curve fitting, saving the delayed imaging after 90 minutes when $T_{1/2}\;{\leq}90\;min$ is ascertained.

• Progress in Medical Physics
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• v.6 no.2
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• pp.83-92
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• 1995

The T1 mapping of an human anatomy may give a characteristic contrast among the various tissues and the normal/abnormal tissues. Here, the methodology of constructing T1 map out of several images with different TRs, will be described using non-linear curve fitting. The general curve fitting algorithm requires the initial trial values T1t and Mot for the variables to be fitted. Three different methods of suppling the trial T1t and Mot are suggested and compared for the efficiency and the accuracy. The curve-fitting routine was written in ANSI C and excuted on a SUN workstation. Several distilled-water phantoms with various concentrations of Gd-DTPA were prepared to examine the accuracy of the curve-fitting program. An MR image was used as the true proton density image without any random noise, and several images with different TRs were generated with the theoretical T1 relaxation times 250, 500, and 1000msec. The random noise of 1, 5, and 10％ were embedded into the simulated images. These images were used to generate the T1 map, and the resultant T1 maps for each T1 were analyzed to study the effect of the random noise on the T1 map.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.4 s.50
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• pp.25-33
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• 2006

The purpose of this study is to develop the curve fitted equations for practicality and actual calculation during seismic performance evaluation of buried pipelines. Curve fitting for strain curve according to the wavelength of the seismic wave was produced using the non-linear least square method and the equations with the best results was suggested. In addition, a degree and coefficient of polynomial fitting equation needed to use curve fitted equation were identified. Interpreting process during the test of resistance of earthquake of buried pipelines with various end boundary conditions were provided through example questions. The results of this study were used to conduct a dynamic response analysis and a seismic performance evaluation of concrete, steel, and FRP pipes with various end boundary conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.913-917
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• 2013

During the restoration process of primary restorative transmission system, some over voltages may happen due to nonlinear interaction between unloaded transformers and transmission systems. These over voltages caused by harmonic resonance can be suppressed by inserting damping loads before energizing transformers. But it is very difficult to predict the occurrence possibility of harmonic resonance and complex simulation must be repeated to estimate the sufficient damping loads. This paper presents a damping loads prediction system to prevent harmonic resonance. Detailed analysis of the relationship between harmonic resonance and the amount of damping loads is discussed. The prediction system is developed using a curve fitting and a neural network based on this relationship. A curve fitting used a Gaussian function based on non-linear least square method and multi-layer back-propagation neural network is applied. The system is applied to primary restorative transmission lines in korean power system and the result showed satisfactory performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1063-1075
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• 2012

To locate an object accurately in the wireless sensor networks, the distance measure based on time-delay plays an important role. In this paper, we propose a maximum likelihood (ML) time-delay estimation algorithm in multi-path wireless propagation channel. We get the joint probability density function after sampling the frequency domain response of the multi-path channel, which could be obtained by the vector network analyzer. Based on the ML criterion, the time-delay values of different paths are estimated. Considering the ML function is non-linear with respect to the multi-path time-delays, we first obtain the coarse values of different paths using the subspace fitting algorithm, then take them as an initial point, and finally get the ML time-delay estimation values with the pattern searching optimization method. The simulation results show that although the ML estimation variance could not reach the Cramer-Rao lower bounds (CRLB), its performance is superior to that of subspace fitting algorithm, and could be seen as a fine algorithm.

• Korean Journal of Optics and Photonics
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• v.16 no.5
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• pp.423-427
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• 2005

In this paper, we propose easily tooling method for Seidel third order aberration, which are not well utilized in actual design process due to the complication of mathematical operation and the difficulty of understanding Seidel third order aberration theory, even though most insightful and systematic means in pre-designing for the initial data of optimization. First, using paraxial ray tracing and Seidel third order aberration theory, spherical aberration coefficient is derived for a two-mirror system with a finite object distance. The coefficient, which is expressed as a higher-order nonlinear equation, consists of design parameters(object distance, two curvatures, and inter-mirror distance) and effective focal length(EFL). Then, the expressed analytical equation is solved by using a computer with numerical analysis method. From the obtained numerical solutions satisfying the nearly zero coefficient condition($<10^{-6}$), linear fitting process offers a linear relationship called the curvature linear equation between two mirrors. Consequently, this linear equation has two worthy meanings: the equation gives a possibility to obtain initial design data for optimization easily. And the equation shows linear relationship to a two-mirror system with a finite object distance under the condition of corrected third order spherical aberration.