• Journal of the Korean Institute of Telematics and Electronics
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• v.10 no.6
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• pp.45-55
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• 1973

This paper discusses the nonlinear time-invarient circuit composed of a tunnel diode. Prior to determine the solution of the nonlinear network which has negative resistance elements, the static characteristics of the nonlinear resistance elements need to be represented by function. Polynomial curve fitting is discussed to represent the static characteristies by least squares approximation. In order to solve the nonlinear network, the state equations for the networks are set up and solved by prediction corrector method. Finally, the limit cycle is plotted to discuss the stability of the nonlinear network and the oscillation condition.

• Journal of Astronomy and Space Sciences
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• v.15 no.1
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• pp.197-208
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• 1998

Ground track manintenance maneuver simulations for the KOMPSAT spacecraft are performed for three and half years. Both longitude targeting and time targeting strate-gies are applied for in-plane maneuvers. The nominal longitude bands of maneuvers for $\pm5km$ and $\pm10km$ are applied for the longitude targeting and the 21-day maneuver time duration is used for the time targeting. Daily solar flux values for the simulation period are derived from the previous solar cycle values. Atmospheric drag formula for the KOMPSAT orbit altitude is derived from Jacchia model using polynomial and sinusoidal curve fitting. Total required delta velocity and proper time between successive maneuvers are estimated during ground track maintenance maneuver simulations.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2528-2530
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• 2004

Neural network minimization problems are often conditioned and in this contribution way to handle this will be discussed. It is shown that a better conditioned minimization problem can be obtained if the problem is separated with respect to the linear parameters. This will increase the convergence speed of the minimization. One of the most powerful uses of neural networks is in function approximation(curve fitting)[1]. A main characteristic of this solution is that function (f) to be approximated is given not explicitly but implicitly through a set of input-output pairs, named as training set, that can be easily obtained from calibration data of the measurement system. In this context, the usage of Neural Network(NN) techniques for modeling the systems behavior can provide lower interpolation errors when compared with classical methods like polynomial interpolation. This paper solve of single-variable minimization using neural network.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.571-575
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• 2000

The physical properties of the spatial model, mass, stiffness and damping matrix, can be defined by a specific natural frequency, damping ratio and mode shape. These modal parameters can be determined from a set of frequency response function(FRF) measured by exciting the structure and measuring the responses at various points around the structure. In this paper, The Transfer Matrix is obtained by experimental modal analysis for the 3-story scaled building model which TMD is installed on top and the physical properties of the spatial model is determined using the residue matrix and the location of poles from FRF measurement using polynomial curve fitting methods.

• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.559-562
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• 2015

본 연구에서는 EDISON_CFD를 활용하여 승용차 모델을 단순화한 Ahmed Body의 후미 경사각 Slant angle $0^{\circ}$, $15^{\circ}$, $30^{\circ}$, $45^{\circ}$의 항력계수변화를 확인하였다. 결과 분석을 통해 Ahmed Body 후면의 후류와 항력계수의 변화 경향성이 같다는 것을 확인하였다. 항력계수는 자동차의 연비 및 최고속도 등 동력성능에 큰 영향을 미치므로 최저 항력계수를 찾아보았다. 각각의 경우에 EDISON_simulation 결과 값을 비교해보면 $15^{\circ}{\sim}30^{\circ}$ 사이에서 최저 항력계수를 갖는 것을 확인할 수 있었다. 정확한 값을 찾기 위해 Polynomial Curve Fitting을 사용하여 Slant angle 이 $22.91^{\circ}$일 때 최저항력계수 0.1375를 갖는 것을 확인하였다.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.105-115
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• 1987

Although there are many theoretical methods for the transformation of random variables. it is difficult to find probability density functions for the new random variables because of the complexity in mathematics. The author developed a simulation model solving the above difficulties using FBI (Fortran Based Interpreter) routines. The FBI is a kind of language Interpreter analyzing the arithmetic statement in character data forms. In this paper. the FBI routines will be explained and the structure and applications of simulation model will be also demonstrated. Polynomial curve fitting method is applied to define the probability density function which can not be defined by well-known pdf. This program can also be used for instructing mathematical statistics and identifying distribution of the simulated data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.3
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• pp.220-227
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• 2019

The satellites in orbit use a sun reference vector from solar model based the ephemeris. To get the ephemeris, we use DE-Series, an ephemeris developed by the Jet Propulsion Laboratory (JPL), or the reference vector generation formula proposed by Vallado. The DE-Series provides the numerical coefficients of Chebyshev polynomials, which have the advantage of high precision, but there is a computational burden on the satellite. The Vallado's method has low accuracy, although the sun vector can be easily obtained through the sun vector generation equation. In this paper, we have developed a program to provide the Chebyshev polynomial coefficients to obtain the sun position coordinates in the inertial coordinate system. The proposed method can improve the accuracy compared to the conventional method and can be used for high - performance, high - precision nano satellite missions.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.5
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• pp.423-430
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• 2012

An adaptive maximum power point tracking (MPPT) scheme employing a variable scaling factor is presented. A MPPT control loop was constructed analytically and the magnitude variation in the MPPT loop gain according to the operating point of the PV array was identified due to the nonlinear characteristics of the PV array output. To make the crossover frequency of the MPPT loop gain consistent, the variable scaling factor was determined using an approximate curve-fitted polynomial equation about linear expression of the error. Therefore, a desirable dynamic response and the stability of the MPPT scheme were maintained across the entire MPPT voltage range. The simulation and experimental results obtained from a 3 KW rated prototype demonstrated the effectiveness of the proposed MPPT scheme.

• Animal Bioscience
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• v.37 no.8
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• pp.1333-1344
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• 2024

Objective: Litter size and piglet loss at birth significantly impact piglet production and are closely associated with sow parity. Understanding how these traits vary across different parities is crucial for effective herd management. This study investigates the patterns of the number of born alive piglets (NBA), number of piglet losses (NPL), and the proportion of piglet losses (PPL) at birth in Landrace sows under tropical conditions. Additionally, it aims to identify the most suitable model for describing these patterns. Methods: A dataset comprising 2,322 consecutive reproductive records from 258 Landrace sows, spanning parities from 1 to 9, was analyzed. Modeling approaches including 2nd and 3rd degree polynomial models, the Wood gamma function, and a longitudinal model were applied at the individual level to predict NBA, NPL, and PPL. The choice of the best-fitting model was determined based on the lowest mean and standard deviation of the difference between predicted and actual values, Akaike information criterion (AIC), and Bayesian information criterion (BIC). Results: Sow parity significantly influenced NBA, NPL, and PPL (p<0.0001). NBA increased until the 4th parity and then declined. In contrast, NPL and PPL decreased until the 2nd parity and then steadily increased until the 8th parity. The 2nd and 3rd degree polynomials, and longitudinal models showed no significant differences in predicting NBA, NPL, and PPL (p>0.05). The 3rd degree polynomial model had the lowest prediction standard deviation and yielded the smallest AIC and BIC. Conclusion: The 3rd degree polynomial model offers the most suitable description of NBA, NPL, and PPL patterns. It holds promise for applications in genetic evaluations to enhance litter size and reduce piglet loss at birth in sows. These findings highlight the importance of accounting for sow parity effects in swine breeding programs, particularly in tropical conditions, to optimize piglet production and sow performance.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.