• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.435-447
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• 2004

In additive nonparametric regression, Linton and Nielsen (1995) showed that the marginal integration when applied to the local linear smoother produces a rate-optimal estimator of each univariate component function for the case where the dimension of the predictor is two. In this paper we give new formulas for the bias and variance of the marginal integration regression estimators which are valid for boundary areas as well as fixed interior points, and show the local linear marginal integration estimator is in fact rate-optimal when the dimension of the predictor is less than or equal to four. We extend the results to the case of the local polynomial smoother, too.

• Proceedings of the Korean Geotechical Society Conference
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• 1997.10a
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• pp.65-72
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• 1997

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.1
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• pp.17-27
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• 2011

A selection experiment for reduced residual feed intake (RFI) in Yorkshire pigs consisted of a line selected for lower RFI (LRFI) and a random control line (CTRL). Longitudinal measurements of daily feed intake (DFI) and body weight (BW) from generation 5 of this experiment were used. The objectives of this study were to evaluate the use of random regression (RR) and nonlinear mixed models to predict DFI and BW for individual pigs, accounting for the substantial missing information that characterizes these data, and to evaluate the effect of selection for RFI on BW and DFI curves. Forty RR models with different-order polynomials of age as fixed and random effects, and with homogeneous or heterogeneous residual variance by month of age, were fitted for both DFI and BW. Based on predicted residual sum of squares (PRESS) and residual diagnostics, the quadratic polynomial RR model was identified to be best, but with heterogeneous residual variance for DFI and homogeneous residual variance for BW. Compared to the simple quadratic and linear regression models for individual pigs, these RR models decreased PRESS by 1% and 2% for DFI and by 42% and 36% for BW on boars and gilts, respectively. Given the same number of random effects as the polynomial RR models, i.e., two for BW and one for DFI, the non-linear Gompertz model predicted better than the polynomial RR models but not as good as higher order polynomial RR models. After five generations of selection for reduced RFI, the LRFI line had a lower population curve for DFI and BW than the CTRL line, especially towards the end of the growth period.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.43-50
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• 2003

Today, the demand of image acquisition systems grows as the multimedia applications go on increasing greatly. Among the systems, film scanner is one of the systems, which can acquire high quality and high resolution images. However due to the nonlinear characteristic of the light source and sensor, colors of the original film image do not correspond to the colors of the scanned image. Therefore color correction mr the scanned digital image is essential in the film scanner. In this paper, polynomial regression method is applied for the color correction to CIE $L^{*}$ $a^{*}$ $b^{*}$ color model data converted from RGB color model data. A1so a film scanner hardware with 12 bit color resolution for each R, G, B and 2400 dpi was implemented by using TMS320C32 DSP chip and high resolution line sensor. An experimental result shows that the average color difference ($\Delta$ $E^{*}$$_{ab}$ ) is reduced from13.48 to 8.46.6.6.6.6.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.4
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• pp.314-320
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• 2011

In this work, optimization of two-stage shock absorption system for lunar lander has been carried out. Because of complexity of impact phenomena of shock absorption system, a 1-D constitutive model is proposed to describe the behavior of shock absorption system. Quadratic polynomial regression meta-model is constructed by using a commercial software ABAQUS with the proposed 1-D constitutive model, and sequential approximate optimization of two-stage shock absorption system has been carried out along with the constructed meta-model. Through the optimization, it is verified that landing impact force on lunar lander can be considerably reduced by changing the cell size and foil thickness of honeycomb structure in two-stage shock absorption system.

• Journal of the Korean Applied Science and Technology
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• v.35 no.4
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• pp.1393-1406
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• 2018

In this study, three parameters (Pressure ($X_1$), Airflow rate ($X_2$), Operation time ($X_3$)) were experimentally designed and the predicted model and optimal conditions were established by using the terminal rise velocity of the microbubbles as the response value. The polynomial regression analysis showed that the optimum value for the terminal rise velocity at the Pressure ($X_1$) of 4.5 bar, Airflow rate ($X_2$) of 3.3 L/min and Operation time ($X_3$) of 2.2 min was 5.14 cm/min ($85.7{\mu}m/sec$). Also, the highest microbubble diameter size distribution in the range of 2 to $5{\mu}m$ and 25 to $50{\mu}m$ was confirmed by using a laser particle counting apparatus.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.644-652
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• 2002

Increasing demands for Electric Resistance Welded pipes of high quality with thick wall require c lose investigations in edge deformation by slitting, strip deformation during break down farming, and difference of circumferential length. In order to obtain good quality of a welding zone, it is necessary to predict the edge shape of the initial strip. The modeling of the multi-pass thick tube roll forming process with rigid plastic finite element method ultra the edge shape prediction of an initial strip with 2nd-degree polynomial regression method are presented. Edge shapes of initial strip have been analyzed by the finite element method and designed by the regression method to satisfy the requirements in target fin pass. It is concluded that the proposed edge design method results in optimal edge shapes sat string the design requirements.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.29-36
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• 2004

The paper describes recent experimental results on the development of Digital Magnetic Compass (DMC), which can provide smart automatic correction functions to the magnetic interferences. The design methodology of magnetic sensing circuit with ring-core fluxgate sensor is represented. The performance results of the sensing circuits are discussed with error analysis by polynomial regressions. As test results, the sensing circuit filtered only the second harmonic signal that is proportional to the direction of earth's magnetic field, and it leads to the obtainment of bearing information. In addition, the total residual errors of DMC can be analyzed by the adoption of polynomial regressions. It shown that the possibility of high precise DMC, in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.15-15
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• 2000

In the past couple of years, there has been increasing interest in the fusion of neural networks and fuzzy logic. Most of the existing fused models have been proposed to implement different types of fuzzy reasoning mechanisms and inevitably they suffer from the dimensionality problem when dealing with complex real-world problem. To overcome the problem, we propose the self-organizing networks with activation nodes based on fuzzy inference and polynomial function. The proposed model consists of two parts, one is fuzzy nodes which each node is operated as a small fuzzy system with fuzzy implication rules, and its fuzzy system operates with Gaussian or triangular MF in Premise part and constant or regression polynomials in consequence part. the other is polynomial nodes which several types of high-order polynomials such as linear, quadratic, and cubic form are used and are connected as various kinds of multi-variable inputs. To demonstrate the effectiveness of the proposed method, time series data for gas furnace process has been applied.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2977-2979
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• 2000

A Fuzzy Hybrid-Multilayer Perceptron (FH-MLP) Structure is proposed in this paper. proposed FH-MLP is not a fixed architecture. that is to say. the number of layers and the number of nodes in each layer of FH-MLP can be generated to adapt to the changing environment. FH-MLP consists of two parts. one is fuzzy nodes which each node is operated as a small fuzzy system with fuzzy implication rules. and its fuzzy system operates with Gaussian or Triangular membership functions in premise part and constants or regression polynomial equation in consequence part. the other is polynomial nodes which several types of high-order polynomial such as linear. quadratic. and cubic form are used and is connected as various kinds of multi-variable inputs. To demonstrate the effectiveness of the proposed method. time series data for gas furnace process has been applied.