• 생물환경조절학회지
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• 제4권2호
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• pp.125-130
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• 1995

동계 시설내 온도 및 광도가 고추의 생장에 미치는 영향을 알기 위하여 생장상내에서 인공적으로 온도 3수준(10, 20 및 3$0^{\circ}C$)과 광도 3수준(5, 15 및 25klux)을 7주간 조합 처리한 결과 나타난 생장반응은 다음과 같다. 1. 생장상내에서 고추 시묘의 초장, 엽면적 및 건물중의 생장은 3$0^{\circ}C$$\times$25klux 처리구에서 가장 양호했고, 각 온도에서도 광도의 증가에 따른 생장의 증가반응이 뚜렷하였다. 2. 처리후 7주째의 생장량을 multiple regression polynomial로 수식화한 결과 초장, 엽수, 엽면적, 경건물 및 지하부 건물중은 수식고정이 적합하였다. 3. 지상부 건물중에 대한 다중 회귀식을 광도와 온도로 편미분한 이론치를 이용하여 단위온도 증가에 대한 단위광도의 향상도와 단위광도 증가에 대한 단위온도 증가의 반응표면을 도식화한 결과 저온화에서의 광도증가는 지상부 건물중 증가반응의 향상도를 크게 높였으나, 광도 10k1ux이하나 온도가 2$0^{\circ}C$이상에서는 온도의 역할이 더 크게 나타났다. 단위광도 증가에 대한 온도반응의 증가에서도 동일한 경향으로 나타나 온도와 광도의 강한 상보성을 나타내었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.295-297
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• 2000

In case of power demand forecasting the most important problem is to deal with the load of special-days, Accordingly, this paper presents a method that forecasting special-days load with regression models and neural networks. Special-days load in summer season was forecasted by the multiple regression models using weekday change ratio Neural networks models uses pattern conversion ratio, and orthogonal polynomial models was directly forecasted using past special-days load data. forecasting result obtains % forecast error of about $1{\sim}2[%]$. Therefore, it is possible to forecast long and short special-days load.

• 기술혁신학회지
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• 제19권4호
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• pp.687-710
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• 2016

본 연구의 목적은 국가연구개발사업을 대상으로 각 연구단계별 연구개발 지출과 논문 성과 간의 시차구조를 분석하는 것이다. 이에 본 연구는 6T(IT, BT, NT, ST, ET, CT) 기술로 범주화 된 104개 기술의 횡단면 자료와 2007년부터 2014년까지의 시계열로 구성된 패널자료를 분석 자료로서 활용하였으며, 일반적인 시차분포모형을 통해 회귀분석을 실시할 경우 다중공선성이 내포된 분석결과가 도출될 가능성이 크기 때문에 다항시차분포모형을 통해 시차효과를 분석하였다. 그 결과 기초연구의 경우 4년 간 비교적 고른 분포를 보이는 것으로 나타났고, 응용연구와 개발연구의 경우 각각 3년, 2년간 투자효과가 유효한 것으로 확인되었다. 이러한 결과로 보건대, 국가연구개발사업의 논문 성과를 진단함에 있어 각 연구개발단계별 시차적 특성을 감안한 분석 및 평가가 신중하게 고려될 필요가 있을 것이다.

• Animal Bioscience
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• 제37권5호
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• pp.817-825
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• 2024

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

• Journal of the Optical Society of Korea
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• 제19권1호
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• pp.102-111
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• 2015

This paper proposes an algorithm for recovering the colors of objects from multiple near-infrared (near-IR) images. The International Commission on Illumination (CIE) color coordinates of objects are recovered from a series of gray images captured under multiple spectral near-IR illuminations using polynomial regression. The feasibility of the proposed algorithm is tested experimentally by using 24 color patches of the Color Rendition Chart. The experimental apparatus is composed of a monochrome digital camera without an IR cut-off filter and a custom-designed LED illuminator emitting multiple spectral near-IR illuminations, with peak wavelengths near the red edge of the visible band, namely at 700, 740, 780, and 860 nm. The average color difference between the original and the recovered colors for all 24 patches was found to be 11.1. However, if some particular patches with high value are disregarded, the average color difference is reduced to 4.2, and this value is within the acceptability tolerance for complex image on the display.

• 품질경영학회지
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• 제23권3호
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• pp.84-92
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• 1995

A method is proposed for the simultaneous optimization of several response functions that depend on the same set of controllable variables and are adequately represented by a response surface model (polynomial regression model) with the same degree and with constraint that the individual responses have the target values. First, the multiple responses data are checked for linear dependencies among the responses by eigenvalue analysis. Thus a set of responses with no linear functional relationships is used in developing a function that measures the distance estimated responses from the target values. We choose the optimal condition that minimizes this measure. Also, under the different degree of importance two step procedures are proposed.

• 조명전기설비학회논문지
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• 제13권4호
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• pp.75-81
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• 1999

본 연구에서는 직교 다항 회귀모델을 이용하여 수용설비의 소비전력을 추정하는 알고리즘을 제시한다. 제시하는 추정모델은 수학적인 방법인 외삽법과 상관법을 이용할 수 있고, 저차의 방정식을 고차의 방정식에 어떤 수정도 없이 그대로 저차의 계수를 사용할 수 있어 다중 회귀모델에 비해 계산시간 및 계산용량이 절약되며, 이것의 반대 상황도 성립하여 소비전력을 추정하는데 매우 유용한 방법이라 할 수 있다. 추정 모델을 2차, 3차 4차로 구성하고 추정한 결과 4차 모델이 양호한 결과를 나타내었으며, 상관법에 의해 수용설비의 소비전력을 추정한 결과 추정 오차율이 2[%] 이하로 양호하였다. 그리고 외삽법에 의해 1997년의 소비전력을 추정한 결과 4차 모델의 추정 오차율이 1[%]대를 나와 추정모델의 유효성과 타당성을 검증할 수 있었다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.993-996
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• 2005

High speed machining(HSM) technique is widely used in the appliance, automobile part and mold industries, which has many advantages such as good quality, low cost and rapid machining time. but it also has problems like tool break, smooth tool path, and so on. In particular, small size end mill is easy to break, so it must be changed before interrupting operation. Generally, the tool life of small size end mill is effected by the milling conditions whose evaluated parameters are spindle, feedrate, and width of cut. The experiments are carried out by full factorial design of experiments using and orthogonal array. This paper shows optimal combination and mathematical model for tool life, and the analysis of variance(ANOVA) is employed to analyze the main effects and the interactions of these milling parameters and the second-order polynomial regression model with three independent variables is estimated to predict tool life by multiple regression analysis.

• 한국정밀공학회지
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• 제23권2호
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• pp.73-80
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• 2006

High speed machining(HSM) technique is widely used in the appliance, automobile part and mold industries, because it has many advantages such as good quality, low cost and rapid machining time. But it also has problems such as tool breakage, smooth tool path, and so on. In particular, small size end mill is easy to break, so it must be changed before interrupting operation. Generally, the tool life of small size end mill is affected by the milling conditions whose selected parameters are spindle speed, feedrate, and width of cut. The experiments were carried out by full factorial design of experiments using an orthogonal array. This paper shows optimal combination and mathematical model for tool life, Therefore, the analysis of variance(ANOVA) is employed to analyze the main effects and the interactions of these milling parameters and the second-order polynomial regression model with three independent variables is estimated to predict tool life by multiple regression analysis.

• Journal of Welding and Joining
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• 제34권2호
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• pp.67-72
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• 2016

Aluminum alloy is one of light weight material and it is used to make LNG tank and ship. However, in order to weld aluminum alloy high density heat source is needed. In this paper, I-butt welding of Al 5083 with 6mm thickness using Plasma-MIG welding was carried out. The experiment was performed to investigate the influence of plasma-MIG welding parameters such as plasma current, wire feeding rate, MIG-welding voltage and welding speed on the tensile strength of weld. In addition we suggested 3 strength estimation models which are second order polynomial regression model, multiple nonlinear regression model and neural network model. The estimation performance of 3 models was evaluated in terms of average error rate (AER) and their values were 0.125, 0.238, and 0.021 respectively. Neural network model which has training concept and reflects non -linearity was best estimation performance.