• 한국수정란이식학회지
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• 제18권3호
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• pp.215-225
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• 2003

본 시험은 한우에서 연령에 따라 혈청성분들의 변화를 알아보기 위하여 한우 866두(거세 638, 비거세 228)에 대하여 혈청 농도를 분석하여 채혈시 일령을 독립 변량으로 하고 혈청 성분들을 종속변수로 하는 다항 회귀방정식으로 추정한 결과는 다음과 같다. 거세우나 비거세우 모두 같은 차수의 회귀방정식이 접합한 혈청 성분은 IGF- I (3차식) calium(1차식) 및 IP(1차식)이었고 거세우에서는 1차식이 적합하고 비거세우에서는 3차식이 적합한 혈청 성분은 testosterone와 creatinine었다. 반면에 HDLC는 거세우에서는 3차식이 적합하나 비거세우에서는 1차식이 적합한 것으로 나타났다. 그리고 거세우에서는 2차식이 적합한데 비거세우에서는 3차식이 적합한 혈청성분은 triglyceride 농도와 globulin농도 그리고 A/G비율 등이었고, 거세우에서는 3차식이 적합하고 비거세우에서는 2차식이 적합한 혈청성분은 BUN이었으며, 거세우에서는 2차식이 적합한데 비거세우에서는 1차식이 적합한 혈청성분은 TP와 albumin이었다. 한편 cortisol은 거세우나 비거세우에서 모두 3차식까지의 회귀방정식으로는 연령에 따른 변화를 설명하기가 적합하지 않았으며 glucose는 비거세우에서는 3차식 변화를 보이고 있으나 거세우에서는 3차식까지의 회귀방정식만으로는 연령에 따른 변화를 설명하기가 어려웠다. 가장 적합한 것으로 판단되는 혈청성분들의 회귀모형 중에서 비교적 R-SQUARE 값이 높은 것(R-SQUARE value>0.1)들은 거세우에서 ICF-I, albumin, creatinine, IP, HDLC 등이었으며, 비거세우에서 testosterone, IGF-I, TP, albumin, glucose, creatinine, IP, HDLC 등으로 나타났다. 따라서 IGF-I, albumin, creatinine, IP, HDLC 등은 거세우나 비거세우 모두에서 연령에 따라 비교적 큰 변화를 보이는 혈청 성분이라고 생각된다.

• Communications for Statistical Applications and Methods
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• 제13권2호
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• pp.379-387
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• 2006

Local polynomial regression is widely used because of good properties such as such as the adaptation to various types of designs, the absence of boundary effects and minimax efficiency Choi and Hall (1998) proposed an estimator of regression function using a convex combination idea. They showed that a convex combination of three local linear estimators produces an estimator which has the same order of bias as a local cubic smoother. In this paper we suggest another estimator of regression function based on a convex combination of five local constant estimates. It turned out that this estimator has the same order of bias as a local cubic smoother.

• Journal of Welding and Joining
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• 제27권5호
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• pp.42-48
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• 2009

Pipe welding is used in various ranges such as civil engineering and ship building engineering. Until now, many technicians work for pipe welding manually under harmful, dangerous and difficult conditions. So it is necessary to install automation process. For automation pipe welding, relation between welding parameters & bead shape should be considered. Using this relation, bead shape could be expected from welding parameters. FCAW was used in this study. Instead of pipe workpiece, fillet joint plate is used, which were inclined 0,45,90,135,180 degree. By analyzing between welding parameters (current, welding speed, voltage) and bead shape parameters with non-linear multiple regression, bead shape parameters could be expected. Piecewise Cubic Hermite Interpolation was used to expect smooth curved bead shape with bead shape parameters. From these processes, bead shape could be expected from welding parameters.

• 한국운동역학회지
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• 제14권3호
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• pp.301-311
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• 2004

The purpose of this study was to verify the usefulness of the Mathcad program as a tool for the studying and teaching the sport biomechanics. A projectile motion was analyzed because it is the one of the most popular motion in sports activities. A 3 dimensional CG data for the high jump bar clear phase was used to calculate the initial velocity vector of the CG. Linear regression function and other functions such as cubic spline and derivative of Mathcad were used to calculate this vector. Finally, the approach angle to the bar and peak jump height was calculated. Programming in Mathcad was relatively easy compare to traditional computer language such as Fortran and C, because of the unique documentation method of Mathcad. Additionally the 2 and 3 dimensional graph function was very easy and useful to describe the mechanical data. If the use of Mathcad program is more popular in the field of sport biomechanics, it could greatly contribute to overcome the limit of research caused by the lack of proper programming ability.

• 한국지리정보학회지
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• 제4권1호
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• pp.57-66
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• 2001

본 연구에서는 도시표면온도를 추출하기 위하여 다시기 Landsat TM band 6 영상을 이용하여 과학기술부의 4가지 모델 즉 two-point linear model, linear regression model, quadratic regression model, cubic regression model에 대하여 각각 공간분석을 실시하였으며 그 결과를 AWS(automatic weather station) 관측자료와 상관 및 회귀분석 함과 동시에 GIS 공간분석 기법을 이용하여 도시 표면온도의 공간적 분포특성을 규명하였다. Landsat TM band 6으로부터 추출된 표면온도를 기초로 하여 토지피복별 표면온도 분포를 분석한 결과 도시 및 나지 지역이 가장 높은 온도분포대를 형성하고 있었으며, 표면온도와 NDVI간의 상관분석결과 평균 -0.85 정도의 음의 상관성을 확인할 수 있었다. 이와 같은 결과는 향후 기상환경 특성을 고려한 도시계획수립에 있어 중요한 인자로 작용할 것으로 사료된다.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.892-896
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• 2005

This paper collected 132 schools reconstruction projects in central Taiwan, which received the most serious damage from the Chi-Chi Earthquake. Regression analysis was implemented to build the prediction model of the cost and the duration for the collected projects. It is found that the cubic regression models are capable for predicting the cost and the duration of the projects contracted by the central agency of which the contracting awarding approach was based on the most advantageous tendering (MAT) approach. On the other hand, power regression models are capable for predicting the cost and the duration of the projects contracted through the low bid tendering (LBT) approach. It is also found that the performance of the regression prediction model differs in accordance with organizations that contracted the reconstruction projects.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.675-677
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• 1998

In this paper, we propose the fuzzy inference algorithm with multi-layer structure. MFIS(Multi-layer Fuzzy Inference System) uses PNN(Polynomial Neural networks) structure and the fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Hendling), and uses several types of polynomials such as linear, quadratic and cubic, as well as the biquadratic polynomial used in the GMDH. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here, the regression polynomial inference is based on consequence of fuzzy rules with the polynomial equations such as linear, quadratic and cubic equation. Each node of the MFIS is defined as fuzzy rules and its structure is a kind of neuro-fuzzy structure. We use the training and testing data set to obtain a balance between the approximation and the generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

• Computers and Concrete
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• 제16권3호
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• pp.343-356
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• 2015

1078 sets of mixtures in total that include fly ash, slag, and/or silica fume have been collected for prediction on concrete properties. A new database platform (Compos) has been developed, by which the stepwise multiple linear regression (SMLR) and BP artificial neural networks (BP ANNs) programs have been applied respectively to identify correlations between the concrete properties (strength, workability, and durability) and the dosage and/or quality of raw materials'. The results showed obvious nonlinear relations so that forecasting by using nonlinear method has clearly higher accuracy than using linear method. The forecasting accuracy rises along with the increasing of age and the prediction on cubic compressive strength have the best results, because the minimum average relative error (MARE) for 60-day cubic compressive strength was less than 8%. The precision for forecasting of concrete workability takes the second place in which the MARE is less than 15%. Forecasting on concrete durability has the lowest accuracy as its MARE has even reached 30%. These conclusions have been certified in a ready-mixed concrete plant that the synthesized MARE of 7-day/28-day strength and initial slump is less than 8%. The parameters of BP ANNs and its conformation have been discussed as well in this study.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.254-259
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• 1998

A new design methology is proposed to identify the structure and parameters of fuzzy model using PNN and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and cubic besides the biquadratic polynomial used in the GMDH. The FPNN(Fuzzy Polynomial Neural Networks) algorithm uses PNN(Polynomial Neural networks) structure and a fuzzy inference method. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here a regression polynomial inference is based on consequence of fuzzy rules with a polynomial equations such as linear, quadratic and cubic equation. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture. In this paper, we will consider a model that combines the advantage of both FPNN and PNN. Also we use the training and testing data set to obtain a balance between the approximation and generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

• 한국산림과학회지
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• 제50권1호
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• pp.29-35
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• 1980

기존(旣存)의 시계열자료(時系列資料)를 회귀분석(回歸分析)함으로써 우리나라 목재수요(木材需要)를 장기예측(長期予測)하였다. 이론적(理論的)인 검토(檢討)를 거쳐 모집(募集)된 자료(資料)는, 계량분석(計量分析)이 가능하도록 정리(整理)해서 가상적(假想的)인 수요함수(需要函數)를 도출(導出)하였다. 설명변수(説明変数)는 수요산업(需要産業)의 생산활동(生産活動)과 상대가격(相対価格)을 택했으며 모형(模型)의 예측력(予測力)을 검증(検證)한 후, 5 차(次) 5 개년계획(個年計㓰)(안(案))의 지침자료(指針資料)에 의해 총량예측치(總量予測値)를 추정(推定)하였다. 이러한 Simulation 과정(過程)을 거쳐 추정(推定)된 장기국내수요(長期國內需要)는 1987년(年)에 8,480천(千)$m^3$, 1991년(年)에는 10,670천(千)$m^3$로 증가(増加)될 것으로 전망(展望)되었으며 총수요(總需要)는 1987년(年)에 21,430천(千)$m^3$ 그리고 1991년(年)에는 27,190천(千)$m^3$가 수요(需要)될 것으로 추계(推計)되었다.