• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2000년도 춘계학술대회논문집
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• pp.26-29
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• 2000

drawbead expert models are developed for calculating drawbead restraining force and drawbead-exit thinnings which are boundary conditions in FEM stamping simulation employing the linear multiple regression method by which the deviation of drawing characteristics between drawing test and mathematical model is minimized. In order to show the efficiency and accuracy of an expert drawbead model a finite element simulation of auto-body panel stamping is carried out. The finite element simulation shows that the expert drawbead model provides the accurate solution guarantees the stable convergence and the merit in the computation time.

• Asian-Australasian Journal of Animal Sciences
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• 제9권4호
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• pp.439-447
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• 1996

Monthly test day production for 12,020 records, were collected from six of the largest specialized dairy farms located in central region of the Kingdom of Saudi Arabia. The records described lactating cows in four parities and two seasons of calving. Monthly test day records were fitted using Wood's model $At{{^b}{_e}}^{-ct}$ with multiple and additive error term. Linear and non-linear regression models were used to find the estimates of the parameters necessary to draw the lactation curves. The shape of the lactation curves of different parities showed that third lactation has the heighest peak (43.08 kg) for linear regression model and (42.08 kg) for non-linear regression model. Fourth lactation has the lowest peak (24.00kg) for linear regression model and (25.64 kg) for non-linear regression models. Cows of second and third lactations reached the peak at 58 day for both linear and non-linear regression models. Cows of first lactation were more persistent and had late peak at 68 and 67 days for both models respectively. While, third lactation cows were lower persistent and had early peak at 58 day for both models. Cows calved at winter months have higher starting values (A), higher ascending slope (b) and higher decending slope (c). Least square means of milk yield of the first four parities and for overall data were 6,653, 7,659, 7,482, 6,988 and 7,614 kg respectively. The corresponding lactation period were 358, 367, 350, 363 and 364 days respectively.

• 운동영양학회지
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• 제14권2호
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• pp.81-86
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• 2010

The purpose of this study was to identify the factors associated with child's Body Mass Index (BMI) and physical activity. The participants (n = 133) were Korean juveniles (3^rd and 4^th graders) and their parents. They completed a questionnaire packet including the SPARK (Sports, Play, and Active Recreation for Kids) survey and the parent equivalent survey. Correlation, multiple linear regression and binary logistic regression analyses were applied to identify the association between child's BMI and 10 factors of SPARK as predict or variables. 25.6% of the participants were classified as overweight (21.1%) or obesity (4.5%). 3 parental factors including mother's BMI and frequency of mother's and father's physical activity were identified as significant predictors of children's BMI. The 10 variables accounted for 28% of the variance (p<.01) in the linear regression model. These results provide insight into parental factors which are related to a child's BMI and physical activity. Parental role modeling which refers to parents' efforts to model an active lifestyle for children plays an important role.

• 한국산업보건학회지
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• 제16권4호
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• pp.398-412
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• 2006

The purpose of this study is to investigate the relationship between the acceleration of vibration by the powered hand tools used in the shipbuilding industry, and to develop the prospective prevalence model for the hand-arm vibration syndrome among the shipbuilding workers.The acceleration levels and frequencies of six types of grinder were measured using the ISO5349 method along with the time of exposure to the vibration from the powered hand tools. Medical examination for 114 workers were performed using the cold provocation test. Comparisons were made between the estimated prevalence of hand-arm vibration syndrome from ISO5349 and the observed values from the medical examinations. By multiple regression, we developed the prospective prevalence model of hand-arm vibration syndrome produced by the hand tools used in the shipbuilding industry. 4 hour-energy-equivalent frequency-weighted accelerations were $6.23m/s^2$ in the grinding job done after welding, and $13.39m/s^2$ in the grinding job done before painting. The mean exposure time while holding powered hand tools was 4.64 hours. Prevalence rates of Raynaud's Phenomenon were 12.04% in the grinding after soldering, and 42.9% in the grinding before painting measured using the ISO5349 method. After exposure to vibration for 10.79 years, about a half of the workers in the grinding after welding could developed Raynaud's Phenomenon. For the workers in the grinding before painting, the latency was 5.02 years. The ISO equation for dose response relationship was not significantly correlated with observed recovery rates of finger skin temperatures, blood flows and amplitudes of nerve conduction velocities. A multiple regression model for dose-response relationship was proposed from the results. Recovery rate of the skin temperatures = -0.668+ 0.337 ${\times}$ 4 hour energy equivalent frequency-weighted accelerations + 0.767 ${\times}$ duration of vibration exposure(years) The validity was proved by multiple regression analysis after correlation transformation and regression results based on model-building data and validation data.

• 상하수도학회지
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• 제34권6호
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• pp.503-512
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• 2020

Identifying the water circulation status is one of the indispensable processes for watershed management in an urban area. Recently, various water circulation models have been developed to simulate the water circulation, but it takes a lot of time and cost to make a water circulation model that could adapt the characteristics of the watershed. This paper aims to develop a water circulation state estimation model that could easily calculate the status of water circulation in an urban watershed by using multiple linear regression analysis. The study watershed is a watershed in Seoul that applied the impermeable area ratio in 1962 and 2000. And, It was divided into 73 watersheds in order to consider changes in water circulation status according to the urban characteristic factors. The input data of the SHER(Similar Hydrologic Element Response) model, a water circulation model, were used as data for the urban characteristic factors of each watershed. A total of seven factors were considered as urban characteristic factors. Those factors included annual precipitation, watershed area, average land-surface slope, impervious surface ratio, coefficient of saturated permeability, hydraulic gradient of groundwater surface, and length of contact line with downstream block. With significance probabilities (or p-values) of 0.05 and below, all five models showed significant results in estimating the water circulation status such as the surface runoff rate and the evapotranspiration rate. The model that was applied all seven urban characteristics factors, can calculate the most similar results such as the existing water circulation model. The water circulation estimation model developed in this study is not only useful to simply estimate the water circulation status of ungauged watersheds but can also provide data for parameter calibration and validation.

• 한국ITS학회 논문지
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• 제21권6호
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• pp.87-96
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• 2022

고령보행자를 포함한 교통약자는 신체적 능력이 저하되어 보행속도가 상대적으로 낮으며, 인지반응시간이 느린 특성을 가지고 있지만, 현재 교통약자를 위한 보행신호는 0.8m/s로 일률적으로 적용하고 있다. 문제점을 개선하기 위하여 스마트 횡단시스템이 개발되어 운영되고 있지만, 보행자별 적정 보행속도를 반영한 신호운영이 이루어지지 못하고 있다. 본 연구에서는 교통약자비율이 높은 지역에서 수집된 영상정보를 활용하여, 교통약자의 종류, 보행자의 수, 도로의 기하구조 등을 고려한 신경망모형과 다중회귀모형기반의 횡단속도 추정모델을 개발하였다. 이를 통해 개발된 모델을 스마트횡단시스템에 적용하여 실시간 교통약자에 따른 최적 보행신호 제공을 지원하고자 하였다. 경기도 파주시의 도시 교통 네트워크에서 수집된 실제 교통 상황 데이터 2,400개를 사용하였다. 모델의 성능은 상관계수, 평균 절대오차 등 7개의 선택된 지표를 통해 평가되었다. 다중선형회귀모델은 상관 계수가 0.652이고 MAE가 0.182였으며, 신경망모델은 상관계수가 0.823이고 MAE가 0.105로 나타나. 신경망모델이 더 높은 예측력을 보였다.

• 한국지능시스템학회논문지
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• 제12권4호
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• pp.334-340
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• 2002

본 논문에서는 상대적으로 큰 퍼지 엔트로피를 갖는 입력-출력 데이터 집단에 다중 회귀 분석을 적용하여 다차원 평면 클러스터를 생성하고, 이 클러스터를 새로운 퍼지 모델의 규칙으로 추가한 후 모델 파라미터의 개략 동조와 정밀 동조를 반복 수행하는 자기구성 퍼지 모델링을 제안한다 Weighted recursive least squared 알고리즘과 fuzzy C-regression model 클러스터링에 의해 퍼지 모델의 파라미터를 개략적으로 동조한 후 gradient descent 알고리즘에 의해 파라미터를 정밀 동조하면서 감수분열 유전 알고리즘을 이용하여 최적의 학습률을 탐색한다. 그리고, 자기구성 퍼지 모델링 기법을 이용하여 Box-Jenkins의 가스로 데이터, 비선형 다변수 정적 함수의 데이터, 하수처리 활성오니 공정과 Mackey-Glass 시계열 데이터의 모델링을 수행하고, 기존의 방법에 의한 모델링 결과와 비교하여 그 성능을 입증한다.

• 대한산업공학회지
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• 제28권3호
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• pp.331-343
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• 2002

This paper proposes a fuzzy rule-based model as a means to build usability models between emotional satisfaction and design variables of consumer products. Based on a subtractive clustering algorithm, this model obtains partially overlapping rules from existing data and builds multiple local models each of which has a form of a linear regression equation. The best subset procedure and cross validation technique are used to select appropriate input variables. The proposed technique was applied to the modeling of luxuriousness, balance, and attractiveness of office chairs. For comparison, regression models were built on the same data in two different ways; one using only potentially important variables selected by the design experts, and the other using all the design variables available. The results showed that the fuzzy rule-based model had a great benefit in terms of the number of variables included in the model. They also turned out to be adequate for predicting the usability of a new product. Better yet, the information on the product classes and their satisfaction levels can be obtained by interpreting the rules. The models, when combined with the information from the regression models, are expected to help the designers gain valuable insights in designing a new product.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.475-485
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• 2008

One of main issues in watermarking is to resolve the strength of watermark for solving the problem of trade-off between fidelity and robustness of watermarking. In the previous research, the strength of watermark has been resolved fixed value generally without considering local image characteristics such as image brightness, contrast, and edge. This paper proposes a new model to predict the strength of watermark considering local image characteristics such as image brightness, contrast, and edge for digital wavelet transform(DWT)-based image watermarking. For the study, psychological experiment was fulfilled to measure the human image perception and regression analysis showed the proposed model was statistically significant at the level of ${\alpha}\;=\;0.01$. Also the model is practically validated on fidelity and robustness of watermarking.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2006년 추계학술발표대회 개요집
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• pp.271-273
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• 2006

This paper focuses on the developed empirical models for the prediction on top-bead width in GMA(Gas Metal Arc) welding process. Three empirical models have been developed: linear, curvilinear and an intelligent model. Regression analysis was employed fur optimization of the coefficients of linear and curvilinear model, while Genetic Algorithm(GA) was utilized to estimate the coefficients of intelligent model. Not only the fitting of these models were checked, but also the prediction on top-bead width was carried out. ANOVA analysis and contour plots were respectively employed to represent main and interaction effects between process parameters on top-bead width.