• 한국도로학회논문집
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• 제14권6호
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• pp.121-129
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• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

• 드라이브 ㆍ 컨트롤
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• 제20권4호
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• pp.133-139
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• 2023

A weighing system calculates the bucket's excavation amount of an excavator. Usually, the excavation amount is computed by the excavator's motion equations with sensing data. But these motion equations have computing errors that are induced by assumptions to the linear systems and identification of the equation's parameters. To reduce computing errors, some commercial weighing system incorporates particular motion into the excavation process. This study introduces a linear regression model on an artificial neural network that has fewer predicted errors and doesn't need a particular pose during an excavation. Time serial data were gathered from a 30tons excavator's loading test. Then these data were preprocessed to be adjusted by MPL (Multi Layer Perceptron) or CNN (Convolutional Neural Network) based linear regression models. Each model was trained by changing hyperparameter such as layer or node numbers, drop-out rate, and kernel size. Finally ID-CNN-based linear regression model was selected.

• 품질경영학회지
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• 제47권4호
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• pp.687-700
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• 2019

Purpose: The purpose of this study is to investigate the interaction effects between price determinants of artworks. We expand the methodology in art market by applying machine learning techniques to estimate the price of artworks and compare linear regression and machine learning in terms of prediction accuracy. Methods: Moderated regression analysis was performed to verify the interaction effects of artistic characteristics on price. The moderating effects were studied by confirming the significance level of the interaction terms of the derived regression equation. In order to derive price estimation model, we use multiple linear regression analysis, which is a parametric statistical technique, and k-nearest neighbor (kNN) regression, which is a nonparametric statistical technique in machine learning methods. Results: Mostly, the influences of the price determinants of art are different according to the auction types and the artist 's reputation. However, the auction type did not control the influence of the genre of the work on the price. As a result of the analysis, the kNN regression was superior to the linear regression analysis based on the prediction accuracy. Conclusion: It provides a theoretical basis for the complexity that exists between pricing determinant factors of artworks. In addition, the nonparametric models and machine learning techniques as well as existing parameter models are implemented to estimate the artworks' price.

• 한국정보통신학회논문지
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• 제17권5호
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• pp.1076-1082
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• 2013

자기 공분산 기울기를 이용하여 음성 신호와 배경 잡음 신호를 구분할 때 구분 가능성을 높이기 위해 주파수 영역에서 음성 신호의 자기 공분산 기울기를 최대화하는 주파수 대역을 찾아내었다. 디지털 샘플링 된 음성 신호를 일정한 개수의 신호로 이루어진 블록으로 나눈 후 각 블록에 고속푸리에변환(Fast Fourier Transform, FFT)을 하여 주파수 영역으로 변환한 다음 임의의 주파수 대역에서 각 블록에서의 공분산을 구하고 이 공분산 값들을 연결하는 직선 근사를 한 후에 이 직선의 기울기를 자기 공분산 기울기로 사용하는데 이 값은 음성 신호의 특성 상 주파수 대역별로 차이가 있다. 따라서 어느 주파수 대역에서 자기 공분산 기울기가 크게 나타나는지 200개의 남성 음성 파일을 이용하여 주파수 대역별로 비교 분석하였다.

• Journal of Preventive Medicine and Public Health
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• 제22권1호
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• pp.25-28
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• 1989

Sixty-two medical records of patients with coal workers' pneumoconiosis who died in hospital as coal workers' pneumoconiosis were analysed for study of the relationship between forced expiratory volume in one second ($FEV_1$) and life expectancy in coal workers'pneumoconiosis. In the group who died of asphyxia from hemoptysis, life expectancy were well fitted with $FEV_1$(p<0.05). But others were not well fitted to simple linear regression equation. The prevalence of ECG sign of col pulmonale was more in the group of cardiorespiratory failure than asphyxia group. So, in the case of far advanced cor pulmonale, it was difficult to predict life expectancy by simple linear regression equation

• 산업경영시스템학회지
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• 제18권34호
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• pp.35-42
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• 1995

In the plastic extrusion process, product quality is influenced by work condition for temperature of cylinders and dies. The work conditions are various, so it is difficult to standardization of the work conditions. Therefore, the work conditions are depended on the workers of experience and skill. In the plastic extrusion process, it has five control heating points on the cylinder and three control heating points on the die. In addition, there is one control point on the extrusion process. It is extrusion speed. In this case, we don't know how these affect product quality. We structure the multiple linear regression equation with the temperature of cylinders and dies as independent variables and the product weight as dependent variable. We solve this equation using statistic computer package named Juse-Qcas.

• 대한교통학회지
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• 제31권1호
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• pp.65-76
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• 2013

사고발생의 주요지점인 신호교차로 교통사고 발생건수는 해마다 증가하고 있어 교통사고를 감소시키기 위한 원인 규명이 매우 필요하다. 국내에서 연구되어진 기존의 교통사고예측 모형들은 대부분 Poisson 모형 등의 비선형 회귀분석을 이용한 사고원인분석이 주를 이루고 있다. 비선형 Econometrics 분석기법들이 사고의 성격을 분석하는데 가장 중요한 통계적 기법이기는 하지만, 도로에서 발생하는 교통사고의 원인분석적 차원에서 접근하면 이런 사고예측 모형들만 가지고 사고발생의 설명변수들을 규명하는데 구조적인 한계가 발생한다. 이는 이러한 통계적 방법들이 사고의 예측력을 높이는데 중점을 두고, 이를 위해 소수의 유효한 설명변수들만을 모형식에 포함시키기 때문이다. 따라서 사고에 대해 보다 구체적인 원인규명을 위해서는 비선형회귀분석모형의 개발과 동시에 비선형 Econometrics 분석기법의 단점을 보완하는 또 다른 통계적 노력이 필요하다. 이에 본 연구에서는 Poisson기법을 이용하여 지방부 4지 신호교차로의 사고예측모형을 개발하였고, 동시에 복합적인 인과관계를 증명하는데 다중변수관계를 포괄적으로 측정하여 탐색하는 구조방정식을 이용하여 사고모형을 개발하여 Poisson 모형의 결과값과 비교 분석하였다.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2008년도 추계학술대회 논문집
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• pp.357-358
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• 2008

• 핵의학기술
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• 제14권1호
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• pp.115-121
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• 2010

방사성핵종과 방사능을 측정하는 dose calibrator의 서로 다른 두개의 기기에서 F-18 FDG을 각각 측정하고, 이 측정값에 의한 인체 내 SUV (Standard Uptake Value)에 미치는 영향은 없는지에 대하여 알아보고자 하였다. 이 연구에서 두개의 다른 dose calibrator는 CRC-15 Dual PET, CRC-15R을 사용하였다. 각 dose calibrator에서 F-18 FDG를 2 mL 주사기 3개에 볼륨 1 mL, 2 mL, 3 mL를 만들어 각각 초기 radio activity를 측정한 후 4시간 30분(270분)까지 30분 간격으로 radio activity를 각각 측정하고 기록한다. 초기 radio activity 값을 기준으로 방사선붕괴 공식으로 산출된 값(decay factor)과 dose calibrator로 측정된 값 간의 직선성을 단순선형을 통하여 분석하였다. CRC-15 Dual PET에서 가장 이상적인 값에 가까운 측정값을 볼륨을 기준으로 하여, CRC-15R에서 측정된 값을 최적화하기 위한 선형회귀식을 회귀분석을 통하여 구한다. 선형회귀식의 산출값을 적용하여 PET/CT 검사를 시행한 50명을 대상으로 lung, liver, region 부위에 ROI을 그려 SUV를 구한다. CRC-15 Dual PET, CRC-15R에서 측정한 radio activity와 그 값을 이용한 SUV를 paired t-test로 통계적으로 유의한 차이가 있는지 알아보았다. CRC-15 Dual PET과 CRC-15R에서 측정한 radio activity의 상관분석결과 1 mL의 경우 상관성을 보여주는 r값은 r=0.999이었으며, 회귀분석에 위한 선형식은 y=1.0345x+ 0.2601이었다. 2 mL의 경우 r=0.999이며, 선형회귀식은 y=1.0226x+0.1669이었다. 3 mL의 경우 r=0.999이며, 선형회귀식은 y=1.0094x+0.1577이었다. 각 세 가지 볼륨에서 얻어진 선형회귀식의 산출 값을 이용하여 구한 lung, liver, region 부위에 ROI의 SUV에서의 차이는 1 mL의 경우, lung, liver, region은 (p<0.0001)로 t-test 결과 모두 유의한 차이가 있었다. 2mL의 경우, lung (p<0.002), liver, region은 ROI의 SUV에서 유의한 차이(p<0.0001)를 보였다. 또한 3 mL의 경우, lung(p<0.044), liver, region의 유의한 차이(p<0.0001)가 있었다. F-18 FDG 검사에서 사용되는 두 개의 dose calibrator CRC-15 Dual PET, CRC-15R의 radioactivity에 대한 측정치에서는 상관관계의 차이가 없다는 것을 알 수 있었다. 그러나 이 두 값을 통해 SUV는 인체 내의 uptake 정도에 있어서는 유의한 차이를 보인다는 것을 알 수 있었다. 따라서 이 두개의 dose calibrator를 사용함에 있어서, 이 두 값이 인체 내 SUV의 차이를 고려하여 사용하여야 할 필요성이 요구된다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2009년도 춘계 학술발표회
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• pp.1043-1052
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• 2009

To derive easily the coefficient of permeability from several other soil properties, the estimation model of coefficient of permeability was proposed using linear regression analysis. The coefficient of permeability is one of the major factors to evaluate the soil characteristics. The study area is located in Kangwon-do Pyeongchang-gun Jinbu-Myeon. Soil samples of 45 spots were taken from the study area and various soil tests were carried out in laboratory. After selecting the soil factor influenced by the coefficient of permeability through the correlation analysis, the estimation model of coefficient of permeability was developed using the linear regression analysis between the selected soil factor and the coefficient of permeability from permeability test. Also, the estimation model of coefficient of permeability was compared with the results from permeability test and empirical equation, and the suitability of proposed model was proved. As the result of correlation analysis between various soil factors and the coefficient of permeability using SPSS(statistical package for the social sciences), the largest influence factor of coefficient of permeability were the effective grain size, porosity and dry unit weight. The coefficient of permeability calculated from the proposed model was similar to that resulted from permeability test. Therefore, the proposed model can be used in case of estimating the coefficient of permeability at the same soil condition like study area.