• 한국소음진동공학회논문집
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• 제22권6호
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• pp.564-573
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• 2012

The objective of this study is to determine the effect for the sound quality according to the noise source and to build the sound quality index of the laundry noise. In order to compare laundry noise among the influence of noise sources, we made virtual laundry noises by synthesizing an actual laundry noise and each noise source such as a dropping noise, water noise, motor noise and circulation pump noise. We conducted a listening test by customers using virtual laundry noises. As a result of listening test, we found that the dropping noise has a decisive effect on the sound quality of the laundry noise. We conducted the multi regression analysis of sound quality for the laundry noise using the statistical data processing. It is verified to the reliability of the multi regression index by comparison with listening results and index results of other actual laundry noises. This study is expected to provide a guide line for improvement of the laundry noise.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.481-481
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• 2000

We investigated the structure-activity relationships on use of multi-layer neural networks. The relationships are techniques required in developments of medicines. Since many kinds of observations might be adopted on the techniques, we discussed some points between the observations and the properties of multi-layer neural networks. In the structure-activity relationships, an important property is not that standard deviations are nearly equal to zero for observed physiological activity, but prediction ability for unknown medicines. Since we adopted non-linear approximation, the function to represent the activity can be defined by observations; therefore, we believe that the standard deviations have not significance. The function was examined by "leave-one-out" method, which was originally introduced for the multi-regression analysis. In the linear approximation, the examination is significance, however, we believe that the method is inappropriate in case of nonlinear fitting as neural networks; therefore, we derived a new index fer the relationships from the differential of information propagation in the neural network. By using the index, we discussed physiological activity of an anti-cancer medicine, Mitomycine derivatives. The neuro-computing suggests that there is no direction to extend the anti-cancer activity of Mitomycine, which is close to the trend of anticancer developing.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 총회 및 춘계학술발표회
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• pp.217-220
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• 2003

In the case of the remediation studies, push pull test is a more time and cost effective mettled than multi-well tracer test. It also gives Just as much or more information than the traditionally used methods. But the data analysis for the hydraulic parameters, there have been some defections such as underestimation of dispersivity, requirement for effective porosity, and calculation of recovery of center of mass to estimate linear velocity. In this research, Weibull distribution function is proposed to estimate the center of mass of breakthrough curve for Push pull test. The hydraulic parameter estimation using Weibull function showed more exact values of center of mass than those of exponential regression for field test data.

• Industrial Engineering and Management Systems
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• 제1권1호
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• pp.73-78
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• 2002

In this paper, we propose a constrained optimization model for conjoint analysis (a preference decomposition technique) to improve parameter estimation by restricting the relative importance of the attributes to an extent as decided by the respondents. Quite simply, respondents are asked to provide some pairwise attribute comparisons that are then incorporated as additional constraints in a linear programming model that estimates the partial preference values. This data collection method is typical in the analytic hierarchy process. Results of a simulation study show the new model can improve the predictive accuracy in partial value estimation by ordinal east squares (OLS) regression.

• 한국의류학회지
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• 제30권1호
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• pp.83-93
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• 2006

The purpose of this study is to analyze the relationship among subjective textures, sensibilities and objective handle of knit fabrics and to provide useful information in planning and designing knit fabrics. We made 20 plain knit fabrics, as specimens, with a combination of 5 kinds of wool/rayon fiber contents and 4 kinds of stitch loop length. For the subjective evaluation, we used 29 questions of subjective textures and sensibilities and employed statistical analysis tools such as factor, Pearson's correlation analysis. An objective handle was measured by Kawabata evaluation system and HV and THV was calculated by KN-402-KT and KN-301-winter. The analysis of a Pearson's correlation with objective properties and handles and structural properties of knit fabrics demonstrated a highly linear relationship. Especially, wool/rayon contents and WT of tensile properties and loop stitch length and G of shear properties showed a correlation coefficient over 0.9. But a relationship of objective properties and subjective textures and sensibilities was non-linear and a linear multi-regression analysis showed that a objective handle had a lower prediction power in the area of subjective textures and sensibilities.

• 아동학회지
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• 제28권5호
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• pp.253-267
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• 2007

This study examined the relationships between multiple intelligences as cognitive factors and affective factors of learning motivation and academic self-concept. The data were collected from 276 4th grade elementary school students and analyzed by correlation, multi-variate analysis, and step-wise multiple regression. Results were that (1) multiple intelligences, learning motivation, and academic self-concept had statistically significant correlations among themselves. Multi-variate analysis showed that intra-personal intelligence explained 58.6% of the linear combination of learning motivation and academic self-concept. (2) Intra-personal intelligence explained 29% to 58% of learning motivation and its sub-factors of achievement motivation, internal locus of control, self-efficacy, and self-regulation. (3) Intra-personal intelligence, logical-mathematical intelligence, musical intelligence, and inter-personal intelligence were explanatory variables for academic self-concept and its sub-factors.

• 대한조선학회논문집
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• 제57권5호
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• pp.297-304
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• 2020

In this study, the prediction method was reviewed to process a cylindrical plate forming using machine learning as a data-driven approach by roll bending equipment. The calculation of the forming variables was based on the analysis using the mechanical relationship between the material properties and the roll bending machine in the bending process. Then, by applying the finite element analysis method, the accuracy of the deformation prediction model was reviewed, and a large number data set was created to apply to machine learning using the finite element analysis model for deformation prediction. As a result of the application of the machine learning model, it was confirmed that the calculation is slightly higher than the linear regression method. Applicable results were confirmed through the machine learning method.

• Imaging Science in Dentistry
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• 제40권2호
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• pp.63-68
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• 2010

Purpose : To compare the CT numbers on 3 cone-beam CT (CBCT) images with those on multi-detector CT (MDCT) image using CT phantom and to develop linear regressive equations using CT numbers to material density for all the CT scanner each. Materials and Methods : Mini CT phantom comprised of five 1 inch thick cylindrical models with 1.125 inches diameter of materials with different densities (polyethylene, polystyrene, plastic water, nylon and acrylic) was used. It was scanned in 3 CBCTs (i-CAT, Alphard VEGA, Implagraphy SC) and 1 MDCT (Somatom Emotion). The images were saved as DICOM format and CT numbers were measured using OnDemand 3D. CT numbers obtained from CBCTs and MDCT images were compared and linear regression analysis was performed for the density, $\rho$ ($g/cm^3$), as the dependent variable in terms of the CT numbers obtained from CBCTs and MDCT images. Results : CT numbers on i-CAT and Implagraphy CBCT images were smaller than those on Somatom Emotion MDCT image (p<0.05). Linear relationship on a range of materials used for this study were $\rho$=0.001H+1.07 with $R^2$ value of 0.999 for Somatom Emotion, $\rho$=0.002H+1.09 with $R^2$ value of 0.991 for Alphard VEGA, $\rho$=0.001H+1.43 with $R^2$ value of 0.980 for i-CAT and $\rho$=0.001H+1.30 with $R^2$ value of 0.975 for Implagraphy. Conclusion: CT numbers on i-CAT and Implagraphy CBCT images were not same as those on Somatom Emotion MDCT image. The linear regressive equations to determine the density from the CT numbers with very high correlation coefficient were obtained on three CBCT and MDCT scan.

• 한국전산구조공학회논문집
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• 제32권2호
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• pp.93-101
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• 2019

이 연구의 목적은 인공신경망 기법을 이용하여 사면의 내진 성능을 비교적 정확하면서도 효율적으로 예측하는 모델을 도출하는데 있다. 사면의 내진 성능은 지진입력 및 사면모델의 무작위성 및 불확실성으로 인하여 정량화하기 쉽지 않다. 이러한 배경 아래 사면에 대한 확률론적 지진 취약도 분석이 몇몇 연구자에 의해 수행되었고, 이를 기반으로 다중 선형회귀분석을 통하여 사면 내진성능에 대한 닫힌식이 제안된 바 있다. 그러나 전통적인 통계학적 선형회귀분석은 다양한 조건의 사면과 이에 따른 내진 성능 사이의 비선형적 관계를 정확하게 표현하지 못하는 한계를 보였다. 이에 따라 본 연구에서는 이러한 문제점을 극복하고자 인공신경망 기법을 사면 내진성능 예측 모델을 생성하는데 적용하였다. 도출된 모델의 유효성은 기존의 다중 선형 및 다중 비선형 회귀분석을 통한 모델과 비교하여 검증하였다. 결과적으로 이전 연구의 전통적인 통계학적 회귀 분석을 통한 모델과 비교 결과, 기본적으로 인공신경망 기법을 통하여 도출된 모델이 사면의 내진성능을 예측하는데 있어 우수한 성능을 보여주었다. 이러한 정확도 높은 모델은 향후 확률에 기반한 사면의 지진취약도 지도를 개발하고, 주요 구조물의 인근 사면으로 인한 리스크를 효과적으로 평가하는데 활용될 수 있을 것이라 기대된다.

• Korean Chemical Engineering Research
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• 제46권3호
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• pp.567-570
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• 2008

내경 0.109 m의 유동층에서 다입자경 모래에 대한 압력요동의 표준편차와 유속간의 선형회귀분석을 이용한 최소유동화속도 측정법의 적용성을 조사하였다. 다입자경 모래를 평균입자크기가 같은 Gaussian 분포에서 입자분포의 표준편차에 따른 최소유동화속도를 측정하고, 측정치를 타 연구자들의 식과 비교 검토하였다. 압력요동의 표준편차 값 선형회귀분석법과 층내 압력강하로부터 구한 최소유동화속도를 구하였다. 최소유동화속도 결정에서 유속 범위는 혼합도가 낮은 유속범위와 free bubbling 영역 이상을 제외한 범위값 이어야 하며, 이 유속범위에서 측정위치는 혼합이 양호한 층 중앙이 가장 적절하다.