• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.676-679
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• 1997

The present paper is concerned with the optimal deslgn that the static spring rate of the fiber-reinforcement composite spring is fitted to that of the steel leaf spring. The thickness and w~dth of springs were selected as deslgn variables. And object functions of the regression model were obtained through the analysis with a common analytic program. After regression coefficients were calculated to get functions of the regression model, optimal solutions were calculated with DOT. E-GlassIEpoxy and CarbonIEpoxy were used as fiber reinforcement materials in the design, which were compared and analyzed with the steel leaf spring. It was found that the static spring rate of the optimal model was almost similar to that of the existing spring.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.4 no.4
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• pp.14-20
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• 2005

This paper deals with the study of feasibility of rotary carbide tools in the machining of aluminium alloy. A rotary tool holder was designed and manufactured for this work. Experiments were performed using Taguchi methods and regression analysis to analyse the influence of various factors and their interactions on the cutting characteristics of rotary carbide tools during machining. The cutting force is influenced the most greatly at the inclination angle. The surface roughness is influenced distinctly at depth of cut. It deduced an equation to predict cutting force and surface roughness. Hence, it could be concluded here that the proposed model agrees with the experimental data satisfactorily.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.450-453
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• 1997

There are many studies about optimization using genetic algorithm and desirability function. It's very important to find the optimal value of something like response surface or regression model. In this study I ind~cate the problem using the old type desirability function, and suggest the new type desirabhty functton that can fix the problem better, and simulate the model. Then I'll suggest the form of desirability function to find the optimum value of response surfaces which are made by mean and standard deviation using genetic algorithm and new type desirability function.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.126-129
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• 2012

In this work a new correlation has been made to predict the solar radiation for 16 different areas over Korea by estimating the regression coefficients taking into account cloud hours of bright sunshine. Particularly, the multiple linear regression model proposed shows reliable results for estimating the global radiation on a horizontal surface with monthly average deviation of -0.26 to +0.53% and each station annual average deviation of -1.61 to +1.7% from measured values.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.525-530
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• 2000

The loss of soil and nutrients from land surfaces to surface water supplies continues to be an important source of nonpoint source pollution. This study was initiate to develop an empirical relationship among the contaminants. SS, COD, T-N, and T-P were collected from agricultural surface water quality studies carried out in Hwasung-Gun, Kyonggi-Do. Correlation analysis, regression analysis, and reliability analysis were conducted. The regression equations were developed between SS and COD, SS and T-P, COD and T-P, and the resulting r$\^$2/ value was over 0.78. The regression equation enables a reasonable prediction of phosphorus concentration and COD concentration for known suspended solid concentration.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.566-573
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• 1999

This paper is the result of sensitivity analysis of derailment with respect to the selected suspension elements for the rail vehicle. Derailment phenominon has been explained by the derailment quotient. Thus, the sensitivity of derailment is suggested by a response surface model(RSM) which is a functional relationship between derailment quotient and characteristics of suspension elements. To summarize generation of RSM, we can introduce the procedure of sensitivity analysis as follows. First, to form a RSM, a experiment is performed by a dynamic analysis code, VAMPIRE according to a kind of the design of experiments(DOE). Second, RSM is constructed to a 1$\^$st/ order polynomial and then main effect fators are screened through the stepwise regression. Finally, we can see the sensitivity level through the RSM which only consists of the main effect factors and is expressed by the liner, interaction and quadratic effect terms.

• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.8-13
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• 2015

The experimental design methodology was applied in the drop tube furnace (DTF) to predict the various combustion properties according to the operating conditions and to assess the coal plant safety. Response surface method (RSM) was introduced as a design of experiment, and the database for RSM was set with the numerical simulation of DTF. The dependent variables such as burnout ratios (BOR) of coal and $CO/CO_2$ ratios were mathematically described as a function of three independent variables (coal particle size, carrier gas flow rate, wall temperature) being modeled by the use of the central composite design (CCD), and evaluated using a second-order polynomial multiple regression model. The prediction of BOR showed a high coefficient of determination (R2) value, thus ensuring a satisfactory adjustment of the second-order polynomial multiple regression model with the simulation data. However, $CO/CO_2$ ratio had a big difference between calculated values and predicted values using conventional RSM, which might be mainly due to the dependent variable increses or decrease very steeply, and hence the second order polynomial cannot follow the rates. To relax the increasing rate of dependent variable, $CO/CO_2$ ratio was taken as common logarithms and worked again with RSM. The application of logarithms in the transformation of dependent variables showed that the accuracy was highly enhanced and predicted the simulation data well.

• Geomechanics and Engineering
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• v.8 no.4
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• pp.511-521
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• 2015

It is a common failure type that high-filled embankment slope sideslips. The deformation mechanism and factors influencing the sideslip of embankment slope is the key to reduce the probability of this kind of engineering disaster. Taking Liujiawan high-filled embankment slope as an example, the deformation and failure characteristics of embankment slope and sheet-pile wall are studied, and the factors influencing instability are analyzed, then the correlation of deformation rate of the anti-slide plies and each factor is calculated with multivariate linear regression analysis. The result shows that: (1) The length of anchoring segment is not long enough, and displacement direction of embankment and retaining structure are perpendicular to the trend of the highway; (2) The length of the cantilever segment is so large that the active earth pressures behind the piles are very large. Additionally, the surface drainage is not smooth, which leads to form a potential sliding zone between bottom of the backfill and the primary surface; (3) The thickness of the backfill and the length of the anti-slide pile cantilever segment have positive correlation with the deformation whereas the thickness of anti-slide pile through mudstone has a negative correlation with the deformation. On the other hand the surface water is a little disadvantage on the embankment stability.

• Asia pacific journal of information systems
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• v.16 no.2
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• pp.47-67
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• 2006

This study takes a quantitative approach to the influence of TTF (Task-Technology Fit) on the individual's use and performance of GSS (Group Support Systems), while traditional studies on TTF have taken the experimental approach to explore the characteristic fit between diverse tasks and technologies. We have the following two research inquires: Are the IS use and performance maximized when information technologies are provided by the exact amount of demand?; and, Does TTF at the high level between task and IT produce better IS use (or performance) than at the low level? To investigate these issues, we use the polynomial regression analysis and response surface methodology of Edwards (1993) instead of traditional direct measure of TTF. This method measures the degree of desired and actual level of information technologies in conducting tasks, and traces the dynamic changes of dependent variables (IS use and performance) according to the variances of each independent variable. Our results conclude that user's IS use and performance are maximized when information technologies are actually provided by no more or less than the desired level. We also found that TTF at the high level promotes better IS use and performance than TTF at the low level.

• Proceeding of EDISON Challenge
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• 2014.03a
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• pp.1-13
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• 2014

Potential Energy Surface(PES)를 양자 계산을 통해 알아내는 것은 화학 반응을 이해하는 데에 큰 도움이 된다. 이를테면 Transition State(TS)의 configuration을 알 수 있고, 따라서 reaction path와 활성화 에너지 값을 예측하여, 진행시키고자 하는 화학반응의 이해를 도울 수 있다. 하지만 PES를 그리기 위해서는 해당 분자의 다양한 configuration에 대한 singlet point energy 계산이 필요하기 때문에, 계산적인 측면에서 많은 비용을 요구한다. 따라서 product와 reactant의 구조와 같은 critical point의 정보를 이용하여 최소한의 configuration을 sampling하여 전체 PES를 재구성하는 기계학습 알고리즘을 개발하여 다차원 PES 상에서의 화학반응의 예측을 가능하게 하고자 한다. 본 연구에서는 Barbaralane의 두 안정화 된 구조의 critical point로 하여 이 주변을 random normal distribution하여, B3LYP/6-31G(d) level의 DFT 계산을 통해 relaxed scanning하여 구조와 에너지를 구하였으며, 이 정보를 Support Vector Regression(SVR) 알고리즘을 적용하여 PES를 재구현하였으며, 반응경로와 TS의 구조 그리고 활성화 에너지를 구하였다. 또한 본 기계학습 알고리즘을 바닥상태에서 일어나는 반응이 아닌, 들뜬 상태와 전자 구조가 변하는 화학반응, avoid crossing, conical intersection과 같은 Non-adiabatic frame에서 일어나는 현상에 적용 가능성을 논하고자 한다.