• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 추계학술발표회 논문집
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• pp.135-140
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• 2003

This study try to surface deformation analyzing and 3-D monitoring of hydro structure by close-range photogrammetry technique using 35mm metric camera. For this, the lens distortion parameters were acquired for 21mm super-wide-angle lens which is mounted in 35mm metric camera. After that, the system designed for absolute deformation analysis of object surface, and examined the application validity Also, optimum photographing condition was derived by calculated the standard deviation of this system. This system can monitor periodically changing of surface area, volume and deformation precisely after placed plate underwater. Finally, this paper suggested efficiency of absolute deformation analysis by using small format camera.

• 한국안전학회지
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• 제19권2호
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• pp.54-60
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• 2004

Flammable substances are frequently used chemical industry processes. An accurate knowledge of the ALTs(Autoignition Temperatures) is important in developing appropriate prevention and control measures in industrial fire protection. The AITs describe the minimum temperature to which a substance must be heated, without the application of a flame or spark, which will cause that substance to ignite. The AITs are dependent upon many factors, namely initial temperature, pressure, volume, fuel/air stoichiometry, catalyst material, concentration of vapor, ignition delay. This study measured relationship between the AITs and the ignition delay times by using ASTM E659-78 apparatus for methanol and ethanol. The A.A.P.E.(Average Absolute Percent Error) and the A.A.D.(Average Absolute Deviation) of the experimental and the calculated delay times by the AITs for methanol were 14.59 and 1.76 respectively. Also the A.A.P.E. and the A.A.D. of the experimental and the calculated delay times by the ATIs for ethanol were 8.33 and 0.88.

• 대한화학회지
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• 제57권3호
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• pp.370-376
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• 2013

A back propagation artificial neural network model with one hidden layer is established to correlate the liquid-liquid equilibrium data of hydrocarbon-water systems. The model has four inputs and two outputs. The network is systematically trained with 48 data points in the range of 283.15 to 405.37K. Statistical analyses show that the optimised neural network model can yield excellent agreement with experimental data(the average absolute deviations equal to 0.037% and 0.0012% for the correlated mole fractions of hydrocarbon in two coexisting liquid phases respectively). The comparison in terms of average absolute deviation between the correlated mole fractions for each binary system and literature results indicates that the artificial neural network model gives far better results. This study also shows that artificial neural network model could be developed for the phase equilibria for a family of hydrocarbon-water binaries.

• 한국안전학회지
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• 제17권4호
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• pp.126-132
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• 2002

By using the reference data, the empirical equations which describe the interrelationships of explosion properties and physical properties of n-chlorinated hydrocarbons have been derived. The properties which have been correlated are the lower and upper explosive limits, the stoichiometric coefficients, the heats of combustion, the carbon numbers. Also, the new equations using the mathematical and statistical methods for predicting the temperature dependence of lower explosive limits(LEL) of chlorinated hydrocarbons on the basis of the literature data are proposed. The fire and explosion properties calculated by the proposed equations in this research were a good agrement with literature data within a few A.A.P.E.(Average Absolute Percent Error) and A.A.D.(Average Absolute Deviation.) From a given explosive properties, by using the proposed equations, it is possible to predict to the fire and explosion characteristics for the other chlorinated hydrocarbons.

• Communications for Statistical Applications and Methods
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• 제25권6호
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• pp.591-604
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• 2018

The accelerated failure time (AFT) model is a linear model under the log-transformation of survival time that has been introduced as a useful alternative to the proportional hazards (PH) model. In this paper we propose variable-selection procedures of fixed effects in a parametric AFT model using penalized likelihood approaches. We use three popular penalty functions, least absolute shrinkage and selection operator (LASSO), adaptive LASSO and smoothly clipped absolute deviation (SCAD). With these procedures we can select important variables and estimate the fixed effects at the same time. The performance of the proposed method is evaluated using simulation studies, including the investigation of impact of misspecifying the assumed distribution. The proposed method is illustrated with a primary biliary cirrhosis (PBC) data set.

• Communications for Statistical Applications and Methods
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• 제31권4호
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• pp.393-408
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• 2024

The sparse linear discriminant analysis can be incorporated into the penalized linear regression framework, but most studies have been limited to specific convex penalties, including the least absolute selection and shrinkage operator and its variants. Within this framework, concave penalties can serve as natural counterparts of the convex penalties. Implementing the concave penalized direction vector of discrimination appears to be straightforward, but developing its theoretical properties remains challenging. In this paper, we explore a class of concave penalties that covers the smoothly clipped absolute deviation and minimax concave penalties as examples. We prove that employing concave penalties guarantees an oracle property uniformly within this penalty class, even for high-dimensional samples. Here, the oracle property implies that an ideal direction vector of discrimination can be exactly recovered through concave penalized least squares estimation. Numerical studies confirm that the theoretical results hold with finite samples.

• 산업경영시스템학회지
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• 제38권3호
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• pp.159-168
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• 2015

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company's profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.

• 한국산학기술학회논문지
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• 제18권3호
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• pp.249-257
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• 2017

신뢰성 있는 통행시간 예측을 위해 DSRC로부터 수집된 통행시간에서의 이상치(outlier) 필터링은 필수이다. 통행시간 예측을 위해 사용되는 보편적 기법인 TRANSGUIDE는 특정 분석 시간동안 통행시간의 변동이 크게 발생하는 조건에서 수집데이터의 이상치 제거를 효율적으로 처리하지 못하는 문제점이 존재한다. 이에 본 연구에서는 TRANSGUIDE의 한계점 을 보완할 수 있는 알고리즘을 제안하고자 한다. TRANSGUIDE가 특정 분석 시간대 충분한 데이터 관측이 어려울 경우 Median Absolute Deviation(MAD)를 이용하여 이상치 제거를 위한 새로운 유효 분석 영역을 설정하였다. 새로운 분석 영역 설정 후 특정 시간대 교통 조건하에서 최대 허용 가능한 이상치를 고려한 변수 ${\alpha}$, ${\beta}$를 제안하였다. 변수 ${\alpha}$, ${\beta}$를 추정하기 위해 과거 데이터와 도로 구간의 특성을 반영하였다. 개발된 알고리즘은 수도권 일반국도 3호선, 2013년 1월 1달간 DSRC 데이터가 존재하는 다차로 일반국도에 적용하였다. 누적상대도수를 이용하여 모형의 정산 수행 후 성능에 대해 정량적 평가를 수행하였다. 개발된 알고리즘은 기존의 TRANSGUIDE가 특정 조건, 즉 일정 분석 시간동안 교통 조건이 급하게 변동되는 구간에서 이상치 제거에 취한한 점을 보완하는 것으로 판단되었다. TRANSGUDIDE가 특정 조건에서 통행시간 예측이 어려울 경우 본 개발 알고리즘은 활용될 것으로 판단한다.

• International Journal of Air-Conditioning and Refrigeration
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• 제14권3호
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• pp.118-123
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• 2006

A few commonly used correlation equations of the enthalpy of vaporization essential to the analysis of refrigeration cycles are reviewed. A new four-parameter correlation equation is proposed assuming that the enthalpy of vaporization could be represented with a linear form of the temperature and an additional function which slowly decreases as the temperature increases. It is not a common practice to measure the enthalpy of vaporization by experiment; therefore, performance of the new correlation is examined using numeric data from the ASHRAE tables for 22 pure substance refrigerants. The new correlation equation and other existing ones are fitted to the data optimizing the root mean squared deviation. All data points are weighted equally and NBP (normal boiling point) is used as a fixed point since the NBP is important for refrigeration application. The new four-parameter equation yields an average absolute deviation of 0.05% for 22 refrigerants which is smaller than those of other four-parameter equations, such as Guermouche-Vergnaud (0.08%), Aerebrot (0.13%), Radoz-Lyderson (0.08%), and Somayajulu four-parameter equation (0.08%).

• 품질경영학회지
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• 제28권2호
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• pp.70-88
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• 2000

Short runs where it is neither possible nor practical to obtain sufficient subgroups to estimate accurately the control limit are common in modem business environments. In this study, the standardized control chart, Hillier's exact method, Q chart, EWMA(Exponentially Weighted Moving Average) chart for Q statistics and EWMA chart for mean and absolute deviation among many SPC(Statistical Process Control) techniques for short runs have been reviewed and advantages and disadvantages of these techniques are discussed. The simulation experiments to compare performances of these variable charts for process mean and variations are conducted for combination of subgroup size, scale and timing of shifts of process mean an/or standard deviation. Based upon simulation results, some guidelines for practitioners to choose short run SPC techniques are recommended.