• Journal of the military operations research society of Korea
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• v.36 no.3
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• pp.43-56
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• 2010

Recently, the acquisition environment of the Korean defense weapon system is emphasizing more the importance of cost analysis in terms of efficient execution for defense acquisition budget. While cost analysis, however, is emphasized in law and process, its infrastructures are still insufficient We have been using computerized cost models to obtain an estimate at early phase of project. But those models have been developed by foreign companies, and so they have many limitations when using in Korean defense environment. For this reason, it began to sympathize that we need the development of the Korean version cost estimation model suitable for our defense industry environment, and now many studies are proceeding. In this study, we suggest Cost Estimating Relationships(CERs) developing methodologies which is key logics of Korean version cost estimation model. Especially, we proposed a new CER's development process depending upon data characteristics such as, multicolinearity, outlier, small samples and heteroscedasticity. Also, we presented a case study for artillery weapon system using these methods we developed. We find that these CERs could be verified through theoretical methods.

• Exercise Science
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• v.21 no.2
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• pp.231-242
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• 2012

The purpose of this study was to develop the prediction model of VO₂max using submaximal metabolic responses from the Bruce protocol, HR responses at several stages and 1,200 m running record, and to compare and analyse the validity of these prediction models. The subjects were consisted of 255 male(133 male for 1,200 m running). They were participated maximal exercise testing with Bruce protocol, and the metabolic responses were measured in the end of the first(3 minute), second stage(6 minute), and 1,200 m running record. Measurement items were VO₂(㎖/kg/min), VCO₂(㎖/kg/min), VE(L/min), HR(bpm) of 3 and 6 minute, time to HR 150 bpm and 170 bpm, HR difference between Bruce protocol 6 and 3 minute, 1,200 m running record. Analyzing with all variables using enter method, the multiple R of total variable model was 0.642(p<.01), SEE was 4.38 ㎖/kg/min, CV was 10.8 %, but multicolinearity was appeared. The multiple R of 3 minutes model 1 and model 2 were 0.341 and 0.461, SEE was 6.05 and 5.72 ㎖/kg/min, CV was 14.9 and 14.1%, and multicolinearity did not appeared. The multiple R of 6 minutes model 1 and model 2 were 0.350 and 0.456, SEE was 6.03 and 5.74 ㎖/kg/min, CV was 14.9 and 14.2%, and multicolinearity did not appeared. The R of HR 170 and HR 170 model were 0.151 and 0.154, SEE were 6.36~6.37 ㎖/kg/min, CV were 15.7%. The R of 1,200 m running model was 0.444, SEE was 4.82 ㎖/kg/min, CV were 11.9%. In conclusion, with considering usefulness and convenience through the validity of these prediction models, the prediction model of VO₂max recommended 6 and 3 minute model, and the validity of HR model and 1,200 m running model were moderately low.

• Journal of Korean Society of Transportation
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• v.11 no.1
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• pp.55-66
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• 1993

본 논문에서는 최근에 소개된 일반화중력모형(Generalized Gravity Model)파라메터의 최우추정치(Maximum Likelihood Estimates) 계산을 위한 새로운 알고리즘을 이론적으로 도출하였다. 개발된 알고리즘은 첫째 계산속도, 둘째 정밀도, 셋째 모형변수(예컨데 통행시간, 통행비용 등)들 간에 공선성(multicolinearity)이 존재할 경우의 계산능력, 넷째 대규모 스케일의 기.종점자료(large O-D Matrices)에 적용시의 계산능력, 다섯째 모형변수의 개수에 따른 계산능력의 평가기준에서 그 계산실적이 기존의 알고리즘과 비교 평가 되었다. 제안된 기법중에서 Modified Scoring 기법은 계산속도 및 정밀도등 앞서 나열한 계산능력의 평가기준 중 모든 부문에서 매우 탁월한 계산실적을 보이는 것으로 판명되었다. 따라서 최선의 추정치를 보장하는 최우추정기법이 대규모 스케일의 교통계획 적용에도 큰 비용(시간)부담없이 손쉽게 적용될 수 있게 되었다. 제안된 새로운 알고리즘의 적용시 교통계획분야에 가져올 수 있는 기대효과는 다음과 같다. 첫째, 최우추정법이 대규모 O-D 통행표에 쉽게 적용될 수 있고 또한 PC등 소형 컴퓨터에서도 처리가 쉽다. 둘째, 모형설명변수의 자유로운 선택등 통계적실험(experimentation)을 가능케 한다. 셋째, 중력모형이 내재되어 있는 결합모형(Combined Model)의 정산속도를 높인다. 넷째, IVHS(Intelligent Vehicle and Highway System)와 같은 분야에서 온라인(On-line)모형정산을 가능케 할 수 있다.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.565-576
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• 2012

Cost estimates are necessary for government acquisition program to support decisions about funding, to develop annual budget requests and to validate resource requirements at key decision points. Many researches have been done about cost estimating technique recently. Parametric cost estimating models based on CERs(Cost Estimating Relationships) have been mainly used using regression method with historical data. However, there are many restrictions in developing Korean version CERs because the number of data points are too small. Specially, data collection and data management system are unstable in Korean defense environment, when developing CERs. In this research, we analyzed the historical data, and found some cost drivers in guided weapon system area. We developed the Acquisition Unit Cost CER using the regression to remove multicollinearity in the historical data. So we could overcome the restriction of the insufficient sample number. This research as a first attempt is meaningful in terms of obtaining our own Acquisition Unit Cost CER using historical cost and physical characteristic in Korean development environment.

• KIEAE Journal
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• v.9 no.1
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• pp.107-113
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• 2009

The energy cost is resulted from the energy use. Its sources are divided into some types and depended on the building use or energy-use type. The energy cost should be affected by the amount of the energy use. The cost could be calculated to consider various factors such as the insulation, heating type, building shape and others. But it can not consider all of the affect factors to the energy cost and need to categorize the factors to the condition for estimating the cost. In this paper, it aimed at providing the estimation model in linear equation and multiple linear regression, utilizing the building exterior condition and management characteristics in apartment housing. Its survey are conducted in two parts of management characteristics and building exterior condition. The correlation analysis is conducted to get rid of the multicolinearity among the inputted factors. The number of linear equation model is 11 and includes the 1st, 2nd and 3rd equation function, power function and others. Among these, it suggested the 2nd and 3rd function and power function in terms of the statistics. In multiple linear regression model, the building volume and management area are inputted to the estimation.

• 한국체육학회지인문사회과학편
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• v.51 no.3
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• pp.373-382
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• 2012

The purpose of this study is to predict VO₂max with body index and submaximal metabolic responses. The subjects are consisted of 250 male aging from 18 to 34 and we separated them into two groups randomly; 179 for a sample, 71 for a cross-validation group. They went through maximal exercise testing with Bruce protocol, and we measured the metabolic responses in the end of the first(3 minute) and second stage(6 minute). To predict VO₂max, we applied multiple regression analysis to the sample with stepwise method. Model 1's variables are weight, 6 minute HR and 6 minute VO₂(R=0.64, SEE=4.74, CV=11.7%, p<.01), and the equation is VO₂max(ml/kg/min)= 72.256-0.340(Weight)-0.220(6minHR)+0.013(6minVO₂). Model 2's variables are weight, 6 minute HR, 6 minute VO₂, and 6 minute VCO₂(R=0.67, SEE=4.59, CV=11.3%, p<.01), and the equation is VO₂max(ml/kg/min)= 68.699-0.277(Weight) -0.206(6minHR)+0.020(6minVO₂)-0.009(6minVCO₂). And the result did not show multicolinearity for both models. Model 2 demonstrated more correlation compared to Model 1. However, when we conducted cross-validation of those models with 71 men, measured VO₂max and estimated VO₂ Max had statistical significance with correlation (R=0.53, 0.56, P<.01). Although both models are functional with validity considering their simplicity and utility, Model 2 has more accuracy.