• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.524-529
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• 1993

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called "component cost" to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. One possible use of component costs is for model reduction by deleting those components that have the smallest component cost. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. When the dynamics of this input are added to the plant, which is to be reduced by CCA, the algorithm for model reduction process will be called Weighted Component Cost Analysis (WCCA). Closed-form analytical expressions of component costs for continuous time case, are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems beyond Lyapunov solvable dimension. A numerical example for NASA's MINIMAST system is presented.presented.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.850-858
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• 2011

The risk analysis plays an important role in weapon system acquisition project due to uncertainties in the acquisition process. But in domestic, studies on risk analysis are insufficient and risk cost is not included in acquisition budget in policy. Therefore, in this study, we suggest a method that measures risk or success probability of project using the stochastic model. In particular, in order to calculate the success probability, we apply the joint probability distribution model of cost and schedule that are critical factors influencing the project risk. And also we verify the applicability of this model in Korean defence industry environment through case studies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.696-706
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• 2013

This study aims to develop DEA model which can look into budget cost variance analysis tool based on standard cost using 68 hospital's input and output data. For accomplishing this purpose, by introducing new DEA model which can get an attainable target cost, we can decompose an actual cost difference into several meaningful sub variances. Also based on the 2008 general hospital data, this model can make variance analysis between actual cost and target cost. Total variance can be divided into technical inefficiency variance, price inefficiency variance, allocation inefficiency variance. This study introduces that by using target budget cost concept, traditional actual cost variance can be divided into a technical variance, price variance, budget variance. Finally, we can get result which confirms there does not exist favorable size effects on efficiency and cost management in running a general hospital.

• Asia-Pacific Journal of Business
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• v.6 no.2
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• pp.1-17
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• 2015

This study compares the most widely used parametric and non-parametric techniques to measure cost and profit efficiency of banks, namely the Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We formulate the specification form of both stochastic cost and profit frontier models and constant return to scale Cost DEA and Profit DEA models and provide an empirical assessment of the cost and profit frontiers based on a panel dataset of National Commercial Banks (NCBs) and Private Banks (PBs) in Bangladesh over the 2001-2010 period. The cost inefficiency and profit efficiency are slightly higher for PBs than NCBs in case of both SFA and DEA. The coefficients of advance and off-balance sheet items are significant that positively influence the banks in stochastic cost frontier model while the advance, other earning assets, price of borrowed fund are significant and negative effects on the banks in stochastic profit frontier model. The average cost inefficiency and average profit efficiency are recorded with 16.3% and 91% respectively. The highest and lowest cost inefficiency are observed for Janata Bank and United Commercial Bank Limited whilst the highest and lowest profit efficiency are recorded for Eastern Bank Limited and Janata Bank respectively. The average technical and allocative efficiency are 68.8% and 35.9%, respectively in case of CRS cost-DEA model whereas they are 70.3% and 31.8% in case of CRS profit-DEA model. The average cost inefficiency is recorded 6.3% by SFA whereas it is 24.5% by DEA. The average profit efficiency is found 91% by SFA while it is 22.1% by DEA, and SFA method shows better bank efficiency than DEA.

• Korean Journal of Construction Engineering and Management
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• v.8 no.5
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• pp.191-200
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• 2007

This paper introduces a tool for predicting potential cost overrun during project execution and for quantifying the uncertainty on the expected project cost, which is occasionally changed by the unknown effects resulted from project's complications and unforeseen environments. The model proposed in this stuff is useful in diagnosing cost performance as a project progresses and in monitoring the changes of the uncertainty as indicators for a warning signal. This model is intended for the use by project managers who forecast the change of the uncertainty and its magnitude. The paper presents a mathematical approach for modifying the costs of incomplete work packages and project cost, and quantifying reduced uncertainties at a consistent confidence level as actual cost information of an ongoing project is obtained. Furthermore, this approach addresses the effects of actual informed data of completed work packages on the re-estimates of incomplete work packages and describes the impacts on the variation of the uncertainty for the expected project cost incorporating Multivariate Probabilistic Analysis (MPA) and Bayes' Theorem. For the illustration purpose, the Introduced model has employed an example construction project. The results are analyzed to demonstrate the use of the model and illustrate its capabilities.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.64-71
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• 2002

This research developed construction cost forecasting model using Building Construction Cost Index, time series analysis and Artificial Neural Networks. By this model, we could calculate the forecasted values of construction cost precisely and efficiently. And we also could find out that the standard deviation of forecasted values is 0.375 and it is a very exact result, so the standard deviation is just 0.33 percent of 112.28, the average of Building Construction Cost Index. And it show more exact forecasting result in comparison with Time Series Analysis.

• Journal of the military operations research society of Korea
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• v.27 no.1
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• pp.10-27
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• 2001

This paper deals with the application of PRICE model in estimating the proper acquisition cost for weapon budgeting phase. The PRICE(Parametric Review of Information for Costing and Evaluation) Hardware model is a computerized method for deriving cost estimates of electronic and mechanical hardware assemblies and systems. The model can be used in obtaining not only initial cost estimates in conceptual phase, but also detailed cost estimates in budgeting phase depending on available historical and empirical data. We analyzed first step cost estimate parameters and derived cost equations using PRICe output dta. Using weight and complexity, We can find cost variation. Sensitivity analysis shows that cost increases exponentially as complexity increases exponentially as complexity increases. We estimated KAAV\`s (Korea Amphibious Assault Vehicle) production cost using the PRICE model and compare with engineering cost estimates which is based on actual production data submitted by the production company. The result shows that tow estimates are close within $\pm2%$ differences.

• Journal of Korean Society for Quality Management
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• v.46 no.4
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• pp.797-820
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• 2018

Purpose: It is to seek for an appropriate cost rate analysis methodology of credit card value propositions in Korea. For this issue, it is claimed that methodologies based on probability distribution is more suitable than methodologies based on data-mining. The analysis model constructed for the cost rate estimation is called VCPM model. Methods: The model includes two major variables denoted as S and P. S is monthly credit card usage amount. P stands for the proportion of usage amount at special merchants over the whole monthly usage amount. The distributions assumed for P are positively skewed distributions such as exponential, gamma and lognormal. The major inputs to the model are also derived from S and P, which are E(S) and the aggregate proportion of usage amount at special merchants over the total monthly usage amount. Results: When the credit card's value proposition is general discount, the VCPM model fits well and generates reasonable cost rate(denoted as R). However, it seems that the model does not work well for other types of credit cards. Conclusion: The VCPM model is reliable for calculating cost rate for credit cards with positively skewed distribution of P, which are general discount card. However, another model should be built for cards with other types of distributions of P.

• The Journal of Fisheries Business Administration
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• v.47 no.4
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• pp.1-13
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• 2016

Fish mortality is the most important success factor in aquaculture management. To analyze the effect of mortality considering biological and economic condition is a important problem in land-based aquaculture. This study is aimed to analyze the effect of mortality for duration of cultivation in land-based aquaculture. This study builds the mathematical model that finds the value of decision variable to minimize cost that sums up the water pool usage cost, sorting cost, fingerling cost and feeding cost under critical standing corp constraint. The proposed mathematical model involves many aspects, both biological and economical: (1) number of fingerlings (2) timing and number of batch splitting event, based on (3) fish growth rate, (4) mortality, and (5) several farming expense. Numerical simulation model presented here in. The objective of numerical simulation is to provide for decision makers to analyse and comprehend the proposed model. When extensive biological and cost data become available, the proposed model can be widely applied to yield more accurate results.

• Journal of Information Technology Applications and Management
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• v.15 no.3
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• pp.195-208
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• 2008

In an emergency management case, evaluating the economic value of information technology investments is a challenging problem due to the effects of decision making, uncertainty of disasters, and difficulty of measurements. Risk assessment and recovery process, one of the major functions in emergency management, consists of (1) measurement of damages or losses, (2) recovery planning, (3) reporting and approving budgets, (4) auctioning off recovery projects to constructors, and (5) construction for the recovery. Specifically and of our interest, measurement of damages or losses is often a costly and time-consuming process because the wide range of field surveys should be performed by a limited pool of trained agents. Managers, therefore, have to balance accuracy of the field survey against the total time to complete the survey. Using information technologies to support field survey and reporting has great potential to reduce errors and lowers the cost of the process. However, existing cost benefit analysis framework may be problematic to evaluate and justify the IT investment because the cost benefit analysis often include the long-run benefit of IT that is difficult to quantify and overlook the impact of managerial control upon the investment outcomes. Therefore, we present an alternative cost-centric control model that conservatively quantifies all cost savings to replace benefits in cost benefit analysis and incorporate the managerial control. The model provides a framework to examine how managerial decision making and uncertainty of disaster affect the economic value of IT investments. The current project in Emergency Agency in South Korea is introduced as a case to apply the cost-centric control model. Our work helps managers to better evaluate and justify IT-related investment alternatives in emergency management.