• Journal of the Korean Society of Safety
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• v.24 no.5
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• pp.69-76
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• 2009

The estimation of costs from industrial accidents is very important because they have a serious effect on individuals, companies, and nation. The department of labor estimates the cost of accidents by using the "Heinrich" method. From that method, the scale of accident cost can be approximately computed, but accurate calculation of uninsured cost is not easy. Therefore, a better method of calculating uninsured cost caused by industrial accident is necessary. This study aimed to construct an estimation method of uninsured cost according to domestic circumstances. The results of this study are as follows: (1) This study derived applicable factors for quantitative estimation of industrial accident cost (2) This study made the equation that the calculation of each item of uninsured cost was possible (3) This study applied the uninsured cost by degrees of disaster to individual items (4) The subjects and types of occurrence in uninsured cost were analyzed and presented. Theses results will provide a basis for further researchers of uninsured cost.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.415-431
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• 2002

A unified framework for statistical inference for the mean of the normal distribution to derive point estimates, confidence intervals and statistical tests is proposed. This optimal design is justified after investigating the basic information and requirements that are possible and impossible to control when specifying practical and statistical requirements. Point estimation is only credible when viewed in the larger context of interval estimation, since the information required for optimal point estimation is unspecifiable. Triple sampling is proposed and justified as a reasonable sampling vehicle to achieve the specifiable requirements within the unified framework.

• 한국IT서비스학회:학술대회논문집
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• 2005.11a
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• pp.345-355
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• 2005

As the portion of information systems(IS) budget to the total government budget becomes greater, the cost estimation of IS development and maintenance projects is recognized as one of the most important problems to be resolved for quantitative and efficient management of IS budget. The primary concern in the cost estimation of IS projects is to estimate software development cost. In this paper, we propose a new method to estimate software cost using support vector regression(SVR), which has attracted considerable attention because of its good performance and theoretical clearness. The paper is the first study which apply SVR to software cost estimation.

• The Journal of Information Systems
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• v.14 no.2
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• pp.173-189
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• 2005

Recently, Korean software industry has enjoyed fast growth, thus phenomenon drew attention to the need for more precise and standardized cost estimation system for software development. However, many obstacles exist in achieving a more precise and universally applicable cost measurement. These obstacles include : (1) the intangible nature of intellectual efforts, (2) lack of cost standards, (3) lack of quantitative yardstick to determine the potential complication, (4) lack of both cost monitoring during development and coordinating between acquisition process and cost estimation. The purpose of this study is to facilitate software development cost estimation considering acquisition process that will meet korean user's needs, and to create better models that will be cost for software development particularly for Korean environment.

• Journal of Information Technology Services
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• v.11 no.4
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• pp.215-231
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• 2012

It is well known that SaaS(Software as a Service) changeover gives several advantages to organization. One of the advantages is the cost reduction effect of IT resources as well as IT human resources. Another one is the curtailment of software development workload in the field of informatization promotions. Nonetheless, it is hard to find comparison cases regarding the quantitative measurement of the introduction of SaaS before and after. Accordingly, when the Government IDC tries to adopt SaaS, it absolutely needs the empirical study whether SaaS is cost-effectiveness or not. In this study, we focus on variation in the Government administration common tasks, processes and labor costs. Using the Man-Month(MM) estimation methods, We verify that how much TCO(Total Cost of Ownership) is reduced per year.

• Journal of Information Technology Services
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• v.8 no.1
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• pp.113-124
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• 2009

Value-based requirements engineering process, called The ViRE(Value-Innovative Requirement Engineering) was suggested to create an uncontested market using ERRC(Eliminate, Reduce, Raise, Create) requirements analysis. But ViRE did not provides a quantitative data analysis method for ERRC decision so as to make objective decisions for customers. In this paper, to solve this problem, we suggest a quantitative ERRC analysis method by estimating requirements cost. Our method defines user requirements and decides their weight. Then, it makes quality level table for all the identified requirements and function modules and estimate implementation cost based on their quality levels. Finally, assess each requirement's impact and then evaluate ERRC value. We could get the more objective ERRC values by evaluate the requirement weight. functional module weight, and implementation cost. And we proved the efficiency of our model by a case study, smart student ID system.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1223-1230
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• 2009

In the construction industry, Case-Based Reasoning (CBR) is considered to be the most suitable approach and determining the attribute weights is an important CBR problem. In this paper, a method is proposed for determining attribute weights that are calculated with attribute relation. The basic items of consideration were qualitative and quantitative influence factors. These quantitative factors were related to the qualitative factors to develop a Cost Drivers-structural equation model which can be used to estimate construction cost by considering attribute weight. The process of determining the attribute weight-structural equation model consists o 4 phases: selecting the predominant Cost Drivers for the SEM, applying the Cost Driers in the SEM, determining and verifying the attribute weights and deriving the Cost Estimation Equation. This study develops a cost estimating technique that complements the CBR method with a Cost Drivers-structural equation model which can be actively used during the schematic estimating phases of construction.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.1069-1086
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• 2003

This article presents the asymptotic theory of triple sampling procedure as pertain to estimating the shape parameter of Pareto distribution. Both point and confidence interval estimation are considered within the same inference unified framework. We show that this group sampling technique possesses the efficiency of Anscome (1953), Chow and Robbins (1965) purely sequential procedure as well as reduce the number of sampling operations by utilizing Stein (1945) two stages procedure. The analysis reveals that the technique performs excellent as far as the accuracy is concerned. The present problem differs from those considered by many authors, in multistage sampling, in that the final stage sample size and the parameter's estimate become highly correlated and therefore we adopted different approach.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.162-163
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• 2014

Operation and maintenance stage consists the largest portion of project life cycle cost. Appropriate management and analysis of such stages have massive effect on the total project cost. The effective prediction of optimized repair period is one of main factors in ㅌ management. However, it has been analyzed that the prediction of appropriate repair period revealed limitations in reliability. Therefore, this study suggests a methodology of repair period prediction by dividing finished projects into similar groups with same properties to be compared with the target project using quantitative variables.

• Korean Journal of Computational Design and Engineering
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• v.11 no.2
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• pp.148-155
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• 2006

This paper presents a new method for assessing the efficiency of production process plans using tolerance chart to lower production cost. The tolerance chart is used to predict the accuracy of a part that is to be produced following the process plan, and to carry out the quantitative measurement on the efficiency of the process plan. By comparing the values of design tolerances and their corresponding resultant tolerances calculated using the tolerance chart, the process plan that is incapable of satisfying the design requirements and the faulty production operations can be identified. Similarly, the process plan that imposes unnecessarily high accuracy and wasteful production operations can also be identified. For the latter, a quantitative measure on the efficiency of the process plan is introduced. The higher the unnecessary cost of the production, the poor is the efficiency of the process plan. A coefficient is introduced for measuring the process plan efficiency. The coefficient also incorporates two weighting factors to reflect the difficulty of manufacturing operations and number of dimensional tolerances involved. To facilitate the identification of the machining operations and the machined surfaces, which are related to the unnecessarily tight resultant tolerances caused by the process plan, a rooted tree representation of the tolerance chart is introduced, and its use is demonstrated. An example is presented to illustrate the new method. This research introduces a new quantitative process plan evaluation method that may lead to the optimization of process plans.