• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1707-1718
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• 2013

Historical cost data estimating system has been introduced since 2004 in the construction industry. Based on contract prices of past projects, this estimating system estimates construction cost according to work types. The Korea Institute of Construction Technology (KICT) announces the historical cost data twice a year annually. The unit price of a small construction project is higher than large construction project due to the increase on production cost per work unit, equipment and labor cost, etc. However, the historical cost data estimating system is applied to project estimation uniformly regardless the construction project's size. This study compared and analyzed the historical cost data of large and small construction project to indicate the problem of historical cost date estimating system. The study derived that the unit price of a small construction project is 21.8% higher than that of large construction project.

• Korean Journal of Construction Engineering and Management
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• v.2 no.2 s.6
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• pp.81-89
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• 2001

Construction industry has particular properties of non-continuity of production, and non-stability of market comparing to other industries. Because of them, the practical construction cost is more difficultly recognized than in manufacturing industry, so, that is various according to many projects. Therefore, it is very hard work to standardize construction cost, and it is worthy of analyzing and measuring exactly construction cost. On this study, the trouble in producing expected construction cost with original cost calculation method is progressed by the data of cost items in complete works. On the basis of analyzing data, as expected cost of practical construction is measured, it can be referred to the method and the standard of indirect labor cost rate in construction.

• Korean Journal of Computational Design and Engineering
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• v.8 no.2
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• pp.101-108
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• 2003

Presented in this paper is the development of an product cost estimation system at the product design stage. The efficient cost estimation function at the design stage is essential for the cost reduction activities through the entire product life cycle. For this purpose, it is necessary to establish a systematic working procedure, and to develop information system for managing a great deal of production and product-related data required for the cost estimation. The developed system has the capability of estimating a cost of assembly type products as well as unit-item type products. As proposed system is based on the variant approach, it can be used easily at an early design stage without the need for detail design information. Also, this system is integrated with legacy PDM (Product Data Management) and ERP (Enterprise Resource Planning) system for fast. accurate and easy product cost estimation. The estimated cost includes material cost, overhead cost as well as labor cost.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.51-68
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• 2015

As interests in the quality of data in database systems are growing recently, analysis and improvement of data quality in databases have been an important issue. However, there has yet to be a clear agreement on how to reasonably calculate the total cost of such project. In this paper, based on real project data and budget statistics, we develop a model to estimate the cost for quality analysis and improvement project of a database. We first conduct statistical analysis to build our basic model. Throughout this analysis, we have identified factors that determine the scale of works required to conduct the project and eventually determine the cost. In addition, we have identified factors that determine the complexity of the project. These factors can adjusts the cost determined by the scale of works. Our model is verified and improved by surveys on experts. We apply our model to newly conducted projects and observe that our model estimates the cost of each project reasonably well.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.55-62
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• 2010

Currently, cost estimation is very important to the government acquisition programs to support decisions about funding and to evaluate resource requirement as key decision points. Parametric cost estimating models have been used extensively to obtain appropriate cost estimates in early acquisition phase. However, they have many restrictions to ensure the cost estimating result in Korean defense environment because they are developed in the U.S.A. environment. In order to obtain a good R&D cost estimate, developing our own CERs (Cost Estimation Relationships) using historical R&D data is essential. Nevertheless, there has been little research to develop our own CERs. In this research, we established a CER development process and found some cost drivers in the historical movement weapon system R&D data. The R&D CER is developed using the PCR(Principle Component Regression) method to remove multicollinearity among data and to overcome the restriction of the insufficient number of sample. At least, this research is meaningful as a first attempt in terms of defining the CER development process and obtaining our own R&D CER based on the historical data in Korean weapon system R&D environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.114-115
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• 2018

This paper studies a mechanism for cost-effective analysis of big data in the cloud environment. Recently, as a storage of electronic medical records can be managed outside the hospital, there is a growing demand for cloud-based big data analysis in small-and-medium hospitals. This paper firstly analyze the Amazon Elastic MapReduce which is a popular cloud framework for big data analysis, and proposes a cost model for analyzing big data using Amazon EMR with less cost. Using the proposed model, the user can construct a cost-effective computing cluster, which maximize the effectiveness of the analysis per operational cost.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.3
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• pp.281-292
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• 2021

With the development of deep learning technology, researchers and technicians keep attempting to apply deep learning in various industrial and academic fields, including the defense. Most of these attempts assume that the data are balanced. In reality, since lots of the data are imbalanced, the classifier is not properly built and the model's performance can be low. Therefore, this study proposes cost-sensitive learning as a solution to the imbalance data problem of image classification in the defense field. In the proposed model, cost-sensitive learning is a method of giving a high weight on the cost function of a minority class. The results of cost-sensitive based model shows the test F1-score is higher when cost-sensitive learning is applied than general learning's through 160 experiments using submarine/non-submarine dataset and warship/non-warship dataset. Furthermore, statistical tests are conducted and the results are shown significantly.

• 시스템엔지니어링워크숍
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• s.1
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• pp.60-64
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• 2003

In this study, we have analyzed the cost of korea high-speed railway system. The predicted cost in planning phase and adjustment data to 5th year are collected. Then, predicted cost is compared with adjustment in year/item/system base. We make a project history table for criteria to review project history and research & development activity. We have developed CBS(cost breakdown structure) and allocated adjustment data to them. It is shown that cost prediction related to research & development activity in planning phase is relatively correct.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.376-381
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• 2002

In this study, we have analyzed the cost of korea high-speed rail project. The predicted cost in planning phase and adjustment data to 5th year are collected. Then, predicted cost is compared with adjustment in year/item/system base. We make a project history table for criteria to review project history and research ＆ development activity. We have developed CBS(cost breakdown structure) and allocated adjustment data to them. It is shown that cost prediction related to research St development activity in planning phase is relatively correct.

• Journal of KIBIM
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• v.7 no.3
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• pp.11-20
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• 2017

BIM technology, which is widely used in the construction industry, has been introduced in various fields for the purpose of saving construction cost and reducing construction schedule. However, in the case of BIM-based cost estimate, there are various trials and errors in applying BIM technology which can be applied for calculating quantity and cost estimate. BIM-based cost estimate can improve the quantity accuracy and allow to easy modifications that were not expected in 2D-based construction process. However, for this purpose, it is necessary to take into consideration that interoperability between BIM data and cost information should be planed in advance. Besides, the definition of a BIM data specification is also required for the seamless data exchange and integrity in each phase of the construction process. Therefore, in this study, we propose a BIM - based cost estimation method and technology in each type of work applicable to the current domestic construction industry.