• Korean Journal of Construction Engineering and Management
• /
• v.7 no.4 s.32
• /
• pp.177-183
• /
• 2006

Risk-based estimation has been successfully introduced into the construction industry. By incorporating historical data associated with probability analysis, risk-based estimate is an effective decision support aid in considering whether to launch a particular project. The industry challenges, however, especially related with management issues, such as labor shortage, wage growth, and supply chain complexity, have often resulted in poor cost performance. The insufficient assessing the project characteristics (i.e., resource availability, project complexity, and project delivery method) can be the main reasons in the poor cost performance. Because the accuracy level of cost performance prediction can be enhanced by extensive evaluation of the subject project characteristics, a new approach for predicting cost performance in an earlier stage of a project can improve the Industry substantiality, in other words, value maximization. The purpose of this paper is to develop a new methodology in developing a risk-based estimate tool by incorporating extensive project characteristics. To do this, an extensive industry survey was conducted from both private and public sectors in building industry in Korea. In addition, significant project characteristics were identified in terms of cost performance indicator. Although the data collection is limited to Korean industry the suggested approach provides the industry with a straightforward methodology in risk management. As many researchers maintained that front-end planning efforts are crucial in achieving the successful outcome in building projects, the new method for risk-based estimation can Improve the cost performance as well as enhance the fulfillment in terms of business sustainability.

• International conference on construction engineering and project management
• /
• 2011.02a
• /
• pp.176-181
• /
• 2011

A role of cost modeler is that of facilitating design process by the systematic application of cost factors so as to maintain sensible and economic relationships between cost, quantity, utility and appearance. These relationships help to achieve the client's requirements within an agreed budget. The purpose of this study is to develop a parametric cost estimating model for the early design stage by using the multi-dimensional system of OLAP (On-line Analytical Processing) based on the case of quantity data related to architectural design features. The parametric cost estimating models have been adopted to support decision making in the early design stage. These models typically use a similar instance or a pattern of historical case. In order to effectively use this type of data model, it is required to set data classification and prediction methods. One of the methods is to find the similar class in line with attribute selection measure in the multi-dimensional data model. Therefore, this research is to analyze the relevance attribute influenced by architectural design features with the subject of case-based quantity data used for the parametric cost estimating model. The relevance attributes can be analyzed by Analytical Characterization. It helps determine what attributes to be included in the OLAP multi-dimension.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2009.04a
• /
• pp.155-156
• /
• 2009

Construction companies can easily understand present noise condition of their construction site via C-Noise. C-Noise is noise simulation software that simple to use. Construction companies spend time and cost for public complaints about construction noise. Construction site noise management using noise simulation software like C-Noise can reduce public complaint. achieve cost reduction to treat it.

• Korean Journal of Remote Sensing
• /
• v.23 no.4
• /
• pp.287-295
• /
• 2007

A mineral potential map showing the distributions of potential areas for exploration of undiscovered mineral deposits is a kind of predictive thematic maps. For any predictive thematic maps to show reasonably significant prediction results, validation information on prediction capability should be provided in addition to spatial locations of high potential areas. The objective of this paper is to apply prediction rate curves to the estimation of prediction probability of future discovery. A case study for Au-Ag mineral potential mapping using geochemical data sets is carried out to illustrate procedures for estimating prediction probability and for an interpretation. Through the case study, quantitative information including prediction rates and probability obtained by prediction rate curves was found to be very important for the interpretation of prediction results. It is expected that such quantitative validation information would be effectively used as basic information for cost analysis of exploration and environmental impact assessment.

• Journal of Ocean Engineering and Technology
• /
• v.31 no.6
• /
• pp.425-430
• /
• 2017

In order to reduce the cost of corrections and time needed for the block assembly process, the reverse setting method is applied for a back-heated block to neutralize deck deformation. The proper reverse setting shape for a back-heated block to correct deformation improved the deck flatness, but an excessive amount of reverse setting could inversely affect the flatness of the block. A prediction method was developed for the proper reverse setting shape using a back-heated block, considering the complex geometry of blocks, thickness of the deck plate, and thermal loading conditions such as welding and back-heating. The prediction method was developed by combining the re-meshing technique and inherent strain-based deformation analysis using the finite element method. Because the flatness deviation was decreased until the lower critical point and thereafter it tended to increase again, the optimum value for which the flatness was the best case was selected by repeatedly calculating the predefined reverse setting values. Based on this analysis and the study of the back-heating deformation of large assembly blocks, including the reverse setting shape, the mechanism for selecting the optimum reverse setting value was identified. The developed method was applied to the actual blocks of a ship, and it was confirmed that the flatness of the block was improved. It is concluded that the developed prediction method can be used to predict the optimum reverse setting shape value of a ship's block, which will reduce the cost of corrections in the construction stage.

• Korean Journal of Plant Resources
• /
• v.23 no.6
• /
• pp.526-534
• /
• 2010

Genomes of clusters of related eukaryotes are now being sequenced at an increasing rate. In this paper, we developed an accurate, low-cost method for annotation of gene prediction and exon-intron structure. The gene prediction was adapted for delta 1-pyrroline-5-carboxylate-synthetase (p5cs) gene from China wild-type of the halophytic Leymus chinensis (Trin.), naturally adapted to highly-alkali soils. Due to complex adaptive mechanisms in halophytes, more attentions are being paid on the regulatory elements of stress adaptation in halophytes. P5CS encodes delta 1-pyrroline-5-carboxylate-synthetase, a key regulatory enzyme involved in the biosynthesis of proline, that has direct correlation with proline accumulation in vivo and positive relationship with stress tolerance. Using analysis of reverse transcription-polymerase chain reaction (RT-PCR) and PCR, and direct sequencing, 1076 base pairs (bp) of cDNA in length and 2396 bp of genomic DNA in length were obtained from direct sequencing results. Through gene prediction and exon-intron structure verification, the full-length of cDNA sequence was divided into eight parts, with seven parts of intron insertion. The average lengths of determinated coding regions and non-coding regions were 154.17 bp and 188.57 bp, respectively. Nearly all splice sites displayed GT as the donor sites at the 5' end of intron region, and 71.43% displayed AG as the acceptor sites at the 3' end of intron region. We conclude that this method is a cost-effective way for obtaining an experimentally verified genome annotation.

• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1023-1035
• /
• 2021

The electricity cost of a desalination facility was also predicted and reviewed, which allowed the proposed model to be incorporated into the future design of such facilities. Input data from 2003 to 2014 of the Korea Hydrographic and Oceanographic Agency (KHOA) were used, and the structure of the model was determined using the trial and error method to analyze as well as hyperparameters such as salinity and seawater temperature. The future seawater quality was estimated by optimizing the prediction model based on machine learning. Results indicated that the seawater temperature would be similar to the existing pattern, and salinity showed a gradual decrease in the maximum value from the past measurement data. Therefore, it was reviewed that the electricity cost for seawater desalination decreased by approximately 0.80% and a process configuration was determined to be necessary. This study aimed at establishing a machine-learning-based prediction model to predict future water quality changes, reviewed the impact on the scale of seawater desalination facilities, and suggested alternatives.

• Proceedings of the KSR Conference
• /
• 2008.06a
• /
• pp.721-732
• /
• 2008

This paper is concerned with the life-cycle cost(LCC) analysis of the urban transit vehicle. LCC is the core part of analyzing the total cost of acquisition and ownership of a system. LCC in railway industry has been focused on the prediction of investment for railway vehicles. Therefore, to investigate future cost for operation and maintenance in detail, it is necessary to evaluate the LCC of the vehicle systematically. This study is focused on making a fundamental model for estimating the LCC of the urban transit vehicle. To develop a appropriate LCC model, we broadly analyzed specs and standards and compared the LCC model developed in other country. Moreover, this paper proposes strategies to develop an unique LCC model for the urban transit vehicle.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.12 no.4
• /
• pp.586-593
• /
• 2001

본 논문에서는 Cost231-Hata 모델과 Cost231-Walfisch-Ikegami 모델을 비교 분석하고, 두 모델의 전파환경이 서로 근접하게 되는 송신안테나의 높이, 건물군의 높이, 그리고 도로폭의 상관관계를 나타내는 전송손실 곡선들을 제시한다. 이러한 곡선들은 Okumura-Hata 모델의 정성적인 전파환경(도심지, 교외지역, 개활지)을 정량적인 요소(건물군의 높이, 도로폭) 로서 설명하여, Okumura-Hata(Cost231-Hata) 모델을 다른 도시, 나라에 적용시킬 때 하나의 기준으로 활용 될 수 있을 것이다. 또한 최근에 제안된 ITU-R 모델과 Okumura-Hata(Cost231-Hata)모델을 비교 분석한 결과, ITU-R 곡선들은 Okumura-Hata의 교외지역 전파환경에 대한 사용식을 확장한 것으로 사료된다.

• New & Renewable Energy
• /
• v.8 no.4
• /
• pp.3-12
• /
• 2012

Large offshore wind farms have actively been developed in order to meet the needs for wind energy since the land-based wind farms have almost been fully developed especially in Europe. The key problem for the construction of offshore wind farms may be on the high cost of energy compared to land-based ones. NREL (National Renewable Energy Laboratory) has developed a spreadsheet-based tool to estimate the cost of wind-generated electricity from both land-based and offshore wind turbines. Component formulas for various kinds and scales of wind turbines were made using available field data. In this paper, this NREL estimation model is introduced and applied to the offshore wind turbines now under designing or in production in Korea, and the result is discussed.