• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.121-131
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• 2024

This research explores the potential of leveraging unstructured data from construction supervision documents, which contain detailed inspection insights from independent third-party monitors of building construction processes. With the evolution of analytical methodologies, such unstructured data has been recognized as a valuable source of information, offering diverse insights. The study introduces a framework designed to assess cost performance by applying advanced analytical methods to the unstructured data found in final construction supervision reports. Specifically, key phrases were identified using text mining and social network analysis techniques, and these phrases were then analyzed through binomial logistic regression to assess cost performance. The study found that predictions of cost performance based on unstructured data from supervision documents achieved an accuracy rate of approximately 73%. The findings of this research are anticipated to serve as a foundational resource for analyzing various forms of unstructured data generated within the construction sector in future projects.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.292-306
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• 2017

Traffic noise cost can be assessed either by the damage cost approach or by the avoidance cost method. This paper provides an overview of pertinent studies of these two approaches and shows that the damage cost approach is more universal and reliable than the avoidance cost counterpart. This study then investigated three sub-components to address the damage cost framework. First of all, unit value per person exposed to noise per year was calculated. Secondly, the area exposed to noise was determined using noise prediction equation. Thirdly, the number of people affected by noise was computed by multiplying the number of people exposed to noise with the percentage of people affected by noise. This paper also suggested a simplified equation that represents the relationship between damage costs and noise levels. Finally, the benefits of noise reduction derived from the damage cost method and those from the avoidance cost approach were compared and discussed.

• Environmental and Resource Economics Review
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• v.15 no.4
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• pp.673-692
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• 2006

In order to test for the dynamic optimality condition for the use of nonrenewable resource, it is necessary to estimate the shadow value of the resource in situ. In the previous literatures, a time series for in situ price has been derived either as the difference between marginal revenue and marginal cost or by differentiating with respect to the quantity of ore extracted the restricted cost function in which the quantity of ore is quasi-fixed. However, not only inconsistent estimates are likely to be generated due to the nonmalleability of capital, but the estimate of marginal revenue will be affected by market power. Since firms will likely fail to minimize the cost of the reproducible inputs subject to market prices under realistic circumstances where imperfect factor markets, strikes, or government regulations are present, the shadow in situ values obtained by estimating the restricted cost function can be biased. This paper provides a valid methodology for checking the dynamic optimality condition for a nonrenewable resource by using the input distance function. Our methodology has some advantages over previous ones: only data on quantities of inputs and outputs are required; nor is the maintained hypothesis of cost minimization required; adoption of linear programming enables us to circumvent autocorrelated errors problem caused by use of time series or panel data. The dynamic optimality condition for domestic coal mining does not hold for constant discount rates ranging from 2 to 20 percent over the period 1970~1993. The dynamic optimality condition also does not hold for variable rates ranging from fourth to four times the real interest rate.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.1
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• pp.33-40
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• 2016

In this study, using the Cost Prediction Model and Performance Prediction Model have developed a way to estimate future management costs and performance for bridge and tunnel by Network Level. Studies to date have primarily focused on the single facility, it is difficult to apply to the analysis of the Network Level. This study, items used as an index of 'Special Act for the Safety Control of Public Structures' was added to Usability and Functionality to Status. Action period and annual budget for each facility can be estimated through the Basic and Advanced analysis. In addition, we verified the technical feasibility through case analysis.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.120-125
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• 2003

The estimated construction costs derived at the Planning stage of a project are utilized as important data determining the feasibility of overall project. Therefore the clients usually expect to have estimations of the construction cost as precise as possible and there has been extensive studies carried out by the cost specialists worldwide to satisfy this client's specific need whereas the local estimators still heavily rely on producing quantities and detail quotations only. This paper is to introduce a case study where elemental/functional area cost analysis is incorporated into a database system for the improved accuracy in cost estimations.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.225-226
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• 2015

현재 개발도상국은 전력망 부족으로 심각한 전력난을 겪고 있는 반면 우리나라는 전력망이 점차 포화되어 관련 산업 일자리가 줄어들고 있다. 이에 대한 대책 중 하나로 우리나라의 우수한 전력망을 해외로 수출하는 방안이 떠오르고 있다. 그러나 현재는 발전설비 및 송 변전 설비와 같이 부분적으로 수출하고 있기 때문에 전체 전력망 계획이 필요하다. 따라서 본 논문에서는 개발도상국에 전력망 수출을 위해서 필요한 부하, 발전, 송전을 추정 및 예측하고 설계하는 방법론을 제안한다. 또한 총 비용(송전비용)이 최소가 되는 전력망을 구축하기 위해 Still 식을 이용하여 경제전압을 선정하고 제안하는 3가지 사례의 경제성을 비교한다.

• Health Policy and Management
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• v.4 no.2
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• pp.126-147
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• 1994

Lyme 질환은 미국 코넷티컷주의 라임지방에서 관절염증상을 보이는 소아과환자에게서 1975년 처음 발견되었다, 사슴, 누루, 개 등에 기생하는 진드기에 의해 전염되며, 발병초기에는 감기증상을 수반한 황소의 눈과 비슷한 붉은 반점이 생긴다. 적기에 치료하지 않으면, 관절염, 심장질환, 안면신경마비 등으로 악화될 수 있다. 본 논문의 목적은 두가지로 나누어 볼 수 있다. 먼저, 진단초기의 Lyme질환과 관련된 의료 및 기타 경제적 비용을 저렴하게 계측할 수 있는 방법론을 개발하고 그 유효성을 검증하는 것이다. 둘째로 lyme질환의 비용에 대한 여러종류의 총괄적 계측치를 제공하고 발병의 위험요인을 색출하는 것이다. 본 논문에서는 차트분석이나 임상연구 등 고가의 비용이 수반되는 분석기법 대신에 Lyme질환 다발지역에 대한 설문조사를 실시하고 그 유효성을 재설문조사를 통해서 검증하는 방법을 사용하였다. 자료분석상의 난점은 조사대상자마다 응답하지 않은 항목(Missing Value)이 다르기 때문에, 총 비용을 계산할 때 모든 항목에 응답한 조사대상자만을 사용한다면 표본의 크기가 너무 작아지는 것이었다. 이에 대한 대안으로 총비용 및 부분별 비용의 합을 계산할 때 표본의 일부가 응답하지 않은 항목에 대해서는 그 항목에 응답한 나머지 조사대상자의 응답치 평균을 대체하는 방법을 사용하였다. 통계적 분석결과, 질환의 증상시작부터 설문조사시기까지 Lyme질환과 관련된 사회적 총비용은 US$ 6400으로 추정되었다. 이중에 200가량은 환자의 보호자와 관련된 비용이고 나머지는 환자와 관련되 것이다. 총의료비용의 평균은 계산방법에 따라서 US$ 3000-4200의 범위를 보였다. 응답되지 않은 항목을 해당항목에 대한 응답치평균으로 대체하였을 때 총의료비평균은 US$ 4108이었다. 시간비용을 생산성손실에 대한 사회적 가치와 실제임금 손실의 두가지 방법에 의해 계산되었다. 실제임금손실은 생산손실의 사회적 가치의 약 30%에 불과하였다. 본 논문의 결과는 의료비용 및 비용과 생산성손실에 대한 정보가 지역보건담당자에 의한 전화설문조사에 의해 경제적이고도 일관성 있게 수집될 수 있다는 근거로 해석될 수 있다.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.961-975
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• 2016

The hierarchically penalized support vector machine (H-SVM) has been developed to perform simultaneous classification and input variable selection when input variables are naturally grouped or generated by factors. However, the H-SVM may suffer from estimation inefficiency because it applies the same amount of shrinkage to each variable without assessing its relative importance. In addition, when analyzing imbalanced data with uneven class sizes, the classification accuracy of the H-SVM may drop significantly in predicting minority class because its classifiers are undesirably biased toward the majority class. To remedy such problems, we propose the weighted adaptive H-SVM (WAH-SVM) method, which uses a adaptive tuning parameters to improve the performance of variable selection and the weights to differentiate the misclassification of data points between classes. Numerical results are presented to demonstrate the competitive performance of the proposed WAH-SVM over existing SVM methods.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.163-172
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• 2004

In the software development project applying object-oriented development methodology, the research on the UCP(Use Case Point) as a method to estimate development effort is being carried on. The existing research proposes the linear model calculating the development effort that multiplies an invariant on AUCP(Adjusted Use Case Point) which applied technical and environmental factors. However, the statistical model that estimates the development effort using AUCP and UUCP(Unadjusted Use Case Point) is not being studied. The irrelevant relationship of the linear regression model, whose development period is increasing tremendously as the software size increases, is confirmed. Moreover, during the UCP calculating process, there can be errors in FP by applying the TCF(Technical Complexity Factor) and EF(Environmental Factor). This paper presents a non-linear regression model, that does not consider the TCF and EF, and that estimate the development effort from UUCP directly by utilizing the exponential function. An exponential function is selected among the linear, logarithm, polynomial, power, and exponential model via statistical evaluations of the models mentioned above.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1059-1070
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• 2020

River cross-section measurement data is one of the most important input data in research related to hydraulic and hydrological modeling, such as flow calculation and flood forecasting warning methods for river management. However, the acquisition of accurate and continuous cross-section data of rivers leading to irregular geometric structure has significant limitations in terms of time and cost. In this regard, a primary objective of this study is to develop a methodology that is able to measure the spatial distribution of continuous river characteristics by minimizing the input of time, cost, and manpower. Therefore, in this study, we tried to examine the possibility and accuracy of continuous cross-section estimation by estimating the water depth for each cross-section through multiple linear regression analysis using RGB-based aerial images and actual data. As a result of comparing with the actual data, it was confirmed that the depth can be accurately estimated within about 2 m of water depth, which can capture spatially heterogeneous relationships, and this is expected to contribute to accurate and continuous river cross-section acquisition.