• Journal of Construction Engineering and Project Management
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• v.1 no.1
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• pp.37-43
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• 2011

Labor productivity is a significant factor associated with controlling time, cost, and quality. Many researchers have developed models to define methods of measuring the relationship between productivity and various parameters such as the size of working area, maximum working hours, and the crew composition. Most of the previous research has focused on estimating productivity; however, this research concentrates on estimating labor productivity and developing time and cost data for repetitive concrete pouring activity. In Korea, "Standard Estimating" only entails the average productivity data of the construction industry, and it is difficult to predict the time and cost spent on any particular project. As a result, errors occur in estimating duration and cost for individual activities or projects. To address these issues, this research sought to collect data, measure productivity, and develop time and cost data using labor productivity based on field conditions from the collected data. A probabilistic approach is also proposed to develop data. A case study is performed to validate this process using actual data collected from construction sites. It is possible that the result will be used as the EVMS baseline of cost management and schedule management.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.565-576
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• 2012

Cost estimates are necessary for government acquisition program to support decisions about funding, to develop annual budget requests and to validate resource requirements at key decision points. Many researches have been done about cost estimating technique recently. Parametric cost estimating models based on CERs(Cost Estimating Relationships) have been mainly used using regression method with historical data. However, there are many restrictions in developing Korean version CERs because the number of data points are too small. Specially, data collection and data management system are unstable in Korean defense environment, when developing CERs. In this research, we analyzed the historical data, and found some cost drivers in guided weapon system area. We developed the Acquisition Unit Cost CER using the regression to remove multicollinearity in the historical data. So we could overcome the restriction of the insufficient sample number. This research as a first attempt is meaningful in terms of obtaining our own Acquisition Unit Cost CER using historical cost and physical characteristic in Korean development environment.

• Journal of the Korea Institute of Building Construction
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• v.15 no.3
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• pp.307-316
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• 2015

As there are a lot of differences in the public building construction cost depending on the construction scale of actual construction cost system, a lot of problems occur in the estimation of the cost. So, the development of a predictive model depending on the construction scale shall be used in a way that it is applied to the case selectively and differently. This study drew a cost estimating model through a regression analysis. For this, 42 construction sites which were ordered during 2011 to 2012 by Public Procurement Service data were selected as a historical data. Based on the application of the model to new construction and the verification of its effect, the reasonable model for estimating the construction cost has been suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1474-1480
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• 2013

This study attempted to estimate construction costs in accordance with the resource-based cost estimation (unit cost price) system by diameter for TBM method, and analyzed the direct cost and the total cost. Based on such figures, this study performed a regression analysis and proposed a model for an equation for estimating construction costs. model for the resource-based cost estimation (unit cost price) system classified by diameter for TBM method proposed by this study can be effectively applied to business planning, preliminary investigation, feasibility study, construction cost estimations in the early design stages.

• Journal of Biomedical Engineering Research
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• v.27 no.1
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• pp.1-5
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• 2006

In this paper, we propose a subject-independent regression model to estimate systolic blood pressures (SBP) conveniently and continuously. There have been several researches on estimating SBP with pulse transit time (PTT) and they showed promising results. However, previous studies used only PTT as the estimation parameter, and their models were generated with just one person's PTT data which is not applicable to estimating other person's SBP. Therefore, we collected several additional biometric parameters with 202 healthy subjects. After statistical analysis of measured biometric parameters with SBP, we chose final estimating parameters including PTT to generate a multiple linear regression model for estimating SBP. Comparing the results of our study with approvable standards of automated sphygmomanometers developed by Association for the Advancement of Medical Instrumentation and approved by American National Standards Institute (ANSI/AAMI) indicates that our proposed method for continuously blood pressures monitoring gives an acceptable error.

• Journal of the Korean Solar Energy Society
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• v.31 no.4
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• pp.72-79
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• 2011

Solar radiation data are the best source of information for estimating average incident radiation. Lacking this or data from nearby locations of similar climate, it is possible to use empirical relationships to estimate radiation from days of hours of bright sunshine. It is necessary to estimate the regression coefficients in order to predict the daily global radiation on a horizontal surface. Therefore many different equations have proposed to evaluate them for certain areas. In this work a new correlation has been made to predict the solar radiation for 16 different areas over Korea by estimating the regression coefficients taking into account hours of bright sunshine. Particularly, the proposed straight line regression model shows reliable results for estimating the global radiation on a horizontal surface with monthly average deviation of -0.2 to +0.5% and each station annual average deviation of -1.6 to +1.7% from measured values.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.411-424
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• 2021

Inference following two-stage adaptive designs (also known as two-stage randomization designs) with survival endpoints usually focuses on estimating and comparing survival distributions for the different treatment strategies. The aim is to identify the treatment strategy(ies) that leads to better survival of the patients. The objectives of this study were to assess the performance three commonly cited methods for estimating survival distributions in two-stage randomization designs. We review three non-parametric methods for estimating survival distributions in two-stage adaptive designs and compare their performance using simulation studies. The simulation studies show that the method based on the marginal mean model is badly affected by high censoring rates and response rate. The other two methods which are natural extensions of the Nelson-Aalen estimator and the Kaplan-Meier estimator have similar performance. These two methods yield survival estimates which have less bias and more precise than the marginal mean model even in cases of small sample sizes. The weighted versions of the Nelson-Aalen and the Kaplan-Meier estimators are less affected by high censoring rates and low response rates. The bias of the method based on the marginal mean model increases rapidly with increase in censoring rate compared to the other two methods. We apply the three methods to a leukemia clinical trial dataset and also compare the results.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.135-142
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• 2021

Estimating the locations of workers in a shipyard is beneficial for a variety of applications such as selecting potential forwarders for transferring data in IoT services and quickly rescuing workers in the event of industrial disasters or accidents. In this work, we propose a human movement stream processing system for estimating worker locations in shipyards based on Apache Spark and TensorFlow serving. First, we use Apache Spark to process location data streams. Then, we design a worker location prediction model to estimate the locations of workers. TensorFlow serving manages and executes the worker location prediction model. When there are requirements from clients, Apache Spark extracts input data from the processed data for the prediction model and then sends it to TensorFlow serving for estimating workers' locations. The worker movement data is needed to evaluate the proposed system but there are no available worker movement traces in shipyards. Therefore, we also develop a mobility model for generating the workers' movements in shipyards. Based on synthetic data, the proposed system is evaluated. It obtains a high performance and could be used for a variety of tasksin shipyards.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.227-228
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• 2022

In order to achieve the goal of cost management, which is one of the three major management goals of building production, this paper introduces an approximate cost estimating automation technology in the design stage as the importance of predicting construction costs increases. BIM is used for accurate estimating, and the quantity of structural members and finishing materials is calculated by creating a 3D model of the actual building. However, only 2D basic design drawings are provided when making an estimating. Therefore, for accurate quantity calculation, digitization of 2D drawings is required. Therefore, this research calculates the quantity of concrete structural members by calculating the area for the recognition area through 2D drawing recognition technology incorporating computer vision. It is judged that the development technology of this research can be used as an important decision-making tool when predicting the construction cost in the design stage. In addition, it is expected that 3D modeling automation and 3D structural analysis will be possible through the digitization of 2D drawings.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.371-381
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• 2008

The systematic methodology for estimating construction cost approximately at planning and pre-design phase of a river facility construction project has not yet been established because of its unique characteristics including its relatively small project size in terms of cost. This research suggests a 4-level cost information structure and identifies critical factors affecting construction cost as a result of thorough analysis of accumulated historical cost data of river facility construction projects. Also, this research presents the framework of the approximate cost estimating methodology for river facility construction project a planning stage.