• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1995.12a
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• pp.9-21
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• 1995

A planning support system enhances our ability to use water capacity expansion as an urban growth management strategy. This paper reports the development of capacity expansion modeling of water supply as part of the continuing development of such a planning support system (PEGASUS: Planning Environment for Generation and Analysis of Spatial Urban Systems) to incorporate water supply, This system is designed from the understanding that land use and development drive the demand for infrastructure and infrastructure can have a significant influence on the ways in which land is developed and used. Capacity expansion Problems of water supply can be solved in two ways: 1) optimal control theory, and 2) mixed integer nonlinear programming (MINLP). Each method has its strengths and weaknesses. In this study the MINLP approach is used because of its strength of determining expansion sizing and timing simultaneously. A dynamic network optimization model and a water-distribution network analysis model can address the dynamic interdependence between water planning and land use planning. While the water-distribution network analysis model evaluates the performance of generated networks over time, the dynamic optimization model chooses alternatives to meet expanding water needs. In addition, the user and capacity expansion modeling-to-generate-alternatives (MGA) can generate alternatives. A cost benefit analysis module using a normalization technique helps in choosing the most economical among those alternatives. GIS provide a tool for estimating the volume of demanded water and showing results of the capacity expansion model.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.46-55
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• 2020

The maintenance cost for highway pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance Preventive maintenance requires the establishment of a strategic plan through accurate prediction old Highway pavement. herefore, in this study, the XGBoost among machine learning classification-based models was used to develop a highway pavement damage prediction model. First, we solved the imbalanced data issue through data sampling, then developed a predictive model using the XGBoost. This predictive model was evaluated through performance indicators such as accuracy and F1 score. As a result, the over-sampling method showed the best performance result. On the other hand, the main variables affecting road damage were calculated in the order of the number of years of service, ESAL, and the number of days below the minimum temperature -2 degrees Celsius. If the performance of the prediction model is improved through more data accumulation and detailed data pre-processing in the future, it is expected that more accurate prediction of maintenance-required sections will be possible. In addition, it is expected to be used as important basic information for estimating the highway pavement maintenance budget in the future.

• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.105-117
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• 2007

In order to succeed in a bid or development, the project manager should estimate its cost and schedule more accurately in the early stage of the project. Usually, the nominal schedule of most projects can be derived from rule of thumb, first-order estimation practice, or ball-park schedule estimation table. But the rule-of-thumb models for the nominal schedule estimation are so various, and the first-order estimation practice does not provide sufficient information. So they do not help much to decide on the proper development effort and schedule for a particular size of project. This paper presents a statistical regression model for deciding the development effort and schedule of a project using the ball-park schedule estimation table. First, we have redefined such words suggested in the ballpark schedule estimation table as shortest possible schedule, efficient schedule and nominal schedule, Next, we have investigated the relationship between the development effort and the schedule. Finally, we have suggested a model for estimating the development effort and the more accurate schedule of such particular sizes of software as are not presented in the ball-park schedule estimation table. The experimental results show that our proposed regression analysis model decreases the mean magnitude of relative error by 2% at maximum. Also this model can estimated the development effort and schedule for a particular size of software.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.79-87
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• 2017

The microphysical processes of the numerical weather prediction (NWP) model cover the following : fall speed, accretion, autoconversion, droplet size distribution, etc. However, the microphysical processes and parameters have a significant degree of uncertainty. Parameter estimation was generally used to reduce errors in NWP models associated with uncertainty. In this study, the micro- genetic algorithm and harmony search algorithm were used as an optimization algorithm for estimating parameters. And we estimate parameters of microphysics for the Unified model in the case of precipitation in Korea. The differences which occurred during the optimization process were due to different characteristics of the two algorithms. The micro-genetic algorithm converged to about 1.033 after 440 times. The harmony search algorithm converged to about 1.031 after 60 times. It shows that the harmony search algorithm estimated optimal parameters more quickly than the micro-genetic algorithm. Therefore, if you need to search for the optimal parameter within a faster time in the NWP model optimization problem with large calculation cost, the harmony search algorithm is more suitable.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.45-45
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• 2017

On-site monitoring of vegetable growth parameters, such as leaf length, leaf area, and fresh weight, in an agricultural field can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agricultural applications. This study reports on validation testing of previously developed vegetable growth estimation models based on UAV-based RGB images for white radish and Chinese cabbage. Specific objective was to investigate the potential of the UAV-based RGB camera system for effectively quantifying temporal and spatial variability in the growth status of white radish and Chinese cabbage in a field. RGB images were acquired based on an automated flight mission with a multi-rotor UAV equipped with a low-cost RGB camera while automatically tracking on a predefined path. The acquired images were initially geo-located based on the log data of flight information saved into the UAV, and then mosaicked using a commerical image processing software. Otsu threshold-based crop coverage and DSM-based crop height were used as two predictor variables of the previously developed multiple linear regression models to estimate growth parameters of vegetables. The predictive capabilities of the UAV sensing system for estimating the growth parameters of the two vegetables were evaluated quantitatively by comparing to ground truth data. There were highly linear relationships between the actual and estimated leaf lengths, widths, and fresh weights, showing coefficients of determination up to 0.7. However, there were differences in slope between the ground truth and estimated values lower than 0.5, thereby requiring the use of a site-specific normalization method.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.3
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• pp.167-172
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• 2016

The computer controlled optical surfacing (CCOS) technique provides superior fabrication performance for optical mirrors when compared to the conventional method, which relies heavily on the skill of the optician. The CCOS technique provides improvements in terms of mass production, low cost, and short polishing time, and are achieved by estimating and controlling the moving speed of the tool and toolpath through a numerical analysis of the tool influence function (TIF). Hence, the exact estimation of various TIFs is critical for high convergence rates and high form accuracy in the CCOS process. In this paper, we suggest a new model for TIFs, which can be applied for various tool shapes, different velocity distributions, and non-uniform tool pressure distributions. Our proposed TIFs were also verified by comparisons with experimental results. We anticipate that these new TIFs will have a major role in improving the form accuracy and shortening the polishing time by increasing the accuracy of the material removal rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5783-5789
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• 2014

Since 2002, many domestic companies have been certified for ISMS. On the other hand, certification, such as the need for ost-effectiveness evaluation, is not specifically enforced. Therefore, for more than 10 years, the ISMS implementation and certification system has been used for performance and cost effective business management. In this study, a model for analyzing the effect of certification organizations, ISMS development, and an analysis of the effect of a standardized system for the study was prepared. To this end, the existing maintenance organizations ISMS certification survey was conducted through an analysis of the economic effects. ISMS certification continues to expand or maintain the policy for improvement. The survey data collected by the analysis mechanism for the economic effects of CVM was analyzed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.12
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• pp.1379-1385
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• 2014

Even the rough prediction of the product test time before the lifetime test of mechanical component begins would be of use in estimating cost and deciding how to keep up with the test. The reliability predictions of mechanical components are difficult because failure or degradation mechanisms are complicated, and few plausible databases are available for lifetime prediction. Therefore, this study conducted lifetime predictions of elastomeric U seals that were respectively installed in a hydraulic actuator and a pneumatic actuator using lifetime models and a field database based on failure physics and an actual test database obtained from the NSWC handbook. To validate the results, the predicted failure rates were compared with the actual lifetime test results acquired in the lab durability tests. Finally, this study discussed an engineering procedure to determine the coefficients in the failure rate models and analyzed the sensitivity of each influential parameter on the seal lifetime.

• Health Policy and Management
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• v.29 no.4
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• pp.445-453
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• 2019

Background: This study is to investigate the association between the distribution of multimorbidity and length of stay and medical expenses among inpatients in a municipal hospital to achieve an integrated care setting. Methods: We used the exploratory factor analysis and the generalized estimating equation model to analyze the data from patients living in the northeast region of Seoul, who were hospitalized from January 2017 to December 2017 in a municipal hospital. Results: As a result of the factor analysis, seven types of multiple chronic diseases were classified. Among the elderly patients admitted to municipal hospitals, the burden of medical expenses was mainly influenced by the length of stay (B=310,719, p-value <0.0001), not the type of disease (all not significant). Length of stay were mainly due to psychiatric illness (factor 1: B=4.323, p-value <0.0001) related to the brain and metabolic diseases (factor 2: B=2.364, p-value=0.003). Conclusion: This study showed that the medical expenses of the elderly patients were largely due to prolonged hospitalization, not multimorbidity. Therefore, it is necessary to develop an integrated care paradigm strategy cope with the multimorbidity of the elderly in the community and to alleviate the socio-economic burden.

• Quality Improvement in Health Care
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• v.25 no.2
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• pp.44-55
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• 2019

Purpose: To investigate whether changes in Medical Aid (MA) status are associated with unmet need and catastrophic health expenditure (CHE). Methods: Data from the 2010 to 2014 Korea Health Panel (KHP) were used. The impact of changes in annual MA status ('MA to MA,' 'MA to MA Exit,' 'MA Exit to MA,' and 'MA Exit to MA Exit') on unmet need (all-cause and financial) and CHE (10% and 40% of household capacity to pay) were examined using the generalized estimating equation (GEE) model. Analysis was conducted separately for MA type I and II individuals. Results: In 1,164 Medical Aid type I individuals, compared to the 'MA to MA' group, the 'MA to MA Exit' group had increased likelihoods of all-cause and financial unmet need. This group also showed higher likelihoods of CHE at the 10% standard. The 'MA Exit to MA Exit' group showed increased likelihoods at the 10% and 40% CHE standards. In 852 type II recipients, the 'MA to MA Exit' group had higher likelihoods of CHE at the 10% standard. Conclusions: Type 1 MA exit beneficiaries had higher likelihoods of all-cause and financial unmet need, along CHE at the 10% standard. Type I 'MA Exit to MA Exit' beneficiaries also showed higher likelihoods of CHE at the 10% and 40% standards. In type II recipients, MA exit beneficiaries had higher likelihoods of CHE at the 10% standard. The results infer the importance of monitoring MA exit beneficiaries as they may be vulnerable to unmet need and CHE.