• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.401-409
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• 2014

This study deals with capacity expansion planning of airport infrastructure in view of economic validation that reflect construction costs and social benefits according to the reduction of passengers' delay time. We first forecast the airport peak-demand which has a seasonal and cyclical feature with ARIMA model that has been one of the most widely used linear models in time series forecasting. A discrete event simulation model is built for estimating actual delay time of passengers that consider the passenger's dynamic flow within airport infrastructure after arriving at the airport. With the trade-off relationship between cost and benefit, we determine an economic quantity of conveyor that will be expanded. Through the experiment performed with the case study of Incheon international airport, we demonstrate that our approach can be an effective method to solve the airport expansion problem with seasonal passenger arrival and dynamic operational aspects in airport infrastructure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• Journal of Climate Change Research
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• v.5 no.2
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• pp.153-163
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• 2014

This study analyzed directions of the energy product efficiency improvement and Carbon Tax for the domestic building sector. In order to analyze GHG reduction potential and total cost, the cost optimization model MESSAGE was used. In the case of the "efficiency improvement scenario," the cumulative potential GHG reduction amount - with respect to the "Reference scenario" - from 2010 to 2030 is forecast to be $104MtCO_2eq$, with a total projected cost of 2.706 trillion KRW. In the "carbon tax scenario," a reduction effect of $74MtCO_2eq$ in cumulative potential GHG reduction occurred, with a total projected cost of 2.776 trillion KRW. The range of per-ton GHG reduction cost for each scenario was seen to be approximately $-475{\sim}272won/tCO_2eq$, and the "efficiency improvement scenario" showed as the highest in the order of priority, in terms of the GHG reduction policy direction. Regarding policies to reduce GHG emissions in the building sector, the energy efficiency improvement is deemed to deployed first in the future.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.155-162
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• 2009

The recent increase of light rail construction by the private sector in Korea has caused a new issue in forecasting rail demand. Integrated fare systems between several rail operators is convenient and brings cost savings to users, and therefore is also very effective in increasing demand. However, it causes some short-term revenue loss to operators so that the private sector often suggests a non-integrated fare system. The current rail demand forecasting model is based upon an integrated fare system. Thus this model cannot be used to forecast the demand with a non-integrated fare system. Some value of transfer fare should be estimated and applied to forecast the demand in a non-integrated fare system. This study conducted a stated preference (SP) survey on urban railway passengers and estimated the value of transfer fare. The estimated value is 2,609 Won/hr, which is about 52% of in-vehicle time. This shows railway users have a tendency to pay more for transfer fares to save time or distance. This value has some limitations since it is derived from the SP survey. If some non-integrated fare system is applied in the future and a RP survey is conducted and compared with these study results, a more clear value of the transfer fare will be derived.

• Journal of the Korean Solar Energy Society
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• v.32 no.3
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• pp.33-41
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• 2012

As the wind farms in large scale demand enormous amount of construction cost, minimizing the economic burden is essential and also it is very important to measure the wind resources and forecast annual energy production correctly to judge the economic feasibility of the proposed site by way of installing a Met mast at or nearby the site. Wind resources were measured by installing a 80[m] high Met mast at WangdeungYeo Island to conduct the research incorporated in this paper and offshore wind farm was designed using WindPRO. Wind farm of 100[MW] was designed making use of 3 and 4.5[MW] wind generator at the place selected to compare their annual energy production and capacity factor applying the loss factor of 10[%] and 20[%] respectively to each farm. As a result, 336,599[MWh] was generated by applying 3[MW] wind generator while 358,565 [MWh] was produced by 4.5[MW] wind generator. Difference in the energy production by 3[MW] generator was 33,660 [MWh] according to the loss factor with the difference in its capacity factor by 3.8[%]. On the other hand, 23 units of 4.5 [MW] wind generators showed the difference of annual energy production by 35,857 [MWh] with 4.0[%] capacity factor difference.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.195-202
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• 2009

As the generation and application of spatial information is gradually expanded not only in traditional surveying fields but also a CNS and an ITS recently. The Accuracy and the newest of data grow to be an important element. But digital map is updated with system based tile. So, it is hard to get the newest of data and to be satisfied with user requirements. In this study, management system is developed to manage feature change efficiently using bid informations from NaraJangter which service the bid informations. A construction works with change possibility of feature from bid informations are classified and are made DB. And the DB is used as the feature change forecast informations. Also, It is converted from bid information of text form to positioning informations connected to spatial information data. If this system is made successfully, this system contributes to reduce the cost for the update of digital map and to take the newest date of spatial informations.

• Steel and Composite Structures
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• v.50 no.5
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• pp.595-608
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• 2024

In this study, aluminum lathe waste was used by replacing aggregates in certain proportions in order to obtain expansive concrete using recycled materials. For this reason, five different aluminum wastes of 1%, 2%, 3%, 4% and 5% were selected and also reference without aluminum waste was produced. Based on the mechanical tests conducted, which included slump, compression, splitting tensile, and flexural tests, it was evident that the workability of the material declined dramatically once the volume ratio of aluminum exceeded 2%. As determined by the compressive strength test (CST), the CS of concrete (1% aluminum lathe wastes replaced with aggregate) was 11% reducer than that of reference concrete. It was noted that the reference concrete's CS values, which did not include aluminum waste, were greater than those of the concrete that contained 5% aluminum. When comparing for splitting tensile strength (STS), it was observed that the results of STS generally follow the parallel inclination as the CS. The reduction in these strengths when 1% aluminum is utilized is less than 10%. These ratios modified 18% when flexural strength (FS) is considered. Therefore, 1% of aluminum waste is recommended to obtain expansive concrete with recycled materials considering minimum loss of strength. Moreover, Scanning Electron Microscope (SEM) analysis was performed and the results also confirm that there was expansion in the aluminum added concrete. The presence of pores throughout the concrete leads to the formation of gaps, resulting in its expansion. Additionally, for practical applications, basic equations were developed to forecast the CS, STS, and FS of the concrete with aluminum lathe waste using the data already available in the literature and the findings of the current study. In conclusion, this study establishes that aluminum lathe wastes are suitable, readily available in significant quantities, locally sourced eco-materials, cost-effective, and might be selected for construction using concrete, striking a balance among financially and ecological considerations.