• Journal of the Korean earth science society
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• v.32 no.7
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• pp.750-760
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• 2011

In this study, the reproducibility of the simulated current climate by using two regional climate models, such as Seoul National University Regional Climate Model (SNURCM) and Weather Resuearch and Forecasting (WRF), is evaluated in advance to produce the standard regional climate scenario of future climate. Within the evaluation framework of a COordinated Regional climate Downscaling EXperiment (CORDEX), 28-year-long (1978-2005) regional climate simulation was conducted by using the Hadley Centre Global Environmental Model (HadGEM2-AO) global simulation data of the National Institute of Meteorological Research (NIMR) as a lateral boundary forcing. The simulated annual surface temperatures were in good agreement with the observation; the spatial correlation coefficients between each model and observation were over 0.98. The cold bias, however, were shown over the northern boundary in the both simulated results. In evaluation of the simulated precipitation, the skill was reasonable and good. The spatial correlation coefficients for the precipitation over the land area were 0.85 and 0.79 in SNURCM and WRF, respectively. It is noted that two regional climate models (RCMs) have different characteristics for the distribution of precipitation over equatorial and midlatitude areas. SNURCM shows better distribution of the simulated precipitation associated with the East Asia summer monsoon in the mid-latitude areas, but WRF shows better in the equatorial areas in comparison to each other. The simulated precipitation is overestimated in summer season (JJA) rather than in spring season (MAM), whereas the spatial distribution of the precipitation in spring season corresponds to the observation better than in summer season. Also the RCMs were capable of reproducing the annual variability of the maximum amount and its timing in July, in which the skills over the inland area were in better agreement with the observation than over the maritime area. The simulated regional climates, however, have the limitation to represent the number of days for extremely hot temperature and heavy rainfall over South Korea.

• Journal of the Korean Geographical Society
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• v.47 no.5
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• pp.677-699
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• 2012

Climate changes may cause substantial changes in spatial patterns and distribution of vector-borne diseases (VBD's), which will result in a significant threat to humans and emerge as an important public health problem that the international society needs to solve. As global warming becomes widespread and the Korean peninsula characterizes subtropical climate, the potentials of climate-driven disease outbreaks and spread rapidly increase with changes in land use, population distributions, and ecological environments. Vector-borne diseases are typically infected by insects such as mosquitoes and ticks, and infected hosts and vectors increased dramatically as the habitat ranges of the VBD agents have been expanded for the past 20 years. Medical geography integrates and processes a wide range of public health data and indicators at both local and regional levels, and ultimately helps researchers identify spatiotemporal mechanism of the diseases determining interactions and relationships between spatial and non-spatial data. Spatial epidemiology is a new and emerging area of medical geography integrating geospatial sciences, environmental sciences, and epidemiology to further uncover human health-environment relationships. An introduction of GIS-based disease monitoring system to the public health surveillance system is among the important future research agenda that medical geography can significantly contribute to. Particularly, real-time monitoring methods, early-warning systems, and spatial forecasting of VBD factors will be key research fields to understand the dynamics of VBD's.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.21-28
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• 2016

Numeric weather prediction is important to prevent meteorological disasters such as heavy rain, heat wave, and cold wave. The Korea meteorological administration provides a realtime special weather report and the rural development administration demonstrates information about 2-day warning of agricultural disasters for farms in a few regions. To improve the early warning systems for meteorological hazards, a nation-wide high-resolution dataset for weather prediction should be combined with web-based GIS. This study aims to develop a web service prototype for early warning of meteorological hazards, which integrates web GIS technologies with a weather prediction database in a temporal resolution of 1 hour and a spatial resolution of 1 km. The spatially and temporally high-resolution dataset for meteorological hazards produced by downscaling of GME was serviced via a web GIS. In addition to the information about current status of meteorological hazards, the proposed system provides the hourly dong-level forecasting of meteorologic hazards for upcoming seven days, such as heavy rain, heat wave, and cold wave. This system can be utilized as an operational information service for municipal governments in Korea by achieving the future work to improve the accuracy of numeric weather predictions and the preprocessing time for raster and vector dataset.

• Korean Journal of Construction Engineering and Management
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• v.17 no.2
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• pp.21-30
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• 2016

The current PF project is entirely relying on construction company's credibility. As such, it has increased a negative and bad recognition in domestic real estate economy. In addition, PF experts has a perception that a project's safety of future cash flow profitability is more important than the construction company's credibility. So many PF experts make an effort in order to set aside safe project structure of PF and analyse systematically the risks of the project. In common feasibility study of the PF Project, financial specialists and real estate specialists are forecasting and evaluating the suitability of the project through reviewing the development profit from the project of sales. However, cash flow analysis and evaluation from the perspective of mid-sized construction companies are still in the primary level. Therefore, this study has analysed the current feasibility study and go/no go decision making procedures. Then the authors have a new cash flow analysis method from the perspective of mid-sized construction companies, by improving the feasibility study and go/no go decision making procedures.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.295-303
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• 2017

In this paper, we analyze the trends of the international shipping market and the domestic and foreign factors of the crisis of the domestic shipping market, and identify the characteristics of the recovery of the Busan New Port trade volume which has decreased since the crisis of the domestic shipping market We quantitatively analyzed the future volume of Busan New Port and analyzed the trends of the prediction and recovery trends. As a result of analyzing Busan New Port container cargo volume by using big data analysis tool R, the variation of Busan New Cargo container cargo volume was estimated by ARIMA model (1,0,1) (1,0,1)[12] Estimation error, AICc and BIC were the most optimal ARIMA models. Therefore, we estimated the estimated value of Busan New Port trade for 36 months by using ARIMA (1, 0, 1)[12], which is the optimal model of Busan New Port trade, and estimated 13,157,184 TEU, 13,418,123 TEU, 13,539,884 TEU, and 4,526,406 TEU, respectively, indicating that it increased by about 2%, 2%, and 1%.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.421-436
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• 2016

Public-Private-Partnerships tend to be committed high project development cost and recover the cost through future revenue during the operation period. In general, long-term concession can bring on more revenue to private investors, but short-term concession less revenue due to the short recovering opportunities. The concession period is usually determined by government in advance or by the private sectors's proposal although it is a very crucial factor for the PPPs. Accurate traffic forecasting should be most important in planing and evaluating the operation period in that the forecasted traffic determines the project revenue with user fees in PPPs. In this regards, governments and the private investors are required to consider the traffic forecast risk when determining concession period. This study proposed a model for the optimal concession period in the PPPs transportation projects. Monte Carlo simulation was performed to find out the optimal concession period while traffic forecast uncertainty is considered as a project risk under the expected return of the private sector. The simulation results showed that the optimal concession periods are 17 years and 21 years at 5.5% and 7% discount level, respectively. This study result can be applied for the private investors and/or any other concerned decision makers for PPPs projects to set up a more resonable concession period.

• Journal of Satellite, Information and Communications
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• v.3 no.1
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• pp.48-54
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• 2008

With the increasing events of natural disasters caused by unpredictable atmospheric movements, the importance of weather forecasting is increasingly emphasized. In this paper, we adopt satellite radar imageries to deal with unusual weather events over Korean region including yellow sand that swept over Korea in spring 2007 and typhoon EWNIAR in 2006. Korea has suffered from these natural events with increasing frequencies over last decades and the satellite radar imaging is considered the most appropriate method to track and analyze the characteristics of the events spanning from mainland China to Japan. The yellow sand mostly comes from Manju area in China and consists of tiny particles so that they move with high speed resulting in difficulty in predicting their moving paths. With the use of various radar images taken at regular time intervals, we could possibly derive the expected movement of the yellow sand particles. In the future, with the help of radar images taken at very short intervals, satellite radar image analysis will become a very useful tool to predict and prepare for the natural disastrous events caused by abrupt change in the atmosphere and deserts around Korea.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.119-131
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• 2010

Drought is one of disaster causing factors to produce severe damage in the World because drought is destroyed to the ecosystem as well as to make difficult the economy of the drought area. This study, using Palmer Drought Severity Index carries out correlation analysis with sea surface temperatures. Comparative analysis carries out by calculated Palmer Drought Severity Index and past drought occurrence year. Result of comparative analysis, PDSI indexes were in accord with the past drought. Cluster analysis for correlation analysis carries out using precipitation and temperature that is input datas palmer drought severity index, and the result of cluster analysis was classified as 6. Also, principal component carries out using result of cluster analysis. 14 principal component analyze out through principal component analysis. Using analyzed 14 principal component carries out correlation analysis with sea surface temperature that is delay time from 0month until 11month. Correlation analysis carries out sea surface temperatures and calculated cycle component of the low frequency through Wavelet Transform analysis form principal component. Result of correlation analysis, yang(+) correlation is bigger than yin(-) correlation. It is possible to check similar correlation statistically the area of sea surface temperature with sea surface temperature in the Pacific. Forecasting possibility of the future drought make propose using sea surface temperature.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.133-143
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• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1D
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• pp.7-15
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• 2011

The travel time value is important factor for the evaluation of feasibility the transportation facility investment. The existing method for calculation of the travel time for each mode uses daily average trip purpose. So the value of travel time is constant because it is estimated with only daily average proportion. This daily constant time value can distort the results of future demands of toll roads or economic appraisals for the projects. The proportion of the trip purpose varies by time periods. Accordingly the value of travel time also varies by time periods. In this study, times periods are classified as morning peak, evening peak, business time off-peak, and non-business time off-peak. And trip purpose proportions are sorted by each time period from raw data of Seoul household trip study, then the value of travel time for each time period is estimated with these sorted purpose proportions. A case study of Seoul Jung-gu and Yongsan-gu performed with newly estimated time value by time periods. The result of benefit calculation with the daily constant time value is overestimated approximately annual 2.5 billion Won compared by time values by time periods. The demands of toll roads are also overestimated with the existing daily constant time value by daily 3,500 vehicles and total revenue of toll roads are overestimated by annually 1 billion Won. In conclusion, the value of travel time by each time period enables the more precise economic evaluation of the transportation facility investment projects, mode choice behavior, and route choice behavior especially for toll roads.