• Atmosphere
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• v.31 no.2
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• pp.185-198
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• 2021

In this study, we examined a spatial downscaling method based on Gradient and Inverse Distance Squared (GIDS) weighting to produce high-resolution grid data from a numerical weather prediction model over Korean Peninsula with complex terrain. The GIDS is a simple and effective geostatistical downscaling method using horizontal distance gradients and an elevation. The predicted meteorological variables (e.g., temperature and 3-hr accumulated rainfall amount) from the Limited-area ENsemble prediction System (LENS; horizontal grid spacing of 3 km) are used for the GIDS to produce a higher horizontal resolution (1.5 km) data set. The obtained results were compared to those from the bilinear interpolation. The GIDS effectively produced high-resolution gridded data for temperature with the continuous spatial distribution and high dependence on topography. The results showed a better agreement with the observation by increasing a searching radius from 10 to 30 km. However, the GIDS showed relatively lower performance for the precipitation variable. Although the GIDS has a significant efficiency in producing a higher resolution gridded temperature data, it requires further study to be applied for rainfall events.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.183-193
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• 2007

Geotechnical Information Database Project was began by Ministry of Construction Transport at the 1999, because many people need a sharing and reusing the geotechnical report in construction process. In the beginning, target was report of national highway construction, the whole of country has been target on since the 2005. Today, the 60,581 number of geotechnical data(counted by boring number) is maintained. In this study, Geotechnical Information Distribute System(GIDS) was developed, in order to improve practical use and to be connected to National Geographic Information Center. and program to be applicable to construction was suggested. GIDS is able to search/download geotechnical report with digital map by internet. This system is consisted of geotechnical data and metadata editor, registration tool, and web system. We expect that GIDS make a effect to improve geotechnical data management and to be use in all part of construction process.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.323-328
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• 2007

Geotechnical Information Database Project was began by Ministry of Construction Transport at the 1999, because many people need a sharing and reusing the geotechnical report in construction process. In the beginning, target was report of national highway construction. the whole of country has been target on since the 2005. Today, the 60,581 number of geotechnical data(counted by boring number) is maintained. In this study, Geotechnical Information Distribute System(GIDS) was developed, in order to improve practical use and to be connected to National Geographic Information Center(NGIC). and program to be applicable to construction was suggested. We expect that GIDS make a effect to improve geotechnical data application and to be use in all part of construction process.

• Annual Conference of KIPS
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• 2011.04a
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• pp.230-233
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• 2011

Chronic disease is linked to patient's' lifestyle. Therefore, doctor has to monitor his/her patient over time. This may involve reviewing many reports, finding any changes, and modifying several treatments. One solution to optimize the burden is using a visualizing tool over time such as a timeline-based visualization tool where all reports and medicine are integrated in a problem centric and time-based style to enable the doctor to predict and adjust the treatment plan. This solution was proposed by Bui et. al. [2] to observe the medical history of a patient. However, there was limitation of studying the diabetes patient's history to find out what was the cause of the current development in patient's condition; moreover what would be the prediction of current implication in one of the diabetes' related factors (such as fat, cholesterol, or potassium). In this paper, we propose a Grid-based Interactive Diabetes System (GIDS) to support bioinformatics analysis application for diabetes diseases. GIDS used an agglomerative clustering algorithm as clustering correlation algorithm as primary algorithm to focus medical researcher in the findings to predict the implication of the undertaken diabetes patient. The algorithm was Chronological Clustering proposed by P. Legendre [11] [12].