• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.151-160
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• 2014

In this paper, a comparison of superpixel characteristics based on SLIC(simple linear iterative clustering) for several color feature spaces is presented. Computer vision applications have come to rely increasingly on superpixels in recent years. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. A superpixel is consist of pixels with similar features such as luminance, color, textures etc. Thus superpixels are more efficient than pixels in case of large scale image processing. Generally superpixel characteristics are described by uniformity, boundary precision and recall, compactness. However previous methods only generate superpixels a special color space but lack researches on superpixel characteristics. Therefore we present superpixel characteristics based on SLIC as known popular. In this paper, Lab, Luv, LCH, HSV, YIQ and RGB color feature spaces are used. Uniformity, compactness, boundary precision and recall are measured for comparing characteristics of superpixel. For computer simulation, Berkeley image database(BSD300) is used and Lab color space is superior to the others by the experimental results.

• Geomechanics and Engineering
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• v.34 no.1
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• pp.29-41
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• 2023

The 3D geospatial modeling of geotechnical information can aid in understanding the geotechnical characteristic values of the continuous subsurface at construction sites. In this study, a geostatistical optimization model for the three-dimensional (3D) mapping of subsurface stratification and the SPT-N value based on a trial-and-error rule was developed and applied to a dam emergency spillway site in South Korea. Geospatial database development for a geotechnical investigation, reconstitution of the target grid volume, and detection of outliers in the borehole dataset were implemented prior to the 3D modeling. For the site-specific subsurface stratification of the engineering geo-layer, we developed an integration method for the borehole and geophysical survey datasets based on the geostatistical optimization procedure of ordinary kriging and sequential Gaussian simulation (SGS) by comparing their cross-validation-based prediction residuals. We also developed an optimization technique based on SGS for estimating the 3D geometry of the SPT-N value. This method involves quantitatively testing the reliability of SGS and selecting the realizations with a high estimation accuracy. Boring tests were performed for validation, and the proposed method yielded more accurate prediction results and reproduced the spatial distribution of geotechnical information more effectively than the conventional geostatistical approach.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.123-123
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• 2020

The present study is aimed to correcting radar-based mean areal precipitation forecasts to improve urban flood predictions and uncertainty analysis of water levels contributed at each stage in the process. For this reason, a long short-term memory (LSTM) network is used to reproduce three-hour mean areal precipitation (MAP) forecasts from the quantitative precipitation forecasts (QPFs) of the McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation (MAPLE). The Gangnam urban catchment located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 24 heavy rainfall events, 22 grid points from the MAPLE system and the observed MAP values estimated from five ground rain gauges of KMA Automatic Weather System. The corrected MAP forecasts were input into the developed coupled 1D/2D model to predict water levels and relevant inundation areas. The results indicate the viability of the proposed framework for generating three-hour MAP forecasts and urban flooding predictions. For the analysis uncertainty contributions of the source related to the process, the Bayesian Markov Chain Monte Carlo (MCMC) using delayed rejection and adaptive metropolis algorithm is applied. For this purpose, the uncertainty contributions of the stages such as QPE input, QPF MAP source LSTM-corrected source, and MAP input and the coupled model is discussed.

• Journal of Korean Association for Spatial Structures
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• v.24 no.2
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• pp.83-90
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• 2024

Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.47-63
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• 2021

Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

• Atmosphere
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• v.23 no.2
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• pp.221-229
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• 2013

There has been an increasing need to assess the effects of climate change on human health. It is hard to use climate data to evaluate health effects because such data have a grid format, which could not represent specific cities or provinces. Therefore, the grid-format climate data of South Korea based on RCP (Representative Concentration Pathway) scenarios were modified into area-format climate data according to the major cities or provinces of the country, up to the year 2100. Moreover, heat index (HI) and discomfort index (DI) databases were developed from the modified climate database. These databases will soon be available for experts via a Website, and the expected HI and DI of any place in the country, or at any time, can be found in the country's climate homepage (http://www.climate.go.kr). The HI and DI were analyzed by plotting the average indices every ten years, and by comparing cities or provinces with index level changes, using the geographic information system (GIS). Both the HI and DI are expected to continually increase from 2011 to 2100, and to reach the most dangerous level especially in August 2100. Among the major cities of South Korea, Gwangju showed the highest HI and DI, and Gangwon province is expected to be the least affected area in terms of HI and DI among all the country's provinces.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.8
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• pp.825-836
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• 2010

The advancement of electronic records brought great changes of the records management system. One of the biggest changes is the transition from passive to automatic management system, which manages massive records more efficiently. The integrated Rule-Oriented Data System (iRODS) is a rule-oriented grid system S/W which provides an infrastructure for building massive archive through virtualization. It also allows to define rules for data distribution and back-up. Therefore, iRODS is an ideal tool to build an electronic record management system that manages electronic records automatically. In this paper we describe the issues related to design and implementation of the electronic record management system using iRODS. We also propose a system that serves automatic processing of distribution and back-up of records according to their types by defining iRODS rules. It also provides functions to store and retrieve metadata using iRODS Catalog (iCAT) Database.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.6
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• pp.237-247
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• 2008

A virtual screening is the process of reducing an unmanageable number of compounds to a limited number of compounds for the target of interest by means of computational techniques such as molecular docking. And it is one of a large-scale scientific application that requires large computing power and data storage capability. Previous applications or softwares for molecular docking such as AutoDock, FlexX, Glide, DOCK, LigandFit, ViSION were developed to be run on a supercomputer, a workstation, or a cluster-computer. However the virtual screening using a supercomputer has a problem that a supercomputer is very expensive and the virtual screening using a workstation or a cluster-computer requires a long execution time. Thus we propose a service-based virtual screening system using Grid computing technology which supports a large data intensive operation. We constructed 3-dimensional chemical molecular database for virtual screening. And we designed a resource broker and a data broker for supporting efficient molecular docking service and proposed various services for virtual screening. We implemented service based virtual screening system with DOCK 5.0 and Globus 3.2 toolkit. Our system can reduce a timeline and cost of drug or new material design.

• Economic and Environmental Geology
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• v.44 no.4
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• pp.289-302
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• 2011

Since the frequency of the earthquake occurrence in Korean peninsular is continuously increasing, the possibility that massive landslides are triggered by earthquake is also growing in Korea. Previously, the landslide is known to be induced by large magnitude earthquake, whose magnitude is larger than 6.0. However, the landslide can be induced by only small magnitude earthquake, especially in the fully saturated soil. Therefore, the susceptibility of landslide caused by small magnitude earthquake in fully saturated soil is analyzed in this study. For that, the topographical and geological characteristics of the site were obtained and managed by GIS software. In the procedure of the study, slope angle, cohesion, friction angle, unit weight of soil were obtained and constructed as a spatial database layer. Combining these data sets in a dynamic model based on Newmark's displacement analysis, the landslide displacements were estimated in each grid cell. In order to check out the possibility of the earthquake induced landslides, the level of the groundwater table is varied from dry to 80% saturated soil. In addition, in order to analyze the effect of the magnitude of earthquake and distance to epicenter, four different earthquakes epicenters were considered in the study area.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.151-161
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• 2009

In Location-Based Services (LBSs), users requesting a location-based query send their exact location to a database server and thus the location information of the users can be misused by adversaries. Therefore, a privacy protection method is required for using LBS in a safe way. In this paper, we propose a new cloaking region generation algorithm using grids for privacy protection in LBSs. The proposed algorithm creates a m inimum cloaking region by finding L buildings and then performs K-anonymity to search K users. For this, we make use of not only a grid-based index structure, but also an efficient pruning techniques. Finally, we show from a performance analysis that our cloaking region generation algorithm outperforms the existing algorithm in term of the size of cloaking region.