• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.148-162
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• 2023

Classification systems can significantly assist the medical sector by allowing for the precise and quick diagnosis of diseases. As a result, both doctors and patients will save time. A possible way for identifying risk variables is to use machine learning algorithms. Non-surgical technologies, such as machine learning, are trustworthy and effective in categorizing healthy and heart-disease patients, and they save time and effort. The goal of this study is to create a medical intelligent decision support system based on machine learning for the diagnosis of heart disease. We have used a mixed feature creation (MFC) technique to generate new features from the UCI Cleveland Cardiology dataset. We select the most suitable features by using Least Absolute Shrinkage and Selection Operator (LASSO), Recursive Feature Elimination with Random Forest feature selection (RFE-RF) and the best features of both LASSO RFE-RF (BLR) techniques. Cross-validated and grid-search methods are used to optimize the parameters of the estimator used in applying these algorithms. and classifier performance assessment metrics including classification accuracy, specificity, sensitivity, precision, and F1-Score, of each classification model, along with execution time and RMSE the results are presented independently for comparison. Our proposed work finds the best potential outcome across all available prediction models and improves the system's performance, allowing physicians to diagnose heart patients more accurately.

• Wind and Structures
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• v.36 no.3
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• pp.161-174
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• 2023

The analytical model of tornado vortices plays an essential role in tornado wind description and tornado-resistant design of civil structures. However, there is still a lack of guidance for the selection and application of tornado analytical models since they are different from each other. For single-cell tornado vortices, this study conducts a comparative study on the velocity characteristics of the analytical models based on numerically simulated tornado-like vortices (TLV). The single-cell stage TLV is first generated by Large-eddy simulations (LES). The spatial distribution of the three-dimensional mean velocity of the typical analytical tornado models is then investigated by comparison to the TLV with different swirl ratios. Finally, key parameters are given as functions of swirl ratio for the direct application of analytical tornado models to generate full-scale tornado wind field. Results show that the height of the maximum radial mean velocity is more appropriate to be defined as the boundary layer thickness of the TLV than the height of the maximum tangential mean velocity. The TLV velocity within the boundary layer can be well estimated by the analytical model. Simple fitted results show that the full-scale maximum radial and tangential mean velocity increase linearly with the swirl ratio, while the radius and height corresponding to the position of these two velocities decrease non-linearly with the swirl ratio.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.329-329
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• 2022

Accurate characterization of terrestrial precipitation variation from high spatial resolution satellite sensors is beneficial for urban hydrology and microscale agriculture modeling, as well as natural disasters (e.g., urban flooding) early warning. However, the widely-used top-down approach for precipitation retrieval from microwave satellites is limited in several hydrological and agricultural applications due to their coarse spatial resolution. In this research, we aim to apply a novel bottom-up method, the parameterized SM2RAIN, where precipitation can be estimated from soil moisture signals based on an inversion of water balance model, to generate high spatial resolution terrestrial precipitation estimates at 0.01º grid (roughly 1-km) from the C-band SAR Sentinel-1. This product was then tested against a common reanalysis-based precipitation data and a domestic rain gauge network from the Korean Meteorological Administration (KMA) over central South Korea, since a clear difference between climatic types (coasts and mainlands) and land covers (croplands and mixed forests) was reported in this area. The results showed that seasonal precipitation variability strongly affected the SM2RAIN performances, and the product derived from separated parameters (rainy and non-rainy seasons) outperformed that estimated considering the entire year. In addition, the product retrieved over the mainland mixed forest region showed slightly superior performance compared to that over the coastal cropland region, suggesting that the 6-day time resolution of S1 data is suitable for capturing the stable precipitation pattern in mainland mixed forests rather than the highly variable precipitation pattern in coastal croplands. Future studies suggest comparing this product to the traditional top-down products, as well as evaluating their integration for enhancing high spatial resolution precipitation over entire South Korea.

• Korean Security Journal
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• no.58
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• pp.9-34
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• 2019

The Korean Police Force is equipped with the dual responsibility to not only protect the constitutional right to protest, but also prevent potential disorder and misconduct might be caused by the abuse of such a right. To this end, the Korean national police employ the crowd counting methodology, termed 'Maximum Figure at Any One Time' with a view to dispatching the proportionate number of police officers to protest scenes for safety management. However, protest organizers rather take advantage of 'Cumulative Figure' methodology, the purpose of which being to publicize the wide recognition of success, noticeably by demonstrating that as many people as possible support for their cause or voice. Hence, different estimates generated by different methods have raised serious political issues in Korean society. Nevertheless, it is found out that there are only three existing academic studies in Korea regarding crowd counting methods, and they are mainly geared towards comparing the two methods, unfortunately without any attempt to analyze the foreign literature in details. Keeping the research gap in mind, the research conducts a comprehensive review of the foreign literature with relation to protest crowd counting methods. Derived from the review and analysis, the counting methods can be broadly categorized into the three models such as: 1) Grid/Density Model, 2) Moving Crowds Model, and 3) Electronic & Non-Image Model. In the end, the research provides brief explanations regarding specific research findings per each model, and further, suggests some policy implications for the development of more accurate crowd counting methodology at protests in Korea.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.929-940
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• 2011

In this study, the future expected discharges are analyzed for Daecheong and Yongdam Dam Watershed in Geum River watershed using A1B scenario based RCM with 27 km spatial resolutions from Korea Meteorological Agency and SWAT model. The direct use of GCM and RCM data for water resources impact assessment is practically hard because the spatial and temporal scales are different. In this study, the problems of spatial and temporal scales were settled by the spatial and temporal downscaling from watershed scale to weather station scale and from monthly to daily of RCM grid data. To generate the detailed hydrologic scenarios of the watershed scale, the multi-site non-stationary downscaling method was used to examine the fluctuations of rainfall events according to the future climate change with considerations of non-stationary. The similarity between simulation and observation results of inflows and discharges at the Yongdam Dam and Daecheong Dam was respectively 90.1% and 84.3% which shows a good agreement with observed data using SWAT model from 2001 to 2006. The analysis period of climate change was selected for 80 years from 2011 to 2090 and the discharges are increased 6% in periods of 2011~2030. The seasonal patterns of discharges will be different from the present precipitation patterns because the simulated discharge of summer was decreased and the discharge of fall was increased.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.79-94
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• 2011

As demonstrated in study for non-submerged groynes, the flow field is predominantly two-dimensional, with mainly horizontal eddies. The eddies shed form the tips of the groynes and migrate in the flow direction. These eddies have horizontal dimensions in the order of tens of meters and time-scales in the order of minutes. In the standard flow simulations, these motions are usually not resolved, due to a too coarse grid, too large time steps and, more importantly, the use of inadequate turbulence modelling. using for example a k-${\varepsilon}$ model, it is necessary to introduce substantial modifications. Therefore simulation resolved in this study, were carried out using the DELFT-3D-MOR programme, which is part of the DELFT3D software package of WL/Delft Hydraulics and In this study, apply a two-dimensional depth-averaged model, taking an horizontal large eddy simulation(HLES). The bed morphology computed when using HLES, as well as the associated time-scale, is similar to what has been obseved in a field case. When using a mean-flow model with-out HELS, the bed morphology is less realistic and the morphological time-scale is much larger. This slow development is the result of neglecting(or averaging). the strong velocity fluctuations associated with the time-varying eddy formation.

• Korean Journal of Ecology and Environment
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• v.53 no.1
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• pp.11-21
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• 2020

In this study, we compared the spatio-temporal differences of phytoplankton communities among 4 lakes in the Boseong River basin. Field research was conducted quarterly from 2014 to 2017 for this study. A total of 345 species of phytoplankton were identified including 107 Bacillariophyceae, 175 Chlorophyceae, 27 Cyanophyceae and 36 other phytoplankton taxa. Lake Boseong showed higher species numbers and density of phytoplankton than other lakes (Dunn's test, P<0.01). Bacillariophyceae such as Asterionella formosa, Aulacoseira granulata, Fragilaria crotonensis was dominated in most research periods, whereas Scenedesmus ecornis and Coelastrum cambricum belonging to Chlorophyceae were dominant species on August. The self-organizing map (SOM) classified 3 clusters with 10 × 7 grid and showed spatio-temporal variation of phytoplankton communities based on significant difference among each clusters. Total 31 species of phytoplankton were chosen as a indicator species using indicator species analysis(ISA) and reflected seasonal phytoplankton succession and diversity and density of phytoplankton according to nutrient concentration. Water temperature, Secchi depth, conductivity and DO were identified as important factors affecting the differences of phytoplankton communities in the studied lakes in Boseong River basin using non-metric multidimensional scaling (NMDS).

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.3-12
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• 2010

In previous studies, the digital measurement systems and analysis algorithms were developed by using the related techniques, such as the aerial photograph detection and high resolution satellite image process. However, these studies were limited in 2-dimensional geo-processing. Therefore, it is necessary to apply the 3-dimensional spatial information and coordinate system for higher accuracy in recognizing and locating of geo-features. The objective of this study was to develop a stochastic algorithm for the optimal sensor placement using the 3-dimensional spatial analysis method. The 3-dimensional information of the LiDAR was applied in the sensor field algorithm based on 2- and/or 3-dimensional gridded points. This study was conducted with three case studies using the optimal sensor placement algorithms; the first case was based on 2-dimensional space without obstacles(2D-non obstacles), the second case was based on 2-dimensional space with obstacles(2D-obstacles), and lastly, the third case was based on 3-dimensional space with obstacles(3D-obstacles). Finally, this study suggested the methodology for the optimal sensor placement - especially, for ground-settled sensors - using the LiDAR data, and it showed the possibility of algorithm application in the information collection using sensors.

• Geophysics and Geophysical Exploration
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• v.9 no.3
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• pp.241-249
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• 2006

Due to the long tectonic history and the very complex geologic formations in Korea, the anisotropic characteristics of subsurface material may often change very greatly and locally. The algorithms commonly used, however, may not give sufficiently precise computational results of traveltime data particularly for the complex and strong anisotropic model, since they are based on the two-dimensional (2D) earth and/or weak anisotropy assumptions. This study is intended to develope a three-dimensional (3D) modeling algorithm to precisely calculate the first arrival time in the complex anisotropic media. Considering the complex geology of Korea, we assume 3D TTI (tilted transversely isotropy) medium having the arbitrary symmetry axis. The algorithm includes the 2D non-linear interpolation scheme to calculate the traveltimes inside the grid and the 3D traveltime mapping to fill the 3D model with first arrival times. The weak anisotropy assumption, moreover, can be overcome through devising a numerical approach of the steepest descent method in the calculation of minimum traveltime, instead of using approximate solution. The performance of the algorithm developed in this study is demonstrated by the comparison of the analytic and numerical solutions for the homogeneous anisotropic earth as well as through the numerical experiment for the two layer model whose anisotropic properties are greatly different each other. We expect that the developed modeling algorithm can be used in the development of processing and inversion schemes of seismic data acquired in strongly anisotropic environment, such as migration, velocity analysis, cross-well tomography and so on.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1353-1366
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• 2015

These days Shewhart control chart for evaluating stability of the process is widely used in various field. But it must follow strict assumption of distribution. In real-life problems, this assumption is often violated when many quality characteristics follow non-normal distribution. Moreover, it is more serious in multivariate quality characteristics. To overcome this problem, many researchers have studied the non-parametric control charts. Recently, SVDD (Support Vector Data Description) control chart based on RBF (Radial Basis Function) Kernel, which is called K-chart, determines description of data region on in-control process and is used in various field. But it is important to select kernel parameter or etc. in order to apply the K-chart and they must be predetermined. For this, many researchers use grid search for optimizing parameters. But it has some problems such as selecting search range, calculating cost and time, etc. In this paper, we research the efficiency of selecting parameter regions as data structure vary via simulation study and propose a new method for determining parameters so that it can be easily used and discuss a robust choice of parameters for various data structures. In addition, we apply it on the real example and evaluate its performance.