• Geophysics and Geophysical Exploration
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• v.3 no.4
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• pp.119-124
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• 2000

A new fast algorithm for travel time calculation using mono-chromatic one-way wave equation was developed based on the delta function and the logarithms of the single frequency wavefield in the frequency domain. We found an empirical relation between grid spacing and frequency by trial and error method such that we can minimize travel time error. In comparison with other methods, travel time contours obtained by solving eikonal equation and the wave front edge of the snapshot by the finite difference modeling solution agree with our algorithm. Compared to the other two methods, this algorithm computes travel time of directly transmitted wave. We demonstrated our algorithm on migration so that we obtained good section showing good agreement with original model. our results show that this new algorithm is a faster travel time calculation method of the directly transmitted wave for imaging the subsurface and the transmission tomography.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.43-49
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• 2019

The wired and wireless Internet is a useful window to easily acquire various types of media data. On the other hand, the public can easily get the media data including the object to which the personal information is exposed, which is a social problem. In this paper, we propose a method to robustly detect a target object that has exposed personal information using a learning algorithm and effectively block the detected target object area. In the proposed method, only the target object containing the personal information is detected using a neural network-based learning algorithm. Then, a grid-like mosaic is created and overlapped on the target object area detected in the previous step, thereby effectively blocking the object area containing the personal information. Experimental results show that the proposed algorithm robustly detects the object area in which personal information is exposed and effectively blocks the detected area through mosaic processing. The object blocking method presented in this paper is expected to be useful in many applications related to computer vision.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.735-742
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• 2021

Recently, renewable energy-related power generation facilities have been surging due to the government's "Renewable Energy 3020", "Green New Deal", "2050 Carbon Neutrality" and "K-RE100" policies. Most renewable energy facilities are small and distributed, making it difficult to manage efficiently, and small distributed resources less than 1MW are having a hard time with participating in the market due to the limited sales and avoidance of trading. In particular, the intermittency of renewable energy has a significant impact on the stability of the power grid. The government is seeking to address volatility and intermittency issues through 'small distributed resource brokerage trading, and to expand the systematic resourceization and acceptability of heterogeneous large and small distributed resources. In this work, we intend to apply an AI-based power generation prediction model to a distributed resource brokerage trading system so that it can be utilized as a foundation platform for pioneering new energy business markets.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.2
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• pp.135-145
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• 2023

Developing high-fidelity Computational Fluid Dynamics (CFD) simulation methods used to evaluate the airwake characteristics along a flight deck of a large ship, the various kind of data such as actual ship measurement and wind tunnel results are required to verify the accuracy of CFD simulation. Inflow velocity profile at the bow, local unsteady flow field data around the flight deck, and highly reliable wind tunnel data which were measured after reviewing Atmospheric Boundary Layer (ABL) simulation and Reynolds Number effects were also used to determine the key parameters such as turbulence model, time resolution and accuracy, grid resolution and type, inflow condition, domain size, simulation length, and so on in STAR CCM⁺. Velocity ratio and turbulent intensity difference between Full-scale CFD and actual ship measurement at the measurement points show less than 2% and 1.7% respectively. And differences in velocity ratio and turbulence intensity between wind tunnel test and small-scale CFD are both less than 2.2%. Based upon this fact, the selected parameters in CFD simulation are highly reliable for a specific wind condition.

• Journal of Radiation Protection and Research
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• v.48 no.1
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• pp.28-43
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• 2023

Background: High-fidelity meteorological data is a prerequisite for the realistic simulation of atmospheric dispersion of radioactive materials near nuclear power plants (NPPs). However, many meteorological models frequently overestimate near-surface wind speeds, failing to represent local meteorological conditions near NPPs. This study presents a new high-resolution (approximately 1 km) meteorological downscaling method for modeling short-range (< 100 km) atmospheric dispersion of accidental NPP plumes. Materials and Methods: Six considerations from literature reviews have been suggested for a new dynamic downscaling method. The dynamic downscaling method is developed based on the Weather Research and Forecasting (WRF) model version 3.6.1, applying high-resolution land-use and topography data. In addition, a new subgrid-scale topographic drag parameterization has been implemented for a realistic representation of the atmospheric surface-layer momentum transfer. Finally, a year-long simulation for the Kori and Wolsong NPPs, located in southeastern coastal areas, has been made for 2016 and evaluated against operational surface meteorological measurements and the NPPs' on-site weather stations. Results and Discussion: The new dynamic downscaling method can represent multiscale atmospheric motions from the synoptic to the boundary-layer scales and produce three-dimensional local meteorological fields near the NPPs with a 1.2 km grid resolution. Comparing the year-long simulation against the measurements showed a salient improvement in simulating near-surface wind fields by reducing the root mean square error of approximately 1 m/s. Furthermore, the improved wind field simulation led to a better agreement in the Eulerian estimate of the local atmospheric dispersion. The new subgrid-scale topographic drag parameterization was essential for improved performance, suggesting the importance of the subgrid-scale momentum interactions in the atmospheric surface layer. Conclusion: A new dynamic downscaling method has been developed to produce high-resolution local meteorological fields around the Kori and Wolsong NPPs, which can be used in short-range atmospheric dispersion modeling near the NPPs.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.317-317
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• 2020

수재해는 수자원 인프라의 부족 및 관리 미흡 등 많은 요인들이 있지만 강우의 유무와 크기가 가장 원초적인 요인들 중 하나이다. 정확한 강우량 추정 및 강우발생시간 예측은 수재해로 인한 피해를 예방하고 빠르게 대처할 수 있다. 그러나 강우예측에는 많은 불확실성을 내포하고 있기 때문에 이러한 불확실성을 이해하고 줄여 나가는 것이 필요하다. 최근 컴퓨터의 성능의 발전에 비례해 강우 예측 자료들도 점진적으로 발전을 거듭하고 있다. 이를 강우-유출 모형에 적용시 유출량 예측의 정확성 또한 비례하여 한층 더 발전할 수 있을 것이다. 하지만 신뢰성이 낮은 입력자료를 대상으로 하는 유출해석 모형은 많은 불확실성을 내포할 것이다. 따라서 본 연구에서는 위천 유역에 대해 LENS(Limited area ENsemble prediction System) 강우앙상블 예측자료의 적용성을 검토하고 그리드 기반 강우 유출 모델 GRM(Grid based Rainfall-runoff Model) 에 적용하여 유출예측의 불확실성을 평가하고자 하였다. 또한 강우예측 및 유출예측은 수 많은 매개변수를 포함하며 최종적인 예측은 더 큰 불확실한 범위로 산출될 수 있다. 이에 따라 본 연구에서는 Python3 기반 코딩으로 LENS 자료 구축 및 GRM 모형의 매개변수 보정을 각 2000회 씩에 걸쳐 총 2회 실시하여 수문학적, 지형학적 인자에 따른 불확실성 범위를 보정하고자 하였다. 매개변수의 보정은 비정형우도(Informal likelihood) NSE, 정형우도(Formal likelihood) Lognormal(Log-likelihood function)의 우도에 따른 행위모델을 산정하여 보정하였다. 따라서 본 연구에서는 선행연구들을 참고한 정형, 비정형 우도의 임계치를 이용한 불확실성해석에 적용하였으며 이는 사용자의 행위모델선정 임계치 범위 선정으로 인한 불확실성을 줄여나감에 기여할 수 있을것으로 사료된다.

• Geotechnical Engineering
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• v.1 no.1
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• pp.59-72
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• 1985

This paper deals with the numerical analysis by the (mite element method introducing Biot's theory of consolidation and the modified Cambridge model proposed by Roscoe school of Cambridge University as constitutive equation and using Christian-Boehner's technique. Especially, time interval and division of elements are investigated in vies of stability and economics. In order to check the validity of author's program, the program was tested with one-dimensional consolidation case followed by Terzaghi's exact solution and with the results of the Magnan's analysis for existing banking carried out for study at Cubzac-les-ports in France. The main conclusions obtained are summarized as follows: 1. In the case of one-dimensional consolidation, the more divided the elements are near the surface of the foundation, the higher the accuracy of the numerical analysis is. 2. For the time interval, it is stable to divide 20 times per 1-lg cycle. 3. At the element which has long drain distance, the Mandel-fryer effect appears due to time lag. 4. Lateral displacement at an initial loading stage predicted by author's program, in which the load was assumed as not concentrative. but rather in grid form, is well consistent with the value of observation. 5. The pore water pressure predicted by author's program has a better accordance with the value of observation compared with Magnan's results. 6. Optimum construction control by Matsuo-Kawamura's method is possible with the predicted lateral displacement and settlement by the program.

• Journal of Environmental Impact Assessment
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• v.24 no.5
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• pp.516-531
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• 2015

In this study, a software module to predict the effectiveness of vegetation buffer strip (VBS) has been developed for using with Chemicals, Agricultural Management and Erosion Losses (CAMEL), a distributed watershed model. Most basic functions for the VBS module are same as CAMEL except functions newly developed to implement sedimentation enhancement by vegetation and level spreaders. For verification of the VBS module, sensitivity analyses for length, roughness, soil and vegetation type of VBS were carried out using a test grid cell. The surface discharge of sediment are highly sensitive to the roughness coefficient of VBS. The removal efficiencies of VBS for the surface discharges of sediment and TP are generally high regardless of environment changes. The surface discharges of TOC and TN are highly sensitive to the length and soil of VBS. The removal efficiencies of VBS for the surface discharges of TOC and TN are generally lower than those of sediment and TP. The newly developed VBS module reasonably simulates the removal efficiencies of surface discharges that vary according to the environment changes. It is expected that this VBS module can be used for evaluating the effectiveness of VBS-based best management practices to be applied to reduce pollution discharges from various non-point sources.

• 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.