• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.23-23
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• 2018

본 연구에서는 다중분위회귀분석모형(Multiple Quantile Regression Model, MQRM)과 MODIS(MODerate resolution Imaging Spectroradiometer) LST (Land Surface Temperature) 자료를 이용하여 전국 공간토양수분을 산정하였다. 공간토양수분을 산정하기 위한 과정은 크게 두가지로 구분된다. 첫 번째로 기존의 MODIS LST 자료를 조건부 합성 보정기법을 적용하여 실측 LST 자료와 비교하여 위성 LST 자료가 갖고 있는 오차를 보정하였다. 그 결과, 조건부 합성 보정기법을 적용하기전 전국 71개 지상관측지점에서 관측한 실측 LST와 MODIS LST의 $R^2$는 전체 평균 0.70으로 어는정도 유의성 있는 상관관계를 나타냈으나 조건부 합성 보정기법을 적용한 후 실측 LST와 MODIS LST의 $R^2$는 전체 평균 0.92로 상당히 크게 향상됨을 알 수 있었다. 두 번째로 보정된 MODIS LST를 이용하여 다중분위회귀분석 모형을 개발하고 토양수분을 예측하는 단계로 입력자료로 위성영상 자료와 관측자료를 융합하여 사용하였다. 위성영상 자료로는 보정된 MODIS LST와 MODIS NDV를 구축하였고 일단위 강수량 및 일조시간의 기상자료는 기상청으로부터 전국 71개 지점에 대해 구축하여 IDW 공간보간기법을 이용한 공간자료로 구축하였다. 토양수분 결과를 비교하기 위한 관측 토양수분은 자동농업기상관측(Automated Agriculture Observing System, AAOS)지점에서 2013년 1월부터 2015년 12월까지의 실측 일단위 토양수분 자료를 구축하여 사용하였다. 다중분위회귀분석 모형은 LST 인자를 중심으로 각각의 분위(0.05, 0.25, 0.5, 0.75, 0.95)에 해당되는 값의 회귀식을 NDVI, 강수 입력자료를 독립인자로서 조합하여 계절 및 토성에 따른 총 80개의 회귀식을 산정하였다. 관측 토양수분과 모의 토양수분을 비교한 결과 $R^2$가 0.70 (철원), 0.90 (춘천), 0.85 (수원), 0.65 (서산), 0.78 (청주), 0.82 (전주), 0.62 (순천), 0.63 (진주), 0.78 (보성)로 높은 상관성을 보였다. 본 연구에서는 다중분위회귀 모형의 성능을 검증하기 위해 기존의 다중선형회귀모형의 결과와 비교하여 크게 개선됨을 나타냈다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.9
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• pp.617-628
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• 2019

The currently considered pyrotechnic separation nut is separated through the complicated process, because it has many internal moving parts and two variable-volume chambers connected by the vent hole. Therefore, it has many design parameters. Some of these are the contact angles between internal moving parts, the masses of the internal moving parts, the inner diameter of the push rod protrusion, the initial volumes of the chambers, the mass of the explosive charge, and the diameter of the vent hole. To improve the pyrotechnic separation nut, it is necessary to understand how the behavior of the separation nut is changed according to design parameters. In this point of view, parametric studies are carried out using the previously proposed prediction model for pyrotechnic separation nut behaviors. In each case, the parameter of the interest is changed while the others are kept unchanged. From the results, it is investigated how each design parameter influences the separation behavior.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.94-94
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• 2017

지속적인 수질의 모니터링과 관리가 어려운 개발도상국의 경우, 모델링을 통한 병원균의 예측이 중요하다. Soil and Water Assessment Tool (SWAT)은 유역 모델로 병원균의 거동을 모의하는데 널리 활용된다. 하지만 SWAT이 모의하는 in-stream 모듈의 경우, 소멸, 부유, 퇴적의 단계만을 고려하여 정확도가 부족하다. 따라서 본 연구는 기존 모듈에 hyporheic exchange와 생장 단계를 추가하여 모듈의 성능 개선 및 열대 산지 유역에서의 병원균의 거동을 모의하였다. 본 연구는 몬순 기후 및 산지 지형을 가진 라오스의 Houay Pano 유역을 대상으로 대장균 (Escheichia coli, E.coli)의 거동을 2011년부터 2013년까지 일 단위로 모의하였다. 기존의 SWAT 박테리아 모듈의 경우, 소멸 단계만을 가지고 보정하였을 때 모델은 대부분 0의 값을 가졌고, 부유 및 퇴적 단계가 추가 된 후에는 우기시 대부분의 모델값이 관측값의 95% 신뢰 구간에 포함되었으나 건기에는 농도가 여전히 낮게 모의됨을 확인 할 수 있다. 건기 시 낮게 모의된 농도를 증가시키기 위해, 온도에 따른 생장 단계를 추가하였으며, 이때 생장 속도는 설정된 최소-최대 생장 온도 사이에서 최대값을 가진다. 하지만 온도에 따른 생장은 열대 기후의 특성상 전 기간에 걸쳐 동시에 증가하여 건기에만 낮게 모의된 농도를 보완하는 데는 한계가 있었다. Hyporheic exchange는 강바닥에 임시로 저장된 박테리아의 양이 특정 유량에 의해서 수계로 유입되는 현상으로, 본 연구에서는 일정한 양의 hyporheic flow를 가정하여 모의하였다. 결과적으로 Hyporheic exchange를 통해 유입되는 적은 양의 E.coli는 기존에 타당하게 모의된 우기의 농도는 그대로 유지하되, 건기에 낮게 모의된 농도는 증가시켜 기존 SWAT 모듈의 한계점을 잘 보완한 것을 확인 하였다. 결론적으로, 기존의 SWAT 모델은 건기 시 낮은 농도의 E.coli를 모의하기에 한계를 보였으며, 전 기간에 걸쳐 높은 온도를 유지하는 열대 기후에서 생장 단계는 이러한 한계를 보완하기에 적합하지 않은 것으로 판단되었다. 그러나 적은 양이 전 기간에 걸쳐 동일하게 유입되는 hyporheic exchange의 경우, 건기에 낮게 모의된 농도를 증가시켜 기존의 한계를 보완할 수 있었다.

• Atmosphere
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• v.31 no.1
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• pp.85-100
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• 2021

The necessity of accurate high-resolution meteorological forecasts becomes increasing in socio-economical applications and disaster risk management. The Korea Meteorological Administration Post-Processing (KMAPP) system has been operated to provide high-resolution meteorological forecasts of 100 m over the South Korea region. This study evaluates and improves the KMAPP performance in simulating wind speeds over complex terrain areas using the ICE-POP 2018 field campaign measurements. The mountainous measurements give a unique opportunity to evaluate the operational wind speed forecasts over the complex terrain area. The one-month wintertime forecasts revealed that the operational Local Data Assimilation and Prediction System (LDAPS) has systematic errors over the complex mountainous area, especially in deep valley areas, due to the orographic smoothing effect. The KMAPP reproduced the orographic height variation over the complex terrain area but failed to reduce the wind speed forecast errors of the LDAPS model. It even showed unreasonable values (~0.1 m s-1) for deep valley sites due to topographic overcorrection. The model's static parameters have been revised and applied to the KMAPP-Wind system, developed newly in this study, to represent the local topographic characteristics better over the region. Besides, sensitivity tests were conducted to investigate the effects of the model's physical correction methods. The KMAPP-Wind system showed better performance in predicting near-surface wind speed during the ICE-POP period than the original KMAPP version, reducing the forecast error by 21.2%. It suggests that a realistic representation of the topographic parameters is a prerequisite for the physical downscaling of near-ground wind speed over complex terrain areas.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.1
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• pp.103-111
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• 2021

Naju Seokdanggan, Treasure No. 49, was dismantled and reconstructed due to poor performance. During construction, the crack area was reinforced and the inclination was improved. It is necessary to analyze the stiffness changes before and after the reconstruction of these cultural properties, and to establish a database of related information. In addition, there is a need for research on a scientific non-destructive testing method capable of predicting or evaluating the reinforcing effect. In this study, a simple equation for estimating the overall stiffness of the structural system was derived from information on the elasticity coefficient and the natural frequency measured by vibration tests before and after reconstruction work, and the applicability of the equation was examined. If the stiffness of important cultural properties is regularly investigated by the suggested method, it is judged that it can be used as data to estimate the time when structural safety diagnosis is necessary or when repair or reinforcement is necessary.

• Atmosphere
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• v.31 no.5
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• pp.637-656
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• 2021

The United States has been known as the world's major producer of crops such as wheat, corn, and soybeans. Therefore, using meteorological long-term forecast data to project reliable crop yields in the United States is important for planning domestic food policies. The current study is part of an effort to improve the seasonal predictability of regional-scale precipitation across the United States for estimating crop production in the country. For the purpose, a dynamic downscaling method using Weather Research and Forecasting (WRF) model is utilized. The WRF simulation covers the crop-growing period (March to October) during 2000-2020. The initial and lateral boundary conditions of WRF are derived from the Pusan National University Coupled General Circulation Model (PNU CGCM), a participant model of Asia-Pacific Economic Cooperation Climate Center (APCC) Long-Term Multi-Model Ensemble Prediction System. For bias correction of downscaled daily precipitation, empirical quantile mapping (EQM) is applied. The downscaled data set without and with correction are called WRF_UC and WRF_C, respectively. In terms of mean precipitation, the EQM effectively reduces the wet biases over most of the United States and improves the spatial correlation coefficient with observation. The daily precipitation of WRF_C shows the better performance in terms of frequency and extreme precipitation intensity compared to WRF_UC. In addition, WRF_C shows a more reasonable performance in predicting drought frequency according to intensity than WRF_UC.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.391-404
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• 2022

Aron Gohr proposed a cryptanalysis method based on deep learning technology for the lightweight block cipher Speck. This is a method that enables a chosen plaintext attack with higher accuracy than the classical differential cryptanalysis. In this paper, by using the probability distribution, we analyze the mechanism of such deep learning based cryptanalysis and propose the results applied to the lightweight block cipher Simon. In addition, we examine that the probability distributions of the predicted values of the neural networks within the cryptanalysis working processes are different depending upon the characteristics of round functions of Speck and Simon, and suggest a direction to improve the efficiency of the neural distinguisher which is the core technology of Aron Gohr's cryptanalysis.

• Journal of the Korean Geotechnical Society
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• v.38 no.8
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• pp.29-37
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• 2022

A three-dimensional analysis is required to interpret the drainage behavior of an improved ground with vertical drains, and the macroelement method enables efficient interpretation considering the three-dimensional drainage effect of vertical drains under two-dimensional plane strain condition. In this study, a novel finite element analysis program was developed by applying the macroelement method to the vacuum consolidation method used in ground improvement practice. The conventional macroelement method was used to calculate the amount of drainage from the vertical drain by setting the excess porewater pressure in the drainage material to zero; however, the program developed in this study was improved to consider negative excess porewater pressure as an actual vacuum consolidation condition. To verify the performance of the program, because of a comparison with the measurement values at the site where the vacuum consolidation method was applied, results predicted by the program and field measurement data showed similar settlement behavior.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.473-478
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• 2022

Evaluation learning based on code testing is becoming a popular solution in programming education via Online judge(OJ). In the recent past, many papers have been published on how to detect plagiarism through source code similarity analysis to support OJ. However, deep learning-based research to support automated tutoring is insufficient. In this paper, we propose Input & Output side FiLM models to predict whether the input code will pass or fail. By applying Feature-wise Linear Modulation(FiLM) technique to GRU, our model can learn combined information of Java byte codes and problem information that it tries to solve. On experimental design, a balanced sampling technique was applied to evenly distribute the data due to the occurrence of asymmetry in data collected by OJ. Among the proposed models, the Input Side FiLM model showed the highest performance of 73.63%. Based on result, it has been shown that students can check whether their codes will pass or fail before receiving the OJ evaluation which could provide basic feedback for improvements.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.97-103
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• 2023

Since most of the information is transmitted through the network, eavesdropping and interception by a third party may occur. Appropriate measures are required for effective, secure and confidential communication in the network. Steganography is a technology that prevents third parties from detecting that confidential information is hidden in other media. Due to structural vulnerabilities, information protected by encryption and steganography techniques can be easily exposed to illegitimate groups. In order to improve the limitations of LSB where the simplicity and predictability of the hiding method exist, I propose a technique to improve the security of the message to be hidden based on PRNG and recursive function. To enhance security and confusion, XOR operation was performed on the result of selecting a random bit from the upper bits of the selected channel and the information transformed by the RS-box. PSNR and SSIM were used to confirm the performance of the proposed method. Compared to the reference values, the SSIM and PSNR of the proposed method were 0.9999 and 51.366, respectively, confirming that they were appropriate for hiding information.