• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.195-195
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• 2020

이 연구는 기후변화 위험에 노출되어 있는 북한에 대한 잠재증발산량의 미래 변화를 전망하였다. 이를 위해 IPCC AR5의 RCP 기후변화 시나리오로부터 모의된 미래 기온자료를 APCC (APEC Climate Center) Integrated Modeling (AIMS)를 사용하여 25개 관측 지점에 대해서 상세화하여, McGuinness-Borne 방법으로 잠재증발산량을 추정하였다. 6개의 성능 지표와 TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution)로 27개 GCMs 간의 과거 기후 재현성을 비교하여, 관측 지점 규모에서 적정 GCM을 선정하였다. 마지막으로 각 지점에서 선정된 대표 시나리오(representative climate change scenarios, RCCS)로 북한 지역의 잠재증발산량의 미래 변화를 3개의 구간(F1: 2011-2040; F2: 2041-2070; F3: 2071-2100)에서 all CCS(climate change scenario)와 비교하고, 미래 변화를 정량적으로 제시하였다. 그 결과 공간 해상도가 더 높은 GCM이 RCCS로 선정되었으며, 미래로 갈수록 잠재증발산량이 증가하리라 전망되었다. 또한, 여름철 잠재증발산량의 모델 간 변동성은 미래 구간에 따라 점진적으로 증가되었고, 연 평균 증발산량은 과거 기후대비 1.4배(F1), 2.0배(F2) 및 2.6배(F3) 증가하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.110-110
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• 2022

2011~2019년 평균 강수량은 100년 전(1912~1920) 보다 861mm 증가(7.4%)하였으며, 2020년 서울, 부산, 대전 등 대도시 지역에서 침수로 인한 인명피해가 발생하는 등 기후변화로 인한 강우량, 집중호우의 발생 빈도와 강우강도 증가 및 지속적인 도시침수로 인한 인명·재산 피해를 지속적으로 발생하고 있다. 이와 같이 도시침수는 단기간 집중호우에 의해 발생하고 좁은 범위에 발생하지만 건물, 인구 등 밀집도가 높은 지역에 발생하여 피해가 크게 발생한다. 또한 우수관 개선, 배수 펌프장 등 구조적인 대책만으로는 한계가 있으며, 예 경보 등 비구조적인 대책과 합께 이루어져야 한다. 이에 본 연구에서는 과거침수피해이력자료와 강우자료를 이용하여 해당 행정동에 대해 침수발생 한계강우량을 추정하였으며, 침수피해이력이 없는 행정동에 대해서는 유역특성과 한계강우량과의 관계를 이용하여 한계강우량을 예측하는 모델을 개발하였다. 3,344개 행정동에 대해 한계강우량을 추정하였으며, 이를 활용하여 2021년 침수 예·경보에 시범적용하였다. 6월~9월 까지 운영한 결과를 대상으로 강우자료와 비교하여 정확성을 검토하고 오차가 10% 이상인 행정동에 대해서는 개선하고자 한다.

• Journal of the Korean Society of Radiology
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• v.82 no.1
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• pp.12-28
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• 2021

Mammography is the primary imaging modality for breast cancer detection; however, a high level of expertise is needed for its interpretation. To overcome this difficulty, artificial intelligence (AI) algorithms for breast cancer detection have recently been investigated. In this review, we describe the characteristics of AI algorithms compared to conventional computer-aided diagnosis software and share our thoughts on the best methods to develop and validate the algorithms. Additionally, several AI algorithms have introduced for triaging screening mammograms, breast density assessment, and prediction of breast cancer risk have been introduced. Finally, we emphasize the need for interest and guidance from radiologists regarding AI research in mammography, considering the possibility that AI will be introduced shortly into clinical practice.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.3
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• pp.25-36
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• 2000

The purpose of this research work is to propose an analytical method of tunnel design based on reasonable site data. Therefore the proposed design method consists of monitoring data and Modified In Situ Rock Model. Also the Rock Mass Rating for very poor quality rock is very difficult to estimate, the balances between the ratings may no longer gives a reliable basis for the rock mass strength. But in reality Rock Mass Rating is only the property which can be obtained from face mapping records of the exposed tunnel face during construction stage. Evaluation of rock parameters for the actual design prior to tunnel construction should be corrected during tunnelling process in particularly complex ground conditions. This study intends to investigate application of in-situ rock model to soft rock tunnelling (weathered rock) by face mapping results and site measurement data that are obtained at the costraction site of Seoul Subway Tunnel. For the preparation of more reliable ground parameters, the Rock Mass Rating values for the weathered rocks were modified and readjusted in accordance with the measurement data. The modified input parameters obtained by the proposed method are used for the prediction of the tunnel behavior at subsequent construction stages. The results of this study revealed that more reasonable feed back tunnel analysis can be possible as suggested. Ample measurement data would be able to confirm the new proposed technique in this research work.

• 재활복지
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• v.21 no.3
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• pp.129-146
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• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.21-29
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• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.81-90
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• 2009

The safety management of a road network comprises four basic inter-related components：identification of sites(black spot) requiring safety investigation, diagnosis of safety problems, selection of feasible treatments for potential treatment candidates, and prioritization of treatments given limited budgets(Persaud, 2001). Identification process of selecting black spot is very important for efficient investigation of sites. In this study, the accident prediction model for EB method was developed by using accident data and geometric conditions of black spots selected from four-leg signalized intersections in In-cheon City for three years (2004-2006). In addition, by comparing the rank nomination technique using EB method to that by using accident counts, we managed to show the problems which the existing method have and the necessity for developing rational prediction model. As a result, in terms of total number of accidents, both the counts predicted by existing non-linear regression model and that by EB method have high good of fitness, but EB method, considering both the accident counts by sites and total number of accident, has better good of fitness than non-linear poison model. According to the result of the comparison of ranks nominated for treatment between two methods, the rank for treatment of almost sites does not change but SeoHae intersection and a few other intersections have significant changes in their rank. This shows that, with the technique proposed in the study, the RTM problem caused by using real accident counts can be overcome.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.609-619
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• 2017

A Manufacturing Readiness Assessment (MRA) was adapted to prevent the probable ascending expense, poor quality, and delay from the development to production phase and assess the level of manufacturing readiness in 2012. Consequently, there are positive effects on improving the quality to identify the manufacturing risks during the production of military supplies and manage the issues in advance. On the other hand, because the appraisee is becoming accustomed to preparing for MRA checklists tailoring, it was found to intensify the MRA points more than before, which damages the goal of the MRA. This paper proposes the quantitative MRA methodology using MWV (Manufacturing Readiness Level 8 Weighted Value) to define and measure the HOM8, DOM8, ICOM8, and M8RA to reflect the history of MRA, the difficulties of MRA checklists, the intrinsic cruciallity and risk assessment of program, which can overcome the problems mentioned before. This paper shows the MWV of four weapon system programs to be carried out and an analysis of the proposed MRL 8 methodology.

• The Journal of Society for e-Business Studies
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• v.20 no.2
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• pp.167-174
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• 2015

Information security organization has normally been organized under the IT department. However, as the importance of information security has gradually increased, the way of information security organized for enterprise security management has become a noteworthy issue. The need for separation of Information security organization from IT department is growing, such as restriction on the concurrent positions in CIO and CISO. Nowadays there are many studies about Information security organization while relatively there has been minimal research regarding a departmentalization. For these reasons this study proposes a Information Security Departmentalization Model which is based on business risk and reliance on the IT for effectively organizing Information security organization, using Contingency theory. In addition, this study classified the position of Information security organization into Planning & Coordination, Internal Control, Management and IT and analyze the strengths and weaknesses of each case.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.3
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• pp.59-67
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• 1993

The variations of the natural frequencies and the peak response acceleration at the top of prestressed concrete reactor building due to random variability and/or model uncertainty of structural parameters are studied. The results may be used as essential input parameters in seismic probabilistic risk assessment or seismic margin assessment of the reactor building. The sensitivity test of each structural parameter is first performed to determine the most influential parameter upon the natural frequency of structure model. Then Monte Carlo simulation technique is applied to evaluate the effect of parameter variation on the natural frequencies and the peak response acceleration. The acceleration time history is obtained by direct integration scheme. As the study results, it is found that the fundamental natural frequency and the peak response acceleration at the top of the building are most strongly affected by Young's modulus among the structural parameters, in which the value of mean plus one standard deviation obtained by probabilistic approach deviates up to about (+)12% from the result of deterministic method. Considering the uncertainty of flexural rigidity, the structural responses vary in range of (-)4%~(+)14%.