• Journal of Energy Engineering
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• v.28 no.3
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• pp.10-17
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• 2019

According to South Korea's policy of supplying eco-friendly hydrogen vehicles, related industries are actively conducting research on the development of hydrogen cars and hydrogen charging station infrastructure. On the other hand, there is a lack of empirical research and assessment of the risk of non-metallic materials (such as liners, seals, gaskets) for classified materials that directly affect the durability and reliability of hydrogen vehicles and hydrogen charging stations. In this study, the risk factors for liners and seals of non-metallic parts used in high-pressure hydrogen installations were derived using FMEA, and the RPN values were calculated by converting the severity, frequency of occurrence and degree of detection into scores. The maximum value of the RPN 600, minimum value 63, average value 278.5 was calculated and periodic control of the liner and seal was identified as important. In addition, through hydrogen soakage and oxygen aging tests for non-metallic rubber products, physical test values that can be used as basic data were presented.

• Journal of Aerospace System Engineering
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• v.14 no.3
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• pp.24-31
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• 2020

A study on the H2O2 based low toxic hypergolic propellant was conducted. The fuel candidates were chosen as a mixture of Amine solvent and reactive additive. The analytical performance was calculated via the NASA CEA code and 96% Isp of the NTO/UDMH was confirmed. The ignition delay measurement with drop test was performed and all candidates showed less than 10 ms in the best performance cases. Based on these results, the feasibility of high response H2O2 based low toxic hypergolic propellant was confirmed.

• Applied Chemistry for Engineering
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• v.30 no.4
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• pp.487-492
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• 2019

Nano flexible vesicles encapsulating an adenosine, an active ingredient for anti-wrinkle, were prepared for the transdermal delivery. The nano flexible vesicle is usually composed of phospholipid, ethanol, and lysolecithin, which is a type of liquid crystalline one made by dispersing the liquid crystalline phase formed through a hydration process into a water phase. In this study, the Taguchi method, one of the experimental design methods, was applied to investigate the factors affecting the vesicle droplet size. Signal to noise (S/N) ratios for the smaller the better characteristics of vesicle droplet size were calculated using the Taguchi orthogonal array. The composition of ethanol and lysolecithin in the vesicle constituents and the amount of aqueous solution added in the hydration process were main factors that had a great effect on the vesicle droplet size and ANOVA test showed that these factors were significant at 95% confidence level.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.541-541
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• 2015

댐 물수지 분석에 있어 매우 중요한 요소는 강수량, 유입 방류량, 토양수분량, 증발산량 등이 있다. 현재 육지에서의 증발산량은 대부분 에디공분산시스템에 의해 관측되고 있으며, 많은 전문가들이 양질의 자료를 산출하고 있다. 하지만 수면에서의 증발량관측은 아직 부족한 상황이다. 우리나라는 기후특성상 여름철에 강우가 집중됨에 따라 효율적인 댐 관리가 매우 중요하다. 댐관리의 주요 인자인 수면증발량은 현재 용담댐에서만 이루어지고 있다. 용담댐의 수면증발량 관측은 2013년부터 수행되고 있고, 수면위에 플랫폼을 설치하고 팬 내부에 수심이 1 m인 대형증발팬을 고정하는 방식을 취하고 있으며, 관측된 수위자료는 호내 수온을 고려하여 수면증발량으로 환산된다. 관측항목으로는 팬 내 외부 및 저수지 표층 수온, 팬 내부 정밀 수위뿐만 아니라 다양한 기상요소들이 있다. 2013년에 생산한 수면증발량은 풍향풍속, 수온, 상대습도, 복사량, 강수량 자료를 통해 정확도를 검증하였으며, Penman(1984)공식을 활용하여 실측 수면증발량과 추정 수면증발량을 비교 분석하였다. 본 연구는 용담호에서 자동 관측되고 있는 수위변동 자료를 활용해 수면에서의 증발량을 분석하였다. 2014년 3월부터 2015년 2월까지의 자료를 활용하였으며, 관측기간 중 최대 일증발량은 9.7 mm/day, 월 최대 일평균증발량은 3.5 mm/month(10월)로 나타났다. 수면에서 가장 많은 증발량이 나타난 시기는 10월 (증발량 : 107.6 mm, 강수량 : 122.9 mm)로 강수량의 약 88 %가 증발되었음을 알 수 있었다. 그 다음으로는 9월과 5월 순이었다. 증발량이 가장 많다고 예상되었던 7월과 8월의 경우는 각각 18일과 21일간 강수가 발생하였으므로 대기 중의 높은 습도로 인해 증발량이 크지 않았다. 결론적으로 수면에서의 증발량이 기상환경에 의존하고 있다는 사실은 명백하다. 그러므로 효율적인 수자원관리를 위해서는 다양한 지점에서의 수면증발 관측 및 기상요소와의 상관 성분석이 시급하다고 판단된다.

• Convergence Security Journal
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• v.20 no.4
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• pp.81-90
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• 2020

In the real world, new types of attacks or variants are constantly emerging, but attack traffic classification models developed through artificial neural networks and supervised learning do not properly detect new types of attacks that have not been trained. Most of the previous studies overlooked this problem and focused only on improving the structure of their artificial neural networks. As a result, a number of new attacks were frequently classified as normal traffic, and attack traffic classification performance was severly degraded. On the other hand, the softmax function, which outputs the probability that each class is correctly classified in the multi-class classification as a result, also has a significant impact on the classification performance because it fails to calculate the softmax score properly for a new type of attack traffic that has not been trained. In this paper, based on this characteristic of softmax function, we propose an efficient method to improve the classification performance against new types of attacks by classifying traffic with a probability below a certain level as attacks, and demonstrate the efficiency of our approach through experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.422-429
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• 2022

In this paper, the intermediate frequency transmission signal level between the network system-based baseband and RF unit consisting of multi-channel airborne relay devices and a lot of mission devices, which are currently undergoing technology development tasks, is kept constant at the reference signal level. Considering the other party's receiving input range, despite changes in the short-range long-range wireless communication environment, it presents a multi-link protection and MLP-A algorithm that allows signals to be transmitted stably and reliably through signal detection automatic gain control, and experiments and analysis considering short-distance and long-distance wireless environments were performed by designing, manufacturing, and implementing RF units to which MLP-A algorithms were applied, and applying distance calculation equations to the configuration of multiple air movements and verification networks. Through this, it was confirmed that a stable and reliable RF communication system can be operated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1193-1204
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• 2021

In information security, AI technology is used to detect unknown malware. Although AI technology guarantees high accuracy, it inevitably entails false positives, so we are considering introducing XAI to interpret the results predicted by AI. However, XAI evaluation studies that evaluate or verify the interpretation only provide simple interpretation results are lacking. XAI evaluation is essential to ensure safety which technique is more accurate. In this paper, we interpret AI results as features that have significantly contributed to AI prediction in the field of malware, and present an evaluation method for the interpretation of AI results. Interpretation of results is performed using two XAI techniques on a tree-based AI model with an accuracy of about 94%, and interpretation of AI results is evaluated by analyzing descriptive accuracy and sparsity. As a result of the experiment, it was confirmed that the AI result interpretation was properly calculated. In the future, it is expected that the adoption and utilization of XAI will gradually increase due to XAI evaluation, and the reliability and transparency of AI will be greatly improved.

• Journal of the Korean Applied Science and Technology
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• v.39 no.5
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• pp.623-631
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• 2022

Using the design of experiment (DOE), factors affecting the particle size of hydrated liquid crystalline vesicles containing a high content of ceramide were analyzed and the mixture composition was optimized. Manufacturing temperature, amount of ethanol, and ultrasonic time were selected as the main variables affecting the droplet size of the vesicles, and the effect of these variables on the droplet size was examined through the signal to noise (S/N) ratios of Taguchi method and ANOVA analysis. In addition, mixture composition experiments of three lipid components constituting the vesicle membrane, hydrogenated phosphatidyl choline (HPC), cholesterol (Chol), and ceramide (Cer), were performed according to the simplex central design matrix of the mixture. Regression analysis was conducted with the experimental data to obtain a model equation, and the optimal mixing composition of the three lipid components to minimize the vesicle droplet size was determined as HPC (0.6), Chol (0.1), and Cer (0.3).

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.448-448
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• 2023

도심 속 하천과 그 주변 지역(이하 수변)은 물과 자연환경이 주는 정서적 안정감과 쾌적함, 그리고 건강성을 대표하는 공간으로 도심 속 쉼터이자 힐링의 장소이다. 최근 수변이 도시경관의 질향상, 휴식 및 여가 공간 제공의 기능뿐만 아니라 열섬효과 완화 등 기후변화 대응에 효과가 있다는 사실도 재조명되면서, 수변이 도시의 발전과 활성화를 이끌어낼 새로운 동력이자 대안으로 급부상하고 있다. 본 연구에서는 서울의 4대 권역하천인 중랑천, 탄천, 안양천, 홍제천을 대상으로 하천과 하천 주변 500m 이내 구역을 하천공간과 수변공간으로 구분하고, 그 현황과 특성을 분석하였다. 하천(제방)으로부터 50m 이내 수변공간에 위치한 도로면적의 비율은 탄천이 40%로 가장 높았으며, 그 외에도 중랑천은 31%, 홍제천과 안양천은 28%로 하천변 도로면적비가 매우 높은 것으로 분석되었다. 특히, 중랑천은 하천공간 내 도로면적이 하천변 50m 이내에 위치한 도로의 면적과 비슷한 수준으로 나타났다.안양천, 중랑천, 탄천 대부분의 구간에서는 친수활동을 하기엔 다소 수심이 낮고(0.3m 이하) 유속이 느린 것(0.3m/s 이하)으로 분석되었고, 수질은 대부분의 구간에서 대장균 군수가 기준치를 수십에서 수백 배 초과하고 있어, 최상류 일부 구간을 제외한 전 구간에서 수영·물놀이 등 수상활동이 부적합한 것으로 분석되었다. 서울시민들은 주로 금요일과 토요일, 오후 12시에서 18시 사이에 하천을 가장 많이 방문하며 평균 2시간 정도를 머물렀으며, 대부분 걷기와 산책 활동을 하는 것으로 조사되었다. 도보, 대중교통 등 교통수단에 따른 하천진출입로 인근평균인구 대비 접근 가능 인구비율을 산출하여 접근성을 분석한 결과, 중랑천과 홍제천에서는 수변지역 내 평균인구의 20~30%가 도보 및 대중교통으로 20~30분 이내에 도달 가능한 것으로 분석되어 접근성이 가장 우수하였고, 안양천은 수변지역 내 평균인구의 15~20%가 30분 이내 도달가능하였으며, 탄천은 수변지역 내 평균인구의 10%미만이 30분 내에 도달가능한 것으로 분석되어 탄천의 접근성이 가장 열악한 것으로 나타났다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.411-425
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• 2023

Today, AI (Artificial Intelligence) technology is widely used in various fields, performing classification and regression tasks according to the purpose of use, and research is also actively progressing. Especially in the field of security, unexpected threats need to be detected, and unsupervised learning-based anomaly detection techniques that can detect threats without adding known threat information to the model training process are promising methods. However, most of the preceding studies that provide interpretability for AI judgments are designed for supervised learning, so it is difficult to apply them to unsupervised learning models with fundamentally different learning methods. In addition, previously researched vision-centered AI mechanism interpretation studies are not suitable for application to the security field that is not expressed in images. Therefore, In this paper, we use a technique that provides interpretability for detected anomalies by searching for and comparing optimization references, which are the source of intrusion attacks. In this paper, based on reference, we propose additional logic to search for data closest to real data. Based on real data, it aims to provide a more intuitive interpretation of anomalies and to promote effective use of an anomaly detection model in the security field.