• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.10a
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• pp.187-191
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• 1994

기계구조물내의 균열은 고하중상태에서 갑작스러운 파괴의 주요 원인의 하나로서 이러한 균열의 조기탐지를 위해 기존의 비파괴검사 방법 이외에, 최근 진동측정 및 진동분석을 이용하는 방법이 경제성 및 그 효용성으로 인하여 깊게 연구되고 있다. 이러한 진동특성의 변화를 이용하여 균열을 탐지하는 방법이 많은 학자들에 의해 연구되어졌으며, 현재까지의 연구결과중 균열의 크기 및 위치를 동시에 탐지할 수 있는 방법중에서 비교적 단순, 정확하다고 판단되는 방법으로는 임의의 두 지점에서의 진폭측정을 이용한 Rizos(1)의 방법과 고유진동수 및 모우드형 측정을 이용한 Kam & Lee(2)의 방법이 있으나 이들 방법은 두가지 이상의 진동특성치를 요구하고 있다. 본 연구의 목적은 진동특성치중 고유진동수만을 이용하여 단순부재에서 균열의 크기 및 위치를 수치적으로 예측할 수 있는 새로운 해석기법을 제시하고, 기존 방법 사용시의 결과와 비교 검토하여 그 유용성을 판단하는데 있다.

• Proceedings of the Korea Society for Simulation Conference
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• 2002.11a
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• pp.17-21
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• 2002

네트워크 보안의 중요성과 필요성이 증대됨에 따라 많은 조직들이 다양한 보안 시 스템을 네트워크에 적용하고 있다. 침입 차단 시스템, 침입 탐지 시스템, 취약점 스캐너와 같은 보안 시스템들이 취약성 정보를 공유하게 되면 일관된 통합 보안 환경을 구축할 수 있다. 본 연구진은 통합 보안 시뮬레이션 환경의 구축을 위해 여러 보안 시스템 모델들이 사용할 수 있는 취약성 정보들을 집약시킴으로써 보안 시스템간의 정보 공유를 쉽게 할 수 있는 SVDB (Simulation based Vulnerability Data Base)를 구축하였다. 네트워크의 한 구성요소인 SVDB는 보안 시스템 모델의 구성에 필요한 다양한 정보를 담고 있어 한 호스트나 네트워크가 갖는 취약성을 조기에 발견할 수 있다. 또한 SVDB는 침입 탐지 시스템과 같은 보안 시스템이 존재하는 네트워크를 시뮬레이션 하는데 필요한 보안 정보를 제공한다. 보안시스템을 위한 시뮬레이션 모델은 DEVS (Discrete EVent system Specification) 방법론을 사용하여 구성하였다. 또한 이렇게 구축된 시뮬레이션 모델들이 SVDB와 연동하기 위한 인터페이스 모듈을 구현하였다. 취약성 스캐너, 침입 탐지 시스템, 침임 차단 시스템이 정보를 공유함으로써 공격에 효과적인 대응하는 것을 시뮬레이션을 통해 보인다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.313-320
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• 2015

While various phishing attacks are getting to be increased in constant, their response methods still stay on the stage of responding after identifying an attack. To detect a phishing site ahead of an attack, a method has been suggested with utilizing the Referer header field of HTTP. However, it has a limitation to implement a traffic gathering system for each of prospective target hosts. This paper presents a unknown phishing site detection method in the Interior network environment. Whenever a user try to connect a phishing site, its traffic is pre-processed with considering of the characteristics of HTTP protocol and phishing site. The phishing site detection phase detects a suspicious site under phishing with analysing HTTP content. To validate the proposed method, some evaluations were conducted with 100 phishing URLs along with 100 normal URLs. The experimental results show that our method achieves higher phishing site detection rate than that of existing detection methods, as 66% detection rate for the phishing URLs, and 0% false negative rate for the normal URLs.

• Journal of Ocean Engineering and Technology
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• v.33 no.6
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• pp.607-614
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• 2019

It has been an issue among researchers that the tsunamis that occurred on the west coast of Japan in 1983 and 1993 damaged the coastal cities on the east coast of Korea. In order to predict and reduce the damage to the Korean Peninsula effectively, it is necessary to install offshore tsunami observation instruments as part of the system for the early detection of tsunamis. The purpose of this study is to recommend the optimal deployment of tsunami observation instruments in terms of the higher probability of tsunami detection with the minimum equipment and the maximum evacuation and warning time according to the current situation in Korea. In order to propose the optimal location of the tsunami observation equipment, this study will analyze the tsunami propagation phenomena on the east sea by considering the potential tsunami scenario on the west coast of Japan through numerical modeling using the COrnell Multi-grid COupled Tsunami (COMCOT) model. Based on the results of the numerical model, this study suggested the optimal deployment of Korea's offshore tsunami observation instruments on the northeast side of Ulleung Island.

• Journal of Internet Computing and Services
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• v.8 no.1
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• pp.125-132
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• 2007

This paper presents an approach to detect premature ventricular contractions(PVC) using the neural network with weighted fuzzy membership functions(NEWFM), NEWFM classifies normal and PVC beats by the trained weighted fuzzy membership functions using wavelet transformed coefficients extracted from the MIT-BIH PVC database. The eight most important coefficients of d3 and d4 are selected by the non-overlap area distribution measurement method. The selected 8 coefficients are used for 3 data sets showing reliable accuracy rates 99,80%, 99,21%, and 98.78%, respectively, which means the selected input features are less dependent to the data sets. The ECG signal segments and fuzzy membership functions of the 8 coefficients enable input features to interpret explicitly.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1573-1579
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• 2022

The irrigation schedule system using early detection of crop water stress is required to maintain crop production and save water resource. However, because previous studies focused on the crop under stress dominant condition, the crop physiological properties, which can be measured by remote sensing technique, on early crop water stress condition are not well known. In this study, the canopy temperature, MERIS Terrestrial Chlorophyll Index (MTCI), and Chlorophyll/Carotenoid Index (CCI) are observed on the soybeans given the early water stress using thermal imaging camera and hyperspectral camera. The increased canopy temperature and decreased MTCI are consist with the previous studies which are for the crop of stress dominant-sign. However, the CCI was increased contrary to expectation because it may faster the reduction of carotenoid than chlorophyll in early stage. These behaviors will be useful to not only develop the irrigation system but also using the early detection of crop stress.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.126-132
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• 2022

At present, due to the rapid spread of smartphones and activation of IoT, malicious codes are disseminated using SNS, or intelligent intrusions such as intelligent APT and ransomware are in progress. The damage caused by the intelligent intrusion is also becoming more consequential, threatening, and emergent than the previous intrusion. Therefore, in this paper, we propose an intelligent intrusion situation-aware reasoning system to detect transgression behavior made by such intelligent malicious code. The proposed system was used to detect and respond to various intelligent intrusions at an early stage. The anticipated system is composed of an event monitor, event manager, situation manager, response manager, and database, and through close interaction between each component, it identifies the previously recognized intrusive behavior and learns about the new invasive activities. It was detected through the function to improve the performance of the inference device. In addition, it was found that the proposed system detects and responds to intelligent intrusions through the state of detecting ransomware, which is an intelligent intrusion type.

• Smart Media Journal
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• v.13 no.4
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• pp.48-56
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• 2024

In the livestock industry, detecting environmental outliers and predicting data are crucial tasks. Outliers in livestock environment data, typically gathered through time-series methods, can signal rapid changes in the environment and potential unexpected epidemics. Prompt detection and response to these outliers are essential to minimize stress in livestock and reduce economic losses for farmers by early detection of epidemic conditions. This study employs two methods to experiment and compare performances in setting thresholds that define outliers in livestock environment data outlier detection. The first method is an outlier detection using Mean Squared Error (MSE), and the second is an outlier detection using a Dynamic Threshold, which analyzes variability against the average value of previous data to identify outliers. The MSE-based method demonstrated a 94.98% accuracy rate, while the Dynamic Threshold method, which uses standard deviation, showed superior performance with 99.66% accuracy.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.3
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• pp.181-187
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• 2016

A thermal power plant has a heat exchanger tube to collect and convert the heat generated from the high temperature and pressure steam to energy, but the tubes are arranged in a complex manner. In the event that a leakage occurs in any of these tubes, the high-pressure steam leaks out and may cause the neighboring tubes to rupture. This leakage can finally stop power generation, and hence there is a dire need to establish a suitable technology capable of detecting tube leaks at an early stage even before it occurs. As shown in this paper, by applying acoustic emission (AE) technology in existing boiler tube leak detection equipment (BTLD), we developed a system that detects these leakages early enough and generates an alarm at an early stage to necessitate action; the developed system works better that the existing system used to detect fine leakages. We verified the usability of the system in a 560MW-class thermal power plant boiler by conducting leak tests by simulating leakages from a variety of hole sizes (ⵁ2, ⵁ5, ⵁ10 mm). Results show that while the existing fine leakage detection system does not detect fine leakages of ⵁ2 mm and ⵁ5 mm, the newly developed system could detect leakages early enough and generate an alarm at an early stage, and it is possible to increase the signal to more than 18 dB.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.45-52
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• 2016

Blast furnaces are crucial equipment for steel production. A typical furnace risks unexpected accidents caused by contraction and expansion of the walls under an environment of high temperature and pressure. In this study, an acoustic emission (AE) monitoring system was tested for evaluating the large-scale structural health of a blast furnace. Based on the growth of shell cracks with the emission of high energy levels, severe damage can be detected by monitoring increases in the AE energy parameter. Using this monitoring system, steel mill operators can establish a maintenance period, in which actual shell cracks can be verified by cross-checking the UT. From this study, we expect that AE systems permit early fault detection for structural health monitoring by establishing evaluation criteria based on the severity of shell cracking.