• Tunnel and Underground Space
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• v.33 no.6
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• pp.561-573
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• 2023

Korea Atomic Energy Research Institute (KAERI) constructed the KURT (KAERI Underground Research Tunnel) to analyze the hydrogeological/geochemical characteristics of deep rock mass. Numerous boreholes have been drilled to conduct various field tests. The selection of suitable investigation intervals within a borehole is of great importance. When objectives are centered around hydraulic flow and groundwater sampling, intervals with sufficient groundwater flow are the most suitable. This study defines such points as hydraulic outliers and aimed to detect them using borehole geophysical logging data (temperature and EC) from a 1 km depth borehole. For systematic and efficient outlier detection, machine learning algorithms, such as DBSCAN, OCSVM, kNN, and isolation forest, were applied and their applicability was assessed. Following data preprocessing and algorithm optimization, the four algorithms detected 55, 12, 52, and 68 outliers, respectively. Though this study confirms applicability of the machine learning algorithms, it is suggested that further verification and supplements are desirable since the input data were relatively limited.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.389-398
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• 2019

In this paper, we propose a method to detect small unmanned aerial vehicles(UAVs) flying in a real-world environment. Small UAV signals are frequently obscured by clutter signals because UAVs usually fly at low altitudes over urban or mountainous terrain. Therefore, to obtain a desirable detection performance, clutter signals must be considered in addition to noise, and thus, a performance analysis of each clutter removal technique is required. The proposed detection process uses clutter removal and pulse integration methods to suppress clutter and noise signals, and then detects small UAVs by utilizing a constant false alarm rate detector. After applying three clutter removal techniques, we analyzed the performance of each technique in detecting small UAVs. Based on experimental data acquired in a real-world outdoor environment, we found it was possible to derive a clutter removal method suitable for the detection of small UAVs.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1069-1080
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• 2016

TDOA(Time Difference Of Arrival)-based localization system such as the passive surveillance system performs the time synchronization between the receivers after separated installing multiple receivers to set the same clock for all receivers. And it estimates 2D(or 3D) location of the target by solving intersection of the multiple hyperbola(or hyperboloid) using TDOA. To perform time synchronization, one receiver must be set to the master, and it provide the reference data to compensate the clock of the rest of the slaves. The positioning accuracy of TDOA-based localization system is changed in accordance with the master that is selected among multiple receivers. So, the optimum receiver which is selected among multiple receivers must be set to master to get best performance in the considered deployment of receivers. In this paper, we propose a selection scheme of master receiver for time synchronization using DOP(Dilution Of Precision) which is based on location of the target and the multiple receivers. The proposed scheme has low complexity and short processing time, and it is easy to automate in the TDOA-based localization systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2171-2180
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• 2011

Security is a significant concern for many sensor network applications. Intrusion detection is one method of defending against attacks. However, standard intrusion detection techniques are not suitable for sensor networks with limited resources. In this paper, propose a new method for selecting and managing the detect nodes in IDS(intrusion detection system) for anomaly detection in sensor networks and the node scheduling technique for maximizing the IDS's lifetime. Using the genetic algorithm, developed the solutions for suggested optimization equation and verify the effectiveness of proposed methods by simulations.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.225-226
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• 2021

드론산업과 센서의 발전에 따라 드론이 수행할 수 있는 능력이 넓어지고 있다. 본 논문에서는 드론에 장착되는 장비 중 카메라에 객체 탐지 기능을 넣어 퇴치할 대상을 인지하고 인식할 수 있음을 검증하고자한다. 이는 여러 산업에 새로운 패러다임을 제안하게 될 수 있는 방법이 될 것 이라 기대된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.302-307
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• 2017

Draft ice in polar regions is formed due to sea level changes and various environmental factors cause damage due to collision with offshore plants and ships for resource development. Drift ice in polar regions is a potential source of accidents for offshore plants that perform long-term operations in one place, as well as on the ship. To prevent accidents with drift ice, offshore plants and ships in polar regions use satellite image information and detection radar to detect drift ice. However, the inability to use visible satellite images at night significantly lowers the detection probability by radar for small drift ice. In this study, we used a thermal imaging system which can be operated day and night for the detection of drift ice, and carried out an experimental study on the detection characteristics of drift ice. To examine the night operation of the thermal imaging system, the experimental condition was set and the thermal image was measured according to the measurement angle change. Under this condition, the correlation was analyzed by theoretical calculating the radiant energy of the drift ice and the sea water.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.5
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• pp.786-795
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• 1999

To detect the precise of arrival of target signal in real ocean environments, Inverse beamformnig(IBF) solutions to the Inverse beamforming integral equation are surveyed theoretically and the performance properties of the IBF are analyzed with simulations. IBF-Cardioid beamforming algorithm is proposed for port/starboard discrimination and the performance gains are studied with simulations. It is shown that IBF has a 3 dB array noise gain advantage over CBF under ideal conditions. This 3 dB array noise gain advantage is proven by theocratical studies and simulations. This array noise gain advantage leads to a minimum detectable level advantage for IBF output compared with CBF output. The fact that the IBF beamwidth is narrower than the CBF beamwidth by a factor of 0.68 proves the performance of detection and spatial resolution improvement. Comparing the simulation results of IBF-Cardioid beamforming and Conventional Cardioid beamforming, it is shown that IBF-Cardioid beamformer have performance enhancement in minimum detection level, detection accuracy and resolution.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.616-618
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• 2002

최근 몇 년 동안 이루어진 네트웍 및 인터넷 시장의 발전과 더불어 빈번히 발생하는 시스템에 대한 침입으로 이를 방어하기 위한 여러 도구들이 개발되어왔다. 이러한 도구들 중 침입탐지시스템은 시스템 방어에 핵심적인 역할을 하는데, 현재까지 이를 평가하기 위한 자동화된 온라인 평가도구는 없는 실정이다. 보안관련 시장이 발달한 미국에서는 DARPA의 지원아래 관련된 연구가 진행되어 1998년부터 2000년까지 대규모의 침입탐지시스템 평가가 이루어졌으나, 이때의 평가들은 당시의 침입 수준만을 고려한 것으로 새로운 침입 환경에 대한 확장은 용이하지 않기 때문에, 급속도로 증가하는 침입 기술에 대응하기 위한 새로운 방법이 필요하다. 본 논문에서는 기존 침입코드를 이용하여 새로운 침입을 만들어 내어 침입탐지 평가도구에 적용할 수 있는 모듈 위치변환과 더미코드 삽입을 제안한다. 모듈 위치변환은 알려진 u2r코드를 모듈 단위로 나누고 나뉘어진 모듈의 위치 변환을 통해 새로운 침입을 만들어낸다. 또한 더미코드 삽입은 침입코드의 모듈 사이에 침입과 관련 없이 수행되는 정상 모듈을 삽입하여 새로운 침입을 만든다. 모듈 위치변환을 통해 평균 6.1%의 침입 변환율과 더미코드 삽입을 통해 새로운 침입을 만들었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.502-505
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• 2014

최근 들어, 모바일 기기의 시스템을 장악하여 중요 정보를 빼내는 등의 악성 행위를 위해 Code Reuse Attack (CRA) 이 널리 사용되고 있다. 이러한 CRA 를 막기 위한 방법으로 branch 의 trace 를 분석하여 CRA 고유의 특성을 찾아내는 Signature 기반 탐지 기술이 있다. 이러한 탐지 기술을 효율적으로 지원하기 위하여, 본 논문에서는 ARM 프로세서용 바이너리를 분석하여, signature 분석을 위해 필수적으로 분석되어야 하는 gadget 의 크기를 빠르게 접근할 수 있는 meta-data 를 생성하는 기술을 제안한다. 이러한 meta-data 를 활용하는 방식은 gadget 의 크기를 계산하는 추가적인 코드의 수행을 제거해 주므로, 더욱 효율적으로 CRA 를 탐지할 수 있도록 도와준다. 실험 결과, 이러한 meta-data 는 본래의 바이너리 코드 대비 9% 만의 크기 증가를 일으키는 것으로 나타났다.