• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.1031-1034
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• 2005

침입탐지시스템과 같은 기존의 보안 시스템의 가장 큰 단점 중에 하나는 많은 경고로 인하여 정확한 공격 탐지 분석이 매우 힘들다는데 있다. 이는 관리자의 지식과 경험으로 극복될 수 있지만 관리자의 지식과 경험이 많다 할지라도 관리 네트워크의 범위가 클수록 경고 메시지 분석에 대한 어려움이 존재한다. 또한 관리자에게 보고하는 많은 경고 중에 정확하지 않은 경고가 다수 포함되어 있기 때문에 필요하지 않은 경고까지 분석해야하는 부담을 갖는다. 본 논문에서 제시하는 알고리즘은 보안 시스템의 경고와 취약성 분석 데이터의 상관관계를 분석하여 취약성이 존재하지 않는 공격에 대한 경고 메시지를 필터링한다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.12
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• pp.1333-1339
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• 2009

A MWR(Missile Warning Radar) of GVES(Ground Vehicle Equipment System) has to effectively decide the threat for a detected target. Linear Approximation Fitting(LAF) and Weighted Linear Approximation Fitting(WLAF) algorithm is proposed as algorithm for a threat decision method. The target is classified into a threat or non-threat using a boundary condition of the angular rate, and the boundary condition is determined using probability model simulation. This paper confirms the performance of proposed threat decision algorithm using measurement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.42-54
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• 2011

This study presented an algorithm to detect zigzag driving maneuver that is highly associated with vehicle crash occurrence. In general, the zigzag driving results from the driver's inattention including drowsy driving and driving while intoxicated. Therefore, the technology to detect such unsafe driving maneuver will provide us with a valuable opportunity to prevent crash in the road. The proposed detection algorithm used angular velocity data obtained from a gyro sensor. Performance evaluations of the algorithm presented promising results for the actual implementation in practice. The outcome of this study can be used as novel information contents under the ubiquitous transportation systems environment.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.59-70
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• 2009

This study presents a novel traffic information system which is capable of detecting unsafe traffic events leading to accident occurrence and providing warning information to drivers for safer driving. Unsafe traffic events are captured by a vehicle image processing-based detection system in real time. Surrogate safety measures (SSM) representing quantitative accident potentials were derived, and further utilized to develop a data processing algorithm and analysis techniques in the proposed system. This study also defined 'emergency warning area' and 'general warning area' for more effective provision of warning information. In addition, methodologies for determining thresholds to trigger warning information were presented. Technical issues and further studies to fully exploit the benefits of the proposed system were discussed. It is expected that the proposed system would be effective for better management of traffic flow to prevent traffic accidents on freeways.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.2069-2076
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• 2008

In this paper, we develop an electrostatic monitoring system which is composed of an electrostatic prediction system and a warning message transmission system. The electrostatic prediction system in a factory receives the value of electrostatic charge from the electrostatic sensor and predicts the next value by using past data and sends the value to the warning message transmission system through the bluetooth communication. The warning message transmission system gets a warning signal and transmits the warning message to the worker's cellphone through a commercial SMS web by a socket program running on Windows PC in a control room. We propose electrostatic forecasting algorithms based on LSR(least square regression) using weight factors in an electrostatic prediction system. Simulation results show that the algorithm with dynamically variable weight factors is best with 64.69V standard deviation and a warning message transmitted by the warning message transmission system is displayed on cellphone after about 5 seconds.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.88-98
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• 2006

VANET has several different characteristics from MANET such as high mobility of nodes and frequent change of node density and network topology. Due to these characteristics, the network topology based protocol, often used in MANET, can not be applied to VANET. In this paper, we propose an emergency warning message broadcast protocol using range based relay node selecting algorithm which determines the minimal waiting time spent by a given node before rebroadcasting the received warning message. Because the time is randomly calculated based on the distance between sender node and receiver node, a node chosen as a relay node is assured to have a minimal waiting time, even though it is not located at the border of radio transmission range. The proposed emergency warning message broadcast protocol has low network traffic because it does not need to exchange control messages for message broadcasting. In addition, it can reduce End-to-End delay under circumstances of low node density and short transmission range in VANET.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.9-16
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• 2017

An Algorithm for Lane Detection and Lane Departure Warning for a Vehicle Driving on Roads is proposed in This Paper. Using Images Obtained from On-board Cameras for Lane Detection has Some Difficulties, e.g. the Increase of Fault Detection Ratio Due to Symbols on Roads, Missing Yellow Lanes in the Tunnel due to a Similar Color Lighting, Missing Some Lanes in Rainy Days Due to Low Intensity of Illumination, and so on. The Proposed Algorithm has been developed Focusing on Solving These Problems. It also has an Additional Function to Determine How much the Vehicle is leaning to any Side between The Lanes and, If Necessary, to Give a Warning to a Driver. Experiments Using an Image Database Built by Collecting with Vehicle On-board Blackbox in Six Different Situations have been conducted for Validation of the Proposed Algorithm. The Experimental Results show a High Performance of the Proposed Algorithm with Overall 97% Detection Success Ratio.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1114-1117
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• 2017

본 연구에서는 소음 센서와 진동 센서를 사용하여 층간소음 정보를 받아 기준치를 초과하면 소음 제공자에게 경고를 할수 있는 소음관리 시스템을 제안하였다. 소음 정보를 입력 받아 경고를 하는 알고리즘을 처리하기 위해 아두이노 보드를 사용하였고, 여러 주소로부터 전송되는 다수의 센서들을 적은 전력으로 전송할 수 있도록 Wi-fi shield와 MQTT 앙상블 데이터 전송방식을 적용하였다. 전송된 정보들은 Firebase 플랫폼을 통해 사용자들이 쉽게 정보에 접근할 수 있도록 구성하였다. 또한 저장된 대용량의 데이터에 대한 체계적인 관리를 위해 R 프로그램을 이용하여 데이터의 특징을 분석하였다. 제안된 시스템의 기능 및 동작을 실험한 결과 정상적으로 동작함을 확인하였다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.5
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• pp.551-561
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• 2024

Underground utility tunnels are spaces densely packed with various infrastructure facilities, such as power, telecommunications, and water supply and drainage systems, making internal environment management crucial. An investigation into accident cases and on-site demands in these tunnels revealed that while fires and floods are the most common types of incidents, the demand for real-time condensation prevention and response is frequent according to on-site managers. Condensation occurs due to the difference in humidity and temperature between the inside and outside of the tunnel. Frequent or prolonged condensation can lead to metal pipe corrosion, electrical failures, and reduced equipment lifespan. Therefore, this study developed a control algorithm and monitoring system to prevent condensation in underground utility tunnels. The proposed control algorithm estimates the likelihood of condensation in real-time based on the measured temperature and humidity and suggests appropriate responses for each stage to the managers. Finally, a practical condensation prevention monitoring system was built based on the developed algorithm, verifying the feasibility and applicability of this technology in the field.

• Journal of Digital Policy
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• v.2 no.4
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• pp.33-39
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• 2023

With a continuous occurrence of right-turn traffic accidents at intersections, there is an increasing demand for measures to address these incidents. In response, a technology has been developed to detect the presence of pedestrians through object detection in CCTV footage at right-turn areas and display warning messages on the screen to alert drivers. The YOLO (You Only Look Once) model, a type of object detection model, was employed to assess the performance of object detection. An algorithm was also devised to address misidentification issues and generate warning messages when pedestrians are detected. The accuracy of recognizing pedestrians or objects and outputting warning messages was measured at approximately 82%, suggesting a potential contribution to preventing right-turn accidents