• Title/Summary/Keyword: Disaster Detection

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A Study on Fire Flame Detection Performance in the Images of Various Color Spaces (다양한 컬러 공간에 따른 영상 내 화염 검출 성능 연구)

  • Choi, Byung-Soo;Kim, Jeong-Dae;Do, Yong-Tae
    • Proceedings of the Korea Multimedia Society Conference
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    • 2012.05a
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    • pp.284-286
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    • 2012
  • There has been increasing attention about the prevention and counter-measure of disasters. Particularly, for the case of fire disaster, early detection reduces the damage caused by fire significantly and effective detection method is important. Since most existing detectors need to be located at a close distance to fire, analyzing camera images to find fire becomes active research topic. In this paper, we analyze the color characteristics of fire images in various color spaces and report the experimental detection results. The best result is 77.8% success rate in YIQ space.

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Damage Detection of Ship Structures Using Wavelet Transformation (웨이블렛 변환 기법을 이용한 선체 구조의 결함진단)

  • Lee, Dae-Sung;Cho, Dae-Seung
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2000.11a
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    • pp.815-820
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    • 2000
  • The early damage detection of large structures is very important to prevent the disaster due to its global failure. In this paper, a damage detection method of the beam-analogy structure based on the wavelet transformation of mode shape is presented. This can effectively detect the singularity of mode shape caused to the inconsistency of bending moment and shear force at the damaged part using the discrete wavelet and its inverse transforms. To investigate the validity and the applicability of the presented damage detection method, numerical simulation and experiment are carried out for the idealized beam and the real ship structures.

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A Hybrid PSO-BPSO Based Kernel Extreme Learning Machine Model for Intrusion Detection

  • Shen, Yanping;Zheng, Kangfeng;Wu, Chunhua
    • Journal of Information Processing Systems
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    • v.18 no.1
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    • pp.146-158
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    • 2022
  • With the success of the digital economy and the rapid development of its technology, network security has received increasing attention. Intrusion detection technology has always been a focus and hotspot of research. A hybrid model that combines particle swarm optimization (PSO) and kernel extreme learning machine (KELM) is presented in this work. Continuous-valued PSO and binary PSO (BPSO) are adopted together to determine the parameter combination and the feature subset. A fitness function based on the detection rate and the number of selected features is proposed. The results show that the method can simultaneously determine the parameter values and select features. Furthermore, competitive or better accuracy can be obtained using approximately one quarter of the raw input features. Experiments proved that our method is slightly better than the genetic algorithm-based KELM model.

A Design of Disaster Prevention System and Detection of Wave Overtopping Number for Storm Surge base on CCTV (CCTV를 활용한 폭풍 해일의 월파 횟수 탐지 및 방재 시스템 설계)

  • Choi, Eun-Hye;Kim, Chang-Soo
    • Journal of Korea Multimedia Society
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    • v.15 no.2
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    • pp.258-265
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    • 2012
  • Our country is suffering from many human victims and property damages caused to occur great and small tidal waves in southern areas every year. Even though there were progressing many researches for storm surges, it was required more researches for detection of tidal wave and prevention system of its which can be applied in practical living fields. In this paper, we propose the disaster prevention system that can approximately detect a dangerousness of coast flooding and number of overtopping per time based on images of CCTV considering actual field application. And if it is detected a hazard of flooding of coast, the proposed detection system for tidal wave based GIS is quickly informed the areas of flooding to manager. The analyzing results of CCTV image of this proposed are derived from difference images between photos of fine day and photos or videos which are taken for the typhoon which is called "DIANMU" at our laboratory.

Detection Scheme of Heart and Respiration Signals for a Driver of Car with a Doppler Radar (도플러 레이더 기반 차량 운전자의 심박 및 호흡 신호 검출 기법 연구)

  • Yun, Younguk;Lee, Jeongpyo;Kim, Jinmyung;Kim, Youngok
    • Journal of the Society of Disaster Information
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    • v.16 no.1
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    • pp.87-95
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    • 2020
  • Purpose: In this paper, we propose an algorithm for detecting respiratory rate and heart beat of a driver of car by exploiting Doppler radar, and verifying the feasibility of the study through experiments. Method: In this paper, we propose a weighted peak detection technique using peak frequency values. The tests are performed in stop-state and driving-state, and the experiment result is analyzed by two proposed algorithms. Result: The results showed more than 95% and 96% accuracy of respiratory and heart rate, respectively. It also showed more than 72% and 84% accuracy of those even for driving experiments. Conclusion: The proposed detection scheme for vital signs can be used for the safety of the driver as well as for prevention of a large size of car accidents.

False Alarm Filtering Algorithm Development of Pipeline Leak Detection System using Flow Volume Balance (유량 밸런스 특성을 활용한 송유관 누유 감지 시스템의 오알람 필터링 알고리즘 개발)

  • Kim, Min-Sung;Kim, Hie-Sik;Jung, Hae-Kyun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.10
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    • pp.95-102
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    • 2016
  • Pipeline is making the most use of transportation of petroleum products on the land. But due to tremendous accident or environmental disaster by oil pipeline leak or pipeline stolen, leak detection systems have been used for preventing it. Leak detection method based on negative pressure wave has been used at the long distance pipeline. But even if it has showed good leak detection quality, due to making a lot of false alarm, it has weak point that disturbs concentration to system. This study suggests algorithm and method of using volume balance to decrease false-alarm of pipeline leak detection system based on negative pressure wave.

Application of Multiple Threshold Values for Accuracy Improvement of an Automated Binary Change Detection Model

  • Yu, Byeong-Hyeok;Chi, Kwang-Hoon
    • Korean Journal of Remote Sensing
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    • v.25 no.3
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    • pp.271-285
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    • 2009
  • Multi-temporal satellite imagery can be changed into a transform image that emphasizes the changed area only through the application of various change detection techniques. From the transform image, an automated change detection model calculates the optimal threshold value for classifying the changed and unchanged areas. However, the model can cause undesirable results when the histogram of the transform image is unbalanced. This is because the model uses a single threshold value in which the sign is either positive or negative and its value is constant (e.g. -1, 1), regardless of the imbalance between changed pixels. This paper proposes an advanced method that can improve accuracy by applying separate threshold values according to the increased or decreased range of the changed pixels. It applies multiple threshold values based on the cumulative producer's and user's accuracies in the automated binary change detection model, and the analyst can automatically extract more accurate optimal threshold values. Multi-temporal IKONOS satellite imagery for the Daejeon area was used to test the proposed method. A total of 16 transformation results were applied to the two study sites, and optimal threshold values were determined using accuracy assessment curves. The experiment showed that the accuracy of most transform images is improved by applying multiple threshold values. The proposed method is expected to be used in various study fields, such as detection of illegal urban building, detection of the damaged area in a disaster, etc.

A Study on Water Surface Detection Algorithm using Sentinel-1 Satellite Imagery (Sentinel-1 위성영상을 이용한 수표면 면적 추정 알고리즘에 관한 연구)

  • Lee, Dalgeun;Cheon, Eun Ji;Yun, Hyewon;Lee, Mi Hee
    • Korean Journal of Remote Sensing
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    • v.35 no.5_2
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    • pp.809-818
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    • 2019
  • The Republic of Korea is very vulnerable to damage from storm and flood due to the rainfall phenomenon in summer and the topography of the narrow peninsula. The damage is recently getting worse because of the concentration rainfall. The accurate damage information production and analysis is required to prepare for future disaster. In this study, we analyzed the water surface area changes of Byeokjeong, Sajeom, Subu and Boryeong using Sentinel-1 satellite imagery. The surface area of the Sentinel-1 satellite, taken from May 2015 to August 2019, was preprocessed using RTC and image binarization using Otsu. The water surface area of reservoir was compared with the storage capacity from WAMIS and RIMS. As a result, Subu and Boryeong showed strong correlations of 0.850 and 0.941, respectively, and Byeokjeong and Sajeom showed the normal correlation of 0.651 and 0.657. Thus, SAR satellite imagery can be used to objective data as disaster management.

Statistics and Management Systems of Unwanted Domestic and Foreign Fire Alarms (국내·외 비화재보의 통계 및 관리체계에 관한 연구)

  • Hwang, Euy-Hong;Lee, Sung-Eun;Choi, Don-Mook
    • Fire Science and Engineering
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    • v.34 no.2
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    • pp.30-40
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    • 2020
  • In the event of a fire and a disaster, prompt and accurate alarms inside and outside the building are directly related to the minimization of damage and the success of life evacuation. However, due to unwanted fire alarms in automated fire detection systems, the number of dispatches by misunderstanding in the 119 service is increasing. This causes the insensitivity to the safety of building managers and the waste of the fire-fighting power. Therefore, in this study, the statistical databases and literature on unwanted fire alarms in Korea and abroad (USA, UK) were identified and the management systems for unwanted fire alarms were compared and analyzed to identify problems of statistics in the management systems for unwanted fire alarms.

Development of Parallel Arc Fault Detector Using Ripple Voltage (리플전압을 이용한 병렬아크 사고 감지기 개발)

  • Choi, Jung-Kyu;Kwak, Dong-Kurl
    • The Transactions of the Korean Institute of Power Electronics
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    • v.21 no.5
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    • pp.453-456
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    • 2016
  • The major causes of electrical fire in low-voltage distribution lines are classified into short-circuit fault, overload fault, electric leakage, and electric contact failure. The special principal factor of the fire is electric arc or spark accompanied with such electric faults. This paper studies the development of an electric fire prevention system with detection and alarm of that in case of parallel arc fault occurrence in low-voltage distribution lines. The proposed system is designed on algorithm sensing the instantaneous voltage drop of line voltage at arc fault occurrence. The proposed detector has characteristics of high-speed operation responsibility and superior system reliability from composition using a large number of semiconductor devices. A new sensing control method that shows the detection of parallel arc fault is sensed to ripple voltage drop through a diode bridge full-wave rectifier at electrical accident occurrence. Some experimental tests of the proposed system also confirm the practicality and validity of the analytical results.