• Fire Science and Engineering
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• v.18 no.4
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• pp.72-77
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• 2004

In this paper, we studied on the short-circuit process, surface structure, and component variation of vinyl cords. In the results of high speed imaging system (HSIS) analysis, as soon as wire covering was damaged by heat, the conductor of wire came in contact with the other conduct of wire, and the short-circuit occurred. Stereomicroscope and SEM analysis indicated that the source part of wire showed V-type form. The molten beads of load part were bigger than those of source part. In the results of EDX analysis, Cu and O were detected in the source part, whereas covering material (Cl, Ca), Cu and O were detected in the load part. The results will help us to find out the cause of electrical fire.

• Korean Journal of Optics and Photonics
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• v.25 no.5
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• pp.245-253
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• 2014

We report a realistic field-performance simulation for a new MWIR camera. It is designed for early detection of missile plumes over a distance range of a few hundred kilometers. Both imaging and radiometric performance of the camera are studied by using real-scale integrated ray tracing, including targets, atmosphere, and background scene models. The simulation results demonstrate that the camera would satisfy the imaging and radiometric performance requirements for field operation.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2013.04a
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• pp.142-143
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• 2013

본 연구는 u-IT 융합기술을 접목하여 옥내 외 화재발생시 조기발견 및 탐지가 용이하다. 아울러 저비용과 고효율로 화재에 신속한 대응이 가능하며 옥외 환경에 적합한 옥외형 화재경보시스템의 성능 및 신뢰성 평가에 관한 것이다. 성능시험, 기능시험, 화염시험 및 옥외방치시험을 3개월간 실시한바 양호하였고 온도변화 성능시험도 $-30^{\circ}C{\sim}70^{\circ}C$에서 양호하였으며 EMI/EMS 시험도 적합하였다. 또한 화염검출거리 증가와 대기전원의 4시간 증가, 동작시간을 3일까지 가능하게 하였으며 센서뿐만아니라 영상으로 상황을 인지하는데 적합하였다.

• Analytical Science and Technology
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• v.12 no.5
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• pp.403-407
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• 1999

A method for detecting chlorine dioxide in drinking water was developed by the modified iodometric titration. This method requires prior removal of interfering chemicals such as chlorine and/or other oxidants: the interferents are removed by $N_2$ purging. Chlorite and chlorate were successfully quantified by the ion chromatography-conductivity detection. Stabilized chlorine dioxide that is commercially available contained only traces of chlorine dioxide (0.01-0.09%). In reality, its main component is chlorite.

• Proceedings of the Optical Society of Korea Conference
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• 2000.02a
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• pp.230-231
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• 2000

최근 자동차, 항공기 등 연소과정을 수반하는 산업이 발전함에 따라 연소환경에 대한 관심이 높아지고 있다. 그런데 연소환경을 접촉식 방법으로 측정하게 되면, 측정기기가 연소환경에 영향을 주기 때문에 정확한 측정을 하기는 어렵다. 그래서 레이저를 이용한 비접촉식방법이 활용되고 있으며,$^{(1)}$ 그 중에서 LIGS(laser induced grating spectrosopy)나 DFWM(degenerate four wave mixing)$^{(1)}$ 은 신호대 잡음비가 높기 때문에 미세량으로 존재하는 분자를 검출하는데 유용할 뿐만 아니라 2차원 영상수집도 가능하다. 또한 LIGS의 시분해 신호를 분석하면 연소장내의 온도와 입자의 밀도 등을 산출할 수 있다. 본 실험에서는 대기압에서 불완전 연소장의 soot에 대한 신호를 수집, 분석하여 화염 위치에 따른 온도 변화와 soot의 농도 등을 정량적으로 조사했다.$^{(2)}$ (중략)

• Journal of the KSME
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• v.33 no.12
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• pp.1043-1051
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• 1993

Nd:Yag 레이저의 제2고조파와 광대역 모드 없는 레이저를 광원으로 사용하고 이중회절발분광 기에 설치된 다채널광검출기로 분광된 CARS 스펙트럼을 레이저 펄스마다 측정 할 수 있는 광 대역 CARS 분광기를 제작하였다. CARS 온도측정 불확정도는 300K에서 1300K까지는 1.5% 이내였다. CARS 기술을 이용하여 분젠버너의 화염면에서의 온도 분포를 측정하였으며, 대향류 버너의 화염내부의 온도 분포 및 CO 농도분포를 측정하였다. 이러한 CARS 기술은 정상상태의 연소진단에 응용할 수 있을 뿐만 아니라 레이저 펄스마다 측정되는 온도의 분포함수를 조사하면 앞으로 난류연소의 진단에도 응용이 가능하며, 내연기관 등과 같이 연속폭발연소 상태의 기체의 온도나 농도 측정이 가능하다. 본 연구에서 연구된 CARS 기술의 온도 측정정확도는 약 2% 이 내이고 농도 측정은 측정기체의 농도가 상온에서는 약 0.1% 이상, 1500K 이상의 고온에서는 0.3%이상이면 가능하다.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1257-1262
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• 2018

In this paper, a deep learning method is proposed to detect the fire effectively by using video of surveillance camera. Based on AlexNet model, classification performance is compared according to kernel size and stride of convolution layer. Dataset for learning and interfering are classified into two classes such as normal and fire. Normal images include clouds, and foggy images, and fire images include smoke and flames images, respectively. As results of simulations, it is shown that the larger kernel size and smaller stride shows better performance.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.11
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• pp.1632-1638
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• 2012

The effects of combined treatment of aqueous $ClO_2$ and UV-C or electron beam irradiation on microbial growth and quality in chicon during storage at $4^{\circ}C$ were investigated. Samples were treated separately with 50 ppm of $ClO_2$, 5 kJ/$m^2$ of UV-C, 2, 5, 7, and 10 kGy of electron beam irradiation, as well as a combination of $ClO_2$ and UV-C or 2 kGy of electron beam irradiation. The populations of total aerobic bacteria as well as yeast and molds in the chicon samples were determined following each treatment. The populations of total aerobic bacteria in the chicon samples decreased by 1.49~2.92 log CFU/g following combined treatment of $ClO_2$ and UV-C irradiation compared to the control, whereas the populations of yeast and molds decreased by 1.63~1.78 log CFU/g. On the contrary, following combined treatment of $ClO_2$ and electron beam irradiation, the populations of total aerobic bacteria as well as yeast and molds in the chicon samples were undetectable during storage. Color measurements indicated that Hunter $L^*$, $a^*$, and $b^*$ values were not significantly different among the treatments during storage. These results suggest that combined treatment of $ClO_2$ and electron beam irradiation can be useful for improving microbiological safety in chicon during storage.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.04a
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• pp.135-138
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• 2008

Many Victims and property damage are caused in fires. In this paper, an flame detection algorithm is proposed to early alarm fires. The proposed flame detection algorithm is based on 2-stage decision strategy of video processing. The first decision is to check with color distribution of input vidoe. In the second, the candidated region is settled as fire region with activity. As a result of simulation, it is shown that the proposed algorithm is useful for fire recognition.

• Journal of IKEEE
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• v.22 no.4
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• pp.1079-1087
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• 2018

Recently, computer vision field based deep learning artificial intelligence has become a hot topic among various image analysis boundaries. In this study, flames are detected in fire images using the Faster R-CNN algorithm, which is used to detect objects within the image, among various image recognition algorithms based on deep learning. In order to improve fire detection accuracy through a small amount of data sets in the learning process, we use image augmentation techniques, and learn image augmentation by dividing into 6 types and compare accuracy, precision and detection rate. As a result, the detection rate increases as the type of image augmentation increases. However, as with the general accuracy and detection rate of other object detection models, the false detection rate is also increased from 10% to 30%.