• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.345-350
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• 2016

This research suggests the keyword filtering about disaster and the method of detecting area in real-time event detecting system by analyzing contents of twitter. The diffusion of smart-mobile has lead to a fast spread of SNS and nowadays, various researches based on studying SNS are being processed. Among SNS, the twitter has a characteristic of fast diffusion since it is written in 140 words of short paragraph. Therefore, the tweets that are written by twitter users are able to perform a role of sensor. By using these features the research has been constructed which detects the events that have been occurred. However, people became reluctant to open their information of location because it is reported that private information leakage are increasing. Also, problems associated with accuracy are occurred in process of analyzing the tweet contents that do not follow the spelling rule. Therefore, additional designing keyword filtering and the method of area detection on detecting real-time event process were required in order to develop the accuracy. This research suggests the method of keyword filtering about disaster and two methods of detecting area. One is the method of removing area noise which removes the noise that occurred in the local name words. And the other one is the method of determinating the area which confirms local name words by using landmarks. By applying the method of keyword filtering about disaster and two methods of detecting area, the accuracy has improved. It has improved 49% to 78% by using the method of removing area noise and the other accuracy has improved 49% to 89% by using the method of determinating the area.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.272-274
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• 2015

본 논문에서는 하천 인근의 재난 방지를 위한 효율적인 재난감지 알고리즘을 제안한다. 제안하는 알고리즘은 영상처리를 기반으로 임계값을 자동으로 변경시켜 물과 물이 아닌 영역을 분리한다. 수위감지 알고리즘을 단순 물의 색상 정보만을 이용해 분석한다면, 야간 저조도, 폭우와 같은 상황 등에서 알고리즘 성능이 저하될 우려가 있다, 이를 해결하기 위해서 물의 색상 정보뿐 아니라 물의 흔들림 정도도 함께 고려하여 물의 영역을 찾아낸다. 또한 보다 안정적인 수위 분포를 분석하기 위해서 시간과 공간에 대한 필터링을 추가하여 빗물, 물결, 카메라의 화이트 노이즈 등 다양한 노이즈에 보다 안정적으로 수위 분포를 분석한다. 본 논문에서 제안하는 수위감지 알고리즘을 적용한다면, 센서, 목자판 인식 등 이전의 수위계측 방식보다 성능, 비용 면에서 모두 우수할 것으로 예측된다.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.430-439
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• 2018

Purpose: The purpose of this study is to verify the effectiveness of maintenance method using GPR exploration by buried detective materials in the ground for efficient maintenance of recovered cavities. Method: EMI sheet, EMI paint, and ferronickel slag were used as the detection materials, and the experiment was conducted by varying the size and depth of the buried detectable material. Results: As a result of the exploration, Detectable influence range by GPR exploration was found depending on the size and depth of buried detectable material in all materials, and the possibility of using it as a detection material was confirmed.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.107-108
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• 2010

Uncertainty and insecurity is a serious issue in all aspects of our society today as the change in environmental and societal conditions became more apparent than ever before through various disasters. Thus, it is now an important point in time for the government and responsible firms to implement an innovative scientific disaster management method that can lead to establishing a more secure and stable future. Therefore, authors have developed ubiquitous- based disaster prevention automation system(DPAS). The system would follow up after sensors detecting fires, thefts, torrents, floods, and infrastructural leaks. It prevents disasters in advance by utilizing a wireless communications net or ethernet to conduct real-time monitoring from a remote place. The system also has an advantage as it is designed in a compact size that applies a precision-focused programmable logic controller(PLC) of one-chip type.

• Ocean and Polar Research
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• v.43 no.4
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• pp.229-243
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• 2021

Quality control (QC) to process observed time series has become more critical as the types and amount of observed data have increased along with the development of ocean observing sensors and communication technology. International ocean observing institutions have developed and operated automatic QC procedures for these observed time series. In this study, the performance of automated QC procedures proposed by U.S. IOOS (Integrated Ocean Observing System), NDBC (National Data Buy Center), and OOI (Ocean Observatory Initiative) were evaluated for observed time-series particularly from the Yellow and East China Seas by taking advantage of a confusion matrix. We focused on detecting additive outliers (AO) and temporary change outliers (TCO) based on ocean temperature observation from the Ieodo Ocean Research Station (I-ORS) in 2013. Our results present that the IOOS variability check procedure tends to classify normal data as AO or TCO. The NDBC variability check tracks outliers well but also tends to classify a lot of normal data as abnormal, particularly in the case of rapidly fluctuating time-series. The OOI procedure seems to detect the AO and TCO most effectively and the rate of classifying normal data as abnormal is also the lowest among the international checks. However, all three checks need additional scrutiny because they often fail to classify outliers when intermittent observations are performed or as a result of systematic errors, as well as tending to classify normal data as outliers in the case where there is abrupt change in the observed data due to a sensor being located within a sharp boundary between two water masses, which is a common feature in shallow water observations. Therefore, this study underlines the necessity of developing a new QC algorithm for time-series occurring in a shallow sea.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.895-903
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• 2016

In a fire disaster in a tunnel, people should be rescued immediately using the information obtained from cameras or sensors. However, in heavy smoke from a fire, people cannot be clearly identified by a mounted CCTV, which is only effective in a clear environment. A thermal camera can be an alternative to this in smoky situations and is capable of detecting people from their emitted thermal energy. On the other hand, the thermal image camera has a smaller field of view than an ordinary camera due to its lens characteristics and temperature error, etc. In order to cover a relatively wide area, panoramic image construction needs to be implemented. In this work, a template-based similarity matching algorithm for constructing the panorama image is proposed and its performance is verified through experiments. This scheme provides guidelines for coping with difficulty in image construction, which requires an exact correspondence search for two images in cases of heavy smoke.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.11
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• pp.1205-1216
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• 2015

Since concentration of greenhouse gas increases continuously from human's fossil fuel use, urbanization, and cultivation, it is trend that climate change is appearing. In Addition, in 20th century, occurrence of disaster is accidental and huge, and damage level also increases gradually. Therefore, in order to preserve the territory and to protect people's life and property against new type disasters, disaster detection satellite (payloads) development is required urgently. In this paper, we conduct a research and development for the prompt preemptive action when occurred a disaster, in particularly, about the disaster observation optimized at Korea's geographical features for the irregular future disasters. For the payload design which is specialized detect disasters, we create a tech tree of satellite imagery applications based 10 disaster types, and analyze the satellite sensor technologies referred to Landsat-8, Worldview-3 and ALOS-2.

• Fire Science and Engineering
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• v.28 no.4
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• pp.64-72
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• 2014

Flammable liquids residues in fire debris and pyrolysis products of flammable materials were analyzed by using Gas detecting tube, Gas Chromatograph/Mass Spectrometers (GC/MS), and Pyrolyzer. Comparison studies between chemical components detected in debris fired with and without Flammable liquids were performed. Though Flammable liquids were not present in debris, Gas detecting tube colors were also changed. Chemical components produced from conventional combustions were different from those produced from pyrolysis. Due to the difference of the reaction conditions between combustions and pyrolysis, different chemical products were produced. Petrochemical products of PVC wood-linoleum block could produce ignitable chemicals, such as toluene, ethylbenzene, undecane, and dodecane. So, for better fire investigation more consideration of those chemicals will be porformed.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.5
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• pp.49-54
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• 2010

The wooden cultural assets have the characteristics such as the fast spread of flame and leading to total destruction. Therefore, there is a need for a system for early countermeasure of recognized problem, along with the technological response for accurately recognizing the situation, for the prevention and early suppression of fire. To utilize such technology for detecting the situation through the latest ubiquitous technology and for a quick response to suppress fire, the ubiquitous sensor network (USN) technology, flame detector, image sensor, USN-based cultural asset disaster prevention management application case and malfunction identification system realization were examined in this study and the study result was presented focusing on the flame detector malfunction identification system for the ubiquitous-type cultural asset disaster prevention system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.195-206
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• 2016

The remote sensing technique using SAR data have many advantages when applied to the disaster site due to its wide coverage and all-weather acquisition availability. Although a single-pol (polarimetric) SAR image cannot represent the land surface better than a quad-pol SAR image can, single-pol SAR data are worth using for disaster-induced change detection. In this paper, an automatic change detection method based on a mixture of GGDs (generalized Gaussian distribution) is proposed, and usability of the textural features and intensity is evaluated by using the proposed method. Three ALOS/PALSAR images were used in the experiments, and the study site was Norita City, which was affected by the 2011 Tohoku earthquake. The experiment results showed that the proposed automatic change detection method is practical for disaster sites where the large areas change. The intensity information is useful for detecting disaster-induced changes with a 68.3% g-mean, but the texture information is not. The autocorrelation and correlation show the interesting implication that they tend not to extract agricultural areas in the change detection map. Therefore, the final tsunami-induced change map is produced by the combination of three maps: one is derived from the intensity information and used as an initial map, and the others are derived from the textural information and used as auxiliary data.