• Title/Summary/Keyword: Early Warning

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통신분야 조기경보시스템의 프레임워크

  • 구자현
    • Review of KIISC
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    • v.15 no.1
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    • pp.76-82
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    • 2005
  • 본 연구는 망의 가용성이나 보안성을 확보하는 것이 중요한 통신사업자들에게 전국적인 IT 인프라에서 발생하는 해킹이나 기타 보안 위협에 따른 피해를 최소화하고, 위협에 대해서 능동적으로 방어하기 위하여 구축하는 조기경보 시스템에 대한 연구이다. 이러한 조기경보시스템을 구축함으로서 해킹, 바이러스, 웜 등의 다양한 전자적인 침해사고 등의 이벤트를 수집, 분류하고 빠른 시간 안에 대응할 수 있는 시스템을 갖추게 된다. 본 연구는 통신사업자가 조기경보시스템(EWIS : Early Warning Information System)을 구축하기 위해서 필요한 프레임워크를 제시하는데 있다.

The 3rd National Conference Of Professional engineers - On Geotechnical Structure Risk & Hazards (제3회 전국기술사대회 특집(토목시공) - 지반구조물 재해 및 위험분석 연구)

  • Yoon, Gil-Lim
    • Journal of the Korean Professional Engineers Association
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    • v.42 no.4
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    • pp.30-33
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    • 2009
  • Great concerns on geotechnical risk & hazard assessment have increased due to human and economic damage by natural disasters with recent global climate changes. In this paper, geotechnical problems in particular, landslide which is interested in European countries and North America, were mainly discussed. For these, 18 key topics on geotechnical risk and hazards which had been discussed at the LARAM 2008 workshop in Italy were analyzed after grouping by subjects. Main topic contents consisted of applications such as field measurement, early warning systems, uncertainty analysis of parameters using radar, optical data and statistical theory and so on.

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Early Detective Warning System of Fire in the Tunnel Road (도로터널 내 차량사고 화재조기감지 예고 시스템)

  • Yoon, Sungwook;Kim, Hyenki
    • Proceedings of the Korea Contents Association Conference
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    • 2012.05a
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    • pp.291-292
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    • 2012
  • 본 연구는 여러 가지 센서를 이용하여 자동차 전용 도로터널의 차량 사고시의 음향을 인식하여 사고인식률을 높이는 화재 예고 시스템에 관한 연구이다. 현행의 CCTV나 자동화재탐재설비에서 감지하는 열센서나 영상전송자료를 파악하기에 앞서, 이차적 재해 가능성을 유의미한 수준에서 미리 예고하고 대응할 수 있는 사전예고시스템을 구성하였다. 유선설치기반의 센서로 대부분 구성된 도로터널 내에서 비교적 설비가 저렴한 무선센서를 사용함으로서 기존 터널에서의 적용성을 증대시켰다.

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A Survey of Real-time Road Detection Techniques Using Visual Color Sensor

  • Hong, Gwang-Soo;Kim, Byung-Gyu;Dogra, Debi Prosad;Roy, Partha Pratim
    • Journal of Multimedia Information System
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    • v.5 no.1
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    • pp.9-14
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    • 2018
  • A road recognition system or Lane departure warning system is an early stage technology that has been commercialized as early as 10 years but can be optional and used as an expensive premium vehicle, with a very small number of users. Since the system installed on a vehicle should not be error prone and operate reliably, the introduction of robust feature extraction and tracking techniques requires the development of algorithms that can provide reliable information. In this paper, we investigate and analyze various real-time road detection algorithms based on color information. Through these analyses, we would like to suggest the algorithms that are actually applicable.

Disaster Emergency Management Systems using Bio-AdHoc Sensor Networks (센서 탑재 바이오 애드 혹 네트워크를 이용한 재난 관리용 시스템)

  • Lee, Dong-Eun;Lee, Goo-Yeon
    • Journal of Industrial Technology
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    • v.26 no.B
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    • pp.183-189
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    • 2006
  • Ad hoc network does not need any preexisting network infrastructure, and it has been developed as temporal networks in the various fields. Infostation is an efficient system to transfer informations which are not sensitive to delay. In this paper, we propose a disaster emergency management system using sensors attached to animals, that is combined with infostation system. We also analyze the performance of the proposed system by simulation. From the performance analysis results, we expect that the proposed system will be very useful to early detect big forest fires which occur frequently in Korea mountain areas.

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Scoring models to detect foreign exchange money laundering (외국환 거래의 자금세탁 혐의도 점수모형 개발에 관한 연구)

  • Hong, Seong-Ik;Moon, Tae-Hee;Sohn, So-Young
    • IE interfaces
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    • v.18 no.3
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    • pp.268-276
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    • 2005
  • In recent years, the money Laundering crimes are increasing by means of foreign exchange transactions. Our study proposes four scoring models to provide early warning of the laundering in foreign exchange transactions for both inward and outward remittances: logistic regression model, decision tree, neural network, and ensemble model which combines the three models. In terms of accuracy of test data, decision tree model is selected for the inward remittance and an ensemble model for the outward remittance. From our study results, the accumulated number of transaction turns out to be the most important predictor variable. The proposed scoring models deal with the transaction level and is expected to help the bank teller to detect the laundering related transactions in the early stage.

An Experimental Study on Density Tool Calibration (광섬유격자 센서를 활용한 사면거동 실시간 안전 진단 시스템)

  • Chang, Ki-Tae;Chung, Kyung-Sun;Kim, Sung-Hwan
    • Journal of the Korean Geophysical Society
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    • v.8 no.1
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    • pp.7-14
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    • 2005
  • Early detection in real-time response of slope movements ensures tremendous saving of lives and repair costs from catastrophic disaster. Therefore, it is essential to constantly monitor the performance and integrity of slope-stabilizing structures such as Rock bolt, Nail and Pile during or after installation. We developed a novel monitoring system using Fiber Bragg Grating (FBG) sensor. It's advantages are highly sensitivity, small dimension and electro-magnetic immunity. capability of multiplexing, system integrity, remote sensing - these serve real-time health monitoring of the structures. Real-time strain measurement by the signal processing program is shown graphically and it gives a warning sound when the monitored strain state exceeds a given threshold level so that any sign of abnormal disturbance on the spot can be easily perceived.

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Preliminary Study on Market Risk Prediction Model for International Construction using Fractal Analysis

  • Moon, Seonghyeon;Kim, Du Yon;Chi, Seokho
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.463-467
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    • 2015
  • Mega-shock means a sporadic event such as the earning shock, which occurred by sudden market changes, and it can cause serious problems of profit loss of international construction projects. Therefore, the early response and prevention by analyzing and predicting the Mega-shock is critical for successful project delivery. This research is preliminary study to develop a prediction model that supports market condition analysis and Mega-shock forecasting. To avoid disadvantages of classic statistical approaches that assume the market factors are linear and independent and thus have limitations to explain complex interrelationship among a range of international market factors, the research team explored the Fractal Theory that can explain self-similarity and recursiveness of construction market changes. The research first found out correlation of the major market factors by statistically analyzing time-series data. The research then conducted a base of the Fractal analysis to distinguish features of fractal from data. The outcome will have potential to contribute to building up a foundation of the early shock warning system for the strategic international project management.

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A Study on the Statistical Predictability of Drinking Water Qualities for Contamination Warning System (수질오염 감시체계 구축을 위한 수질 데이터의 통계적 예측 가능성 검토)

  • Park, No-Suk;Lee, Young-Joo;Chae, Seonha;Yoon, Sukmin
    • Journal of Korean Society of Water and Wastewater
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    • v.29 no.4
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    • pp.469-479
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    • 2015
  • This study have been conducted to analyze the feasibility of establishing Contamination Warning System(CWS) that is capable of monitoring early natural or intentional water quality accidents, and providing active and quick responses for domestic C_water supply system. In order to evaluate the water quality data set, pH, turbidity and free residual chlorine concentration data were collected and each statistical value(mean, variation, range) was calculated, then the seasonal variability of those were analyzed using the independent t-test. From the results of analyzing the distribution of outliers in the measurement data using a high-pass filter, it could be confirmed that a lot of lower outliers appeared due to data missing. In addition, linear filter model based on autoregressive model(AR(1) and AR(2)) was applied for the state estimation of each water quality data set. From the results of analyzing the variability of the autocorrelation coefficient structure according to the change of window size(6hours~48hours), at least the window size longer than 12hours should be necessary for estimating the state of water quality data satisfactorily.