• Journal of Korean Society of Disaster and Security
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• v.6 no.1
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• pp.19-27
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• 2013

Damage on assets and lives caused by natural disasters can be minimized by the provision of early warning information and preventive activities. In this sense, the importance of a disaster early warning system continues to increase. This study specifies the kinds of early warning systems depending on the type of natural disasters such as typhoon, flood and heavy snow. The mechanism for information transmission and status of early warning operations are analyzed. Through this analysis, the urgent need to establish a national integrated early warning transmission system is emphasized. In addition, this study offers methods to prevent unnecessary overlapping of investments by establishing an organic mechanism among individual early warning systems. Based on the standardization of disaster-related information, this study also provides methods to improve the efficiency of disaster early warning systems by organizing a permanent team for handling the systematic management and operation of the system.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.135-141
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• 2015

The objective of this study is to develop an early warning system for rainfall induced landslides. For this study, we suggested an analysis process using rainfall forecast data. 1) For a selected slope, safety factor with saturated depth was analyzed and safety factor threshold was established (warning FS threshold=1.3, alarm FS threshold=1.1). 2) If rainfall started, saturated depth and safety factor was calculated with rainfall forecast data, 3) And every hour after safety factor is compared with threshold, then warning or alarm can issued. In the future, we plan to make a early warning system combined with the in-situ inclinometer sensors.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.11
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• pp.25-39
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• 1992

Due to the data processing development by the computer, the early warning system recently has made a remarkable evolution in its functions and performance as a component of the communication and control system which is also supported by the computer communication and intelligence system. In this paper it is presented that a integrated data processing system is designed to integrate the information sent from the various radar systems which constitute an early warning system. The suggested system model of this paper is devided into two types of structures, the centralized model and the distributed model, according to the data processing algorithm. We apply the queueing theory to analyse the performance of the designed models and the OPNET system kernel to make the analysing program with C language. From the analysis of the queueing components by applying the analysis programs to the designed systems, we got the tendancies and characteristics of both models, that is, a fast data processing performance of the distributed model and a stable data processing capability of the centralized model.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.504-514
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• 2009

Recently, fire monitoring application systems have been an active research area due to the safety of industries, historical monuments and so on. The fire monitoring application systems can reduce the damage of properties by providing earlier warning for possible fire situation. However, the existing systems have a drawback that they detect fire with delay due to their uniform epoch in fire detection algorithm. Moreover, they do not provide user-friendly graphical user interfaces in their fire monitoring systems. To resolve the problems, First, we propose a new fire detection algorithm (Early Fire Detection Fire Algorithm) which uses the distribution of sensing data for early fire detection. Our fire detection algorithm is better in terms of fire detection time than the existing work because it can set a start time of fire detection epoch dynamically based on data distribution. Second, we develop a fire monitoring application system which provides users with both a user-friendly graphical user interface and a fire alarm message when fire occurs. Finally, we show from our experiment that our developed system is effectively used for early fire warning in a variety of fire situations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.33-37
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• 2002

Insulation aging diagnosis system provides early warning regarding electrical equipment defects. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear. it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a electromagnetic wave and acoustic signal to diagnose an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System and acquires 2D patterns from analyzing it. For filtering the noise contained in sensor signals we used ICA algorithms. Using this data, we design of the neuro-fuzzy model that diagnoses an electrical equipment and is investigated in this paper. Validity of the new method is asserted by numerical simulation.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.157-161
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• 2009

In recent years, there is a remarkable progress in ICTs (Information and Communication Technologies), and then many attempts to apply ICTs to other industries are being made. In the field of disaster managements, ICTs such as RFID (Radio Frequency IDentification) and USN (Ubiquitous Sensor Network) are used to provide safe environments. Actually, various types of early warning systems using USN are now widely used to monitor natural disasters such as floods, landslides and earthquakes, and also to detect human-caused disasters such as fires, explosions and collapses. These early warning systems issue alarms rapidly when a disaster is detected or an event exceeds prescribed thresholds, and furthermore deliver alarm messages to disaster managers and citizens. In general, these systems consist of a number of various sensors and measure real-time stream data, which requires an efficient and rapid data processing technique. In this study, an event-driven architecture (EDA) is presented to collect event effectively and to provide an alert rapidly. A publish/subscribe event processing method to process simple event is introduced. Additionally, a complex event processing (CEP) technique is introduced to process complex data from various sensors and to provide prompt and reasonable decision supports when many disasters happen simultaneously. A basic concept of CEP technique is presented and the advantages of the technique in disaster management are also discussed. Then, how the main processing methods of CEP such as aggregation, correlation, and filtering can be applied to disaster management is considered. Finally, an example of flood forecasting and early alarm system in which CEP is incorporated is presented It is found that the CEP based on the EDA will provide an efficient early warning method when disaster happens.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.73-79
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• 2008

Economic growth, industrialization and urbanization have made society more vulnerable than ever to seismic hazard in Korea. Although Korea has not experienced severe damage due to earthquakes during the last few decades, there is little doubt of the potential for large earthquakes in Korea as documented in the historical literature. As we see no immediate promise of short-term earthquake prediction with current science and technology, earthquake early warning systems attract more and more attention as a practical measure to mitigate damage from earthquakes. Earthquake early warning systems provide a few seconds to tens of seconds of warning time before the onset of strong ground shaking. To achieve rapid earthquake location, we propose to take full advantage of information from existing seismic networks; by using P wave arrival times at two nearest stations from the earthquake hypocenter and also information that P waves have not yet arrived at other stations. Ten earthquakes in the Korean peninsula and its vicinity are selected for the feasibility study. We observed that location results are not reliable when earthquakes occur outside of the seismic network. Earthquakes inside the seismic network, however, can be located very rapidly for the purpose of earthquake early warning. Seoul metropolitan area may secure $10{\sim}50$ seconds of warning time before any strong shaking starts for certain events. Carefully orchestrated actions during the given warning time should be able to reduce hazard and mitigate damages due to potentially disastrous earthquakes.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.263-272
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• 2024

A model based on genetic algorithm optimization, GA-SVM, is proposed to warn university students of their status. This model improves the predictive effect of support vector machines. The genetic optimization algorithm is used to train the hyperparameters and adjust the kernel parameters, kernel penalty factor C, and gamma to optimize the support vector machine model, which can rapidly achieve convergence to obtain the optimal solution. The experimental model was trained on open-source datasets and validated through comparisons with random forest, backpropagation neural network, and GA-SVM models. The test results show that the genetic algorithm-optimized radial basis kernel support vector machine model GA-SVM can obtain higher accuracy rates when used for early warning in university learning.

• Smart Structures and Systems
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• v.6 no.4
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• pp.405-421
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• 2010

This paper proposes a method for early warning of hazard for pipelines. Many pipelines transport dangerous contents so that any damage incurred might lead to catastrophic consequences. However, most of these damages are usually a result of surrounding third-party activities, mainly the constructions. In order to prevent accidents and disasters, detection of potential hazards from third-party activities is indispensable. This paper focuses on recognizing the running of construction machines because they indicate the activity of the constructions. Acoustic information is applied for the recognition and a novel pipeline monitoring approach is proposed. Principal Component Analysis (PCA) is applied. The obtained Eigenvalues are regarded as the special signature and thus used for building feature vectors. One-class Support Vector Machine (SVM) is used for the classifier. The denoising ability of PCA can make it robust to noise interference, while the powerful classifying ability of SVM can provide good recognition results. Some related issues such as standardization are also studied and discussed. On-site experiments are conducted and results prove the effectiveness of the proposed early warning method. Thus the possible hazards can be prevented and the integrity of pipelines can be ensured.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.1
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• pp.39-49
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• 2017

This study develops an early warning system (EWS) to prevent the banking crisis. The proposed system incorporates both the perspective of crises and fundamental characteristics of the banking system in each economy. A fuzzy logic method with data from 1990-2009 is employed to construct the EWS of banking crisis based on 21 pre-determined variables from the aspect of total economy, financial and banking sectors. Our results show: Firstly, South Korea recorded higher probability to have a banking crisis in 1997 as there was large foreign debt in dollars. Secondly, China, Australia and New Zealand banking systems appear to be vulnerable to the crisis in 2007. The surge of China export, FDIs and booming stock market were signs of a heated economy. Australia with high commodity prices was also vulnerable to crisis. Thirdly, Australia, China, Japan and New Zealand banking systems appear to be exposed to the higher chance of a crisis in 2010. Japan with deflation coupled with expensive yen did not augur well for its export. Overall, the findings show that in Asian Financial Crisis 1997/98 and Global Financial Crisis 2008/09, many economies are exposed to a higher probability of having the crisis and this shows an urgent need of having surveillance in these economies.