• 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.

• Journal of Biomedical Engineering Research
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• v.18 no.3
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• pp.315-323
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• 1997

Driving is a complex vigilance task that includes improper lookout, excessive speed and inattention. The primary objective of this research is to detect driver drowsiness so that the driver can be alerted to an impending traffic accident in performance. We developed the automatic detection and warning system during drowsy driving. A drowsiness detection system must be able to monitor driver status and detect the detrimental changes of a driver performance. Eyeblink has been found to be a reliable factor of drowsiness detection in earlier studies. As an additional parameter, we also considered the yawning which often occurs in a low vigilance state and predicts the drowsy state. We used a computer vision method to extract the eyeblink and yawning in the face image sequences. When the drowsy state was detected, the driver was refreshed by alarming device and menthol scent generator after deciding the warning level by fuzzy logic. For the evaluation of our system, we measured the physiological parameters such as EOG and EEG. The results indicated that it is possible to detect and alert the driver drowsiness temporarily or continuously by using our system.

• Journal of Korea Water Resources Association
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• v.38 no.7 s.156
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• pp.575-584
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• 2005

The judgement model to warn of possible pollution accident is constructed by multi-perceptron, multi layer neural network, neuro-fuzzy and it is trained stability, notice, and warming situation due to developed standard axis. The water quality forecasting model is linked to the runoff forecasting model, and joined with the judgement model to warn of possible pollution accident, which completes the artificial intelligence warning system. And GUI (Graphic User Interface) has been designed for that system. GUI screens, in order of process, are main page, data edit, discharge forecasting, water quality forecasting, warming system. The application capability of the system was estimated by the pollution accident scenario. Estimation results verify that the artificial intelligence warning system can be a reasonable judgement of the noized water pollution data.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.11-26
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• 2004

Software for analyzing documents on the net to detect specific categories of occurrences is in great demand. In the current world where detecting terrorist threats is critical there is a great need for such systems. One of the critical application areas of such software is the automatic detection of a national infrastructure emergency. In this research an agent-based generic architecture for emergency warning systems is proposed and implemented. This system, called the National Infrastructure Emergency Warning System (NIEWS), is designed to analyze given documents, to detect threats, and to report possible threats with the necessary information to the appropriate users autonomously. In addition, a systematic analysis framework to detect emergencies on the subject of defensive information warfare is designated and implemented through a knowledge base. The developed system along with the knowledge base is implemented and successfully deployed to Strategic Crisis Exercise (SCE) at the United State Army War College (USAWC), saving a good amount of money by replacing human SMEs (subject matter experts) in the SCE.

• The Journal of Information Systems
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• v.32 no.3
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• pp.183-203
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• 2023

Purpose The purpose of this study is to examine the current operational status and problems of the Public Warning System (PWS) in China, and to propose feasible solutions to improve the performance and efficiency of the PWS through a comparative analysis with the Cell Broadcast Service (CBS)-based disaster SMS system adopted by other developed countries in the world. Design/methodology/approach In this study, the characteristics of PWS using SMS, applications, and CBS, respectively, are analyzed in detail, and compared and analyzed in terms of convenience, standardization, data security, speed, and location accuracy. In addition, CBS-based PWS in developed countries, such as U.S., E.U., Korea and Japan, were studied and their performance on key criteria was evaluated. Findings Based on the results of the study, the problems of China's PWS are summarized and recommendations are made to improve the PWS through the introduction of CBS technology. To this end, specific improvement measures are proposed in terms of the application of CBS technology, system construction and operation, and improvement of data security. In addition, the comparative analysis of PWSs in other developed countries is conducted to provide reference for the direction of PWS's improvement.

• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.46-55
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• 2005

In this paper, we realize the panoramic infrared warning system to detect the small threaten object and propose the infrared image enhancement method to improve the warning ability of this system. This system composes of the sense head unit, the signal processing unit, and so on. In the proposed system, the sense head unit acquires the panoramic IR image with 360 degree field of view(FOV) by rotating the thermal sensor. The signal processing unit divides panoramic image into four sub-images with 90 degree FOV and computes the adaptive plateau value by using statistical characteristics of each subimage. Then the histogram equalization is performed for each subimage by using the adaptive plateau value. We realize the signal Processing unit by using the DSP and FPGA to perform the proposed method in real time. Experimental results show that the proposed method has better discrimination and lower false alarm rate than the conventional methods in this warning system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.849-856
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• 2020

Recently, as the number of high-height vehicles such as double-decker buses has increased, collision accidents have occurred in bridges and tunnels due to the deviation from the designated routes and driver's carelessness. In the case of the existing front collision warning system, it is limited to vehicles and pedestrians, so it is difficult to use it as a pass height warning system for the high height vehicles. In this paper, we propose a system that generates a warning by determining the correlation and time series characteristics of data for each segment using multiple lidar sensors and then determining the possibility of collision in the upper part of the vehicle. Also, the proposed system confirmed the proper operation through a real-time driving test and a system performance evaluation by the Korea Automobile Testing & Research Institute.

• IE interfaces
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• v.25 no.3
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• pp.319-326
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• 2012

To effectively predict financial crisis, this paper presents an early warning system based on artificial intelligence technologies. Both Genetic Algorithms and Neural Networks are utilized for the proposed system. First, a genetic algorithm has been developed for the effective selection of economic indices, which are used for monitoring financial crisis. Then, an optimum weight of the selected indices has been determined by a neural network method. To validate the effectiveness of the proposed system, a series of experiments has been conducted by using the Korean economic indices from 2005 to 2008.

• 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.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.400-403
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• 2003

This paper presents the signal processing of the panoramic thermal warning system that detects the small target such as aircraft and helicopter from afar. We develope the all round looking thermal imaging system which can scan all the way. This system acquires the panoramic images to reconstruct the IR images by revolving head of sensor typed line sensor at high speed. For detection, where the object of interest may be small, it is sometimes difficult to specify from object and background by conventional contrast enhancement methods. Therefore we use the adaptive plateau equalization algorithm each region to improve the contrast and make the hardware system which consists of the signal processing board for real-time display. We can verify the proposed method by the computer simulation and the hardware implementation.