• Proceedings of the KSR Conference
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• 2005.11a
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• pp.299-304
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• 2005

A Vigilance control is a device fitted in the driving cab of a railway train to ensure that the driver is alert on the job. A simple vigilance control requires that the driver press a button at intervals not less than a certain amount and not more than another amount of time. If the driver fails to operate the vigilance control within those limits, a hooter sounds, and should the driver still doesn't operate the vigilance control then the brakes are applied. If the driver falls asleep or takes ill, then clearly such a vigilance control will sooner or later apply the brakes. The this vigilance control system which is applied to reduce the drive load at Syria diesel multiple unit train is proposed.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.95-97
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• 2004

This paper estimates Adaptive Resonance Theory 1(ART1) as a vigilance parameter of pattern clustering algorithm. Inherent characteristics of the model are analyzed. In particular the vigilance parameter ${\rho}$ and its role in classification of patterns is examined. Our estimates show that the vigilance parameter as designed originally does not necessarily increase the number of categories with its value but can decrease also. This is against the claim of solving the stability-plasticity dilemma. However, we have proposed a modified vigilance parameter estimate criterion which takes into account the problem of subset and superset patterns and stably categorizes arbitrarily many input patterns in one list presentation when the vigilance parameter is closer to one.

• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.176-183
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• 2005

The theory of signal detection has been applied to a wide range of practical situation for a long time, including sonar detection, air traffic control and so on. In general, in this theory, sensitivity parametric index d' and bias parametric index $\beta$ are used to evaluated the performance of vigilance. These indices use observer's response "hit" and "false alarm" to explain and evaluate vigilance, but not considering reaction time. However, the reaction time of detecting should be considered in measuring vigilance in some supervisory tasks such as unlimited monitoring tasks (e.g., supervisors in nuclear plant). There are some researchers have used the segments of reaction time to generate a pair of probabilities of hit and false alarm probabilities and plot the receiver operating characteristic curve. The purpose of this study was to develop a quantitative vigilance-measuring model by fuzzy sets, which combined the concepts of hit, false alarm and reaction time. The model extends two-values logic to multi-values logic by membership functions of fuzzy sets. A simulated experiment of monitoring task in nuclear plant was carried out. Results indicated that the new vigilance-measuring model is more efficient than traditional indices; the characteristics of vigilance would be realized more clearly in unlimited monitoring task.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2525-2527
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• 2004

This paper classify using Adaptive Resonance Theory 1(ART1) as a vigilance parameter of pattern clustering algorithm. Inherent characteristics of the model are analyzed. In particular the vigilance parameter $\rho$ and its role in classification of patterns is examined. Our estimates show that the vigilance parameter as designed originally does not necessarily increase the number of categories with its value but can decrease also. This is against the claim of solving the stability-plasticity dilemma. However, we have proposed a modified vigilance parameter setting criterion which takes into account the problem of subset and superset patterns and stably categorizes arbitrarily many input patterns in one list presentation when the vigilance parameter is closer to one. And this paper goal is the input pattern cognition and classification using neural network.

• Journal of Korean Institute of Industrial Engineers
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• v.8 no.1
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• pp.13-21
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• 1982

Experiments on the eye movement behavior were performed using Vidicon Eye Camera. Factorial design ( $3{\times}3$) was used to evaluate the validity of the eye movement as a performance measure in vigilance task. Eye movement data were recorded in video tapes, then the data were converted to digital signals, which were reduced to quantitative fixation and saccadic movement data by a microcomputer. To compare with existing vigilance performance measures, response time and the number of false alarms were also recorded. The results showed that the saccadic movement is a good measure of the performance in vigilance task : 1. Both the response time and the saccadic movement increased significantly during the initial two time blocks. 2. High correlations were shown between the response time and the saccadic movement. 3. The locational uncertainty affects the saccadic movement, the number of fixations, the response time but doesn't affect the duration of eye fixations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1318-1324
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• 2003

There are two problems in the conventional ART1 algorithm. One is in similarity testing method of the conventional ART1 between input patterns and stored patterns. The other is that vigilance threshold of conventional ART1 influences the number of clusters and the rate of recognition. In this paper, new similarity testing method and dynamical vigilance threshold method are proposed to solve these problems. The former is similarity test method using the rate of norm of exclusive-NOR between input patterns and stored patterns and the rate of nodes have equivalence value, and the latter method dynamically controls vigilance threshold to similarity using fuzzy operations and the sum operation of Yager. To check the performance of new methods, we used 26 alphabet characters and nosed characters. In experiment results, the proposed methods are better than the conventional methods in ART1, because the proposed methods are less sensitive than the conventional methods for initial vigilance and the recognition rate of the proposed methods is higher than that of the conventional methods.

• Bulletin of the Society of Naval Architects of Korea
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• v.11 no.1
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• pp.27-34
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• 1974

This study is aimed at a validation of the vigilance simulation model which was proposed earlier (2). The model estimates a perceived danger value, an alertness level and the probability of detection at a given elapsed time of vigilance. Twenty-nine male and seven female subjects were given a simple task. They were asked to detect a number(four numbers out of six digits in the telephone directory which have the probability of occurrence in the range of 0.0010-0.0018) in six different experimental conditions, for periods of two to three hours. Analysis of the experiments showed that although the mean detection rate varied slightly in two hours, the within-subject variance and the number of cyclic performance fluctuations increased significantly. A primal factor that affects the performance seems to be the frequency of target occurrence. By curve fitting, the relation between the probability of detection and the percentages of danger event occurrence was derived; $y=0.50(1-{\varepsilon}^{-50x^2})+0.39$. Assuming the equation represents the normal detection rate(100% performance), the Relative Vigilance Performance Rating was calculated. This rating method could be a useful criterion in selecting and training of the vigilance personnel. The results show that the simulation model is a good estimator of human a performance when the probability of danger occurrence is greater than 0.0015; it gives a good reference for improving the vigilance system. Suggestions are made that (1) the validity of proposed functional equations over the extended range of danger probability be studied, (2) an analysis of the cyclic fluctuations of the alertness level be accomplished, and (3) the cost functions of detection reliability be included in any future model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.486-492
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• 2003

The vigilance threshold of conventional fuzzy ART algorithm decide whether to permit the mismatch between any input pattern and stored pattern. If the vigilance threshold was large, despite of little difference among input and stored patterns, the input pattern may be classified to new category. On the other hand, if the vigilance threshold was small, the similarity between two patterns may be accepted in spite of lots of difference and the input pattern are classified to category of the stored pattern. Therefore, the vigilance threshold for the image recognition must be experientially set for the good result. Moreover, it may occur in the fuzzy ART algorithm that the information of stored patterns is lost in the weight-adjusting process and the rate of pattern recognition is dropped. In this paper, I proposed the enhanced fuzzy ART algorithm that supports the dynamical setting of the vigilance threshold using the generalized intersection operator of fuzzy logic and the weight value being adaptively set in proportional to the current weight change and the previous weight by reflecting the frequency of the selection of winner node. For the performance evaluation of the proposed method, we applied to the recognition of container identifiers from shipping container images. The experiment showed that the proposed method produced fewer clusters than conventional ART2 and fuzzy ART algorithm. and had tile higher recognition rate.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.572-577
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• 1994

The automatic detection of artifacts and vigilance level as for pre-processing of the automatic EEG interpretation are discussed. The equations for detecting artifacts and vigilance level were determined such that they would conform to the procedures that an EEGer (one of the authors, H.S.) usually adopts for visual inspection of the actual EEG record. The automatic EEG interpretation was found to be improved by the newly developed pre-processing method even will artifact contamination or in drowsy condition of the subjects.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.986-988
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• 1995

The ART(Adaptive Resonance Theory) model is self- organized with nonstationary input patterns in real time. But there is a multirun problem caused by fault clustering, or pertubated clustering and confines the advantage of the stationary real-time processing in ART model. In this paper, we propose the incremental vigilance threshold approach to decrease the number of multiruns. The incremental vigilance threshold approach is to learn with incremental vigilance threshold and competition with clusters.