• Proceedings of the Korea Information Processing Society Conference
• /
• 2002.11a
• /
• pp.763-766
• /
• 2002

레이더 영상에서의 물체 위치는 극좌표계로 주어지기 때문에 직각좌표계로 표현되는 일반적인 물체 추적에서의 클러스터링을 통한 물체 추출 방법은 비효율적이다. 본 논문에서는 이러한 레이더 영상의 특성을 고려하여 개선된 ART2클러스터링 기법을 이용하는 방법을 제안하였다. 이진화와 labeling을 통해 추적하고자 하는 물체 외의 물체나 잡영을 제거한 영상에서의 adaptive vigilance parameter를 이용한 ART2 클러스터링 기법의 적용은 추적하고자 하는 물체를 추출함에 있어 우수한 실험 결과를 보였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.11a
• /
• pp.197-202
• /
• 2006

본 논문에서는 퍼지 신경회로망을 사용하여 영상에서 물체를 배경으로부터 추출해내는 방법을 제시하였다. 퍼지 신경회로망의 vigilance parameter를 조정하여 영상을 2개의 클래스로 분류하고, 물체 영역과 배경영역의 Cb와 Cr의 대표값을 추출하였다. 제안한 방법을 사용하여 물체색상의 위치 및 크기와 밝기에 상관없이 물체영역을 추출하였다.

• Proceedings of the KSR Conference
• /
• 2008.11b
• /
• pp.2035-2039
• /
• 2008

In this paper, degrades modes of high-speed trains are deduced and analyzed by using Systems engineering architecture methods for a preceding research of hazard identification and scenarios deduction of the KTX. Moreover, Vigilance System of the high-speed trains is analyzed.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.165-171
• /
• 2011

A Consider the dead man's switch installed in each and every locomotive cab, which support operational safety on railways around the world. The concept is very simple - every 150 to 180 seconds an illuminated push-button demands to be acknowledged so as to know that the Train Driver is alive and active. In the absence of a response over a period of minutes, the vigilance control will automatically apply the train brakes and bring the train to a stand. If we multiply the resetting of the vigilance control 60 times per hour by a 10-hour shift it equals 600 presses of the button during the shift that a Train Driver must pay attention to and acknowledge. This adds a fair bit of pressure on the train driver's job, particularly when he/she is driving through stations, with passengers moving about on platforms in an environment of complex signaling arrangements - all the while looking out for restricting signals. From this perspective, the Vigilance System's demand to be acknowledged every 150/180 seconds is disturbing and can unnecessarily take a driver's attention away from what is happening outside the confines of the cab. A much more dramatic situation can happen when a train driver is driving hour after hour at night when, by Mother's Nature request - people need to sleep. Experience and research shows that the the dead man's switch can be pressed by train driver in a state of deep relaxation and 'micro-sleep'. The vigilance control system which is applied to reduce the drive load considering bio-response multiple unit train is proposed.

• Journal of Korea Multimedia Society
• /
• v.17 no.11
• /
• pp.1325-1334
• /
• 2014

Recently game addiction of young people has become a social issue. Therefore, many studies, mostly surveys, have been conducted to diagnose game addiction. In this paper, we suggest how to distinguish levels of addiction based on EEG. To this end, we first classify four groups by the degrees of addiction to internet games (High-risk group, Vigilance group, Normal group, Good-user group) using CSG (Comprehensive Scale for Assessing Game Behavior) and then measure their Event Related Potential(ERP) in the Go/NoGo Task. Specifically, we measure the signals of P300, N400 and N200 from the channels of the NoGo stimulus and Go stimulus. In addition, we extract distinct features from the discrete wavelet transform of the EEG signal and use these features to distinguish the degrees of addiction to internet games. The experiments in this study show that High-risk and Vigilance group exhibit lower Go-N200 amplitude of Fz channel than Normal and Good-user groups. In Go-P300 and NoGo-P300 of Fz channel, High-risk and Vigilance groups exhibit higher amplitude than Normal and Good-user group. In Go-N400 and NoGo-N400 of Pz channel, High-risk and Vigilance group exhibit lower amplitude than Normal and Good-user group. The test after the learning study of the extracted characteristics of each frequency band from the EEG signal showed 85% classification accuracy.

• Safety and Health at Work
• /
• v.10 no.1
• /
• pp.67-74
• /
• 2019

Background: Few studies have examined the effects of a forward rotating shift pattern on police employee performance and well-being. This study sought to compare sleep duration, cognitive performance, and vigilance at the start and end of each shift within a three-shift, forward rotating shift pattern, common in United Kingdom police forces. Methods: Twenty-three police employee participants were recruited from North Yorkshire Police (mean age, 43 years). The participants were all working the same, 10-day, forward rotating shift pattern. No other exclusion criteria were stipulated. Sleep data were gathered using both actigraphy and self-reported methods; cognitive performance and vigilance were assessed using a customized test battery, comprising five tests: motor praxis task, visual object learning task, NBACK, digital symbol substitution task, and psychomotor vigilance test. Statistical comparisons were conducted, taking into account the shift type, shift number, and the start and end of each shift worked. Results: Sleep duration was found to be significantly reduced after night shifts. Results showed a significant main effect of shift type in the visual object learning task and NBACK task and also a significant main effect of start/end in the digital symbol substitution task, along with a number of significant interactions. Conclusion: The results of the tests indicated that learning and practice effects may have an effect on results of some of the tests. However, it is also possible that due to the fast rotating nature of the shift pattern, participants did not adjust to any particular shift; hence, their performance in the cognitive and vigilance tests did not suffer significantly as a result of this particular shift pattern.

• The Journal of the Korean dental association
• /
• v.39 no.7 s.386
• /
• pp.556-563
• /
• 2001

• Journal of KIISE:Software and Applications
• /
• v.30 no.11
• /
• pp.1072-1079
• /
• 2003

This study is purported for suggesting a new clustering algorithm that enables incremental categorization of numerous documents. The suggested algorithm adopts the natures of the spherical k-means algorithm, which clusters a mass amount of high-dimensional documents, and the fuzzy ART(adaptive resonance theory) neural network, which performs clustering incrementally. In short, the suggested algorithm is a combination of the spherical k-means vector space model and concept vector and fuzzy ART vigilance parameter. The new algorithm not only supports incremental clustering and automatically sets the appropriate number of clusters, but also solves the current problems of overfitting caused by outlier and noise. Additionally, concerning the objective function value, which measures the cluster's coherence that is used to evaluate the quality of produced clusters, tests on the CLASSIC3 data set showed that the newly suggested algorithm works better than the spherical k-means by 8.04% in average.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.106.5-106
• /
• 2001

A method for automatically selecting the electroencephalogram(EEG) segments was developed by grading each segment based on organization of EEG, vigilance level, open versus closed eyes condition and the artifact contamination.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.11a
• /
• pp.180-184
• /
• 1997

This paper presents the fuzzy neural network which utilizes a fuzzified Kohonen learning uses a fuzzy membership value, a function of the iteration, and a intra-membership value instead of a learning rate. The IRIS data set if used to test the fuzzy neural network. The test result shows the performance of the fuzzy neural network depends on k and the vigilance parameter T.