• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.915-936
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• 2017

In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.

• Journal of Korean Home Economics Education Association
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• v.19 no.3
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• pp.61-76
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• 2007

The purpose of the study is to identify and understand problems existing in the middle school home economics practice rooms in Jeju Special Self-Governing Province. The findings are based on the examination and the analysis of the indoor environment and the condition of the facilities and equipment. Study method employs on-site research and a survey. The on-site research was conducted about temperature, humidity, intensity of illumination, and status of teaching instrument in 10 out of 41 middle schools in Jeju Special Self-Governing Province from August 16 to September 30, 2006. Meanwhile, the survey was implemented by mail for 95 teachers in charge of manual training and home economics education in 41 middle schools in Jeju from November 1 to 23, 2005. 64 questionnaires out of total 95 were collected, including those collected during the period of on-site research. Finally, 61 questionnaires which were effective among the answered ones were used for analysis. Collected materials were analyzed with the SPSS Win.12.0 program for frequency, percentile analysis. In conclusion, the study determines that the condition of the home economics practice rooms of the middle school in JSSGP in terms of temperature, humidity, lighting and ventilation is very inadequate. The structure of the practice room represents an inefficient work flow pattern. Further, the facilities and equipment are in a very poor condition because the facilities are old and the retention rate of teaching tools is low. Therefore, to address these problems, the study suggests that improvements on the facilities and equipment should be made and teaching tools should be replenished in accordance with the industry standard.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.829-842
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• 2003

In this Paper, we propose the new face detection and tracking method based on template matching for real-time applications such as, teleconference, telecommunication, front stage of surveillance system using face recognition, and video-phone applications. Since the main purpose of paper is to track a face regardless of various environments, we use template-based face tracking method. To generate robust face templates, we apply wavelet transform to the average face image and extract three types of wavelet template from transformed low-resolution average face. However template matching is generally sensitive to the change of illumination conditions, we apply Min-max normalization with histogram equalization according to the variation of intensity. Tracking method is also applied to reduce the computation time and predict precise face candidate region. Finally, facial components are also detected and from the relative distance of two eyes, we estimate the size of facial ellipse.