• Title/Summary/Keyword: 보행자 이동

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A Critical Reconsideration on the Function and Meaning of Follies in Gwangju - Focused on the First Gwangju Follies - (광주 폴리의 기능과 의미에 대한 비판적 재고 - 제 1차 광주폴리를 중심으로 -)

  • Han, Sung-Mi
    • Journal of the Korean Institute of Landscape Architecture
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    • v.43 no.6
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    • pp.41-51
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    • 2015
  • The purpose of the Follies that were constructed for the Gwangju-Biennale were for urban regeneration, to activate the empty old-town areas, and to strengthen the tradition and sense of place of the city. However, the ten Follies constructed around the wall of the old castle reveal many problems including that of leaving Follies alone instead of actively using them, damage to shop-keepers nearby, and pedestrian inconvenience, which is different from the original purposes. This study is meant to help understand the source of the negative phenomena, and to offer plans that will be conductive to the role of urban regeneration through activating the Follies and the spaces around them. As results of the investigation, there was no context giving uniformity among the various Follies. Also, the study showed that the insufficience of designers' understanding of the circumference near the Follies and lack of a consensus between the citizens and designers in the process of making the Follies. The crucial solution for solving these problems, and bringing to life the original purpose of creating the Follies was derived as applying "human activity" to the Follies. This study suggested 'street performance' as an effective device for application to human activity. While a Folly has no fixed function, the development of space program categories based on the applied characteristics of each Folly, and the simulation thereof showed effective potential for attracting people and activating those stagnated spaces. Recently, Gwangju city depicted the second Follies in applications such as reading roon, toilet, and movable food cart, which have clear purpose and different characteristics from the first ones. However, the first Follies will not be moved or demolished. As they are located around the National Asia Culture Center, some of them are supposed to be used to view the center. Consequently, a counterplan for the continuous and efficient use of those Follies is needed. Gwangju has a plan for the installation of 100 Follies throughout the city and it is expected that this study will be a meaningful guide line for improved Follies in the future.

Development of a deep-learning based tunnel incident detection system on CCTVs (딥러닝 기반 터널 영상유고감지 시스템 개발 연구)

  • Shin, Hyu-Soung;Lee, Kyu-Beom;Yim, Min-Jin;Kim, Dong-Gyou
    • 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.