• Title/Summary/Keyword: 건설현장의 빛환경

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A Comparative Study on the Semantic and Functional Appropriateness of the Safety Sign Color Standards in Construction Sites (건설안전표지 색채기준의 의미적·기능적 적절성 판단 및 개선방안 도출을 위한 국가 간 비교법제 연구)

  • Jang, YeEun;Yi, June-Seong
    • Journal of the Korea Institute of Construction Safety
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    • v.1 no.1
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    • pp.22-30
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    • 2018
  • Construction accidents in Korea are continuously increasing. Safety signs with high visibility color can diminish such accidents in dangerous places. In order for safety color to be more effective as a global communication means in construction sites, it needs to be checked out whether safety color standard reflect the characteristics of construction industry such as worker or work environment. This paper compared safety color standards among Korea, the US, the UK, and Australia. First, blue color was included in all, which should be corrected considering aged workers increasing in construction industry. Because with age, the ability to distinguish between blue, purple, and gray colors decreases. Second, Korea, which has only single code designated to safety colors, should find alternatives like tolerance to be applicable to a variety of light environments on construction sites, as the contrast which affect the visibility may decrease in dark conditions.

A Study on the Data Organization of Specification Information for reference of Design Information (설계정보 참조를 위한 시방정보의 자료구조화에 관한 연구)

  • Kim Jae-hyun;Song Younk-Kyou;Kim Uk
    • Korean Journal of Construction Engineering and Management
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    • v.2 no.3 s.7
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    • pp.92-100
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    • 2001
  • The architectural drawing, construction project specification, etc. are included in the contract of a documents. However, construction project specification, for being documentation, is not utilized to such an extent. The reason is that specification information is difficult in collecting information in relation to the architectural drawing, material finishing list and other architectural information. Therefore, an integrated model, which can be associated with other architectural information, is needed, and a DB based on this integrated model must be established in order for it to be utilized in design, construction, and management. The DB, which is established through this process, must be updated according to modification in design, and construction. Furthermore the specification must be in document on the web for reference. Consequently in this research, the structure of integrated model has been introduced, and it has made the search and preparation of the integrated model on the Internet, using the specification information DB established for the mutual reference of DB, possible. The improvements of construction project specification standards are expected by this system. Also, it will bring about Improvements upon claim prevention, and design, construction, management qualities. Furthermore, it will make the use of information more convenient in practical business such as order agency, design service and building site.

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Parameter Analysis for Super-Resolution Network Model Optimization of LiDAR Intensity Image (LiDAR 반사 강도 영상의 초해상화 신경망 모델 최적화를 위한 파라미터 분석)

  • Seungbo Shim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.137-147
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    • 2023
  • LiDAR is used in autonomous driving and various industrial fields to measure the size and distance of an object. In addition, the sensor also provides intensity images based on the amount of reflected light. This has a positive effect on sensor data processing by providing information on the shape of the object. LiDAR guarantees higher performance as the resolution increases but at an increased cost. These conditions also apply to LiDAR intensity images. Expensive equipment is essential to acquire high-resolution LiDAR intensity images. This study developed artificial intelligence to improve low-resolution LiDAR intensity images into high-resolution ones. Therefore, this study performed parameter analysis for the optimal super-resolution neural network model. The super-resolution algorithm was trained and verified using 2,500 LiDAR intensity images. As a result, the resolution of the intensity images were improved. These results can be applied to the autonomous driving field and help improve driving environment recognition and obstacle detection performance