• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• 한국의학물리학회지:의학물리
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• 제18권2호
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• pp.98-106
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• 2007

2005년 6월 연세의료원 세브란스병원에서는 진단목적으로 20대의 5 mesa 화소 Totoku ME511L 평판 LCD 표시장치를 추가하여 PACS를 확장하였다. 20대의 Totoku ME511L 표시장치를 대상으로 반사, 휘도 반응, 휘도 공간 의존, 분해능, 잡음, 베일링 그레어, 그리고 색도 항목에 대하여 AAPM TG 18보고서에 기준하여 정량적인(또는 시각적인) 인수검사를 실시하였다. 측정에 사용된 장치는 색도를 측정할 수 있는 만원경식 휘도계, 조도계, 반사 측정에 필요한 빛 선원, 빛 차단 장치, 그리고 TG18 테스트 패턴들이었다. 선택된 8대의 표시장치에 대한 평균 확산 반사계수($R_d$)는 $0.019{\pm}0.02sr^{-1}$이었다. 휘도 반응 검사에서, 휘도비(LR), 최대 휘도 변이($L_{max}$), 그리고 최대 대조도 반응 변이는 각각 $550{\pm}100,\;2.0{\pm}1.9%$, 그리고 $5.8{\pm}1.8%$이었다. 휘도 균일도 검사에서, 최대 휘도 변이는 TG18-UNL10 테스트 패턴의 10% 휘도에 대하여 $14.3{\pm}5.5%$이었다. 분해능 측정은 휘도 측정법으로 수행하였으며 중심에서 퍼센트 휘도(${\Dalta}L$)는 $0.94{\pm}0.64%$이었다. 시각적인 방법의 잡음측정의 모든 경우에서, 중앙 및 주위 4사분면에서 가장 작은 것을 제외하고 15개의 모든 정사각형의 표적을 인식할 수 있었다. 글레어 비(GR)은 $12,346{\pm}1,995$이었다. 최대 색도 균일도 지표(D)는 $0.0025{\pm}0.0008$이었다. 또한 국내 실정에 적합한 진단용 표시장치의 정도관리 가이드라인 연구 결과를 제시하였다. 모든 인수검사 결과는 AAPM TG18 보고서 기준에 포함되어 진단 목적으로 사용하기에 적합하였다. 결론으로 인수검사는 표시장치가 진단에 사용하기에 적합한 성능임을 알려줄 뿐만 아니라 정도관리의 가이드라인, 최적 판독 환경, 그리고 표시장치의 교체시기를 결정하여주는 중요한 역할을 할 수 있다.