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딥러닝을 활용한 BIM 객체정보기반의 벽마감 구조틀 부재 수량 예측모델에 관한 연구
박도윤 ( Park Do-yoon ),윤석헌 ( Yun Seok-heon ) 한국건축시공학회 2022 한국건축시공학회 학술발표대회 논문집 Vol.22 No.1
The work of modeling and calculating the quantity of detailed parts requires a lot of time and effort. However, The information of BIM Model can be used to predict the amount of uncreated parts with Deep Learning. In this study, Deep Learning was used to predict the total length of the member of frame that was not created. As a result, it was confirmed that the error rate was inside or outside 3%. And predicting other components in this way will increase productivity in Architectural field.
편성익 ( Sung Ik Pyeon ),송근암 ( Geun Am Song ),백동훈 ( Dong Hoon Baek ),김광하 ( Gwang Ha Kim ),이봉은 ( Bong Eun Lee ),이성준 ( Seong Jun Lee ),윤정빈 ( Jung Bin Yoon ),한성용 ( Sung Yong Han ),박도윤 ( Do Youn Park ) 대한소화기학회 2017 대한소화기학회지 Vol.69 No.2
The gastrointestinal tract is the most common site of extra-nodal non-Hodgkin lymphoma. However, the incidence of primary rectal lymphoma is extremely rare. Among the primary gastrointestinal lymphomas, follicular lymphoma has been described as a rare disease. It is difficult to diagnose rectal lymphoma due to its variable growth patterns and inadequate biopsies. Majority of patients with rectal lymphoma have non-specific symptoms or negative biopsies, often delaying the diagnosis. Our patient is a 62-year-old female. Two sessile and smooth subepithelial lesions with a yellowish normal mucosa were found on a screening colonoscopy. The initial mucosal biopsy finding was chronic inflammation, but we were highly suspicion of malignancy; we performed an endoscopic mucosal resection. Herein, we present a rare case of rectal follicular lymphoma diagnosed by endoscopic mucosal resection with a literature review. (Korean J Gastroenterol 2017;69:139-142)