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이종재,윤현조,정연준,김재천,Lee, Jong-Jae,Youn, Hyun-Jo,Jeong, Yeoun-Jun,Kim, Jae-Chun 대한소아외과학회 2001 소아외과 Vol.7 No.2
The effectiveness of operative and non-operative management for postoperative adhesive ileus in children has been discussed. This study reviews the clinical characteristics and the treatment consequences of adhesive ileus in our institution. Department of Surgery of Chunbuk National University Hospital, retrospectively. A total of 62 cases of post-operative small bowel obstruction treated between January 1975 and December 1998 under the 15 years of age are included in this study. The patients were divided into two groups, operative(n=26) and non-operative(n=36) groups. The prevalent age was between 11 and 15 years(28 cases; 45.2 %), and the most common previous operation was appendectomy(28 cases; 45.2 %). The most common operative procedures were adhesiolysis(17 cases; 65.4 %). The interval between admission and operation was 1 day in 11 cases(42.3 %). The most common site of adhesion was the ileum in 13 cases(50.0 %) and band constriction was the most frequent pattern(8 cases; 30.8 %). Intestinal resection was significantly high in delayed operations of more than four days, in the patients with three or more classical signs of strangulation(fever, tachycardia, leukocytosis, abdominal pain, rebound tenderness), and in the cases of complete obstruction on plain abdomen film(p < 0.05). In conclusion, operation should be considered in cases with three or more signs of strangulation, no clinical improvement for over four days of conservative treatment, and signs of complete obstruction on plain abdomen film during the observation periods.
An Overview of Information Processing Techniques for Structural Health Monitoring of Bridges
이종재,박영수,윤정방,구기영,이진학,Lee, Jong-Jae,Park, Young-Soo,Yun, Chung-Bang,Koo, Ki-Young,Yi, Jin-Hak Computational Structural Engineering Institute of 2008 한국전산구조공학회논문집 Vol.21 No.6
교량 건전성 모니터링은 응답 데이터를 활용한 구조모델링기술, 신호분석, 정보처리 기술의 발전에 따라 손상추정 및 안전성평가와 함께 중요한 연구주제로 부각되었다. 교량 모니터링 시스템은 일반적으로 센서, 데이터 취득장비, 전송시스템 등과 같은 하드웨어와 신호처리, 손상추정, 전시 및 데이터 관리 등과 같은 소프트웨어로 구성된다. 본 논문에서는 교량의 건전도 모니터링을 위한 정보처리기술에 대한 연구 개발 활동을 정리하였다. 교량 건전성 모니터링의 과정에 대한 간단한 소개와 함께, 다양한 신호처리 및 손상추정 알고리즘을 포함한 정보처리기법에 대해서 소개하였다. 현 교량 건전성 모니터링 시스템에서의 주요 문제점과 향후 연구개발활동을 논의하였다. The bridge health monitoring has become an important research topic in conjunction with damage assessment and safety evaluation of structures owing to the improvement of structural modeling techniques incorporating response measurements and the advancements in signal analysis and information processing capabilities. The bridge monitoring systems are generally composed of hardwares such as sensors, data acquisition equipment, data transmission systems, etc, and softwares such as signal processing, damage assessment, display and management, etc. In this paper, the research and development(R&D) activities on the information processing for structural health monitoring of bridges are reviewed. After a brief introduction to the process of bridge health monitoring, various information processing techniques including various signal processing and damage detection algorithms are introduced in detail. Several challenges addressing critical issues in the current bridge health monitoring system and future R&D activities are discussed.
이종재,윤정방,Lee Jong-Jae,Yun Chung-Bang 한국전산구조공학회 2006 한국전산구조공학회논문집 Vol.19 No.2
교량의 손상추정을 위한 구조계 규명기법은 신호취득시스템 및 정보처리기술의 발전과 함께 최근에 많은 연구개발이 이루어지고 있다. 신경망기법이나 유전자 알고리즘과 같은 소프트컴퓨팅 기법은 뛰어난 패턴인식성능 때문에 손상추정 문제에 활발히 활용되고 있다. 본 연구에서는 모드계수를 활용한 신경망기법기반 손상추정을 수행하였으며, 신경망을 훈련시키기 위한 훈련패턴을 생성하는 해석모델에서의 불확실성을 효과적으로 고려할 수 있는 방법을 제시하였다. 해석모델의 불확실성 대하여 민감하지 않은 입력자료인 손상 전 후의 모드형상의 차 또는 모드형상의 비를 신경망의 입력자료로 활용하였다. 단 순보와 다주형교량에 대한 수치예제를 통하여 본 연구에서 제시한 기법의 타당성 및 적용성을 검증하였다. The use of system identification approaches for damage detection has been expanded in recent years owing to the advancements in data acquisition system andinformation processing techniques. Soft computing techniques such as neural networks and genetic algorithm have been utilized increasingly for this end due to their excellent pattern recognition capability. In this study, damage detection of bridge structures using neural networks technique based on the modal properties is presented, which can effectively consider the modeling uncertainty in the analysis model from which the training patterns are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness and applicability of the proposed method.
이종재 ( Lee¸ Jong-jae ) 한국구조물진단유지관리공학회 2008 한국구조물진단유지관리공학회 학술발표대회 논문집 Vol.12 No.1
An accurate and practical strength estimation method that can be used before the placement of concrete is highly desirable. In this study, the estimation of the concrete strength is performed using support vector regression (SVR) on the basis of the mix proportion data of two ready-mixed concrete companies. Then, the estimation performance of the SVR is compared with that of artificial neural network (ANN). The SVR method have been proven to be very efficient in terms of estimation accuracy as well as computational time, and very practical in terms of training rather than the explicit regression analyses and the ANN techniques.