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정적 변형률 데이터를 사용한 CNN 딥러닝 기반 PSC 교량 손상위치 추정
한만석,신수봉,안효준,Han, Man-Seok,Shin, Soo-Bong,An, Hyo-Joon 한국BIM학회 2020 KIBIM Magazine Vol.10 No.2
As the number of aging bridges increases, more studies are being conducted on developing effective and reliable methods for the assessment and maintenance of bridges. With the advancement in new sensing systems and data learning techniques through AI technology, there is growing interests in how to evaluate bridges using these advanced techniques. This paper presents a CNN(Convolution Neural Network) deep learning based technique for evaluating the damage existence and for estimating the damage location in PSC bridges using static strain data. Simulation studies were conducted to investigate the proposed method with error analysis. Damage was simulated as the reduction in the stiffness of a finite element. A data learning model was constructed by applying the CNN technique as a type of deep learning. The damage status and its location were estimated using data set built through simulation. It was assumed that the strain gauges were installed in a regular interval under the PSC bridge girders. In order to increase the accuracy in evaluating damage, the squared error between the intact and measured strains are computed and applied for training the data model. Considering the damage occurring near the supports, the results of error analysis were compared according to whether strain data near the supports were included.
일개 대학병원 내 한방물리요법을 받은 환자들의 후향적 의무기록 분석
황의형 ( Eui Hyoung Hwang ),이현엽 ( Hyeon Yeop Lee ),허광호 ( Kwang Ho Heo ),조현우 ( Hyun Woo Cho ),황만석 ( Man Seok Hwang ),신미숙 ( Mi Suk Shin ),김정화 ( Jeong Hwa Kim ),박성하 ( Seong Ha Park ),신병철 ( Byung Cheul Shin 한방재활의학과학회 2014 한방재활의학과학회지 Vol.24 No.1
ObjectivesThe aim of this study was to offer the fundamental data for the physical thera-pies of Korean medicine through analyse the database of one university hospital.MethodsAs this study was retrospective analysis, following items were selected and an-alysed in the electronic medical record (EMR) database. (1) sex, (2) inpatient or outpatient, (3) medical department, (4) diagnosis, (5) kind of insurance.ResultsAlthough all kind of physical therapies were used, interferential current therapy (ICT) was the most used physical therapy. And department of rehabilitation medicine of Korean medicine prescribed physical therapies most among the 8 specialty departments. As physical therapies were used in various kinds of diseases, they were especially used in musculoskeletal diseases and nervous system diseases.ConclusionsThe analysis of actual condition of using physical therapies in a real clinical setting of Korean medicine could be a useful fundamental data for the application of mod-ernized physical therapies. (J Korean Med Rehab 2014;24(1):55-63)
비급성 요통에 대한 무작위대조군 임상연구 수행을 위한 추나표준화 설문조사 보고
김병준,황의형,허광호,황만석,허인,송윤경,이정한,고연석,박태용,조재흥,이은정,문수정,하인혁,이민호,신병철,Kim, Byung-Jun,Hwang, Eui-Hyoung,Heo, Kwang-Ho,Hwang, Man-Suk,Heo, In,Song, Yun-Kyung,Lee, Jung-Han,Ko, Youn-Seok,Park, Tae-Young,Cho, Jae-He 척추신경추나의학회 2015 척추신경추나의학회지 Vol.10 No.2
Objectives : To find out the standardized chuna manual technique for non-acute low back pain. Methods : The survey questions were developed by the consensus from the professor who major in Rehabillitation Medicine of Korean Medicine(RMKM). August 15th to september 1st 2015, the questionnaire was given to 23 RMKM doctors by e-mail. 20(90.9%) the questionnaire were retrieved out. Standardized technique of chuna were selected through experts consesus based on questionaire results. Results : Two essential techniques and two selective techniques were selected as standardized Chuna manual technique for lumbar region. Six essential technique and one selective technique were selected as standardized Chuna manual technique for iliac region. Conclusions : This is the first consensus of experts opinion for Chuna manual technique for operating randomized controlled trials(RCT). These reports are helpful for Korean Medicine doctor who operate Chuna manual technique and expected to make clinical evidence of Chuna manual medicine
전동휘 ( Dong Hwi Jeon ),이은정 ( Eun Jung Lee ),소현우 ( Hyun Woo So ),황만석 ( Man Suk Hwang ),유정은 ( Jeong Eun Yoo ),박양춘 ( Yang Chun Park ),정인철 ( In Chul Jung ),오민석 ( Min Seok Oh ) 대한한의학회 한방재활의학과학회 2017 한방재활의학과학회지 Vol.27 No.2
Objectives The aim of this study was to develop a standard tool of pattern identification for Knee Osteoarthritis, which will be applied to clinical research. Methods The advisor committee for this study was organized by 11 panel of experts (Korean Rehabilitation Medicine professors, Acupuncture and Moxibustion professors belonging to Korean Medicine colleges, Principal Researcher of Korea Institute of Oriental Medicine, Doctor of Korean medicine). The pattern identifications and symptoms for this tool were extracted from published Korean and Chinese literature. Through the discussion among internal experts and consultation from advisors, the Instrument on Pattern Identifications for Knee Osteoarthritis was developed. Results 1) Five pattern identifications (The Wind, Chill, and Moisture, The Moist-Heat, Blood Stasis, Yang Deficiency of Spleen and Kidney, Yin Deficiency of Liver and Kidney) were set for the tool. 2) The mean weights which represent the importance of each symptom and scored on a hundred-point scale was obtained. 3) The Instrument on Pattern Identifications for Knee Osteoarthritis was designed in the self-reporting format composed of 46 questions. Conclusions The Instrument on Pattern Identifications for Knee Osteoarthritis was created through this study. Though this study is not proved about validity, reliability, the instrument of pattern identification for Knee Osteoarthritis is meaningful and expected to be applied to the subsequent. (J Korean Med Rehabil 2017;27(2):77-91)