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신호진,전은미,권도경,권준석,이철진,Shin, Ho-Jin,Jeon, Eun-Mi,Kwon, Do-kyung,Kwon, Jun-Seok,Lee, Chul-Jin 한국플랜트학회 2021 플랜트 저널 Vol.17 No.3
P&ID(Piping and Instrument Diagram)는 플랜트의 장치 및 계장 정보를 집약적으로 담고 있는, 엔지니어링 핵심도면이다. 한 장의 P&ID에는 심볼로 표현된 수백 여개의 정보들이 존재하며, 이에 대한 디지털 전산화 작업이 수작업으로 진행되고 있어 많은 인력과 시간이 소요된다. 기존 연구들은 CNN 모델을 이용하여 도면 객체 검출에 성공하였으나, 도면 한 장당 약 30분, 인식률은 90% 정도로 현장에서 구현하기에는 부족한 성능이다. 따라서 본 연구에서는 영역 검출과 객체 인식을 동시에 처리하는 1-stage 객체 검출 알고리즘을 제안하였다. 이미지 레이블링 오픈소스 툴을 이용하여 학습 데이터를 구축하고 딥러닝 모델 학습을 통해 도면 내 심볼 이미지 인식 방법을 제안한다. P&ID((Piping and Instrument Diagram) is a key drawing in the engineering industry because it contains information about the units and instrumentation of the plant. Until now, simple repetitive tasks like listing symbols in P&ID drawings have been done manually, consuming lots of time and manpower. Currently, a deep learning model based on CNN(Convolutional Neural Network) is studied for drawing object detection, but the detection time is about 30 minutes and the accuracy is about 90%, indicating performance that is not sufficient to be implemented in the real word. In this study, the detection of symbols in a drawing is performed using 1-stage object detection algorithms that process both region proposal and detection. Specifically, build the training data using the image labeling tool, and show the results of recognizing the symbol in the drawing which are trained in the deep learning model.
패혈증에 의한 급성 신부전의 예견인자로서의 APACHE III prognostic system과 Liano system의 유용성
신호진(Ho Jin Shin),이수봉(Soo Bong Lee),곽임수(Ihm Soo Kwak),나하연(Ha Yeon Rha),송상헌(Sang Heun Song),정현철(Hyun Chul Jung),배우형(Woo Hyung Bae),안승재(Seung Jae Ahn) 대한신장학회 2000 Kidney Research and Clinical Practice Vol.19 No.2
N/A Uncontrolled infection quite often 1eads to systemic inflammatory response syndrome and multi-organ dysfunction syndrome. Despite advances in medical knowledge and technology, the mortality of patient with sepsis is still 35-60%, and even reach up to 50-90% in septic patients having acute renal failure. The purpose of this study was to examine the characteristics and predictive factors of progression to acute renal failure(ARF) in sepsis. We analyzed the bacteriologic and laboratory data of 54 admitted patients with SIRS(systemic inflam-matory response syndrome) at Pusan National University Hospital from July 1997 to July 1999(ARF 23 vs non-ARF 31). Multiple factor which may influence mortality and progression to AEK in sepsis, were evaluated and measured on admission day. The following of results, 1) Of the 54 patients, 23 were ARF group and 31 were non-ARF group. Mean age were,52 years and 51 years. The mortality of ARF group and non-ARF group were 78% and 23%, Urine output, albumin, cholesterol, mean arterial blood pressure and evidence of underlying disease were not statistically different in each group. 2) Although the sources of sepsis could not identified in 9%(ARF), 23%(non-ARF), the others had the primary site of infections ' gastrointestinal tract(35% vs 29%), lung(30% vs 19%), genitourinary tract(9% vs 13%), skin(17% vs 16%). 3) Although statistically not different, gram-posi-tive bacterial infection was more common in ARF group(mainly staphylococcus aureus). Culture negative results were 4 patients(ARF), 1 patient(non- ARF). 4) APACHE III score in ARF group was higher than non-ARF group(48.1±16.5 vs 30.2±15.6). Liafio score in ARF group was higher than non-ARF group(39.1±13.0 vs 28.9±8.3). 5) APACHE III score and Liailo score in non- survivors were higher than survivors(APACHE III score:48.6±15.3 vs 28.1±14.0, Liaho score:37.9±12.0 vs 29.4±9.2) 6) APACHE lII system was positively correlated with Liaho system(r=0.512, p=0.001). In conclusion, APACHE III system and Liaho system were significant predictors of progression to ARF and mortality in sepsis. In the future, prospec-tive and multicenter studies are required to improve the method of treatment and the prognosis in sepsis.
감각 되먹임 종류가 건강한 성인 남성의 올바른 앉은 자세 학습에 미치는 영향
신호진 ( Ho-jin Shin ),김성현 ( Sung-hyeon Kim ),조휘영 ( Hwi-young Cho ) 대한물리의학회 2021 대한물리의학회지 Vol.16 No.4
PURPOSE: The growing number of people exposed to a static sitting posture has resulted in an increase in people with a poor posture out of the optimally aligned posture because of the low awareness of a correct sitting posture. Learning the correct sitting posture by applying sensory feedback is essential because a poor posture has negative consequences for the spine. Therefore, this study examined the effects of the sensory feedback types on learning correct sitting posture. METHODS: Thirty-six healthy adult males were assigned to a visual feedback group, a tactile feedback group, and a visuotactile feedback group to learn the correct sitting posture by applying sensory feedback. The spine angle, muscle activity, and muscle thickness were measured in the sitting position using retro-reflexive markers, electromyography, and ultrasound immediately after, five minutes, and 10 minutes after intervention. RESULTS: The intervention time was significantly shorter in the visuotactile feedback group than the visual feedback group (p < .05). Compared to the pre-intervention, the repositioning error angles of the thoracic and lumbar vertebrae of all groups were reduced significantly immediately after intervention and after five minutes. After 10 minutes, there was a significant difference in the thoracic and lumbar repositioning error angles of the tactile feedback group and the visuotactile feedback group (p < .05). No significant difference was noted at any time compared to the pre-intervention in all groups (p > .05). CONCLUSION: The use of tactile and visuotactile feedback in intervention to correct the sitting posture is proposed.
SAN을 이용한 제한된 버퍼 크기를 갖는 출력큐잉 ATM 스위치 성능평가
장경수,신호진,신동렬,Jang, Kyung-Soo,Shin, Ho-Jin,Shin, Dong-Ryeol 한국정보처리학회 2000 정보처리논문지 Vol.7 No.8
High speed switches have been developing to interconnect a large number of nodes. It is important to analyze the switch performance under various conditions to satisfy the requirements. Queueing analysis, in general, has the intrinsic problem of large state space dimension and complex computation. In fact, The petri net is a graphical and mathematical model. It is suitable for various applications, in particular, manufacturing systems. It can deal with parallelism, concurrence, deadlock avoidance, and asynchronism. Currently it has been applied to the performance of computer networks and protocol verifications. This paper presents a framework for modeling and analyzing ATM switch using stochastic activity networks (SANs). In this paper, we provide the ATM switch model using SANs to extend easily and an approximate analysis method to apply A TM switch models, which significantly reduce the complexity of the model solution. Cell arrival process in output-buffered Queueing A TM switch with finite buffer is modeled as Markov Modulated Poisson Process (MMPP), which is able to accurately represent real traffic and capture the characteristics of bursty traffic. We analyze the performance of the switch in terms of cell-loss ratio (CLR), mean Queue length and mean delay time. We show that the SAN model is very useful in A TM switch model in that the gates have the capability of implementing of scheduling algorithm. 네트워크 연결을 위한 고속 스위치는 계속해서 발달하여 왔으며, 스위치가 필요한 성능을 내는가를 여러 조건으로 분석하는 것은 중요한 일이다. 하지만, 복잡한 구조를 가진 시스템을 모델링하여 그 성능을 측정하는 것은 쉬운 일이 아니다. 큐잉이론을 이용한 모델링은 큰 상태 공간을 고려해야 됨은 물론이고 성능평가에 있어서도 복잡한 계산과정을 수행해야 하지만, SAN(Stochastic Activity Networks)에 의한 모델링과 성능평가는 그에 비해 간단하다는 장점이 있다. 본 논문의 목적은 출력포트에 큐를 갖는 고속 ATM 스위치를 확장된 SPN(Stochastic Petri Net)인 SAN을 이용해 모델링하고, 셀 도착 과정은 실제 트래픽과 유사한 특징을 가지고 있는 MMPP(Markov Modulated Poisson Process)로 모델링하여 그 성능을 평가하는데 있다. MMPP 모델을 이용한 버스티 트래픽을 고겨한 성능측정과 아울러 SAN의 장점을 이용한 확장이 용이한 스위치 모델을 보이고자 한다. 제한된 버퍼 크기를 갖는 출력 큐잉 ATM 스위치에 도착하은 셀은 포아송 도착 과정에서는 정확히 표현할 수 없는 버스티 특징을 표현할 수 있어 좀더 실제 트래픽에 가까운 MMPP로 모델링한다. SAN 모델은 UltraSAN 소프트웨어 패키지를 이용해 대기행렬의크기, 지연시간 그리고 셀 손실률에 대한 성능을 측정한다.