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정영준 대한이비인후과학회 2017 대한이비인후과학회지 두경부외과학 Vol.60 No.10
Epiphora is an overflow of tears onto the face and mainly occurs secondary to abnormal excretory system such as nasolacrimal duct obstruction (NLDO), which could be congenital or acquired. In past years, patients with NLDO have been usually managed by ophthalmologists using external dacryocystorhinostomy (EX-DCR) which has been considered the gold standard of treatment. Recently, the advancement of nasal endoscope and endoscopic sinus surgery has contributed to perform endoscopic DCR (EN-DCR), which now offers comparable success rate to EX-DCR with many advantages. ENT surgeons are familiar with intranasal anatomy and nasal endoscope handling rather than ophthalmologists. Therefore, these advantages lead to more ENT surgeons performing endoscopic DCR. However, the learning curves exist to reach a favorable success rate because surgical technique should be delicate in the narrow nasal cavity. This paper attempts to describe management of epiphora from ENT perspective, focus on surgical anatomy, evaluation modalities and update on endoscopic technique and surgical outcome compared with EX-DCR. This present review would serve as a guide for beginners and increase their confidence with endoscopic anatomy and correct management of epiphora including EN-DCR procedures. Korean J Otorhinolaryngol-Head Neck Surg 2017;60(10):481-90
개방형 SW를 이용한 IoT 네트워크 성능시험기 개선에 관한 연구
정영준,정이도,이성화,김진태 한국인터넷방송통신학회 2023 한국인터넷방송통신학회 논문지 Vol.23 No.6
본 연구는 최근 다양화, 대규화 되어가는 IoT시스템을 위한 시험기 개선에 관한 것으로 IoT성능시험기의 패킷 처리 성능개선, 트래픽 프로토콜 생성과 동작에 유연성을 확보하는 방안에 대한 것이다. 본 연구의 목표는 고도화되어 가는 대용량 IoT 네트워크 시스템에서 데이터 트래픽 전송의 안정성을 사전에 검증하고 성능을 측정하는 개방형 소프트웨어인 DPDK기반 고속 IoT 네트워크 성능시험 시스템을 설계하는 것이다. DPDK 기반 트래픽 발생기를 이용하여 고속 IoT 성능시험기의 기본 구성을 설계하였으며 실험을 통해 해당 시스템 적용시 트래픽 모델링하고 패킷생성능력의 기대효과를 제시하였다.
정영준,이상익,이종혁,이드아함드파지,서병훈,김동수,서예진,최원 한국농공학회 2022 한국농공학회 학술대회초록집 Vol.2022 No.-
Surrogate modeling of physical systems can offer an advantage in terms of computational cost compared to simulations; therefore, it can help some tasks that require a lot of repetitive simulations regarding similar physical systems (e.g. design optimization, uncertainty analysis, unknown parameter estimation) Data-driven surrogate models, however, require a massive amount of labeled data, which is often very hard to obtain by simulations or in-situ experiments. They also demonstrate relatively poor performance when interpreting unseen problems during training processes (i.e. out-of-distribution). In this study, we propose an improved hybrid surrogate model by integrating the physics-informed deep learning method with the general data-driven black-box model. The proposed hybrid model, pure data-driven model, and pure physics-informed model are compared when solving various problems. The prediction accuracies and applicability of the aforementioned models are compared with varying model parameter sizes and training dataset sizes while interpreting in-distribution and out-of-distribution tasks.
정영준,좌종근 濟州大學校 情報通信硏究所 2000 情報通信硏究所論文集 Vol.3 No.-
In this paper. the Γ type eqivalent circuit is used to analyze the steady state characteristics of induction motor driven by inverter source. The base tests for equivalent circuit parameters of induction motor are a no-load test by rated frequency (60Hz) and a blocked rotor test by 25% of rated frequency (15Hz) which are perfomed with inverter source. and measurement of the de resistance of the stator winding. To determine more accurate parameters, four simultaneous equations obtained from equivalent circuit of the no-load test and blocked rotor test are solved by using initial values which are evaluated from simplifed equivalent circuits. The induction motor performances are computed by using these parameters and compared with measured values of the tested motor. Then it is found that the compared results show good agreement between them.
베이지안 딥러닝 기법을 이용한 확률적 적설심 예측 모델 개발
정영준,최원,이종혁,서병훈,김동수,서예진,이상익 한국농공학회 2022 한국농공학회논문집 Vol.64 No.6
Heavy snow damage can be prevented in advance with an appropriate security system. To develop the security system, we developed a model thatpredicts snow depth after a few hours when the snow depth is observed, and utilized it to calculate a failure probability with various types ofgreenhouses and observed snow depth data. We compared the Markov chain model and Bayesian long short-term memory models with varying inputdata. Markov chain model showed the worst performance, and the models that used only past snow depth data outperformed the models that used otherweather data with snow depth (temperature, humidity, wind speed). Also, the models that utilized 1-hour past data outperformed the models that utilized3-hour data and 6-hour data. Finally, the Bayesian LSTM model that uses 1-hour snow depth data was selected to predict snow depth. We comparedthe selected model and the shifting method, which uses present data as future data without prediction, and the model outperformed the shifting methodwhen predicting data after 11-24 hours.
정영준,문태현,김인상,안진철,강정욱 대한이비인후과학회 2009 대한이비인후과학회지 두경부외과학 Vol.52 No.2
Background and Objectives:To analyze the viability of chondrocytes according to different degrees of crushing and to investigate the mechanism of cell death in the crushed cartilage. Subjects and Method:Septal cartilages were obtained from 22 patients and cartilage pieces were allocated to four groups;normal, mildly crushed, moderately crushed and severely crushed. The cartilage specimens were stained with hematoxylin-eosin and examined under light microscope. The viability of the chondrocytes and the mechanism of cell death were assessed using confocal laser scanning microscopy. Results:As crushing intensity increased, chondrocyte viability significantly decreased. The mechanism of cell death was mainly due to necrosis rather than apoptosis. Conclusion:The viability of chondrocytes in the crushed cartilage depends on the degree of crushing. The mechanism of cell death after crushing is mainly necrosis. Therefore, for the clinical use of the crushed cartilage, slight overcorrection and standardization of the degree of crushing are recommended.