• 대한전기학회논문지:전력기술부문A
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• 제48권11호
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• pp.1365-1373
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• 1999

In many countries including Korea, in order to transmit the more electric power, the higher transmission line voltage is inevitable. So, a rapid reclosing scheme is important for EHV/UHV transmission lines to ensure requirements for high reliability of main lines. A critical aspect of reclosing operation is the extinction of the secondary arc since it must extinguish before successful reclosure can occur. Therefore the accurate simulation techniques of arcing faults are of importance. And successful reclosing switching can be accomplished by adopting a proper method such as HSGS and hybrid scheme to reduce the secondary arc extinction time. First of all, this paper discusses a suggested arc model, which have time dependent resistance for primary arc and piecewise linear approximated arc model for secondary arc. And this simulation technique is applied to Korean 765 kV transmission lines. Also hybrid scheme is simulated and evaluated for the purpose of shortening dead time. For adaptive reclosing scheme, variable dead time control algorithm is suggested. Two kinds of algorithm are tested. One is max tracking algorithm and the other is rms tracking algorithm. According to simulation results, rms tracking has less errors than max tracking. Therefore rms tracking is applied to Korean 765 kV transmission lines with hybrid scheme.

• 한국멀티미디어학회논문지
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• 제25권11호
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• pp.1653-1671
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• 2022

Crop diseases affect crop production, more than 30 billion USD globally. We proposed a classification study of crop species and diseases using deep learning algorithms for corn, cucumber, pepper, and strawberry. Our study has three steps of species classification, disease detection, and disease classification, which is noteworthy for using captured images without additional processes. We designed deep learning approach of deep learning convolutional neural networks based on Mask R-CNN model to classify crop species. Inception and Resnet models were presented for disease detection and classification sequentially. For classification, we trained Mask R-CNN network and achieved loss value of 0.72 for crop species classification and segmentation. For disease detection, InceptionV3 and ResNet101-V2 models were trained for nodes of crop species on 1,500 images of normal and diseased labels, resulting in the accuracies of 0.984, 0.969, 0.956, and 0.962 for corn, cucumber, pepper, and strawberry by InceptionV3 model with higher accuracy and AUC. For disease classification, InceptionV3 and ResNet 101-V2 models were trained for nodes of crop species on 1,500 images of diseased label, resulting in the accuracies of 0.995 and 0.992 for corn and cucumber by ResNet101 with higher accuracy and AUC whereas 0.940 and 0.988 for pepper and strawberry by Inception.

• Wind and Structures
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• 제28권6호
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• pp.381-388
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• 2019

This paper described the application of Geospatial Analysis in determining mean wind speed, $V_h$ for wind load calculation imposed to electrical transmission tower structural design. The basic wind speed data on available station obtained from Malaysian Meteorology Department is adjusted by considering terrain and ground roughness factor. The correlation between basic wind speed, terrain factor and ground roughness stated in EN-50341-1 is used to obtain the $V_h$ for overhead transmission line elements 50 m above ground. Terrain factor, $k_r$ and ground roughness, $z_0$ in this study are presented by land use types of study area. Wind load is then calculated by using equation stated in design code EN-50341-1 by using the adjusted mean wind speed. Scatter plots of $V_h$ for different $k_r$and $z_0$ are presented in this paper to see the effect of these parameters to the value of $V_h$. Geospatial analysis is used to represent the model of $V_h$. This model can be used to determine possible area that will subject to wind load which severe to the stability of transmission tower and transmission line.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.206-214
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• 2022

The way to measure the extent of damage from floods and droughts is to identify changes in the extent of water systems. In order to effectively grasp this at a glance, satellite images are used. KOMPSAT-5 uses Synthetic Aperture Radar (SAR) to capture images regardless of weather conditions such as clouds and rain. In this paper, various deep learning models are applied to perform semantic segmentation of the water system in this SAR image and the performance is compared. The models used are U-net, V-Net, U2-Net, UNet 3+, PSPNet, Deeplab-V3, Deeplab-V3+ and PAN. In addition, performance comparison was performed when the data was augmented by applying elastic deformation to the existing SAR image dataset. As a result, without data augmentation, U-Net was the best with IoU of 97.25% and pixel accuracy of 98.53%. In case of data augmentation, Deeplab-V3 showed IoU of 95.15% and V-Net showed the best pixel accuracy of 96.86%.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.634-636
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• 2021

이번 연구에서는 피드백 전계 효과 트랜지스터(feedback field-effect transistor, FBFET)의 메크로 모델링에 대한 연구를 SPICE 시뮬레이터를 통해 진행했다. 기존에 제시된 FBFET의 메크로 모델은 두 개의 회로로 구성돼 있으며, 하나는 전하 축적 기능을 구현한 회로이며 다른 하나는 전류 생성 회로이다. 기존 전류 생성회로는 I_DS-V_GS 특성만 구현 가능하여 회로 예측에 어려움이 있다. 이를 해결하기 위해 전류 생성 회로에 다이오드를 추가함으로 I_DS-V_DS 특성까지 구현 가능한 모델을 제시한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.77.1-77
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• 2002

Platelets arrest bleeding and repair damaged blood vessels. The purpose of this paper is to formulate a mathematical model for the control of platelet adhesion within the vasculature consistent with experimental findings, particularly those of Frenette, Ruggeri , Savage, Yuan, Lawrence and Springer. In addition to providing some, albeit rudimentary, insight into the behavior of platelets, a numerical simulation of this theoretical model may be useful in a systematic study of pathological cases. Glycoprotein receptor complex (GPIb/V/IX), found on the platelet surface membrane, binds to the adhesive protein and ligand von Willebrand factor (vWf), located within the sub-endothelium. The binding...

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.9-10
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• 2011

• 한국산업정보학회논문지
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• 제15권2호
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• pp.23-30
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• 2010

본 논문은 WCDMA, HSDPA 및 WiBro와 같은 광역무선통신망 기반의 V2I2V 차량통신시스템을 구현하여 차량통신시스템의 실제 도로주행 실험을 통해 이동차량과 위치관리서버 사이의 다양한 성능인자에 대한 실험적 성능을 측정하였다. GPS가 탑재된 이동차량 내 클라이언트와 각 이동차량의 위치 추적을 위한 위치 관리 서버 사이의 RTT, 종단간 전달지연 및 기타 성능인자들을 측정하였다. 이동차량이 도심지에서의 운행 시 차량의 이동속도별, 광대역통신망의 종류별 성능인자들을 측정하고 분석하였다. 본 연구 결과는 광역무선통신망 기반의 차량통신시스템을 이용한 서비스 지원 시, 차량통신을 이용한 교통 안전정보 서비스의 지원 가능성을 판단할 수 있는 기초 자료로 활용할 수 있을 것이다.

• 자동차안전학회지
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• 제15권4호
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• pp.16-22
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• 2023

This paper presents a proactive longitudinal motion planning algorithm for improving the safety of an automated bus. Since the field of view (FOV) of the autonomous vehicle was limited depending on onboard sensors' performance and surrounding environments, it was necessary to implement vehicle-to-vehicle (V2V) communication for overcoming the limitation. After a virtual V2V-equipped target was constructed considering information obtained from V2V communication, the reference motion of the ego vehicle was determined by considering the state of both the V2V-equipped target and the sensor-detected target. Model predictive control (MPC) was implemented to calculate the optimal motion considering the reference motion and the chance constraint, which was deduced from manual driving data. The improvement in driving safety was confirmed through vehicle tests along actual urban roads.

• 한국임상약학회지
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• 제26권4호
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• pp.312-317
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• 2016

Objective: Midazolam is mainly metabolized by cytochrome P450 (CYP) 3A. Inhibition or induction of CYP3A can affect the pharmacological activity of midazolam. The aims of this study were to develop a population pharmacokinetic (PK) model and evaluate the effect of CYP3A-mediated interactions among ketoconazole, rifampicin, and midazolam. Methods: Three-treatment, three-period, crossover study was conducted in 24 healthy male subjects. Each subject received 1 mg midazolam (control), 1 mg midazolam after pretreatment with 400 mg ketoconazole once daily for 4 days (CYP3A inhibition phase), and 2.5 mg midazolam after pretreatment with 600 mg rifampicin once daily for 10 days (CYP3A induction phase). The population PK analysis was performed using a nonlinear mixed effect model ($NONMEM^{(R)}$ 7.2) based on plasma midazolam concentrations. The PK model was developed, and the first-order conditional estimation with interaction was applied for the model run. A three-compartment model with first-order elimination described the PK. The influence of ketoconazole and rifampicin, CYP3A5 genotype, and demographic characteristics on PK parameters was examined. Goodness-of-fit (GOF) diagnostics and visual predictive checks, as well as bootstrap were used to evaluate the adequacy of the model fit and predictions. Results: Twenty-four subjects contributed to 900 midazolam concentrations. The final parameter estimates (% relative standard error, RSE) were as follows; clearance (CL), 31.8 L/h (6.0%); inter-compartmental clearance (Q) 2, 36.4 L/h (9.7%); Q3, 7.37 L/h (12.0%), volume of distribution (V) 1, 70.7 L (3.6%), V2, 32.9 L (8.8%); and V3, 44.4 L (6.7%). The midazolam CL decreased and increased to 32.5 and 199.9% in the inhibition and induction phases, respectively, compared to that in control phase. Conclusion: A PK model for midazolam co-treatment with ketoconazole and rifampicin was developed using data of healthy volunteers, and the subject's CYP3A status influenced the midazolam PK parameters. Therefore, a population PK model with enzyme-mediated drug interactions may be useful for quantitatively predicting PK alterations.