• 한국정보통신학회논문지
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• 제8권5호
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• pp.970-976
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• 2004

본 논문에서는 MRC(Maximal Ratio Combing) 결합 기법을 사용한 RAKE 수신기에서 채널 추정 알고리즘에 따른 성능을 분석한다. 채널 추정 알고리즘에는 WMSA(Weighted Multi-Slot Averaging), 동일 이득 채널 추정 (Equal Cain Estimation ; ECE), 심볼 단위 채널 추정(Symbol-to-Symbol Estimation ; SSE)의 세 가지가 있는데 상업용 시뮬레이션 틀인 HP사의 ADS를 이용하여 비동기 방식 IMT-2000시스템(3GPP)을 대상으로 성능을 분석한다. 성능 분석을 위해서 본 논문은 Jakes 페이딩 채널 모델을 사용한다. 모의실험 결과를 통하여, 저속 도플러(3Km/h)일 때 WMSA 알고리즘이 다른 알고리즘 성능보다 더 좋음을 알 수 있다. 그러나 고속 도플러(120Km/h)일 때, 간단한 구조를 갖는 ECE 알고리즘이 보다 더 유용함을 알 수 있다.

• 한국태양에너지학회 논문집
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• 제29권6호
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• pp.1-13
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• 2009

Photovoltaic conditioning systems normally use a maximum power point tracking (MPPT) technique to deliver the highest possible power to the load continuously when variations occur in the insolation and temperature. A unique method of tracking the maximum power points (MPPs) and forcing the boost converter system to operate close to these points is presented through deriving small-signal model and transfer function of boost converter considering input capacitor. This paper aims at modeling boost converter including fairly large equivalent series resistance(ESR) of input reservoir capacitor by state-space-averaging method and PWM switch model and compares both methods using Bode plots. In the future, properly designed controller for compensation will be constructed in 3kw real system for maximum photovoltaic power tracking control.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2011년도 추계학술발표대회 논문집
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• pp.249-255
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• 2011

This paper is about the study of a stand-alone photovoltaic power conditioning system with an energy storage system with battery. The paper proposes the appropriate circuit model of stand-alone PV PCS considering the maintenance of the battery system. It also proposes the buck converter modeling by a state-space averaging method considering characteristics of solar cell. Lastly, it shows the way to choose the suitable battery and to design the model of bi-directional converter for charging and discharging battery. PSIM simulation is used to validate the proposed algothim of the system.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.723-728
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• 2008

We performed numerical analysis of base drag phenomenon, when a projectile with backward step flies into atmosphere at supersonic speed. We compared with other researchers. From our previous studies that were 2-dimensional simulation, we found out from sophisticated simulations that need dense mesh points to compare base pressure and velocity profile after from base with experimental data. Therefore, we focus on high order spatial disceretization over 3rd order with TVD such as MUSCL TVD 3rd, 5th, and WENO 5th order, and Limiters such as minmod, Triad. Moreover, we enforce to flux averaging schemes such as Roe, RoeM, HLLE, AUSMDV. In present, one dimensional result of Euler tests, there are Sod, Lax, Shu-Osher and interacting blast wave problems. AUSMDV as a flux averaging scheme with MUSCL TVD 5th order as spatial resolution is good agreement with exact solutions than other combinations. We are carrying out the same approaches into 3-dimensional base flow only candidate flux schemes that are Roe, AUSMDV. Additionally, turbulence models are used in 3-dimensional flow, one is Menter s SST DES model and another is Sparlat-Allmaras DES/DDES model in Navier-Stokes equations.

• 한국태양에너지학회 논문집
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• 제28권5호
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• pp.85-95
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• 2008

Photovoltaic conditioning systems normally use a maximum power point tracking (MPPT) technique to deliver the highest possible power to the load continuously when variations occur in the insolation and temperature. A unique method of tracking the maximum power points (MPPs) and forcing the boost converter system to operate close to these points is presented through deriving small-signal model and transfer function of boost converter considering input capacitor. This paper aims at modeling boost converter including fairly large equivalent series resistance(ESR) of input reservoir capacitor by state-space-averaging method and PWM switch model. In the future, properly designed controller for compensation will be constructed in 3kw real system for maximum photovoltaic power tracking control.

• Journal of the Korean Wood Science and Technology
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• 제47권4호
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• pp.385-392
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• 2019

In our previous study, we investigated the use of ensemble models based on LeNet and MiniVGGNet to classify the images of transverse and longitudinal surfaces of five Korean softwoods (cedar, cypress, Korean pine, Korean red pine, and larch). It had accomplished an average F1 score of more than 98%; the classification performance of the longitudinal surface image was still less than that of the transverse surface image. In this study, ensemble methods of two different convolutional neural network models (LeNet3 for smartphone camera images and NIRNet for NIR spectra) were applied to lumber species classification. Experimentally, the best classification performance was obtained by the averaging ensemble method of LeNet3 and NIRNet. The average F1 scores of the individual LeNet3 model and the individual NIRNet model were 91.98% and 85.94%, respectively. By the averaging ensemble method of LeNet3 and NIRNet, an average F1 score was increased to 95.31%.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2002년도 추계학술발표대회 논문집
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• pp.292-295
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• 2002

In this paper, an analytical model for the prediction of the elastic properties of multi-axial warp knit fabric (MWK) composites is proposed. The geometric limitation, effect of stitching fibers and design parameters of MWK composites are considered in the model. The elastic behavior of MWK composites was conducted by using an averaging method. The predicted elastic properties are in reasonably good agreement with experimental values. Finally the effect of stitching in the MWK composites are discussed.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1997년도 봄 학술발표회 논문집
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• pp.383-391
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• 1997

The prediction of effective properties of heterogeneous material like concrete is of primary importance in design or analysis. This paper os about micromechanice-based evaluation of elastic moduli of concretes considering composite material behavior. In this study, micromechanixe-based schemes for the effective elastic modui of the lightweight foamed concrete and the normal concrete are proposed based on averaging techniques using a single-layered inclusion model and a multi-phase and multi-layered inclusion model. respectively, For the verification's sake, elastic moduli evaluated in this study are compared with experimental data and results by existing formula.

• 한국공작기계학회논문집
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• 제12권5호
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• pp.1-7
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• 2003

In order to predict vibrations occurred during end-milling processes, the cutting dynamics was modelled by using neural network and combined with structural dynamics by considering dynamic cutting state. Specific cutting force constants of the cutting dynamics model were obtained by averaging cutting forces. Tool diameter, cutting speed, fled, axial and radial depth of cut were considered as machining factors in neural network model of cutting dynamics. Cutting farces by test and by neural network simulation were compared and the vibration displacement during end-milling was simulated.

• 대기
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• 제28권3호
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• pp.291-303
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• 2018

In this study, a new consensus technique for predicting tropical cyclone (TC) intensity in the western North Pacific was developed. The most important feature of the present consensus model is to select and combine the guidance numerical models with the best performance in the previous years based on various evaluation criteria and averaging methods. Specifically, the performance of the guidance models was evaluated using both the mean absolute error and the correlation coefficient for each forecast lead time, and the number of the numerical models used for the consensus model was not fixed. In averaging multiple models, both simple and weighted methods are used. These approaches are important because that the performance of the available guidance models differs according to forecast lead time and is changing every year. In particular, this study develops both a multi-consensus model (M-CON), which constructs the best consensus models with the lowest error for each forecast lead time, and a single best consensus model (S-CON) having the lowest 72-hour cumulative mean error, through on training process. The evaluation results of the selected consensus models for the training and forecast periods reveal that the M-CON and S-CON outperform the individual best-performance guidance models. In particular, the M-CON showed the best overall performance, having advantages in the early stages of prediction. This study finally suggests that forecaster needs to use the latest evaluation results of the guidance models every year rather than rely on the well-known accuracy of models for a long time to reduce prediction error.