• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.3
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• pp.307-312
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• 2013

The interest in reducing the emissions and increasing the fuel economy of ICE vehicles has prompted research on hybrid vehicles, which come in the series, parallel, and power-split types. This study focuses on the series-type hybrid electric vehicle, which has a simple structure. Because each component of a series hybrid vehicle is larger than the corresponding component of the parallel type, the sizing of the vehicle is very important. This is because the performance may be greater or less than what is required. Thus, in this research, the optimal fuel economy was determined and simulated in a real-world system. The optimal sizing was achieved based on the motor, engine/generator, and battery for 13 cycles, where DP was used. The model was developed using ASCET or a Simulink-Amisim Co-simulation platform on the rapid controller prototype, ES-1000.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.11
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• pp.1098-1103
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• 2013

A low-noise amplifier(LNA) using series RLC matching network and resistive feedback at 8 GHz is presented. Inductive degeneration is used for the input matching with which the proposed LNA shows quite a wide bandwidth in terms of $S_{21}$. An equivalent circuit model is deduced for input matching by conversion from parallel circuit to series resonant circuit. By exploiting the resistive feedback and series RLC input matching, fully integrated LNA achieves maximum $S_{21}$ of 8.5 dB(peak to -3 dB bandwidth is about 3.5 GHz) noise figure of 5.9 dB, and IIP3 of 1.6 dBm while consuming 7 mA from 1.2 V supply.

• Journal of Biosystems Engineering
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• v.33 no.4
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• pp.260-268
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• 2008

Optical diffuse reflectance sensing has potential for rapid and reliable on-site estimation of soil properties. For good results, proper calibration to measured soil properties is required. One issue is whether it is necessary to develop calibrations using samples from the specific area or areas (e.g., field, soil series) in which the sensor will be applied, or whether a general "factory" calibration is sufficient. A further question is if specific calibration is required, how many sample points are needed. In this study, these issues were addressed using data from 42 paddy fields representing 14 distinct soil series accounting for 74% of the total Korean paddy field area. Partial least squares (PLS) regression was used to develop calibrations between soil properties and reflectance spectra. Model evaluation was based on coefficient of determination ($R^2$) root mean square error of prediction (RMSEP), and RPD, the ratio of standard deviation to RMSEP. When sample data from a soil series were included in the calibration stage (full information calibration), RPD values of prediction models were increased by 0.03 to 3.32, compared with results from calibration models not including data from the test soil series (calibration without site-specific information). Higher $R^2$ values were also obtained in most cases. Including some samples from the test soil series (hybrid calibration) generally increased RPD rapidly up to a certain number of sample points. A large portion of the potential improvement could be obtained by adding about 8 to 22 points, depending on the soil properties to be estimated, where the numbers were 10 to 18 for pH, 18-22 for EC, and 8 to 22 for total C. These results provide guidance on sampling and calibration requirements for NIR soil property estimation.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.667-675
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• 2018

When a financial time series consists of daily (closing) returns, traditional volatility models such as autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) are useful to figure out daily volatilities. With high frequency returns in a day, one may adopt various multivariate GARCH techniques (MGARCH) (Tsay, Multivariate Time Series Analysis With R and Financial Application, John Wiley, 2014) to obtain intraday volatilities as long as the high frequency is moderate. When it comes to the ultra high frequency (UHF) case (e.g., one minute prices are available everyday), a new model needs to be developed to suit UHF time series in order to figure out continuous time intraday-volatilities. Aue et al. (Journal of Time Series Analysis, 38, 3-21; 2017) proposed functional GARCH (fGARCH) to analyze functional volatilities based on UHF data. This article introduces fGARCH to the readers and illustrates how to estimate fGARCH equations using UHF data of KOSPI and Hyundai motor company.

• Journal of Preventive Medicine and Public Health
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• v.46 no.1
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• pp.10-18
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• 2013

Objectives: We investigated the association between particulate matter less than $10{\mu}m$ in aerodynamic diameter ($PM_{10}$) exposure and non-accidental mortality in Asian populations by meta-analysis, using both time-series and case-crossover analysis. Methods: Among the 819 published studies searched from PubMed and EMBASE using key words related to $PM_{10}$ exposure and non-accidental mortality in Asian countries, 8 time-series and 4 case-crossover studies were selected for meta-analysis after exclusion by selection criteria. We obtained the relative risk (RR) and 95% confidence intervals (CI) of non-accidental mortality per $10{\mu}g/m^3$ increase of daily $PM_{10}$ from each study. We used Q statistics to test the heterogeneity of the results among the different studies and evaluated for publication bias using Begg funnel plot and Egger test. Results: Testing for heterogeneity showed significance (p<0.001); thus, we applied a random-effects model. RR (95% CI) per $10{\mu}g/m^3$ increase of daily $PM_{10}$ for both the time-series and case-crossover studies combined, time-series studies relative risk only, and case-crossover studies only, were 1.0047 (1.0033 to 1.0062), 1.0057 (1.0029 to 1.0086), and 1.0027 (1.0010 to 1.0043), respectively. The non-significant Egger test suggested that this analysis was not likely to have a publication bias. Conclusions: We found a significant positive association between $PM_{10}$ exposure and non-accidental mortality among Asian populations. Continued investigations are encouraged to contribute to the health impact assessment and public health management of air pollution in Asian countries.

• Journal of the Society of Naval Architects of Korea
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• v.32 no.2
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• pp.93-102
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• 1995

A series of test was performed by measuring the failure strength and the failure mode of fiber reinforced composite laminates joint containing two holes in Series or Parallel. $[0^{\circ}/45^{\circ}/90^{\circ}/-45^{\circ}]_s$ laminate with W/d(Side distance ratio) 4.0 and E/d(Edge distance ratio) 3.0 has the full bearing strength and are preferable in case of the good efficiency in two series hole. Comparisons were made between testing results and predicting values of the FEM model. Good agreements were fecund between them except the case of $E/d=2{\sim}3$. In the case of $G_h{\geq}3.0d$ and $G_v{\geq}3.0d$ since the interaction coefficients between two parallel holes and between two series holes were small, holes can be treated as independent. The Acoustic Emission(AE) and SEM method were utilized to find out the initial defects, damage and the fracture mechanism.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.52-56
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• 2004

The Information of classification and estimate about KOSPI200 index`s up and down in the stock market becomes an important standard of decision-making in designing portofolio in futures and option market. Because the coming trend of time series patterns, an economic indicator, is very subordinate to the most recent economic pattern, it is necessary to study the recent patterns most preferentially. This paper compares classification and estimated performance of SVM(Support Vector Machine) and Fuzzy SVM model that are getting into the spotlight in time series analyses, neural net models and various fields. Specially, it proves that Fuzzy SVM is superior by presenting the most suitable dimension to fuzzy membership function that has time series attribute in accordance with learning Data Base.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.5
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• pp.386-393
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• 2001

A series active power filter compensating current harmonics and unbalanced source voltages in a 3phase-3wire power system is presented. The system is composed of series active power filter and shunt passive filters that are tuned at 5th and 7th harmonics. The proposed series active power filter improves harmonic compensation characteristics of the shunt passive filters, reduces source side harmonic currents and compensates the unbalanced source voltages. In the proposed algorithm, compensation voltage for harmonic reduction is calculated by a performance function, and compensation voltage for the unbalanced source voltage is calculated based on the synchronous reference frame. Some results obtained from the experimental model using the proposed method are Presented to demonstrate and confirm its validity.

• Wind and Structures
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• v.39 no.4
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• pp.271-285
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• 2024

The multiple-fan wind tunnel is an important facility for reproducing target wind field. Existing control methods for the multiple-fan wind tunnel can generate wind speeds that satisfy the target statistical characteristics of a wind field (e.g., power spectrum). However, the frequency-domain features cannot well represent the nonstationary winds of extreme storms (e.g., downburst). Therefore, this study proposes a multiple-fan wind tunnel control scheme based on Deep Reinforcement Learning (DRL), which will completely transform into a data-driven closed-loop control problem, to reproduce the target wind field in the time domain. Specifically, the control scheme adopts the Deep Deterministic Policy Gradient (DDPG) paradigm in which the strong fitting ability of Deep Neural Networks (DNN) is utilized. It can establish the complex relationship between the target wind speed time series and the current control strategy in the DRL-agent. To address the fluid memory effect of the wind field, this study innovatively designs the system state and control reward to improve the reproduction performance based on historical data. To validate the performance of the model, we established a simplified flow field based on Navier Stokes equations to simulate a two-dimensional numerical multiple-fan wind tunnel environment. Using the strategy of DRL decision maker, we generated a wind speed time series with minor error from the target under low Reynolds number conditions. This is the first time that the AI methods have been used to generate target wind speed time series in a multiple-fan wind tunnel environment. The hyperparameters in the DDPG paradigm are analyzed to identify a set of optimal parameters. With these efforts, the trained DRL-agent can simultaneously reproduce the wind speed time series in multiple positions.

• Bulletin of the Korean Mathematical Society
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• v.52 no.4
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• pp.1113-1122
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• 2015

This paper is concerned with the pattern formation of a diffusive predator-prey model with two time delays. Based upon an analysis of Hopf bifurcation, we demonstrate that time delays can induce spatial patterns under some conditions. Moreover, by use of a series of numerical simulations, we show that the type of spatial patterns is the spiral wave. Finally, we demonstrate that the spiral wave is asymptotically stable.