• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.183-189
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• 2024

In order to effectively predict time series data, this study proposed a hybrid prediction model that decomposes the data into trend, seasonality, and residual components using Seasonal-Trend Decomposition on Loess, and then applies ARIMA to the trend component, Fourier Series Regression to the seasonality component, and XGBoost to the remaining components. In addition, performance comparison experiments including ARIMA, XGBoost, LSTM, EMD-ARIMA, and CEEMDAN-LSTM models were conducted to evaluate the prediction performance of each model. The experimental results show that the proposed hybrid model outperforms the existing single models with the best performance indicator values in MAPE(3.8%), MAAPE(3.5%), and RMSE(0.35) metrics.

• Food Science and Biotechnology
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• v.16 no.3
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• pp.477-481
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• 2007

Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares (PLS) regression were used to predict the amylose content of polished rice. Spectral reflectance data in a wavelength range of 1,000 to 2,500 nm were obtained with a commercial spectrophotometer for 60 different varieties of Korean rice. For a comparison of this spectroscopic method to a standard chemical analysis, the amylose contents of the tested rice samples were determined by the iodine-blue colorimetric method. The highest correlation for the rice amylose ($R^2=0.94$, standard error of prediction=0.20% amylose content) was obtained when using the FT-NIR spectrum data pre-treated with normalization, the first derivative, smoothing, and scattering correction.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.3
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• pp.67-73
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• 2006

In this paper, a reconfigurable model following flight control method is proposed based on direct adaptive scheme using parameter estimation. Adaptive control scheme updates the control gains to make the system output follow the reference output even when fault occurs. By adopting the frequency domain parameter estimation method, system changes by the fault can be estimated. Recursive Fourier transformation is used for system identification. Using recursive Fourier transform, the proposed adaptive control algorithm guarantees the system stability and improves the system characteristics. To evaluate the performance of proposed control method, numerical simulations are performed.

• YAKHAK HOEJI
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• v.47 no.6
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• pp.461-468
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• 2003

A method is described for measuring clinically relevant levels of glucose in a pH 7.4 phosphate buffer by nearinfrared (NIR) absorption spectroscopy. Three types of NIR spectrometer, dispersive type, photo-diode array (PDA) type, and fourier transform (FT) type spectrometer were used and the performance was compared. Spectra were collected with a cuvette cell or quartz liquid fiber of 1 mm or 2 mm optical pathlength as transmittance method. Glucose absorption band appeared at second overtone, first overtone, and combination region for all systems. By use of the multivariate technigue of partial least squares (PLS) regression, glucose concentrations can be determined with a 16, 44, and 9.1 mg/d l standard error of prediction for dispersive type, photo-diode array type, and fourier transform type system, respectively. Sensitivity of spectrometer was evaluated by absorbance for the difference of 10 mg/d l glucose. Three absorption bands, second overtone, first overtone, and combination region were suited to three types systems, dispersive type, photo-diode array type, and fourier transform type systems, respectively. This investigation showed that three types NIR spectrometer were proper method for identification and quantitative analysis of glucose and possible for noninvasive blood glucose monitoring.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.138-143
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• 2000

In order to investigate the relationship between fabric sound parameters and subjective sensation, each sound from 60 fabrics was recorded and analyzed by Fast Fourier transform. Level pressure of total sound (LPT), three coefficients (ARC, ARF, ARE) of auto regressive models, loudness (Z), and sharpness (Z) by Zwickers model were estimated as sound parameters. For subjective evaluation, seven sensation (softness, loudness, sharpness, clearness, roughness, highness, and pleasantness) was rated by both semantic differential scale (SDS) and free modulus magnitude estimation (FMME). As the results, the ARC values were positively proportional to both LPT and loudness (Z) values. In both of SDS and FMME, softness, clearness, and pleasantness were negatively correlated with loudness, sharpness, roughness, and highness. In regression models, softness and clearness by FMME were negatively affected by LPT뭉 ARC, while loudness, sharpness, roughness, and highness were positively expected. Regression models for pleasantness showed low values for R2.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.346-348
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• 2003

In this study, we attempted to estimate the discharge of the Amazon River branches from JERS-1/SAR images, which are independent of the weather. We visualized some traces of the Amazon River branches, transformed river shapes into a one-dimensional signal, and calculated the characteristics of the river shapes such as the meandering wavelength and the amplitude with Fourier and wavelet analysis. Then, we related the characteristics of the river shapes with the existing discharge data and derived some regression equations. Finally, we estimated the discharge of the Amazon River branches from the SAR images.

• Korean Journal of Food Science and Technology
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• v.38 no.2
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• pp.165-168
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• 2006

Fourier transform-near infrared spectroscopy (FT-NIRS) was evaluated for determination of total dietary fiber (TDF) content of brown rice. Enzymatic-gravimetric method was suitable to obtain reference values for calibration of NIR at 1,000-2,500 nm range. Standard error of laboratory procedure ranged 0.17 to 0.72%. Partial least square (PLS) regression was used to develop the calibration equations. Regression was performed automatically using NIRCal chemometric software. Accuracy of prediction model for TDF content was certified for regression coefficient (r), standard error of estimation (SEE) and standard error of prediction (SEP), showing 0.9780, 0.0636, and 0.0642, respectively. This prediction model can be used for determination of TDF in brown rice and would be useful for real-time analysis in food industry.

• Bulletin of the Korean Chemical Society
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• v.27 no.12
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• pp.2101-2103
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• 2006

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2956-2958
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• 1999

The classical solution to the noise removal problem is the Wiener filter, which utilizes the second-order statistics of the Fourier decomposition. We discuss a Bayesian formalism which gives rise to a type of wavelet threshold estimation in non-parametric regression. A prior distribution is imposed on the wavelet coefficients of the unknown response function, designed to capture the sparseness of wavelet expansion common to most application. For the prior specified, the posterior median yields a thresholding procedure

• Food Science and Preservation
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• v.12 no.6
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• pp.608-612
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• 2005

Fourier transform-near infrared (FT-NIR) spectroscopy is a simple, rapid, non-destructive technique which can be used to make quantitative analysis of chemical composition in grain. An interest in total dietary fiber (TDF) of grain such as rice has been increased due to its beneficial effects for health. Since measuring methods for TDF content were highly depending on experimental technique and time consumptions, the application of FT-NIR spectroscopy to determine TDF content in milled rice. Results of enzymatic-gravimetric method were $1.17-1.92\%$ Partial least square (PLS) regression on raw NIR spectra to predict TDF content was developed Accuracy of prediction model for TDF content was certified for regression coefficient (r), standard error of estimation (SEE) and standard error of prediction (SEP). The r, SEE and SEP were 0.9705, 0.0464, and 0.0604, respectively. The results indicated that FT-NIR techniques could be very useful in the food industry and rice processing complex for determination of TDF in milled rice on real time analysis.