• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4105-4105
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• 2001

Near infrared spectroscopy (NIRS) was employed to qualify and quantify on survival, the injury rate and apoptosis of the human breast cancer cell line MCF-7 cells. MCF-7 cells were cultured in RPMI medium supplemented with 10% FCS in a 95% air and 5% CO2 atmosphere at 37$^{\circ}C$. For the viable cells preparation, cells were de-touched by 0.1% of trypsin treatment and washed with RPMI supplemented with 10% FCS medium by centrifugation at 1000 rpm for 3min. For the dead cells preparation, cells were de-touched by a cell scraper. The cells were counted by a hemacytometer, and the viability was estimated by the exclusion method with frypan blue dye. Each viable and dead cells were suspended in PBS (phosphate bufferred saline) or milk at the cell density desired. For the quantitative determination of cell death by measuring the LDH (lactate dehydrogenase) activity liberated from cells with cell membrane injuries, LDH-Cytotoxic Test Wako (Wako, Pure Pharmaceutical Co. Ltd., Japan) was used. We found that NIRS measurement of MCF-7 cells at the density range could evaluate and monitor the different characteristics of living cells and dead cells. The spectral analysis was performed in two wavelength ranges and with 1,4, 10 mm pathlength. Different spectral data pretreatment and chemometrics methods were used. We applied SIMCA classificator on spectral data of living and dead cells and obtained good accuracy when identifying each class. Bigger variation in the spectra of living cells with different concentrations was observed when compared to the same concentrations of dead cells. PLS was used to measure the number of cells in PBS. The best model for measurement of dead cells, as well as living cells, was developed when raw spectra in the 600-1098 nm region and 4 mm pathlength were used. Smoothing and second derivative spectral data pretreatment gave worst results. The analysis of PLS loading explained this result with the scatter effect found in the raw spectra and increased with the number of cells. Calibration for cell count in the 1100-2500 nm region showed to be very inaccurate.

• 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.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.1-8
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• 2013

This paper proposes a new feature extraction algorithm to improve children's speech recognition in Korean. The proposed feature extraction algorithm combines three methods. The first method is on the vocal tract length normalization to compensate acoustic features because the vocal tract length in children is shorter than in adults. The second method is to use the uniform bandwidth because children's voice is centered on high spectral regions. Finally, the proposed algorithm uses a smoothing filter for a robust speech recognizer in real environments. This paper shows the new feature extraction algorithm improves the children's speech recognition performance.

• Journal of Korean Institute of Industrial Engineers
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• v.3 no.1
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• pp.39-47
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• 1977

Most of the current literature on inventory theory has been devoted to the study of single stage models. A class of inventory problems which is of great interest is the multistage inventory system which involves a series and hierarchical sequence of stations. This study analyzes some aspect of the series type and multi-stage inventory system, using the fixed cycle ordering which bas a modificatory control function in the system equations. The objective of this study is to clarify the dynamic behavior of the system. The author has derived the theoretical formulas of variation of ordering quantity and stock fluctuation of each stage due to power spectral density function. Influence of parameters such as, (1) intensity of autocorrelation of demand sequence ($\lambda$), (2) forecasting exponential smoothing factors of each stage (${\alpha}_1,\;{\alpha}_2,\;{\alpha}_3$) and (3) production control factor of the 3rd stage ($\gamma$), as operators of the system on the variation of ordering quantity and stock fluctuation of the system. is also clarified. As a result of this study, the relations between the variation of ordering quantity, stock fluctuation and the parameters of the system, have been found. The principles and the theorical analysis presented here will be applicable to more complex type of discrete control systems in constructing the specific condition of the system to minimize inventory variances.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.2
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• pp.53-63
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• 2016

Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect the taste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significant economic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong Reservoir's Water Quality Monitoring Program and Algae Alarm System. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the Landsat TM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were most significant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible band ratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacteria blooms in Daecheong reservoir.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.13 no.3
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• pp.209-229
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• 2001

Simultaneous field measurements of short-period and long-period waves were made at five stations inside or outside Okkye Harbor, which is located in the east coast of Korea. Based on the measured data, spacial and temporal variations of the long-period wave energy were examined. Three smoothing methods were examined for the spectral estimates: fixed interval averaging method, incremental interval averaging method, and moving averaging method. It was shown that a proper smoothing method should be chosen depending on the period of first resonant mode and the length of data being used. By comparing the results obtained using the long-term data with those obtained using two-day data, we showed that it is necessary to analyze the data of calm seas and storm seas separately. The Helmholtz resonant period in Okkye Harbor was found to be about 9.6 minutes with its relative amplification ratio of 9 to 10, and local amplifications were apparent at the periods of 1.2 to 1.3 minutes and 0.7 minute. During calm seas, both at the harbor entrance and inside the harbor the energy of the waves of 9 minutes or longer period was larger than the infra-gravity wave energy by more than 100 times. However, during storm seas the energy level was very high all over the period band, and local amplification was larger than that during calm seas by more than 100 times, especially inside the harbor, Finally it was shown that the energies of the Helmholtz resonant mode and the infra-gravity waves of 1 to 2 minutes are proportional to the storm wave height.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.259-265
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• 2004

A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.11 no.4
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• pp.201-215
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• 1999

Field measurements were made for long- and short-period waves and current velocities at the harbor mouth using pressure-type wave gauges and a current meter, respectively, at the Gamcheon Harbor which has a rectangular shape with a narrow entrance. The measured pressure data were subjected to spectral analyses after removing tidal effects by applying trend removal and high-pass filtering. For the band averaging of the raw spectra, in order to obtain good resolution over the entire frequency, instead of a constant band width, variable band widths were used, which gradually increase as marching from the lowest frequency towards higher frequencies. The Helmholtz resonance mode at the Gamcheon Harbor shows the relative amplification ratio of 9.2 at the wave period of 31.7 minutes, which is quite large compared with those at the harbors located on the east coast of Korea. The second and the third resonance period was 10.3 and 5.4 minute, respectively. On the other hand, the analysis of every 24 hours data shows that during storms the spectral densities are very large compared to those during calm seas and also the second and third resonances are predominant.

• Journal of the Korean Wood Science and Technology
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• v.45 no.4
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• pp.399-408
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• 2017

Research on the rapid and accurate prediction of physical properties of wood using near-infrared (NIR) spectroscopy has attracted recent attention. In this study, partial least squares analysis was performed between NIR spectra and air-dried specific gravity of five domestic conifer species including larch (Larix kaempferi), Korean pine (Pinus koraiensis), red pine (Pinus densiflora), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa). Fifty different lumbers per species were purchased from the five National Forestry Cooperative Federations of Korea. The air-dried specific gravity of 100 knot- and defect-free specimens of each species was determined by NIR spectroscopy in the range of 680-2500 nm. Spectral data preprocessing including standard normal variate, detrend and forward first derivative (gap size = 8, smoothing = 8) were applied to all the NIR spectra of the specimens. Partial least squares analysis including cross-validation (five groups) was performed with the air-dried specific gravity and NIR spectra. When the performance of the regression model was expressed as $R^2$ (coefficient of determination) and root mean square error of calibration (RMSEC), $R^2$ and RMSEC were 0.63 and 0.027 for larch, 0.68 and 0.033 for Korean pine, 0.62 and 0.033 for red pine, 0.76 and 0.022 for cedar, and 0.79 and 0.027 for cypress, respectively. For the calibration model, which contained all species in this study, the $R^2$ was 0.75 and the RMSEC was 0.37.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.319-330
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• 2006

A signal in real world usually composes of multiple signals having different scales of frequencies. For example sun-spot data is fluctuated over 11 year and 85 year. Economic data is supposed to be compound of seasonal component, cyclic component and long-term trend. Decomposition of the signal is one of the main topics in time series analysis. However when the signal is subject to nonstationarity, traditional time series analysis such as spectral analysis is not suitable. Huang et. at(1998) proposed data-adaptive method called empirical mode decomposition (EMD) . Due to its robustness to nonstationarity, EMD has been applied to various fields. Huang et. at, however, have not considered denoising when data is contaminated by error. In this paper we propose efficient denoising method utilizing cross-validation.