• Journal of Korean Society for Atmospheric Environment
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• v.17 no.5
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• pp.395-405
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• 2001

To make an assessment of the compatibility between DOAS and conventional point monitoring system (MCSAM-2: MS2), we investigated the concentrations of three criteria pollutants which include S $O_2$, N $O_2$, and $O_3$from a national monitoring station in Seoul during the periods of June 1999~August 2000. The average concentration values for the whole study period derived from hourly concentration data sets of those three species indicated that the mean differences between the two methods can be approximated as 18%. When the bias structure of two systems was evaluated through the computation of percent difference(PD) between the two such as ( $C_{DOAS}$- $C_{conventional}$ $C_{DOAS}$*100, differences between the two systems appeared to be quite systematic among different compounds. While the mode of bias peaked at 0~20% or 20~40% in terms of PD values, the cause of such positive bias mainly arised from generally enhanced concentration values of DOAS system. The structure of bias among different species was further assessed through linear regression analysis. Results of the analysis indicated that the dominant portions of differences observed from two monitoring systems can be accounted for by the systematic differences in their spanning and zeroing systems. S $O_2$(MS2)=0.6385 S $O_2$(DOAS)+2.0985($r^2$=0.7894) N $O_2$(MS2)=0.6548 N $O_2$(DOAS)+7.437($r^2$=0.7687) $O_3$(MS2)=1.0359 $O_3$(DOAS)-7.7885($r^2$=0.7944) The findings of slope values at around 0.64~0.65 from two species suggest that DOAS should respond more sensitively in upper bound concentration range. The offset values apart from zero indicate that more deliberate comparison needs to be made between these monitoring systems. However, based on the existence of strong correlations from at least 8,000 data points for each species of comparison, we were able to conclude that the compatibility of two monitoring systems is highly significant. With the improvement of calibration techniques for the DOAS system. its applicability for routine monitoring of airborne pollutant species is expected to be quite extendable.

• Journal of The Korean Astronomical Society
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• v.47 no.6
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• pp.235-253
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• 2014

Intensity interferometry, based on the Hanbury Brown-Twiss effect, is a simple and inexpensive method for optical interferometry at microarcsecond angular resolutions; its use in astronomy was abandoned in the 1970s because of low sensitivity. Motivated by recent technical developments, we argue that the sensitivity of large modern intensity interferometers can be improved by factors up to approximately 25 000, corresponding to 11 photometric magnitudes, compared to the pioneering Narrabri Stellar Interferometer. This is made possible by (i) using avalanche photodiodes (APD) as light detectors, (ii) distributing the light received from the source over multiple independent spectral channels, and (iii) use of arrays composed of multiple large light collectors. Our approach permits the construction of large (with baselines ranging from few kilometers to intercontinental distances) optical interferometers at the cost of (very) long-baseline radio interferometers. Realistic intensity interferometer designs are able to achieve limiting R-band magnitudes as good as $m_R{\approx}14$, sufficient for spatially resolved observations of main-sequence O-type stars in the Magellanic Clouds. Multi-channel intensity interferometers can address a wide variety of science cases: (i) linear radii, effective temperatures, and luminosities of stars, via direct measurements of stellar angular sizes; (ii) mass-radius relationships of compact stellar remnants, via direct measurements of the angular sizes of white dwarfs; (iii) stellar rotation, via observations of rotation flattening and surface gravity darkening; (iv) stellar convection and the interaction of stellar photospheres and magnetic fields, via observations of dark and bright starspots; (v) the structure and evolution of multiple stars, via mapping of the companion stars and of accretion flows in interacting binaries; (vi) direct measurements of interstellar distances, derived from angular diameters of stars or via the interferometric Baade-Wesselink method; (vii) the physics of gas accretion onto supermassive black holes, via resolved observations of the central engines of luminous active galactic nuclei; and (viii) calibration of amplitude interferometers by providing a sample of calibrator stars.

• Analytical Science and Technology
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• v.16 no.5
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• pp.391-398
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• 2003

Basic research for the determination of boron content in biological sample has been carried out using the PGAA facility of the 24MW research reactor(HANARO). For investigation of characteristics for the measurement condition, neutron flux and its homogeneity were measured at irradiating geometry. The size of thermal neutron beam collimated from beam guide is $2{\times}2cm^2$ at the sample position. The neutron flux measured was the range of $1.0{\sim}6.5{\times}10^7n{\cdot}cm^{-2}{\cdot}s^{-1}$, and flux distribution from center within the radius of 4.5 mm and 9.0 mm was $5.77{\pm}0.71{\times}10^7n{\cdot}cm^{-2}{\cdot}s^{-1}$ and $4.68{\pm}1.64{\times}10^7n{\cdot}cm^{-2}{\cdot}s^{-1}$, respectively. Accordingly, sample size is adjusted within 10 mm for a homogeneous irradiation of high quality. Measurement system is designed to reduce the background source by Compton scattering and to improve the analytical sensitivity. To investigate the energy calibration and Compton suppression effect of gamma-ray counting system, the background conditions on both of Compton and single-mode were measured using NaCl standard. On the other hand, degree of spectral interference for sodium 472 keV peak as a matrix effect in the sample is established for an accurate boron analysis, and then boron content in three certified reference materials (NIST SRM 1570a, 1547, 1573a) was measured by using two modes and the results were compared with each other.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.52.2-52.2
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• 2014

The Immersion Grating Infrared Spectrometer (IGRINS) is an unprecedentedly minimized infrared cross-dispersed echelle spectrograph with a high-resolution and high-sensitivity optical performance. A silicon immersion grating features the instrument for the first time in this field. IGRINS will cover the entire portion of the wavelength range between 1.45 and $2.45{\mu}m$ accessible from the ground in a single exposure with spectral resolution of 40,000. Individual volume phase holographic (VPH) gratings serve as cross-dispersing elements for separate spectrograph arms covering the H and K bands. On the 2.7m Harlan J. Smith telescope at the McDonald Observatory, the slit size is $1^{\prime\prime}{\times}15^{\prime\prime}$. IGRINS has a $0.27^{\prime\prime}$ pixel-1 plate scale on a $2048{\times}2048$ pixel Teledyne Scientific & Imaging HAWAII-2RG detector with SIDECAR ASIC cryogenic controller. The instrument includes four subsystems; a calibration unit, an input relay optics module, a slit-viewing camera, and nearly identical H and K spectrograph modules. The use of a silicon immersion grating and a compact white pupil design allows the spectrograph collimated beam size to be 25mm, which permits the entire cryogenic system to be contained in a moderately sized rectangular vacuum chamber. The fabrication and assembly of the optical and mechanical hardware components were completed in 2013. In this presentation, we describe the major design characteristics of the instrument and the early performance estimated from the first light commissioning at the McDonald Observatory.

• Journal of Sensor Science and Technology
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• v.8 no.5
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• pp.359-367
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• 1999

CsI(Li) single crystals doped with 0.02, 0.1, 0.2 and 0.3 mole% lithium as an activator were grown by Czochralski method. The lattice structure of grown CsI(Li) single crystal was bcc, its lattice constant was $4.568\;{\AA}$. The absorption edge of CsI(Li) single crystal was 245 nm, and the spectral range of luminescence was $300{\sim}600\;nm$, its maximum luminescence intensity appeared at 425 nm. The energy resolutions of CsI(Li) single crystal doped with 0.2 mole% lithium were 14.5% for $^{137}Cs$(662 keV), 11.4% for $^{54}Mn$(835 keV) and 17.7% and 7.9% for $^{22}Na$(511 keV and 1275 keV), respectively. The relation formula of $\gamma$-ray energy versus energy resolution was ln (FWHM%) = -0.893lnE + 8.456 and energy calibration formula was ${\log}E_r=1.455\;{\log}(ch.)-1.277$. The phosphorescence decay time of CsI(Li) crystal doped with 0.2 mole% lithium was 0.51 s at room temperature, and its time resolution measured by CFT(constant-fraction timing method) was 9.0 ns.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.2
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• pp.217-223
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• 2008

Amylose and protein contents are important traits determining the edible quality of rice, especially in East Asian countries. Near-Infrared Reflectance Spectroscopy (NIRS) has become a powerful tool for rapid and nondestructive quantification of natural compounds in agricultural products. To test the practically of using NIRS for estimation of brown rice amylose and protein contents, the spectral reflectances ($400{\sim}2500\;nm$) of total 9,483 accessions of rice germplasm in Rural development Administration (RDA) Genebank ere obtained and compared to chemically determined amylose and protein content. The protein content of tested 119 accessions ranged from 6.5 to 8.0% and 25 accessions exhibited protein contents between 8.5 to 9.5%. In case of amylose content, all tested accessions ranged from 18.1 to 21.7% and the grade from 18.1 to 19.9% includes most number of accessions as 152 and 4 accessions exhibited amylose content between 20.5 to 21.7%. The optimal performance calibration model could be obtained from original spectra of brown rice using MPLS (Modified Partial Least Squares) with the correlation coefficients ($r_2$) for amylose and protein content were 0.865 and 0.786, respectively. The standard errors of calibration (SEC) exhibited good statistic values: 2.078 and 0.442 for amylose and protein contents, respectively. All these results suggest that NIR spectroscopy may serve as reputable and rapid method for quantification of brown rice protein and amylose contents in large numbers of rice germplasm.

• Journal of Animal Environmental Science
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• v.18 no.3
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• pp.257-266
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• 2012

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal and dired animal forages. Analysis of forage quality by NIRS usually involves dry grinding samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations on prediction ability of chemical composition and fermentation parameter for Italian ryegrass silages by NIRS. A population of 147 Italian ryegrass silages representing a wide range in chemical parameters were used in this investigation. Samples were scanned at 1nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in oven-dried grinding and fresh ungrinding condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with four spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV) and maximizing the correlation coefficient of cross validation (${R^2}_{CV}$). The results of this study show that NIRS predicted the chemical parameters with high degree of accuracy in oven-dried grinding treatment except for moisture contents. Prediction accuracy of the moisture contents was better for fresh ungrinding treatment (SECV 1.37%, $R^2$ 0.96) than for oven-dried grinding treatments (SECV 4.31%, $R^2$ 0.68). Although the statistical indexes for accuracy of the prediction were the lower in fresh ungrinding treatment, fresh treatment may be acceptable when processing is costly or when some changes in component due to the processing are expected. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation parameter of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.4
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• pp.258-263
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• 2019

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages. The objective of this study was to evaluate the potential of NIRS, applied to imported forage, to estimate the moisture and chemical parameters for imported hays. A population of 392 imported hay representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1 nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation(R²) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS predicted the chemical parameters with very high degree of accuracy. The R² and SECV for imported hay calibration were 0.92(SECV 0.61%) for moisture, 0.98(SECV 0.65%) for acid detergent fiber, 0.97(SECV 0.40%) for neutral detergent fiber, 0.99(SECV 0.06%) for crude protein and 0.97(SECV 3.04%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of imported hay in Korea for routine analysis method to evaluate the feed value.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.1
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• pp.50-57
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• 2016

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation ($R^2{_{cv}}$) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, $R^2{_{cv}}$, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy ($R^2{_{cv}}$ 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.