Excitation spectra of the 1.6 rm emission originating from $Ho^{3+}$:$^{5}$ I$_{5}$ \longrightarrow$^{5}$ I$_{7}$ transition in fluoride, sulfide, and selenide glasses were measured at wavelengths around 900nm where the fluorescing $^{5}$ I$_{5}$ level is located. In specific energy range where the frequency upconversion populating $^{5}$ F$_{1}$ state happens, the excitation efficiency of the 1.6 fm emission was deteriorated in fluoride and sulfide hosts. In selenide however spectral line shapes of the excitation spectrum and the '$^{5}$ I$_{8}$ \longrightarrow$^{5}$ I$_{5}$ absorption spectrum looked seemingly identical to each other. Differences in optical nonlinearity as well as electronic band gap energy of the host glasses used are responsible for the experimental observations. On the other hand, codoping of rare earths such as Tb$^{3+}$, Dy$^{3+}$, Eu$^{3+}$, and Nd$^{3+}$ was effective in decreasint the terminating $^{5}$ I$_{7}$ level lifetime. However, at the same time, some of the codopants increased unnecessary absorption at the 1.6 $\mu$m wavelengths via their ground state absorption. Though the lifetime quenching effect of Eu$^{3+}$ was moderate, it exhibited no additional extrinsic absorption at the 1.6 $\mu$m band.EX>m band.
Since design response spectrum does not reflect local soil characteristics, site specific response spectrum of observed ground motions appears relatively higher than design response spectrum at high frequency range. These problems have been pointed out from the domestic seismic design industry. Among various estimation methods, this study used the method H/V ratio of ground motion for estimating site amplification. This method has been extended to background noise, Coda waves and S waves recently for estimating site amplification. This study applied this method to the background noise and Coda wave energy. This study analysed more than 267 background noises from 15 macro earthquakes including main Fukuoka earthquake (2005/03/20, M=6.5) and then compared to results from S waves, at 8 main domestic seismic stations. The results showed that most of the domestic seismic stations gave similar results to those from S waves. Each station showed its own characteristics of site amplification property in low, high and specific resonance frequency ranges. Comparison of this study to other studies using different method can give us much information about dynamic amplification of domestic sites characteristics and site classification.
Park Hyung-Soo;Lee Jong-Kyung;Lee Hyo-Won;Kim Su-Gon;Ha Jong-Kyu
Journal of The Korean Society of Grassland and Forage Science
/
v.26
no.1
/
pp.45-52
/
2006
This study was carried out to explore the accuracy of Near Infrared Reflectance Spectroscopy (NIRS) fer the prediction of digestibility and energy value of corn silages. The spectral data were regressed against a range of digestibility and energy parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with first and second order derivatization, with scatter correction procedure(SNV-Detrend) to reduce the effect of extraneous noise. Calibration models for NIRS measurements gave multivariate correlation coefficients of determination$(R^2)$ and standard errors of cross validation of 0.92(SECV 1.73), 0.91(SECV 1.13) and 0.93(SECV 1.74) for in vitro dry matter digestibility(IVDMD), in vitro true digestibility(IVTD), and cellulase dry matter digestibility(CDMD), respectively. The standard error of prediction(SEP) and the multiple correlation coefficient of validation$(R^2v)$ on the validation set(n=39) was used in comparing the prediction accuracy. The SEP value was 0.30(TDN), 0.01(NEL), and 0.01(ME). The relative ability of NIRS to predict digestibility and energy value was very good for CDMD, total digestible nutrients(TDN), net energy fer lactation(NEL) and metabolizable energy(ME). This paper shows the potential of NIRS to predict the digestibility and energy value of con silage as a routine method in feeding programmes and for giving advice to farmers.
Kim, Kyung-Jae;Lee, Shung-Hee;Kim, Jung-Woo;Kim, Ha-Won;Shim, Mi-Ja;Choi, Eung-Chil;Kim, Byong-Kak
The Korean Journal of Mycology
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v.13
no.4
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pp.203-212
/
1985
Of 450 strains isolated from the soil microbes collected in various locations in Korea, a strain had a strong inhibitory activity against bacterial ${\alpha}-amylase$ and was named strain DMC-72 of the genus Streptomyces. The amylase inhibitory metabolite produced by this strain was purified by means of acetone precipitation, adsorption on Amberlite IRC-50 and SP-Sephadex C-25. The inhibitor was found to be a derivative of oligosaccharides by spectral and chemical data. The inhibitor was stable at the pH range of $1{\sim}13$ and at $100^{\circ}C$ for half an hour, also inhibited other amylases such as salivary ${\alpha}-amylase$, pancreatic ${\alpha}-amylase$, fungal ${\alpha}-amylase$ and glucoamylase. However, it showed no inhibitory activity against ${\alpha}-glucosidase$, ${\beta}-glucosidase$, dextranase, and ${\beta}-amylase$. The kinetic studies of the inhibitor showed that its inhibitory effects on starch hydrolysis by ${\alpha}-amylase$ were noncompetitive.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
/
2001.06a
/
pp.1243-1243
/
2001
During two consecutive years, it was developed global calibrations for the prediction of fatty acids on Iberian pig fat. These equations should analyse well samples of that animal fat because of their high accuracy (SECV/sub C16:0/ = 0.26%; SECV/sub C18:0/ = 0.28%; SECV/sub C18:1/ = 0.26%; SECV/sub C18:2/ = 0.15%) and their broad covering composition range. In some cases, when new samples are predicted H (Mahalanobis distance) values higher than 3 (recommended value for agricultural products by the ISI software) are obtained. However, there are not any obvious factors which tells that samples scanned are very different to the spectral mean of the calibration population. Furthermore, these samples are well predicted according to the SEP values. The objective of the present work is to deepen the understanding of the H statistic when analysing animal fats. Three different validation files were predicted with equations obtained from January '97 to April '98. The Set A has spectra of 20 samples not included on the calibration file and scanned in May of 1998. The Set B has spectra of 20 samples included on the calibration file and scanned again in November '99. The Set C contains 150 spectra of one sample representative of the mean values (for fatty acids composition) of the calibration file. This sample was analysed three times per week during June '99 to July '00. The H mean values for the Set A, Set B and Set C were respectively 1.35, 14.39 and 11.71. These anomalous values for the Set B and C make not sense because Set B contains replicate subsamples of the same samples scanned during calibration development and Set C only contains spectra of one sample which represent the mean spectrum of the calibration files. Results will be shown to demonstrate that small day to day variations are responsible of the high H values. When a PCA and LIB file are created with calibration samples and spectra of the Set C modelling day to day variations, the H values for Set A, Set B and Set C were respectively 1.83, 2.16 and 0.93.
Esler, Michael B.;Gishen, Mark;Francis, I.Leigh;Dambergs, Robert G.;Kambouris, Ambrosias;Cynkar, Wies U.;Boehm, David R.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
/
2001.06a
/
pp.1523-1523
/
2001
The wine industry requires practical methods for objectively measuring the composition of both red wine grapes on the vine to determine optimal harvest time; and of freshly harvested grapes for efficient allocation to vinery process streams for particular red wine products, and to determine payment of contract grapegrowers. To be practical for industry application these methods must be rapid, inexpensive and accurate. In most cases this restricts the analyses available to measurement of TSS (total soluble solids, predominantly sugars) by refractometry and pH by electropotentiometry. These two parameters, however, do not provide a comprehensive compositional characterization for the purpose of winemaking. The concentration of anthocyanin pigment in red wine grapes is an accepted indicator of potential wine quality and price. However, routine analysis for total anthocyanins is not considered as a practical option by the wider wine industry because of the high cost and slow turnaround time of this multi-step wet chemical laboratory analysis. Recent work by this ${group}^{l,2}$ has established the capability of near infrared (NIR) spectroscopy to provide rapid, accurate and simultaneous measurement of total anthocyanins, TSS and pH in red wine grapes. The analyses may be carried out equally well using either research grade scanning spectrometers or much simpler reduced spectral range portable diode-array based instrumentation. We have recently expanded on this work by collecting thousands of red wine grape samples in Australia. The sample set spans two vintages (1999 and 2000), five distinct geographical winegrowing regions and three main red wine grape varieties used in Australia (Cabernet Sauvignon, Shiraz and Merlot). Homogenized grape samples were scanned in diffuse reflectance mode on a FOSE NIR Systems6500 spectrometer and subject to laboratory analysis by the traditional methods for total anthocyanins, TSS and pH. We report here an analysis of the correlations between the NIR spectra and the laboratory data using standard chemometric algorithms within The Unscrambler software package. In particular, various subsets of the total data set are considered in turn to elucidate the effects of vintage, geographical area and grape variety on the measurement of grape composition by NIR spectroscopy. The relative ability of discrete calibrations to predict within and across these differences is considered. The results are then used to propose an optimal calibration strategy for red wine grape analysis.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
/
2001.06a
/
pp.1273-1273
/
2001
The efficiency of the luminal fermentation process influences overall efficiency of luminal production, animal health and reproduction. Ruminant production systems have a significant impact on the global environment, as well. Animal wastes contribute to pollution of the environment as ammonia volatilized to the air and nitrate leached to ground water. Microbial protein synthesis in the rumen satisfies a large proportion of the protein requirements of animals. Quantifying the microbial synthesis is possible by using markers for lumen bacteria and protozoa such as nucleic acids, purine bases, some specific amino acids, or by isotopic $^{15}N,^{32}P,\;and\;^{35}S$ labelled feeds. All those methods require cannulated animals, they are time-consuming and some methods are very expensive as well. Many attempts have been made to find an alternative method for indirect measurement of microbial synthesis in intact animals. The present investigations aimed to assess possibilities of NIRS for prediction of purine nitrogen excretion and ruminal microbial nitrogen synthesis by NIR spectra of urine. Urine samples were collected from 12 growing sheep,6 of them male, and 6- female. The sheep were included in feeding experiment. The ration consisted of sorghum silage and protein supplements -70:30 on dry matter basis. The protein supplements were chosen to differ in protein degradability. The urine samples were collected daily in a vessel containing $60m{\ell}$ 10% sulphuric acid to reduce pH below 3 and diluted with tap water to 4 liters. Samples were stored in plastic bottles and frozen at $-20^{\circ}C$ until chemical and NIRS analysis. The urine samples were analyzed for purine derivates - allantoin, uric acid, xantine and hypoxantine content. Microbial nitrogen synthesis in the lumen was calculated according to Chen and Gomes, 1995. Transmittance urine spectra with sample thickness 1mm were obtained by NIR System 6500 spectrophotometer in the spectral range 1100-2500nm. The calibration was performed using ISI software and PLS regression, respectively. The following statistical results of NIRS calibration for prediction of purine derivatives and microbial protein synthesis were obtained.(Table Omitted). The result of estimation of purine nitrogen excretion and microbial protein synthesis by NIR spectra of urine showed accuracy, adequate for rapid evaluation of microbial protein synthesis for a large number of animals and different diets. The results indicate that the advantages of the NIRS technology can be extended into animal physiological studies. The fast and low cost NIRS analyses could be used with no significant loss of accuracy when microbial protein synthesis in the lumen and the microbial protein flow in the duodenum are to be assessed by NIRS.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
/
2001.06a
/
pp.1121-1121
/
2001
A previous study (Berzaghi et al., 2001) evaluated the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural networks (ANN) on the prediction of the chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with reference values for moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected using 10 different Foss NIR Systems instruments, only some of which had been standardized to one master instrument. The aim of the present study was to evaluate the behaviour of these different calibration methods when predicting the same samples measured on different instruments. Twenty-two sealed samples of different kind of forages were measured in duplicate on seven instruments (one master and six slaves). Three sets of near infrared spectra (1100 to 2500nm) were created. The first set consisted of the spectra in their original form (unstandardized); the second set was created using a single sample standardization (Clone1); the third was created using a multiple sample procedure (Clone6). WinISI software (Infrasoft International Inc., Port Mathilda, PA, USA) was used to perform both types of standardization, Clone1 is just a photometric offset between a “master” instrument and the “slave” instrument. Clone6 modifies both the X-axis through a wavelength adjustment and the Y-axis through a simple regression wavelength by wavelength. The Clone1 procedure used one sample spectrally close to the centre of the population. The six samples used in Clone 6 were selected to cover the range of spectral variation in the sample set. The remaining fifteen samples were used to evaluate the performances of the different models. The predicted values for dry matter, protein and neutral detergent fibre from the master Instrument were considered as “reference Y values” when computing the statistics RMSEP, SEPC, R, Bias, Slope, mean GH (global Mahalanobis distance) and mean NH (neighbourhood Mahalanobis distance) for the 6 slave instruments. From the results we conclude that i) all the calibration techniques gave satisfactory results after standardization. Without standardization the predicted data from the slaves would have required slope and bias correction to produce acceptable statistics. ii) Standardization reduced the errors for all calibration methods and parameters tested, reducing not only systematic biases but also random errors. iii) Standardization removed slope effects that were significantly different from 1.0 in most of the cases. iv) Clone1 and Clone6 gave similar results except for NDF where Clone6 gave better RMSEP values than Clone1. v) GH and NH were reduced by half even with very large data sets including unstandardized spectra.
Volcanic ash (VA) can be estimated by remote sensing sensors through their spectral signatures determined by the inherent optical property (IOP) including complex refractive index and the scattering properties. Until now, a very limited range of VA refractive indices has been reported and the VA from each volcanic eruption has a different composition. To improve the robustness of VA remote sensing, there is a need to understanding of VA - radiation interactions. In this study, we calculated extinction coefficient, scattering phase function, asymmetry factor, and single scattering albedo which show different values between andesite and pumice. Then, IOPs were used to analyze the relationship between theoretical remote sensed radiation calculated by radiative transfer model under various aerosol optical thickness (${\tau}$) and sun-sensor geometries and characteristics of VA. It was found that the mean rate of change of radiance at top of atmosphere versus ${\tau}$ is six times larger than in radiance values at 0.55 ${\mu}m$. At the surface, positive correlation dominates when ${\tau}$ <1, but negative correlation dominates when ${\tau}$ >1. However, radiance differences between andesite and pumice at 11 ${\mu}m$ are very small. These differences between two VA types are expressed as the polynomial regression functions and that increase as VA optical thickness increases. Finally, these results would allow VA to be better characterized by remote sensing sensors.
KOMPSAT-3A images have been used in various kinds of applications, since its launch in 2015. However, there were limits to scientific analysis and application extensions of these data, such as vegetation index estimation, because no tool was developed to obtain the surface reflectance required for analysis of the actual land environment. The surface reflectance is a product of performing an absolute atmospheric correction or calibration. The objective of this study is to quantitatively verify the accuracy of top-of-atmosphere reflectance and surface reflectance of KOMPSAT-3A images produced from the OTB open-source extension program, performing the cross-validation with those provided by a site measurement data of RadCalNet, an international Calibration/Validation (Cal/Val) portal. Besides, surface reflectance was obtained from Landsat-8 OLI images in the same site and applied together to the cross-validation process. According to the experiment, it is proven that the top-of-atmosphere reflectance of KOMPSAT-3A images differs by up to ± 0.02 in the range of 0.00 to 1.00 compared to the mean value of the RadCalNet data corresponding to the same spectral band. Surface reflectance in KOMPSAT-3A images also showed a high degree of consistency with RadCalNet data representing the difference of 0.02 to 0.04. These results are expected to be applicable to generate the value-added products of KOMPSAT-3A images as analysisready data (ARD). The tools applied in thisstudy and the research scheme can be extended as the new implementation of each sensor model to new types of multispectral images of compact advanced satellites (CAS) for land, agriculture, and forestry and the verification method, respectively.
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