• Bulletin of the Korean Chemical Society
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• 제27권11호
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• pp.1825-1831
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• 2006

The influence of solvent viscosity on conformational dynamics of the heme-pocket, a small vacant site near the binding site of myoglobin (Mb) and hemoglobin (Hb), and playing a functionally important role by serving as a station in ligand binding and escape, was studied by probing time-resolved vibrational spectra of CO photodissociated from MbCO and HbCO in $D_2O$, 75 wt% glycerol/$D_2O$, and trehalose at 283 K. Two absorption bands ($B_1$ and $B_2$) of the sample in viscous solvents, arising from CO in the heme pocket, are very similar to those in $D_2O$. Two bands in Mb and Hb under all three solvents exhibit very similar nonexponential spectral evolution ($B_1$ band; blue shifting and broadening, $B_2$ band; narrowing with a negligible shifting), suggesting that in the present experimental time window of 100 ps, the extents of the spectral shift and narrowing is much influenced neither by the viscosity of solvent nor by the quaternary contact of Hb. Spectral evolution can be described by a biexponential function with a fast universal time constant of 0.52 ps and a slow time constant ranging from 13 to 32 ps. For both proteins in all three solvents majority of spectral evolution occurs with the fast universal time constant. The magnitude of the slow rate in the spectral shift of B1 band decreases with increasing solvent viscosity, indicating that it is influenced by global conformational change which is retarded in viscous solvent, thereby serve as a reporter of global conformational change of heme proteins after deligation.

• Journal of Forest and Environmental Science
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• 제24권3호
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• pp.165-169
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• 2008

This study attempts to analyze the relationship between forest volume and age based on 5th NFI data and spectral characteristics of satellite imagery using ASTER sensor in Korea. Forest stand volume and age had the negative correlation with the spectral reflectance in all of the band (Blue, Green, Red, SWIR). With increasing of stand volume and age, spectral reflectance decrease. The spectral reflectance of band1 showed the highest correlation between stand volume and spectral reflectance among the VNIR wavelength. The spectral reflectance band 1, 2 (visible wavelength) and stand age have high correlation compared to other bands. The correlation coefficients between forest volume and vegetation indices have low relationship. This result indicates that the reflectance of blue band may be important factor to improve the potential of optical remote sensing data to estimate forest volume and age.

• 대한의용생체공학회:의공학회지
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• 제11권1호
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• pp.19-24
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• 1990

A simple diffraction grating spectrometer is successfully utilized to distinguish the similar red colored sediments obstained from both of cancer and non-cancer urine reactions caused by the the previous developed reagent for the cancer diagnosis by examining their spectral absorption bands in order to improve its sensitivity and specficity. It is found that the cancer and non-cancer absorp- tion band regions lie between 4250 A and 4750 A and between 5250 A and 5400 A, respectively.

• 천문학회보
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• 제38권1호
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• pp.42.2-42.2
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• 2013

The F-GAMMA (FERMI-GST AGN Multi-frequency Monitoring Alliance) project is a program for the monthly monitoring of the broad-band spectra of currently about 90 selected Fermi-GST AGNs. F-GAMMA utilizes several facilities in cm, mm, sub-mm, infrared and optical bands, achieving an unprecedented coverage for the study of the spectral evolution of powerful relativistic jets in AGNs. The KVN joined the F-GAMMA project in May 2011, aiming to monitor flux density at 22 and 43 GHz. We present the preliminary results of flux density variability, evolution of spectral index, and modulation index.

• Bulletin of the Korean Chemical Society
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• 제20권2호
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• pp.159-162
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• 1999

Three different chemical compositions of total paraffin, total naphthene, total aromatic content in naphtha have been successfully analyzed using FT-Raman spectroscopy. Partial least squares (PLS) regression has been utilized to develop calibration models for each composition from Raman spectral bands. The PLS calibration results showed Blood correlation with those of gas chromatography (GC). Using PLS regression, the spectral information related to each composition has been successfully extracted from highly overlapped Raman spectra of naphtha.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.65-65
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• 2002

In remote sensing, images are acquired over the same area by sensors of different spectral ranges (from the visible to the microwave) and/or with different number, position, and width of spectral bands. These images are generally partially redundant, as they represent the same scene, and partially complementary. For many applications of image classification, the information provided by a single sensor is often incomplete or imprecise resulting in misclassification. Fusion with redundant data can draw more consistent inferences for the interpretation of the scene, and can then improve classification accuracy. The common approach to the classification of multisensor data as a data fusion scheme at pixel level is to concatenate the data into one vector as if they were measurements from a single sensor. The multiband data acquired by a single multispectral sensor or by two or more different sensors are not completely independent, and a certain degree of informative overlap may exist between the observation spaces of the different bands. This dependence may make the data less informative and should be properly modeled in the analysis so that its effect can be eliminated. For modeling and eliminating the effect of such dependence, this study employs a strategy using self and conditional information variation measures. The self information variation reflects the self certainty of the individual bands, while the conditional information variation reflects the degree of dependence of the different bands. One data set might be very less reliable than others in the analysis and even exacerbate the classification results. The unreliable data set should be excluded in the analysis. To account for this, the self information variation is utilized to measure the degrees of reliability. The team of positively dependent bands can gather more information jointly than the team of independent ones. But, when bands are negatively dependent, the combined analysis of these bands may give worse information. Using the conditional information variation measure, the multiband data are split into two or more subsets according the dependence between the bands. Each subsets are classified separately, and a data fusion scheme at decision level is applied to integrate the individual classification results. In this study. a two-level algorithm using hierarchical clustering procedure is used for unsupervised image classification. Hierarchical clustering algorithm is based on similarity measures between all pairs of candidates being considered for merging. In the first level, the image is partitioned as any number of regions which are sets of spatially contiguous pixels so that no union of adjacent regions is statistically uniform. The regions resulted from the low level are clustered into a parsimonious number of groups according to their statistical characteristics. The algorithm has been applied to satellite multispectral data and airbone SAR data.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.159-164
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• 2004

SAM(Spectral Angle Mapper) is the method using the similarly of the angle between pairs of signatures instead of the spectral distance(MDC, MLC etc.) for classification or clustering. In this paper, we applied unsupervised techniques(Unsupervised SAM and ISODATA) to the Hyperspectral Image(Hyperion) which has innumerable, narrow and contiguous spectral bands and Multispectral Image(ETM$\^$+/) for the clustering of signatures. The overall measured accuracies of the USAM and ISODATA of multispectral image were 76.52%, 53.91% and the USAM and ISODATA of hyperspectral image were 63.04%, 53.91%. From the results of our test, we report that the Unsupervised SAM is better classfication technique than ISODATA. Also we believe that the "Spectral Angle" can potentially be one of the most accurate classifier not only multispectral images but hyperspectral images.

• 천문학회보
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• 제40권1호
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• pp.71.2-71.2
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• 2015

We present the high-resolution near-infrared spectra of standard stars observed with Immersion Grating Infrared Spectrograph (IGRINS). IGRINS covers the full spectral range of H and K bands simultaneously with a high spectral resolution (R=40,000), revealing many previously undetected and/or unknown lines. In this work, we present preliminary results of spectroscopic diagnostics for stellar physical parameters. Our ultimate goal is to provide a library of near-infrared spectra of standard stars, which covers all spectral types and luminosity classes, with a high-resolution and high signal to noise ratio ($SNR{\geq}200$).

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.361-364
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• 2008

It is well known that combining spatial and spectral information can improve land use classification from satellite imagery. High spatial resolution classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, extracting the spatial information is one of the most important steps in high resolution satellite image classification. In this paper, we propose a new spatial feature extraction method. The extracted features are integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a Support Vector Machines classifier. In order to evaluate the proposed feature extraction method, we applied our approach to KOMPSAT-2 data and compared the result with the other methods.

• Journal of the Optical Society of Korea
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• 제5권1호
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• pp.9-15
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• 2001

The ocean Scanning Multi-spectral Imager (OSMI) is a payload on the KOrea Multi-Purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring f the study of biological oceanography. OSMI performs solar and dark calibrations for on-orbit instrument calibration. The purpose of the solar calibration is to monitor the degradation of imaging performance for each pixel of 6 spectral bands and to correct the degradation effect on OSMI image during the ground station date processing. The design, the operation concept, and the radiometric characteristics of the solar calibration are investigated. A linear model of image response and a solar calibration radiance model are proposed to study the instrument characteristics using the solar calibration data. The performance of spectral responsivity and spatial response uniformity. The first solar calibration data and the analysis results are important references for further study on the on-orbit stability of OSMI response during its lifetime.