• Bulletin of the Korean Chemical Society
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• v.26 no.1
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• pp.36-37
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• 2005

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.449-461
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• 2021

Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.807-821
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• 2020

The objective of this study is to evaluate the applicability of representative spatio-temporal fusion models developed for the fusion of mid- and low-resolution satellite images in order to construct a set of time-series high-resolution images for crop monitoring. Particularly, the effects of the characteristics of input image pairs on the prediction performance are investigated by considering the principle of spatio-temporal fusion. An experiment on the fusion of multi-temporal Sentinel-2 and RapidEye images in agricultural fields was conducted to evaluate the prediction performance. Three representative fusion models, including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model (SPSTFM), and Flexible Spatiotemporal DAta Fusion (FSDAF), were applied to this comparative experiment. The three spatio-temporal fusion models exhibited different prediction performance in terms of prediction errors and spatial similarity. However, regardless of the model types, the correlation between coarse resolution images acquired on the pair dates and the prediction date was more significant than the difference between the pair dates and the prediction date to improve the prediction performance. In addition, using vegetation index as input for spatio-temporal fusion showed better prediction performance by alleviating error propagation problems, compared with using fused reflectance values in the calculation of vegetation index. These experimental results can be used as basic information for both the selection of optimal image pairs and input types, and the development of an advanced model in spatio-temporal fusion for crop monitoring.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.93-96
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• 2001

In this paper, we present a vision algorithm and method for input image improvement and preprocessing of dented and raised characters on the sidewall of tires. we define optical condition between reflect coefficient and reflectance by the physical vector calculate. On the contrary this work will recognize the engraved characters using the computer vision technique. Tire input images have all most same grey levels between the characters and backgrounds. The reflectance is little from a tire surface. therefore, it's very difficult segment the characters from the background. Moreover, one side of the character string is raised and the other is dented. So, the captured images are varied with the angle of camera and illumination. For optimum input images, the angle between camera and illumination was found out to be with in 90。 .In addition, We used complex filtering with low-pass and high-pass band filters to improve input images, for clear input images. Finally we define equation reflect coefficient and reflectance. By doing this, we obtained good images of tires for pattern recognition.

• Journal of IKEEE
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• v.22 no.1
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• pp.189-192
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• 2018

This study focused on the development of simulation methodology and design optimization for the DBR(Distributed Bragg Reflectors) structures, which are commonly used in manufacturing optical films and the key components of LED chip and LCD inspection equipments. From the multi-layer simulation, the following results are obtained. First, the wavelength(nm) vs. reflectance(%) can be calculated in the DBR structures that $TiO_2$ and $SiO_2$ thin films are stacked alternately. As a results, it is suggested that highly efficient DBR structures can be designed and manufactured using simulation methodology.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.spc1
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• pp.304-309
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• 2006

Near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of fatty acid composition in sesame (Sesamum indicum L.) seed oil. A total of ninety-three samples of intact seeds were scanned in the reflectance mode of a scanning monochromator, and reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations were developed using modified partial least square regression with internal cross validation (n=63). The equations obtained had low standard errors of cross-validation and moderate $R^2$ (coefficient of determination in calibration). Prediction of an external validation set (n=30) showed significant correlation between reference values and NIRS estimated values based on the SEP (standard error of prediction), $r^2$ (coefficient of determination in prediction) and the ratio of standard deviation (SD) of reference data to SEP. The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for oleic and linoleic acid, having good correlation between reference and NIRS estimate. The results indicated that NIRS, a nondestructive screening method could be used to rapidly determine fatty acid composition in sesame seeds in the breeding programs for high quality sesame oil.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.7
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• pp.584-588
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• 2009

Layered ZnS/$CaF_2$/ZnS/Cu film was deposited on glass substrate by using evaporation method. ZnS and $CaF_2$ were chosen as high and low refractive materials. Cu was used as mid-reflective layer. Reflectance with different optical thickness of $CaF_2$ ranging from $0.25{\lambda}\;to\;0.5{\lambda}$ were systematically investigated by using spectrophotometer. In order to expect the experimental results, the simulation program, the Essential Macleod Program(EMP) was adopted and compared with the experimental data. Based on the results taken by spectrophotometer, the ZnS/$CaF_2$/ZnS/Cu multi-layered thin film show the maximum reflectance of 80% at 625nm $(0.25{\lambda}\;in\;CaF_2)$ and 42% at 660nm $(0.5{\lambda}\;in\;CaF_2)$ respectively. As compared with the experimental results and simulation data, it was confirmed the experimental data is well matched with the EMP data.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.143-146
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• 2009

One of the most important issues of crystalline silicon solar cell is minimizing reflectance at the surface. Laser texturing is an isotropic process that will sculpt the surface of a silicon wafer, regardless of its crystallographic orientation. We investigated surface texturing process using Nd-YAG laser ($\lambda$=1064 nm) on multi-crystalline silicon wafer. Removal of slag formed after the laser process was performed using acid solution (HF : $HNO_3$ : $CH_3COOH$ : DI water). The reflectance and carrier lifetime of the samples were measured and analyzed using UV-Vis spectrophotometer and carrier lifetime tester. It was found that the minimum reflectance of the samples was 16.39% and maximum carrier life time was $21.8\;{\mu}s$.

• Journal of the Korea Institute of Military Science and Technology
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• v.1 no.1
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• pp.114-127
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• 1998

A user friendly computer code(EMCOMST; Electro-Magnetic response for COMposite STructures) was developed which provides with computations of the response characteristics such as reflectance and transmittance to the incident wave angles, frequencies, composite thicknesses, ply orientations, and types of backplate as the linearly polarized transverse electro-magnetic wave is emitted to the advanced composite structures. In this investigation were reviewed the electromagnetic characteristics of the continuous orthotropic fiber-reinforced organic matrix composites with or without ferrite fillers, which are actively applied to low-weight and high-strength aircraft structures. Also were calculated the response of the three layered compound structures which have appropriately stacked above-mentioned materials as transmitting layer, absorbing layer, reflection layer, respectively under the specific thickness constraints for mechanical strength design requirements. For the composite structures presented in this study, minimum reflectance value less than -5㏈ can be obtained in the frequency range of 4 to 12 ㎓. In addition, analysis of structures attached isotropic radar absorbing materials(RAM) is facilitated by putting the material properties in the material input card entries adequately.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.5
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• pp.394-406
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• 2004

A split-plot designed experiment including four rice varieties and 10 nitrogen levels was conducted in 2003 at the Experimental Farm of Seoul National University, Suwon, Korea. Before heading, hyperspectral canopy reflectance (300-1100nm with 1.55nm step) and nine crop variables such as shoot fresh weight (SFW), leaf area index, leaf dry weight, shoot dry weight, leaf N concentration, shoot N concentration, leaf N density, shoot N density and N nutrition index were measured at 54 and 72 days after transplanting. Grain yield, total number of spikelets, number of filled spikelets and 1000-grain weight were measured at harvest. 14,635 narrow-band NDVIs as combinations of reflectances at wavelength ${\lambda}l\;and\;{\lambda}2$ were correlated to the nine crop variables. One NDVI with the highest correlation coefficient with a given crop variable was selected as the NDVI of the best fit for this crop variable. As expected, models to predict crop variables before heading using the NDVI of the best fit had higher $r^2$ (>10\%)$ than those using common broad- band NDVI red or NDVI green. The models with the narrow-band NDVI of the best fit overcame broad- band NDVI saturation at high LAI values as frequently reported. Models using NDVIs of the best fit at booting showed higher predictive capacity for yield and yield component than models using crop variables.