• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.169-176
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• 2021

The Global Space-based Inter-Calibration System (GSICS) is an international partnership sponsored by World Meteorological Organization (WMO) to continue and improve climate monitoring and to ensure consistent accuracy between observation data from meteorological satellites operating around the world. The objective for GSICS is to inter-calibration from pairs of satellites observations, which includes direct comparison of collocated Geostationary Earth Orbit (GEO)-Low Earth Orbit (LEO) observations. One of the GSICS inter-calibration methods, the Ray-matching technique, is a surrogate approach that uses matched, co-angled and co-located pixels to transfer the calibration from a well calibrated satellite sensor to another sensor. In Korea, the first GEO satellite, Communication Ocean and Meteorological Satellite (COMS), is used to participate in the GSICS program. The National Meteorological Satellite Center (NMSC), which operated COMS/MI, calculated the Radiative Transfer Model (RTM)-based GSICS coefficient coefficients. The L1P reproduced through GSICS correction coefficient showed lower RMSE and Bias than L1B without GSICS correction coefficient applied. The calculation cycles of the GSICS correction coefficients for COMS/MI visible channel are provided annual and diurnal (2, 5, 10, 14-day), but long-term evaluation according to these cycles was not performed. The purpose of this paper is to perform evaluation depending on the annual/diurnal cycles of COMS/MI GSICS correction coefficients based on the ray-matching technique using Suomi-NPP/Visible Infrared Imaging Radiometer Suite (VIIRS) data as reference data. As a result of evaluation, the diurnal cycle had a higher coincidence rate with the reference data than the annual cycle, and the 14-day diurnal cycle was the most suitable for use as the GSICS correction coefficient.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.566-571
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• 2009

A calibration method for multiple sets of stereo vision cameras is proposed. To measure the three-dimensional shape of a very long object, measuring the object at different viewpoints and registration of the data are necessary. In this study, two lasers beams generate two strings of calibration targets, which form straight lines in the world coordinate system. An evaluation function is defined to calculate the sum of the squares of the distances between each transformed target and the fitted line representing the laser beam to each target, and the distances between points appearing in the data sets of two adjacent viewpoints. The calculation process for the approximation method based on data linearity is presented. The experimental results show the effectiveness of the method.

• Journal of Astronomy and Space Sciences
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• v.9 no.2
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• pp.193-202
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• 1992

The fist sounding rocket in Korea, KSR-420S has been under the development at Korea Aerospace Research Institute (KARI), and is expected to be launched in 1993 to measure the vertical ozone profile over the Korean Peninsula. The KSR-420S is expected to provide the fist in situ measurement of ozone concentrations over the Korean Peninsula. An optical ozone detector has been developed at Korea Research Institute of Standards and Science (KRISS), and its calibration has been completed recently. In this paper, measurement principles of the ozone detector in KSR-420S, its calibration data, ozone measurement procedure and data reduction algorithm are presented with sample calculations.

• Korean Journal of Remote Sensing
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• v.18 no.5
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• pp.281-289
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• 2002

Although EOC data have been frequently used in several applications since the launch of the KOMPSAT-1 satellite in 1999, its radiometric characteristics are not clear due to the inherent limitations of the on-board calibration system. The radiometric characteristics of remotely sensed imagery can be measured by the sensitivity of radiant flux coming from various surface features on the earth. The objective of this study is to analyze the radiometric characteristics of EOC data by simulating the sensor- received radiance. Initially, spectral reflectance values of reference targets were measured on the ground by using a portable spectre-radiometer at the EOC spectrum. A radiative transfer model, LOWTRAN, then simulated the sensor-received radiance values of the same reference target. By correlating the digital number (DN) extracted from the EOC image to the corresponding radiance values simulated from LOWTRAN, we could find the radiometric calibration coefficients for EOC image. The radiometric gain coefficients of EOC are very similar to those of other panchromatic optical sensors.

• The Korean Journal of Applied Statistics
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• v.7 no.1
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• pp.1-17
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• 1994

This article basically considers the calibration problem with censored data from the Bayesian point of view. The Gibbs sampling method is discussed to solve the difficulty encountered in computing the posterior distribution. Also presented is an approach for impementing the Gibbs sampling in actual data situation with the estimation procedures.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1614-1614
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• 2001

The sweetness (。Bix) of fruit is the main quality factor contributing to the fruit taste. The brix of the apple fruit can be measured non-destructively by near infrared (NIR) spectroscopy, allowing the sweetness grading of individual apple fruit. However, the fruit quality is influenced by various factors such as growing location, producing year, variety and harvest time etc., accordingly the robust NIR calibration is required. In this experimental results are presented the influence of two variations such as growing location and producing year of apple fruit in establishing of calibrations for sweetness, and developed a stable and highly accurate calibration. Apple fruit (Fuji) was collected every year from 1995 to 1997 in 3 different growing locations (Andong, Youngchun and Chungsong) of Kyungpook in Korea. NIR reflectance spectra of apple fruit were scanned in wavelength range of 1100∼2500nm using an InfraAlyzer 500C (Bran+Luebbe) with halogen lamp and PbS detector. The multiple linear regression and stepwise was carried out between the NIR raw spectra and the brix measured by refractometer to select the best regression equations. The calibration models by each growing district were well predicted to dependent sample set, but poorly predicted to independent sample set. Combined calibration model using data of three growing districts predicted reasonable well to a population set drawn from all growing districts(SEP = 0.69%, Bias=-0.075). The calibration models by each harvest year were not transferable across harvest year, however a combined calibration model using data of three harvest years was sufficiently robust to predict each sample sets(SEP = 0.53%, Bias = 0.004).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.30-38
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• 2006

A new calibration method for five-hole pressure probe is presented. This method provides accuracies better than those based on the traditional regression method. The calibration algorithm uses a single sector interpolation response surface calculated by comparing the regression curve fits with the actual calibration data. A five-hole pressure probe with hemispherical tip was fabricated and calibrated at Reynolds number of $4.11{\times}10^6$/m and flow angle of ${\pm}48$ degrees. Two data prediction models, the least-square regression and a single sector error interpolation, were evaluated. The comparison of these two calibration methods to a five-hole probe is described and discussed. An evaluation of the calibration accuracy is also given.

• Smart Media Journal
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• v.2 no.1
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• pp.27-30
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• 2013

In this paper, we research the hand tracking and calibration algorithm using the EPIC sensor. We analyze the characteristics of EPIC sensor to be more sensitive in the around E-filed, and then we implement the 2-dimensional axis-transformation using the difference of detected amplitude between EPIC sensors. In addition, we implement the calibration algorithm considering the characteristics of EPIC sensor, and then we apply the Kalman filter to efficiently track a target. Thus, we implement the environment of window applications for verification and analysis the implemented algorithm. In turn, we use the DAQ API to extract the analog data. The DAQ hardware has the function of measuring and generating an electrical signal. Moreover, we confirm the movement of mouse cursor by detecting the potential difference depending on the movement of the user's hands.

• Journal of the Korean Society of Tobacco Science
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• v.22 no.1
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• pp.76-83
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• 2000

This study was carried out to predict blending ratio of cut tobacco(CT), expanded stem(ES), and expanded cut tobacco(ECT) in cigarettes. CT, ES, and ECT samples from A brand were, ground and blended with reference to A blending ratio, and scanned by near infrared spectroscopy(NIRSystem Co., Model 6500). Calibration equations were developed and then determined blending ratio by NIRS. The standard error of calibration(SEC) and performance(SEP) of C factory samples between NIRS and known blending ratio were 0.97%, 1.93% for CT, 0.50%, 1.12 % for ES and 0.68%, 1.10% for ECT, respectively. The SEP of CT, ES and ECT of Band D factory samples determined by C factory calibration equation were more inaccurate than those of C factory samples determined by C factory calibration equations. These results were caused by the difference of CT, ES and ECT spectra followed by each factory. The SEP of CT, ES and ECT of Band D factories determined by calibration equations derived from each factory samples were more accurate than those of determined by calibration equation derived from C factory samples. Each factory SEP of CT, ES and ECT determined by calibration equation derived from all calibration samples(B+C+D factory) was similar to that determined by calibration equation derived from each factory samples. To improve the analytical inaccuracy caused by spectra difference, we need to apply a specific calibration equation for each factory sample. Data in development of specific calibrations between sample and NIRS spectra might supply a method for rapid determination of blending ratio of CT, ES, and ECT.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1141-1141
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• 2001

The aim of the study was to evaluate the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural network (ANN) on the prediction of 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 information relative to moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected with 10 different Foss NIR Systems instruments, which were either standardized or not standardized to one master instrument. The spectra were trimmed to a wavelength range between 1100 and 2498 nm. Two data sets, one standardized (IVAL) and the other not standardized (SVAL) were used as independent validation sets, but 10% of both sets were omitted and kept for later expansion of the calibration database. The remaining samples were combined into one database (n=21,696), which was split into 75% calibration (CALBASE) and 25% validation (VALBASE). The chemical components in the 3 validation data sets were predicted with each model derived from CALBASE using the calibration database before and after it was expanded with 10% of the samples from IVAL and SVAL data sets. Calibration performance was evaluated using standard error of prediction corrected for bias (SEP(C)), bias, slope and R2. None of the models appeared to be consistently better across all validation sets. VALBASE was predicted well by all models, with smaller SEP(C) and bias values than for IVAL and SVAL. This was not surprising as VALBASE was selected from the calibration database and it had a sample population similar to CALBASE, whereas IVAL and SVAL were completely independent validation sets. In most cases, Local and ANN models, but not modified PLS, showed considerable improvement in the prediction of IVAL and SVAL after the calibration database had been expanded with the 10% samples of IVAL and SVAL reserved for calibration expansion. The effects of sample processing, instrument standardization and differences in reference procedure were partially confounded in the validation sets, so it was not possible to determine which factors were most important. Further work on the development of large databases must address the problems of standardization of instruments, harmonization and standardization of laboratory procedures and even more importantly, the definition of the database population.