• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.178-186
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• 2009

The quality control is needed to ensure the accuracy of medical information and achieved by evaluating the performance of and maintaining the system and practicing various measurements and evaluations. The Korean Institute for Accreditation of Medical Image, therefore, have held educational program for quality control of special medical equipments. The major of programs participants, however, are radiology specialists with only small number of radiological technologists from some hospitals, furthermore, the follow-up education and the share of information between participants and non-participants are insufficient in general, thus, the knowledge level of radiological technologists, regardless of their participation, is relatively low. This study carried out the questionnaire research for the 500 radiological technologists registered in Korean Society of MRI Technology, on the basis of 2008, and performed analysis for five months from May to Oct., 2008. The questionnaires were delivered by post to each radiological technologists and the response rate was 36%(n=180). The results of this revealed that the 86.7% of respondents felt the necessity of inspection on quality management, while only the 27.8% completed the educational program for manager of special medical equipment. and only the half(53.9%) had the knowledge about inspection on quality management. The completion of educational program had no correlations with sex, age, size of occupying hospital, the number of radiological technologists in occupying site and MRI laboratory, career year of general radiologist and in MRI laboratory, and the presence of biomedical engineering department in occupying hospital. The 78.0% of participants at the educational program for quality management held by the Korean Institute for Accreditation of Medical Image had the knowledge about inspection on quality management(p<.05) whereas the 43.9% of the hospitals held such program and the 54.4% of radiological technologists from those hospitals had related knowledge, which indicated that such programs held by hospitals had not effects on the knowledge level of radiological technologists. This indicates also that the contents, methods, and other conditional factors of educational programs are important for the outcome of them.

• Journal of agriculture & life science
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• v.43 no.2
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• pp.31-38
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• 2009

The DNA sequencer is known to be more sensitive for the quality of template DNA, method of purification followed by sequencing reaction, and gel concentration. Therefore, we investigated optimal conditions for template preparation, purification, sequencing reaction, gel concentration, and injection medium. For plasmid prepara- tion, using chloroform instead of phenol improved the average read length from 532 bp to 684 bp. The addition of 2.5% DMSO sequencing PCR reaction resulted in 200 bp longer sequences. Purification using 50 mM EDTA and 0.6 M Sodium acetate(pH 8.0) presented 20 bp longer sequences than that using 50 mM EDTA(pH 8.0) and 0.6 M sodium acetate(pH 5.2). The injection for sequencing analysis using ABI formamide presented 90 bp longer sequences than that of using formamide deionized by resin. Moreover, there were 150 bp more readable sequences in 3.6% PAGE gel than in 4%. Consequently, it was concluded that an average of 700 bp per reaction with 85% accuracy can be obtained by the following optimal conditions: template preparation using chloroform, 2.5% DMSO, 50 mM EDTA and 0.6 M sodium acetate(pH 8.0), ABI formamide and 3.6% gel concentration.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.99-120
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• 1997

Solar radiation is scattered and absorbed atmospheric compositions in the atmosphere before it reaches the surface and, then after reflected at the surface, until it reaches the satellite sensor. Therefore, consideration of the radiative transfer through the atmosphere is essential for the quantitave analysis of the satellite sensed data, specially at shortwave region. This study examined a feasibility of using radiative transfer code for estimating the atmospheric effects on satellite remote sensing data. To do this, the flux simulated by LOWTRAN7 is compared with CAGEX data in shortwave region. The CAGEX (CERES/ARM/GEWEX Experiment) data provides a dataset of (1) atmospheric soundings, aerosol optical depth and albedo, (2) ARM(Aerosol Radiation Measurement) radiation flux measured by pyrgeometers, pyrheliometer and shadow pyranometer and (3) broadband shortwave flux simulated by Fu-Liou's radiative transfer code. To simulate aerosol effect using the radiative transfer model, the aerosol optical characteristics were extracted from observed aerosol column optical depth, Spinhirne's experimental vertical distribution of scattering coefficient and D'Almeida's statistical atmospheric aerosols radiative characteristics. Simulation of LOWTRAN7 are performed on 31 sample of completely clear days. LOWTRAN's result and CAGEX data are compared on upward, downward direct, downward diffuse solar flux at the surface and upward solar flux at the top of the atmosphere(TOA). The standard errors in LOWTRAN7 simulation of the above components are within 5% except for the downward diffuse solar flux at the surface(6.9%). The results show that a large part of error in LOWTRAN7 flux simulation appeared in the diffuse component due to scattering mainly by atmispheric aerosol. For improving the accuracy of radiative transfer simulation by model, there is a need to provide better information about the radiative charateristrics of atmospheric aerosols.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.33-44
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• 2001

The paper presents several satellite models and satellite image decomposition methods for inaccessible area where ground control points can hardly acquired in conventional ways. First, 10 different satellite sensor models, which were extended from collinearity condition equations, were developed and then behavior of each sensor model was investigated. Secondly, satellite images were decomposed and also pseudo images were generated. The satellite sensor model extended from collinearity equations was represented by the six exterior orientation parameters in $1^{st}$, $2^{nd}$ and $3^{rd}$ order function of satellite image row. Among them, the rotational angle parameters such as $\omega$(omega) and $\Phi$(phi) correlated highly with positional parameters could be assigned to constant values. For inaccessible area, satellite images were decomposed, which means that two consecutive images were combined as one image, The combined image consists of one satellite image with ground control points and the other without ground control points. In addition, a pseudo image which is an imaginary image, was prepared from one satellite image with ground control points and the other without ground control points. In other words, the pseudo image is an arbitrary image bridging two consecutive images. For the experiments, SPOT satellite images exposed to the similar area in different pass were used. Conclusively, it was found that 10 different satellite sensor models and 5 different decomposed methods delivered different levels of accuracy. Among them, the satellite camera model with 1st order function of image row for positional orientation parameters and rotational angle parameter of kappa, and constant rotational angle parameter omega and phi provided the best 60m maximum error at check point with pseudo images arrangement.

• Journal of Food Hygiene and Safety
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• v.34 no.5
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• pp.413-420
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• 2019

In this study, a sample preparation method and a simultaneous determination method by ultra-high performance liquid chromatography coupled with tandem mass spectrometry for 9 isomers of chlorogenic acid and arbutin in fruits were developed. The samples were extracted using 90% methanol (pH 3.0), with the solutions being shaken and then sonicated for 10 min each. After centrifugation at 4,000 rpm for 10 min, the extraction was concentrated under a vacuum at $40^{\circ}C$ using a vacuum evaporator. The residue was dissolved in 5 mL of 5% methanol and filtered through a $0.45{\mu}m$ membrane before UHPLC-MS/MS analysis. The separations were performed on a C18 column with gradient elution of water (containing 0.1% formic acid) and methanol (containing 0.1% formic acid). The specificity, linearity, limit of detection, limit of quantification, accuracy, and precision of the proposed methods were also evaluated.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1177-1186
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• 2021

As the Arctic melt ponds play an important role in determining the interannual variation of the sea ice extent and changes in the Arctic environment, it is crucial to monitor the Arctic melt ponds with high accuracy. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), which is the NASA's latest altimeter satellite based on the green laser (532 nm), observes the global surface elevation. When compared to the CryoSat-2 altimetry satellite whose along-track resolution is 250 m, ICESat-2 is highly expected to provide much more detailed information about Arctic melt ponds thanks to its high along-track resolution of 70 cm. The basic products of ICESat-2 are the surface height and the number of reflected photons. To aggregate the neighboring information of a specific ICESat-2 photon, the segments of photons with 10 m length were used. The standard deviation of the height and the total number of photons were calculated for each segment. As the melt ponds have the smoother surface than the sea ice, the lower variation of the height over melt ponds can make the melt ponds distinguished from the sea ice. When the melt ponds were extracted, the number of photons per segment was used to classify the melt ponds covered with open-water and specular ice. As photons are much more absorbed in the water-covered melt pondsthan the melt ponds with the specular ice, the number of photons persegment can distinguish the water- and ice-covered ponds. As a result, the suggested melt pond detection method was able to classify the sea ice, water-covered melt ponds, and ice-covered melt ponds. A qualitative analysis was conducted using the Sentinel-2 optical imagery. The suggested method successfully classified the water- and ice-covered ponds which were difficult to distinguish with Sentinel-2 optical images. Lastly, the pros and cons of the melt pond detection using satellite altimetry and optical images were discussed.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.367-376
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• 2021

Strawberry cultivation in Korea is grown in greenhouse, but most farms manage their water supply using a timer control method based on the experience of growers. The timer control has problems in that it is difficult to consider the weather condition, the growth stage of crops, and the moisture content of the substrate, so that the crops cannot be managed at an optimal level, and the accuracy of cultivation management are lacking. The watering methods using integrated solar irradiance and substrate moisture contents are control systems that provide eco-friendly and precise water supply considering the growth conditions of crops. The purpose of this study was to compare the combined water supply control with integrated solar irradiance and substrate moisture contents and timer control method in hydroponic cultivation of strawberries using coir, and to set the optimal integrated solar irradiance level for complex water supply control. The irrigation system was automatically watered when it reached 100, 150, 250 J·cm^-2 based on the external solar irradiance, and forced irrigation was performed at a substrate moisture content of less than 60% in all treatments. The amount of irrigation at once was 50 mL. The timer treatment was applied as a control. The smaller the level of integrated radiation to start watering, the greater the daily amount of irrigation. Both the fresh weight and dry weight per plant were higher in the complex irrigation control method than the timer control, and the 100 and 150 J·cm^-2 treatment had the highest fresh weight, and the 100 J·cm^-2 treatment showed a significantly higher dry weight. The yield was also significantly higher in the complex control method than in the timer, and the early yield increased as the level of integrated solar irradiance was smaller. The fresh weight of fruit was the lowest in the timer-controlled irrigation. As a result of this study, the possibility of combined control irrigation method using integrated solar irradiance and substrate moisture content was confirmed for precise water supply management of strawberries in hydroponics.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1631-1645
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• 2021

This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1829-1836
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• 2021

Cloud detection means determining the presence or absence of clouds in a pixel in a satellite image, and acts as an important factor affecting the utility and accuracy of the satellite image. In this study, among the satellites of various advanced organizations that provide cloud detection data, we intend to perform quantitative and qualitative comparative analysis on the difference between the cloud detection data of GK-2A/AMI, Terra/MODIS, and Suomi-NPP/VIIRS. As a result of quantitative comparison, the Proportion Correct (PC) index values in January were 74.16% for GK-2A & MODIS, 75.39% for GK-2A & VIIRS, and 87.35% for GK-2A & MODIS in April, and GK-2A & VIIRS showed that 87.71% of clouds were detected in April compared to January without much difference by satellite. As for the qualitative comparison results, when compared with RGB images, it was confirmed that the results corresponding to April rather than January detected clouds better than the previous quantitative results. However, if thin clouds or snow cover exist, each satellite were some differences in the cloud detection results.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.