• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.2
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• pp.44-48
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• 2017

Purpose Estradiol (E2) is a steroid hormone mainly produced in women and is a useful indicator for diagnosis of gynecological diseases, menstrual cycle, menopause, and precocious puberty. E2 measurement is performed by diluting the $^{125}I$ radioactive tracer and tracer buffer in the kit. However, It was not precisely specified when the period of tracer is available after activating. The purpose of this study was to determine the appropriate dilution time based on the measurement value with dilution time. Materials and Methods From December 2016 to February 2017, 60 E2 samples with concentrations ranging from 8 to 4577 pg/mL were divided into low, medium, and high concentrations. Dilution of the $^{125}I$ tracer was performed on a 230 RPM agitator for 30 minutes, 1 hour 30 minutes, and 2 hours 30 minutes, respectively. 24 hour dilution was gently shaken and refrigerated. To verify the difference and significance of the results according to the dilution time, a test of normality was performed using SPSS 18.0 and analyzed by Kruskal-Wallis test. The measured value according to the dilution time was compared with the interquartile range of the absolute error. Results The results of Kruskal-Wallis test were not significant (P>0.05). Measurement results are showed as interquartile range of absolute error. At low concentration, it is 0.052 between 1 hour 30 minutes and 2 hours 30 minutes, and 0.105 between 30 minutes and 1 hour 30 minutes. At medium concentration, 0.062 between 30 minutes and 1 hour 30 minutes, and 0.038 between 1 hour 30 minutes and 2 hours 30 minutes. At high concentration, it is 0.029 between 1 hour 30 minutes and 2 hours 30 minutes, and 0.06 between 2 hours 30 minutes and 24 hours. Conclusion There were no statistically significant differences. However, the change in the measured value is the smallest between 1 hour and 30 minutes to 2 hours and 30 minutes. Therefore, we recommend diluting time between 1 hour 30 minutes and 2 hours 30 minutes.

• Radiation Oncology Journal
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• v.15 no.1
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• pp.71-78
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• 1997

Purpose : To collect beam data for dynamic wedge fields using conventional measurement tools without the multi-detector system, such as the linear diode detectors or ionization chambers. Materials and Methods : The accelerator CL 2100 C/D has two photon energies of 6MV and 15MV with dynamic wedge an91es of 15o, 30o, 45o and 60o. Wedge transmission factors, percentage depth doses(PDD's) and dose Profiles were measured. The measurements for wedge transmission factors are performed for field sizes ranging from $4\times4cm^2\;to\;20\times20cm^2$ in 1-2cm steps. Various rectangular field sizes are also measured for each photon energy of 6MV and 15MV, with the combination of each dynamic wedge angle of 15o 30o. 45o and 60o. These factors are compared to the calculated wedge factors using STT(Segmented Treatment Table) value. PDD's are measured with the film and the chamber in water Phantom for fixed square field. Converting parameters for film data to chamber data could be obtained from this procedure. The PDD's for dynamic wedged fields could be obtained from film dosimetry by using the converting parameters without using ionization chamber. Dose profiles are obtained from interpolation and STT weighted superposition of data through selected asymmetric static field measurement using ionization chamber. Results : The measured values of wedge transmission factors show good agreement to the calculated values The wedge factors of rectangular fields for constant V-field were equal to those of square fields The differences between open fields' PDDs and those from dynamic fields are insignificant. Dose profiles from superposition method showed acceptable range of accuracy(maximum 2% error) when we compare to those from film dosimetry. Conclusion : The results from this superposition method showed that commissionning of dynamic wedge could be done with conventional dosimetric tools such as Point detector system and film dosimetry winthin maximum 2% error range of accuracy.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.333-346
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• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.387-396
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• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Horticultural Science & Technology
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• v.34 no.2
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• pp.269-281
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• 2016

The statistical analyses of coefficient of variation, heritability, and genetic advance were carried out to identify differences in morphological characteristics, such as the stem and inflorescence length, of 10 major commercial cultivars of spray chrysanthemum (Chrysanthemum morifolium). For morphological characteristics, stem lengths ranged from 46.4 cm to 54.9 cm, the maximum diameter of stem was 5.6 to 8.5 mm, the hardness of the stem was 0.17 to $0.70kg{\cdot}m^{-2}$, the fresh weight of stem was 7.5 to 17.5 g, the dry weight of the stem was 1.6 to 3.3 g, the ratio of dry weight/fresh weight of stem was 15.9% to 23.1%. Also, the number of leaves on the stem was 8.4 to 12.2, the stem leaf area was 17.8 to $37.8m^2$, the fresh weight stem leaves was 5.3 to 18.6 g, the dry weight was 0.5 to 1.4 g and the ratio of dry weight /fresh weight of stem leaves was 7.6% to 11.5%. The inflorescence length ranged from 10.1 to 18.6 cm, the fresh weight of inflorescence was 7.3 to 26.7 g, the dry weight of inflorescence was 1.2 to 2.8 g, the ratio of dry weight /fresh weight of inflorescence was 10.4% to 17.1%. For flower, the diameter of the flower center was 8.2 to 13.3 mm, the petal width was 5.7 to 14.0 mm, the petal length was 12.9 to 33.1 mm, and the petal thickness was 157.8 to $354.4{\mu}m$. The mean values of each character in each cultivar were very different, and DMRT and LSD values based on morphological characteristics among 10 cultivars were highly significant. For variability and genetic parameters, the lowest CV (coefficient of variation), PCV (phenotypic coefficient of variation), and GCV (genotypic coefficient of variation) were 4.79% to 5.15% in stem length, and the highest variations were 62.97% to 65.21% in leaf area. ECV (error or environmental coefficient of variation) was the lowest for leaf area (1.71%) and it was the highest for leaf dry weight (19.30%). Heritability also significantly differed among the characteristics, ranging from 68.69% to 99.67%, the lowest value was shown in ratio of dry weight /fresh weight of stem and the highest value was for leaf area of stem. The value for genetic advance was the lowest in hardness of stem at 0.30 and the highest in leaf thickness at 156.65. The lowest genetic advance as percentage of mean of stem hardness was 9.17%, while the highest percentage of stem length was 134.27%. Thus the characters which had the highest values indicated above show the influence of additive gene action and may provide useful resources for selection programs for agronomic improvement.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.1
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• pp.1-12
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• 1991

An experiment has been carefully designed and performed to verify the theory for the echointergration technique of estimating the density of fish school by the use of steel spheres in a laboratory tank. The spheres used to simulate a fish school were randomly distributed throughout the insonified volume to produce the acoustic echoes similar to those scattered from real fish schools. The backscattered echoes were measured as a function of target density at tow frequencies of 50kHz and 200kHz. Data acquisition, processing and analysis were performed by means of the microcomputer-based sonar-echo processor including a FFT analyzer. Acoustic scattering characteristics of a 36cm mackerel was investigated by measuring fish echoes with frequencies ranging from 47.8kHz to 52.0kHz. The fluctuation of bottom echoes caused by the effects of fish-school attenuation and multiple scattering which occurred in dense aggregations of fishes was also examined by analyzing the echograms of sardine schools obtained by a 50kHz telesounder in the set-net's bagnet, and the echograms obtained by a scientific echo sounder of 50kHz in the East China Sea, respectively. The results obtained can be summarized as follows: 1. The measured and the calculated echo shapes on the steel sphere used to simulate a fish school were in close agreement. 2. The waveform and amplitude of echo signals by a mackerel without swimbladder fluctuated irregularly with the measuring frequency. 3. When a collection of 30 targets/m super(3) lied the shadow region behind another collection of 5 targets/m super(3), the mean losses in echo energy for the 30 targets/m super(3) were about -0.4dB at 50kHz and about -0.2dB at 200kHz, respectively. 4. In the echograms obtained in the East China Sea, the bottom echoes fluctuated remarkably when the dense aggregations of fish appeared between transducer and seabed. Especially, in the case of the echograms of sardine school obtained in a set-net's bagnet, the disappearance of bottom echoes and the lengthening of the echo trace by fish aggregations were observed. Then the mean density of the sardine school was estimated as 36 fish/m super(3). It suggests that when the distribution density of fishes in oceans is greater than this density, the effects of fish-school attenuation and multiple scattering must be taken into account as a possible source of error in fish abundance estimates. 5. The relationship between mean backscattering strength (, dB) and target density ($\rho$, No./m super(3)) were expressed by the equations: =-46.2+13.7 Log($\rho$) at 50kHz and =-43.9+13.4 Log($\rho$) at 200kHz. 6. The difference between the experimentally derived number and the actual number of targets gradually decreased with an increase in the target density and was within 20% when the density was 30 targets/m super(3). From these results, we concluded that when the number of targets in the insonified volume is large, the validity of the echo-integration technique of estimating the density of fish schools could be expected.

• Tuberculosis and Respiratory Diseases
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• v.50 no.3
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• pp.310-319
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• 2001

Background : The peak flowmeter is very useful in monitoring of out-patients as well as those in emergency departments because of its convenience and simplicity with low cost. There have been many studies aimed at determining the accuracy and reproducibility of the peak flow meter in normal population. However, there is a paucity of reports regarding its accuracy in patients with chronic obstructive pulmonary disease(COPD) or asthma. The accuracy of the peak expiratory flow(PEF) measured with a mini-Wright peak flowmeter was assessed by a comparison with the results of a mass flow sensor. Methods : The PEF measurements were performed in 108 patients aged 19-82 years presenting with either a chronic obstructive lung disease or asthma before and after inhaling salbutamol. The PEF measurements from the mini-Wright flowmeter were compared with those obtained by the calibrated mass flow sensor. Results : The average of the readings taken by the mini-Wright meter were 37-39 l/min higher than those taken by the mass flow sensor. The average percentage error of the mini-Wright meter were higher, ranging less than 300 l/min. The mean of the differences between the values obtained using both instruments (the bias)$\pm$limits of agreement(${\pm}2$ SD) were $37.1{\pm}90\;l/min$ for the PEF(p<0.001). Conclusions : The mini-Wright peak flowmeter overestimated the flows in patients with COPD or asthma. It was also found that the accuracy of the mini-Wright peak flowmeter decreased in its mid to low range. The limits of agreement are wide and the difference between the two instruments is significant. Therefore, the measurements made between the two types of machines in patients with asthma or COPD cannot be used interchangeably.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.1
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• pp.50-57
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• 2016

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation ($R^2{_{cv}}$) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, $R^2{_{cv}}$, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy ($R^2{_{cv}}$ 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

• The Journal of Korean Society for Radiation Therapy
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• v.19 no.2
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• pp.99-106
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• 2007

Purpose: The patient's position and anatomy during the treatment course little bit varies to some extend due to setup uncertainties and organ motions. These factors could affected to not only the dose coverage of the gross tumor but over dosage of normal tissue. Setup uncertainties and organ motions can be minimized by precise patient positioning and rigid immobilization device but some anatomical site such as prostate, the internal organ motion due to physiological processes are challenge. In planning procedure, the clinical target volume is a little bit enlarged to create a planning target volume that accounts for setup uncertainties and organ motion as well. These uncertainties lead to differences between the calculated dose by treatment planning system and the actually delivered dose. The purpose of this study was to evaluate the differences of interfractional displacement of organ and GTV based on the tomoimages. Materials and Methods: Over the course of 3 months, 3 patients, those who has applied rectal balloon, treated for prostatic cancer patient's tomoimage were studied. During the treatment sessions 26 tomoimages per patient, Total 76 tomoimages were collected. Tomoimage had been taken everyday after initial setup with lead marker attached on the patient's skin center to comparing with C-T simulation images. Tomoimage was taken after rectal balloon inflated with 60 cc of air for prostate gland immobilization for daily treatment just before treatment and it was used routinely in each case. The intrarectal balloon was inserted to a depth of 6 cm from the anal verge. MVCT image was taken with 5 mm slice thickness after the intrarectal balloon in place and inflated. For this study, lead balls are used to guide the registration between the MVCT and CT simulation images. There are three image fusion methods in the tomotherapy, bone technique, bone/tissue technique, and full image technique. We used all this 3 methods to analysis the setup errors. Initially, image fusions were based on the visual alignment of lead ball, CT anatomy and CT simulation contours and then the radiation therapist registered the MVCT images with the CT simulation images based on the bone based, rectal balloon based and GTV based respectively and registered image was compared with each others. The average and standard deviation of each X, Y, Z and rotation from the initial planning center was calculated for each patient. The image fusions were based on the visual alignment of lead ball, CT anatomy and CT simulation contours. Results: There was a significant difference in the mean variations of the rectal balloon among the methods. Statistical results based on the bone fusion shows that maximum x-direction shift was 8 mm and 4.2 mm to the y-direction. It was statistically significant (P=<0.0001) in balloon based fusion, maximum X and Y shift was 6 mm, 16mm respectively. One patient's result was more than 16 mm shift and that was derived from the rectal expansions due to the bowl gas and stool. GTV based fusion results ranging from 2.7 to 6.6 mm to the x-direction and 4.3$\sim$7.8 mm to the y-direction respectively. We have checked rotational error in this study but there are no significant differences among fusion methods and the result was 0.37$\pm$0.36 in bone based fusion and 0.34$\pm$0.38 in GTV based fusion.