• Progress in Medical Physics
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• v.23 no.4
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• pp.261-268
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• 2012

Breast cancer is the second leading cause of women cancer death in Korea. The key for reducing disease mortality is early detection. Although digital mammography (DM) has been credited as one of the major reasons for the early detection to decrease in breast cancer mortality observed in the last 20 years, DM is far from perfect for several limitations. Digital breast tomosynthesis (DBT) is expected to overcome some inherent limitations of conventional mammography caused by overlapping of normal tissue and pathological tissue during the standard 2D projections for the improved lesion margin visibility and early breast cancer detection. In this study, we compared a DM system and DBT system acquired with different thickness of breast phantom. We acquired breast phantom data with same average glandular dose (AGD) from 1 mGy to 4 mGy under same experimental condition. The contrast, micro-calcification measurement accuracy and observer study were conducted with breast phantom images. As a result, the higher accuracy of lesion detection with DBT system compared to DM system was demonstrated in this study. Furthermore, the pain of patients caused by severe compression can be reduced with DBT system. In conclusion, the results indicated that DBT system play an important role in breast cancer detection.

• Journal of the korean academy of Pediatric Dentistry
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• v.28 no.4
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• pp.613-619
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• 2001

The aims of this study were to compare the accuracy, sensitivity and specificity of cnventional visual examination, radiography and a new laser fluorescence method, KaVo Diagnodent, for the detection of occlusal caries lesions. One hundred sound human premolars and molars which had no restorations or interproximal cavities were tested by three methods. Tooth lesions depth was assessed at histologic examination using Caries detector dye The following results were obtained. 1. Diagnodent show 7.8 in sound tooth, 25.4 in initial caries, 30.5 in enamel caries, and 53.8 in dentin caries with average score 2. Spearman and Pearson relation coefficient was high between tooth-specimen test with dye and Diagnodent(0.736, 0.619), visual examination(0.664, 0.666), and was low between tooth-specimen test with dye and radiographic examination(P<0.01, total) 3. Accuracy of occlusal caries was highest on Diagnodent(65%) and lowest on radiographic examination(35%) 4. In initial caries, the sensitivity and specificity of Diagnodent method was the highest. In enamel caries, the sensitivity of visual examination was the highest and specificity of Diagnodent method was the highest. In dentinal caries, the sensitivity and specificity of Diagnodent method was the highest and sensitivity of visual examination was the lowest.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.19-26
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• 2017

Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.

• Journal of Genetic Medicine
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• v.7 no.1
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• pp.53-58
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• 2010

Purpose: To find the most effective method for extraction of cell-free DNA (cf-DNA) from maternal plasma, we compared a blood DNA extraction system (blood kit) and a viral DNA extraction system (viral kit) for non-invasive first-trimester fetal gender determination. Materials and Methods: A prospective cohort study was conducted with maternal plasma collected from 44 women in the first-trimester of pregnancy. The cf-DNA was extracted from maternal plasma using a blood kit and a viral kit. Quantitative fluorescent-polymerase chain reaction (QF-PCR) was used to detect the SRY gene and AMEL gene. The diagnostic accuracy of the QF-PCR results was determined based on comparison with the final delivery records. Results: A total of 44 women were tested, but the final delivery record was only obtained in 36 cases which included 16 male-bearing and 20 female-bearing pregnancies. For the blood kit and viral kit, the diagnostic accuracies for fetal gender determination were 63.9% (23/36) and 97.2% (35/36), respectively. Conclusion: In non-invasive first-trimester fetal gender determination by QF-PCR, using a viral kit for extraction of cf-DNA may result in a higher diagnostic accuracy.

• Analytical Science and Technology
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• v.29 no.4
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• pp.170-178
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• 2016

Accuracy and precision of ID methods for different spike isotopes of ⁷⁶Se, ⁷⁷Se, and ⁷⁸Se were compared for the analysis of Selenium using quadrupole ICP/MS equipped with Octopole reaction cell. From the analysis of Se inorganic standard solution, all of three spikes showed less than 1 % error and 1 % RSD for both short-term (a day) and long-term (several months) periods. They showed similar results with each other and ⁷⁸Se showed was a bit better than ⁷⁶Se and ⁷⁷Se. However, different spikes showed different results when NIST SRM 1568a and SRM 2967 were analyzed because of the several interferences on the m/z measured and calculated. Interferences due to the generation of SeH from ORC was considered as well as As and Br in matrix. The results showed similar accuracy and precisions against SRM 1568a, which has a simple background matrix, for all three spikes and the recovery rate was about 80% with steadiness. The %RSD was a bit higher than inorganic standard (1.8 %, 8.6 %, and 6.3 % for ⁷⁸Se, ⁷⁶Se and ⁷⁷Se, respectively) but low enough to conclude that this experiment is reliable. However, mussel tissue has a complex matrix showed inaccurate results in case of ⁷⁸Se isotope spike (over 100 % RSD). ⁷⁶Se and ⁷⁷Se showd relatively good results of around 98.6 % and 104.2 % recovery rate. The errors were less than 5 % but the precision was a bit higher value of 15 % RSD. This clearly shows that Br interferences are so large that a simple mathematical calibration is not enough for a complex-matrixed sample. In conclusion, all three spikes show similar results when matrix is simple. However, ⁷⁸Se should be avoided when large amount of Br exists in matrix. Either ⁷⁶Se or ⁷⁷Se would provide accurate results.

• Journal of Wetlands Research
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• v.12 no.1
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• pp.95-103
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• 2010

Discharge data examine the process of hydrologic cycle and used significantly in water resource planning and irrigation and flood control planning. However, it needs lots of time and money to get the discharge data. So discharge rating curve is usually used in converting discharge data. Therefore reliability of discharge rating curve absolutely depends on quality of discharge data. Many engineers who study hydrologic engineering make high quality discharge data to develop reliable discharge rating curve. And they carry out research on standard and method of discharge measurement, and equipment improvement. Now various flow meters are utilized to make discharge data in Korea. However, accuracy of equipment and experimental research data from measurement are not enough. In this paper, constant discharge flowed through standard concrete channel, and the velocity is measured using various flow meters. Also Discharge is calculated by measured data to compare and analyze. The equipment for the experiment is Price AA(USGS Type AA Current meter), flow meter, ADC, C2 small current meter, flow tracker, Electromagnetic current meter. The discharge got form various flow meters which are widely used for discharge measurement. The various depths of water were examined and compared such as 0.30 m, 0.35 m, 0.40 m, 0.45 m, 0.50 m, 0.55 m. The experiment progresses a round-measurement on 6-case. Wading measurement(one point method : the 60 % height in surface of the water) was applied to improve creditability and accuracy among measurement methods. USGS Type AA current Meter, Flow Meter, ADC, C2 Small Current meter got the certificate of quality guaranteed. So the results of experiment were used to compare discharge. The Results showed the difference based on USGS Type AA current Meter at average discharge and velocity. Electromagnetic current meter made differences over $\pm$ 10 % and Flow Meter made differences under $\pm$ 10 %. Also ADC, Flow Meter, C2 Small Current meter made differences under $\pm$ 5 %.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.97-105
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• 2018

Purpose : Proton Therapy using Bragg-peak, because it has distinct characteristics in providing maximum dosage for tumor and minimal dosage for normal tissue, a medical imaging system that can quantify changes in patient position or treatment area is of paramount importance to the treatment of protons. The purpose of this research is to evaluate the usefulness of the algorithm by comparing the image matching through the set-up and in-house code through the existing dips program by producing a Matlab-based in-house registration code to determine the error value between dips and DRR to evaluate the accuracy of the existing treatment. Materials and Methods : Thirteen patients with brain tumors and head and neck cancer who received proton therapy were included in this study and used the DIPS Program System (Version 2.4.3, IBA, Belgium) for image comparison and the Eclipse Proton Planning System (Version 13.7, Varian, USA) for patient treatment planning. For Validation of the Registration method, a test image was artificially rotated and moved to match the existing image, and the initial set up image of DIPS program of existing set up process was image-matched with plan DRR, and the error value was obtained, and the usefulness of the algorithm was evaluated. Results : When the test image was moved 0.5, 1, and 10 cm in the left and right directions, the average error was 0.018 cm. When the test image was rotated counterclockwise by 1 and $10^{\circ}$, the error was $0.0011^{\circ}$. When the initial images of four patients were imaged, the mean error was 0.056, 0.044, and 0.053 cm in the order of x, y, and z, and 0.190 and $0.206^{\circ}$ in the order of rotation and pitch. When the final images of 13 patients were imaged, the mean differences were 0.062, 0.085, and 0.074 cm in the order of x, y, and z, and 0.120 cm as the vector value. Rotation and pitch were 0.171 and $0.174^{\circ}$, respectively. Conclusion : The Matlab-based In-house Registration code produced through this study showed accurate Image matching based on Intensity as well as the simple image as well as anatomical structure. Also, the Set-up error through the DIPS program of the existing treatment method showed a very slight difference, confirming the accuracy of the proton therapy. Future development of additional programs and future Intensity-based Matlab In-house code research will be necessary for future clinical applications.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.5
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• pp.399-407
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• 2009

Laser induced breakdown spectroscopy(LIBS) is an simple analysis method for directly quantifying many kinds of soil micro-elements on site using a small size of laser without pre-treatment at any property of materials(solid, liquid and gas). The purpose of this study were to find an optimum condition of the LIBS measurement including wavelengths for quantifying soil elements, to relate spectral properties to the concentration of soil elements using LIBS as a simultaneous un-breakdown quantitative analysis technology, which can be applied for the safety assessment of agricultural products and precision agriculture, and to compare the results with a standardized chemical analysis method. Soil samples classified as fine-silty, mixed, thermic Typic Hapludalf(Memphis series) from grassland and uplands in Tennessee, USA were collected, crushed, and prepared for further analysis or LIBS measurement. The samples were measured using LIBS ranged from 200 to 600 nm(0.03 nm interval) with a Nd:YAG laser at 532 nm, with a beam energy of 25 mJ per pulse, a pulse width of 5 ns, and a repetition rate of 10 Hz. The optimum wavelength(${\lambda}nm$) of LIBS for estimating soil and plant elements were 308.2 nm for Al, 428.3 nm for Ca, 247.8 nm for T-C, 438.3 nm for Fe, 766.5 nm for K, 85.2 nm for Mg, 330.2 nm for Na, 213.6 nm for P, 180.7 nm for S, 288.2 nm for Si, and 351.9 nm for Ti, respectively. Coefficients of determination($r^2$) of calibration curve using standard reference soil samples for each element from LIBS measurement were ranged from 0.863 to 0.977. In comparison with ICP-AES(Inductively coupled plasma atomic emission spectroscopy) measurement, measurement error in terms of relative standard error were calculated. Silicon dioxide(SiO2) concentration estimated from two methods showed good agreement with -3.5% of relative standard error. The relative standard errors for the other elements were high. It implies that the prediction accuracy is low which might be caused by matrix effect such as particle size and constituent of soils. It is necessary to enhance the measurement and prediction accuracy of LIBS by improving pretreatment process, standard reference soil samples, and measurement method for a reliable quantification method.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.589-600
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• 2020

Effective conservation and management of protected areas require monitoring the settlement of invasive alien species and reducing their dispersion capacity. We simulated the potential distribution of invasive alien plant species (IAPS) using three representative species distribution models (Bioclim, GLM, and MaxEnt) based on the IAPS distribution in the forest genetic resource reserve (2,274ha) in Uljin-gun, Korea. We then selected the realistic and suitable species distribution model that reflects the local region and ecological management characteristics based on the simulation results. The simulation predicted the tendency of the IAPS distributed along the linear landscape elements, such as roads, and including some forest harvested area. The statistical comparison of the prediction and accuracy of each model tested in this study showed that the GLM and MaxEnt models generally had high performance and accuracy compared to the Bioclim model. The Bioclim model calculated the largest potential distribution area, followed by GLM and MaxEnt in that order. The Phenomenological review of the simulation results showed that the sample size more significantly affected the GLM and Bioclim models, while the MaxEnt model was the most consistent regardless of the sample size. The optimal model overall for predicting the distribution of IAPS among the three models was the MaxEnt model. The model selection approach based on detailed flora distribution data presented in this study is expected to be useful for efficiently managing the conservation areas and identifying the realistic and precise species distribution model reflecting local characteristics.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1181-1189
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• 2022

Clouds are composed of tiny water droplets, ice crystals, or mixtures suspended in the atmosphere and cover about two-thirds of the Earth's surface. Cloud detection in satellite images is a very difficult task to separate clouds and non-cloud areas because of similar reflectance characteristics to some other ground objects or the ground surface. In contrast to thick clouds, which have distinct characteristics, thin transparent clouds have weak contrast between clouds and background in satellite images and appear mixed with the ground surface. In order to overcome the limitations of transparent clouds in cloud detection, this study conducted cloud detection focusing on transparent clouds using machine learning techniques (Random Forest [RF], Convolutional Neural Networks [CNN]). As reference data, Cloud Mask and Cirrus Mask were used in MOD35 data provided by MOderate Resolution Imaging Spectroradiometer (MODIS), and the pixel ratio of training data was configured to be about 1:1:1 for clouds, transparent clouds, and clear sky for model training considering transparent cloud pixels. As a result of the qualitative comparison of the study, bothRF and CNN successfully detected various types of clouds, including transparent clouds, and in the case of RF+CNN, which mixed the results of the RF model and the CNN model, the cloud detection was well performed, and was confirmed that the limitations of the model were improved. As a quantitative result of the study, the overall accuracy (OA) value of RF was 92%, CNN showed 94.11%, and RF+CNN showed 94.29% accuracy.