• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.232-240
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• 2018

This study is to suggest a method to evaluate the detector performance using change of absorbed dose and histogram according to sensitivity change of Auto Exposure Control(AEC). The experiment site is skull, abdomen pelvis and the accuracy of the detector was evaluated by measuring the absorbed dose of the detector sensitivity S200, S400, S800, S1000. Also the dynamic range of the detector was evaluated through the histogram analysis. As a result, the absorbed dose decreased gradually as the sensitivity was set higher from S200 to S1000. And through the sensitivity histogram analysis, as the sensitivity of the skull is set higher, the amount of information at both ends of the histogram is lost. Abdomen and pelvis areas showed underflow phenomena in which the amount of information in the first part of the histogram was lost as the sensitivity was set higher. In conclusion, the detector accurately implemented the sensitivity change, but the dynamic range of the image due to the sensitivity change of the AEC due to the deterioration of the detector performance can not be realized properly and it was found that the evaluation through the absorbed dose and the histogram is useful when evaluating the performance of the detector.

• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.153-158
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• 2021

X-ray image analysis is a very important field to improve the early diagnosis rate and prediction accuracy of periodontal disease. Research on the development and application of artificial intelligence-based algorithms to improve the quality of such dental X-ray images is being widely conducted worldwide. Thus, the aim of this study was to design a super-resolution algorithm for predicting periodontal disease and to evaluate its applicability in dental X-ray images. The super-resolution algorithm was constructed based on the convolution layer and ReLU, and an image obtained by up-sampling a low-resolution image by 2 times was used as an input data. Also, 1,500 dental X-ray data used for deep learning training were used. Quantitative evaluation of images used root mean square error and structural similarity, which are factors that can measure similarity through comparison of two images. In addition, the recently developed no-reference based natural image quality evaluator and blind/referenceless image spatial quality evaluator were additionally analyzed. According to the results, we confirmed that the average similarity and no-reference-based evaluation values were improved by 1.86 and 2.14 times, respectively, compared to the existing bicubic-based upsampling method when the proposed method was used. In conclusion, the super-resolution algorithm for predicting periodontal disease proved useful in dental X-ray images, and it is expected to be highly applicable in various fields in the future.

• 한국노년학
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• v.38 no.1
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• pp.169-185
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• 2018

The purpose of this study examined the feasibility and efficacy of a senior center-based diabetes self-management program applying action research approach. The cyclical action research method was applied for this study: plan, act, evaluate, and reflect in delivering three waves of the intervention program. Three waves of a 12 weeks-length small group diabetes self-management program were offered during the period of 15 months in a senior center in Seoul. Planning of $2^{nd}$ and $3^{rd}$ wave program were based on reflection of $1^{st}$ and $2^{nd}$ program evaluation respectively. Among the 46 participants, 93.48% (N=43) completed the program. The quantitative evaluation showed statistically significant improvement in HbA1C(p<.001), fasting plasma glucose(p<.001), BMI(p=.016), waist circumference(p=.001), systolic blood pressure(p=.036), diabetes self-management behavior(p<.001) and health knowledge(p=.008). Qualitative data revealed that individual management was very helpful in empowering and adhering for own diabetes care for the participants. Participants reported high satisfaction towards the program with mean satisfaction score of 65.12. Application of the Diabetes Self-management program with action study strategy was successful in community setting for improving participants' subjective and objective outcomes. Action research method guides the practitioner to tailor the program to respond for the participants and field needs.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.926-932
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• 2017

Image distortion can occur when photographing deep sea targets with an optical camera. This problem arises because sunlight is not sufficiently transmitted due to seawater and various floating particles of dust. Particularly, color distortion takes place, causing green and blue color channels to be over emphasized due to water depth, while distortion of boundaries also occurs due to light refraction by seawater and floating particles of dust. These distortions degrade the overall quality of underwater images. In this paper, we analyze underwater images of the bottom of vessels. Based on the results, we propose a technique for color correction and edge enhancement. Experimental results show that the proposed method increases edge clarity by 3.39 % compared to the effective edges of the original underwater image. In addition, a quantitative evaluation and subjective image quality evaluation were concurrently performed. As a result, it was confirmed that object boundaries became clear with color correction. The color correction and contour enhancement method proposed in this paper can be applied in various fields requiring underwater imaging in the future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.5
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• pp.621-640
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• 2019

Quantitative stability assessment of underground cavities can be presented as a factor of safety based on the Shear Strength Reduction Method (SSRM). Also, SSRM is one of the stability evaluation methods commonly used in slope stability analysis. However, there is a lack of research that considers the relationship between the probability of occurrence of cavities in the ground and the potential failure surface of the slope at the same time. In this study, the effect of small underground cavities on the failure behavior of the slope was analyzed by using SSRM. Considering some of the glaciology studies, there is a case that suggests that there is a cavity effect inside the glacier in the condition that the glacier slides. In this study, the stability evaluation of underground cavities and slope stability analysis, where SSRM is used in geotechnical engineering field, was carried out considering simultaneous conditions. The slope stability analysis according to the shape and position change of underground cavities which are likely to occur in the lower part of a mountain road was analyzed by using SSRM in FLAC3D software and the influence of underground cavities on the slope factor of safety was confirmed. If there are underground cavities near slope potential failure surface, it will affect the calculation of a factor of safety. The results of this study are expected to be basic data on slope stability analysis with small underground cavities.

• Journal of the Korean Society of Radiology
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• v.14 no.7
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• pp.975-980
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• 2020

Cervical neural foraminal stenosis is a very common spinal disease that affects a relatively large number of people of all ages. However, since imaging methods that quantitatively provide neural foraminal stenosis are lacking, this study attempts to present quantitative measurement results by reconstructing 3D computed tomography images. Using a 3D reconstruction software, the surrounding bones were removed, including the spinous process, transverse process, and lamina of the cervical spine so that the neural foramen were well observed. Using Image J, a region of interest including the neural foramen area of the 3D image was set, and the number of pixels of the neural foramen area was measured. The neural foramen area was calculated by multiplying the number of measured pixels by the pixel size. In order to measure the widest area of the neural foramen, it was measured between 40-50 degrees in the opposite direction and 15-20 degrees toward the head. The measured cervical neural foramen area showed consistent measurement values. The largest measured area of the right neural foramen C5-6 was 12.21 ㎟, and after 2 years, the area was measured to be 9.95 ㎟, indicating that 18% stenosis had progressed. Since 3D reconstruction using axial CT scan images, no additional radiation exposure is required, and the area of stenosis can be objectively presented. In addition, it is good to explain to patients with neural stenosis while viewing 3D images, and it is considered a good method to be used in the evaluation of the progression of stenosis and post-operative evaluation.

• Journal of Korea Water Resources Association
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• v.50 no.7
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• pp.489-502
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• 2017

The objective of this study is to propose and evaluate the BAYES-ESP, which is a dam inflow prediction method based on Ensemble Streamflow Prediction method (ESP) and Bayesian theory. ABCD rainfall-runoff model was used to predict monthly dam inflow. Monthly meteorological data collected from KMA, MOLIT and K-water and dam inflow data collected from K-water were used for the model calibration and verification. To estimate the performance of ABCD model, ESP and BAYES-ESP method, time series analysis and skill score (SS) during 1986~2015 were used. In time series analysis monthly ESP dam inflow prediction values were nearly similar for every years, particularly less accurate in wet and dry years. The proposed BAYES-ESP improved the performance of ESP, especially in wet year. The SS was used for quantitative analysis of monthly mean of observed dam inflows, predicted values from ESP and BAYES-ESP. The results indicated that the SS values of ESP were relatively high in January, February and March but negative values in the other months. It also showed that the BAYES-ESP improved ESP when the values from ESP and observation have a relatively apparent linear relationship. We concluded that the existing ESP method has a limitation to predict dam inflow in Korea due to the seasonality of precipitation pattern and the proposed BAYES-ESP is meaningful for improving dam inflow prediction accuracy of ESP.

• Journal of the Korean Wood Science and Technology
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• v.44 no.3
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• pp.337-349
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• 2016

In this study, an analytical method to evaluate the quality of isoflavonoid compounds purified and isolated from the fruits of Cudrania tricuspidata was developed and validated using Ultra Performance Liquid Chromatography (UPLC). The fruits of C. tricuspidata were extracted with methanol and further fractioned with n-hexane, ethyl acetate and water. The resulting ethyl acetate extract separated into four isoflavonoid compounds by a combination of silica gel and sephadex LH-20 column chromatography. The structures of the compounds were elucidated as alpinumisoflavone, 6,8-diprenyl genistein, 6,8-diprenyl orobol, 4'-O-methylalpinumisoflavone by various techniques such as UV-Vis, ESI-MS, $^1H\;NMR$ and $^{13}C\;NMR$ spectroscopy. Finally, a method to characterize the compounds was developed by using the UPLC equipped with a $C_{18}$ column and a gradient mobile phase system consisting of 2% acetic acid in water (solvent A) and 2% acetic acid in methanol (solvent B). The developed method was validated with the parameters such as selectivity, linearity, limit of detection, limit of quantitation, accuracy, and precision, which are defined by the ICH (International Conference on Harmonization). Using the validated method, the compounds in the fruits harvested in different months were also quantitatively analyzed. We propose this approach this approach can readily be utilized as an efficient evaluation method to quantify the extracts of C. tricuspidata.

• Analytical Science and Technology
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• v.29 no.5
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• pp.234-241
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• 2016

The approach presented in this article refers to the bioanalytical method validation for the detection and quantitative determination of arsenic species including arsenite (As(III)), arsenate (As(V)), dimethylarsinic acid (DMA) and monomethylarsonic acid (MMA) in dog plasma by high-performance liquid chromatography inductively coupled plasma mass spectrometry (HPLC-ICP/MS). The arsenic species were separated using an agilent As speciation column by a mobile phase of 2 mM sodium phosphate monobasic, 0.2 mM ethylenediaminetetraacetic acid disodium salt dehydrate, 10 mM sodium acetate, 3 mM sodium nitrate and 1 % ethyl alcohol at pH 11 (adjusted with 1M NaOH). The method validation experiment was obtained selectivity, linearity, accuracy, precision, matrix effect, recovery, system suitability, dilution integrity and various stabilities. All calibration curves showed good linearity (R²>0.999) within test ranges. The lower limit of quantitation (LLOQ) was 5 ng/mL for As(III), As(V) and DMA, and 20 ng/mL for MMA. The system suitability and dilution values were within 6.5 % and 7.7 %. Subsequently, the developed and validated HPLC-ICP/MS method was also successfully applied to determine the arsenic speciation in dog plasma samples, and the recoveries for the spiked samples were in the range of 91.5–102.2 %. Therefore, this method could be applied to the evaluation of arsenic exposure, health effect assessment and other bio-monitoring studies in biological samples.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.103-110
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• 2011

A widely used 3D face reconstruction method, structure from motion(SfM), shows robust performance when frontal, left, and right face images are used. However, this method cannot reconstruct a self-occluded facial part correctly when only one side view face images are used because only partial facial feature points can be used in this case. In order to solve the problem, the proposed method exploit a constrain that is bilateral symmetry of human faces in order to generate bilateral facial feature points and use both input facial feature points and generated facial feature points to reconstruct a 3D face. For quantitative evaluation of the proposed method, 3D faces were obtained from a 3D face scanner and compared with the reconstructed 3D faces. The experimental results show that the proposed 3D face reconstruction method based on both facial feature points outperforms the previous 3D face reconstruction method based on only partial facial feature points.