• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.6
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• pp.369-378
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• 2016

The design spectrum for Korea, which is known to belong to an intra-plate region, is developed from the ground motion records of the earthquakes occurred in Korea and overseas intra-plate regions. The horizontal spectrum is defined as geometric mean spectrum, GMRotI50. From the statistical analysis of the geometric mean spectra, a mean plus one standard deviation spectrum in lognormal distribution is obtained. Regression analysis is performed on this curve to determine the shape of spectrum including transition periods. The developed design spectrum is valid for the estimation both spectral acceleration and displacement.

• Journal of The Korean Astronomical Society
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• v.23 no.2
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• pp.106-111
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• 1990

Photoelectric observation in 1984 shows light variation outside eclipses. The effect of the changing ambient temperature on the light curves were studied. Difficulty of studying and unitary, or mean, light curve of AR Lac is stressed.

• Journal of Gastric Cancer
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• v.18 no.2
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• pp.182-188
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• 2018

Purpose: Despite the fact that there are several reports of single-port laparoscopic distal gastrectomy (SPDG), no analysis of its learning curve has been described in the literature. The aim of this study was to investigate the favorable factors for SPDG and to analyze the learning curve of SPDG. Materials and Methods: A total of 125 cases of SPDG performed from November 2011 to December 2015 were enrolled. All operations were performed by 2 surgeons (surgeon A and surgeon B). The moving average method was used for defining the learning curve. All cases were divided into 10 cases in a sequence, and the mean operative time and estimated blood loss data were extracted from each group. Results: Surgeon A performed 68 cases (female-to-male sex ratio, 91.1%:8.82%), and surgeon B performed 57 cases (female-to-male sex ratio, 61.4%:38.5%). The operative time of surgeon B significantly decreased after 30 cases ($157.8{\pm}38.4$ minutes vs. $118.1{\pm}34.5$ minutes, P=0.003); that of surgeon A did not significantly decrease before and after around 30 cases ($160.8{\pm}51.6$ minutes vs. $173.3{\pm}35.2$ minutes, P=0.6). The subgroup analysis showed that the operative time significantly decreased in the patients with body mass index (BMI) of <$25kg/m^2$ (<$25kg/m^2$:${\geq}25kg/m^2$, $159.3{\pm}41.7$ minutes: $194.25{\pm}81.1$ minutes; P=0.001). Conclusions: Although there was no significant decrease in the operative time for surgeon A, surgeon B reached the learning curve upon conducting 30 cases of SPDG. BMI of <$25kg/m^2$ was found to be a favorable factor for SPDG.

• Journal of the Korean Society of Radiology
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• v.10 no.8
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• pp.645-652
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• 2016

In this study, based on the analysis of texture feature values of statistical properties. And we examined the normal and the applicability of the computer-aided diagnosis of cerebral infarction in the brain computed tomography images. The experiment was analyzed to evaluate the ROC curve recognition rate of disease using six parameters representing the feature values of the texture. As a result, it showed average mean 88%, variance 92%, relative smoothness 94%, uniformity of 88%, a high disease recognition rate of entropy 84%. However, it showed a slightly lower disease recognition rate and 58% for skewness. In the analysis using ROC curve, the area under the curve for each parameter indicates 0.886 (p = 0.0001) or more, resulted in a meaningful recognition of the disease. Further, to determine the cut-off values for each parameter are determined to be the prediction of disease through the computer-aided diagnosis.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.55.2-56
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• 2021

The progenitor of Type Ia supernovae (SNe Ia) is mainly believed to be a close binary system of acarbon-oxygen white dwarf (CO WD) and non-degenerate companion (single degenerate) or another WD (double degenerate). However, it is unclear which system is more prevalent. Here, we present a high cadence optical/Near-IR light curve of normal but slightly faint type Ia SN 2019ein from IMSNG project. We fit the early light curve (t <+8.3 days from the first detection) with various models to find the shock-heated cooling emission from SN ejecta-companion interaction. No significant shock-heated cooling emission is found, from which we constrain the progenitor star size as the following. The upper limit (R_upper,*) of the companion size in R-band is ~0.2R_⊙ when forcing the first light time (t_fl) to have one value and ~0.9R_⊙ when using the mean value of tfl from the fitting in each band. Assuming the source of the I-band curve is almost powered from the radioactive decay, we obtained R_upper,*~1.2R_⊙. The early B-V color curve is in agreement with the model color curve of the 2M_⊙ main sequence companion. These results allow us to at least rule out large stars like red giants as a companion star of the binary progenitor system of this supernova. B-R and V-R color do not show any significant signs of a red bump, which shows a thin helium shell (MHe<0.1M_⊙) for the sub-Mch WD (double detonation model). In addition, we estimated the distance to NGC 5353 as 37.098±0.028Mpc.

• Journal of the Korean Society of Radiology
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• v.81 no.5
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• pp.1164-1174
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• 2020

Purpose To evaluate a deep learning model to predict recurrence of thyroid tumor using preoperative ultrasonography (US). Materials and Methods We included representative images from 229 US-based patients (male:female = 42:187; mean age, 49.6 years) who had been diagnosed with thyroid cancer on preoperative US and subsequently underwent thyroid surgery. After selecting each representative transverse or longitudinal US image, we created a data set from the resulting database of 898 images after augmentation. The Python 2.7.6 and Keras 2.1.5 framework for neural networks were used for deep learning with a convolutional neural network. We compared the clinical and histological features between patients with and without recurrence. The predictive performance of the deep learning model between groups was evaluated using receiver operating characteristic (ROC) analysis, and the area under the ROC curve served as a summary of the prognostic performance of the deep learning model to predict recurrent thyroid cancer. Results Tumor recurrence was noted in 49 (21.4%) among the 229 patients. Tumor size and multifocality varied significantly between the groups with and without recurrence (p < 0.05). The overall mean area under the curve (AUC) value of the deep learning model for prediction of recurrent thyroid cancer was 0.9 ± 0.06. The mean AUC value was 0.87 ± 0.03 in macrocarcinoma and 0.79 ± 0.16 in microcarcinoma. Conclusion A deep learning model for analysis of US images of thyroid cancer showed the possibility of predicting recurrence of thyroid cancer.

• Journal of Korean Academy of Nursing
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• v.38 no.2
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• pp.321-331
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• 2008

Purpose: To examine the relationship between body fat percentage (BFP) and N-K cell activity (NKCA) in Korean breast and rectal cancer patients just after diagnosis. Methods: With 35 subjects enrolled between November 2002 and May 2003, Bioelectrical Impedance Analysis was used to estimate BFP. FACS Analysis was used to measure N-K cell activity. The relationships between BFP and NKCA were identified by using curve estimation, simple regression, and multiple regression, Results: The mean BFPs of the subjects and all the sub-groups were higher than acceptable BFPs. Both the mean NKCAs of male and female subjects were lower than that of healthy women. NKCA was explained by BFP with a 14.9% variance in the total subjects (p<.05). There were significant negative relationships between BFP and NKCA after controlling age, type of cancer, and stage of cancer while no significant relationship was found after controlling for gender. The relationships between BFP and NKCA in the sub-groups of female, breast cancer, and stage I, and II were significant. The relationships between male, rectal cancer, and the stage III, and VI sub-groups were not identified, but they revealed a mild to moderate steep in curve estimation. Conclusion: Weight reduction could prevent the risk and advancement of breast and rectal cancer in Koreans.

• Journal of Environmental Science International
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• v.24 no.12
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• pp.1617-1627
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• 2015

This study was carried out to investigate the characteristics of suspended solid concentration in small forest watershed, Hwacheon, Gangwondo. For five rainfall events from July 2013 to August 2013, rainfall, discharge, and suspended solid load has been measured. The results showed that the fist flush effect was observed for suspended solid in each rainfall event, sediment rating curve was obtained with $y=30.029x^{1.573}$ at rising limb and $y=12.902x^{1.8827}$ at falling limb, and EMC (event mean concentration) of suspended solid was calculated to 9.4 mg/L. EMC was compared to the values from the watershed that has various land use types and EMC from forest watershed was much lower that from the crop, paddy or low covered forest watershed.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.10
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• pp.4143-4145
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• 2014

Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) Ewing sarcoma (ES) outcome data. The aim of this study was to identify and optimize ES-specific survival prediction models and sources of survival disparities. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ES. 1844 patients diagnosed between 1973-2009 were used for this study. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome (bone and joint specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: The mean follow up time (S.D.) was 74.48 (89.66) months. 36% of the patients were female. The mean (S.D.) age was 18.7 (12) years. The SEER staging has the highest ROC (S.D.) area of 0.616 (0.032) among the factors tested. We simplified the 4-layered risk levels (local, regional, distant, un-staged) to a simpler non-metastatic (I and II) versus metastatic (III) versus un-staged model. The ROC area (S.D.) of the 3-tiered model was 0.612 (0.008). Several other biologic factors were also predictive of ES-specific survival, but not the socio-economic factors tested here. Conclusions: ROC analysis measured and optimized the performance of ES survival prediction models. Optimized models will provide a more efficient way to stratify patients for clinical trials.

• International Journal of Highway Engineering
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• v.6 no.3 s.21
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• pp.55-64
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• 2004

Maximum dry unit weight, ${\gamma}_{dmax}$, is the most important engineering properties for subgrade soil. Existing models to predict ${\gamma}_{dmax}$ containing many parameters, seem to be rather complex. This paper presents new simple models to predict ${\gamma}_{dmax}$. for sandy soils, A number of sieve analysis and compaction tests for 36 types of sands were conducted to develop the regression-based models. Parameters used to estimate ${\gamma}_{dmax}$ are both the geometric mean and geometric standard deviation of the soils, or the particle-size distribution curve parameters. Maximum dry unit weights predicted by the models are in good agreement with the laboratory measurements for the soil samples obtained at 16 locations within the Korea.