• Journal of Korean Neurosurgical Society
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• v.47 no.5
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• pp.345-351
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• 2010

Objective : In this study, the Mindfulness Based Stress Reduction (MBSR) program was applied to patients presenting with depression and anxiety after surgery from spontaneous subarachnoid hemorrhage (SAH) and the effects were assessed. Methods : The subjects were patients admitted for cerebral aneurysm rupture and treated by means of surgery from March to December, 2007. More than 6 months had passed after surgery, without any special lesions showing up on computed tomography (CT), and the Glasgow outcome scale (GOS) was 5 points. Among patients with anxiety and depression symptoms, 11 patients completed the program. The MBSR program was conducted once a week, 2.5 hours each, for 8 weeks. The evaluation criteria were : 1) the Beck Depression Inventory (BDI): it measures the type and level of depression, 2) the State-Trait Anxiety Inventory : the anxiety state of normal adults without mental disorder, and 3) Heart Rate Variability (HRV) : the influence of the autonomous nervous system on the sinoarterial node varies continuously in response to the change of the internal/external environment. Results : The BDI value was decreased from 18.5 ${\pm}$ 10.9 to 9.5 ${\pm}$ 7.1 (p = 0.013) : it was statistically significant, and the depression level of patients was lowered. The state anxiety was decreased from 51.3 ${\pm}$ 13.9 to 42.3 ${\pm}$ 15.2; the trait anxiety was reduced from 50.9 ${\pm}$ 12.3 to 41.3 ${\pm}$ 12.8, and a borderline significant difference was shown (p = 0.091, p = 0.056). In other words, after the treatment, although it was not statistically significant, a decreased tendency in anxiety was shown. In the HRV measurement, standard deviation normal to normal (SDNN), square root of the square root of the mean sum of squared differences between adjacent normal to normal intervals (RMSSD), and total power (TP) showed significant increase, Physical Stress Index (PSI) showed a significant reduction, and thus an improvement in the homeostatic control mechanism of the autonomic nervous system was ween. Conclusion : The MBSR program was applied to the patients showing anxiety and depression reaction after SAH treatment, and a reduction in depression symptoms and physiological reactions were observed. The application of the MBSR program may be considered as a new tool in improving the quality of life for patients after surgery.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.3
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• pp.215-233
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• 2022

The zircon U-Pb and trace element analyses were performed for banded gneiss in the Euiam gneiss complex, central Gyeonggi Massif. An age of detrital zircon shows predominant age peaks at ca. 2500-2480 Ma with numerous ages ranging from Siderian to Rhyacian period. The youngest age peak of detrital zircon constrains the maximum deposition age of protolith of banded gneiss at ca. 2070 Ma. Meanwhile, the zircon rim yielded metamorphic age of ca. 1966 ± 39 Ma ~ 1918 ± 13 Ma. Based on the error range, degree of discordancy, and value of mean squared weighted deviation, we considered that the age of 1918 ± 13 Ma is the most reasonable age indicating the timing of metamorphism for banded gneiss. The zircon rims yield Ti-in-zircon crystallization temperature of 690-740℃. Therefore, we suggested that there was a high-grade metamorphic event in the Gyeonggi Massif at ca. 1918 Ma which is older than the metamorphic event that occurred in the Gyeonggi Massif during ca. 1880-1860 Ma.

• The Journal of Advanced Prosthodontics
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• v.15 no.6
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• pp.281-289
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• 2023

PURPOSE. This study aimed to predict the positional coordinates of incisor points from the scan data of conventional complete dentures and verify their accuracy. MATERIALS AND METHODS. The standard triangulated language (STL) data of the scanned 100 pairs of complete upper and lower dentures were imported into the computer-aided design software from which the position coordinates of the points corresponding to each landmark of the jaw were obtained. The x, y, and z coordinates of the incisor point (X_P, Y_P, and Z_P) were obtained from the maxillary and mandibular landmark coordinates using regression or calculation formulas, and the accuracy was verified to determine the deviation between the measured and predicted coordinate values. Y_P was obtained in two ways using the hamularincisive-papilla plane (HIP) and facial measurements. Multiple regression analysis was used to predict Z_P. The root mean squared error (RMSE) values were used to verify the accuracy of the X_P and Y_P. The RMSE value was obtained after crossvalidation using the remaining 30 cases of denture STL data to verify the accuracy of Z_P. RESULTS. The RMSE was 2.22 for predicting X_P. When predicting Y_P, the RMSE of the method using the HIP plane and facial measurements was 3.18 and 0.73, respectively. Cross-validation revealed the RMSE to be 1.53. CONCLUSION. Y_P and Z_P could be predicted from anatomical landmarks of the maxillary and mandibular edentulous jaw, suggesting that Y_P could be predicted with better accuracy with the addition of the position of the lower border of the upper lip.

• Journal of Korean Society of Transportation
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• v.32 no.3
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• pp.266-279
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• 2014

For the evaluation of roadway safety, diverse methods, including before-after studies, simple comparison using historic traffic accident data, methods based on experts' opinion or literature, have been applied. Especially, many research efforts have developed traffic accident prediction models in order to identify critical elements causing accidents and evaluate the level of safety. A traffic accident prediction model must secure predictability and transferability. By acquiring the predictability, the model can increase the accuracy in predicting the frequency of accidents qualitatively and quantitatively. By guaranteeing the transferability, the model can be used for other locations with acceptable accuracy. To this end, traffic accident prediction models using non-linear regression, artificial neural network, and structural equation were developed in this study. The predictability and transferability of three models were compared using a model development data set collected from 90 signalized intersections and a model validation data set from other 33 signalized intersections based on mean absolute deviation and mean squared prediction error. As a result of the comparison using the model development data set, the artificial neural network showed the highest predictability. However, the non-linear regression model was found out to be most appropriate in the comparison using the model validation data set. Conclusively, the artificial neural network has a strong ability in representing the relationship between the frequency of traffic accidents and traffic and road design elements. However, the predictability of the artificial neural network significantly decreased when the artificial neural network was applied to a new data which was not used in the model developing.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.80-90
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• 2014

The objective of this research is to estimate the stand volume of Pinus koraiensis, by using the investigated volume and the information of remote sensing(RS), in the research forest of Kangwon National University. The average volume of the research forest per hectare was $307.7m^3/ha$ and standard deviation was $168.4m^3/ha$. Before and after carrying out 3 by 3 majority filtering on TM image, eleven indices were extracted each time. Independent variables needed for linear regression equation were selected using mean pixel values by indices. The number of indices were eleven: six Bands(except for thermal Band), NDVI, Band Ratio(BR1:Band4/Band3, BR2:Band5/Band4, BR3:Band7/Band4), Tasseled Cap-Greeness. As a result, NDVI and TC G were chosen as the most suitable indices for regression before and after filtering, and R-squared was high: 0.736 before filtering, 0.753 after filtering. As a result of error verification for an exact comparison, RMSE before and after filtering was about $69.1m^3/ha$, $67.5m^3/ha$, respectively, and bias was $-12.8m^3/ha$, $9.7m^3/ha$, respectively. Therefore, the regression conducted with filtering was selected as an appropriate model because of low RMSE and bias. The estimated stand volume applying the regression was $160,758m^3$, and the average volume was $314m^3/ha$. This estimation was 1.2 times higher than the actual stand volume of Pinus koraiensis.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1235-1249
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• 2019

Kilauea Volcano is one of the most active volcano in the world. In this study, we used the ALOS-2 PALSAR-2 satellite imagery to measure the surface deformation occurring near the summit of the Kilauea volcano from 2015 to 2017. In order to measure two-dimensional surface deformation, interferometric synthetic aperture radar (InSAR) and multiple aperture SAR interferometry (MAI) methods were performed using two interferometric pairs. To improve the precision of 2D measurement, we compared root-mean-squared deviation (RMSD) of the difference of measurement value as we change the effective antenna length and normalized squint value, which are factors that can affect the measurement performance of the MAI method. Through the compare, the values of the factors, which can measure deformation most precisely, were selected. After select optimal values of the factors, the RMSD values of the difference of the MAI measurement were decreased from 4.07 cm to 2.05 cm. In each interferograms, the maximum deformation in line-of-sight direction is -28.6 cm and -27.3 cm, respectively, and the maximum deformation in the along-track direction is 20.2 cm and 20.8 cm, in the opposite direction is -24.9 cm and -24.3 cm, respectively. After stacking the two interferograms, two-dimensional surface deformation mapping was performed, and a maximum surface deformation of approximately 30.4 cm was measured in the northwest direction. In addition, large deformation of more than 20 cm were measured in all directions. The measurement results show that the risk of eruption activity is increasing in Kilauea Volcano. The measurements of the surface deformation of Kilauea volcano from 2015 to 2017 are expected to be helpful for the study of the eruption activity of Kilauea volcano in the future.