• Korean Journal of Mineralogy and Petrology
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• v.36 no.1
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• pp.73-94
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• 2023

We carried out the sensitive high resolution ion microprobe (SHRIMP) zircon U-Pb age dating and whole-rock geochemical analysis of granitoids and felsic porphyries in the Ssangyong Valley, Yongchu Valley, and Mungyeong Saejae geosites in the Mungyeong Geopark. The igneous rocks crop out in the western, northwestern and central parts of the Mungyeong city area, respectively, and intruded (meta)sedimentary successions of the Ogcheon Metamorphic Belt, Cambro-Ordovician Mungyeong Group and Jurrasic Daedong Group. The U-Pb isotopic compositions of zircon from two felsic porphyries and one granite samples in the Ssanyeong Valley yielded the Cretaceous intrusion ages of 93.9±3.3 Ma (tσ), 95.1±4.0 Ma (tσ) and 94.4±2.0 Ma (tσ), respectively. On the other hand, a felsic dike sample and a granite in the Yongchu Valley and a porphyritic granite in the Mungyeong Saejae had intrusion ages of 90.2±2.0 Ma (tσ), 91.0±3.0 Ma (tσ) and 88.6±1.5 Ma (tσ), respectively. Based on the average standard error calculated in combination with results of previous studies in this area (Lee et al., 2010; Yi et al., 2014; Aum et al., 2019), the geochronological results show that spatial variation in intrusion age of ~5 Myr between the Ssangyong (94.5±0.2 Ma) and Yongchu Valleys (89.7±0.4 Ma) is apparent. The geochemical compositions of major and trace elements in the samples showed an affinity of typical post-orogenic granite, indicating their petrogenesis during the late stage of Early Cretaceous magmatic activity possibly in association with subduction events of the Izanagi Plate.

• Journal of Korea Water Resources Association
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• v.56 no.3
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• pp.195-210
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• 2023

Additional deposition and erosion in large rivers in South Korea have continued to occur toward morphological stabilization after massive dredging through the four major river restoration project, subsequently requiring precise bathymetry monitoring. Hyperspectral bathymetry method has increasingly been highlighted as an alternative way to estimate bathymetry with high spatial resolution in shallow depth for replacing classical intrusive direct measurement techniques. This study introduced the conventional Optimal Band Ratio Analysis (OBRA) of hyperspectral bathymetry method, and evaluated the performance in a domestic large river in normal turbid and flow condition. Maximum measurable depth was estimated by applying correlation coefficient and root mean square error (RMSE) produced during OBRA with cascadedly applying cut-off depth, where the consequent hyperspectral bathymetry map excluded the region over the derived maximum measurable depth. Also non-linearity was considered in building relation between optimal band and depth. We applied the method to the Nakdong and Hwang River confluence as a large river case and obtained the following features. First, the hyperspectal method showed acceptable performance in morphological mapping for shallow regions, where the maximum measurable depth was 2.5 m and 1.25 m in the Nakdong and Hwang river, respectively. Second, RMSE was more feasible to derive the maximum measurable depth rather than the conventional correlation coefficient whereby considering various scenario of excluding range of in situ depths for OBRA. Third, highly turbid region in Hwang River did not allow hyperspectral bathymetry mapping compared with the case of adjacent Nakdong River, where maximum measurable depth was down to half in Hwang River.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.171-187
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• 2023

When a person's face is recognized through a recording device such as a low-pixel surveillance camera, it is difficult to capture the face due to low image quality. In situations where it is difficult to recognize a person's face, problems such as not being able to identify a criminal suspect or a missing person may occur. Existing studies on face recognition used refined datasets, so the performance could not be measured in various environments. Therefore, to solve the problem of poor face recognition performance in low-quality images, this paper proposes a method to generate high-quality images by performing image quality improvement on low-quality facial images considering various environments, and then improve the performance of facial feature point detection. To confirm the practical applicability of the proposed architecture, an experiment was conducted by selecting a data set in which people appear relatively small in the entire image. In addition, by choosing a facial image dataset considering the mask-wearing situation, the possibility of expanding to real problems was explored. As a result of measuring the performance of the feature point detection model by improving the image quality of the face image, it was confirmed that the face detection after improvement was enhanced by an average of 3.47 times in the case of images without a mask and 9.92 times in the case of wearing a mask. It was confirmed that the RMSE for facial feature points decreased by an average of 8.49 times when wearing a mask and by an average of 2.02 times when not wearing a mask. Therefore, it was possible to verify the applicability of the proposed method by increasing the recognition rate for facial images captured in low quality through image quality improvement.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.497-508
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• 2023

Agricultural reservoirs are crucial structures for water resources monitoring especially in Korea where the resources are seasonally unevenly distributed. Optical and Synthetic Aperture Radar (SAR) satellites, being utilized as tools for monitoring the reservoirs, have unique limitations in that optical sensors are sensitive to weather conditions and SAR sensors are sensitive to noises and multiple scattering over dense vegetations. In this study, we tried to improve water body detection accuracy through optical-SAR data fusion, and quantitatively analyze the complementary effects. We first detected water bodies at Edong, Cheontae reservoir using the Compact Advanced Satellite 500(CAS500), Kompsat-3/3A, and Sentinel-2 derived Normalized Difference Water Index (NDWI), and SAR backscattering coefficient from Sentinel-1 by K-means clustering technique. After that, the improvements in accuracies were analyzed by applying K-means clustering to the 2-D grid space consists of NDWI and SAR. Kompsat-3/3A was found to have the best accuracy (0.98 at both reservoirs), followed by Sentinel-2(0.83 at Edong, 0.97 at Cheontae), Sentinel-1(both 0.93), and CAS500(0.69, 0.78). By applying K-means clustering to the 2-D space at Cheontae reservoir, accuracy of CAS500 was improved around 22%(resulting accuracy: 0.95) with improve in precision (85%) and degradation in recall (14%). Precision of Kompsat-3A (Sentinel-2) was improved 3%(5%), and recall was degraded 4%(7%). More precise water resources monitoring is expected to be possible with developments of high-resolution SAR satellites including CAS500-5, developments of image fusion and water body detection techniques.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.267-275
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• 2023

This study predicted rice harvest date in South Korea using 11-year (2012-2022) hindcasts based on dynamically downscaled 2m air temperature at subseasonal (1-month lead) timescale. To obtain high (5 km) resolution meteorological information over South Korea, global prediction obtained from the NOAA Climate Forecast System (CFSv2) is dynamically downscaled using the Weather Research and Forecasting (WRF) double-nested modeling system. To estimate rice harvest date, the growing degree days (GDD) is used, which accumulated the daily temperature from the seeding date (1 Jan.) to the reference temperature (1400℃ + 55 days) for harvest. In terms of the maximum (minimum) temperatures, the hindcasts tends to have a cold bias of about 1. 2℃ (0. 1℃) for the rice growth period (May to October) compared to the observation. The harvest date derived from hindcasts (DOY 289) well simulates one from observation (DOY 280), despite a margin of 9 days. The study shows the possibility of obtaining the detailed predictive information for rice harvest date over South Korea based on the dynamical downscaling method.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.661-674
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• 2023

From the seafloor of Taean, Chungcheongnamdo Province, a ship of the Joseon Dynasty was discovered for the first time in the history of underwater excavations in Korea in 2014 and was named Mado Shipwreck No. 4. A total of 27 unused whetstones loaded as tribute were discovered on the hull of Mado No. 4, which revealed that Mado Shipwreck No. 4 was a Grain transport ship that sank while carrying tribute from Naju to Hanyang between 1417 and 1425 (King Taejong to King Sejong). All of the 27 whetstones are in the shape of narrow and long sticks. The average values of length, width, thickness, and weight are 161.5 mm, 36.1 mm, 22.7 mm, and 253.2 g, respectively. The result of X-ray diffraction analysis shows that the constituent minerals are quartz, alkali feldspar, and plagioclase, which is similar to that of the high-resolution digital stereomicroscope analysis. The average porosity of Mado-2672 and 2673 is 2.69% and 1.78%, respectively, and the average surface hardness is 807.2HLD and 834.5HLD, respectively. It is interpreted that if the porosity increases beyond a certain level, it affects the decrease in surface hardness. All of these are made of feldspathic sandstones with an average SiO₂ content of 74.51% and were confirmed to be suitable as grindstones. They are all medium whetstones when classified based on the SiO₂ content. These whetstones are small in size and weight and are convenient to carry, so they are presumed to be a type of non-stationary whetstone, and are estimated to have been mainly used in the fields such as weapon polishing and craft production during the Joseon Dynasty.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.4
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• pp.303-312
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• 2023

The determination of the oxidation states of metal elements in manganese nodules sheds light on the understanding of the formation mechanism of nodules, providing insights into the paleo-environmental conditions such as the redox potential of the aqueous system. This study aims to reveal the oxidation states and chemical bonding of manganese in the natural polymetallic nodules, utilizing conventional X-ray photoelectron spectroscopy (XPS). Specifically, shallow manganese nodules from the Siberian Arctic Sea, effectively recording mineralogical variations, were used in this study. Detailed analysis of XPS Mn 2p spectra showed changes in the manganese oxidation state from the center to the outer parts of the nodules. The central part of the nodules showed a higher Mn⁴⁺ content, approximately 67.9%, while the outermost part showed about 63% of Mn⁴⁺ due to an increase in the Mn³⁺+Mn²⁺. The decrease in the Mn oxidation state with the growth is consistent with the previously reported mineralogical variations from todorokite to birnessite with growth. Additionally, the O 1s spectra presented a predominance of Mn-O-H bonds in the outer layers compared to the center, suggesting hydration by water in the layered manganates of outer layers. The results of this study demonstrate that XPS can be directly applied to understand changes in paleo-environmental conditions such as the redox states during the growth of manganese nodules. Finally, future studies using high-resolution synchrotron-based XPS experiments could achieve details in oxidation states of manganese and trace metal elements.

• Pediatric Infection and Vaccine
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• v.31 no.1
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• pp.37-45
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• 2024

Purpose: This study aimed to examine the clinical features and determinants of macrolide-unresponsive Mycoplasma pneumoniae pneumonia (MUMP) and to assess the differences in the time to fever resolution between doxycycline (DXC), tosufloxacin (TFX) and corticosteroid (CST) as second-line treatment. Methods: We retrospectively analyzed the medical records of patients under the age of 18 who were admitted to Nowon Eulji University Hospital between July 2018 and February 2020, diagnosed with mycoplasma pneumonia. Macrolide resistance was confirmed by detecting point mutations in the 23S rRNA gene. MUMP was clinically defined by persistent fever (≥38.0℃) lasting for 72 hours or more after the initiation of macrolide treatment. In cases of MUMP, patients were treated with an addition of CST, or the initial macrolide was replaced either DXC or TFX. Results: Out of 157 cases of mycoplasma pneumonia, 83 cases (52.9%) did not respond to macrolides. Patients with MUMP exhibited significantly higher C-reactive protein (CRP) levels (3.2±3.0 vs. 2.4±2.2 mg/dL, P=0.047), more frequent lobar/segmental infiltrations or pleural effusions (56.6% vs. 27.0%, P<0.001; 6.0% vs. 0.0%, P=0.032), and a higher prevalence of 23S rRNA gene mutations (96.4% vs. 64.6%, P<0.001) when compared to those with macrolide-susceptible M. pneumoniae pneumonia. In terms of second-line treatment, 15 patients (18.1%) responded to CST, 30 (36.1%) to DXC, and 38 (45.8%) to TFX. The time to defervescence (TTD) after initiation second-line treatment was significantly shorter in the CST group compared to the DXC (10.3±12.7 vs. 19.4±17.2 hours, P=0.003) and TFX groups (10.3±12.7 vs. 25.0±20.1 hours, P=0.043), with no significant difference observed between the DXC and TFX groups (19.4±17.2 vs. 25.0±20.1 hours, P=0.262). Conclusions: High CRP levels, the presence of positive 23S rRNA gene mutation, lobar or segmental lung infiltration, and pleural effusion observed in chest X-ray findings were significant factors associated with macrolide unresponsiveness. In this study, CST demonstrated a shorter TTD compared to DXC or TFX. Further, larger-scale prospective studies are needed to determine the optimal second-line treatment for MUMP.

• Korean Journal of Radiology
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• v.25 no.1
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• pp.11-23
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• 2024

Objective: To investigate whether reader training improves the performance and agreement of radiologists in interpreting unenhanced breast magnetic resonance imaging (MRI) scans using diffusion-weighted imaging (DWI). Materials and Methods: A study of 96 breasts (35 cancers, 24 benign, and 37 negative) in 48 asymptomatic women was performed between June 2019 and October 2020. High-resolution DWI with b-values of 0, 800, and 1200 sec/mm² was performed using a 3.0-T system. Sixteen breast radiologists independently reviewed the DWI, apparent diffusion coefficient maps, and T1-weighted MRI scans and recorded the Breast Imaging Reporting and Data System (BI-RADS) category for each breast. After a 2-h training session and a 5-month washout period, they re-evaluated the BI-RADS categories. A BI-RADS category of 4 (lesions with at least two suspicious criteria) or 5 (more than two suspicious criteria) was considered positive. The per-breast diagnostic performance of each reader was compared between the first and second reviews. Inter-reader agreement was evaluated using a multi-rater κ analysis and intraclass correlation coefficient (ICC). Results: Before training, the mean sensitivity, specificity, and accuracy of the 16 readers were 70.7% (95% confidence interval [CI]: 59.4-79.9), 90.8% (95% CI: 85.6-94.2), and 83.5% (95% CI: 78.6-87.4), respectively. After training, significant improvements in specificity (95.2%; 95% CI: 90.8-97.5; P = 0.001) and accuracy (85.9%; 95% CI: 80.9-89.8; P = 0.01) were observed, but no difference in sensitivity (69.8%; 95% CI: 58.1-79.4; P = 0.58) was observed. Regarding inter-reader agreement, the κ values were 0.57 (95% CI: 0.52-0.63) before training and 0.68 (95% CI: 0.62-0.74) after training, with a difference of 0.11 (95% CI: 0.02-0.18; P = 0.01). The ICC was 0.73 (95% CI: 0.69-0.74) before training and 0.79 (95% CI: 0.76-0.80) after training (P = 0.002). Conclusion: Brief reader training improved the performance and agreement of interpretations by breast radiologists using unenhanced MRI with DWI.