• 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.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.526-535
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• 2021

Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.171-187
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• 2022

Recently, the demand and development for non-face-to-face services are rapidly progressing due to the pandemic caused by the COVID-19, and attention is focused on the metaverse at the center. Entering the era of the 4th industrial revolution, Metaverse, which means a world beyond virtual and reality, combines various sensing technologies and 3D reconstruction technologies to provide various information and services to users easily and quickly. In particular, due to the miniaturization and economic increase of convergence sensors such as unmanned aerial vehicle(UAV) capable of high-resolution imaging and high-precision LiDAR(Light Detection and Ranging) sensors, research on digital-Twin is actively underway to create and simulate real-life twins. In addition, Game engines in the field of computer graphics are developing into metaverse engines by expanding strong 3D graphics reconstuction and simulation based on dynamic operations. This study constructed a mirror-world type metaverse that reflects real-world coordinate-based reality using Unreal Engine 5, a recently announced metaverse engine, with accurate 3D spatial information data of convergence sensors based on unmanned aerial system(UAS) and LiDAR. and then, spatial information contents and simulations for users were produced based on various public data to verify the accuracy of reconstruction, and through this, it was possible to confirm the construction of a more realistic and highly utilizable metaverse. In addition, when constructing a metaverse that users can intuitively and easily access through the unreal engine, various contents utilization and effectiveness could be confirmed through coordinate-based 3D spatial information with high reproducibility.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.885-894
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• 2006

The purpose of this study is focused on the development of the effective classification technique using ultra multiband of hyperspectral image. This study suggests the classification technique using canonical correlation analysis, one of multivariate statistical analysis in hyperspectral image classification. High accuracy of classification result is expected for this classification technique as the number of bands increase. This technique is compared with Maximum Likelihood Classification(MLC). The hyperspectral image is the EO1-hyperion image acquired on September 2, 2001, and the number of bands for the experiment were chosen at 30, considering the band scope except the thermal band of Landsat TM. We chose the comparing base map as Ground Truth Data. We evaluate the accuracy by comparing this base map with the classification result image and performing overlay analysis visually. The result showed us that in MLC's case, it can't classify except water, and in case of water, it only classifies big lakes. But Canonical Correlation Classification (CCC) classifies the golf lawn exactly, and it classifies the highway line in the urban area well. In case of water, the ponds that are in golf ground area, the ponds in university, and pools are also classified well. As a result, although the training areas are selected without any trial and error, it was possible to get the exact classification result. Also, the ability to distinguish golf lawn from other vegetations in classification classes, and the ability to classify water was better than MLC technique. Conclusively, this CCC technique for hyperspectral image will be very useful for estimating harvest and detecting surface water. In advance, it will do an important role in the construction of GIS database using the spectral high resolution image, hyperspectral data.

• 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.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.295-305
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• 2024

This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

• Tuberculosis and Respiratory Diseases
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• v.44 no.1
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• pp.124-135
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• 1997

Background : Diffuse panbronchiolitis(DPB) is a disease characterized clinically by chronic cough, expectoration and dyspnea; and histologically by chronic inflammation localized mainly in the region of the respiratory bronchiole. It is prevalent in Japanese, but is known to be rare in Americans and Europians. Only a few cases in Chinese, Italians, North Americans and Koreans have been reported. It is diagnosed by characteristic clinical, radiological and pathologic features. High-resolution CT(HRCT) is known to be valuable in the study of the disease process and response to therapy in DPB. To our knowledge, there has been no correlation of its appearance on HRCT with the severity of the disease process, and radioaerosol scan(RAS) of the lung has not previously been used for the diagnosis of DPB. Method : During recent two years we have found 12 cases of DPB in Kangnam St. Mary's Hospital, Catholic University Medical College. We analysed the clinical characteristics, compared HRCT classifications with clinical stages of DPB, and determined characteristic RAS manifestations of DPB. Results : 1. The ages ranged from 31 to 83 years old(mean 54.5 years old), and male female ratio was 4:8. 75%(9/12) of patients had paranasal sinusitis, and only one patient was a smoker. 2. The patients were assigned to one of three clinical stages of DPB on the basis of clinical findings, sputum bacterology and arterial blood gas analysis. of 12 cases, 5 were in the first stage, 4 were in the second stage, and 3 were in the third stage. In most of the patients, pulmonary function tests showed marked obstructive and slight restrictive impairments. Sputum culture yielded P.aeruginosa in 3 cases of our 12 cases, K.pneumoniae in 2 cases, H.influenzae in 2 cases, and S.aureus in 2 cases. 3. Of 12 patients, none had stage I characteristics as classified on HRCT scans, 4 had slage II findings, 5 had stage III findings, and 3 had stage IV characteristics. 4. We peformed RAS in 7 of 12 patients With DPB. In 71.4% (5/7) of the patients, RAS showed mottled aerosol deposits characteristically in the transitional and intermediary airways with peripheral airspace defects, which contrasted sharply with central aerosol deposition of COPD. 5. There were significant correlations between HRCT stages and clinical stages(r= 0.614, P < 0.05), between HRCT types and Pa02(r= -0.614, P < 0.05), and between HRCT types and ESR(r= 0.618, P < 0.01). Conclusion : The HRCT classifications correspond well to the clinical stage. Therfore in the examination of patients with DPB, HRCT is useful in the evaluation of both the location and severity of the lesions. Also, RAS apears to be a convenient, noninvasive and useful diagnostic method of DPB.

• The korean journal of orthodontics
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• v.31 no.2 s.85
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• pp.225-236
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• 2001

It is widely accepted that the shape and structure of bone are closely related to the activity of attached muscle. Numerous clinical and animal experimental studies indicated the significant effects of masticatory muscle function on maxillofacial morphology. Recently, the development of ultrasonography has spread throughout different fields of medicine. In the clinical examinations, ultrasonography is a convenient, inexpensive technique to apply with accurate and reliable results. The aim of this study is to assess the thickness of the masseter muscle and its correlation to maxillofacial skeleton by examining 35 male and 15 female dental students at Kangnung National University. The masseter muscle thickness of the subjects were measured by ultrasonographic scanning with a 7.5MHz linear probe, and their maxillofacial morphology were investigated by lateral cephalometric radiographs. The relationship between the masseter muscle thickness and maxillofacial morphology of normal adult was statistically analyzed, and the following results were obtained. 1. The average thickness of male masseter muscle was 13.8${\pm}$1.71mm in the relaxed state and 14.8${\pm}$1.77mm at maximal clenching state, while that of female was 11.6${\pm}$1.58mm and 12.4${\pm}$1.47mm, respectively. Ethnic difference in thickness of the masseter muscle and maxillofacial skeleton was found when the results of many researchers were compared with those of this study. 2. The thickness of the masseter muscle in both sexes increased significantly at maximal clenching state than in relaxed state(P<0.05). 3. The masseter muscle thickness of male was greater than that of female both in the relaxed state and maximal clenching states(P<0.05). 4. In males, the thickness of the masseter muscle was negatively correlated with the mandibular plane angle and positively correlated with the mandibular ramus height and anterior cranial base length(P<0.05). It may suggest that the male with thicker masseter muscle has smaller facial divergence. 5. No significant correlation was found between the masseter muscle thickness and maxillofacial morphology in females(P<0.05). Therefore, these data suggest that ultrasonography can add valuable information to the conventional examinations of masseter muscle function.