• Geomechanics and Engineering
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• v.24 no.4
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• pp.337-348
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• 2021

Brillouin Optical Frequency Domain Analysis (BOFDA) is a distributed fiber optic sensing (DFOS) technique that has unique advantages for performance monitoring of piles. However, the complicated production process and harsh operating environment of offshore PHC pipe piles make it difficult to apply this method to pile load testing. In this study, sensing cables were successfully pre-installed into an offshore PHC pipe pile directly for the first time and the BOFDA technique was used for in-situ monitoring of the pile under axial load. High-resolution strain and internal force distributions along the pile were obtained by the BOFDA sensing system. A finite element analysis incorporating the Degradation and Hardening Hyperbolic Model (DHHM) was carried out to evaluate and predict the performance of the pile, which provides an improved insight into the offshore pile-soil interaction mechanism.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1058-1060
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• 2003

A ground control point (GCP) is a point on the surface of Earth where image coord inates and map coordinates can be identified. The GCP is useful for the geometric correction of systematic and unsystematic errors usually contained in a remotely sensed data. Especially in case of synthetic aperture radar (SAR) data, it has serious geometric distortions caused by inherent side looking geometry. In addition, SAR images are usually severely corrupted by speckle noises so that it is difficult to identify ground control points. We developed a ground point extraction algorithm that has an improved capability. An application of radargrammetry to Daejon area in Korea was studied to acquire the geometric information. For the ground control point extraction algorithm, an ERS SAR data with precise Delft orbit information and rough digital elevation model (DEM) were used. We analyze the accuracy of the results from our algorithm by using digital map and GPS survey data.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.949-965
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• 2023

In this study, we propose a method to monitor the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar images and the deep learning model, Swin Transformer. Utilizing the Google Earth Engine platform, datasets from 2017 to 2021 were constructed for seven agricultural reservoirs, categorized into 700 K-ton, 900 K-ton, and 1.5 M-ton capacities. For four of the reservoirs, a total of 1,283 images were used for model training through shuffling and 5-fold cross-validation techniques. Upon evaluation, the Swin Transformer Large model, configured with a window size of 12, demonstrated superior semantic segmentation performance, showing an average accuracy of 99.54% and a mean intersection over union (mIoU) of 95.15% for all folds. When the best-performing model was applied to the datasets of the remaining three reservoirsfor validation, it achieved an accuracy of over 99% and mIoU of over 94% for all reservoirs. These results indicate that the Swin Transformer model can effectively monitor the surface area of agricultural reservoirs in South Korea.

• Economic and Environmental Geology
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• v.55 no.3
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• pp.309-316
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• 2022

In order to minimize the human and time consumption required for rock classification, research on rock classification using artificial intelligence (AI) has recently developed. In this study, basic volcanic rocks were subdivided by using polarizing microscope thin section images. A convolutional neural network (CNN) model based on Tensorflow and Keras libraries was self-producted for rock classification. A total of 720 images of olivine basalt, basaltic andesite, olivine tholeiite, trachytic olivine basalt reference specimens were mounted with open nicol, cross nicol, and adding gypsum plates, and trained at the training : test = 7 : 3 ratio. As a result of machine learning, the classification accuracy was over 80-90%. When we confirmed the classification accuracy of each AI model, it is expected that the rock classification method of this model will not be much different from the rock classification process of a geologist. Furthermore, if not only this model but also models that subdivide more diverse rock types are produced and integrated, the AI model that satisfies both the speed of data classification and the accessibility of non-experts can be developed, thereby providing a new framework for basic petrology research.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.65.2-65.2
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• 2015

We developed a three-dimensional magnetohydrodynamic (MHD) code to reproduce the structure of a solar wind, the properties of a coronal mass ejection (CME) and the interaction between them. This MHD code is based on the finite volume method incorporating total variation diminishing (TVD) scheme with an unstructured grid system. In particular, this grid system can avoid the singularity at the north and south poles and relax tight CFL conditions around the poles, both of which would arise in a spherical coordinate system (Tanaka 1994). In this model, we first apply an MHD tomographic method (Hayashi et al. 2003) to interplanetary scintillation (IPS) observational data and derive a solar wind from the physical values obtained at 50 solar radii away from the Sun. By comparing the properties of this solar wind to observational data obtained near the Earth orbit, we confirmed that our model captures the velocity, temperature and density profiles of a solar wind near the Earth orbit. We then insert a spheromak-type CME (Kataoka et al. 2009) into the solar wind to reproduce an actual CME event. This has been done by introducing a time-dependent boundary condition to the inner boundary of our simulation domain. On the basis of a comparison between a simulated CME and observations near the Earth, we discuss the physics involved in an ICME interacting with a solar wind.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.6
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• pp.640-652
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• 2007

The MM5, RAMS and WRF, meteorological models have provided the dynamical parameters as inputs to air quality model. A major content of this study is that significant characteristics of three models for high-ozone occurrence analyze for surface wind and air temperature fields and compare with observation data in Seoul metropolitan area. An analysis of air temperature field revealed that location of core in high temperature of MM5 and WRF differed from that of RAMS. MM5 and WRF indicated high temperature in Seoul but RAMS represented it on the outskirts of Seoul. MM5 and WRF were underestimated maximum temperature during daytime but RAMS simulated similar value with observation data. Surface wind field with three models, it was shown many differences at horizontal distribution of wind direction. RAMS indicated weak wind speed in land and strong sea breeze at coastal areas than MM5 and WRF. However wind speed simulated by three model were overestimated during both daytime and nighttime.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.193-199
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• 2013

This work investigates the orbital perturbations of the cubesats that lie on LEO due to Earth albedo. The motivation for this paper originated in the investigation of the orbital perturbations for closed- Earth pico-satellites due to the sunlight reflected by the Earth (the albedo). Having assumed that the Sun lies on the equator, the albedo irradiance is calculated using a numerical model in which irradiance depends on the geographical latitude, longitude and altitude of the satellite. However, in the present work the longitude dependency is disregarded. Albedo force and acceleration components are formulated using a detailed model in a geocentric equatorial system in which the Earth is an oblate spheroid. Lagrange planetary equations in its Gaussian form are used to analyze the orbital changes when $e{\neq}0$ and $i{\neq}0$. Based on the Earth's reflectivity data measured by NASA Total Ozone Mapping Spectrometer (TOMS project), the orbital perturbations are calculated for some cubesats. The outcome of the numerical test shows that the albedo force has a significant contribution on the orbital perturbations of the pico-satellite which can affect the satellite life time.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2002.11a
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• pp.313-318
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• 2002

Purpose of the grounding system design are establish a safe environment for personnel as well as the general public in the vicinity of the power system equipment, and establish a low resistance connection to earth such that protective devices detect and isolate faults quickly and potential rise of the grounding system does not exceed a value which could damage electrical equipment. This paper deals with the grounding system design for the electric facilities. In this paper, emphasize the necessity of the computer programs for the grounding system designs. Especially, earth soil models for the grounding system design are must used two-layered soil model.

• Journal of Korean Society on Water Environment
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• v.36 no.4
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• pp.300-313
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• 2020

The Bayesian approach can be used to estimate hydrologic model parameters from the prior expert knowledge about the parameter values and the observed data. The purpose of this study was to compare the performance of the two Bayesian methods, the Metropolis-Hastings (MH) algorithm and the Generalized Likelihood Uncertainty Estimation (GLUE) method. These two methods were applied to the TANK model, a hydrological model comprising 13 parameters, to examine the uncertainty of the parameters of the model. The TANK model comprises a combination of multiple reservoir-type virtual vessels with orifice-type outlets and implements a common major hydrological process using the runoff calculations that convert the rainfall to the flow. As a result of the application to the Nam River A watershed, the two Bayesian methods yielded similar flow simulation results even though the parameter estimates obtained by the two methods were of somewhat different values. Both methods ensure the model's prediction accuracy even when the observed flow data available for parameter estimation is limited. However, the prediction accuracy of the model using the MH algorithm yielded slightly better results than that of the GLUE method. The flow duration curve calculated using the limited observed flow data showed that the marginal reliability is secured from the perspective of practical application.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.441-444
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• 2005

The goal of this study is to investigate the relationship between microphytobenthic biomass and normalized vegetation index obtained from Landsat TM images. Monitoring a seasonal change of microphytobenthic biomass in the sand bar is specifically focused. Since the study area, Hampyeong Bay, was difficult to approach, we failed to obtain ground truths simultaneously on satellite image acquisition. Instead, chlorophyll-a concentration in surface top layer was measured on different dates for microphytobenthic biomass. Although data were acquired on different dates, a correlation between the field and satellite images was calculated for investigating general trends of seasonal change. NDVI and tasseled cap transformed images were also used to review the variation of microphytobenthic biomass by using Landsat TM and ETM+ images. Atmosphere effects were corrected by applying COST model. Seaweeds were also flouring in the same season of microphytobentic blooming. Songseok-ri area was minimally affected by seaweeds from February to May, and selected as a test site. NDVI value was classified into high-, moderate-, and low-grade. It was well developed over fme-grained sediments and rapidly reduced from May to November over sand bar. In this bay, correlation between grain size and microphytobenthic biomass was clearly seen. From the classified NDVI and tasseled cap transformed data, we finally constructed spatial distribution and seasonal variation maps of microphytobenthic biomass.