• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.3
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• pp.275-283
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• 2002

To detect the position and depth of buried underground utilities, method of Ground Penetrating Radar(GPR) survey is the most commonly used. However, the skin-depth of GPR is very shallow, and in the places where subsurface materials are not homogeneous and are compose of clays and/or salts and gravels, GPR method has limitations in application and interpretation. The aim of this study is to overcome these limitations of GPR survey. For this purpose the site where the GPR survey is unsuccessful to detect the underground big pipes is selected, and soil tests were conducted to confirm the reason why GPR method was not applicable. Non-destructive high-frequency electromagnetic (HFEM) survey was newly developed and was applied in the study area to prove the effectiveness of this new technique. The frequency ranges $2kHz{\sim}4MHz$ and the skin depth is about 30m. The HFEM measures the electric field and magnetic field perpendicular to each other to get the impedance from which vertical electric resistivity distribution at the measured point can be deduced. By adopting the capacitive coupled electrodes, it can make the measuring time shorter, and can be applied to the places covered by asphalt an and/or concrete. In addition to the above mentioned advantages, noise due to high-voltage power line is much reduced by stacking the signals. As a result, the HFEM was successful in detecting the buried underground objects. Therefore this method is a promising new technique that can be applied in the lots of fields, such as geotechnical and archaeological surveys.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.60-69
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• 2020

Purpose: Cavity growth process monitoring is to periodically monitor changes in common size and topography for general and observational grades to predict the rate of common growth. The purpose of this study is to establish a systematic cavity management plan by evaluating the general and observational class community in a non-destructive method. Method: Using GPR exploration equipment, the acquired surface image and the surrounding status image are analyzed in the GPR probe radargram in depth, profile, and cross section of the location. The exact location is selected using the distance and surrounding markings shown on the road surface of the initial detection cavity, and the test cavity is analyzed by calling the radar at the corresponding location. Result: As a result of monitoring tests conducted at a cavity 30 sites of general and observation grade, nine sites have been recovered. Changes in scale were seen in 21 cavity locations, and changes in size and grade occurred in 13 locations. Conclusion: The under road cavity is caused by various causes such as damage to the burial site, poor construction, soil leakage caused by groundwater leakage, waste and ground vibration. Among them, indirect factors could infer the effects of groundwater and localized rainfall.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.737-746
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• 2023

Purpose: Ground subsidence due to cavity can bring about various problems, such as casualties, decrease of the safety of the structures, and indirect social costs. Therefore, ground subsidence should be prevented through the exploration and recovery of the cavity under the pavements. Method: In this study, GPR exploration method was carried out on both actual roadway and mock-up site to compensate for the problems caused by excavation and restoration process. Result: This study compared the cavity scales obtained from GPR exploration results and the direct excavation of the identified cavity. It was confirmed that the predicted soil depth by GPR exploration was similar to the identified soil depth, but the predicted cavity scale by GPR exploration overestimated the longitudinal and cross-sectional widths compared to the identified cavity scale. Conclusion: Based on the correlation between the predicted cavity scales by GPR exploration, it is possible to qualitatively estimate the cavity scales using the empirical formula proposed in this study.

• Journal of Soil and Groundwater Environment
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• v.21 no.4
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• pp.30-41
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• 2016

The amount of groundwater related data is drastically increasing domestically from various sources since 2000. To justify the more expansive continuation of the data acquisition and to derive valuable implications from the data, continued employments of sophisticated and state-of-the-arts statistical tools in the analyses and predictions are important issue. In the present study, we employed a well established machine learning technique of Gaussian Process Regression (GPR) model in the trend analyses of groundwater level for the long-term change. The major benefit of GPR model is that the model provide not only the future predictions but also the associated uncertainty. In the study, the long-term predictions of groundwater level from the stations of National Groundwater Monitoring Network located within Han River Basin were exemplified as prediction cases based on the GPR model. In addition, a few types of groundwater change patterns were delineated (i.e., increasing, decreasing, and no trend) on the basis of the statistics acquired from GPR analyses. From the study, it was found that the majority of the monitoring stations has decreasing trend while small portion shows increasing or no trend. To further analyze the causes of the trend, the corresponding precipitation data were jointly analyzed by the same method (i.e., GPR). Based on the analyses, the major cause of decreasing trend of groundwater level is attributed to reduction of precipitation rate whereas a few of the stations show weak relationship between the pattern of groundwater level changes and precipitation.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.30-33
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• 2001

This paper discusses the system design of a synthetic aperture radar system based on a pulse-echo radar. The design consists of an ultra-wide bandwidth antenna, an amplitude modulation, timing stabilities, and high speed a/d conversions with an equivalent-time sampling. Experiment results show that GPR(Ground Penetrating Radar) can be used to explore buried electric facilities.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.2
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• pp.177-184
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• 2003

A series of experimental work has been conducted to evaluate the capability of Ground Penetrating Radar (GPR) system in detecting delamination inside concrete. Three antenna at 900 MHz, 1000 MHz, and 1500 MHz frequency are used in the experiments for laboratory size specimens, and 400 MHz antenna has been used for a large size specimen. The laboratory size specimens have the dimensions of 1,000 mm (length) ${\times}$ 600 mm (width) ${\times}$ 140 mm (thickness) with a delamination of 200 mm (length) ${\times}$ 600 mm (width) ${\times}$ 140 mm (thickness). The cover depth of the delamination is varied as follows: 20 mm, 30 mm, 60 mm, and 70 mm. In all cases, the delamination has been successfully identified. The property of three frequencies was seized about detecting delamination. Also, it was shown that the image results in GPR were improved by signal processing.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.1-9
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• 2015

PURPOSES : The objective of this study is to propose a quality control and quality assurance method for use during asphalt pavement construction using non-destructive methods, such as ground penetrating radar (GPR) and an infrared (IR) camera. METHODS : A 1.0 GHz air-coupled GPR system was used to measure the thickness and in situ density of asphalt concrete overlay during the placement and compaction of the asphalt layer in two test construction sections. The in situ density of the asphalt layer was estimated based on the dielectric constant of the asphalt concrete, which was measured as the ratio of the amplitude of the surface reflection of the asphalt mat to that of a metal plate. In addition, an IR camera was used to monitor the surface temperature of the asphalt mat to ensure its uniformity, for both conventional asphalt concrete and fiber-reinforced asphalt (FRA) concrete. RESULTS : From the GPR test, the measured in situ air void of the asphalt concrete overlay gradually decreased from 12.6% at placement to 8.1% after five roller passes for conventional asphalt concrete, and from 10.7% to 5.9% for the FRA concrete. The thickness of the asphalt concrete overlay was reduced from 7.0 cm to 6.0 cm for the conventional material, and from 9.2 cm to 6.4 cm for the FRA concrete. From the IR camera measurements, the temperature differences in the asphalt mat ranged from $10^{\circ}C$ to $30^{\circ}C$ in the two test sections. CONCLUSIONS : During asphalt concrete construction, GPR and IR tests can be applicable for monitoring the changes in in situ density, thickness, and temperature differences of the overlay, which are the most important factors for quality control. For easier and more reliable quality control of asphalt overlay construction, it is better to use the thickness measurement from the GPR.

• Biomolecules & Therapeutics
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• v.29 no.1
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• pp.22-30
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• 2021

Till the 21st century, fatty acids were considered as merely building blocks for triglycerides, phospholipids, or cholesteryl esters. However, the discovery of G protein-coupled receptors (GPCRs) for free fatty acids at the beginning of the 21st century challenged that idea and paved way for a new field of research, merged into the field of receptor pharmacology for intercellular lipid mediators. Among the GPCRs for free fatty acids, free fatty acid receptor 4 (FFA4, also known as GPR120) recognizes long-chain polyunsaturated fatty acids such as DHA and EPA. It is significant in drug discovery because it regulates obesity-induced metaflammation and GLP-1 secretion. Our study reviews information on newly developed FFA4 agonists and their application in pathophysiologic studies and drug discovery. It also offers a potency comparison of the FFA4 agonists in an AP-TGF-α shedding assay.

• Geomechanics and Engineering
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• v.30 no.1
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• pp.11-26
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• 2022

One of the most important issues in tunneling, is the squeezing phenomenon. Squeezing can occur during excavation or after the construction of tunnels, which in both cases could lead to significant damages. Therefore, it is important to predict the squeezing and consider it in the early design stage of tunnel construction. Different empirical, semi-empirical and theoretical-analytical methods have been presented to determine the squeezing. Therefore, it is necessary to examine the ability of each of these methods and identify the best method among them. In this study, squeezing in a part of the Alborz service tunnel in Iran was estimated through a number of empirical, semi- empirical and theoretical-analytical methods. Among these methods, the most robust model was used to obtain a database including 300 data for training and 33 data for testing in order to develop a machine learning (ML) method. To this end, three ML models of Gaussian process regression (GPR), artificial neural network (ANN) and support vector regression (SVR) were trained and tested to propose a robust model to predict the squeezing phenomenon. A comparative analysis between the conventional and the ML methods utilized in this study showed that, the GPR model is the most robust model in the prediction of squeezing phenomenon. The sensitivity analysis of the input parameters using the mutual information test (MIT) method showed that, the most sensitive parameter on the squeezing phenomenon is the tangential strain (ε_θ^α) parameter with a sensitivity score of 2.18. Finally, the GPR model was recommended to predict the squeezing phenomenon in tunneling projects. This work's significance is that it can provide a good estimation of the squeezing phenomenon in tunneling projects, based on which geotechnical engineers can take the necessary actions to deal with it in the pre-construction designs.

• Journal of the Korean GEO-environmental Society
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• v.20 no.9
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• pp.5-11
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• 2019

Recently, ground collapse in urban area has been widely paid attention as it frequently happens. To investigate the causes and suggest the measurements, many researches such as ground exploration from GPR, mock test and numerical simulations have been conducted. The proposed risk evaluation chart recently focuses only on the current ground status and is not capable of forecasting the ground collapse. This paper presents the prediction method of ground collapse using the numerical simulations of 30 cases considering void size and ground height as variables. It finally provides the charts that can analyze quantitatively the ground collapse.