• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.479-493
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• 2023

The need for safety management has arisen due to the increasing number of years of operated underground structures, such as tunnels and utility tunnels, and accidents caused by those aging infrastructures. However, in the case of privately managed underground utility ducts, there is a lack of detailed guidelines for facility safety and maintenance, resulting in inadequate safety management. Furthermore, the absence of basic design information and the limited space for safety assessments make applying currently used non-destructive testing methods challenging. Therefore, this study suggests non-destructive inspection methods using ultrasonic and impact-echo techniques to assess the quality of underground structures. Thickness, presence of rebars, depth of rebars, and the presence and depth of internal defects are assessed to provide fundamental data for the safety assessment of box-type general underground structures. To validate the proposed methodology, different conditions of concrete specimens are designed and cured to simulate actual field conditions. Applying ultrasonic and impact signals and collecting data through multi-channel accelerometers determine the thickness of the simulated specimens, the depth of embedded rebar, and the extent of defects. The predicted results are well agreed upon compared with actual measurements. The proposed methodology is expected to contribute to developing safety diagnostic methods applicable to general underground structures in practical field conditions.

• Journal of the Korean Society of Radiology
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• v.82 no.5
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• pp.1124-1139
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• 2021

The objective assessment of atrophy and the measurement of brain volume is important in the early diagnosis of dementia and neurodegenerative diseases. Recently, several MR-based volumetry software have been developed. For their clinical application, several issues arise, including the standardization of image acquisition and their validation of software. Additionally, it is important to highlight the diagnostic performance of the volumetry software based on expert opinions. We instituted a task force within the Korean Society of Neuroradiology to develop guidelines for the clinical use of MR-based brain volumetry software. In this review, we introduce the commercially available software and compare their diagnostic performances. We suggest the need for a standard protocol for image acquisition, the validation of the software, and evaluations of the limitations of the software related to clinical practice. We present recommendations for the clinical applications of commercially available software for volumetry based on the expert opinions of the Korean Society of Neuroradiology.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.403-421
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• 2023

As the number of underground structures has increased in recent decades, it has become crucial to predict geological hazards ahead of a tunnel face during tunnel construction. Consequently, this study developed a finite element (FE) numerical model to simulate electrical resistivity surveys in tunnel boring machine (TBM) operations for predicting mixed ground conditions in front of tunnel faces. The accuracy of the developed model was verified by comparing the numerical results not only with an analytical solution but also with experimental results. Using the developed model, a series of parametric studies were carried out to estimate the effect of geological conditions and sensor geometric configurations on electrical resistivity measurements. The results of these studies showed that both the interface slope and the difference in electrical resistivity between two different ground formations affect the patterns and variations in electrical resistivity observed during TBM excavation. Furthermore, it was revealed that selecting appropriate sensor spacing and optimizing the location of the electrode array were essential for enhancing the efficiency and accuracy of predictions related to mixed ground conditions. In conclusion, the developed model can serve as a powerful and reliable tool for predicting mixed ground conditions during TBM tunneling.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.5
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• pp.339-350
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• 2024

In construction sites, the engine of heavy machinery is tested by practitioners who manually adjust engine settings and directly measure the output. This process has consistently raised concerns regarding time costs and the risk of incidents. To address these issues, simulations of heavy equipment are conducted using Speedgoat and the Simulink API. However, due to the varying compatibility of different versions of Speedgoat hardware and Simulink API, engineers need to have a comprehensive understanding of various Simulink APIs. It is practically challenging for engineers, who must have a deep understanding of heavy equipment structures, to also possess programming skills including API usage. Thus, this paper proposes a tool that allows inputting configuration values for heavy equipment simulation and visually outputs and logs the simulation results. The proposed tool provides functionalities to deliver configuration values, such as engine settings of heavy equipment, to the simulator model and to monitor and log the resulting simulation outputs. These functionalities have been validated through scenarios. By using the developed tool, engineers are expected to reduce the burden of learning Simulink API and focus more on understanding the structure of heavy equipment. Additionally, it is anticipated that this tool will provide a more efficient and safer working environment for heavy equipment testing on construction sites.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.233-245
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• 2021

Many studies on the microstructures in rocks have been conducted using experimental methods with various equipment as well as natural rock studies to see the development of microstructures and understand their mechanisms. Grain boundary migration of mineral aggregates in rocks could cause grain growth or grain size changes during metamorphism or deformation as one of the main recrystallization mechanisms. This study suggests improved ways regarding the analog material experiments with reformed equipment to see sequential observations of these grain boundary migration. It can be more efficient than the existing techniques and carry out an appropriate microstructure analysis. This reformed equipment was implemented to enable optical manipulation by mounting polarizing plates capable of rotating operation on a stereoscopic microscope and a deformation rig capable of experimenting with analog materials. The equipment can automatically control the temperature and strain rate of the deformation rig by microcontrollers and programming and can take digital photomicrographs with constant time intervals during the experiment to observe any microstructure changes. The composite images synthesized using images by rotated polarizing plates enable us to see more accurate grain boundaries. As a rock analog material, norcamphor(C7H10O) was used, which has similar birefringence to quartz. Static grain growth and simple shear deformation experiments were performed using the norcamphor to verify the effectiveness of the equipment. The static grain growth experiments showed the characteristics of typical grain growth behavior. The number of grains decreases and the average grain size increases over time. These case experiments also showed a clear difference between the growth curves with three temperature conditions. The result of the simple shear deformation experiment under the medium temperature-low strain rate showed no significant change in the average grain size but presented the increased elongation of grain shapes in the direction of about 53° regarding the direction perpendicular to the shearing direction as the shear strain increases over time. These microstructures are interpreted as both the plastic deformation and the internal recovery process in grains are balanced by the deformation under the given experimental conditions. These experiments using the reformed equipment represent the ability to sequentially observe changing the microstructure during experiments as desired in the tests with the analog material during the entire process.

• Weed & Turfgrass Science
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• v.7 no.3
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• pp.191-199
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• 2018

This study was to investigate the occurrence patterns of paddy weeds, their resistance levels to an ALS inhibiting herbicide, and to estimate the areas of resistance in these paddy fields. We used soil collected from 358 paddy fields of Jeonnam province in 2017. Based on their life cycles, weeds were 96% annuals and 4% perennial. Additionally, according to morphological classification, 59% were broad leaves, 28% were sedges and 13% were grasses. Different areas within Jeonnam province contained different numbers and occurrence rates of weed species. However, generally, we observed Lindernia dubia var. dubia, Monochoria vaginalis var. plantaginea, Ludwigia prostrata, L. procumbens, Cyperus difformis, Scirpus juncoides, Eleocharis Kuroguwai, Echinochloa oryzoides, and E. crus-galli var. echinata. We also observed seven weeds resistant to an ALS inhibiting herbicide. They were M. vaginalis, S. juncoides, C. difformis, L. dubia, Ludwigia prostrata, E. oryzoides, and E. crus-galli var. echinata. Although there were differences in the number and occurrence rate of resistant weed species to an ALS inhibiting herbicide among areas in Jeonnam province, the M. vaginalis, C. difformis, and S. juncoides occurred in 23 cities and counties in Jeonnam including Gwangju metropolitan city. Based on the rates (52%) of resistant occurrence to an ALS inhibiting herbicide in Jeonnam province, the area of weed resistant paddy fields was estimated to be 91,543 ha.

• Progress in Medical Physics
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• v.25 no.3
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• pp.143-150
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• 2014

In general radiotherapy, mega-voltage (MV) x-ray images are widely used as the unique method to verify radio-therapeutic fields. But, the image quality of MV images is much lower than that of kilo-voltage x-ray images due to scatter interactions. Since 1990s, studies for the scatter correction have performed with digital-based MV imaging systems. In this study, a novel method for the scatter correction is suggested using scatter to primary ratio (SPR), instead of conventional methods such as digital image processing or scatter kernel calculations. We measured two MV images with and without a solid water phantom describing a patient body with given imaging conditions, and calculated un-attenuated ratios. Then, we obtained SPR distributions for the scatter correction. For experimental validation, a line-pair (LP) phantom using several Al bars and a clinical pelvis MV image was used. As the result, scatter signals of the LP phantom image were successfully reduced so that original density distribution of the phantom was restored. Moreover, image contrast values increased after SPR correction at all ROIs of the clinical image. The mean value of increases was 48%. The SPR correction method suggested in this study has high reliability because it is based on actually measured data. Also, this method can be easily adopted in clinics without additional cost. We expected that the SPR correction can be an effective method to improve the quality of MV image guided radiotherapy.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.13-18
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• 2013

This study was conducted to estimate the Genomic Estimated Breeding Value (GEBV) using Genomic Best Linear Unbiased Prediction (GBLUP) method in Hanwoo (Korean native cattle) population. The result is expected to adapt genomic selection onto the national Hanwoo evaluation system. Carcass weight (CW), eye muscle area (EMA), backfat thickness (BT), and marbling score (MS) were investigated in 552 Hanwoo progeny-tested steers at Livestock Improvement Main Center. Animals were genotyped with Illumina BovineHD BeadChip (777K SNPs). For statistical analysis, Genetic Relationship Matrix (GRM) was formulated on the basis of genotypes and the accuracy of GEBV was estimated with 10-fold Cross-validation method. The accuracies estimated with cross-validation method were between 0.915~0.957. In 534 progeny-tested steers, the maximum difference of GEBV accuracy compared to conventional EBV for CW, EMA, BT, and MS traits were 9.56%, 5.78%, 5.78%, and 4.18% respectively. In 3,674 pedigree traced bulls, maximum increased difference of GEBV for CW, EMA, BT, and MS traits were increased as 13.54%, 6.50%, 6.50%, and 4.31% respectively. This showed that the implementation of genomic pre-selection for candidate calves to test on meat production traits could improve the genetic gain by increasing accuracy and reducing generation interval in Hanwoo genetic evaluation system to select proven bulls.

• Journal of Radiation Protection and Research
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• v.23 no.4
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• pp.229-236
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• 1998

In order to establish a testing system for personnel dosimetry performance, the radiation fields from photons, beta particles and neutrons are required, in recent, Korea Institute of Nuclear Safety(KINS) established the reference radation fields except neutrons and tested a variety of their properties. As a result of the test, the reference beams were shown to meet satisfactorily not only the standards of the International Organization for Standardization(ISO), but also the standard levels of the developed countries which are intercomparable with the international traceability. This paper describes the reference beam of gamma radiation. The self-designed and established reference radiation fields were investigated and analyzed by ISO and other international standards. The secondary photon contribution and the beam uniformity of the gamma radiation field were measured and evaluated to fulfill those requirements suggested by the ISO-4037. The measured air kerma rate for the $^{137}$Cs and $^{60}$Co gamma fields was 0.1891 $\sim$ 23.4967 $\mu$Gy/s sand 0.5844 $\sim$ 15.9954 $\mu$Gy/s respectively. The uncertainty with 95 % confidence level of the measured air kerma rate was determined to be less than 2.5 % which is comparable to the international reference gamma radiation fields. It was found that the evaluated air kerma calibration factors of Exradin ionization chamber were in good agreement within 0.9 % and 0.03 % with those given by PTB and NIST, respectively. The gamma radiation fields installed at KINS can maintain traceability systems in Korea, Germany and United State.

• Journal of the Korean Society of Radiology
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• v.14 no.6
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• pp.773-780
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• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.