• Journal of Korean Tunnelling and Underground Space Association
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• v.12 no.6
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• pp.463-473
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• 2010

A new approach for prediction of a fault zone ahead of tunnel face by using statistical control charts is suggested and applied to the construction site. $x-R_s$ control charts of RMR parameters were investigated as approaching and passing through fault zone. The abnormal signal from the control charts was observed and analyzed based on statistical criteria. Fault zones in the application area were predicted in advance using this method and it was verified by comparing with observation data like horizontal boring and face mapping.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.285-285
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• 2022

기후변화가 현실화되면서 수자원평가 (Water Resources Assessment)에 대한 관심과 중요성이 높아지고 있다. 본 연구에서는 '주민공감 문제기획리빙랩' 대상지인 순천은 동천을 중심으로 홍수량을 정량적으로 분석하였다. 순천시의 가장 시급한 사안 중 하나인 범람 및 침수 문제로, 최근 3년(2018~2020)간의 집중호우로 인한 내수배제로 주택 및 도로침수, 산사태 등의 피해를 겪었다. 시기마다 고질적으로 반복되는 동천 인근 지역의 침수문제를 사전에 예방하고 피해의 빈도나 규모를 줄이기 위하여 분석을 수행하였다. 이에 본 연구에서는 환경부의 지원을 받아 한강홍수통제소와 한국건설기술연구원이 공동으로 개발한 동적수자원평가모형(DWAT, Dynamic Water Resources Assessment Tool)을 이용하여 정량적으로 홍수량 산정을 하고자 한다. 본 모형은 전 세계가 무료로 이용할 수 있는 수자원평가도구로 사용자의 편의를 위해 GIS전처리 기능을 포함하고 있어, 자동으로 유역 매개변수 및 면적 평균강우량을 Thiessen method를 사용하여 산정할 수 있다. 또한, 물의 순환과정을 투수 및 불투수지역으로 구분되며, 투수지역은 1개의 토양층과 1개의 불압대수층으로 구성되고, 유출기여역과 함양역으로 유역을 분할하여 적용할 수 있으며, 대수층을 통하여 지하수의 흐름을 산정할 수 있다. 기상청에서 제공하는 기상자료를 분석하여 과거 관측 강우사상 3개를 선정하여 검·보정을 수행하였으며, 그 결과 모형 효율계수(Nash-Sutcliffe efficiency) 및 결정계수(Coefficient of Determination)가 0.78~0.94, 0.82~0.94로 우수한 모의 결과를 산정할 수 있었다. 빈도별 확률강우량을 Huff 4분위법을 사용하여 확률홍수량을 산정하였다. 미래 홍수량 증감량 산정을 위하여 RCP(Representative Concentration Pathways) 기후변화 시나리오를 사용하였다. 관측값과 모의값의 누적확률분포 이용하여 모의값의 확률분포를 관측값의 확률분포에 사상시키는 방법인 분위사상법(Quantile Mapping)을 사용하여 시나리오자료를 보정하였다. 본 연구에서 산정한 홍수량을 바탕으로 침수피해를 막기 위한 구조적 및 비구조적 방안을 위한 기초자료로 사용될 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• Journal of The Geomorphological Association of Korea
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• v.27 no.3
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.

• Journal of The Geomorphological Association of Korea
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• v.26 no.3
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• pp.53-67
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• 2019

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.

• Journal of The Korean Association For Science Education
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• v.27 no.1
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• pp.84-92
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• 2007

The purpose of this study was to investigate biologists' brain activation patterns during the generation of scientific questions on biological phenomena. Eight right-handed healthy biologists volunteered to be participants in the present study. The question-generation tasks were presented in a block design. The BOLD signals of the biologists' brain were measured by 3.0T fMRI system and data were analyzed using Statistical Parametric Mapping (SPM2). According to our results, the left inferior and middle frontal gyri, the medial prefrontal cortex, the bilateral hippocampus, the occipito-parietal route, the fusiform gyrus, and the cerebellum were activated significantly during the generation of scientific questions. Therefore, we suggested that generating scientific question is associated with analyzing observed situations, using verbal strategy, retrieving episodic memories for comparisons, and feeling cognitive conflicts.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.3
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• pp.30-42
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• 2024

In this paper, we presented the processing process of the sea floor mapping system using multi-beam echo-sounding data through actual measurements and the results of processing the multi-beam echo-sounding data obtained by exploring some waters of Yeosu Bay. Simultaneously and continuously observe the location and water depth of the sea using GNSS and multi-beam echo sounder, synchronization of the two data, depth correction process considering the tide level at the time of observation, 3D model of the seafloor, contour map, and longitudinal and cross-section data of the seafloor topography. In addition, by extracting efficiently the dredging volume according to the dredging area and planned water depth required for dredging construction management of submarine projects, it can be used for maintenance and management of marine construction sites and ports.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.5
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• pp.704-711
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• 2020

Objective: Muscle fiber types, numbers and area are crucial aspects associated with meat production and quality. However, there are few studies of pig muscle fibre traits in terms of the detection power, false discovery rate and confidence interval precision of whole-genome quantitative trait loci (QTL). We had previously performed genome scanning for muscle fibre traits using 183 microsatellites and detected 8 significant QTLs in a White Duroc×Erhualian F₂ population. The confidence intervals of these QTLs ranged between 11 and 127 centimorgan (cM), which contained hundreds of genes and hampered the identification of QTLs. A whole-genome sequence imputation of the population was used for fine mapping in this study. Methods: A whole-genome sequences association study was performed in the F₂ population. Genotyping was performed for 1,020 individuals (19 F₀, 68 F₁, and 933 F₂). The whole-genome variants were imputed and 21,624,800 single nucleotide polymorphisms (SNPs) were identified and examined for associations to 11 longissimus dorsi muscle fiber traits. Results: A total of 3,201 significant SNPs comprising 7 novel QTLs showing associations with the relative area of fiber type I (I_RA), the fiber number per square centimeter (FN) and the total fiber number (TFN). Moreover, one QTL on pig chromosome 14 was found to affect both FN and TFN. Furthermore, four plausible candidate genes associated with FN (kinase non-catalytic C-lobe domain containing [KNDC1]), TFN (KNDC1), and I_RA (solute carrier family 36 member 4, contactin associated protein like 5, and glutamate metabotropic receptor 8) were identified. Conclusion: An efficient and powerful imputation-based association approach was utilized to identify genes potentially associated with muscle fiber traits. These identified genes and SNPs could be explored to improve meat production and quality via marker-assisted selection in pigs.

• Korean Journal of Agricultural Science
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• v.40 no.2
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• pp.155-162
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• 2013

Genome-wide association study was performed on data from 266 Hanwoo steers derived from 66 sire using bovine 10K mapping chip in Hanwoo (Korean Cattle). SNPs were excluded from the analysis if they failed in over 5% of the genotypes, had median GC scores below 0.6, had GC scores under 0.6 in less than 90% of the samples, deviated in heterozygosity more than 3 standard deviations from the other SNPs and were out of Hardy-Weinberg equilibrium for a cutoff p-value of $1^{-15}$. Unmapped and SNPs on sex chromosomes were also excluded. A total of 4,522 SNPs were included in the analysis. To test an association between SNP and QTL, GWAS for five genetic mode (additive, dominant, overdominant, recessive and codominant) was implemented in this study. Three SNPs (rs29018694, ss46526851 and rs29018222) at a threshold p< $1.11{\times}10^{-5}$ were detected on BTA12 and BTA21 for dressing percentages in codominant and recessive genetic mode. The G allele for rs29018694 has 4.9% higher dressing percentage than A allele, while the T allele for ss46526851 has 2.57 % higher dressing percentage than C allele. Therefore, rs29018694 SNP showed a bigger effect than the other two SNPs (ss46526851 and rs29018222) in this study. In conclusion, this study identifies three loci with moderate effects and many loci with infinitesimally small effect across genome in Hanwoo.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.9
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• pp.1210-1213
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• 2004

Quantitative trait loci (QTL) mapping can be applied to detect chromosomal locations that control economic traits in farm animals. Teat number has been considered as one of the most important factors to evaluate mothering ability of sow. Especially, teat number is more important when the number is less than the litter size. This study was conducted to identify QTL affecting teat number in the Korean native pig${\times}$Landrace resource family. A total of 240 animals was genotyped for 132 polymorphic microsatellites covering the 18 pig autosomes. Mean and standard deviation of teat number in $F_2$animals is 13.46${\pm}$1.40. QTL was analyzed using F2 QTL Analysis Servlet of QTL express. A QTL for teat number on SSC9 was significant at the 1% chromosome-wide level and three suggestive QTL were detected on SSC3, 7 and 14. All QTL detected in this study had additive effect and Landrace alleles were associated with higher teat number in comparison with Korean native pig for three of four QTL.