• Journal of the Korean Geotechnical Society
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• v.38 no.10
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• pp.17-29
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• 2022

Recently, the interest in integrated underground geospatial information mapping (IUGIM) to ensure the safety of underground spaces and facilities has been increasing. Because IUGIM is used in the fields of underground space development and underground safety management, the up-to-dateness and accuracy of information are critical. In this study, IUGIM and field data were classified, and the accuracy of IUGIM was improved by spatial interpolation. A spatial interpolation technique was used to process borehole data in IUGIM, and a quantitative evaluation was performed with mean absolute error and root mean square error through the cross-validation of seven interpolation results according to the technique and model. From the cross-validation results, accuracy decreased in the order of nonuniform rational B-spline, Kriging, and inverse distance weighting. In the case of Kriging, the accuracy difference according to the variogram model was insignificant, and Kriging using the spherical variogram exhibited the best accuracy.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.173-181
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• 2009

This paper proposes an algorithm to transform RDF(Resource Description Framework) models for ontology into CPN(Colored Petri Net) models. The algorithm transforms the semantics of the RDF model into the topology of the CPN by mapping the classes and the properties of the RDF onto the places of the CPN model then reflects the RDF statements on the CPN by representing the relationships between them as token transitions on the CPN. The basic idea of reflecting the RDF statements on the CPN is to generate a token, which is an ordered pair consisting of two tokens (one from the place mapped into the subject and the other one from the place mapped into the object) and transfer it to the place mapped into the predicate. We have actually built CPN models for given RDF models on the CNPTools and inferred and extracted answers to the RDF queries on the CPNTools.

• Journal of Korean Library and Information Science Society
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• v.54 no.2
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• pp.1-22
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• 2023

In this study, we propose a plan to reflect LRM in various library-related standards or systems through analyzing the reflection of LRM in RDA. To this end, LRM and RDA 2020 were analyzed in terms of entities, relationships, attributes, and encoding schemes. First of all, for the mapping of entities, relationships, and attributes, all properties and relationships were extracted for each entity of RDA, LRM elements corresponding to each property and relationship were found and mapped, and encoding schemes were additionally compared. As a result, the things to consider in the standards and systems to which LRM is to be applied are: first, entities development considering the LRM hierarchy; second, new relation or shortcut path relation development; third, attributes expansion according to the entities considering the LRM hierarchical structure, and fourth, the development of various encoding scheme. Through this study, it will be possible to find an application plan using the application of RDA as a model in standards or systems to accept LRM.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.364-364
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• 2021

최근 지구온난화에 따른 홍수 및 가뭄 재해의 피해는 심각해졌다. 그러므로 미래 재해로 인한 피해를 완화시키기 위한 수자원 계획 수립 및 관리의 중요성이 높아지고 있다. 전지구모형(General Circulation Model, GCM)은 기후 변화 연구에서 기후 요인의 변동을 조사하는데 널리 사용되어지고 있다. 본 연구에서는 기후 변화 시나리오를 고려하여 도시유역의 소유역 별 투수성포장 시설의 우선순위를 산정했다. 기후 변화 시나리오에는Representative Concentration Pathway(RCP)와 Shared Socioeconomic Pathway(SSP) 시나리오가 사용되었으며 CMIP5와 CMIP6의 GCM을 고려하였다. GCM을 이용하여 산정된 미래 월 강수량은 분위사상(Quantile Mapping)법의 비모수변환(Non-Parametirc Transformation)법 중 하나인 스플라인 평활(Smoothing Spline) 방법을 사용하여 편이보정 되었다. 연구대상지는 목감천 유역이 선정되었으며, 27개의 소유역에 대해 투수성포장 시설의 우선순위를 산정되었다. 우선순위 산정을 위한 평가 기준들은 Driving force-Pressure-State-Impact-Response(DPSIR) 모형을 기반으로 산정 되었다. 평가기준에 따른 27개의 소유역에 대한 값들은 통계청 및 국가수자원관리종합정보시스템(WAMIS), 편이보정 된 미래 강수량과 Storm Water Management Model(SWMM)을 이용한 유출분석 결과를 통해 도출했다. 평가기준들의 객관적 가중치 산정을 위해 엔트로피 방법을 이용했다. 최종적으로 목감천 소유역 별 투수성포장 시설의 우선순위 산정에는 다기준의사결정기법 중 하나인 TOPSIS방법을 사용했다. 산정 결과 DPSIR 모형을 기반으로 수문학적 요소에 큰 가중치를 부여한 경우 하류보다는 상류 유역에서 높은 우선순위를 확인했으며, 각 요소별 동일한 가중치를 주었을 때 하류 유역에 높은 우선순위가 집중되었다.

• The Journal of Engineering Geology
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• v.34 no.1
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• pp.51-65
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• 2024

Landslides are natural disasters that causes significant property damage worldwide every year. In Korea, damage due to landslides is increasing owing to the effects of climate change, and it is important to identify the factors that increase the prevalence of landslides in order to reduce the damage they cause. Therefore, this study used a random forest model to analyze the importance of 14 factors in influencing landslide damage in a specific area of Chungju, Chungcheongbuk-do province, Korea. The random forest model performed accurately with an AUC of 0.87 and the most-important factors were ranked in the order of aspect, slope, distance to valley, and elevation, suggesting that topographic factors such as aspect and slope more greatly influence landslide damage than geological or soil factors such as rock type and soil thickness. The results of this study are expected to provide a basis for mapping and predicting landslide damage, and for research focused on reducing landslide damage.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.6
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• pp.522-528
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• 2009

This study focused on establishing prediction models using visible-near infrared spectrum to simultaneously detect multiple components of soils and enhancing the performance quality by suitably transformed input spectra and classification of soil spectral types for prediction model input. The continuum-removed spectra showed significant result for all cases in terms of soil properties and classified or bulk predictions. The prediction model using classified soil spectra at an absorption peak area around 500nm and 950nm efficiently indicating soil color showed slightly better performance. Especially, Ca and CEC were well estimated by the classified prediction model at $R^{2}$ > 0.8. For organic carbon, both classified and bulk prediction model had a good performance with $R^{2}$ > 0.8 and RPD> 2. This prediction model may be applied in global soil mapping, soil classification, and remote sensing data analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.62-73
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• 2010

A bird is needed efficient conservation through habitat management, as the representative of an organism to evaluate the steady of complex ecosystem. So, this study will offer the useful basic data for preserving habitat from now on, as presenting a estimating model with the GIS program which selected factors effecting the habitat of a forest-dwelling bird in Changwon. As the resort of the survey, the number of forest-dwelling birds living in the 135 survey sites were 5 order, 15 family, 26 species and 922 individual. Also, as the result of making habitat analysis into a predict model, 'NDVI', 'Distance to valley', 'Distance to mixed forest' and 'Area of field' were significant and they had R-squares of 51.3%. Next, as the resort of researching the accuracy of Model, it was a reasonable prediction, as the correlation coefficient is 0.735 and MAPE is 20.7%, and a predict map of habitat was made with the model. This map could predict species diversity of no investigated areas and could be an useful basic data for preserving habitat, as an on-the-spot survey.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.151-163
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• 2018

The objective of this study was to estimate LOADEST (LOAD Estimator) coefficients for simulating pollutant loads in ungauged watersheds. Regression models of LOADEST were used to simulate pollutant loads, and the multiple linear regression (MLR) was used for coefficients estimation on watershed characteristics. The fifth and third model of LOADEST were selected to simulate T-N (Total-Nitrogen) and T-P (Total-Phosphorous) loads, respectively. The results and statistics indicated that regression models based on LOADEST simulated pollutant loads reasonably and model coefficients were reliable. However, the results also indicated that LOADEST underestimated pollutant loads and had a bias. For this reason, simulated loads were corrected the bias by a quantile mapping method in this study. Corrected loads indicated that the bias correction was effective. Using multiple regression analysis, a coefficient estimation methods according to the watershed characteristic were developed. Coefficients which calculated by MLR were used in models. The simulated result and statistics indicated that MLR estimated the model coefficients reasonably. Regression models developed in this study would help simulate pollutant loads for ungauged watersheds and be a screen model for policy decision.

• Korean Journal of Cognitive Science
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• v.12 no.1_2
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• pp.77-89
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• 2001

Applying perceptual hierarchy of facial feature points, a neural network model for recognizing facial expressions was designed. Input data were convolution values of 150 facial expression pictures by Gabor-filters of 5 different sizes and 8 different orientations for each of 39 mesh points defined by MPEG-4 SNHC (Synthetic/Natural Hybrid Coding). A set of multiple regression analyses was performed with the rating value of the affective states for each facial expression and the Gabor-filtered values of 39 feature points. The results show that the pleasure-displeasure dimension of affective states is mainly related to the feature points around the mouth and the eyebrows, while a arousal-sleep dimension is closely related to the feature points around eyes. For the filter sizes. the affective states were found to be mostly related to the low spatial frequency. and for the filter orientations. the oblique orientations. An optimized neural network model was designed on the basis of these results by reducing original 1560(39x5x8) input elements to 400(25x2x8) The optimized model could predict human affective rating values. up to the correlation value of 0.886 for the pleasure-displeasure, and 0.631 for the arousal-sleep. Mapping the results of the optimized model to the six basic emotional categories (happy, sad, fear, angry, surprised, disgusted) fit 74% of human responses. Results of this study imply that, using human principles of recognizing facial expressions, a system for recognizing facial expressions can be optimized even with a a relatively little amount of information.

• Proceedings of the KSRS Conference
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• v.2
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• pp.827-830
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• 2006

The tsunami from the megathrust earthquake magnitude 9.3 on 26 December 2004 is the largest tsunami the world has known in over forty years. This tsunami destructively attacked 13 countries around Indian Ocean with at least 230,000 fatalities, displaced people 2,089,883 and 1.5 million people who lost their livelihoods. The ratio of women and children killed to men is 3 to 1. The total damage costs US$ 10.73 billion and rebuilding costs US$ 10.375 billion. The tsunami's death toll could have been drastically reduced, if the warning was disseminated quickly and effectively to the coastal dwellers along the Indian Ocean rim. With a warning system in Indian Ocean similar to that operating in the Pacific Ocean since 1965, it would have been possible to warn, evacuate and save countless lives. The best tribute we can pay to all who perished or suffered in this disaster is to heed its powerful lessons. UNESCO/IOC have put their tremendous effort on better disaster preparedness, functional early warning systems and realistic arrangements to cope with tsunami disaster. They organized ICG/IOTWS (Indian Ocean Tsunami Warning System) and the third of this meeting is held in Bali, Indonesia during $31^{st}$ July to $4^{th}$ August 2006. A US$ 53 million interim warning system using tidal gauges and undersea sensors is nearing completion in the Indian Ocean with the assistance from IOC. The tsunami warning depends strictly on an early detection of a tsunami (wave) perturbation in the ocean itself. It does not and cannot depend on seismological information alone. In the case of 26 December 2004 tsunami when the NOAA/PMEL DART (Deep-ocean Assessment and Reporting of Tsunami) system has not been deployed, the initialized input of sea surface perturbation for the MOST (Method Of Splitting Tsunami) model was from the tsunamigenic-earthquake source model. It is the first time that the satellite altimeters can detect the signal of tsunami wave in the Bay of Bengal and was used to validate the output from the MOST model in the deep ocean. In the case of Thailand, the inundation part of the MOST model was run from Sumatra 2004 for inundation mapping purposes. The medium and high resolution satellite data were used to assess the degree of the damage from Indian Ocean tsunami of 2004 with NDVI classification at 6 provinces on the Andaman seacoast of Thailand. With the tide-gauge station data, run-up surveys, bathymetry and coastal topography data and land-use classification from satellite imageries, we can use these information for coastal zone management on evacuation plan and construction code.