• Tunnel and Underground Space
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• v.19 no.3
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• pp.236-247
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• 2009

Overpopulation has significantly increased the use of underground spaces in urban areas, and led to the developments of shallow-depth underground space. Due to unexpected rock fall, however, it is very necessary to understand and categorize the rock mass behaviors prior to the tunnel excavation, by which unnecessary casualties and economic loss could be prevented. In case of cave-in, special attention should be drawn since it occurs faster and greater in magnitude compared to rock fall and plastic deformation. Types of cave-in behavior are explained and categorized using seven parameters - Uniaxial Compressive Strength (UCS), Rock Quality Designation (RQD), joint surface condition, in-situ stress condition, ground water condition, earthquake & ground vibration, tunnel span. This study eventually introduces a new index called Cave-in Behavior Index (CBI) which explains the behavior of cave-in under given in-situ conditions expressed by the seven parameters. In order to assess the mutual interactions of the seven parameters and to evaluate the weighting factors for all the interactions, survey data of the experts' opinions and Rock Engineering Systems (RES) were used due to lack of field observations. CBI was applied to the tunnel site of Seoul Metro Line No. 9. UDEC analyses on 288 cases were done and occurrences of cave-in in every simulation were examined. Analyses on the results of 288 cases of simulations revealed that the average CBI for the cases when cave-in for different patterns of tunnel support was estimated by a logistic regression analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.2
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• pp.95-102
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• 2002

Spatial interpolation has become a common procedure in converting temperature forecasts and observations at irregular points for use in regional scale ecosystem modeling and the model based decision support systems for resource management. Neglection of terrain effects in most spatial interpolations for short term temperatures may cause erroneous results in mountainous regions, where the observation network hardly covers full features of the complicated terrain. A spatial interpolation model for daytime hourly temperature was formulated based on error analysis of unsampled site with respect to the site topography. The model has a solar irradiance correction scheme in addition to the common backbone of the lapse rate - corrected inverse distance weighting. The solar irradiance scheme calculates the direct, diffuse and reflected components of shortwave radiation over any surfaces based on the sun-slope geometry and compares the sum with that over a reference surface. The deviation from the reference radiation is used to calculate the temperature correction term by an empirical conversion formula between the solar energy and the air temperature on any sloped surfaces at an hourly time scale, which can be prepared seasonally for each land cover type. When this model was applied to a 14 km by 22 km mountainous region at a 10 m horizontal resolution, the estimated hourly temperature surfaces showed a better agreement with the observed distribution than those by a conventional method.

• The Journal of the Korea Contents Association
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• v.17 no.10
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• pp.472-482
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• 2017

In this study, discrete mathematical items were classified into analytical items and mathematical items were analyzed on the basis of analytic framework items of mathematics and the past items of mathematics subject contents of the period 2011-2017 school year. First, the discrete mathematics evaluation areas and evaluation contents proposed by the Korea Institute for Curriculum and Evaluation should be evenly distributed. Second, the items of measuring metacognitive knowledge as a strategic knowledge on the use of cognitive methods should be given. Third, the ratio of the number of items in discrete mathematics to the number of that was 3.8%~6.8%, and the ratio according to the item weighting was 2.2%~6.3%. Fourth, it is analyzed that all the items are suitable for the evaluation goal and the pre-service math teachers who have faithfully implemented the curriculum have maintained the appropriate level of difficulty to solve. Finally, the content items such as the method of counting the discrete mathematics curriculum, the Recurrence Relation, the generation function, and the graph are matched with the teacher certification examination and the mathematics education curriculum of each teachers college. By these reasons, we conclude that the contribution of pre-service teachers to the motivation of learning is obtained and implications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.184-189
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• 2018

Recently, research on lightweight automobiles is increasing continuously to respond to the high safety standards and environmental regulations. The application of high strength steel is one of the effective methods for developing lightweight car bodies. A TWB (Tailor Welded Blank) is major method that allows partial high strength with light weighting using a multi-thickness and multi-material welded blank. On the other hand, additional welding process is required to prepare the blank and quality control for the welding process also required. To secure this point, the TRB (Tailor Rolled Blank) method was suggested. In the TRB method, the thickness of sheet is controlled by the rolling presses and the production efficiency is much higher than welding in TWB methods. In this study, the formability of high strength TRB steel plate was analyzed to examine the rolling effect of the blank. The formability of the specimen was tested using 0.8 and 1 mm thick steel sheets for the TRB plate. The strain was analyzed by the digital image sensing of grid markings on the specimen and the forming limit diagram was calculated. An Erichsen test for the 0.8 and 1 mm thick TRB specimens was carried out and the formability was investigated by comparing with FE analysis.

• Journal of Korean Society of Rural Planning
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• v.21 no.2
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• pp.11-21
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• 2015

This study carried out evaluation of vulnerability in accessability and functionality using road network that was extracted from Intelligent Transportation System(ITS) and digital map. It was built in order to figure out accessability that locational data which include community center, public facilities, medical facilities and highway IC. The method for grasping functionality are Digital Elevation Model(DEM) and land slide hazard map provided by Korea Forest Service. The evaluation criteria for figure out accessability was set to related comparison of average time in urban area. Functionality value was calculated by the possibility of backing the vehicle possibility of snowfall and landslides. At last, this research computed weighting value through Analytic Hierarchy Process (AHP), calculated a vulnerable score. As the result, the accessability of rural village came out that would spend more time by 1.4 to 3.2 times in comparison with urban area. Even though, vulnerability of the road by a snowfall was estimated that more than 50% satisfies the first class, however, it show up that the road were still vulnerable due snowing because over the 14% of the road being evaluated the fifth class. The functionality has been satisfied most of the road, however, It was vulnerable around Lake Daechung and Piban-ryung, Yumti-jae, Suriti-jae where on the way Boeun. Also, the fifth class road are about 35 km away from the city hall on distance, take an hour to an hour and a half. The fourth class road are about 25 km away from the city hall on distance, take 25 min to an hour. The other class of the road take in 30 min from the city hall or aren't affected of weather and have been analyzed that a density of road is high. In A result that compare between distribution and a housing density came out different the southern and the eastern area, so this result could be suggested quantitative data for possibility of development.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.273-280
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• 2005

Robust magneto-telluric (MT) response function estimators are now in standard use in electromagnetic induction research. Properly devised and applied, these methods can reduce the influence of unusual data (outlier) in the response (electric field) variable, but often not sensitive to exceptional predictor (magnetic field) data, which are termed leverage points. A bounded influence estimator is described which simultaneously limits the influence of both outlier and leverage point, and has proven to consistently yield more reliable MT response function estimates than conventional robust approach. The bounded influence estimator combines a standard robust M-estimator with leverage weighting based on the statistics of the hat matrix diagonal, which is a standard statistical measure of unusual predictors. Further extensions to MT data analysis are proposed, including a establishment of data rejection criterion which minimize the influence of both electric and magnetic outlier in frequency domain based on statistical distribution of electromagnetic field. The rejection scheme made in this study seems to have an effective performance on eliminating extreme data, which is even not removed by BI estimator, in frequency domain. The effectiveness and advantage of these developments are illustrated using real MT data.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6935-6940
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• 2013

Background: This study aimed to develop a prognostic model in patients with early-stage cervical squamous cell carcinoma based on clinicopathological features, including invasive margin characteristics. Materials and Methods: Clinicopathological features and outcomes of 190 patients with FIGO stage IB-IIA cervical squamous cell carcinoma treated by surgery were collected and analyzed for factors associated with tumor recurrence. In addition to well-recognized pathological risk factors, the pathological characteristics of invasive margin (type of invasive pattern and degree of stromal desmoplasia and peritumoral inflammatory reaction) were also included in the analysis. Multiple scoring models were made by matching different clinicopathological variables and/or different weighting of the score for each variable. The model with the best performance in the prediction of recurrence and decreased survival was selected. Results: The model with the best performance was composed of a combined score of invasive pattern, lymphovascular space invasion (LVSI), and degree of inflammatory reaction and stromal desmoplasia (total score =10). Compared to those with score ${\leq}8$, the patients with score 9-10 had a significantly higher recurrence rate in the overall group (p<0.001) and the subgroup without adjuvant therapy (p<0.001), while the significance was marginal in the subgroup with adjuvant therapy (p=0.069). In addition, the patients with score 9-10 had a higher rate of tumor recurrence at distant sites (p=0.007). The disease-free survival was significantly lower in the patients with score 9-10 than those with score ${\leq}8$ among the overall patients (p<0.001), in the subgroup without adjuvant therapy (p<0.001), and the subgroup with adjuvant therapy (p=0.047). Conclusions: In this study, a prognostic model based on a combination of pathological characteristics of invasive margin and LVSI proved to be predictive of tumor recurrence and decreased disease-free survival in patients with early-stage cervical squamous cell carcinoma.

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.68-77
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• 2008

We have developed an inversion algorithm for loop-loop electromagnetic (EM) data, based on the localised non-linear or extended Born approximation to the solution of the 2.5D integral equation describing an EM scattering problem. Source and receiver configuration may be horizontal co-planar (HCP) or vertical co-planar (VCP). Both multi-frequency and multi-separation data can be incorporated. Our inversion code runs on a PC platform without heavy computational load. For the sake of stable and high-resolution performance of the inversion, we implemented an algorithm determining an optimum spatially varying Lagrangian multiplier as a function of sensitivity distribution, through parameter resolution matrix and Backus-Gilbert spread function analysis. Considering that the different source-receiver orientation characteristics cause inconsistent sensitivities to the resistivity structure in simultaneous inversion of HCP and VCP data, which affects the stability and resolution of the inversion result, we adapted a weighting scheme based on the variances of misfits between the measured and calculated datasets. The accuracy of the modelling code that we have developed has been proven over the frequency, conductivity, and geometric ranges typically used in a loop-loop EM system through comparison with 2.5D finite-element modelling results. We first applied the inversion to synthetic data, from a model with resistive as well as conductive inhomogeneities embedded in a homogeneous half-space, to validate its performance. Applying the inversion to field data and comparing the result with that of dc resistivity data, we conclude that the newly developed algorithm provides a reasonable image of the subsurface.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.1
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• pp.22-38
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• 2012

Adaptation of climate change is necessary to avoid unexpected impacts of climate change caused by human activities. Vulnerability refers to the degree to which system cannot cope with impacts of climate change, encompassing physical, social and economic aspects. Therefore the quantification of climate change impacts and its vulnerability is needed to identify vulnerable regions and to setup the proper strategies for adaptation. In this study, climate change vulnerability is defined as a function of climate exposure, sensitivity, and adaptive capacity. Also, we identified regions vulnerable to ozone due to climate change in Korea using developed proxy variables of vulnerability of regional level. 18 proxy variables are selected through delphi survey to assess vulnerability over human health sector for ozone concentration change due to climate change. Also, we estimate the weighting score of proxy variables from delphi survey. The results showed that the local regions with higher vulnerability index in the sector of human health are Seoul and Daegu, whereas regions with lower one are Jeollanam-do, Gyeonggi-do, Gwangju, Busan, Daejeon, and Gangwon-do. The regions of high level vulnerability are mainly caused by their high ozone exposure. We also assessed future vulnerability according to the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2, A1FI, A1T, A1B, B2, and B1 scenarios in 2020s, 2050s and 2100s. The results showed that vulnerability increased in all scenarios due to increased ozone concentrations. Especially vulnerability index is increased by approximately 2 times in A1FI scenarios in the 2020s. This study could support regionally adjusted adaptation polices and the quantitative background of policy priority as providing the information on the regional vulnerability of ozone due to climate change in Korea.

• Journal of Wetlands Research
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• v.7 no.4
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• pp.97-107
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• 2005

As the distributed model is developed and widely used, the accuracy of a rainfall measurement and more dense rainfall observation network are required for the reflection of various spatial properties. However, in reality, it is not easy to get the accurate data from dense network. Generally, we could not have the proper rainfall gages in space and even we have proper network for rainfall gages it is not easy to reflect the variations of rainfall in space and time. Often, we do also have missing rainfall data at the rainfall gage stations due to various reasons. We estimate the distribution of mean areal rainfall data from the point rainfalls. So, in the aspect of continuous rainfall property in time, we should fill the missing rainfall data then we can represent the spatial distribution of rainfall data. This study uses the Fuzzy-Genetic algorithm as a interpolation method for filling the missing rainfall data. We compare the Fuzzy-Genetic algorithm with arithmetic average method, inverse distance method, normal ratio method, and ratio of distance and elevation method which are widely used previously. As the results, the previous methods showed the accuracy of 70 to 80 % but the Fuzzy-Genetic algorithm showed that of 90 %. Especially, from the sensitivity analysis, we suggest the values of power in the equation for filling the missing data according to the distance and elevation.