• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.47-56
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• 2004

The purpose of this study is to estimate soil loss amount according to the rainfall-runoff erosivity factor frequency and to analyze the hazard zone that has high possibilities of soil erosion in the watershed. RUSLE was used to analyze soil loss quantity. The study area is Gwanchon that is part of Seomjin river basin. To obtain the frequency rainfall-runoff erosivity factor, the daily maximum rainfall data for 39 years was used. The probability rainfall was calculated by using the Normal distribution, Log-normal distribution, Pearson type III distribution, Log-Pearson type III distribution and Extreme-I distribution. Log-Pearson type III was considered to be the most accurate of all, and used to estimate 24 hours probabilistic rainfall, and the rainfall-runoff erosivity factor by frequency was estimated by adapting the Huff distribution ratio. As a result of estimating soil erosion quantity, the average soil quantity shows 12.8 and $68.0ton/ha{\cdot}yr$, respectively from 2 years to 200 years frequency. The distribution of soil loss quantity within a watershed was classified into 4 classes, and the hazard zone that has high possibilities of soil erosion was analyzed on the basis of these 4 classes. The hazard zone represents class IV. The land use area of class IV shows $0.01-5.28km^2$, it ranges 0.02-9.06% of total farming area. Especially, in the case of a frequency of 200 years, the field area occupies 77.1% of total fanning area. Accordingly, it is considered that soil loss can be influenced by land cover and cultivation practices.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.99-118
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• 2012

The aim of this study is to define a correlation between spatial distribution characteristics of FFG(Functional Feeding Groups) of aquatic insects and related environmental factors in the Geum River based on the theory of RCC(River Continuum Concept). For that objective we had used SMRA(Stepwise Multiple Regression Analysis) method to analyze close relationship between the distribution of aquatic insects and the physical and chemical factors that may affect their inhabiting environment in the study area. And then, a probabilistic method named Frequency Ratio Model(FRM) and spatial analysis function of GIS were applied to produce a predictive distribution map of biota community considering their distribution characteristics according to the environmental factors as related variables. As a result of SMRA, the values of decision coefficient for factors of elevation, stream width, flow velocity, conductivity, temperature and percentage of sand showed higher than 0.5. Therefore these 6 environmental factors were considered as major factors that might affect the distribution characteristics of aquatic insects. Finally, we had calculated RMSE(Root Mean Square Error) between the predicted distribution map and prior survey database from other researches to verify the result of this study. The values of RMSE were calculated from 0.1892 to 0.4242 according to each FFG so we could find out a high reliability of this study. The results of this study might be used to develop a new estimation method for aquatic ecosystem with macro invertebrate community and also be used as preliminary data for conservation and restoration of stream habitats.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.671-683
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• 2018

The flood damage caused by heavy rains in urban watershed is increasing, and, as evidenced by many previous studies, urban flooding usually exceeds the water capacity of drainage networks. The flood on the area which considerably urbanized and densely populated cause serious social and economic damage. To solve this problem, deterministic and probabilistic studies have been conducted for the prediction flooding in urban areas. However, it is insufficient to obtain lead times and to derive the prediction results for the flood volume in a short period of time. In this study, IDNN, TDNN and NARX were compared for real-time flood prediction based on urban runoff analysis to present the optimal real-time urban flood prediction technique. As a result of the flood prediction with rainfall event of 2010 and 2011 in Gangnam area, the Nash efficiency coefficient of the input delay artificial neural network, the time delay neural network and nonlinear autoregressive network with exogenous inputs are 0.86, 0.92, 0.99 and 0.53, 0.41, 0.98 respectively. Comparing with the result of the error analysis on the predicted result, it is revealed that the use of nonlinear autoregressive network with exogenous inputs must be appropriate for the establishment of urban flood response system in the future.

• Design Convergence Study
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• v.15 no.6
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• pp.195-214
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• 2016

Predictive analysis is based on a probabilistic learning algorithm called pattern recognition or machine learning. Therefore, if users want to extract more information from the data, they are required high statistical knowledge. In addition, it is difficult to find out data pattern and characteristics of the data. This study conducted statistical data analyses and visual data analyses to supplement prediction analysis's weakness. Through this study, we could find some implications that haven't been found in the previous studies. First, we could find data pattern when adjust data selection according as splitting criteria for the decision tree method. Second, we could find what type of data included in the final prediction model. We found some implications that haven't been found in the previous studies from the results of statistical and visual analyses. In statistical analysis we found relation among the multivariable and deducted prediction model to predict high box office performance. In visualization analysis we proposed visual analysis method with various interactive functions. Finally through this study we verified final prediction model and suggested analysis method extract variety of information from the data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.645-654
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• 2014

PMS (Pavement Management System) of National highways in Korea has used HDM (Highway Development and Management)-4 developed by World Bank for decision-making for maintenance and rehabilitation of pavements. However using HDM-4 is not appropriate in Korea because HDM-4 requires excessive input factors for analysis and economic analysis models loaded in HDM-4 are not suitable for Korean circumstances. Thus this study aims development of decision-making system for effective pavement management with reflecting Korean circumstances. Moreover this study proposed to define component of system, deterioration models, and basic units for component, and to analyze characteristics of component of system, and also to develop optimal decision-making system. The decision-making system for PMS mainly consists of 1) DB of highways, traffics, and socio-economic index, 2) pavement deterioration model, 3) speed prediction models by pavement conditions, 4) economic evaluation models, and 5) decision-making supporting system. Also this study provided analysis results in case studies for system verifications. However pavement deterioration models considering future probabilistic characteristic and index of decision-making are needed to develop for a further study.

• Journal of Educational Research in Mathematics
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• v.20 no.2
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• pp.163-183
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• 2010

It has long been of controversy what the meanings of probability is. And a century has past after the mathematical probability has been at the center of the school curriculum of it. Recently statistical meaning of probability becomes important for various reasons. However the simple modification of its definition is not enough. The computational reasoning of the probability and its practical application needs didactical changes and new instructional transformations along with the modification of it. Most of the current text books introduce probability as a limit of the relative frequencies, a statistical probability. But when the probability computation of the union of two events, or of the simultaneous events is faced on, they use mathematical probability for explanation and practices. Accordingly there is a gap for students in understanding those. Probability is an intuitive concept as far as it belongs to the domain of the experiential frequency. And frequency distribution must be the instructional bases for the (statistical) probability novices. This is what we mean by the probability in accordance with the distribution concepts. First of all, in order to explain the probability of the complementary event we should explain the empirical relative frequency of it first. These are the case for the union of two events and for the simultaneous events. Moreover we need to provide a logic of probabilistic guesses, inferences and decision, which we introduce with the name “the likelihood principle”, the most famous statistical principle. We emphasized this be done through the problems of practical decision making.

• Management & Information Systems Review
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• v.34 no.5
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• pp.71-92
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• 2015

This study analyzes the impact of Corporate Social Responsibility (CSR) activities on financial performances using Bayesian Network. The research tries to overcome the issues of the uniform assumption of a linear function between financial performance and CSR activities in multiple regression analysis widely used in previous studies. It is required to infer a causal relationship between activities of CSR which have an impact on the financial performances. Identifying the relationship would empower the firms to improve their financial performance by informing the decision makers about the different CSR activities that influence the financial performance of the firms. This research proposes General Bayesian Network (GBN) and presents Markov Blanket induced from GBN. It is empirically demonstrated that all the proposals presented in this study are statistically significant by the results of the research conducted by Korean Economic Justice Institute (KEJI) under Citizen's Coalition for Economic Justice (CCEJ) which investigated approximately 200 companies in Korea based on Korean Economic Justice Institute Index (KEJI index) from 2005 to 2011. The Bayesian Network to effectively infer the properties affecting financial performances through the probabilistic causal relationship. Moreover, I found that there is a causal relationship among CSR activities variable; that is Environment protection is related to Customer protection, Employee satisfaction, and firm size; Soundness is related to Total CSR Evaluation Score, Debt-Assets Ratio. Though the what-if analysis, I suggest to the sensitive factor among the explanatory variables.

• Journal of Educational Research in Mathematics
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• v.26 no.4
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• pp.635-662
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• 2016

Combinatorics, the basis of probabilistic thinking, is an important area of mathematics and closely linked with other subjects such as informatics and STEAM areas. But combinatorics is one of the most difficult units in school mathematics for leaning and teaching. This study, using the designed combinatorial models and executable expression, aims to analyzes the eye movement of graduate students when they translate the written combinatorial problems to the corresponding executable expression, and examines not only the understanding process of the written combinatorial sentences but also the degree of difficulties depending on the combinatorial semantic structures. The result of the study shows that there are two types of solving process the participants take when they solve the problems : one is to choose the right executable expression by comparing the sentence and the executable expression frequently. The other approach is to find the corresponding executable expression after they derive the suitable mental model by translating the combinatorial sentence. We found the cognitive processing patterns of the participants how they pay attention to words and numbers related to the essential informations hidden in the sentence. Also we found that the student's eyes rest upon the essential combinatorial sentences and executable expressions longer and they perform the complicated cognitive handling process such as comparing the written sentence with executable expressions when they try the problems whose meaning structure is rarely used in the school mathematics. The data of eye movement provide meaningful information for analyzing the cognitive process related to the solving process of the participants.

• Earthquakes and Structures
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• v.2 no.3
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• pp.207-232
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• 2011

The development of reliable earthquake mitigation plans and seismic risk management procedures can only be based on the establishment of comprehensive earthquake hazard and loss scenarios. Two cities, Grevena (Greece) and D$\ddot{u}$zce (Turkey), were used as case studies in order to apply a comprehensive methodology for the vulnerability and loss assessment of lifelines. The methodology has the following distinctive phases: detailed inventory, identification of the typology of each component and system, evaluation of the probabilistic seismic hazard, geotechnical zonation, ground response analysis and estimation of the spatial distribution of seismic motion for different seismic scenarios, vulnerability analysis of the exposed elements at risk. Estimating adequate earthquake scenarios for different mean return periods, and selecting appropriate vulnerability functions, expected damages of the water and waste water systems in D$\ddot{u}$zce and of the roadway network and waste water system of Grevena are estimated and discussed; comparisons with observed earthquake damages are also made in the case of D$\ddot{u}$zce, proving the reliability and the efficiency of the proposed methodology. The results of the present study constitute a sound basis for the development of efficient loss scenarios for lifelines and infrastructure facilities in seismic prone areas. The first part of this paper, concerning the estimation of the seismic ground motions, has been utilized in the companion paper by Kappos et al. (2010) in the same journal.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.13 no.1
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• pp.1-10
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• 2015

In the safety assessment of the geological disposal system of the radioactive wastes, the abnormal scenarios, in which the system is impacted by the abnormal events, need to be considered in addition to the reference scenario. In this study, characterization and prediction of well intrusion as one of the abnormal events which will impact the disposal system were conducted probabilistically and statistically for the safety assessment. The domestic well development data were analyzed, and the prediction methodologies of the well intrusion were suggested with a computation example. From the results, the annual well development rate per unit area in Korea was about 0.8 well/yr/km² in the conservative point of view. Considering the area of the overall disposal system which is about 1.5 km², the annual well development rate within the disposal system could be 1.2 well/yr. That is, it could be expected that more than one well would be installed within the disposal system every year after the institutional management period. From the statistical analysis, the probabilistic distribution of the well depth followed the log-normal distribution with 3.0363 m of mean value and 1.1467 m of standard deviation. This study will be followed by the study about the impacts of the well intrusion on the geological disposal system, and the both studies will contribute to the increased reliability of safety assessment.