• Economic and Environmental Geology
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• v.38 no.1
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• pp.45-55
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• 2005

Traditional GIS-based probabilistic spatial data integration models for landslide susceptibility analysis have failed to provide the theoretical backgrounds and effective methods for integration of different types of spatial data such as categorical and continuous data. This paper applies two spatial data integration models including non-parametric empirical estimation and parametric predictive discriminant analysis models that can directly use the original continuous data within a likelihood ratio framework. Similarity rates and a prediction rate curve are computed to quantitatively compare those two models. To illustrate the proposed models, two case studies from the Jangheung and Boeun areas were carried out and analyzed. As a result of the Jangheung case study, two models showed similar prediction capabilities. On the other hand, in the Boeun area, the parametric predictive discriminant analysis model showed the better prediction capability than that from the non-parametric empirical estimation model. In conclusion, the proposed models could effectively integrate the continuous data for landslide susceptibility analysis and more case studies should be carried out to support the results from the case studies, since each model has a distinctive feature in continuous data representation.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1229-1238
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• 2018

We examined if a state of sea-ice in Bering Sea acts as a prelude of variation in that of Chukchi Sea by using satellites-based Arctic sea-ice concentration time series. Datasets consist of monthly values of sea-ice concentration during 36 years (1982-2017). Time series analysis armed with Transfer entropy is performed to describe how sea-ice data in Chukchi Sea is affected by that in Bering Sea, and to explain the relationship. The transfer entropy is a measure which identifies a nonlinear coupling between two random variables or signals and estimates causality using modification of time delay. We verified this measure checked a nonlinear coupling for simulated signals. With sea-ice concentration datasets, we found that sea-ice in Bering Sea is influenced by that in Chukchi Sea 3, 5, 6 months ago through the transfer entropy measure suitable for nonlinear system. Particularly, when a sea-ice concentration of Bering Sea has a local minimum, sea ice concentration around Chukchi Sea tends to decline 5 months later with about 70% chance. This finding is considered to be a process that inflow of Pacific water through Bering strait reduces sea-ice in Chukchi Sea after lowering the concentration of sea-ice in Bering Sea. This approach based on information theory will continue to investigate a timing and time scale of interesting patterns, and thus, a coupling inherent in sea-ice concentration of two remote areas will be verified by studying ocean-atmosphere patterns or events in the period.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.95-103
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• 2022

This study aims to understand a gamer participatory mechanism by comparing Gamer Participation 1.0(Bartz Liberation War) and Gamer Participation 2.0(Truck Demonstration). The process of gamers' political participation is analyzed by applying the communication-mediated O-S-O-R model with the case of gamers' truck protests caused by probability items' issue. This study found out that changes in the social, technological, and discursive layers that constitute the gamer's communication ecology led to diversification of communication channels and changes in the perception of games. Gamers utilized the technological layer of the media environment that presupposes immediate mutual communication, expressed opinions on issues in the mobilization process, and shared the necessity of participation to derive collective mobilization. Through communication, gamers were able to participate in socio-political issues with high participation thresholds. This study is significant in that it discussed the gamers' democratic citizenship and role as issue publics. The study suggests that the need for theoretical and methodological expansion to analyze various participatory cases.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.333-343
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• 2022

For water resource management, the design flood is calculated using the flood frequency analysis technique and the rainfall runoff model. The method by design flood frequency analysis calculates the stochastic design flood by directly analyzing the actual discharge data and is theoretically evaluated as the most accurate method. Actual discharge data frequency analysis of the measured flow was limited due to data limitations in the existing flood flow analysis. In this study, design flood frequency analysis was performed using the measured flow data stably secured through the water level-discharge relationship curve formula. For the frequency analysis of design flood, the parameters were calculated by applying the bayesian inference, and the uncertainty of flood volume by frequency was quantified. It was confirmed that the result of calculating the design flood was close to that calculated by the rainfall-runoff model by applying long-term rainfall data. It is judged that hydrological analysis can be done from various perspectives by using long-term actual flow data through hydrological survey.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.129-141
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• 2023

This study analyzes the dynamic characteristics of daily freight rates of dry bulk and tanker shipping markets and their forecasting accuracy by using the error correction models. In order to calculate the error terms from the co-integrated time series, this study uses the common stochastic trend model (CSTM model) and vector error correction model (VECM model). First, the error correction model using the error term from the CSTM model yields more appropriate results of adjustment speed coefficient than one using the error term from the VECM model. Furthermore, according to the adjusted determination coefficients (adjR²), the error correction model of CSTM-model error term shows more model fitness than that of VECM-model error term. Second, according to the criteria of mean absolute error (MAE) and mean absolute scaled error (MASE) which measure the forecasting accuracy, the results show that the error correction model with CSTM-model error term produces more accurate forecasts than that of VECM-model error term in the 12 cases among the total 15 cases. This study proposes the analysis and forecast tasks 1) using both of the CSTM-model and VECM-model error terms at the same time and 2) incorporating additional data of commodity and energy markets, and 3) differentiating the adjustment speed coefficients based the sign of the error term as the future research topics.

• Geotechnical Engineering
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• v.7 no.3
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• pp.21-32
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• 1991

The purpose of this paper is to develop a reliability model for slope stability of Earth-rockfill dams which accounts for all uncertainties encountered. The uncertain factors of the design variables include the cohesion, the angle of internal friction, and the porewater Pressure in each zone. More specifically, the model errors in estimating those variables are studied in depth. To reduce the uncertainties due to model errors, updated design variables are obtained using Bayesian Theory. For stability analysis, both the two-dimesional stability analysis and the three-dimensional stability analysis where the end effects and the system reliability concept are considered are used for the reliability calculations. The deterministic safety factor by the three-dimensional analysis is lager than that by the two-dimensional anlysis. However, the probability of failure by the three-dimensional analysis is about 3.5 times larger that by the two-dimensional analysis. It is because the system reliability concept is used in the three-dimensional analysis. The sensitivity analysis shows that the probability of failure is more sensitive to the uncertainty of the cohesion than that of the angle of internal friction.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.329-347
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• 2017

Early research into category-based feature inference reported various phenomena in human thinking including typicality, diversity, similarity effects, etc. Later research discovered that participants' prior knowledge has an extensive influence on these sorts of reasoning. The current research tested the effects of causal knowledge on feature inference and conducted modeling on the results. Participants performed feature inference for categories consisted of four features where the features were connected either in common cause or common effect structure. The results showed typicality effects along with violations of causal Markov condition in common cause structure and causal discounting in common effect structure. To model the results, it was assumed that participants perform feature inference based on the difference between the probabilities of an exemplar with the target feature and an exemplar without the target feature (that is, $p(E_{F(X)}{\mid}Cat)-p(E_{F({\sim}X)}{\mid}Cat)$). Exemplar probabilities were computed based on causal model theory (Rehder, 2003) and applied to inference for target features. The results showed that the model predicts not only typicality effects but also violations of causal Markov condition and causal discounting observed in participants' data.

• Archives of design research
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• v.18 no.1 s.59
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• pp.49-58
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• 2005

Focusing on the information sender, message, channel, and receiver, the existing information theory deals with the noise, information contents, and probability of choice, which involve in the process of information transmission. In the current digital environment, besides simply conveying information itself through media, the important issue is how to efficiently convey information. Therefore, we need to analyze the theory in different perspective, and to research the Information redundancy for the methodology of information design. The redundancy causes the receiver to have attraction to the information and to reduce its contents due to its supplement and repetition. So it can play a role of efficient communication method. The concept of redundancy is applied to the communication of art such as literature, architecture, painting, and design to accomplish efficient communication. In order to get persuasive information design for the receiver's perspective we need to make use of this concept. The redundancy can be applied with the technical aspect of multimedia and Interaction, which add supplemental expression, or sort of event for the receiver's experience and memory. In the process of constructing information it can be applied with the structure of gaming redundancy, entropy, the accumulating communication code using entertaining feature, and storytelling methodology. The noise and entropy could be used for the means of making redundancy, not the obstacle to information. The redundancy gives the receiver attraction on the information and makes them have strong will of interpreting it so that the purpose of conveying information will be accomplished efficiently.

• Geotechnical Engineering
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• v.11 no.1
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• pp.9-22
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• 1995

The purpose of this study is to propose safety factors of pile bearing capacity based on the reliability analysis. Each prediction method involves various degrees of uncertainties. To account for these uncertainties in a systematic way, the ratios of the measured bearing capacity from pile load tests to the predicted bearing capacity are represented in the form of a probability density function. The safety factor for each design method is obtained so that the probability of pile foundation failure is less than 10-3. The Bayesian theorem is applied in a way that the distribution using static formulae is assumed to be the A-prior and the distribution using dynamic formulae or wave equation based methods is assumed to be the likelihood, and these two are combined to obtain the posterior which has the reduced uncertainty. The results of this study show that static formulae of the pile bearing capacity using the 5.p.7. N-value as well as dynamic formulae are highly unreliable and have to have the safety factor more than 7.4 : the wave equation analysis using PDA(Pile Driving Analyzer) system the most reliable with the safety factor close to 2.7. The safety factor could be reduced certain amount by adoption the Bayes methodology in pile design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.509-516
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• 2020

Since the 1960s, many rivers have been polluted and destroyed due to river repair projects for economic development and the covering of small rivers due to urbanization. Many studies have analyzed rivers using measured river topographic factors, but surveying is not easy when the flow rate changes rapidly, such as during a flood. In addition, the previous research has been mainly about the cross section of a river, so information on the longitudinal profile is insufficient. This research used informational entropy theory to obtain an equation that can calculate the average river slope, river slope, and river longitudinal elevation for a river basin in real time. The applicability was analyzed through comparison with measured data of a river's characteristic factors obtained from a river plan. The parameters were calculated using informational entropy theory, nonlinear regression analysis, and actual data. The longitudinal elevation entropy equation for each stream was then calculated, and so was the average river slope. All of the values were over 0.96, so it seems that reliable results can be obtained when calculating river characteristic factors.