• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.3
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• pp.103-113
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• 2018

Tide-surge characteristics of the West/South domestic coasts were analyzed with a tool of EST (empirical simulation technique). As a result, stations of Incheon, Gunsan, Mokpo and Busan are categorized as tide-dominant coasts, while Yeosu, Tongyoung and Busan are as surge-dominant coasts. In the tide-dominant coasts, extreme sea level of less than 50-yr frequency is formed without typhoon-surge, while only 10-yr extreme sea level is formed in the surge-dominant coasts. As the results of casual condition of extreme sea level formation considering the relative degree of surge on tide, the regional characteristics were detected also. Three methods for estimating the design tide level were compared. The AHHW method shows an unrealistic outcomes of the concern of over estimate design. Furthermore, the probability distribution function method has been concerned as causing missing data if a huge typhoon occurs in a neap tide or a low tide. To cope with these drawbacks, the applicability of the EST method is proved to be suitable especially in tide-dominant coasts.

• 한국사회정책
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• v.24 no.1
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• pp.1-31
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• 2017

This paper attempts to analyze citizens' giving behavior by household income level. Particularly, it focuses on participation and amount of secular giving by using 'Social Survey'in 2011, 2013, and 2015 from the Bureau of Statistics and employing Heckman selection model for statistical analysis. This study shows that citizens' participation has a proportional tendency by their income level. Similar to participation of secular giving, citizens' giving amount has also a proportional tendency by their income level. However, the degree of proportional tendency seems not to be significant in the case of amount of secular giving. This empirical analysis promotes understanding of participation and amount of secular giving by citizens' income section in Korea by showing the differences. This paper provides meaningful empirical understanding regarding citizens' secular giving behavior by their income level. In addition, it offers important clues to motivate relevant prospective studies and develop social agenda which contribute to strengthening giving culture in Korea.

• Korean Journal of Environment and Ecology
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• v.37 no.6
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• pp.499-507
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• 2023

This study conducted an empirical analysis on a land purchase requisition policy in Bukhansan National Park to draw the efficacy, limitations and implications of this policy. A logistic regression analysis was conducted to identify factors that affected the landowners' decision on applying for land purchase requisition using the government's records on acquisition of private lands in the park since 2006 when this policy began to be implemented. Results illustrate that the probability that a landowner applied for purchase requisition increased if the land was classified as forest, if a large proportion of the land was designated as the nature conservation district, if it was located farther from park boundary, and if it had higher appraised value per square meter. These results indicate that as the landowners had less chance to utilize their lands, they more likely apply for purchase requisition. These results also imply that the government can achieve a high conservation performance level if private lands are acquire by the land acquisition requisition policy. The logistic regression model also predict that 401m² of the private lands in Bukhansan National Park will likely be purchase-requested in future. Despites its usefulness in mitigating landowners' complaints in national parks, the land purchase requisition policy has not been widely utilized. Based on these empirical results, this study provides policy implications to facilitate the ulitization of this policy.

• Geotechnical Engineering
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• v.13 no.6
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• pp.107-122
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• 1997

This paper presents a ground surface settlement prediction method for shield tunneling in cohesive soils. In order to develop the method, a parametric study on shield tunneling was performed by using a threetimensional elasto-plastic finite element analysis, which can simulate the construction procedure. By using the results of the finite element analysis, the ground movement mechanism was investigated and a base which relates the ground surface settlement and iuluencing factors was formed. The data base was then used to formulate semi -empirical equations for both surface settlement ratio above tunnel face and imflection point by means of a regression analysis. Furthermore, a prediction method for transverse and longitudinal surface settlement profiles was suggested by using the leveloped equations in conjunction with the normal probability curve. Effectiveness of the developed method was illustrated by comparing settlement profiles obtained by using the developed method with the results of finite element analysis and measured data. Based on the comparison, it was concluded that the developed method can be effectively rosed for practical applications at least within the conditions investigated.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.1-9
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• 2016

In accordance with the increased political and social utilization of social media, demands on online trend analysis and monitoring technologies based on social bigdata are also increasing rapidly. In this paper, we define 'risk' as issues which have probability of turn to negative public opinion among big social issues and classify their types in details. To define risk types, we conduct a complete survey on news documents and analyzed characteristics according to issue domains. We also investigate cross-medias analysis to find out how different public media and personalized social media. At the result, we define 58 risk types for 6 domains and developed automatic classification model based on machine learning algorithm. Based on empirical experiments, we prove the possibility of automatic detection for social issue risk in social media.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.253-268
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• 2011

In this paper, we estimate systematic risk from credit migration (or transition) matrices under "Asymptotic Single Risk Factor" model. We analyzed transition matrices issued by KR(Korea Ratings) and concluded that systematic risk implied on credit migration somewhat coincide with the real economic cycle. Especially, we found that systematic risk implied on credit migration is better than that implied on the default rate. We also emphasize how to conduct a stress test using systematic risk extracted from transition migration. We argue that the proposed method in this paper is better than the usual method that is only considered for the conditional probability of default(PD). We found that the expected loss critically increased when we explicitly consider the change of credit quality in a given portfolio, compared to the method considering only PD.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.438-448
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• 2011

The purpose of this paper is to enrich storytelling contents for culture and tourism industry and provide the implication for carrying out governmental policy by estimating economic value of storytelling using a Contingent Valuation Method. The empirical result shows that the economic value of storytelling development in culture and tourism industry is annually estimated 16,000 won per person, resulting from logit model and WTP mean method. The willingness-to-pay, degree of support and perception of the policy and culture contents expenditure have meaningful effects on probability of supporting and participating in execution of the policy. The findings imply that the economic value of storytelling development highly increases as the interest and expenditure of culture contents increase. Futhermore, informing storytelling related policy and business to the people will increase economic value of fostering storytelling-based culture and tourism.

• Journal of Educational Research in Mathematics
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• v.25 no.3
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• pp.323-345
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• 2015

This study examined the types of abduction appeared in the exploration activities of 'law of large numbers' in order to figure out relation between statistical reasoning and abduction. When the classroom discourse of students was analyzed by Peirce's abduction, Eco's abduction type and Toulmin's argument pattern, students used overcoded abduction the most in the discourse of abduction. However, there composed a low percent of undercoded abduction leading to various thinking, and creative abduction used to make new principles or theories. By the CAS calculators used in the process of reasoning, students were provided with empirical context to understand the concept of abstract probability, through which they actively participated in the argumentation centered on the reasoning. As a result, it was found that not only to understand the abduction, but to build statistical context with tools in the learning of statistical reasoning is important.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.43-49
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• 2015

The aim of this study was to model unusual association with declarative knowledge by positive affect using ACT-R cognitive architecture. Existing research related with cognitive modeling tends to pay a lot of attention to strong and negative cognitive moderator. Mild positive affect, however, has far-reaching effects on problem solving and decision making. Typically, subjects with positive affect were more likely to respond to unusual associates in a word association task than subjects with neutral affect. In this study, a cognitive model using ACT-R cognitive architecture was developed to show the effect of positive affect on the cognitive organization related with memory. First, we organized the memory structure of stimulus word 'palm' based on published results in a word association task. Then, we decreased an ACT-R parameter that reflects the amount of weighting given to the dissimilarity between the stimulus word and the associate word to represent reorganized memory structure of the model by positive affect. As a result, no significant associate probability difference between model prediction and existing empirical data was found. The ACT-R cognitive architecture could be used to model the effect of positive affect on the unusual association by decreasing (manipulating) the weight of the dissimilarity. This study is useful in conducting model-based evaluation of the effects of positive affect in complex tasks involving memory, such as creative problem solving.