• Korean Journal of Construction Engineering and Management
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• v.19 no.4
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• pp.93-101
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• 2018

A city is like a living organism that is born, grows and become extinct within an ecosystem. In recent years, more and more cities have been planned by designers rather than spontaneously growing over time. This planning means that if a city is not appropriately designed at the beginning, it is very hard to fix or adjust it later. A poor urban design inconveniences many people, and forces them to adjust to it. For this reason, it is important to design a city as optimally as possible at the design phase. One of the reasons why a city is not designed optimally is complexity. Previous urban design methods have attempted to resolve the complexity by using a top-down problem-solving method based on the experience and knowledge of the urban planner. However, such an approach does not have the organic characteristics of a bottom-up problem-solving method of an artificial life, based on the creation principle of the ecosystem. Therefore, in this study the general principle of artificial life, which can provide a solution to the bigger problems that accumulate as a result of the solutions to small units of problems, is adopted. This enables us to draw various urban design alternatives, and it proves that the alternatives, despite being drawn through a limited modeling method, have almost no differences from those designed by an expert, and its possibilities of future development has also been verified.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.55-71
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• 2013

The prediction model is the main factor affecting the performance of a knowledge-based system for bankruptcy prediction. Earlier studies on prediction modeling have focused on the building of a single best model using statistical and artificial intelligence techniques. However, since the mid-1980s, integration of multiple techniques (hybrid techniques) and, by extension, combinations of the outputs of several models (ensemble techniques) have, according to the experimental results, generally outperformed individual models. An ensemble is a technique that constructs a set of multiple models, combines their outputs, and produces one final prediction. The way in which the outputs of ensemble members are combined is one of the important issues affecting prediction accuracy. A variety of combination schemes have been proposed in order to improve prediction performance in ensembles. Each combination scheme has advantages and limitations, and can be influenced by domain and circumstance. Accordingly, decisions on the most appropriate combination scheme in a given domain and contingency are very difficult. This paper proposes a confidence-based selection approach as part of an ensemble bankruptcy-prediction scheme that can measure unified confidence, even if ensemble members produce different types of continuous-valued outputs. The present experimental results show that when varying the number of models to combine, according to the creation type of ensemble members, the proposed combination method offers the best performance in the ensemble having the largest number of models, even when compared with the methods most often employed in bankruptcy prediction.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.107-120
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• 2003

Over the decades, a lot of studies have dealt with the traffic characteristics and phenomena at a merging area. However, relatively few analytical techniques have been developed to evaluate the traffic flow at the area and, especially, the ramp merging capacity has rarely been. This study focused on the merging behaviors that were characterized by the relationship between the shoulder lane flow and the on-ramp flow, and modeled these behaviors to determine ramp merge capacity by using gap acceptance theory. In the process of building the model, both an ideal mergence and a forced mergence were considered when ramp-merging vehicles entered the gap provided by the flow of the shoulder lane. In addition, the model for the critical gap was proposed because the critical gap was the most influential factor to determine merging capacity in the developed models. The developed models showed that the merging capacity value was on the increase as the critical gap decreased and the shoulder lane volume increased. This study has a meaning of modeling the merging behaviors including the forced merging type to determine ramp merging capacity more precisely. The findings of this study would help analyze traffic phenomena and understand traffic behaviors at a merging area, and might be applicable to decide the primary parameters of on-ramp control by considering the effects of ramp merging flow.

• Journal of Korean Society of Transportation
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• v.33 no.6
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• pp.554-563
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• 2015

This study dealt with developing an accident model for rural signalized intersections with random parameter negative binomial method. The limitation of previous count models(especially, Poisson/Negative Binomial model) is not to explain the integrated variations in terms of time and the distinctive characters a specific point/segment has. This drawback of the traditional count models results in the underestimation of the standard error(t-value inflation) of the derived coefficient and finally affects the low-reliability of the whole model. To solve this problem, this study improves the limitation of traditional count models by suggesting the use of random parameter which takes account of heterogeneity of each point/segment. Through the analyses, it was found that the increase of traffic flow and pedestrian facilities on minor streets had positive effects on the increase of traffic accidents. Left turning lanes and median on major streets reduced the number of accidents. The analysis results show that the random parameter modeling is an effective method for investigating the influence on traffic accident from road geometries. However, this study could not analyze the effects of sequential changes of driving conditions including geometries and safety facilities.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5287-5294
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• 2016

Background: Breast cancer is a worldwide public health concern and is the most prevalent type of cancer in women in the United States. This study concerned the best fit of statistical probability models on the basis of survival times for nine state cancer registries: California, Connecticut, Georgia, Hawaii, Iowa, Michigan, New Mexico, Utah, and Washington. Materials and Methods: A probability random sampling method was applied to select and extract records of 2,000 breast cancer patients from the Surveillance Epidemiology and End Results (SEER) database for each of the nine state cancer registries used in this study. EasyFit software was utilized to identify the best probability models by using goodness of fit tests, and to estimate parameters for various statistical probability distributions that fit survival data. Results: Statistical analysis for the summary of statistics is reported for each of the states for the years 1973 to 2012. Kolmogorov-Smirnov, Anderson-Darling, and Chi-squared goodness of fit test values were used for survival data, the highest values of goodness of fit statistics being considered indicative of the best fit survival model for each state. Conclusions: It was found that California, Connecticut, Georgia, Iowa, New Mexico, and Washington followed the Burr probability distribution, while the Dagum probability distribution gave the best fit for Michigan and Utah, and Hawaii followed the Gamma probability distribution. These findings highlight differences between states through selected sociodemographic variables and also demonstrate probability modeling differences in breast cancer survival times. The results of this study can be used to guide healthcare providers and researchers for further investigations into social and environmental factors in order to reduce the occurrence of and mortality due to breast cancer.

• Journal of health informatics and statistics
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• v.42 no.4
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• pp.309-316
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• 2017

Objectives: Radon and its progeny pose environmental risks as a carcinogen, especially to the lungs. Investigating factors affecting indoor radon concentrations and models thereof are needed to prevent exposure to radon and to reduce indoor radon concentrations. The purpose of this study was to identify factors affecting indoor radon concentration and to construct a comprehensive model thereof. Methods: Questionnaires were administered to obtain data on residential environments, including building materials and life style. Decision tree and structural equation modeling were applied to predict residences at risk for higher radon concentrations and to develop the comprehensive model. Results: Greenery ratio, impermeable layer ratio, residence at ground level, daily ventilation, long-term heating, crack around the measuring device, and bedroom were significantly shown to be predictive factors of higher indoor radon concentrations. Daily ventilation reduced the probability of homes having indoor radon concentrations ${\geq}200Bq/m^3$ by 11.6%. Meanwhile, a greenery ratio ${\geq}65%$ without daily ventilation increased this probability by 15.3% compared to daily ventilation. The constructed model indicated greenery ratio and ventilation rate directly affecting indoor radon concentrations. Conclusions: Our model highlights the combined influences of geographical properties, groundwater, and lifestyle factors of an individual resident on indoor radon concentrations in Korea.

• Proceedings of the Korea Port Economic Association Conference
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• 2006.08a
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• pp.1-12
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• 2006

As national economies globalize, demand for intercontinental container shipping services is growing rapidly, providing a potential economic boon for the countries and communities that provide port services. On the promise of profits, many governments are investing heavily in port infrastructure, leading to a possible glut in port capacity, driving down prices for port services and eliminating profits as ports compete for business. Further, existing ports are making strategic investments to protect their market share, increasing the chance new ports will be overcapitalized and unprofitable. Governments and port researchers need a tool for understanding how local competition in their region will affect demand for port services at their location, and thus better assess the profitability of a prospective port. We propose to develop such a tool by extending our existing simulation model of global container traffic to incorporate demand-side shipper preferences and supply-side strategic responses by incumbent ports to changes in the global port network, including building new ports, scaling up existing ports, and unexpected port closures. We will estimate shipper preferences over routes, port attributes and port services based on US and international shipping data, and redesign the simulation model to maximize the shipper's revealed preference functions rather than simply minimize costs. As demand shifts, competing ports will adjust their pricing (short term) and infrastructure (long term) to remain competitive or defend market share, a reaction we will capture with a game theoretic model of local monopoly that will predict changes in port characteristics. The model's hypotheses will be tested in a controlled laboratory experiment tailored to local port competition in Asia, which will also serve to demonstrate the subtle game theoretic concepts of imperfect competition to a policy and industry audience. We will apply the simulation model to analyze changes in global container traffic in three scenarios: addition of a new large port in the US, extended closure of an existing large port in the US, and cooperative and competitive port infrastructure development among Korean partner countries in Asia.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.321-334
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• 2021

A fixed reflectivity-rainfall relationship approach, such as the Marshall-Palmer relationship, for an entire year and different seasons, can be problematic in cases where the relationship varies spatially and temporally throughout a region. From this perspective, this study explores the use of long-term radar reflectivity for South Korea to obtain a nationwide calibrated Z-R relationship and the associated uncertainties within a Bayesian inference framework. A calibrated spatially structured pattern in the parameters exists, particularly for the wet season and parameter for the dry season. A pronounced region of high values during the wet and dry seasons may be partially associated with storm movements in that season. Overall, the radar rainfall fields based on the proposed modeling procedure are similar to the observed rainfall fields. In contrast, the radar rainfall fields obtained from the existing Marshall-Palmer relationship show a systematic underestimation. In the event of high impact weather, it is expected that the value of national radar resources can be improved by establishing an active watershed-level hydrological analysis system.

• Korea Science and Art Forum
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• v.37 no.2
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• pp.101-112
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• 2019

Regardless of the size, the role and meaning of the space required for human daily life are the same. Especially, as the spatial design is small and the size is small, the careful design and problem solving are needed to enable comfortable and convenient life even in a narrow space. The purpose of this study is to design a convergence model that utilizes the advantages of BIM, which can simulate actual design based on a new one-person housing space design plan optimized for one person. This study applied the BIM design technology to one-person housing 2D design, and the suitability examination and the space optimization design of the interior design were carried out. As a result of the study, utility of space improvement, consideration of housing environment, interference check, application of eco-friendly housing system, and MEP design item were derived. Therefore, BIM space design in interior space has been confirmed as a way to overcome limit and inefficiency of 2D design which is applied to actual space by various space design elements. Based on the results of this study, the One-person housing space model, which is applied to the study, is a pure creation designed based on various one-person housing of social and cultural peculiarities derived from previous research. This design example was applied to BIM technology to confirm the detailed and practical design possibility.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.773-784
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• 2019

With the recent development of 4th industrial revolution technology, BIM information systems are spreading to civil engineering fields as a link to this technology. Accordingly, the Land, Infrastructure and Transport Ministry is announcing a technical policy to introduce the BIM information system into the construction sector from 2020. Usually, SOC-related facilities are complex, making it difficult to implement BIM without a standards framework. To overcome these problems, it is urgent to develop a BIM standard classification system. In this study, the BIM property classification system was developed to link the previously developed object classification system by analyzing domestic and foreign prior studies and working standards. This includes property information of businesses, facilities, parts of facilities and components that correspond to the level of object composition in the road and river sectors. It also suggested ways to apply expansion to various SOC areas and to organize spatial information by facility. The results of this study were applied to road facilities to verify the possibility of information building. The development of the BIM Standards Classification System through this R&D will contribute to the development of construction IT by providing conditions for convenient modeling and information system.