• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.95-101
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• 2011

This study proposes the accident estimation model developed based on the time-series cross-sectional data at 50 intersections in Cheongju. The data were collected repeatedly and accumulated from 2004 to 2007. This study focused on deriving the optimal among the various models including TSCSREG(Time Series Cross Section Regression). Four different models utilizing various elements affecting accidents were developed. Through a statistical test, it was found that the t values of independent variables of the fixed effect models were less than those of the random effect models. Two variables were then found to be positive to the accidents: the number of crosswalks at an intersection and the number of intersections.

• Journal of Distribution Science
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• v.18 no.2
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• pp.59-67
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• 2020

Purpose: This study examines the relationship between formation of employment subcenters and regional industrial structures in Incheon. Research design, data, and methodology: We used the five-year panel data from 2012 to 2016 in 146 basic municipal units of Incheon to analyze panel regression models. Gross employment density and employment to population ratio were used as indicators of employment subcenters formation. The entropy index and Hachman index were used for analyzing the diversity and heterogeneity of industrial structures. Result: The analyses of two panel regression models showed that for the formation of employment subcenters, both the Entropy and Hachman index were significantly negative in most models. But tertiary industry was shown to have a significant positive relationship in all models. In the wholesale and retail sector, it was found that the average number of employees in the employment subcenters is significantly higher than that in the non-employment subcenters. Conclusions: The specialization of the industrial structure rather than the diversification contributes to the formation of the employment subcenters in Incheon. In particular, it can be considered that the wholesale and retail sector plays a very important role in forming the employment subcenters in many areas of Incheon.

• Journal of the Korean Wood Science and Technology
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• v.30 no.3
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• pp.18-25
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• 2002

Research to discuss the fire performance of materials requires tools for measuring their burning characteristics and validated fire growth models to predict fire behavior of the materials under specific tire scenarios using the measured properties as input for the models. In this study, burning characteristics such as time to ignition, weight loss rate, flame spread, heat release rate, total heat evolved, and effective heat of combustion for four types of wood-based materials were evaluated using the cone calorimeter and inclined panel tests. Time to ignition was affected by not only surface condition and specific gravity of the tested materials but also the type and magnitude of heat source. Results of weight loss rate, measured by inclined panel tests, indicated that heat transfer from the contacted flame used as the heat source into the inner part of the specimen was inversely proportional to specific gravity of material. Flame spread was closely related with ignition time at the near part of burning zone. Under constant and severe external heat flux, there was little difference in weight loss rate and total heat evolved between four types of wood-based panels. More applied heat flux caused by longer ignition time induced a higher first peak value of heat release rate. Burning characteristics data measured in this study can be used effectively as input for fire growth models to predict the fire behavior of materials under specific fire scenarios.

• Asian Journal of Atmospheric Environment
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• v.11 no.3
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• pp.194-201
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• 2017

This study investigates the factors that affect China's air pollution using city-level panel data and spatial econometric models. We address three air pollutants ($PM_{10}$, $SO_2$, and $NO_2$) present in 30 cities in China between 2004-2012 using global OLS and spatial models. To develop the spatial econometric analysis, we create a spatial weights matrix to define spatial patterns based on two neighborhood criteria - the queen contiguity and k nearest neighbors. The results show that the estimated coefficients are relatively consistent across different spatial weight criteria. The OLS models indicate that the effect of green spaces is statistically significant in decreasing the concentrations of all air pollutants. In the $PM_{10}$ and $SO_2$ analyses, the OLS models find that the number of buses and population density are also positively related to a reduction in the concentration of air pollutants. In addition, an increase in the temperature and the presence of secondary industries increase $SO_2$ and $NO_2$ concentrations, respectively. All spatial models capture a positive and significant effect of green spaces on reducing the concentration of each air pollutant. Our results suggest that green spaces in cities should receive priority consideration in local planning aimed at sustainable development. Furthermore, policymakers need to be able to discern the differences among pollutants when establishing environmental policies.

• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.103-113
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• 2014

This study designed and implemented a query model for consecutive analyses of dynamic multivariate graph data. First, the query model consists of two procedures; setting the discriminant function, and determining an alteration method. Second, the query model was implemented as a query system that consists of a query panel, a graph visualization panel, and a property panel. A Node-Link Diagram and the Force-Directed Graph Drawing algorithm were used for the visualization of the graph. The results of the queries are visually presented through the graph visualization panel. Finally, this study used the data of worldwide import & export data of small arms to verify our model. The significance of this research is in the fact that, through the model which is able to conduct consecutive analyses on dynamic graph data, it helps overcome the limitations of previous models which can only perform discrete analysis on dynamic data. This research is expected to contribute to future studies such as online decision making and complex network analysis, that use dynamic graph models.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.521-529
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• 2013

The acceptance of the test of the homogeneity for panel time series models allows for the pooling of the series to achieve parsimony. In this paper, we introduce a panel bilinear time series model as well as derive the stationary condition and the limiting distribution of the test statistic of the homogeneity test for the model. For the applications study, we use Korea Mumps data from January 2001 to December 2008. Finally, we perform test of homogeneity for the panel data with 8 independent bilinear time series.

• Journal of Energy Engineering
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• v.23 no.3
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• pp.66-71
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• 2014

Oil is obviously vital for economic growth and industry development. This paper attempts to explore whether or not there is a inverted-U relationship between oil consumption and economic growth. To this end, we employ a panel data analysis with fixed effect or random effect models using the set of data from 61 countries for the year 1990-2008. In conclusion, a statistically significant inverted-U relationship between per capita consumption of oil and per capita GDP is found. However, the level of per capita GDP at the peak point of per capita oil consumption is estimated to be 65,072 in 2005 international constant dollars, which is much larger than economic scales of sampled countries. Thus, as per capita GDP grows, per capita oil consumption is predicted to increase until eventually reaching the peak.

• Ocean and Polar Research
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• v.41 no.1
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• pp.35-46
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• 2019

The purpose of this study is to identify factors influencing fish production of shallow-sea aquaculture in South Korea. This study employed the two-way fixed effect and random effect models based on the panel models and also the difference between GMM and system GMM models based on the dynamic panel models using the amount of fish farming production, the number of stocked fry, the number of cultured fish, the amount of inputted feed, the farming area, the number of workers, and the sales price data from 2010 to 2017. First, the two-way fixed effect model of the panel models was selected by panel characteristics, time characteristics and Hausman tests and also the model was statistically significant. As a result of the two-way fixed effect model, the number of stocked fry, the amount of inputted feed, and the number of workers were identified as factors that increase the fish production of shallow-sea aquaculture. However, the number of cultured fish and the sales price were analyzed as factors that reduce the fish production of shallow-sea aquaculture. Second, the system GMM model of the dynamic panel models was selected by Hansen test and Arellano-Bond test in order to identify whether or not the over-discrimination condition is appropriate. Based on the system GMM model, the number of stocked fry, the amount of inputted feed, the number of workers in this year and 1 year ago, the number of cultured fish 2 years ago, and the sale price 3 years ago were analyzed as factors that increase the fish production of shallow-sea aquaculture. However, the amount of fish farming production 1, 2, 3 years ago, the farming area in this year, and the number of cultured fish in this year and 1 year ago were identified as factors that reduce the fish production of shallow-sea aquaculture. In conclusion, this study suggests that it is desirable to control the amount of stocked fry rather than to expand the farming area for fish farming in shallow-sea aquaculture, so as to keep the sale price at a certain level by maintaining the appropriate amount of fish production.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.5
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• pp.74-84
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• 1994

This paper discusses a method to generate the tool path for NC machining of automobile panel dies. The source data representing a panel die may be generated from digitizing machines, other CAD/CAM systems via IGES files, of compound surface models. From the source data, three types of interferencefree tool paths are generated automatically ; a parallel (Cartesian), an isometric, and a pencil cutting tool path. For the interference-free tool path, a polyhedral model composed of several triangles, and an 'offset triangle' approach are exploited. Finally, some practical examples are illustrated.

• Asia pacific journal of information systems
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• v.26 no.1
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• pp.66-79
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• 2016

The availability of detailed data on customers' online behaviors and advances in big data analysis techniques enable us to predict consumer behaviors. In the past, researchers have built purchase prediction models by analyzing clickstream data; however, these clickstream-based prediction models have had several limitations. In this study, we propose a new method for purchase prediction that combines information theory with machine learning techniques. Clickstreams from 5,000 panel members and data on their purchases of electronics, fashion, and cosmetics products were analyzed. Clickstreams were summarized using the 'entropy' concept from information theory, while 'random forests' method was applied to build prediction models. The results show that prediction accuracy of this new method ranges from 0.56 to 0.83, which is a significant improvement over values for clickstream-based prediction models presented in the past. The results indicate further that consumers' information search behaviors differ significantly across product categories.