• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.87-96
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• 2022

This paper is an empirical analysis as a reference model that can predict up to the maximum number of elementary school student care needs in local governments across the country. This study analyzed and predicted the characteristics of the region based on machine learning to predict the demand for elementary care in a new apartment complex. For this purpose, a total of 292 variables were used, including data related to apartment structure, such as number of parking spaces per household, and building-to-land ratio, environmental data around apartments such as distance to elementary schools, and population data of administrative districts. The use of various variables is of great significance, and it is meaningful in complex analysis. It is also an empirical case study that increased the reliability of the model through comparison with the actual value of the basic local government.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.17-34
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• 2022

This paper develops a model for dynamic station assignment to optimize the Demand Responsive Transit (DRT) operation. In the process of optimization, we use the bus travel time as a variable for DRT management. In addition, walking time, waiting time, and delay due to detour to take other passengers (detour time) are added as optimization variables and entered for each DRT passenger. Based on a network around Anaheim, California, reserved origins and destinations of passengers are assigned to each demand responsive bus, using K-means clustering. We create a model for selecting the dynamic station and bus route and use Non-dominated Sorting Genetic Algorithm-III to analyze seven scenarios composed combination of the variables. The result of the study concluded that if the DRT operation is optimized for the DRT management, then the bus travel time and waiting time should be considered in the optimization. Moreover, it was concluded that the bus travel time, walking time, and detour time are required for the passenger.

• Database Research
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• v.34 no.3
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• pp.159-169
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• 2018

Discretization of continuous variables intended to improve the performance of various algorithms such as data mining by transforming quantitative variables into qualitative variables. If we use appropriate discretization techniques for data, we can expect not only better performance of classification algorithms, but also accurate and concise interpretation of results and speed improvements. Various discretization techniques have been studied up to now, and however there is still demand of research on discretization studies. In this paper, we propose a new discretization technique to set the cut-point using Wasserstein distance with considering the distribution of continuous variable values with classes of data. We show the superiority of the proposed method through the performance comparison between the proposed method and the existing proven methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.261-273
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• 2022

This study aims to predict the land use demand of Seongnam-city using system dynamics and to simulate the effect of changes in family structure and land use density adjustment policy on land use demand. This study attempted to construct causal loop diagrams and an analysis model. The changes in land use demand over time were predicted through simulation results. As a result of the analysis, as of 2035, an additional supply of 2.08 km² for residential land and 1.36 km² for commercial land is required. Additionally, the current supply area of industrial land can meet the demand. Three policy experiments were conducted by changing the variable values in the basic model. In the first policy experiment, it was found that when the number of household members decreased sharply compared to the basic model, up to 7.99 km² of additional residential land were required. In the second policy experiment, if the apartment floor area ratio was raised from 200% to 300%, it was possible to meet the demand for residential land with the current supply area of Seongnam-city. In the third policy experiment, it was found that even if the average number of floors in the commercial area was raised from four to five and the building-to-land ratio in the commercial area was raised from 80% to 85%, the demand for commercial land exceeded the supply area of the commercial area in Seongnam-city. This study is meaningful in that it proposes a new analytical model for land use demand prediction using system dynamics, and empirically analyzes the model by applying the actual urban planning status and statistics of Seongnam-city.

• The Korean Journal of Financial Studies
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• v.8 no.1
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• pp.157-188
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• 2002

본 연구는 우리나라 IPO시장에서 나타나고 있는 초과수익률의 원인을 밝히고자 최근 벤처금융의 중심으로 급부상하고 있는 KOSDAQ시장의 공모 IPO를 대상으로 실증분석을 시도하였다. 연구결과 상장일 표본전체 IPO의 초과수익률(AR1)이 9.91%로 나타났으며, 벤처캐피탈투자 IPO는 5.13%, 비투자 IPO는 13.29%로 나타났다. 상한가의 행진이 종료된 날을 기준으로 한 표본전체 IPO의 초과수익률(AR2)은 30.97%, 벤처캐피탈 투자기업 IPO는 24.34%, 비투자기업 IPO는 34.67%로 나타났다. 초과수익률의 원인을 분석하기 위한 8개의 변수 중 IPO의 수요증감 척도인 KOSDAQ 지수는 초과수익률(AR)과는 양(+)의 관계로, 벤처캐피탈리스트들의 능력 및 가치책정의 행태를 엿볼 수 있는 변수인 본질가치와 공모가액의 차이는 음(-)의 관계로, 사업규모나 자본조달의 크기를 엿볼 수 있는 공모금액의 크기는 양(+)의 관계로 1% 유의수준에서 유의한 것으로 나타났다. 그러나 여타 변수들은 통계적으로 유의성을 확보하지는 못하였으나 초과수익률의 원인이론으로 '신호이론'과 '투기적 거품가설'에 의한 설명이 가능하였으며 분석결과를 다음과 같이 정리할 수 있었다. 첫째, IPO 본질가치에 대한 신뢰와 IPO의 발행규모에 대한 신뢰수준이 통계적으로 유의한 결과로 나타났는바 이러한 결과는 기업가치와 벤처 또는 사업의 계속적 수행 등에 대한 신호역할을 수행하고 있다고 할 수 있으며 상장초기 초과수익률은 주로 이러한 신호역할에 의한 수요집중으로 발생된 결과인 것으로 사료되었다. 둘째, 노련한 벤처캐피탈회사로 선정된 KTB의 투자기업들은 상장 후 4주간의 거래에 있어 AR 평균이 음(-)으로 여타 벤처캐피탈이 투자된 기업보다 손실 폭이 더욱 켰음에도 불구하고 상장일 초과수익률 AR2가 매우 높게 나타나 우리나라 IPO시장에 있어 과민반응(fads) 현상이 존재하고 있는 것으로 분석되었다. 셋째, 벤처캐피탈 투자 IPO의 초과수익률이 상대적으로 낮아 벤처캐피탈 투자여부가 IPO의 저가발행 수준을 축소하고 있어 벤처캐피탈리스트의 제 3자 보증역할이 어느 정도는 수행되고 있는 것으로 분석되었다.

• Journal of Technology Innovation
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• v.24 no.3
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• pp.139-159
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• 2016

The purpose of this study is to find out the factors which promoting career development of scientist and engineer laborforce. We made up three logit analysis models to figure out the factors affecting the career of scientist and engineer laborforce. Dependent variables were composed of job attributes in 2011, current job attribute, changing of working conditions, efforts of job seeking, university education, and personal characters. Three analysis model were composed of demand side model which including job attributes factors, supply side model which focus on employment or university education characters and total model including the demand and the supply factors. The results showed a stable career to the development of scientist and engineer laborforce's job attributes on the demand side than the supply side, such as a college education even more important. After all, the initial stable jobs and good matching policy were the most important policies to be seated in the science and engineering professions.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1041-1049
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• 2010

In Korean professional baseball, attendance is the largest source of revenue for development of professional baseball and the highest concern of professional baseball teams. So, if there is demand forecasting model, it will be helpful for pennant chasers to work out the strategies for drawing attendance. For this reason, this research intends to suggest the model which estimates Korean professional baseball's attendance and uses all usable variables which have an effect on attendance in limited circumstances. We supposed that dependent variable is attendance as well as several independent variables and error term are homoscedastic variance. And then, we compared the models which assume conditional heteroscedastic variance like GARCH and EGARCH with GARCH-t models which use the assumption that error term's distribution follows student-t distribution. In result of that, we could confirm that the models which were made by using GARCH(1,1)-t made estimates the most accurately among the several models considered.

• Tunnel and Underground Space
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• v.23 no.3
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• pp.192-202
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• 2013

The domestic demand of natural gas has increased continuously due to the sudden rise of oil price and regulations on greenhouse gas to global warming. In order to improve the supply security of natural gas market in Korea, the agreement on supply of pipeline natural gas (PNG) in Russia was signed between Gazprom and Korea Gas Corporation in 2008. If the supply plan of Russian natural gas is realized, underground storage facilities would be required in order to balance supply and demand of natural gas because the gas demand is concentrated in the winter. This study investigated the safety of the storage facility in quantitative way considering several design parameters such as gas pressure, depth of the storage cavern, rock condition and in-situ horizontal stress ratio. Two dimensional stress analyses were conducted using axi- symmetry condition to examine the behavior of cavern depending upon suggested design parameters. Results showed that the factor of safety, defined as the ratio of 'shear strength'/'shear stress', was largely affected by the depth, rock class and gas pressure but was insensitive to the coefficient of lateral pressure(Ko).

• Economic Analysis
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• v.26 no.4
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• pp.98-136
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• 2020

We empirically investigate the determinants of a firm's exit from exporting, using Korean manufacturing firm-level data for the period from 2006 to 2014. Specifically, we estimate the effects of not only firm-level and industry-level characteristics, but also macroeconomic variables on the probability that a firm stops exporting by applying a Complementary Log-Log Model analysis. The results of our estimation suggest that firm-level heterogeneity, such as workforce size, capital intensity, intangible assets and foreign ownership, industry-level variation, such as the labor displacement rate, and macroeconomic variables, such as domestic demand and world demand, significantly affect the possibility of a firm ceasing exports. Also, we show that market interest rates increase the possibility of an export cessation and that the effects of market interest rates are more pronounced on firms with a higher debt ratio. In the primary exporting industries, the probability of a firm ceasing exports decreases as productivity at the firm rises.

• Environmental and Resource Economics Review
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• v.18 no.3
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• pp.495-521
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• 2009

This paper measures welfare losses from beef consumption reduction, which might be resulted from psychological anxiety about potential outbreak of BSE (commonly known as "bad cow dieses") risks after announcement of resuming US-beef imports in April of 2008. Unlike the previous literature of utilizing the contingent valuation method or experimental market approach, this study estimated quality-differentiated consumer demand functions using the information of self-reported beef consumption quantity, individually constructed price indices of beef, and subjective perception of BSE risks. The empirical results based on a survey sample of 360 residents in Jeon Ju city were consistent with the anticipation from economic theory, in terms of coefficients of own prices, substitute prices and income variables. The announcement of resuming US-beef imports did not make significant differences in the sign and sizes of the main economic variables. However, the subjective perception variable about BSE risks had negative significant impacts on beef demand functions after the announcement but not significant before the announcement. The welfare losses in a form of equivalent variation (EV) corresponding to the increases in concerns about BSE risks were measured to be about 30 thousand won per household.