• Journal of the military operations research society of Korea
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• v.35 no.3
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• pp.1-15
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• 2009

Central supply depot of Air Force has been receiving and storing the goods from the inside and outside of the country. And it also has been distributing the goods to the air base by air, rail, road, etc. These goods have been called central goods. Among these central goods, 10% of them are transported by air and the amount of freight is increasing day by day. So, air transportation in the Air Force has been more important than ever. But, studies of demand estimation for activating air transportation are very difficient. This study verified the main factors affecting to air transportation and the function of regression model will be useful data for estimating air freight demand.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.691-699
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• 2011

Land sliding is one of well-known nature disaster. As a part of effort to reduce damage from land sliding, many researchers worked on increasing prediction ability. However, because previous studies are conducted mostly by non-statisticians, previously proposed models were hardly statistically justifiable. In this paper, we predicted the probability of land sliding using the logistic regression model. Since most explanatory variables under consideration were correlated, we proposed the final model after backward elimination process.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1117-1124
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• 2010

The PM10 (Promethium 10) data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model has been considered for analyzing the monthly PM10 data at the southern part of the Gyeonggi-Do, Suwon monitoring site in Korea. In the ARE model, six meteorological variables and four pollution variables are used as the explanatory variables for the PM10 data set. The six meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, radiation, and amount of cloud. The four air pollution explanatory variables are sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), carbon monoxide (CO), and ozone ($O_3$). The result showed that the monthly ARE models explained about 13-49% for describing the PM10 concentration.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05b
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• pp.1334-1339
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• 2002

The objective of this study is to help practicing engineers easily use the Clark model which is used for estimating the magnitude of design flood for small stream. A representative unit hydrograph was derived on the basis of the past rainfall-runoff data and unit hydrographs, and the storage coefficient of Clark model was estimated by using hydrograph recession analysis. Since the storage coefficient(K) is a dominating factor among the parameters of Clark method, a mulitple regression formula, which has the drainage area, main channel length and slope as parameters, is propsed to estimate K value of a basin where measured data are missing. The result of regression analysis showed that there is a correlation between a storage coefficient(K) and aforemetioned three parameters in homogenious basins. A regression formular for K was derived using these correlations in a basin of Han River, Nakdong River, Young River, Kum River and Sumjin River

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.21-32
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• 2023

The amount of money processed in medicine from the Korea Consumer Agency was studied by the various time series models. The medical data set from the Korea Consumer Agency were consisted of counseling, damage relief and conciliation. For the analysis of time series, autoregressive moving average model, vector autoregressive model and the transfer function model were used. We considered the stationarity and cross correlation function for the identification and fitting. As a result, the transfer function model showed a better prediction. Whereas, the vector autoregressive model also provided good information for the degree and duration of the influence of variables.

• Proceedings of the Korea Contents Association Conference
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• 2013.05a
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• pp.241-242
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• 2013

이 연구는 경찰공무원의 직무교육이 직무만족, 직무성과에 미치는 관계를 규명하는데 있다. 이 연구는 2012년 경찰교육원 교육과정 중 경비관련 직무 5개 과정에 입교한 전국 경찰관을 모집단으로 선정한 후 판단표집법을 이용하여 268명의 사례를 분석하였다. 자료처리는 SPSSWIN 18.0을 이용하여 빈도분석, 요인분석, 신뢰도분석, 다중 회귀분석, 경로분석 등이다. 결론은 다음과 같다. 첫째, 경찰관의 직무교육이 직무만족에 영향을 미친다. 둘째, 경찰관의 직무교육이 직무성과에 영향을 미친다. 셋째, 경찰관의 직무만족이 직무성과에 영향을 미친다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.599-605
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• 2021

In this study, we empirically investigated how start-up support programs provided at colleges affect students' satisfaction with their major and their Entrepreneurial Intentions. The participants included 248 students from five colleges two-four-year colleges located in Seoul, Gyeonggi-do Province, Chungcheong-do Province, Gyeongsangbuk-do Province, and Jeola-do Province. SPSSWIN 24.0 for descriptive statistics analysis, exploratory factor analysis, reliability analysis, multiple regression analysis, and moderated regression analysis. showed that, among various forms of support for business start-up, support for education on start-up and support for start-up activities had a positive impact on the students' opportunity motivation and achievement motivation at a statistically significant level. opportunity motivation, achievement motivation, and independence motivation all positive influence on the students' resolution to start a business support for education on start-up and support for start-up activities had positive impact on the studens' entrepreneurial Intentions. These findings suggest that college programs that support students' business start-up need to be developed and applied with a focus on support for education on start-up and support for start-up activities to enhance college students' satisfaction with their major and stimulate their Entrepreneurial Intentions.

• Journal of the Korea Institute of Building Construction
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• v.23 no.6
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• pp.821-830
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• 2023

This research aims to identify risk factors for fall accidents at small and medium-sized construction sites through a comprehensive regression analysis. Initially, the study involved collecting a decade's worth of fall accident data from these sites. A t-test confirmed a significant variation in the treatment duration following fall accidents between two distinct groups: small and medium-sized versus large construction sites. Subsequently, a regression analysis was conducted to establish a model highlighting the risk factors associated with safety accidents. The factors influencing fall accidents were determined to be, in descending order of impact, the time of the accident, the day of the accident, and the occupational classification. The findings from this study are expected to serve as foundational data for enhancing policies and conducting statistical analyses tailored to construction site sizes. They also provide crucial information for future research on risk quantification at small and medium-sized construction sites.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.993-1003
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• 2012

The purpose of this study was to estimate the determinants of victory and defeat through analyzing records of Korean men pro-basketball. Statistical models of victory and defeat were established by collecting present basketball records (2010-2011, 2011-2012 season). Korea Basketball League (KBL) informs records of every pro-basketball game data. The six offence variables (2P%, 3P%, FT%, OR, AS, TO), and the four defense variables (DR, ST, GD, BS) were used in this study. PASW program was used for logistic regression and Answer Tree program was used for the decision tree. All significance levels were set at .05. Major results were as follows. In the logistic regression, 2P%, 3P%, and TO were three offense variables significantly affecting victory and defeat, and DR, ST, and BS were three significant defense variables. Offensive variables 2P%, 3P%, TO, and AS are used in constructing the decision tree. The highest percentage of victory was 80.85% when 2P% was in 51%-58%, 3P% was more than 31 percent, and TO was less than 11 times. In the decision tree of the defence variables, the highest percentage of victory was 94.12% when DR was more than 24, ST was more than six, and BS was more than two times.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.505-513
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• 2017

Recently, numerous small area estimation studies have been conducted to obtain more detailed and accurate estimation results. Most of these studies have employed spatial regression models, which require a clear definition of spatial neighborhoods. In this study, we introduce the Delaunay triangulation as a method to define spatial neighborhood, and compare this method with the k-nearest neighbor method. A simulation was conducted to determine which of the two methods is more efficient in defining spatial neighborhood, and we demonstrate the performance of the proposed method using a land price data.