• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.63-68
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• 2003

도시가구의 지출 중 집세가 차지하는 비율이 높으며 그 변동에 따라 도시가구의 생활에 미치는 영향도 커서 중요한 통계자료로 인식되고 있다. 집세 계약기간이 통상 2년 단위이기 때문에 집세변동의 발생빈도가 적어서 이러한 소표본 군의 통계단위로 일반적인 집세지수를 작성하는데는 많은 어려움이 따른다. 그렇다고 해서 소표본 군의 표본을 확대하는 것도 어렵기 때문에 이러한 산술적인 표본확대가 어려운 소표본 군의 문제점을 해결하기 위해 소지역 추정법을 도입하였다. 이러한 소표본 통계단위에서의 집세 변동률 추정방법을 경기도 지역의 6개 도시에서의 집세변동을 추정하는데 적용하였으며 검토해 보았다.

• International Area Studies Review
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• v.15 no.1
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• pp.585-602
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• 2011

This study is to investigate the long run convergence behavior of the housing rent of Korean 21 cities, by using the Phillips and Sul (2007)'s newly developed panel convergence test method. The empirical result shows that the 21 Korean cities nationwide converge in four different groups according to the level of convergence. The 1st group is composed of 3 Seoul metropolitan cities, the 2nd group is composed of Bucheon, the 3rd group is composed of 10 cities such as Busan, Daegu, etc, and the 4th group is composed of 7 cities including Jeonju and Mokpo etc. About the speed of convergence among the member cities within the group, the 1st group has the highest speed and next the 4th group, followed by the 2nd group, and finally the 3rd group. The fact that the member cities of the 1st group with the highest rent level and the 4th group with the lowest rent level converges rapidly means the polarization of rent between the two groups. Finally, this paper suggests policy implications to relax the widening gap of individual income between the higher and the lower rent convergent groups.

• Proceeding of EDISON Challenge
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• 2014.03a
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• pp.643-648
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• 2014

세일링 요트 (sailing yacht)는 세일 (sail)의 양력을 주로 이용하여 추진력을 얻는다. 요트 경주에서와 같이 항주 속도가 중요한 문제에서는 세일의 성능이 좋을수록 빠른 속도를 낼 수 있기 때문에 세일 주변의 유동해석을 통한 성능 추정과 효율의 최적화는 매우 중요하다. 본 논문에서는 일반적인 경주요트의 형태로써 지브 세일 (jib sail)과 메인 세일 (main sail) 그리고 한 개의 마스트(mast)로 구성된 슬루프(sloop)형 요트에 대한 유동해석을 하였다. 풍상범주 상태에서의 30ft급 세일링 요트인 KORDY-30의 jib sail과 main sail의 높이에 따른 단면을 모델링하였다. 슬루프형 요트의 경우, 세일링 요트에서 jib sail과 main sail이 각각 단독으로 있는 형태의 요트보다 세일의 개수가 증가함에 따라 양력이 증가하지만 항력도 따라서 증가 할 것이라고 가정했다. 따라서 jib sail의 각도를 다양하게 변화시켜 양력계수와, 항력계수의 변화를 살펴보고 그에 따른 양항비의 분석을 통해 최적의 효율을 갖는 jib sail의 각도를 알아보았다.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.1 s.139
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• pp.24-33
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• 2005

It is important to understand the flow characteristics around two sails of a sloop yacht. In this paper a computational aerodynamic investigation is performed over sail-like airfoils similar to the main and iIb sails of a 30 feet sailing yacht. Lift and drag are calculated for various conditions of slit distance between the two sails and overlapped length of the jib sail. The thrust and CE(center of effort) of the sail system are obtained. It is found that the combination of two sails produces the thrust force larger than the sum of the thrust force of each sail standing separately and the slit distance of the two sails are important factor to increase lift force.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.4 s.148
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• pp.431-439
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• 2006

Due to the limitation of size of the test section, blockage effects could not be avoided in the model test of yacht sails for common wind tunnels. In this paper, a numerical analysis is performed to investigate the blockage effects on the lift and drag forces measured from wind tunnel experiments for a 30 feet sloop yacht sail. Complex airflows around the jib and main sails including three-dimensional flow separations are calculated for various close-hauled conditions. It is found that the blockage of a wind tunnel changes the flow separation and consequently the lift and drag forces of the sails, especially the main sail, reduce and increase, respectively, due to the blockage effects.

• 한국노년학
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• v.38 no.2
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• pp.271-290
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• 2018

The study aims to analyze the effects of socio-economic deprivation on suicidal ideation. The analysis data were used as a guide for Korea Welfare Panel Study 9. the frequency analysis, mean difference analysis, correlation analysis, and logistic regression were performed by SPSS programs. The results of analysis are as follows. First, The results of frequency analysis by deprivation type showed a high frequency of deprivation in the following order. Experience of not receiving a public pension, experience of being able to work but unemployed, experience of not being able to eat a balanced diet due to financial difficulties, and experience where you had nothing to eat but no more money to buy. Second, the average difference analysis shows that when a person does not have a spouse, the lower the academic background and the income level, the higher the likelihood of suicide. Third, regression analysis shows that the following deprivation patterns have a statistically significant effect on older adults' thoughts of suicide. Experience in which the respondents or their family could not go to hospital because they had no money, experience that move house because is back rent more than 2 months or can not pay rent, experience that they could not afford to buy food and eat well-balanced meals, experience of failing to pay your bills on time, experience of being able to work but not having a job, and experience in which financial difficulties left them short of food and no money to live. Based on such research results, some policy measures, such as the expanding management of medical care benefits cases, the improvement of elderly housing, residential conditions and the diet survey for the elderly, and the expansion of measures to support elderly people's tax rates, were proposed.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.151-161
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• 2018

Income is a vital aspect of economic life. Knowing what their income will help people create budgets that allow them to pay for their living expenses. Income data is used by banks, stores, and service companies for marketing purposes and for retaining loyal customers; it is a crucial demographic element used at a wide variety of customer touch points. Therefore, it is essential to be able to make income predictions for existing and potential customers. This paper aims to predict employment earnings or income based on history, and uses machine learning techniques such as SVMs (Support Vector Machines), Gaussian, decision tree and DCNNs (Deep Convolutional Neural Networks) for predicting employment earnings. The results show that the DCNN method provides optimum results with 88% compared to other machine learning techniques used in this paper. Improvement of the data length such PCA has the potential to provide more optimum result.