• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.83-96
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• 2000

본연구는 웹 상에서 원격 협력 학습을 위한 수준별 협력 학습자 진단 및 스케줄링 에이전트의 설계와 구현에 관한 연구이다. 원격 협력 학습은 동일한 학습내용에 흥미를 갖는 아동이 동시에 학습할 수 있는 환경이 필요하며 학습자의 지식 또한 비슷한 수준이어야 효과적인 협력학습을 할 수 있다. 분산 환경의 이질적인 학습자를 모으기 위해서는 좀 더 자율적이고 지능적인 시스템이 필요하며 학습자에 대한 지식을 표현하는 학습자 모델이 요구된다. 이를 위해 에이전트 시스템이 적절하게 사용될수 있으며 학습자의 수준을 판단하기 위한 진단 에이전트와 협력학습이 가능한 여러명의 학습자들을 알맞은 시간과 서버에 연결하는 스케줄링 에이전트를 웹 기반 지능형 교수 시스템에 접목하였다. 학습자 수준을 진단하는 진단 에이전트는 확신도를 높이기 위해 3-모수 로지스틱 확신공식과 시간 가중치 확신인자 공식을 적용하여 신뢰도를 높였다 또한 협력학습의 스케줄링을 위해 다양한 제약조건들의 최적해를 구하기 위해 제약 만족 문제(CSP)로 스케줄링 에이전트를 모델링하였다 본 연구에서 설계 구현한 협력학습자 진단 및 스케줄링 에이전트의 효율성을 살펴보기 위해 여러명의 학습자를 대상으로 실험하였다. 실험을 통해 각 학습자의 지식 수준 진단과 다수의 학습자가 적절한 협력학습을 하기 위한 스케줄링이 매우 효율적으로 이루어짐을 볼 수 있었다.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.931-940
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• 2011

Classification is to generate a rule of classifying objects into several categories based on the learning sample. Good classification model should classify new objects with low misclassification error. Many types of classification methods have been developed including logistic regression, discriminant analysis and tree. This paper presents a new classification method using penalized partial least squares. Penalized partial least squares can make the model more robust and remedy multicollinearity problem. This paper compares the proposed method with logistic regression and PCA based discriminant analysis by some real and artificial data. It is concluded that the new method has better power as compared with other methods.

• KIEAE Journal
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• v.12 no.1
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• pp.11-19
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• 2012

The subject of this study is capital area including Seoul and Incheon, and metropolitan area including Daejeon and Busan among urban redevelopment project district that are currently promoting urban redevelopment project. Data for analysis is implemented collected through visiting each households in project district. Resettlement decision characteristics are analyzed with considering householder's characteristic, house member's characteristic, residential space's characteristic, and area characteristic of families residing in urban redevelopment project area. Through researching characteristics and preferences of residents in project area by urban redevelopment business, improvement were found and implications were provided. Consequently, there are many factors to consider resettlement when deciding household's resettlement when deciding on household's resettlement after the redevelopment project depending on household's characteristics. So, political methods are needed to accomplish urban redevelopment project by resident's position through characteristic and preference survey of resident on project district. Therefore, the study can be utilized as basic data that considers characteristic of each households and region when establishing house policy in order to correspond to housing market that satisfies future consumer's demand.

• Journal of Biomedical Engineering Research
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• v.22 no.4
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• pp.369-375
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• 2001

The statistical regression model is one of the most frequently used clinical analysis methods. It has basic assumption of linearity, additivity and normal distribution of data. However, most of biological data in medical field are nonlinear and unevenly distributed. To overcome the discrepancy between the basic assumption of statistical model and actual biological data, we propose a new analytical method based on artificial neural network. The newly developed multilayer perceptron(MLP) is trained with 120 data set (60 normal, 60 patient). On applying test data, it shows the discrimination power of 0.76. The diabetic risk factors were also identified from the MLP neural network model and the logistic regression model. The signigicant risk factors identified by MLP model were post prandial glucose level(PP2), sex(male), fasting blood sugar(FBS) level, age, SBP, AC and WHR. Those from the regression model are sex(male), PP2, age and FBS. The combined risk factors can be identified using the MLP model. Those are total cholesterol and body weight, which is consistent with the result of other clinical studies. From this experiment we have learned that MLP can be applied to the combined risk factor analysis of biological data which can not be provided by the conventional statistical method.

• Land and Housing Review
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• v.12 no.4
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• pp.31-40
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• 2021

In the present article we examine life-cycle housing demand for Korea. Distinguished in this work from prior research is the consideration of non-monocinity in the life-cycle housing demand. To this end, we adopt spline logistic regression models. Our findings suggest that life-cyclicity is most clear in Korean housing demand; namely, 1) small (mid-large) house ownership falls (grows) dramatically as households age into middle aged; 2) middle aged households do not participate in the rental or purchase market actively; 3) elderly population does not dispose of their housing to the same extent as younger generations acquire housing.

• Journal of Korea Planning Association
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• v.54 no.3
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• pp.49-62
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• 2019

In order to balance with supply policy, public housing management and operation policies have been implemented in terms of housing welfare, but citizens have not yet achieved the results that the citizens are experiencing. The purpose of this study is to analysis the residential satisfaction of the including the housing performance through the characteristics of the public housing residents in Seoul. The data used in this study is based on the survey data of public housing panel survey in Seoul (2016). The study method used ordered logistic regression analysis based on the fact that dependent variables appeared as ordered responses. Major research results are as follows. Firstly, housing performance and residential satisfaction may not match. Even though the satisfaction of housing area, type, and management fee is high, satisfaction with residential environment is low if commuting distance, the number of small libraries, and hospitals are small. Secondly, it showed different characteristics of residential environment factors among types of public housing. Rather than focusing on supply, customized supply is needed considering characteristics of public housing types. Thirdly, the policy for public housing needs to be realized by a fair policy on the residential environment. It is necessary to contribute to better housing stability as a customized policy considering the local residential environment.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.198-198
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• 2022

최근 도시화에 따른 토지 피복 변화와 열섬현상 등의 원인으로 상승하는 도시의 기온이 식물 계절에 미치는 영향에 관한 연구들이 다수 진행되고 있다. 본 연구는 수도권인 서울과 경기도 지역을 대상으로 도시 내 열섬현상으로 인한 기온 상승과 도시 지역 내 식생 생장기간 변화의 관계성을 분석하였다. 식물계절 모니터링에 사용한 개량식생지수(Enhanced Vegetation Index, EVI)는 Google Earth Engine (GEE)에서 제공하는 30 m 해상도의 2000-2021년 NASA-USGS Landsat 위성(TM5, ETM+7, OLI8)의 지표면 반사율(surface reflectance, SR) 자료에서 도출하여 생장기간 산정에 사용하였다. 또한 PRISM (Parameter-elevation Regressions on Independent Slopes Model)을 각 기상관측지점의 일별 지상 기온 자료에 적용하여 30 m 해상도로 생성한 격자형 지표면 온도의 공간적 패턴을 분석하였다. 연구 지역 내 도시화 정도(magnitude)를 도심으로부터의 거리와 환경부 토지피복도 및 인구 밀도를 종합하여 특정하였고, 최종적으로 기후변화 및 도시화 정도와 생장기간 변화의 특징을 분석하였다. 비선형 로지스틱 회귀를 사용하여 EVI 데이터를 종합하여 분석한 결과, 수도권 지역에서 전반적으로 식물계절 개엽일(Start of Season)은 앞당겨지며 낙엽일(End of Season, EOS)은 늦춰져 생장기간(Length of Growing Season, LOS)이 길어짐을 발견하였다.

• Environmental and Resource Economics Review
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• v.25 no.1
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• pp.1-25
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• 2016

This study investigated the variability of WTP estimates(i.e. mean or median) with ad hoc assumptions of specific parametric probability distributions(i.e. normal, logistic, lognormal, and exponential distribution) to estimate WTP function using dichotomous choice CV data on mortality risk reduction. From the perspective of policy decision, the variability of these WTP estimates are intolerable in comparison with those of Turnbull nonparametric estimation method which is free from ad hoc distribution assumptions. The Turnbull nonparametric estimation can avoid a kind of misspecification bias due to ad hoc assumption of specific parametric distributions. Furthermore, the WTP estimates by Turnbull nonparametric estimation are robust because the similar estimates are elicited from a dichotomous choice or double dichotomous choice CV data, and the statistically significant WTP estimates can be obtained even though it is not possible by parametric estimation methods. If there are considerable variability among those WTP estimates by parametric estimation methods in condition with no criteria of model adequacy, the mean WTPs from Turnbull nonparametric estimation can be the robust estimates without ad hoc assumptions, which can avoid controversial issues in the perspective of policy decisions.

• The Journal of the Korea Contents Association
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• v.13 no.9
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• pp.236-247
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• 2013

This study examines the impact of school violence on South Korean students' psychological well-being. The research is designed to analyze how different types of experiences of school violence-victim, perpetrator, victim-perpetrator, and non-involvement-influence students' suicidal impulse and sense of happiness. Empirical data was gained from a national-scale survey conducted by Social Development Research Institute at Yonsei University in 2013, and was analyzed using binary logistic and multiple regression methods. Findings suggest that any types of experiences of school violence had significant effect on suicidal impulse. In particular, the likelihood of victim-perpetrator to experience suicidal impulse was 7.1 times stronger than non-involvement. However, the effect of experiences of school violence on students' sense of happiness was insignificant. While the impact of school violence on sense of happiness among victims and victim-perpetrators was significant, its impact among perpetrators proved insignificant. Rather, stress factor-in particular, stress from peers-had more significant impact on the level of students' happiness. This study contributes to understanding the multiple effect of school violence by examining both negative and positive dimensions of psychological well-being.

• 한국노년학
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• v.37 no.3
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• pp.707-726
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• 2017

Korea is proceeding to aging society at much faster pace than other countries. To alleviate various problems (health, environment, social relationships, psychology and emotion, and financial problems) of the elderly caused by aging society, there has been increasing attention to social capital. This study investigated types of ways that the elderly at individual level are aware of social capital and the characteristic. In addition, factors that influence the types were studied. Data from 1060 elderly with the age of 65 and older were collected in Korea. Excluding missing data on variables used in the study, data of 960 elderly were used for analyses. K-mean cluster analysis was conducted to investigate types of elderly awareness on social capital at individual level. Multinominal logistic regression was used to find out factors of the types. K-mean cluster analysis resulted in three types of awareness on social capital among the elderly: (1) potential of social capital; (2) severance of social capital; and (3) wealth of social capital. Multinominal logistic regression resulted in that compared to potential of social capital type, when the elderly were younger, inclination of politics was more progressive, they did not have religion, they did not reside in rural, and they did not live in multiplex housing, the elderly were more likely to be in severance of social capital type. Also, when the elderly were women, had higher education and standard of living, were Christian, and did not reside in rural regions. they tended to be in wealth of social capital type. Based on the study results about awareness on social capital among the elderly and factors related to the awareness types, practical and political suggestions that promote social capital to solve problems of the elderly were provided.