• 한국국방경영분석학회지
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• 제34권2호
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• pp.43-61
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• 2008

성과기반군수는 전투준비태세를 향상시키고 무기체계의 수법주기비용을 절감하기 위하여 연구되었다. 최근 미국 국방부는 성과기반군수를 연구하고 발전시켜서 이것을 미국 군수분야에 적용하고 있다. 따라서 본 연구논문에서는 미국의 군수기원 분야의 발전동향을 살펴보고 우리나라의 군수지원 분야의 실태를 분석한 후, 효율적인 군수지원을 위하여 성과기반군수를 활용한 군수지원 발전방안을 제시하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.913-915
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• 1995

In this paper, a transient signal classification system using logistic regression and neural networks is presented, where four neural networks such as MLP, MLP-Class, RBF and LVQ are utilized to classify given transient signals, based on the logistic regression method. Also, some test results with experimental transient signal data are provided.

• 대한안전경영과학회지
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• 제9권4호
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• pp.29-38
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• 2007

We adapted association rules of data mining in order to investigate the relation among the factors of musculoskeletal disorders and proposed the method of preventing the musculoskeletal disorders associated with multiple logistic regression in previous study. This multiple logistic regression was difficult to establish the method of preventing musculoskeletal disorders in case factors can't be managed by worker himself, i.e., age, gender, marital status. In order to solve this problem, we devised association rules of factors of musculoskeletal disorders and proposed the interactive method of preventing the musculoskeletal disorders, by applying association rules with the result of multiple logistic regression in previous study. The result of correlation analysis showed that prevention method of one part also prevents musculoskeletal disorders of other parts of body.

• Journal of the Korean Data and Information Science Society
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• 제23권2호
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• pp.385-392
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• 2012

Logistic regression is a well known binary classification method in the field of statistical learning. Mixed-effect regression models are widely used for the analysis of correlated data such as those found in longitudinal studies. We consider kernel extensions with semiparametric fixed effects and parametric random effects for the logistic regression. The estimation is performed through the penalized likelihood method based on kernel trick, and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of optimal hyperparameters, cross-validation techniques are employed. Numerical results are then presented to indicate the performance of the proposed procedure.

• 한국산림과학회지
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• 제107권4호
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• pp.478-485
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• 2018

본 연구에서는 백두대간 등산로 훼손에 영향을 미치는 자연환경요인을 선정하고 영향 관계를 분석하였다. 연구대상지는 백두대간 고루포기산~생계령 구간 내 표본지 총 123개소이며 등산로 훼손, 임상, 하층식생, 수관밀도와 FGIS를 통해 얻은 경사, 토성, 암석노출 총 7가지 정보를 분석에 활용하였다. 등산로 훼손 발생지 43곳과 미발생지 80곳을 로지스틱 회귀분석을 통해 분석한 결과, 등산로 훼손에 영향을 미치는 자연환경요인으로 경사도, 하층식생, 토성, 암석노출 총 4가지를 선정하였다. 경사도와 하층식생은 양의 상관관계를 보였고 암석노출은 음의 상관관계로 나타났다. 토성은 미사 비율이 낮고 모래 비율이 높은 토성일수록 양의 상관관계를 보이는 것으로 나타났다. 따라서 등산로 훼손을 줄이기 위해서는 경사도, 하층식생, 토성, 암석노출 4가지 자연환경요인들을 적절하게 관리하여야 한다.

• 응용통계연구
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• 제27권1호
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• pp.89-102
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• 2014

본 연구에서는 질병관리본부에서 매년 조사하고 있는 지역사회 건강조사 자료를 이용하여 서울시 지역을 대상으로 개인의 흡연 여부에 대한 영향 요인을 확인하고 지역간 차이를 모형에 반영시키는 다수준 로지스틱 모형을 이용하여 분석하였다. 다수준 모형에서의 적합한 분석 모형의 수준을 결정하기 위해 ICC(intraclass correlation coefficient)와 프로파일링 분석, 수준별 모형의 예측정확도를 이용하였다. 제안된 모형들의 성능을 평가하기 위해 민감도, 특이도, 정확도를 구하고 ROC curve를 작성하였다. 결과적으로 지역사회 건강조사 자료와 같이 개인과 집단 변수를 동시에 고려할 수 있다면 다양한 다수준 모형의 적용이 가능하며 활용성이 높다는 것을 알 수 있었다.

• 한국응급구조학회지
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• 제17권3호
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• pp.169-179
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• 2013

Purpose: The performance rate to perform Cardiopulmonary Resuscitation (CPR) by witness in out-of-hospital Cardiac Arrest (OHCA) is very low in South Korea. To prevent the death caused by OHCA, it is important to encourage the witness to perform CPR actively. The purpose of the study is to investigate the influencing factors to affect bystander CPR rate. Methods: I conducted a questionnaire survey from 25 February to 4 March, 2013, receiving responses from 517 people in Korea. The questionnaire included social demographic factors, history of heart disease, knowledge of CPR, and the reliability of emergency medical service (EMS). A logistic regression analysis was conducted. Results: Among the 517 respondents, 294 (57.4%) had intention of performing CPR. Multiple logistic regression analysis found the following significant predictors of CPR intention: gender (odds ratio [OR] = 0.390), age (OR = 1.024), religion (OR = 0.843), and knowledge of CPR (OR = 4.734). Conclusion: This study indicated that the strongest predictor is knowledge of CPR. Therefore, it would be helpful to teach CPR nationwide to encourage performing CPR. In addition, effect of CPR education in religious facilities is necessary.

• 한국농공학회논문집
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• 제49권3호
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• pp.63-68
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• 2007

The LRA(Logistic Regression Analysis) conducts a quantitative analysis by collecting a lot of samples and the AHP(Analytic Hierarchy Program) makes use of expert decision influenced by subjective judgment to a certain degree. This study is to suggest a combination method in mapping landslide hazard by giving equal weight for the result of LRA and AHP. Topographic factors(slope, aspect, elevation), soil dram, soil depth and land use were adopted to classify landslide hazard areas. The three methods(LRA, AHP, the combined approach) was applied to a $520km^2$ region located in the middle of South Korea which have occurred 39 landslides during 1999 and 2003. The suggested method showed 58.9% matching rate for the real landslide sites comparing with the classified areas of high-risk landslide While LRA and AHP Showed 46.1% and 48.7% matching rates respectively. Further studies are recommended to find the optimal combining weight of LRA and AHP with more landslide data.

• 대한의용생체공학회:의공학회지
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• 제22권4호
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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.

• 한국학교보건학회지
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• 제35권3호
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• pp.133-142
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• 2022

Purpose: The purpose of the study was to investigate the effect of the environment on adolescent binge drinking. Methods: The study was designed as a cross-sectional study. Using statistics from the 17th (20201) Korea Youth Risk Behavior Web-based Survey, the raw data target population was 2,629,588 people, and the sample group used for analysis as the final data was 54,848 people. A Rao-scott 𝑥² test and univariate multinomial logistic regression analysis were performed using IBM SPSS 27.0. Results: In the results of univariate logistic regression analysis and multivariate logistic regression analysis, common related variables were gender, school level, academic achievement, sleep satisfaction, current smoking, daily smoking, and alcohol education experience. Conclusion: As a result of confirming the factors influencing binge drinking in Korean adolescents, some variables that increase the possibility of problematic drinking behavior in the socio-environmental areas such as individuals, communities, and national policies were identified. For effective prevention and intervention, it is necessary to develop programs to build a healthy environmental support system with support from national policies, including individuals, peer groups, and communities.