• The Korean Journal of Health Service Management
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• v.10 no.1
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• pp.117-129
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• 2016

Objectives : This study investigated the prevalence of unmet health care needs among Korean adults and related factors. Methods : The study participants were adults over the age of 20 mental health experience from the Korea Health Panel in 2012(n=4,730). Statistical analysis methods used in this study were the ${\chi}^2$-test, Logistic Regression Analysis and other basic statistics such frequency-and percentage using SPSS version 22.0. Results : (1)Significant variables of stress: Factors were age, economic activity, subjective health status, and activity limitation. (2)Significant variables of depression: Factors were age, income class(low) and activity limitation. (3)Significant variables of suicidal impulse: Factors were age, chronic diseases, income class, and activity limitation. Conclusions : Stress, depression, and suicidal impulse can be unmet medical factors; therefore improvement measures and mental health counseling programs in response to suicide impulses, should be developed. Thus there is a need for a health sciences approach.

• The Korean Journal of Health Service Management
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• v.8 no.1
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• pp.1-13
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• 2014

The purpose of this study is to investigate the perception of quality property of hospital information system, the quality level, and its effects. The participants were 730 employees who are using hospital information system in hospitals. In order to analyze the relationship, the quality property regulates the consideration of user's taste and the state of user's favor for the design of hospital information system, and the quality level regulates user's convenience and properness. The main results from this study can be summarized as follows, First, the perception of quality property for hospital information system showed few significance level between occupation, but revealed significance level between position. The evaluation of quality level showed significance level depending on the occupation and position. Second, quality property which generally affects to the quality level of the hospital information system were different between types of occupation and quality factor.

• The Korean Journal of Health Service Management
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• v.14 no.1
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• pp.123-136
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• 2020

Objectives: This study aimed to analyze the factors influencing the life satisfaction of retirees(n=1,919) in one-person and multi-person households using the 2015 wave of the Korean Retirement and Income Study, collected by the National Pension Service. Methods: Frequency analysis and χ2-test were performed to examine the general characteristics and relation between one-person and multi-person household retirees. Logistic analysis was conducted to examine the factors affecting life satisfaction. Results: Public pension income was a statistically significant factor affecting life satisfaction, economic, health, and life in multi-person households. Conclusions: To improve life satisfaction after retirement, selective insurance benefits are needed depending on the type of household. Moreover a policy for expanding labor market participation is needed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.317-320
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• 2005

본 논문은 비선형 시스템의 퍼지모델을 설계하기 위해 데이터 입자 기반 퍼지 집합 퍼지 모델의 최적 동정을 제안한다. 퍼지모델은 주로 경험적 방법에 의해 추출되기 때문에 보다 구체적이고 체계적인 방법에 의한 동정 및 최적화 될 필요성이 요구된다. HCM 클러스터링을 통한 데이터 입자는 입력 변수의 개별적인 퍼지 규칙을 형성하고, 퍼지 공간 분할 및 삼각형 멤버쉽 함수의 초기 정점을 정의한다. 또한, 데이터 입자의 중심을 이용하여 후반부의 구조를 결정한다. 초기 퍼지 모델을 동정하기 위해 유전자 알고리즘을 이용하여 입력 변수의 수, 선택될 입력 변수, 멤버쉽 함수의 수, 그리고 후반부 형태를 결정한다. 데이터 입자에 의한 전반부 멤버쉽 파라미터는 유전자 알고리즘을 이용하여 최적으로 동정한다 제안된 모델을 평가하기 위해 수치적인 예를 사용한다.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3004-3006
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• 2000

In this paper, we propose an optimal design method of Fuzzy-Neural Networks model with parallel structure for complex and nonlinear systems. The proposed model is consists of a multiple number of FNN connected in parallel. The proposed FNNs with parallel structure is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. We use a HCM clustering and GAs to identify the structure and the parameters of the proposed model. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model. we use the time series data for gas furnace and the numerical data of nonlinear function.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.253-258
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• 2005

In this study, we introduce a new category of fuzzy inference systems based on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects (data, in particular) drawn together by the criteria of proximity, similarity, or functionality. To identify the structure of fuzzy rules we use genetic algorithms (GAs). Granulation of information with the aid of Hard C-Means (HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms and the least square method (LSM). The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2669-2671
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• 2001

In this paper, we propose design a Multi-Fuzzy Inference model structure. In order to determine structure of the proposed Multi-Fuzzy Inference model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

• The Korean Journal of Health Service Management
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• v.6 no.4
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• pp.83-98
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• 2012

The objective of this study is to analyze the utilization patterns of national health insurance and medical aid inpatients in tertiary hospitals. For the analysis, the study utilize the nationwide data on '2010 Survey of Patients' of Ministry of Health & Welfare. The statistical methodology used in the study is the logistic regression model. This study has three major findings. First, utilization rate of national health insurance inpatients was higher than medical aid inpatients in tertiary hospitals. Second, the significant affecting demographic factors in utilizing tertiary hospitals were sex, age, surgery case, treatment result, inpatients residence region and short length of stay. Third, compared to other disease groups, the inpatients on 'congenital malformation, deformity and chromosomal abnormalities', 'factors influencing health status and contact with health services' and 'neoplasm' groups are more likely to utilize tertiary hospitals. Finally, according to residence region, Seoul residence inpatients in both of national health insurance and medical aid more likely to utilize tertiary hospitals than other region inpatients.

• The Korean Journal of Health Service Management
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• v.14 no.2
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• pp.55-65
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• 2020

Objectives: This study intends to analyze the relationship between medical service experience and subjective health awareness by using data from Panel Study of Worker's Compensation Insurance(PSWCI). Methods: Tte χ2-test was performed to investigate subjective health awareness and medical service experience relevance. Logistic analysis was performed to analyze the influencinge factors. Results: The subjective health awareness scored "bad" in"'lack treatment period" compared to "adequate treatment period" in medical service experience (OR = 2.603 [95% CI = 1.666-2.555]). Conclusions: To improve the subjective health awareness of patients with industrial accidents, the industrial accident compensation and medical care approval system should be improved, and long-term industrial accident insurance policies should be developed to accommodate direct and indirect medical services.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.366-369
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• 2006

본 논문에서는 계층적 공정 경쟁 유전자 알고리즘을 통한 비선형시스템의 정보입자 기반 퍼지집합 퍼지집합 모델의 최적화 방법을 제안한다. 퍼지집합 모델은 주로 전문가의 경험에 기반을 두어 얻어지기 때문에 동정과 최적화 과정이 필요하며 GAs를 이용하여 퍼지모델을 최적화한 연구가 많이 있다. GAs는 전역 해를 찾을 수 있는 최적화 알고리즘으로 잘 알려져 있지만 조기 수렴 문제를 포함하고 있다. 병렬유전자 알고리즘(PGA)은 조기수렴를 더디게 하고 전역 해를 찾기 위한 진화알고리즘이다. 적응형 계층적 공정 경쟁기반 유전자 알고리즘(AHFCGA)을 이용하여 퍼지모델의 입력변수, 멤버쉽함수의 수, 멤버쉽함수의 정점 등의 전반부 구조와 파라미터를 동정하였고, LSE를 사용하여 후반부 파라미터를 동정하였으며 실험적 예제를 통하여 제안된 방법의 성능을 평가한다.