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지역단위 고혈압사업에 있어서 환자의 치료순응도와 결정요인
김지,민경복,권순호,한달선,배상수,Kim, Jee,Min, Kyung-Bok,Kwon, Soon-Ho,Han, Dal-Sun,Bae, Sang-Soo 대한예방의학회 1999 예방의학회지 Vol.32 No.2
Objectives: To investigate compliance of hypertension patients using modified Theory of Reasoned Action(TRA). Methods: The data were collected for 7-12 April 1997, by interviewing 190 Hypertension patients in Hwachon, Kangwon-do. The analytical techniques employed include contingency table analysis and logit analysis. Results: 15.1% of patients were unaware of the fact that he/she has hypertension and 11.2% did not know that he/she should take drug. 20.8% of patients took drug continuously, 20.1% had drug intermittently, and 53.1% had never have treatment. In the contingency table analysis, several variables were found to be significantly related to patient compliance. They included variables for attitude towards the consequences of taking drugs, normative beliefs, systolic BP at the enrollment, knowledge of how to take hypertensive drugs, variables for general health behavior and experience with having health worker's home visit. The logit analysis was performed by two steps. first step uses experience with drug treatment of hypertension as the dependent variable, and second step uses continuity of treatment. Included in the predictors that are significantly related to the former analysis are subjected norms produced by combining normative beliefs and motivation to comply, knowledge of how to take hypertensive drugs, and opinion about natural recovery of diseases. The only significant determinant of continuous treatment was knowledge of how to take hypertensive drugs. Conclusions: The results of analysis suggest the usefulness of TRA as a framework for the study of compliance of hypertensive patients. The findings have some practical implication as well. One is that efforts for enhancing compliance should be directed not only patients but also to other persons influencing patient's attitude and behavior. It also suggest that correct understanding of hypertension treatment is essential to perform the appropriate patient role.
나덕렬,연병길,강연욱,민경복,이수현,이상숙,이미라,표옥정,박찬병,김선민,배상수,김동현,Na, Duk-L.,Yeon, Byeon-Gil,Kang, Yeon-Wook,Min, Kyung-Bok,Lee, Soo-Hyun,Lee, Sang-Suk,Lee, Mi-Ra,Pyo, Ok-Jung,Park, Chan-Byung,Kim, Sun-Mean,Bae, Sang-S 대한예방의학회 1999 예방의학회지 Vol.32 No.3
Objectives: In Korea, as in most countries, there will be a sharp increase in the number of dementia patients in the near future. However basic data on dementia prevalence, which is important in defining epidemiologic characteristics and in implementing preventive strategy, are limited. This study was conducted to estimate the prevalence rate of dementia in the urban elderly aged 65 or older in Kwangmyung, Korea. Methods: A two phase design was used for case finding and case identification. In phase I, a representative sample aged 65 or older was selected and interviewed by door-to-door survey with a Korean version of the Mini-Mental State Examination (K-MMSE). In phase II, Of the 946 subjects interviewed in phase 1,356 elderly were randomly selected disproportionately according to K-MMSE score. Of these elderly, 223 (61.5%) underwent standardized clinical evaluations, including psychiatric interview, neurological examination, and neuropsychological assessment. Dementia was diagnosed by the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria. The diagnosis of Alzheimer's disease (AD) was made by National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and feinted Disorders Association(NINCDS-ADRDA) criteria and vascular dementia (VD) by DSM-IV. Results: The overall weighted prevalence rate of all dementia among Kwangmyung residents aged 65 or older was 12,8%(age-adjusted rate: 13,0%, 95% Confidence Interval[CI]: 10.6-15.3%). Women had much higher prevalence rate than men even when age was controlled(15.9%[95% CI 12.6-19.2%] vs 7.5%[95% CI 4.0-10.4%]), The rates of dementia were 5.2%, 12.2%, 17.0%, and 34.3% for the age groups of 65-69, 70-74, 75-79 and 80 and over, respectively. The rate of AD appeared to be slightly higher than that of VD(5.2% vs 4.8%), though not statistically significant. Most of the cases(69%) were mild dementia according to CDR(<1) in these subjects. Conclusions : These results showed that the prevalence rate of dementia among urban elderly in Korea appears to be higher than those of other Asian countries.
한 대기업 근로자들의 직무스트레스와 정신건강과의 관련성
유경열 ( Kyeong Yeol Yu ),이경종 ( Kyung Jong Lee ),민경복 ( Kyoung Bok Min ),박규철 ( Kyu Chul Park ),채상국 ( Sang Kug Chai ),박재범 ( Jae Bum Park ) 한국산업위생학회 2011 한국산업보건학회지 Vol.21 No.3
Objectives: This study was conducted to investigate the association between job stress and mental health among male and female workers in a large electric manufacture company. Methods: A cross-sectional study was carried out on 3,228 employees who participated in annual medical check-up working in a large electric manufacture company in Gyeonggi Province. Medical check-up and self-administrated questionnaire were performed at the same time. Korean Occupational Stress Scale Short Form (KOSS-SF) and Psychosocial Wellbeing Index Short Form (PWI-SF) were applied to assess occupational stress and mental health. Hierarchical multiple linear regression and multiple logistic regression were performed to estimate the association between job stress and mental health. Results: The proportion of high risk of mental health was 17.1% in male, and 46.9% in women. Job stress had a greater effect on mental health than other general and work characteristics. All subscales of job stress were revealed to affect mental health. Bad occupational climate and lack of reward are the strongest risk factors in mental health of male and female respectively. Conclusions: Our results suggest that job stress could affect mental health among large electronic manufacture workers.
무인기로 촬영한 무 재배지 영상의 정규식생지수(NDVI)를 활용한 병충해 분석 연구
임수현(Su-Hyeon Im),Syed Ibrahim Hassan,Lien Minh Dang,민경복(Kyung-Bok Min),문현준(Hyeonjoon Moon) 대한전기학회 2018 전기학회논문지 Vol.67 No.10
This paper compares and analyzes Fusarium wilt of radish by using an unmanned aerial vehicle(UAV) with the NDVI-7 camera. The UAV have taken near-infrared images of the Radish field in Gangwon area, which is affected by Fusarium wilt. Based on those images, we analyzed NDVI(Normalized difference vegetation index) and compared conditions of radish by using the Blue value among Regular Vegetation Index in NDVI. First, the radish field is divided into three fields for radish, soil and vinyl. Each field has separate Blue values that are radish 0.4890, soil 0.2959, vinyl -0.0605 respectively. Second, radish condition levels are divided into four stages which are normal, early, middle, and late stage of Fusarium wilt. The average values of each stage are normal 0.5165(100%), early 0.4565(88%), middle 0.3444(66%), and late 0.1772(34%) respectively. This result shows that this NDVI value is validated by measuring conditions of Radish and soil.
CNN을 이용한 딥러닝 기반 하수관 손상 탐지 분류 시스템
Syed Ibrahim Hassan,Dang Lien Minh,임수현(Su-hyeon Im),민경복(Kyung-bok Min),남준영(Jun-young Nam),문현준(Hyeon-joon Moon) 한국정보통신학회 2018 한국정보통신학회논문지 Vol.22 No.3
연구는 인공지능 분야의 딥러닝 기술을 기반으로 한 하수관 손상의 자동 탐지 분류 시스템을 제안한다. 성능의 최적화를 위하여 DB 획득 시 발생된 조도 및 그림자 변화와 같은 다양한 환경변화에 강인한 시스템을 구현하였다. 제안된 시스템에서는 Convolutional Neural Network(CNN) 기반의 균열 탐지 및 손상 분류 기법을 구현하였다. 최적의 결과를 위하여 256 x 256 픽셀 해상도의 CCTV 영상 9,941개를 이용하여 CNN모델을 적용하여 손상부위에 대한 딥러닝을 수행하였고 그 결과 98.76 %의 인식률을 획득하였다. 기계학습을 통한 딥러닝 모델을 기반으로 다양한 환경의 하수도 DB에서 720 x 480 픽셀 해상도의 646개의 이미지를 추출하여 성능 평가를 수행 하였다. 본 시스템은 다양한 환경에서 구축된 하수관 데이터베이스 에서 손상 유형의 자동 탐지 및 분류에 최적화된 인식률을 제시한다. We propose an automatic detection and classification system of sewer damage database based on artificial intelligence and deep learning. In order to optimize the performance, we implemented a robust system against various environmental variations such as illumination and shadow changes. In our proposed system, a crack detection and damage classification method using a deep learning based Convolutional Neural Network (CNN) is implemented. For optimal results, 9,941 CCTV images with 256 x 256 pixel resolution were used for machine learning on the damaged area based on the CNN model. As a result, the recognition rate of 98.76% was obtained. Total of 646 images of 720 x 480 pixel resolution were extracted from various sewage DB for performance evaluation. Proposed system presents the optimal recognition rate for the automatic detection and classification of damage in the sewer DB constructed in various environments.