• 보건의료산업학회지
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• 제10권3호
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• pp.63-74
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• 2016

Objectives : There is a need to develop a data quality management algorithm to improve the quality of healthcare data using a data quality management system. In this study, we developed a data quality control algorithms associated with diseases related to hypertension in patients with diabetes mellitus. Methods : To make a data quality algorithm, we extracted the 2011 and 2012 discharge damage survey data from diabetes mellitus patients. Derived variables were created using the primary diagnosis, diagnostic unit, primary surgery and treatment, minor surgery and treatment items. Results : Significant factors in diabetes mellitus patients with hypertension were sex, age, ischemic heart disease, and diagnostic ultrasound of the heart. Depending on the decision tree results, we found four groups with extreme values for diabetes accompanying hypertension patients. Conclusions : There is a need to check the actual data contained in the Outlier (extreme value) groups to improve the quality of the data.

• 한국간호교육학회지
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• 제3권
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• pp.78-98
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• 1997

Health education, as the most fundamental concept for national health promotion, alms for developing the self-care ability of the general public. High school days are regarded as the period when most important physical, mental and social developments occur, and most health-related behaviors are formed. School health education is one of the major learning resources influencing health potential in the home and community as well as for the individual student. High school health education in Korea has a fundamental systemic flaw in that health-related subjects are divided and taught under various subjects areas at school. In order to achieve the goal of school health education, it is essential to make a systematic assessment of the learner's concerns connected with his health and life, and the factors affecting them. So far, most of the research projects that had been carried out for improving high school health education were limited in their concerns to a particular aspect of health. Even though some had been done in view of comprehensive school health education, they failed to Include a health assessment of the learner. Therefore, in this study the high school students' concerns related to health and life were investigated in the first place on the basis of the PRECEDE model, developed by Green and others for the purpose of a comprehensive diagnostic research on high school health education. This study was done in two steps : one was the basic study for developing research instrument and the other was the main one. The former was conducted at five high schools in Seoul and Cheongju for 2 months-beginning in March, 1996. The students were asked to respond to questions related to their health and lives in unstructured open-ended question forms. On the basis of analysis of the basic study, the diagnostic instruments for the quality of life, health problems, health behavior and educational factors were constructed to be used for the collection of data for main study. An expert panel and the pilot study were used to improve content validity and reliability of the instruments. The reliability of the instruments was measured at between .7697 and .9611 by the Cronbach $\alpha$. The data for this study were collected from the sample consisted of the junior and senior classes of twenty general and vocational high schools in Seoul and Cheongju for two months period beginning in July, 1996. In analyzing the data, both t-test and $X^2$-test were done by using SAS-$PC^+$ Program to compare data between the sexes of the high school students and the types of high school. A canonical correlation analysis was carried out to determine the relationships among the diagnostic variables, and a multivariate multiple regression analysis was conducted by using LISREL 8.03 to ascertain the influences of variables on the high school students' health and quality of life. The results were as follows : 1) The findings of the hypothesis tests (1) The canonical correlation between the educational diagnosis variables and behavioral, epidemiological, social diagnosis variables was .7221, which was significant at the level of p<.001. (2) The canonical correlation between the educational diagnosis variables and the behavior variables was .6851, which also was significant (p<.001). (3) The canonical correlation between the behavioral diagnosis variables and the epidemiological variables was 4295, which was significant (p<.001). (4) The canonical correlation between the epidemiological diagnosis variables and the social variables was .6005, which was also significant (p<.001). Therefore, the relationship between each diagnosis variable suggested by the PRECEDE model had been experimentally proven to be valid, supporting the conceptual framework of the study as appropriate for assessing the multi-dimensional factors affecting high school students' health and quality of life. Health behavior self-efficacy, the level of parents' interest and knowledge of health, and the level of the perception of school health education, all of which are the educational diagnostic variables, are the most influential variables in students' health and quality of life. In particular, health behavior self-efficacy, a causative factor, was one of the main influential variables in their health and quality of life. Other diagnostic variables suggested in the steps of the PRECEDE model were found to have reciprocal relations rather than a unidirectional causative relationship. The significance of this research is that it has diagnosed the needs of high school health education by the learner-centered assessment of variety of factors related to the health and the life of the students. This research findings suggest an integrated system of school health education to be contrived to enhance the effectiveness of the education by strengthening the influential factors such as self-efficacy to improve the health and quality of the lives of high school students.

• 수산해양기술연구
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• 제28권2호
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• pp.144-150
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• 1992

This paper describes an application of artificial neural network to diagnose the defects of rotating machiner. Induction motor was used to the object of defect diagnosis. For defect diagnosis, the frequency spectrum of vibration was utilized. Learning method of applied neural network was back propagation. Neural network has following advantage; Once it has been learned, inference time is very short and it can provide a reasonable conclusion regardless of insufficient input data. So, this defect diagnosis system can be used superiorly to rule based expert system as quality inspection of rotating machinery in the shop.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 1999년도 유체기계 연구개발 발표회 논문집
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• pp.317-323
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• 1999

The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Many research has been conducted to manipulate field vibration signal data for diagnosing the fault of designated machinery. As the pattern recognition tool of that signal, neural network which use usually back-propagation algorithm was used in the diagnosis of rotating machinery. In this paper, self-organizing feature map(SOFM) which is unsupervised learning algorithm is used in the abnormal vibration diagnosis of rotating machinery and then learning vector quantization(LVQ) which is supervised teaming algorithm is used to improve the quality of the classifier decision regions.

• 한국인터넷방송통신학회논문지
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• 제22권4호
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• pp.81-86
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• 2022

본 연구에서 csv포맷으로 구조화된 파일 데이터의 컬럼의 도메인을 자동 판별하는 방법을 제안한다. 데이터와 데이터 간 융합을 통해 새로운 데이터를 생성할 수 있고, 이들 새로운 데이터가 중요한 자원이 되기 위해서는 조인 되는 컬럼의 일관성이 유지되어야 한다. 데이터 품질을 측정하기 위한 방법 중의 하나가 도메인 기반 품질 진단 방법이다. 도멘인이란 각 컬럼의 성격을 규정하는 가장 광범위한 지표이므로 이를 자동으로 판별하는 방법이 필요하다. 기존의 연구에서는 관계형 데이터베이스의 도메인 자동 판별이 주로 연구 되었지만 본 연구는 파일데이터의 특성을 이용하여 도메인을 자동화 할 수 있는 모델을 개발하였다. 파일데이터의 도메인 판별을 특화하기 위하여 정규표현식을 이용하여 데이터를 단순화 하고 이를 패턴화 하였고, 컬럼명에 해당하는 데이터 헤더의 내용을 분석하여 사용된 접미사를 분석하여 파생변수로 사용하였다. 정규표현식과 접미사의 파생변수를 추가하였을 때 기존 방법인 87%의 정확도 보다 큰 95%의 정확도로 도메인을 자동 판별하는 결과를 도출하였다. 본 연구는 공공데이터 품질진단에 자동화 방법론을 제시하여 품질 측정 기간 및 인원을 줄일 수 있을 것으로 기대된다.

• 대한의용생체공학회:의공학회지
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• 제27권1호
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• pp.6-13
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• 2006

Ultrasound visualization is a typical diagnosis method to examine organs, soft tissues and fetus data. It is difficult to visualize ultrasound data because the quality of the data might be degraded by artifact and speckle noise, and gathered with non-linear sampling. Rendering speed is too slow since we can not use additional data structures or procedures in rendering stage. In this paper, we use several visualization methods for fast rendering of ultrasound data. First method, denoted as adaptive ray sampling, is to reduce the number of samples by adjusting sampling interval in empty space. Secondly, we use early ray termination scheme with sufficiently wide sampling interval and low threshold value of opacity during color compositing. Lastly, we use bilinear interpolation instead of trilinear interpolation for sampling in transparent region. We conclude that our method reduces the rendering time without loss of image quality in comparison to the conventional methods.

• 한국기계가공학회지
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• 제15권4호
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• pp.23-29
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• 2016

Rotary machine is major equipment in industry. The rotary machine is applied for a machine tool, ship, vehicle, power plant, and so on. But a spindle fault increase product's expense and decrease quality of a workpiece in machine tool. A turbine in power plant is directly connected to human safety. National crisis could be happened by stopping of rotary machine in nuclear plant. Therefore, it is very important to know rotary machine condition in industry field. This study mentioned fault diagnosis algorithm with statistical parameter and empirical mode decomposition. Vibration locations can be found by analyze kurtosis of data from triaxial axis. Support vector of data determine threshold using hyperplane with fault location. Empirical mode decomposition is used to find fault caused by intrinsic mode. This paper suggested algorithm to find direction and causes from generated fault.

• 보건의료산업학회지
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• 제14권1호
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• pp.93-102
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• 2020

Objectives: This study analyzed the prescription characteristics of medication for acute respiratory diseases before and after pay-for-performance to provide basic data on effective medical quality management policies. Methods: The research data were collected from the 2013-2014 sample cohort of the National Health Insurance Corporation, from Internal Medicine, Pediatrics, Otorhinolaryngology, Family Medicine and General practitioner clinics (classification of disease codes: J00-J06, J20-J22, J40 outpatients). Results: The antibiotics prescription rates decreased from 43.9% in 2013 to 43.5% in 2014 when the major diagnosis was for upper respiratory infections and increased from 62.0% in 2013 to 62.5% in 2014 when the major diagnosis was for lower respiratory infections. Conclusions: There is a need to identify the correct antibiotic prescription method by expanding the current assessment standards. Such standards must include acute lower respiratory infections and minor diagnoses as the current evaluation techniques focus only on the major diagnosis of acute upper respiratory infections.

• Asian Pacific Journal of Cancer Prevention
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• 제15권6호
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• pp.2935-2937
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• 2014

Studies of the causes of cancer, early detection, prevention or treatment need accurate, comprehensive, and timely cancer data. The clinical laboratory provides important cancer information needed for physicians which influence clinical decisions regarding treatment, diagnosis and patient monitoring. Poor communication between health care providers and clinical laboratory personnel can lead to medical errors and wrong decisions in providing cancer care. Because of the key impact of laboratory information on cancer diagnosis and treatment the quality of the tests, lab reports, and appropriate lab management are very important. A laboratory information management system (LIMS) can have an important role in diagnosis, fast and effective access to cancer data, decrease redundancy and costs, and facilitate the integration and collection of data from different types of instruments and systems. In spite of significant advantages LIMS is limited by factors such as problems in adaption to new instruments that may change existing work processes. Applications of intelligent software simultaneously with existing information systems, in addition to remove these restrictions, have important benefits including adding additional non-laboratory-generated information to the reports, facilitating decision making, and improving quality and productivity of cancer care services. Laboratory systems must have flexibility to change and have the capability to develop and benefit from intelligent devices. Intelligent laboratory information management systems need to benefit from informatics tools and latest technologies like open sources. The aim of this commentary is to survey application, opportunities and necessity of intelligent clinical laboratory as a tool to increase cancer care management productivity.

• 대한의생명과학회지
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• 제10권4호
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• pp.485-493
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• 2004

In the current field of Medical Informatics, the information increases, and changes fast, so we can access the various data types which are ranged from text to image type. A small number of technician digitizes these data to establish database, but it is needed a lot of money and time. Therefore digitization by many end-users confronting data and establishment of searching database is needed to manage increasing information effectively. New data and information are taken fast to provide the quality of care, diagnosis which is the basic work in the medicine. And also It is needed the medical database for purpose of private study and novice education, which is tool to make various data become knowledge. However, current medical database is used and developed only for the purpose of hospital work management. In this study, using text input, file import and object images are digitized to establish database by people who are worked at the medicine field but can not expertise to program. Data are hierarchically constructed and then knowledge is established using a tree type database establishment method. Consequently, we can get data fast and exactly through search, apply it to study as subject-oriented classification, apply it to diagnosis as time-depended reflection of data, and apply it to education and precaution through function of publishing questions and reusability of data.