• 제목/요약/키워드: Diagnosis-Analysis System

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웹기반 진단 보조 시스템의 진단 일치도 연구 (A Study for Diagnostic Agreement between Web-based Diagnosis Support System and Korean Medical Doctors' Diagnosis)

  • 이승엽;강민지;임현정;양웅모
    • 대한융합한의학회지
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    • 제6권1호
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    • pp.37-42
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    • 2024
  • Objectives: This study aims to evaluate the clinical validity of the system by conducting a clinical study to assess the diagnostic agreement between the system and Korean medical doctors. Methods: This study was conducted from September 7, 2023, to December 7, 2023, across five Korean medicine institutions, involving 100 adult participants aged 20-64 who consented to participate. Participants first entered their symptoms into a web-based program, which utilized an AI-based algorithm to diagnose 36 types of pattern differentiation. Subsequently, Korean medical doctors conducted face-to-face diagnoses using the same 36 types. The diagnostic agreement between the system and the doctors' diagnoses was analyzed using descriptive statistical analysis, and the results were expressed as a percentage agreement. Results: Analysis of the diagnostic data from 100 participants revealed that the web-based diagnosis support system identified an average of 7.76±0.79 patterns per patient, while Korean medical doctors identified an average of 7.99±0.10 patterns per patient. The diagnostic agreement between the system and the doctors showed an average of 7.08±1.08 patterns per patient, with an overall diagnostic agreement rate of 88.57±13.31%. Conclusion: This study developed a web-based diagnosis support system for traditional Korean medicine and evaluated its clinical validity by assessing diagnostic agreement. Comparing the diagnoses of the system with those of Korean medical doctors for 100 patients, the system showed an approximately 89% agreement rate with the clinical diagnoses. The system holds potential for aiding Korean medical doctors in pattern differentiation diagnosis in clinical practice.

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퍼지 규칙기반 간 기능 검사 해석 시스템의 개발 (Development of Fuzzy Rule-based Liver Function Test Diagnosis System)

  • 김종원;오경환
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1992년도 춘계학술대회
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    • pp.155-160
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    • 1992
  • Liver function test is one of the most common tests for diagnosis and follow-up of patients and for heal th screening. Automatic interpretation and suggestions on the diagnostic possibilities contribute to shorten the interpretation time of the test results and help to provide qualified health care. Fuzzy logic has been recently introduced and being spread for these purposes. The present study aims at model Ins the foray rule-based laboratory diagnosis system. The fuzzy rule-based laboratory diagnosis system was applied to the diagnosis regarding liver function test. The system was evaluated by comparing with the stepwise multivariate discriminant function analysis, which showed similar results, and the overall accuracy of the fuzzy diagnosis system was about 80%.

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전기신호를 이용한 전동기 온라인 고장진단 (Online Fault Diagnosis of Motor Using Electric Signatures)

  • 김낙교;임정환
    • 전기학회논문지
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    • 제59권10호
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    • pp.1882-1888
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    • 2010
  • It is widely known that ESA(Electric Signature Analysis) method is very useful one for fault diagnosis of an induction motor. Online fault diagnosis system of induction motors using LabVIEW is proposed to detect the fault of broken rotor bars and shorted turns in stator. This system is not model-based system of induction motor but LabVIEW-based fault diagnosis system using FFT spectrum of stator current in faulty motor without estimating of motor parameters. FFT of stator current in faulty induction motor is measured and compared with various reference fault data in data base to diagnose the fault. This paper is focused on to predict and diagnose of the health state of induction motors in steady state. Also, it can be given to motor operator and maintenance team in order to enhance an availability and maintainability of induction motors. Experimental results are demonstrated that the proposed system is very useful to diagnose the fault and to implement the predictive maintenance of induction motors.

대학 지식경영 성과측정시스템의 진단 사례연구 (Diagnosis of Performance Measurement System of Knowledge Management : A Case of University)

  • 이영찬;이승석
    • 지식경영연구
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    • 제10권1호
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    • pp.71-100
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    • 2009
  • Recently, many of organizations build up their performance measurement system (PMS) to measure their knowledge management performance. However, the system that doesn't well reflect the organization's strategies as well as surroundings could obstruct their performance improvement, instead. Therefore, It is really important to establish the PMS to reflect organization's surroundings and strategies. The purpose of this study is to make a diagnosis of a performance measurement practice of a domestic university's knowledge management. To serve this research purpose, we examine the uptight performance index and PMS from existing references. And we diagnose the specific practices and maturity rates of measuring performances, and the recognition of the performance index at "D" university recently adopting balanced scorecard to performance evaluation through the survey on academic affairs committee members, performance evaluation committee members, and administration members. The method analyzing data from the survey is a gap analysis which includes alignment analysis, congruence analysis, consensus analysis, and confusion analysis. We make a diagnosis of performance measurement practices at "D" university, raise several points of this performance measurement system, and present the improvement plans from these problems.

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변압기 고장 진단을 위한 하이브리드형 전문가 시스템 (A Hybrid Type Based Expert System for Fault Diagnosis in Transformers)

  • 전영재;윤용한;김재철;최도혁
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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    • pp.143-145
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    • 1996
  • This paper presents the hybrid type based expert system for fault diagnosis in transformers. The proposed system uses the novel fault diagnostic technique based on dissolved gas analysis(DGA) in oil-immersed transformers. The uncertainty of key gas analysis, norm threshold, and gas ratio boundaries are managed by using a fuzzy set. Also, the uncertainty of the fault diagnostic rules are handled by using fuzzy measures. Finally, kohnen's feature map performs fault classification in transformers. To verify the effectiveness of the proposed diagnosis technique, the hybrid type based expert system for fault diagnosis has been tested by using KEPCO's transformer gas records.

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유도전동기 베어링의 원거리 실시간 결함진단시스템 개발 (Web-based Real Time Failure Diagnosis System Development for Induction Motor Bearing)

  • 권오헌;이승현
    • 한국안전학회지
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    • 제20권3호
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    • pp.1-8
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    • 2005
  • The industrial induction motor is widely used in the rotating electrical machine for the transmission of power. It is very reliable equipment, but it could lead to the loss of production and lift when failure occurs. Therefore, the failure data is acquired and analyzed by attaching an exclusive instrument to existing induction motor. However, these instruments could lead to side effects, increasing the production costs, because they are very expensive. The purpose of this study is the development of an induction motor bearing failure diagnosis system constructed using LabVIEW which can be supplied the kernelled function, process monitoring and current signature analysis. In addition, the availability and reasonability of the constructed system was examined for an induction motor with failure defects in outer raceway and ball bearing. From the results, it shows that failure diagnosis system constructed is useful for real-time monitoring with detection of bearing defects over the web.

무선센서네트워크 기반 휴대용 헬스케어 모니터링 시스템을 위한 휴대폰 자체 간이진단 관리 (Pre-diagnosis Management in WSN based Portable Healthcare Monitoring System)

  • 히패쳉;이승철;정완영
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2009년도 추계학술대회
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    • pp.538-541
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    • 2009
  • Increasing of number of people who suffered from long term chronic diseases which required frequent daily health monitoring and body check up in conjunction with the trendy uses of mobile phones and Personal Digital Assistants (PDAs) in various ubiquitous computing had make portable healthcare system a well known application today. A mobile phone based portable healthcare monitoring system with multiple vital signals monitoring ability at real time in WSN and CDMA network is developed. This system carries out real time monitoring and local data analysis process in the mobile phone. Any detection of abnormal health condition and diagnosis at earlier stage will reduce the risk of patient's life. As an extension to the existing model, a pre-diagnosis management system (PDMS) is designed to minimize the time consuming in pre-diagnosis process in the hospital or healthcare center. An alert is sent to the web server at the healthcare center when the patient detects his health is at critical state where the immediate diagnosis is needed. Preparation of diagnosis equipments and arrangement of doctor and nurses at the hospital side can be done earlier before the arrival of patient at the hospital with the help of PDMS. An efficient pre-diagnosis management increases the chances of diseases recovery rate as well.

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프레스공정시스템에서 유도전동기 및 윤활유 레벨 상태모니터링을 위한 진단시스템 개발 (Diagnostic system development for state monitoring of induction motor and oil level in press process system)

  • 이인수
    • 한국지능시스템학회논문지
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    • 제19권5호
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    • pp.706-712
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    • 2009
  • 본 논문에서는 프레스공정라인에서 발생하는 고장을 감지하고 분류하기 위한 고장진단기법을 제안한다. 또한 윤활유 레벨을 자동감지 하기 위한 방법도 제안하다. 제안한 방법에서는 FFT 주파수해석과 여러 경계인수를 갖는 ART2 신경회로망을 사용하며, LabVIEW를 이용하여 고장진단 및 윤활유 레벨 자동감시를 위한 GUI(Graphical User Interface) 프로그램을 제작하여 고장진단을 수행하였다. 실험결과들로부터 제안한 유도전동기 고장진단 및 윤활유 레벨 자동감시시스템의 성능을 확인하였다.

케이블 사고 자가원인 진단시스템 구축 및 사고사례 검증에 관한 연구 (The Study of Accident Cases Verification and Construction of It's Cause Diagnosis System of Power Cable Accident)

  • 김영석;송길목;김선구
    • 조명전기설비학회논문지
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    • 제23권9호
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    • pp.91-97
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    • 2009
  • 전력케이블 사고 발생시에는 사고원인을 규명 해야하며, 본 연구에서는 FMEA 방법을 이용하여 케이블 사고에 대한 자가원인 진단 시스템을 구축하였다. 자가원인 진단 시스템은 사고당시의 데이터 입력, 픽토그래프를 통한 사고형태의 표현, FMEA 방식을 적용한 사고확률 값으로 구성되어 있으며, 각 선택에 따라 사고원인에 대한 사고가능성이 결과로 나타나게 된다. 또한 실제 케이블 사고사례의 원인분석을 통해 자가원인 진단 시스템을 검증한 결과, 이 시스템은 실제 분석결과와 잘 일치되었다.

유입변압기 고장분류를 위한 PNN 기반 Rogers 진단기법 개발 (PNN based Rogers Diagnosis Method for Fault Classification of Oil-filled Power Transformer)

  • 임재윤;이대종;지평식
    • 전기학회논문지P
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    • 제65권4호
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    • pp.280-284
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    • 2016
  • Stability and reliability of a power system in many respects depend on the condition of power transformers. Essential devices as power transformers are in a transmission and distribution system. Being one of the most expensive and important elements, a power transformer is a highly essential element, whose failures and damage may cause the outage of a power system. To detect the power transformer faults, dissolved gas analysis (DGA) is a widely-used method because of its high sensitivity to small amount of electrical faults. Among the various diagnosis methods, Rogers diagonsis method has been widely used in transformer in service. But this method cannot offer accurate diagnosis for all the faults. This paper proposes a fault diagnosis method of oil-filled power transformers using PNN(Probability Neural Network) based Rogers diagnosis method. The test result show better performance than conventional Rogers diagnosis method.