• 제목/요약/키워드: Diagnosis

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갱년기장애 및 폐경기증후군 변증진단 도구의 진단결과 도출을 위한 변증별 절단점 연구 (A Clinical Study on the Pattern-Specific Cut-Point for the Pattern Identification Diagnostic Tool for Climacteric and Postmenopausal Syndrome)

  • 이인선;김종원;전수형;지규용;강창완
    • 대한한방부인과학회지
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    • 제32권2호
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    • pp.29-49
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    • 2019
  • Objectives: This study was a methodological study to verify the reliability and validity and to make a diagnosis of a diagnostic tool for climacteric and postmenopausal syndrome pattern identification (CaPSPI). Methods: This study was conducted from June 1, 2018 to October 18, 2018 with ${{\bigcirc}{\bigcirc}}$ University Korean Medicine Hospital IRB's approval (2018-3). To make a diagnosis using CaPSPI, we decided the cut-points for the tool. Three professors of ${{\bigcirc}{\bigcirc}}$Korean Medical University conducted pattern identification diagnosis. The result is marked from 0 to 3, 0 is 'No', 1 is 'Slightly Yes', 2 is 'Yes' and 3 is 'Very Yes'. And if two or more professors' diagnoses are the same, we took the diagnoses as a diagnostic criteria. The decision of pattern by three experts converted to 0-1 scores in two ways. In "method 1", if the diagnosis was zero points, the score was 0 (have no such identification), and the rest was 1 (have such identification). In "method 2", if the diagnosis was zero or 1 point, the score was 0, and the rest was 1. After that, intraclass correlation was calculated for experts agreement. And logistic regression was conducted. A response variable was the results of the experts' diagnosis and an explanatory variable was the results of the pattern identification diagnostic tool. Results: The diagnosis of the three experts showed excellent concordance of more than 0.794 and showed a significant correlation with the diagnostic tool. Both 'Method 1' and 'Method 2' showed statistically significant effects with the diagnosis of 3 experts and the results of the diagnostic tool. The frequency of cumulative pattern identification diagnosis in 'Method 1' and 'Method 2' were found to be 578 occasions and 203 occasions, respectively. The average number of pattern held by participants in 'Method 1' and 'Method 2' were found to be 5.26 and 1.85, respectively. In both "Method 1" and "Method 2," the yield frequency of liver qi depression was the highest, and the frequency of kidney yin deficiency and liver-kidney yin deficiency was relatively high. Conclusions: Based on the above results, it is thought that, in diagnosis using CaPSPI of menopausal women, 'method 1' could be used for the health diagnosis and prevention, 'method 2' could be used for the pattern diagnosis. On the conclusion, CaPSPI is thought to be available for pattern diagnosis of menopause women.

응급간호단위에 적용되는 간호진단의 타당도 연구 (A Validation Study of Nursing Diagnosis in Emergency Care Unit)

  • 최경원;오혜경
    • 기본간호학회지
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    • 제10권2호
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    • pp.145-153
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    • 2003
  • Purpose: Related factors for 24 nursing diagnoses frequently used in the emergency care unit were validated in this study. Method: A convenience sample of 65 registered nurses who had worked for 2 years or more in emergency care units and received instruction on nursing diagnosis was used for the study. The classification of nursing diagnoses was based on NANDA (1996) and validation, on Fehring (1987)'s DCV model. Result: Differences were found between emergency and general care units for related factors for nursing diagnosis. Newly reported related factors were not found for emergency care units. Conclusion: It is helpful for nurses who work in emergency care to be able to apply the nursing diagnosis validated in this study. These findings can be used as the database to provide a nursing diagnosis system appropriate to improving the emergency nursing practice.

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Interobserver Variation in the Diagnosis of Gastric Epithelial Dysplasia and Carcinoma between Two Pathologists in Japan and Korea

  • Kushima, Ryoji;Kim, Kyoung-Mee
    • Journal of Gastric Cancer
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    • 제11권3호
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    • pp.141-145
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    • 2011
  • Although the biological potential of gastric epithelial dysplasia (GED) as a precursor of gastric cancer has never been in doubt, the classification of these lesions has been controversial and fraught with marked variations in approach to diagnosis across the world. The complexity of cyto-architectural features has been considered to be of paramount importance for the diagnosis of carcinoma in Japan, while breach of the basement membrane and invasion into the lamina propria has been considered the sine qua non of malignancy and hence a pre-requisite for the diagnosis of cancer in the West. In Korea, although the incidence of gastric cancer is similar to Japan, the diagnostic approach to GED or cancer seems to lie midway between Western and Japanese criteria. In this review, we will discuss the difference in the diagnosis of GED and cancer between two pathologists working in the comprehensive cancer center located in Japan and Korea, one of the most prevalent areas in the world for gastric cancer.

HMM/ANN복합 모델을 이용한 회전 블레이드의 결함 진단 (Fault Diagnosis of a Rotating Blade using HMM/ANN Hybrid Model)

  • 김종수;유홍희
    • 한국소음진동공학회논문집
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    • 제23권9호
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    • pp.814-822
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    • 2013
  • For the fault diagnosis of a mechanical system, pattern recognition methods have being used frequently in recent research. Hidden Markov model(HMM) and artificial neural network(ANN) are typical examples of pattern recognition methods employed for the fault diagnosis of a mechanical system. In this paper, a hybrid method that combines HMM and ANN for the fault diagnosis of a mechanical system is introduced. A rotating blade which is used for a wind turbine is employed for the fault diagnosis. Using the HMM/ANN hybrid model along with the numerical model of the rotating blade, the location and depth of a crack as well as its presence are identified. Also the effect of signal to noise ratio, crack location and crack size on the success rate of the identification is investigated.

A Hybrid Fault Diagnosis Method based on SDG and PLS;Tennessee Eastman Challenge Process

  • Lee, Gi-Baek
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.110-115
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    • 2004
  • The hybrid fault diagnosis method based on a combination of the signed digraph (SDG) and the partial least-squares (PLS) has the advantage of improving the diagnosis resolution, accuracy and reliability, compared to those of previous qualitative methods, and of enhancing the ability to diagnose multiple fault. In this study, the method is applied for the multiple fault diagnosis of the Tennessee Eastman challenge process, which is a realistic industrial process for evaluating process contol and monitoring methods. The process is decomposed using the local qualitative relationships of each measured variable. Dynamic PLS (DPLS) model is built to estimate each measured variable, which is then compared with the estimated value in order to diagnose the fault. Through case studies of 15 single faults and 44 double faults, the proposed method demonstrated a good diagnosis capability compared with previous statistical methods.

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국내 중풍 환자의 설진에 관한 연구 고찰 (A Review of Studies of Tongue Deviations in Korean Stroke Patients)

  • 박영화;임보라;조준호;원정윤;권도익
    • 대한한방내과학회지
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    • 제38권2호
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    • pp.152-163
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    • 2017
  • Objectives: The aim of this review was to compare the findings of 14 studies of tongue diagnosis in Korean stroke patients. Methods: The purpose, subjects, observation methods, statistical methods, classification of tongue diagnosis, significance, and limitations were analyzed and compared. Results: In Korean stroke patients, tongue diagnosis is significant in pattern identifications, prognosis evaluation, degree of neurological deficit, past history, blood tests, and pulse diagnosis. Interobserver reliability of tongue diagnosis is relatively high.

Expert System for Fault Diagnosis of Transformer

  • Kim, Jae-Chul;Jeon, Hee-Jong;Kong, Seong-Gon;Yoon, Yong-Han;Choi, Do-Hyuk;Jeon, Young-Jae
    • 한국지능시스템학회논문지
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    • 제7권1호
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    • pp.45-53
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    • 1997
  • This paper presents hybrid expert system for diagnosis of electric power transformer faults. The expert system diagnose and detect faults in oil-filled power transformers based on dissolved gas analysis. As the preprocessing stage, fuzzy information theory is used to manage the uncertainty in transformer fault diagnosis using dissolved gas analysis. The Kohonen neural network takes the interim results by applying fuzzy informations theory as inputs, and performs the transformer fault diagnosis. The Proposed system tested gas records of power transformers from Korea Electric Power Corporation to verify the diagnosis performance of transformer faults.

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부호유향그래프와 동적 부분최소자승법에 기반한 화학공정의 다중이상진단 (Multiple-Fault Diagnosis for Chemical Processes Based on Signed Digraph and Dynamic Partial Least Squares)

  • 이기백;신동일;윤인섭
    • 제어로봇시스템학회논문지
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    • 제9권2호
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    • pp.159-167
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    • 2003
  • This study suggests the hybrid fault diagnosis method of signed digraph (SDG) and partial least squares (PLS). SDG offers a simple and graphical representation for the causal relationships between process variables. The proposed method is based on SDG to utilize the advantage that the model building needs less information than other methods and can be performed automatically. PLS model is built on local cause-effect relationships of each variable in SDG. In addition to the current values of cause variables, the past values of cause and effect variables are inputted to PLS model to represent the Process armies. The measured value and predicted one by dynamic PLS are compared to diagnose the fault. The diagnosis example of CSTR shows the proposed method improves diagnosis resolution and facilitates diagnosis of masked multiple-fault.

Kalman Filter 알고리즘을 이용한 태양광 발전 시스템의 출력저하 진단법 (Diagnosis Method of Output Power Lowering of PV System by Using Kalman Filter Algorithm)

  • 강병관;김승탁;이현구;배선호;박정욱
    • 전기학회논문지
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    • 제60권8호
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    • pp.1537-1546
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    • 2011
  • The photovoltaic(PV) generation system have recently become widely used to solve the environmental problems and running out of fossil fuels. However, the study on maintenance is inadequate for PV system. This paper proposes the novel diagnosis method of output power decline to maintain the normal output performance of PV array. The diagnosis method used the proportional relation of irradiation-output current(S-I) of PV array at maximum power point(MPP). And, first order polynomial using the relation is proposed to easily apply PV system. To estimate the relation in case of separation of PV array producer and diagnosis system producer. Kalman Filter algorithm is also proposed at 30.2kW grid-connected PV system. Then, the performance of diagnosis method is evaluated using the hardware tests as well as the simulation.

Rotor Fault Detection System for Inverter Driven Induction Motors using Currents Signals and an Encoder

  • Kim, Nam-Hun
    • Journal of Power Electronics
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    • 제7권4호
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    • pp.271-277
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    • 2007
  • In this paper, an induction motor rotor fault diagnosis system using current signals, which are measured using the axis-transformation method is presented. Inverter-fed motor drives, unlike line-driven motor drives, have stator currents which are rich in harmonics and therefore fault diagnosis using stator current is not trivial. The current signals for rotor fault diagnosis need precise and high resolution information, which means the diagnosis system demands additional hardware such as a low pass filter, high resolution ADC, an encoder and additional hardware. Therefore, the proposed axis-transformation method is expected to contribute to a low cost fault diagnosis system in inverter-fed motor drives without the need for any additional hardware. In order to confirm the validity of the developed algorithms, various experiments for rotor faults are tested and the line current spectrum of each faulty situation, using the Park transformation, is compared with the results obtained from the FFT(Fast Fourier Transform).