• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문초록집
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• pp.382.1-382
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• 2002

This paper presents a new approach integrated Case-Based Reasoning with Self- Organization Map(SOM) in diagnosis systems. The causes of faults are obtained by case-base trained from SOM. When the vibration problem of rotating machinery occurs, this provides an exact diagnosis method that shows the fault cause of vibration problem. In order to verify the performance of algorithm, we applied it to diagnose the fault cause of the electric motor.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2005년도 봄학술 발표회 논문집(I)
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• pp.359-362
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• 2005

Self diagnosis monitoring system is defined as concrete structural carbon and glass hybrid fiber materials, in response to the change in external disturbance and environments, toward structural safety and serviceability as well as the extension of structural service life. In this study, carbon and glass hybrid fiber materials were investigated fundamentally for the applicability of self diagnosis in smart concrete structural system as embedded functions of sensors.

• 동의신경정신과학회지
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• 제24권spc1호
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• pp.23-36
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• 2013

Objectives : The purpose of this guideline is to show the evidence-based guidelines of diagnosis and evaluation of Hwabyung by the synthesis and organization of existing research contents. Methods : We investigated the existing research on the concept of Hwabyung. Further, we investigated the diagnostic tools, self-diagnostic method, symptoms assessment tools, oriental medical diagnostic methods, treatment evaluation tools and other testing methods of Hwabyung. Results : There was a Hwabyung diagnostic interview schedule (HIBDS) in the standardized measure for the diagnosis of Hwabyung. In the symptoms assessment tools of Hwabyung, there was a self-report measurement tool of Hwabyung and measurement tool of Hwabyung to be evaluated by the interviewer. In the oriental medical diagnostic method, there was an instrument of pattern identification for Hwabyung. In the treatment assessment tool, there was an instrument of oriental medical evaluation for Hwabyung. In addition, MMPI, SCL-90R, Zung's self-rating anxiety scale (SAS), Zung's self-rating depression scale (SDS), State-Trait Anger Expression Inventory (STAXI) and etc. can be used for the diagnosis and assessment of Hwabyung. Conclusions : We expect 'Clinical Guidelines for the Treatment of Hwabyung' to be useful for the diagnosis and assessment of Hwabyung.

• 반도체디스플레이기술학회지
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• 제21권1호
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• pp.85-90
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• 2022

In this paper, an asynchronous nonvolatile memory module using a self-diagnosis function was designed. For the system to work, a lot of data must be input/output, and memory that can be stored is required. The volatile memory is fast, but data is erased without power, and the nonvolatile memory is slow, but data can be stored semi-permanently without power. The non-volatile static random-access memory is designed to solve these memory problems. However, the non-volatile static random-access memory is weak external noise or electrical shock, data can be some error. To solve these data errors, self-diagnosis algorithms were applied to non-volatile static random-access memory using error correction code, cyclic redundancy check 32 and data check sum to increase the reliability and accuracy of data retention. In addition, the possibility of application to an asynchronous non-volatile storage system requiring reliability was suggested.

• 반도체디스플레이기술학회지
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• 제22권1호
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• pp.43-48
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• 2023

This paper discusses the design of 32Mbyte asynchronous nonvolatile memory modules, which includes self-diagnosis and RTC (Real Time Clock) functions to enhance their data stability and reliability. Nonvolatile memory modules can maintain data even in a power-off state, thereby improving the stability and reliability of a system or device. However, due to the possibility of data error due to electrical or physical reasons, additional data loss prevention methods are required. To minimize data error in asynchronous nonvolatile memory modules, this paper proposes the use of voltage monitoring circuits, self-diagnosis, BBT (Bad Block Table), ECC (Error Correction Code), CRC (Cyclic Redundancy Check)32, and data check sum, data recording method using RTC. Prototypes have been produced to confirm correct operation and suggest the possibility of commercialization.

• 동의생리병리학회지
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• 제20권1호
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• pp.245-256
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• 2006

This research sought to survey oriental medicine diagnosis methods currently practiced, analyze their advantages and disadvantages, and work out clinical establish direction for oriental medicine diagnosis methods. Oriental medicine diagnosis methods currently practiced in the related circles are categorized into traditional Korean diagnosis methods and holistic auxiliary diagnosis methods. The traditional Korean diagnosis method focuses on treating diseases of traditional Korean health management methods which are based on the bodily self-viability capabilities according to the Orient's viewpoint of health. Under the diagnosis method, based on the cognition of maximizing the state of the bodily self-viability capabilities together with the characteristics of diseases, symptoms, pulse, first face-to-face patient observation, physical constitution, and life principle are managed according to form, color, pulse and symptom which divide the bodily viability capacities into inherent and acquired elements amid both elements interacting.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권9호
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• pp.512-519
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• 2000

A Neural networks has been used for a expert system and fault diagnosis system. It is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping.쪼두 a fault occur in system a state of system is changed with transient state. Because of a previous state signal is considered as a information DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• Journal of information and communication convergence engineering
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• 제15권2호
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• pp.85-90
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• 2017

Expert systems for health diagnosis are only for medical experts who have deep knowledge in the field but we need a self-checking pre-diagnosis system for preventive public health monitoring. Korea Traditional Medicine is popular in use among Korean public but there exist few available health information systems on the internet. A computerized self-checking diagnosis system is proposed to reduce the social cost by monitoring health status with simple symptom checking procedures especially for Korea Traditional Medicine users. Based on the national reports for disease/symptoms of Korea Traditional Medicine, we build a reliable database and devise an intelligent inference engine using fuzzy c-means clustering. The implemented system gives five most probable diseases a user might have with respect to symptoms given by the user. Inference results are verified by Korea Traditional Medicine doctors as sufficiently accurate and easy to use.

• Asian Pacific Journal of Cancer Prevention
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• 제15권6호
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• pp.2879-2882
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• 2014

Background: Breast cancer (BC) is the most common form of cancer in Iranian women, and it remains a major health problem. An increasing number of young women are being diagnosed with BC, and therefore, there is an increasing likelihood that more women will survive breast cancer for many years. Many opine that self-disclosure of BC diagnosis is important because talking about cancer helps people to make sense of their experiences; in fact, self-disclosure appears to play an important role in many health outcomes. However, this has not yet been studied in BC patients in Iran. Therefore, this study aimed to explore the status of self-disclosure of BC diagnosis by Iranian women to friends and colleagues. Materials and Methods: All BC records for 2001-2011 of employed women were studied at five hospitals in Mashhad. Data about the self-disclosure of BC diagnosis were gathered through telephone interviews, and the participants filled out a questionnaire about their status of self-disclosure of BC diagnosis to various groups of people. Results: The mean age of employed women at the time of diagnosis was $44.3{\pm}6.7$ years. Over 60% self-disclosed to work colleagues and over 90% to bosses/managers. Seventy per cent reported that they had support from their family and husband's family, while 95% reported that they had support from parents, siblings, children and friends. Conclusions: Most employed women self-disclosed freely to family, friends, colleagues and bosses/managers. Apparently, self-disclosure of breast cancer diagnosis may have negative effects at work. About half of patients reported that they had support from family, managers and colleagues; however, for nearly 28% of employed women, disclosure had less positive effects. In particular, it altered their perception of others, produced difficulties with work and family and diminished closeness with the people who were told. However, the stigma of BC is far less than it once was.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제3권5호
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• pp.129-140
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• 2014

기존의 메모리에서 발생하는 다양한 고장들을 검출하기 위한 기법으로 BIST(Built-in self test)가 있고 고장이 검출되면 Spare를 할당하여 수리하는 BIRA(Built-in redundancy analysis)가 있다. 그리고 BIST와 BIRA를 통합한 형태인 BISR(Built-in self repair)를 통해 전체 메모리의 수율을 증가시킬 수 있다. 그러나 이전에 제안된 기법들은 RAM을 위해 제안된 기법으로 RAM의 메모리 구조와 특성이 다른 NAND-형 플래시 메모리에 사용하기에는 NAND-형 플래시 메모리의 고유 고장인 Disturbance를 진단하기 어렵다. 따라서 본 논문에서는 NAND-형 플래시 메모리에서 발생하는 Disturbance 고장을 검출하고 고장의 위치도 진단할 있는 BISD(Built-in self diagnosis)와 고장 블록을 수리할 수 있는 BISR을 제안한다.