• 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.

• 한국항해학회지
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• 제16권1호
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• pp.1-12
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• 1992

In this study, the self test-system for the marine Gyrocompass was developed and the obtained results are summarized as follows : 1) Utilizing the newly developed self-test system, the time length for observing the transient state of Gyrocompass reading which has been over 4 hours can be reduced to less than 20 minutes. In addition, the dynamic characteristics of the Gyrocompass can be measured within 2 hours after starting the system. 2) Prior test and diagnosis was done by checking all parameters recurrently with period of 2.5minutes. 3) Testing and diagnosis results was shown in graphic mode and could be transmitted to INMARSAT unit using personal computer. 4) The results of the newly designed trouble algorithm for the system was found to be applicable under arbitrary given conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.328-330
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• 2004

In this paper, ECG based cardiac disease diagnosis models are developed. Conventionally, ECG monitoring equipments can only measure and store ECG signals and they always require medical doctor's diagnosis actions which are not desirable for continuous ambulatory monitoring and diagnosis healthcare systems. In this paper, two kinds of neural based self cardiac disease diagnosis engines are developed and tested for four kinds of diseases, sinus bradycardia, sinus tachycardia, left bundle branch block and right bundle branch block. For diagnosis engines, error backpropagation neural network (BP) and probabilistic neural network (PNN) were applied. Five signal features including heart rate, QRS interval, PR interval, QT interval, and T wave types were selected for diagnosis characteristics. To show the validity of proposed diagnosis engine, MIT-BIH database were used to test. Test results showed that BP based diagnosis engine has 71% of diagnosis accuracy which is superior to accuracy of PNN based diagnosis engine. However, PNN based diagnosis engine showed superior diagnosis accuracy for complex-disease diagnoses than BP based diagnosis engine.

• 한국보건간호학회지
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• 제14권2호
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• pp.342-354
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• 2000

This study was conducted to identify the characteristics of activities of daily living(ADU) and its influencing factors in patients with chronic arthritis. The data were obtained from 104 patients with chronic arthritis in one university hospital from May to August. 2000. For analysing data. SAS program was used for t-test. ANOVA, Schefte test. Pearson correlation. and stepwise multiple regression. The results were as follows: 1. The variables which influenced self-efficacy were duration of disease. number of painful joint, quality of sleep and alcohol drinking. 2. The variables which influenced fatigue were diagnosis and number of painful joint. 3. The variables which influenced ADL were age. duration of disease. diagnosis. number of painful joint. number of exercise and alcohol drinking. 4. ADL was positive correlation with self-efficacy and negative correlation with fatigue. And self-efficacy was negative correlation with fatigue. 5. The predictors to explain ADL were self-efficacy. number of painful joint. lupus. duration of disease and religion. These predictors explained $66.01\%$ of the activites of daily living. According to these findings. the most significant influencing factor of ADL was self-efficacy. therefore the development of nursing intervention for enhancing self-efficacy would be needed. Also. it is suggested that an exercise program should be recommended as one of useful and appropriate nursing intervention for reducing fatigue and increasing ADL.

• 조명전기설비학회논문지
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• 제27권10호
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• pp.69-74
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• 2013

There is needed the triple pyroelectric Infrared flame detector to really recognize problem, for the prevention and early suppression of fire. This system recognizes the characteristics of fire sources in various type and is communicated the message to the operators. Therefore, the prevention and early suppression of fire is available. Especially this paper focuss on development of the self diagnosis type flame detector for preventing malfunction comparing of basic and detected values.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.2134-2143
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• 2018

This work introduces a fault diagnosis method for transformer based on self-powered radio frequency identification (RFID) sensor tag and improved Hilbert-Huang transform (HHT). Consisted by RFID tag chip, power management circuit, MCU and accelerometer, the developed RFID sensor tag is used to acquire and wirelessly transmit the vibration signal. A customized power management including solar panel, low dropout (LDO) voltage regulator, supercapacitor and corresponding charging circuit is presented to guarantee constant DC power for the sensor tag. An improved band restricted empirical mode decomposition (BREMD) which is optimized by quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to deal with the raw vibration signal. Compared with traditional methods, this improved BREMD method shows great superiority in reducing mode aliasing. Then, a promising fault diagnosis approach on the basis of Hilbert marginal spectrum variations is brought up. The measured results show that the presented power management circuit can generate 2.5V DC voltage for the rest of the sensor tag. The developed sensor tag can achieve a reliable communication distance of 17.8m in the test environment. Furthermore, the measurement results indicate the promising performance of fault diagnosis for transformer.

• 고전문학과교육
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• 제15호
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• pp.191-243
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• 2008

The purpose of this paper is to develope the husband and wife epic test. The results of this paper are as follows. First, in the epic of dividing mate, , , , , etc, the essential item of diagnosis is qualification criteria of a mate. Second, in the epic of pushing mate, , , , , , etc, the essential item of diagnosis is mistrust about mate, Third, in the epic of recovering mate, , , , , , etc, the essential item of diagnosis is ability of recovering couple relationship, Fourth, in the epic of protecting mate, , , , , , etc, the essential item of diagnosis is sympathy for mate.

• Journal of Yeungnam Medical Science
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• 제39권2호
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• pp.81-88
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• 2022

Vertigo is the sensation of self-motion of the head or body when no self-motion is occurring or the sensation of distorted self-motion during an otherwise normal head movement. Representative peripheral vertigo disorders include benign paroxysmal positional vertigo, Ménière disease, and vestibular neuritis. Vestibular neuritis, also known as vestibular neuronitis, is the third most common peripheral vestibular disorder after benign paroxysmal positional vertigo and Ménière disease. The cause of vestibular neuritis remains unclear. However, a viral infection of the vestibular nerve or ischemia of the anterior vestibular artery is known to cause vestibular neuritis. In addition, recent studies on immune-mediated mechanisms as the cause of vestibular neuritis have been reported. The characteristic clinical features of vestibular neuritis are abrupt true-whirling vertigo lasting for more than 24 hours, and no presence of cochlear symptoms and other neurological symptoms and signs. To accurately diagnose vestibular neuritis, various diagnostic tests such as the head impulse test, bithermal caloric test, and vestibular-evoked myogenic potential test are conducted. Various treatments for vestibular neuritis have been reported, which are largely divided into symptomatic therapy, specific drug therapy, and vestibular rehabilitation therapy. Symptomatic therapies include generalized supportive care and administration of vestibular suppressants and antiemetics. Specific drug therapies include steroid therapy, antiviral therapy, and vasodilator therapy. Vestibular rehabilitation therapies include generalized vestibular and customized vestibular exercises.

• 재활간호학회지
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• 제7권2호
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• pp.127-139
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• 2004

Purpose: This study was to investigate the degree of body image, self esteem and quality of life, to identify general and disease of characteristics on influencing this factors with the intention of providing basal data for developing nursing intervention to promote body image, self esteem and quality of life. Method: Subjects of this study were 91 grown-up congenital heart patients over 18 years in 2 tertiary hospitals. The data on body image, self esteem and quality of life were collected through questionnaire from March to April 2004. The data were analyzed by descriptive statistics, t-test, Pearson's correlation, ANOVA and tukey test using SAS for Windows 8.1 program. Result: 1) The mean scores of body image, self esteem and quality of life were 63.01, 25.29 and 496.79. 2) Body image was correlated with age(p=.0239), educational level(p=.0182), diagnosis(p=.0066), number of operation(p=.0148), cyanosis(p<.0001), complication(p=.0096) and NYHA level(p=.0378). 3) Self esteem was correlated with education level(p=.0026), economic level(p=.0240), number of operation(p=.0113) and cyanosis (p=.0006). 4) Quality of life was correlated with age(p=.0432) and diagnosis(p=.0020), number of operation (p=.0063), duration of last operation(p=.0225), cyanosis(p<.0001), complication(p=.0090) and NYHA level(p<.0001). 5) There was significantly positive relationship between body image, self esteem and quality of life. Subjects with more positive body image had higher self esteem(r=.7897, p<.05) and subjects with higher self esteem had higher quality of life(r=.6091, p<.05).

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회B
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• pp.2070-2075
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• 2008

Identification of steady-state is the first step in developing a fault detection and diagnosis (FDD) system. In a complete FDD system, the steady-state detector will be included as a module in a self-learning algorithm which enables the working system's reference model to "tune" itself to its particular installation. In this study, a steady-state detector of a residential air conditioner based on moving windows was designed. Seven representing measurements were selected as key features for steady-state detection. The optimized moving window size and the feature thresholds was suggested through startup transient test and no-fault steady-state test. Performance of the steady-state detector was verified during indoor load change test. From the research, the general methodology to design a moving window steady-state detector was provided for vapor compression applications.