• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.11a
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• pp.285-288
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• 2006

Genetic Algorithms(GA) which searches optimum solution using natural selection and the law of heredity has been applied to teaming algorithms in order to estimate performance deterioration of the aircraft gas turbine engine. The compressor, gas generation turbine and power turbine are considered for estimation for performance deterioration of a complex component at design point was conducted. As a result of that, complex defect diagnostics has been conducted. As a result, the accuracy of diagnostics were verified with its relative error with in 10% at each component.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.1
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• pp.113-120
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• 2007

A new material was tested and its applicability was investigated so as to give the capability of self-diagnosis of fracture in composite mortar. In the research for giving self-diagnosis capability, conductive mortar intermixed with cokes and carbon fiber powder(milled carbon fiber) was developed and its using for self-diagnosis material was proposed. Then after examining change in the value of electric resistance and AE characteristics before and after the occurrence of cracks at each weight-stage, the relationships of each factors were analyzed. As the results, it can be recognized that a new composite material with cokes and carbon fiber powder(milled carbon fiber) can be applied for self-diagnosis of fracture in mortar specimen.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.236-239
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• 2004

현대의 다양한 심리적 갈등을 해결하기 위해 많은 연구가 진행되어지고 있다. 기존지 심리 진단 방식은 전문 상담인을 직접 찾아가서 상담을 받고 진단해야 하는 등에 여러 과정을 거쳐야만 했다. 본 논문에서는 이러한 복잡한 과정을 거치지 않고 온라인상에서 사용자의 상태를 입력하면 퍼지 추론을 이용하여 현재 사용자의 심리상태를 파악하여 진단하는 진단시스템을 구성하였다. 또한 공격적 추론과 퇴행적 추론을 모두 고려한 복합추론으로 결과 값을 도출하는 방법을 제안하였고, 제안된 추론법을 심리진단 시스템에 적용하였다.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.53-60
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• 2014

With the rapid development of IT technology, recently, the development of IT convergence technology related to the facility diagnosis is prevalent, and the study for the efficient integrated management scheme is required to handle all relevant information, from the design to the maintenance, including the stage of repair. In this paper, an efficient scheme to process the complex data for the facility and its diagnosis is proposed based on IT convergence technique and the real-time complex data management is designed. In order to evaluate the performance of the proposed system, the real-time management system is designed for a particular facility, and the comparative results show the good performance of the proposed system.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.11-26
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• 2009

In order to diagnose cardiovascular disease, we proposed EP-based(emerging pattern- based) classification technique using multi-parametric diagnosis indexes. We analyzed linear/nonlinear features of HRV for three recumbent postures and extracted four diagnosis indexes from ST-segments to apply the multi-parametric diagnosis indexes. In this paper, classification model using essential emerging patterns for diagnosing disease was applied. This classification technique discovers disease patterns of patient group and these emerging patterns are frequent in patients with cardiovascular disease but are not frequent in the normal group. To evaluate proposed classification algorithm, 120 patients with AP (angina pectrois), 13 patients with ACS(acute coronary syndrome) and 128 normal people data were used. As a result of classification, when multi-parametric indexes were used, the percent accuracy in classifying three groups was turned out to be about 88.3%.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• v.y2005m4
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• pp.248-251
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• 2005

In this paper, health monitoring technique has been studied for performance deterioration caused by the defects of the gas turbine. The parameters for performance diagnostics have been extracted by using GSP program for modeling the target engine. The virtual sensor model for the health monitoring has been built of those data. The position and magnitude of the defects of the engine components have been determined by using Multiple Linear Regression technique and the method using the weight in order to diagnose the single and multiple defects.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.353-358
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• 2021

Parkinson's disease is the second most common degenerative brain disease after Alzheimer's in old age. Symptoms of Parkinson's disease are factors that reduce the quality of life in daily life, such as shaking hands, slowing behavior and cognitive function. Parkinson's disease that can slow the progression of the disease through early diagnosis. To diagnoze Parkinson's disease early, an algorithm was implemented to extract features using wav2vec and to diagnose the presence or absence of Parkinson's disease with deep learning(ANN). As a results of the experiment, the accuracy was 97.47%. It was better than the results of diagnosing Parkinson's disease using the existing neural network. The audio voice file could simply reduce the experiment process and obtain improved results.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.3
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• pp.134-141
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• 2011

There have been increased economic and societal demands to continuously monitor the integrity and long-term deterioration of civil infrastructures to ensure their safety and adequate performance throughout their life span. However, it is very difficult to continuously monitor the structural condition of the pipeline structures because those are placed underground and connected each other complexly, although pipeline structures are core underground infrastructures which transport primary sources. Moreover, damage can occur at several scales from micro-cracking to buckling or loose bolts in the pipeline structures. In this study, guided wave measurement can be achieved with a self-sensing circuit using a piezoelectric active sensor. In this self sensing system, a specific frequency-induced structural wavelet response is obtained from the self-sensed guided wave measurement. To classify the multiple types of structural damage, supervised learning-based statistical pattern recognition was implemented using the damage indices extracted from the guided wave features. Different types of structural damage artificially inflicted on a pipeline system were investigated to verify the effectiveness of the proposed SHM approach.

• Journal of Digital Convergence
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• v.13 no.7
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• pp.249-258
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• 2015

This study was conducted to determine the affecting factors among patients with drinking behavior of liver cirrhosis. Data were collected by questionnaire from 157 patients who were diagnosed with liver cirrhosis at a tertiary hospital located in D-city. Measurements included patients' demographic characteristics, clinical characteristics, disease-related of symptom experience, emotional-factors of anxiety-depression and social-factor of social support. Data were analyzed using t-test, and logistic regression analyses. The incidence rate of drinking behavior was 31.8%. Multivariate analysis revealed that smoking(yes), men, symptom experience, social support and anxiety were more likely to report high level of drinking behavior. Future research should consider managing drinking behavior as an essential component of comprehensive care for patients with liver cirrhosis.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.1
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• pp.113-121
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• 2019

In this study, self - healing microcapsules which can be mixed directly with cement composites were prepared, and the quality and crack healing performance of cement composites with self - healing microcapsules were evaluated. In the past, it has been focused on evaluating self-healing capsules and crack healing properties. Therefore, self - healing microcapsules have been studied for their effect on the quality of cement composites when mixed with cement composites. The table flow and the air flow rate of the cement composite material mixed with self-healing microcapsules were found to have no significant influence on table flow and air volume regardless of mixing ratio. Compressive strength and splitting tensile strength tended to decrease with increasing capsule mixing ratio. As a result of evaluation of crack healing properties according to water flow, initial water permeability decreased, and reaction products were generated over time and cracks were healed.