• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.71-72
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• 2005

Ship system is very complicated. Machine in ship system are in close connection with each other, so one is affected by others. Thus, person who want to be a marine engineer have to study not only each machine but also their relationship. For this, intelligent diagnosis system for advanced education is necessity. In this paper, AMS and failure diagnosis system is developed by using LabVIEW, G programming language.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.39-52
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• 2002

Research Direction The significant research direction in mechanical fault diagnosis area: Theorles and approaches for fault feature extracting and fault classification. Identification Complicated fault generating mechanism and its model Intelligent fault diagnosis system (including the expert system and network based remote diagnosis system) One of the Key Points： Fault feature extracting techniques based on (modern) signal processing(omitted)

• Proceedings of the Polymer Society of Korea Conference
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• 2006.10a
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• pp.78-79
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• 2006

Bio-nanotechnology challenges have been emerging in development of molecular and cellular intelligent bio-materials, engineered cells for enhancing intelligence, biodevices for diagnosis and prevention, and biodevices for therapeutics and prevention. The perspectives of bionanotechnology challenges are overviewed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.257-260
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• 1996

This study is about the construction of algorithm for selecting Yongshin of the Four Pillars. To emulate the method the expert uses when he select the Yongshin, we introduce the Hopfield Network. The result of the simulation classified with Yongshin is presented.

• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.559-564
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• 2008

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.243-246
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• 2006

본 논문에서는 모발내에 있는 약 30여가지의 생체 미네랄과 8가지의 중금속 정보 분석을 통해 생체내에 양양상태의 과잉, 결핍 및 불균형 상태를 평가하고, 그 결과가 현재 생체에 미치는 영향을 예측하여, 건강을 유지하는 방향을 제시할 수 있는 의료용 지능적 의학진단 시스템을 구축하였다. 이 논문에서는 생체내 미네랄 정보를 다중 퍼지규칙베이스 시스템으로 구축함으로써 환자에게 보다 효율적으로 치료와 예방방법을 제시할 수 있는 의학진단시스템을 구축하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.1-8
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• 2004

In this paper, we propose neural network-based fault diagnosis method to diagnose of sensor in the gas monitoring system. In the proposed method, using thermal modulation of operating temperature of sensor, the signal patterns are extracted from the voltage of load resistance. Also, ART2 neural network is used for fault isolation. The performance and effectiveness of the proposed ART2 neural network based fault diagnosis method are shown by simulation results using real data obtained from the gas monitoring system.

• Journal of Intelligence and Information Systems
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• v.13 no.1
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• pp.81-90
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• 2007

This paper shows an intelligent disease diagnosis system for public. Our system deals with 30 diseases and their typical symptoms selected based on the report from Ministry of Health and Welfare, Korea. Technically, the system uses a modified FCM algorithm for clustering diseases and the input vector consists of the result of user-selected questionnaires. The modified FCM algorithm improves the quality of clusters by applying symmetrically measure based on the fuzzy theory so that the clusters are relatively sensitive to the shape of the pattern distribution. Furthermore, we extract the highest 5 diseases only related to the user-selected questionnaires based on the fuzzy membership function between questionnaires and diseases in order to avoid diagnosing unrelated disease.

• Journal of Biomedical Engineering Research
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• v.38 no.5
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• pp.227-231
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• 2017

Early diagnosis of pancreatic cancer had been considered one of the important barrier for successful therapy since the five year survival rate after treatment of pancreatic cancer was critically low. Nonetheless, patients often miss the golden time of treatment because they rarely visit the hospital until their symptoms are severe. To overcome these problems, a lot of information about the patient's symptoms should be applied as biomarkers for early diagnosis. For this reason, a biomarker for early detection of pancreatic cancer (CA19-9) has been developed as a diagnostic kit. However, since the diagnosis is not accurate enough, pancreatic symptoms (abdominal pain, jaundice, anorexia, diabetes, etc.) and biomarkers (CA19-9) should be considered together. We develop an intelligent diagnostic system that considers CA19-9 and the incidence of pancreatic cancer for pancreatic symptoms that was determined by studying a large number of patient information. It shows a higher accuracy than one using CA19-9 alone. It may increase the survival rate of pancreatic cancer because it can diagnose pancreatic cancer early.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.1
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• pp.13-23
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• 1996

Weld defects degrade the strength and safety of astructure and are resulted from the various cases. The complexity of causal relation of weld defects requires an expert for the analysis of weld defects and the measures counter to them. An expert system has the intelligent functions such as the representation of knowledge and the inference. On this research, weld defect are systematically analysed and their causal model is developed. This information is saved to the knowledge base. The suitable inference algorithm for the diagnosis of weld defects is developed and realized with C++ programming.