• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.945-948
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• 2005

Mobile computing devices are becoming increasingly prevalent in a huge range of physical area, offering a considerable market opportunity. The focus of this paper is on the development of a platform of fault diagnosis system integrating with personal digital assistant (PDA). An improvement of induction machine rotor fault diagnosis based on AI algorithms approach is presented. This network system consists of two parts; condition monitoring and fault diagnosis by using Artificial Intelligence algorithm. LabVIEW allows easy interaction between acquisition instrumentation and operators. Also it can easily integrate AI algorithm. This paper presents a development environment fur intelligent application for PDA. The introduced configuration is a LabVIEW application in PDA module toolkit which is LabVIEW software.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.219-223
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• 2001

Within a mechanical system such as an automotive the number of standard machine parts is increasing, so that the parts selection becomes more important than ever before. Selection of appropriate bearings in the preliminary design phase of a machine is also important. In this paper, three decision-making approaches are compared to find out a model that is appropriate to bearing selection problem. An artificial neural network, which is trained with real design cases, is used to select a bearing mechanism at the first step. Then, the subtype of the bearing is selected by the weighting factor method. Finally, types of peripherals such as lubrication methods are determined by a rule-based expert system.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.322-324
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• 2012

사람의 제어 없이 기기간에 통신하는 M2M(Machine to Machine) 통신은 우리의 삶의 중요한 부분으로 자리 잡아가고 있다. 특히 M2M의 한 부분으로써 헬스케어는 많은 연구가 진행되는 분야이다. 현재, 헬스케어 센서들은 환자의 상태를 모니터링하고 환자의 상태 정보를 의사에게 알려준다. 하지만, 만약 우리가 헬스케어 센서에 좀 더 지능성을 부여 할 수 있다면 환자가 위험 상황에 처하기 전 미리 판단하여 위험성을 의사에게 알려주어 보다 신속한 조치를 취하도록 할 수 있다. 본 논문에서는 M2M 네트워크의 헬스케어 시나리오에서 지능형 모바일 센서 에이전트의 구현을 설명한다. 이 센서 에이전트는 환자의 혈압을 측정하고 지능형 아답터와 매니저를 이용하여 원격의 의사에게 해당 정보를 알려준다.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1405-1414
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• 2014

The office management service platform configured with office's sensor devices, G/DSCL(Gateway/Device Service Capability Layer), NSCL(Network Service Capability Layer), and NA(Network Application). In this paper, we designed gateway resource tree and service scenario to fit the office management service and demonstrated appropriate operation of the office management service through intelligent functional modeling.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.244-249
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• 1997

Internal and external heat sources will cause to deform to machine elements in the contact joint of structure,which results in the change of contact pressure distribution different from initial assembly. Heat induced variations of contact pressure will change the static and dynamic properties such as contact stiffness,damping as well as contact heat conduction in the structure. In order to design and control the intelligent machine tool operating in variant conditions more sophisticatedly, the good prediction for the changes of prescribed propeties are strongly required especially in the contact elements adjacent to the rotational or linear bearing This paper presents some computational and experimental results in regard to static and dynamic characteristics of the press-fitted bush and shaft assembly which is a model of the bearing innerrace and shaft assembly. In the condition of heat generation on the outer surface of the bush,the effects of changes in the negative clearance and the heat flux on pressure distribution and dynamic properties are investigated. Results of this study show that the edge effect of the bush and the initial clearance have effects on the transient dynamic characteristics significantiy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.991-994
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• 2000

Recently, reliability engineering is regarded as the major field for aerospace and electronics, semiconductor related industry to improve safety and life cycle. And advanced manufacturing systems with high speed and intelligent have been developed for the betterment of machining ability In this case, reliability prediction has also important roll from design procedure to manufacturing and assembly process. Accordingly in this study, reliability evaluation system has been developed for prevention trouble. quality and life cycle improvement extremely for advanced mother machinary.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.122-129
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• 2006

The context-awareness has become the one of core technologies and the indispensable function. for application services in ubiquitous computing environment. In this research, we incorporated the capability of context-awareness in a music recommendation system. Our proposed system consists of such components as Intention Module, Mood Module and Recommendation Module. Among these modules, the Intention Module infers whether a user wants to listen to the music or not from the environmental context information. We built the Intention Module using data mining techniques such as decision tree, support vector machine and case-based reasoning. The results showed that the case-based reasoning model outperformed the other models and its accuracy was 84.1%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.457-462
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• 1995

This paper describes diagnosis strategy of the Flexible Multiple Fault Diagnosis Module for forecasting faults in system and deciding current machine state form sensor information. Most studydeal with diagnosis control stategy about single fault in a system, this studies deal with multiple fault diagnosis. This strategy is consist of diagnosis control module such as backward tracking expert system shell, various neural network, numerical model to predict machine state and communication module for information exchange and cooperate between each model. This models are used to describe structure, function and behavior of subsystem, complex component and total system. Hierarchical structure is very efficient to represent structural, functional and behavioral knowledge. FT(Fault Tree). ST(Symptom Tree), FCD(Fault Consequence Diagrapy), SGM(State Graph Model) and FFM(Functional Flow Model) are used to represent hierachical structure. In this study, IA(Intelligent Agent) concept is introduced to match FT component and event symbol in diagnosed system and to transfer message between each event process. Proposed diagnosis control module is made of IPC(Inter Process Communication) method under UNIX operating system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.563-564
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• 2006

In silicon wafer manufacturing process, the grinding process has been adopted to improve the flatness of water. The grinding of wafer is usually used by the infeed grinding machine. Grinding conditions are spindle speed, feed speed, rotation speed, grinding stone etc. But grinding condition selection and analysis is so difficult in grinding machine. In the intelligent grinding system based on knowledge many researchers have studied expert system, neural network, fuzzy etc. In this paper we deal grinding condition selection method, Taguchi method and Genetic Analysis.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.17-18
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• 2017

본 논문은 스마트 팩토리의 중요 요소인 무인반송차(AGV)를 자율 주행시키기 위해 오픈 소스 자율 주행차 시뮬레이터인 udacity를 이용해 머신 러닝시키는 시스템을 개발하였다. 공장의 운행 루트를 자율주행 시뮬레이터의 전경으로 가공하고, 3개의 카메라를 부착시킨 AGV를 운행시키면서 머신 러닝시킨다. AGV를 주행하여 얻어진 여러 학습 데이터를 통해 도출된 결과들을 각각 비교하여 우수한 모델을 선정하고 운행시킨 결과 AGV가 정해진 운행 루트를 정확하게 주행하는 것을 확인하였다. 이를 통해, 가상 운행 환경에서 저비용으로 AGV 운행 학습이 가능하다는 것을 보였다.