• Journal of Agricultural Extension & Community Development
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• v.4 no.1
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• pp.97-120
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• 1997

This study intends to develop a computer software for an efficient swineherd production and management. Current softwares are concerned on the sow management and ignore the actual farm environment. This study focuses on the farm environment in developing the software and covers the production management financial management, marketing management, and business planning for swineherd farm. The FSR(Farming Systems Research) analysis and interview survey aye applied to collect the data for the system planning, farmer's demand and analysis on the system, system design and program development. The systems are designed to meet the needs for the progressive swineherd farmers. Visual FoxPro 5.1 is used to develop the system. The developed system includes pig farm financial records keeping and management, pig farm production management program, pig farm marketing management program, and pig farm business diagnosis and planning program to meet the scope of the study. The weekly maintenance records and financial records are adopted for the input interface since most of farmers use their computer less than 5 hours a week. Pulldown Menu systems are adopted and designed for easy use by structuring to meet the pig farm and system demands. The manu system allocates the input-output screen based on the sectors, scopes, users, frequencies, importances, and the usages of the information. The GUI(Graphic User Interface) method is used to develop input-output screens for easy use. Backward Chaining mechanism fo the Expert System is used in the diagnosis of the pig farm management and the Systems Simulators Approach is used in the pig farm management planning.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.32.5-32
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• 2002

Processing plasmas are playing a crucial role in either depositing thin films or etching fine patterns. Any variability in process factors (such as radio frequency power or pressure) can cause a significant shift in plasma state. When this shift becomes large enough to change operating condition beyond an acceptable level, overall product quality can greatly be jeopardized. Thus, timely and accurate diagnosis of plasma malfunction is crucial to maintaining device yield and throughput. Many diagnostic systems have been developed, including HIPOCRATES [1] and PIES [2]. Plasma equipment was also diagnosed by combining neural network and expert system called Dempster-Schafer Theory [3]. A fact c...

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.295-300
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• 1998

In this paper, a real time diagnostic algorithm fur estimating the impact location by loose parts is proposed. It is composed of two modules such as the alarm discrimination module (ADM) and the impact-location estimation module(IEM). ADM decides whether the detected signal that triggers the alarm is the impact signal by loose parts or the noise signal. When the decision from ADM is concluded as the impact signal, the beginning time of burst-type signal, which the impact signal has usually such a form in time domain, provides the necessary data fur IEM. IEM by use of the arrival time method estimates the impact location of loose parts. The overall results of the estimated impact location are displayed on a computer monitor by the graphical mode and numerical data composed of the impact point, and thereby a plant operator can recognize easily the status of the impact event. This algorithm can perform the diagnosis process automatically and hence the operator's burden and the possible operator's error due to lack of expert knowledge of impact signals can be reduced remarkably. In order to validate the application of this method, the test experiment with a mock-up (flat board and reactor) system is performed. The experimental results show the efficiency of this algorithm even under high level noise and potential application to Loose Part Monitoring System (LPMS) for improving diagnosis capability in nuclear power plants.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.468-475
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• 2012

Nurses have performed their nursing practice according to the standard guidelines such as NANDA, NIC, and NOC, and recorded the information on nursing process into EMR system. In particular, NANDA, nursing diagnosis taxonomy, has difficulty expressing nursing diagnosis in detail because it represents abstract concepts of nursing diagnosis. So, the hospitals in KOREA have developed and used the list of nursing diagnosis on their own without referring the international standard terminologies, and it caused the delay of computerization of nursing records. Therefore, we proposed a ontology development methodology on nursing diagnosis based on NANDA and SNOMED-CT. The developed ontology, systematically developed with the frequently used nursing diagnosis terminologies in each hospital, based on the proposed methodology enables knowledge expansion and interoperable exchange of nursing records between EMR systems. We developed an ontology using the 112 nursing diagnosis terms defined by extracting and refining information on nursing diagnosis recorded in Kyungpook National University Hospital. We also confirmed the content validity and the usefulness of the developed ontology through expert assessment and experiment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.5
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• pp.835-841
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• 1997

Microscopic examination of the morphology of wear debris is an accepted method for machine condition and fault diagnosis. However wear particle analysis has not been widely accepted in industry because it is dependent on expert interpretation of particle morphology and subjective assessment criteria. This paper was undertaken to analyze the morphology of wear debris for machine condition diagnosis of the lubricated moving surfaces by image processing and analysis. The lubricating wear test was performed under different sliding conditions using a wear test device made in our laboratory and wear testing specimen of the pin-on-disk-type was rubbed in paraffine series base oil. In order to describe characteristics of debris of various shape and size, four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) have been developed and outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring, thus to overcome many of the difficulties in current methods and to facilitate wider use of wear particle analysis in machine condition monitoring.

• Tribology and Lubricants
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• v.17 no.2
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• pp.153-161
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• 2001

The development of techniques in diagnosing the state of the system is one of the essential tools in establishing the automation and unmanned manufacturing system for the realization of CIM/FMS in the fields. In this paper, we developed various diagnostic schemes for the journal bearing supported rotor system. Up to now, vibration of the shaft, measurement of the displacement and the temperature have been used for diagnostic tools, however, the statistical features only could not differentiate the state from states. Thus, we identified the sensor data f3r the steady state in the signal processing and then applied the fuzzy c-mean technology to cope with the nonlinear characteristics of the system. This will, in return, establish a possible diagnostic system for the rotor system in the fields.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.84-94
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• 1996

In order to prevent shell sticking by providing sufficient lubrication between the strand and the mold, the mold oscillation has been used. Now it is well known that the shape of the oscillation curve has a decisive effect on the surface quality of the cast product. Besides, oscillation parameters such as stroke and frequency are also very important. In order to guarantee that parameters which have been found to be optimal for a certain grade of steel do not change with time, periodical checks of the physical condition of the whole equipment are necessary. The portable mold oscillation analyzer with integrated computer, developed by POSCO, records the movement of the mold in every spatial direction. The system uses the gap sensors to measure the mold movement (displacement ) in the two horizontal directions according to the mold narrow and broad faces and the vertical strokes in the four corners of mold. The gap sensor is a non-contacting minute displacement measuring device using the principle of high frequency eddy current loss. The mold oscillation diagnosis system integrates the gap sensors, their converters and the industrial portable computer with plug-in data acquisition boards. The all programs, such as the fast Fourier transformation module (amplitude and phase spectrums) and harmonic analysis module, was coded by LabVIEW$^{TM}$ software as the graphical language. In an own 'expert module' which is included in the diagnosis program, one can obtain much information about the mold oscillation equipment.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.10
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• pp.1833-1840
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• 1992

In the diagnostic process for automobile, Neuro-Fuzzy technique was compared with the conventional diagnostic method for the verification of performance, and proto-type system was developed. For the utilities of the system, 1/3 octave filter(band-pass filter) and A/D converter were used for data acquisition and then data were analyzed using octave band processing and pattern recognition using hamming network algorithm. In order to raise the reliability of the diagnostic results by considering many operating variables and condition of automobile to be diagnosed, fuzzy inference technique was applied in combining several information. The validation of this diagnostic system was examined through computer simulation and experiment, and it showed an acceptable performance for diagnostic process.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.275-278
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• 2004

This paper focused on problems of design, construction, and maintenance caused by construction implementation processes. They were analyzed through case study of structure safety diagnosis projects. From the case study, it is expected that the introduction of Construction Management from the first stage of procurement will improve construction cost increase or burden on small design company. It strengthens coherent management from design and source contractor selection to build review of responsibility. The coherency will prevent changes in designing or infirm unreliable construction. It is desirable that expert opinions are considered when structure changes and establishment occur and that, if necessary, actions such as source selection, periodic audits, and diagnosis arc checked and fed back to maintenance.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.165-166
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• 2008

전력 텔레매트릭스 시스템은 전력계통의 사고에 신속하게 대처하고 계통설비의 합리적인 유지보수 및 운영을 통해 계통의 신뢰도를 높이고자 고안된 시스템이다. 이 시스템의 상위 HMI 부분은 MMS, CMD, FEA 등으로 나뉘어져 있는데 그중 CMD(Condition Monitoring Diagnosis) 시스템은 전력설비의 상태를 감시하고 진단하여 설비 유지보수에 도움을 주는 부분으로서 MMS과의 데이터 공유를 통하여 전력설비를 더욱 합리적으로 유지보수 및 운영할 수 있도록 하여주는 시스템이다. 본 논문에서는 이러한 CMD 시스템을 이루고 있는 핵심 알고리즘에 관하여 논할 것이다. 또한 개발된 알고리즘이 실제로 전력텔레매트릭스 시스템의 CMD 시스템에 삽입되어 현장 센서 테이터가 어떻게 이동이 되는지 보여 줄 것이다.