• Journal of the Korean Institute of Gas
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• v.8 no.2 s.23
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• pp.28-34
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• 2004

Enhanced methodologies for process diagnosis and abnormal situation management have been developed for the last two decades. However, there is no single method that always shows better performance over all kinds of diagnostic problems. In this paper, a framework of message-passing, cooperative, intelligent diagnostic agents is presented for improved on-line fault diagnosis through cooperative problem solving of different expertise. A group of diagnostic agents in charge of different process functional perform local diagnoses in parallel; exchange related information with other diagnostic agents; and cooperatively solve the global diagnostic problem of the whole process plant or business units just like human experts would do. For their better understanding, sharing and exchanging of process knowledge and information, we also suggest a way of remodeling processes and protocols, taking into account semantic abstracts of process information and data. The benefits of the suggested multi-agents-based approach are demonstrated by the implementations for solving the diagnostic problems of various chemical processes.

• Proceedings of the Korean Society of Veterinary Clinics Conference
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• 2009.04a
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• pp.306-306
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• 2009

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1137-1140
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• 2005

Automatic welding has been used frequently on pipeline projects. The productivity and reliability are most essential features of the automatic welding system. The mechanized GMAW process is the most widely used welding process and the carriage and band system is most effective welding system for pipeline laying. This application-oriented paper introduces new automatic welding equipment for pipeline construction. It is based on cutting-edge design and practical welding physics to minimize downtime. This paper also describes the control system which was designed and implemented for new automatic welding equipment. The system has the self diagnostic function which facilitates maintenance and repairs, and also has the network function via which the welding task data can be transmitted and the welding process data can be monitored. The laser vision sensor was designed for narrow welding groove in order to implement higher accuracy of seam tracking and fully automatic operation.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.20 no.1
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• pp.1-13
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• 2016

Objectives The aim of this study is to develop diagnostic and assessable questionnaires for cervical movement system impairment syndromes. Methods We reviewed the previous study and literature, and organized various checkable items for differential diagnosis of four different cervical movement system impairment syndromes. Next, we selected items which can be developed as questionnaire items. Finally, we conducted a face validity study with twelve Korean medical doctors and carried out survey research to evaluate the importance score of the items with three experts. Results We developed a diagnostic and assessable questionnaire as follows: 9 items for cervical extension syndrome; 5 items for cervical flexion syndrome; 9 items for cervical rotation syndrome. By conducting 2 rounds of survey research, we were able to bridge the differences in the importance score of each item. Conclusions A questionnaire for the diagnosis and assessment of movement system impairment syndromes was developed. This questionnaire holds promising applications for objective diagnosis and assessment of cervical movement system impairment syndromes. This tool may also be used for detecting the sub-health status of musculoskeletal systems.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.685-686
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• 2007

This paper presents an application of power system fault diagnostic algorithm for the PEFP Proton Accelerator Research Center using neural network. Proposed fault diagnostic system is constructed by the radial basis function (RBF) neural network because it has the capabilities of the pattern classification and function approximation of any nonlinear function. Proposed system identifies faulted section in the power system based on information about the operation of protection devices such as relays and circuit breakers. In this paper, parameters of the RBF neural networks are tuned by the GA-TS algorithm, which has the global optimal solution searching capabilities. To show the validity of the proposed method, proposed algorithm has been tested with a practical power system in Proton Accelerator Research Center of PEFP.

• Journal of The Korean Radiological Technologist Association
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• v.30 no.1
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• pp.58-62
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• 2004

The purpose of this study was to determine the factors influencing on the size of Radiofrequency ablation using an internally cooled needle electrodes in cattle liver. Ablation procedures involved the use of cool-tip RF system generator and internally coo

• Korean Journal of Veterinary Service
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• v.41 no.3
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• pp.211-216
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• 2018

Heat stroke in a dog is a life-threatening syndrome characterized by a high body temperature over $41^{\circ}C$, by the central nervous system dysfunction, and by multiple organ dysfunction. A 11-month-old male American Pit Bull Terrier was presented to clarify the cause of death to diagnostic laboratory. This dog showed clinical signs such as high body temperature ($42^{\circ}C$), severe tachypnea, hematochezia, epistaxis and hemoptysis after transportation at hot summer time. At necropsy, there were hemorrhages in skin, serosa of stomach and small intestine, and also dark red fluid in lumen of intestine. Histopathologic examination revealed extensive hemorrhages in stomach, muscle, skin, and tongue. In microbiology, pathologic bacteria such as Pasteurella, Boedetella, Salmonella, Clostridium, and circulating virus in Korea such as CDV, CIV, CAV, CHV, CCV, CPIV were negative except CPV. There were many gross and microscopic lesions suggesting hest stroke while pathologic agents and related lesions were not detected. Therefore we diagnosed this case as heatstroke.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.55-62
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• 2004

In this paper, the diagnostic expert system for silicone oil-filled transformer is developed using dissolved gas analysis(DGA). There are many diagnostic methods for diagnostic oil-immersed transformer. But DGA is used to the proposed expert system since it has been verified that DGA is very efficient diagnostic method for transformer. In addition, it is resonable that fuzzy rule, degree of inclusion and fuzzy measure must be considered to handle the uncertainty nature of gas boundary and rules. The proposed expert system consists of knowledge base module, inference engine module and human-machine interface(HMI) module. The knowledge base module consists of the knowledge using the rule. The inference engine module is used to the fuzzy rule. The history of the transformer gas data is managed by the database. the effect of the proposed expert system is verified by case studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.3029-3034
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• 2014

The paper describes the scleral diagnostic system implementation for human eyes by using the scleral color code and vessels sign pattern code generations. The system is based on the high performance DSP image signal processor, programmable gain control for preprocessing and RISC SD frames storage. RGB image signals are optimized by PGC, the edge image is detected form the gray image converted. The processing algorithms are executed by scleral color code generation and scleral vessels sign pattern code creation for discriminating and matching. The scleral symptomatic color code is generated by YCbCr values at memory map tolerated and the vessel sign pattern code is created by digitizing the 24 clock and 13 ring zones, overlay matching and tolerances. The experimental results for performance are that the system runs 40ms, and the color and pattern for diagnostic errors are around 20% and 24% on average. The system and technique enable a scleral diagnosis with subdividing the patterns and patient database.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.675-680
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• 2012

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around the world. Wind farms are adding a significant amount of electrical generation capacity. The increase in the number of wind farms has led to the need for more effective operation and maintenance. CMS(Condition Monitoring System) can be used to aid plant operator in achieving these goals. Its aim is to provide operators with information regarding th e health of their machine, which in turn, can help them improve operation efficiency. In this work, wind turbine fault diagnostic algorithm which can diagnose the mass unbalance and aerodynamic asymmetry of the blades is proposed. Proposed diagnostic algorithm utilizes both FFT(Fast Feurier Transform) of the signal from accelerometers installed inside of nacelle and simple diagnostic logic. Furthermore, to verify the applicability of the proposed system, 3W small sized wind turbine system is tested and physical experiments are carried out.