• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.507-509
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• 2022

자동차 내부 진단 데이터를 수집하기 위해서는 다양한 자동차 부품에 포함되어 있는 ECU(Electronic Control Unit)의 진단데이터를 수집하여야 한다. ECU의 진단데이터를 수집하기 위해서는 진단통신을 활용할 수 있다. 본 논문에서는 표준 진단 통신을 통해 ECU의 기능에 따른 진단데이터를 수집하는 방법과 진단통신 모듈에 대해서 분석하였다. 많은 자동차 제조사가 사용하는 자동차 전장 표준인 AUTOSAR의 표준 모듈 중에서 진단 통신 모듈에 대해서 연구하였으며, 진단데이터 처리가 ECU를 통해 처리되는 과정에 대해서 연구하였다.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2006년도 제33회 추계학술대회 발표논문집
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• pp.151-151
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• 2006

• 한국임상수의학회:학술대회논문집
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• 한국임상수의학회 2009년도 추계학술대회
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• pp.240-240
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• 2009

• 한국임상수의학회:학술대회논문집
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• 한국임상수의학회 2009년도 추계학술대회
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• pp.239-239
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• 2009

• Journal of Veterinary Science
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• 제19권6호
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• pp.850-854
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• 2018

Novel H5N6 highly pathogenic avian influenza viruses (HPAIVs) were isolated from duck farms and migratory bird habitats in South Korea in November to December 2017. Genetic analysis demonstrated that at least two genotypes of H5N6 were generated through reassortment between clade 2.3.4.4 H5N8 HPAIVs and Eurasian low pathogenic avian influenza virus in migratory birds in late 2017, suggesting frequent reassortment of clade 2.3.4.4 H5 HPAIVs and highlighting the need for systematic surveillance in Eurasian breeding grounds.

• 대한수의학회지
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• 제62권2호
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• pp.14.1-14.5
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• 2022

Salmonella enterica serotype Choleraesuis causes swine paratyphoid, with clinical findings of enterocolitis and septicemia. However, the clinicopathological features of S. Choleraesuis infections in pigs have not been reported in Korea. We describe the pathological findings of two weaned pigs with S. Choleraesuis infections, presenting with diarrhea, cough, and sudden death. Pathological examination indicated severe necrotic colitis in pig 1 and septicemic lesions in pig 2. Multidrug-resistant S. Choleraesuis was isolated from the pigs' lungs and intestinal contents. Further research is required for the surveillance of S. Choleraesuis infections in pigs and the virulence estimation in the S. Choleraesuis isolates.

• 대한전기학회논문지:전력기술부문A
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• 제54권9호
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• pp.449-456
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• 2005

The preventive diagnostic technique prevents transformers from power failure through giving alarm and observing transformers in service. And it helps to establish the plan for optimum maintenance of the transformer as well as to find location or cause of fault using accumulated data. Data detection and experience of the preventive diagnostic system need to establish the preventive diagnostic algorithm regarding interrelationship between detected data and deterioration of equipment. Therefore in-depth analysis about the preventive diagnosis system is required. KEPCO has adopted the preventive diagnostic system at nine 345kV substations since 1997. Techniques for component sensors of the preventive diagnosis system were settled but diagnosis algorithm, diagnostic criteria and practical use of accumulated data are not yet established. This paper, to build up the base of preventive diagnostic algorithm for the Power transformer. investigated the preventive diagnostic criteria for the power transformer.

• 전기학회논문지P
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• 제54권2호
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• pp.94-100
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• 2005

Abnormal symptoms on operating conditions of power transformer are monitored by a preventive diagnostic system which prevents the sudden power failure in case of quick progress of abnormal situation. The preventive diagnostic system helps plan the proper maintenance method according to the transformer conditions via accumulated data. KEPCO has adopted the preventive diagnostic system at nine of 345kV substations since 1997. Application techniques of the diagnostic sensors were settled, but diagnostic algorithm and practical use of accumulated data are not yet established. To build up the diagnostic algorithm and effective use of the preventive diagnostic system, the reliability of the data which were accumulated in a server computer is very important. This paper describes the data analysis in the server in order to advance the reliability of the accumulated data of the preventive diagnostic system. The principles and data flows of the diagnostic sensors were analyzed, and the data discrepancy between sensors and server were calibrated.

• Nuclear Engineering and Technology
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• 제54권4호
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• pp.1271-1287
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• 2022

When abnormal operating conditions occur in nuclear power plants, operators must identify the occurrence cause and implement the necessary mitigation measures. Accordingly, the operator must rapidly and accurately analyze the symptom requirements of more than 200 abnormal scenarios from the trends of many variables to perform diagnostic tasks and implement mitigation actions rapidly. However, the probability of human error increases owing to the characteristics of the diagnostic tasks performed by the operator. Researches regarding diagnostic tasks based on Artificial Intelligence (AI) have been conducted recently to reduce the likelihood of human errors; however, reliability issues due to the black box characteristics of AI have been pointed out. Hence, the application of eXplainable Artificial Intelligence (XAI), which can provide AI diagnostic evidence for operators, is considered. In conclusion, the XAI to solve the reliability problem of AI is included in the AI-based diagnostic algorithm. A reliable intelligent diagnostic assistant based on a merged diagnostic algorithm, in the form of an operator support system, is developed, and includes an interface to efficiently inform operators.

• 대한수의학회지
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• 제54권4호
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• pp.257-260
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• 2014

A calf suffering from diarrhea was admitted to the Animal and Plant Quarantine Agency for diagnostic evaluation. Postmortem examination revealed that the mesenteric lymph node was enlarged and small intestine wall was thin. Microscopically, a large number of small round organisms were attached to the small intestine villi. Villous atrophy and proprial neutrophil infiltration were also observed. Based on modified Ziehl-Neelsen staining, electron microscopy, and ELISA results, the calf was diagnosed with fatal cryptosporidiosis.