• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2597-2599
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• 2005

This research is developing the technique of troubleshooting in digital excitation system of nuclear power plant. and the design technique of excitation system is thought to be advanced through this research. Especially, the development of simulator enables to accumulate digital control technique, more analysis for excitation system algorithm. etc helps to develop other nuclear power plants.

• Journal of Environmental Impact Assessment
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• v.11 no.2
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• pp.109-116
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• 2002

The diagnostic and prognostic methods for generating 3 dimensional wind field were comparatively analyzed and 4 dimensional data assimilation (FDDA) technique by incorporating Automatic Weather System (AWS) into the prognostic methods was discussed for the urban scale air quality model. The A WS covered the urban scale grid distance of 10.6 km and 4.3 km in South Korea and Kyong-in region, respectively. This is representing that AWS for FDDA could be fairly well accommodated in prognostic model with the meso${\gamma}$~ microa scale (~5 km), indicating that the 3 dimensional wind field by FDDA technique could be a useful interpretative tool in urban area for the atmospheric environmental impact assessment.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.176-180
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• 2008

A field-oriented UHF system for on-line PD monitoring of transformers is designed, which has been installed inside the oil tank of transformer in a substation by two ways: on-line installing mode through the oil-valve and pre-installing mode through the man hole/hand hole cover. This system has successfully captured long intermittent discharge signals that hadn't been detected through conventional techniques, and solved the problem successfully. The results demonstrate that UHF technique has great advantages for on-line PD monitoring of transformers. By adopting the peak detection technique, it becomes easy and effective for the transplantation of the phase-resolved pattern recognition technique from conventional method to UHF method, and then to realize continuous on-line monitoring, source characterization and trending analysis.

• Journal of the Korea Safety Management & Science
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• v.17 no.1
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• pp.119-124
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• 2015

According as radiation therapy technique develops, standardization of radiation therapy has been complicated by the plan QA(Quality Assurance). However, plan QA tools are two type, OADT (opposite accumulation dose tool) and 3DADT (3 dimensional accumulation dose tool). OADT is not applied to evaluation of beam path. Therefore tolerance error of beam path will establish measurement value at OADT. Plan is six beam path, five irradiation field at each beam path. And beam path error is 0 degree, 0.2 degree, 0.4 degree, 0.6 degree, 0.6 degree, 0.8 degree. Plan QA accomplishes at OADT, 3DADT. The more path error increases, the more plan QA error increases. Tolerance error of OADT path is 0.357 using tolerance error of conventional plan QA. Henceforth plan QA using OADT will include beam path error. In addition, It will increase reliability through precise and various plan technique.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.51 no.1
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• pp.23-30
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• 2018

Kudoa septempunctata, a myxosporean parasite that infects olive flounder Paralichthys olivaceus is known to cause Kudoa food poisoning. Entire trunk muscle (ETM) is used for diagnosis of the parasite in fish and this method demands sacrifice of the host, causing a loss of commercial value. We developed a non-destructive method that uses a plastic syringe-style implanter to draw the sample, called the part-point muscle (PPM) sampling technique. We validated the PPM method in fish infected with K. septempunctata at the level detectable by the ETM method. We confirmed that the PPM method is equally sensitive in comparison to the ETM method for diagnosing K. septempunctata spores in olive flounder muscle. Our study also confirmed that the parasite is uniformly distributed in the dorsal muscle of infected fish. Over a period of 1 month, we observed no mortality of the host fish used for sampling by the PPM method. Thus, our studies demonstrate that the PPM sampling technique is an efficient, non-destructive method for diagnosing K. septempunctata in olive flounder.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3000-3005
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• 2015

Reliable monitoring and diagnosis of industrial processes is quite important for in terms of quality and safety. The goal of fault diagnosis is to find process variables responsible for causing specific abnormalities of the process. This work presents a classification-based diagnostic scheme based on nonlinear representation of process data. The use of a nonlinear kernel technique is able to reduce the size of the data considered and provides efficient and reliable representation of the measurement data. As a filtering stage a preprocessing is performed to eliminate unwanted parts of the data with enhanced performance. The case study of an industrial batch process has shown that the performance of the scheme outperformed other methods. In addition, the use of a nonlinear representation technique and filtering improved the diagnosis performance in the case study.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.1
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• pp.79-87
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• 2011

The fault detection technique of the grid-connected photovoltaic system using wavelet transform has been suggested in this paper. The additional hardware and sensors are required to detect the inverter failure in the conventional method, and it has the disadvantage of high cost and re-design problem if the inverter specification has been changed. The suggested method used the inverter voltage and current waveform to detect the failure and the location by the wavelet coefficients variations. The prompt and accurate diagnostic function is possible using the normalized standard deviation method. The merit of the proposed method is the simple calculation and precise diagnostic capabilities of the fault detection. The computer simulation is performed and the experimental result verifies the validity of the proposed method.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.48-54
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• 2019

This paper proposed a method of validation data augmentation for improving the grading accuracy of diabetic macular edema (DME) using deep learning. The data augmentation technique is basically applied in order to secure diversity of data by transforming one image to several images through random translation, rotation, scaling and reflection in preparation of input data of the deep neural network (DNN). In this paper, we apply this technique in the validation process of the trained DNN, and improve the grading accuracy by combining the classification results of the augmented images. To verify the effectiveness, 1,200 retinal images of Messidor dataset was divided into training and validation data at the ratio 7:3. By applying random augmentation to 359 validation data, $1.61{\pm}0.55%$ accuracy improvement was achieved in the case of six times augmentation (N=6). This simple method has shown that the accuracy can be improved in the N range from 2 to 6 with the correlation coefficient of 0.5667. Therefore, it is expected to help improve the diagnostic accuracy of DME with the grading information provided by the proposed DNN.

• Clinical Endoscopy
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• v.57 no.3
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• pp.283-292
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• 2024

We developed three e-learning systems for endoscopists to acquire the necessary skills to improve the diagnosis of early gastric cancer (EGC) and demonstrated their usefulness using randomized controlled trials. The subjects of the three e-learning systems were "detection", "characterization", and "preoperative assessment". The contents of each e-learning system included "technique", "knowledge", and "obtaining experience". All e-learning systems proved useful for endoscopists to learn how to diagnose EGC. Lecture videos describing "the technique" and "the knowledge" can be beneficial. In addition, repeating 100 self-study cases allows learners to gain "experience" and improve their diagnostic skills further. Web-based e-learning systems have more advantages than other teaching methods because the number of participants is unlimited. Histopathological diagnosis is the gold standard for the diagnosis of gastric cancer. Therefore, we developed a comprehensive diagnostic algorithm to standardize the histopathological diagnosis of gastric cancer. Once we have successfully shown that this algorithm is helpful for the accurate histopathological diagnosis of cancer, we will complete a series of e-learning systems designed to assess EGC accurately.

• Clinical Endoscopy
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• v.55 no.2
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• pp.197-207
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• 2022

Background/Aims: Endoscopic visualization of the microscopic anatomy can facilitate the real-time diagnosis of pancreatobiliary disorders and provide guidance for treatment. This study aimed to review the technique, image classification, and diagnostic performance of confocal laser endomicroscopy (CLE). Methods: We conducted a systematic review of CLE in pancreatic and biliary ducts of humans, and have provided a narrative of the technique, image classification, diagnostic performance, ongoing research, and limitations. Results: Probe-based CLE differentiates malignant from benign biliary strictures (sensitivity, ≥89%; specificity, ≥61%). Needle-based CLE differentiates mucinous from non-mucinous pancreatic cysts (sensitivity, 59%; specificity, ≥94%) and identifies dysplasia. Pancreatitis may develop in 2-7% of pancreatic cyst cases. Needle-based CLE has potential applications in adenocarcinoma, neuroendocrine tumors, and pancreatitis (chronic or autoimmune). Costs, catheter lifespan, endoscopist training, and interobserver variability are challenges for routine utilization. Conclusions: CLE reveals microscopic pancreatobiliary system anatomy with adequate specificity and sensitivity. Reducing costs and simplifying image interpretation will promote utilization by advanced endoscopists.