• 전기학회논문지
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• 제56권10호
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• pp.1852-1858
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• 2007

To Increase availability and to enhance the safety, the modernization of Instrumentation & Control (I&C) systems is considered. The extended use of the digital technology lets nuclear power plants(NPPs) to replace their old analog systems with some proven digital systems. To adapt digital equipment to plants effectively and systematically, however, there must be an essential prerequisite, which is to evaluate current I&C equipment. This paper shows a practical methodology to evaluate the current status and reliability of I&C systems of NPPs using Reliability Evaluation System(RES) before performing upgrades or replacements for systems. The proposed method was applied to KORI Unit 2. The proposed method shows the current status of operating I&C systems effectively for upgrading I&C systems.

• 한국태양에너지학회 논문집
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• 제39권6호
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• pp.93-112
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• 2019

In this paper, a very new web-based software for renewable energy system (RES) design and economic evaluation was introduced. This solution would provide the precise RES estimation service including not only photovoltaic (PV), wind turbine (WT) and fuel cell (FC) individually but also energy storage system (ESS) as combined forms with PV or WT. The three reasons why we ought to develop it are: First, the standardized tool suitable to the domestic environment for estimating power generation from RES facilities and economic evaluation is required. Secondly, the standardized tool is needed to spread domestic RES supply policy and to promote the new industry in the micro-grid field. The last, the reliability of economic evaluation should be enhanced more for new facilities. To achieve those aims, the weather database of one hundred locations have established and the RES facility database has also constructed. For the energy management, mathematical models for PV, WT, ESS and FC were developed. As a final phase, the analytical process to evaluate economics has performed with field data verification.

• 대한의용생체공학회:의공학회지
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• 제44권3호
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• pp.182-189
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• 2023

CT is a medical device that acquires medical images based on Attenuation coefficient of human organs related to X-rays. In addition, using this theory, it can acquire sagittal and coronal planes and 3D images of the human body. Then, CT is essential device for universal diagnostic test. But Exposure of CT scan is so high that it is regulated and managed with special medical equipment. As the special medical equipment, CT must implement quality control. In detail of quality control, Spatial resolution of existing phantom imaging tests, Contrast resolution and clinical image evaluation are qualitative tests. These tests are not objective, so the reliability of the CT undermine trust. Therefore, by applying an artificial intelligence classification model, we wanted to confirm the possibility of quantitative evaluation of the qualitative evaluation part of the phantom test. We used intelligence classification models (VGG19, DenseNet201, EfficientNet B2, inception_resnet_v2, ResNet50V2, and Xception). And the fine-tuning process used for learning was additionally performed. As a result, in all classification models, the accuracy of spatial resolution was 0.9562 or higher, the precision was 0.9535, the recall was 1, the loss value was 0.1774, and the learning time was from a maximum of 14 minutes to a minimum of 8 minutes and 10 seconds. Through the experimental results, it was concluded that the artificial intelligence model can be applied to CT implements quality control in spatial resolution and contrast resolution.