• Nuclear Engineering and Technology
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• v.36 no.6
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• pp.485-496
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• 2004

Typical probabilistic safety assessment (PSA) results were used to estimate the performance indicator (PI) thresholds of unplanned reactor scram (URS) and safety system unavailability (SSU) for Korean nuclear power plants (NPPs). The changes in core damage frequency (${\Delta}$CDFs) of $10^{-6}/yr$, $10^{-5}/yr$, and $10^{-4}/yr$ were adopted as the risk criteria in setting up the PI thresholds. The PI thresholds for the URS were estimated using information pertaining to the initiating event frequencies, the CDF, and the CDF contribution of each initiating event. The PI thresholds of the SSU were estimated using information on the unavailability, the Fussell-Vesely importance, and the CDF.

• Nuclear Engineering and Technology
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• v.43 no.2
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• pp.105-132
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• 2011

The concept of improved performance indicators (PIs) for use in the KINS Safety Performance Indicator (SPI) program for reactor safety area is proposed in this paper. To achieve this, the recently developed PIs from the USNRC that use risk information were investigated, and a feasibility study for the application of these PIs in Korean NPPs was performed. The investigated PIs are Baseline Risk Index for Initiating Events (BRIIE), Unplanned Scrams with Complications (USwC), and Mitigating System Performance Index (MSPI). Moreover, the thresholds of the existing safety performance indicators of KINS were evaluated in consideration of the risk and regulatory response to different levels of licensee performance in the graded inspection program.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.159-164
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• 2024

Net surplus serves as a crucial indicator of how efficiently local governments utilize their resources. This study aims to analyze and categorize the patterns of net surplus across 75 local governments in Korea. By employing machine learning techniques such as K-means clustering and silhouette analysis, this research delves into surplus patterns, revealing insights that differ from those provided by traditional analytical methods. Machine learning enables a broader spectrum of discoveries, leading us to identify three distinct clusters in the net surplus of Korean local finances. The characteristics of these three clusters show that the wealthiest cities have the highest surplus ratios. In contrast, mid-sized municipalities, constrained by limited central government support and scarce local resources, exhibit the lowest surplus ratios. Interestingly, a significant number of cities maintain a median surplus ratio even under challenging fiscal conditions. Additionally, we identify critical thresholds that differentiate the three clusters: a grant-in-aid ratio of 19.31%, a debt ratio of 3.52%, and a local tax ratio of 25.58%. This identification of thresholds is a key contribution of our study, as these specific thresholds have not been previously addressed in the literature.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1441-1461
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• 2017

Nowadays, Dynamic Adaptive Streaming over HTTP (DASH) has become very popular in streaming multimedia contents. In DASH, a client estimates current network bandwidth and then determines an appropriate video quality with bitrate matching the estimated bandwidth. Thus, estimating accurately the available bandwidth is a significant premise in the quality of video streaming, especially when network traffic fluctuates substantially. To cope with this challenge, researchers have presented various filters to estimate network bandwidth adaptively. However, experiment results show that current schemes either adapt slowly to network changes or adapt fast but are very sensitive to delay jitter and produce sharply changed estimation. This paper presents a novel bandwidth estimation scheme based on Moving Average Convergence Divergence (MACD). We applied an MACD indicator and its two thresholds to classifying network states into stable state and agile state, based on the network state different filters are applied to estimate network bandwidth. In the paper, we studied the performance of various MACD indicators and the threshold values on bandwidth estimation. Then we used a DASH proxy-based environment to compare the performance of the presented scheme with current well-known schemes. The simulation results illustrate that the MACD-based bandwidth estimation scheme performs superior to existing schemes both in the speed of adaptively to network changes and in stability in bandwidth estimation.