• Journal of the Korea Society of Computer and Information
• /
• v.26 no.11
• /
• pp.1-9
• /
• 2021

3D-NAND flash memory provides high capacity per unit area by stacking 2D-NAND cells having a planar structure. However, due to the nature of the lamination process, there is a problem that the frequency of error occurrence may vary depending on each layer or physical cell location. This phenomenon becomes more pronounced as the number of write/erase(P/E) operations of the flash memory increases. Most flash-based storage devices such as SSDs use ECC for error correction. Since this method provides a fixed strength of data protection for all flash memory pages, it has limitations in 3D NAND flash memory, where the error rate varies depending on the physical location. Therefore, in this paper, pages and layers with different error rates are classified into clusters through the K-means machine learning algorithm, and differentiated data protection strength is applied to each cluster. We classify pages and layers based on the number of errors measured after endurance test, where the error rate varies significantly for each page and layer, and add parity data to stripes for areas vulnerable to errors to provides differentiate data protection strength. We show the possibility that this differentiated data protection policy can contribute to the improvement of reliability and lifespan of 3D NAND flash memory compared to the protection techniques using RAID-like or ECC alone.

• Journal of Environmental Health Sciences
• /
• v.44 no.6
• /
• pp.548-555
• /
• 2018

Objectives: We conducted ecological risk assessment for cadmium, a heavy metal and carcinogen, to identify safety standards by environmental media and to determine its impact on ecosystems by estimating and evaluating exposure levels. Methods: Species sensitivity distributions (SSDs) were generated using ECOTOX DB. A hazardous concentration of 5% (HC5) protective of most species (95%) in the environment was estimated. Using this estimate, predicted no effect concentrations (PNECs) were calculated for aquatic organisms. Based on the calculated PNECs for aquatic organisms, PNEC values for soil and sediment were calculated using the partition coefficient. Predicted exposure concentrations (PECs) were also calculated from environmental monitoring data with hazard quotients (HQs) calculated using PNECs for environmental media. Results: Chronic toxicity data were categorized into four groups and 11 species. In species sensitivity distribution (SSD) analysis, HC5 was $0.340{\mu}g/L$. Based on this value, the PNEC value for aquatic organisms was calculated as $0.113{\mu}g/L$. PNEC values for soil and sediments using a partition coefficient were calculated as 15.02 mg/kg and 90.61 mg/kg, respectively. In an analysis of environmental monitoring data, PEC values were calculated as $0.017{\mu}g/L$ for water, 1.01 mg/kg for soil, and 0.521 mg/kg for sediment. Conclusions: HQs were 0.150, 0.067 and 0.006 for water, soil and sediment, respectively. HQs of secondary toxicity were 0.365 for birds and 0.024 for mammals. In principle, it is judged that an HQ above 1 indicates a high level of risk concern while an HQ less than 1 indicates an extremely low level of risk concern. Therefore, with HQs of cadmium in the environment being <1, its risk levels can be considered low for each media.