RRSD: A file replication method for ensuring data reliability and reducing storage consumption in a dynamic Cloud-P2P environment

2019 ◽  
Vol 100 ◽  
pp. 844-858 ◽  
Author(s):  
ShengYao Sun ◽  
WenBin Yao ◽  
BaoJun Qiao ◽  
Ming Zong ◽  
Xin He ◽  
...  
Author(s):  
S. Basu ◽  
D. F. Parsons

We are approaching the invasiveness of cancer cells from the studies of their wet surface morphology which should distinguish them from their normal counterparts. In this report attempts have been made to provide physical basis and background work to a wet replication method with a differentially pumped hydration chamber (Fig. 1) (1,2), to apply this knowledge for obtaining replica of some specimens of known features (e.g. polystyrene latex) and finally to realize more specific problems and to improvize new methods and instrumentation for their rectification. In principle, the evaporant molecules penetrate through a pair of apertures (250, 350μ), through water vapors and is, then, deposited on the specimen. An intermediate chamber between the apertures is pumped independently of the high vacuum system. The size of the apertures is sufficiently small so that full saturated water vapor pressure is maintained near the specimen.


Micromachines ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 879
Author(s):  
Ruiquan He ◽  
Haihua Hu ◽  
Chunru Xiong ◽  
Guojun Han

The multilevel per cell technology and continued scaling down process technology significantly improves the storage density of NAND flash memory but also brings about a challenge in that data reliability degrades due to the serious noise. To ensure the data reliability, many noise mitigation technologies have been proposed. However, they only mitigate one of the noises of the NAND flash memory channel. In this paper, we consider all the main noises and present a novel neural network-assisted error correction (ANNAEC) scheme to increase the reliability of multi-level cell (MLC) NAND flash memory. To avoid using retention time as an input parameter of the neural network, we propose a relative log-likelihood ratio (LLR) to estimate the actual LLR. Then, we transform the bit detection into a clustering problem and propose to employ a neural network to learn the error characteristics of the NAND flash memory channel. Therefore, the trained neural network has optimized performances of bit error detection. Simulation results show that our proposed scheme can significantly improve the performance of the bit error detection and increase the endurance of NAND flash memory.


Nanomaterials ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 822
Author(s):  
Christine Thanner ◽  
Martin Eibelhuber

Ultraviolet (UV) Nanoimprint Lithography (NIL) is a replication method that is well known for its capability to address a wide range of pattern sizes and shapes. It has proven to be an efficient production method for patterning resist layers with features ranging from a few hundred micrometers and down to the nanometer range. Best results can be achieved if the fundamental behavior of the imprint resist and the pattern filling are considered by the equipment and process parameters. In particular, the material properties and pattern size and shape play a crucial role. For capillary force-driven filling behavior it is important to understand the influencing parameters and respective failure modes in order to optimize the processes for reliable full wafer manufacturing. In this work, the nanoimprint results obtained for different pattern geometries are compared with respect to pattern quality and residual layer thickness: The comprehensive overview of the relevant process parameters is helpful for setting up NIL processes for different nanostructures with minimum layer thickness.


PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e104798 ◽  
Author(s):  
Alberto Pepe ◽  
Alyssa Goodman ◽  
August Muench ◽  
Merce Crosas ◽  
Christopher Erdmann

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