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Routing algorithms are known to be potential bottlenecks for packet processing. Network ow caching can function as a general acceleration technique for packet processing workloads. The goal of this article is to evaluate the effectiveness of packet ow caching techniques in high-speed networks. The area of focus is the data distribution characteristics that lead to the effectiveness of caching network ows (connections). Based on a statistical analysis and simulations, the article sets the necessary conditions for the effective use of caches in packet forwarding applications. Public domain network traces were examined and measured for data locality. Software simulations show a strong correlation between the ow packet distance metrics and the cache hit rate.
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The main goal of this work was to implement a reliable machine learning algorithm that can classify the age of a dog, given only a photograph of its face. The problem, which seems simple for humans, presents itself as very difficult for the machine learning algorithms due to differences of facial features among the dogs population. As convolutional neural networks (CNNs) performed poorly in this problem, authors took other approach of creating novel architecture consisting of combination of CNN and vision transformer (ViT) and examining the age of the dogs separately for every breed. Authors were able to achieve better results than those in initial works covering the problem.
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