口语 发表于 2025-3-21 16:09:45
书目名称Algorithms and Architectures for Parallel Processing影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0153068<br><br> <br><br>书目名称Algorithms and Architectures for Parallel Processing影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0153068<br><br> <br><br>书目名称Algorithms and Architectures for Parallel Processing网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0153068<br><br> <br><br>书目名称Algorithms and Architectures for Parallel Processing网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0153068<br><br> <br><br>书目名称Algorithms and Architectures for Parallel Processing被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0153068<br><br> <br><br>书目名称Algorithms and Architectures for Parallel Processing被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0153068<br><br> <br><br>书目名称Algorithms and Architectures for Parallel Processing年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0153068<br><br> <br><br>书目名称Algorithms and Architectures for Parallel Processing年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0153068<br><br> <br><br>书目名称Algorithms and Architectures for Parallel Processing读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0153068<br><br> <br><br>书目名称Algorithms and Architectures for Parallel Processing读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0153068<br><br> <br><br>持续 发表于 2025-3-22 00:01:35
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Reliable Content Delivery in Lossy Named Data Networks Based on Network Codinge the number of packets retransmitted in lossy NDN networks. Extensive real physical emulation shows that network coding reduces the number of packet retransmission and improves the reliability of content delivery in lossy NDN networks.下边深陷 发表于 2025-3-22 11:08:09
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Harden Tamper-Proofing to Combat MATE Attackciency since it only introduces the constant extra cost of time and space. We deploy our work on SPECint-2006 benchmark suit. The experimental results demonstrate our scheme is light-weight for computation and storage.Militia 发表于 2025-3-22 20:17:04
A Fast and Effective Detection of Mobile Malware Behavior Using Network Trafficic, which can quickly and effectively detect malware behavior. We first employ the traffic collection platform to collect network traffic generated by various apps. After preprocessing (filtering and aggregating) the collected network traffic data, we get a large number of TCP flows. Next we extractinstructive 发表于 2025-3-22 22:50:58
A Scalable Pthreads-Compatible Thread Model for VM-Intensive Programs16 cores than Pthreads. Moreover, by using Linux Perf, we further analyze critical bottlenecks that limit the scalability of workloads programmed by Pthreads. This paper also reviews the performance impact of the latest Linux 4.10 kernel optimization on . and Pthreads, and results show that . still使隔离 发表于 2025-3-23 05:01:31
Identifying Bitcoin Users Using Deep Neural Networkcognition and clustering, where the implementation relies directly on the distance between address feature vectors..We set up an address-user pairing dataset with extensive collections and careful sanitation. We tested our method using the dataset and proved its efficiency. In contrast to heuristic-可触知 发表于 2025-3-23 09:26:11
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