Composite Tor traffic features extraction method of webpage in actual network flow based on SDN by Hongping YAN, Qiang ZHOU, Shihao WANG, Wang YAO, Liukun HE, Liangmin WANG

“…Website fingerprinting (WF) methods for Tor webpage traffic are often based on the separated Tor traffic or even the separated Tor webpage traffic.However, distinguishing Tor traffic from the original traffic of the actual network and Tor webpage traffic from the Tor traffic costs amount of computation, which is more difficult than the WF attack itself.According to the current architecture of the Internet and the characteristics of network traffic converging to regional central nodes, the bi-directional statistical feature (BSF) was proposed for distinguishing Tor traffic through the intra-domain global perspective provided by the SDN structure of the central node and the node information disclosed by the Tor network.Furthermore, a hidden feature extraction method for Web traffic based on lifted structure fingerprinting (LSF) was proposed, and a composited Tor-webpage-identification traffic feature (CTTF) was proposed based on BSF and LSF deep features.For solving the problem of traffic training data scarcity, a traffic data augmentation method based on translation was proposed, which made the augmented traffic data as consistent as the Tor traffic data captured in the real working environment.The experimental results show that the identification rate based on CTTF can be improved by about 4% compared with using only the original data features.When there is less training data, the classification accuracy is improved more obvious after using the traffic data augmentation method, and the false positive rate can be effectively reduced.…”
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Usable observations over Europe: evaluation of compositing windows for Landsat and Sentinel-2 time series by Katarzyna Ewa Lewińska, David Frantz, Ulf Leser, Patrick Hostert

“…We considered separate and joint use of both data archives and analyzed the spatio-temporal availability of composites during each calendar year and pixel-specific growing season across a variety of time windows and hypothesizing data interpolation. …”
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Explainable machine learning and feature engineering applied to nanoindentation data by C.O.W. Trost, S. Žák, S. Schaffer, L. Walch, J. Zitz, T. Klünsner, H. Leitner, L. Exl, M.J. Cordill

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Robust biochar yield and composition prediction via uncertainty-aware ResNet-based autoencoder by Yali Zhang, Bowen Lei, Amirhossein Mahdaviarab, Xiao Wang, Zong Liu

“…This paper presents a ResNet-based autoencoder model that utilizes biomass properties and pyrolysis conditions to more accurately and robustly predict biochar yield and composition. The developed model has the advantage of addressing the common data uncertainty concerns in training data. …”
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Energy Efficient Indivisible Workload Distribution in Geographically Distributed Data Centers by Muhammad Imran Khan Khalil, Iftikhar Ahmad, Abdulwahab Ali Almazroi

Subjects: “…Energy efficiency in cloud computing…”
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Transformation-Based Data Synthesis for Limited Sample Scenario by Chang-Hwa Lee, Sang Wan Lee

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Data center virtualization and its economic implications for the companies by Cristian STEFAN, Mariana JURIAN, Logica BANICA

Subjects: “…data centre…”
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Use of Data Mining for Intelligent Evaluation of Imputation Methods by David Red, Carlos R. Primorac

Subjects: “…computer science…”
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Detection and analysis of energy data by using quantum filter by Haohan WU, Gang JIANG

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An edge streaming data processing framework for autonomous driving by Hang Zhao, LinBin Yao, ZhiXin Zeng, DongHua Li, JinLiang Xie, WeiLing Zhu, Jie Tang

Subjects: “…edge computing…”
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Detection and analysis of energy data by using quantum filter by Haohan WU, Gang JIANG

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The Formation of Artificial Data based on a Conveyor Enterprise by A. V. Zaripov, R. S. Kulshin, A. A. Sidorov

Subjects: “…data generation…”
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Survey of data possession provability proving on cloud storage by Wei FU, Qing YE, Ze-mao CHEN, Xiao-ping WU

Subjects: “…cloud computing;cloud storage;cloud security;data possession provability…”
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Associations between 24-hour movement compositions and cardiometabolic health in children and adolescents: a five-part compositional analysis using data from the International Children’s Accelerometery Database (ICAD) by Russell R Pate, John J Reilly, Kate Northstone, EMF van Sluijs, Russ Jago, Niels Wedderkopp, R Davey, Luis B Sardinha, Jardena Puder, J Reilly, K Northstone, LB Andersen, S Kriemler, R Jago, J Salmon, G Cardon, Pedro Curi Hallal, Adam Runacres, Zoe A Marshall, Soyang Kwon, Ester Van Slujis, S Anderssen, P Hallal, S Kwon, N Møller, R Pate, JJ Puder, LB Sardinha

“…The aim of this study was to determine the joint influence of SED, light-, moderate- and vigorous-intensity PA (LPA, MPA and VPA), and sleep on CMR factors using five-part compositional analyses.Methods Data were pooled from 16 cohort studies comprising 22 474 children and adolescents from the International Children’s Accelerometery Database. …”
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SOT-MRAM-based true in-memory computing architecture for approximate multiplication by Min Song, Qilong Tang, Xintong Ouyang, Wei Duan, Yan Xu, Shuai Zhang, Long You

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Big data security features and operation practices by Zhiyong LIU, Zhongjiang HE, Yilong RUAN, Junfeng SHAN, Chao ZHANG

Subjects: “…big data;data security;blockchain;federated learning;artificial intelligence;cloud computing…”
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Big data security features and operation practices by Zhiyong LIU, Zhongjiang HE, Yilong RUAN, Junfeng SHAN, Chao ZHANG

Subjects: “…big data…”
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Improved Design for LKJ Data Transfer Device by XU Suqiang

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Hyperdimensional computing: a framework for stochastic computation and symbolic AI by Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau, Alex Veidenbaum

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Enhancing Gen3 for clinical trial time series analytics and data discovery: a data commons framework for NIH clinical trials by Meredith C. B. Adams, Meredith C. B. Adams, Meredith C. B. Adams, Colin Griffin, Hunter Adams, Stephen Bryant, Robert W. Hurley, Robert W. Hurley, Robert W. Hurley, Umit Topaloglu, Umit Topaloglu

Subjects: “…data commons…”
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