Computational Intelligence
The dataset was constructed by capturing real-time background traffic of 9 applications. The 9 applications represent different types of network behaviour in the background, for high level of network
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The Geomagnetic field can be used for classifying different landmark locations inside a big building.
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This folder contains the code and datasets necessary for performing experiments on the Steimann and Defects4J coverage matrices detailed in "Doric: Foundations for Statistical Fault Localisation". See the README.txt inside the folder for further details.
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Programmableweb
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Context: Multiple types of processing units (e.g., CPUs, GPUs and FPGAs) can be used jointly to achieve better performance in computational systems. However, these units are built with fundamentally different characteristics and demand attention especially towards software deployment.
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# of original news:30;
# of candidate news:25899;
# of reprinted news (no source label):4234 (537)
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The whole data set will be published after the acceptance of our paper via the same url as shown in the paper.
When using PackageRank software to analyze our data set, please do not change the name of the .net files.
The .net file has the following format:
Node count: *Vertices count
Node List:
number "node name"
EX: 1 "org.apache.tools.ant.taskdefs.optional.sitraka"
Arc List:
node1 node2 weight
EX: 1 2 3
Meaning: from node 1 to node 2 with weight 3
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Computational modelling of metabolic processes has proven to be a useful approach to formulate our knowledge and improve our understanding of core biochemical systems that are crucial to maintain cellular functions. Recently, it has become evident that metabolism is not only responsible for generating the required energy and controlling the abundance of metabolites within a cell, but also has an important role in and influence on cellular fate specification.
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We provide results of "Robust Visual Tracking Based on Adaptive Extraction and Enhancement of Correlation Filter" on OTB2015 dataset, including the results of proposed tracker with HOG, HOGCN, and deep CNN features.
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