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Detection of Black Holes01:10

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Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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An Android Malware Detection Approach to Enhance Node Feature Differences in a Function Call Graph Based on GCNs.

Haojie Wu1, Nurbol Luktarhan2, Gaoqi Tian1

  • 1School of Software, Xinjiang University, Urumqi 830091, China.

Sensors (Basel, Switzerland)
|July 11, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces an improved method for Android malware detection using function call graphs (FCGs) and graph neural networks (GNNs). The approach enhances node feature differences, leading to higher detection accuracy for malicious applications.

Failed At:

2026-06-19T13:40:13.505528+00:00

Keywords:
Android malware detectionTF–IDFfunction call graphgraph convolutional networkself-loop

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