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AdaTest: Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection

Overview of attention for article published in ACM Transactions on Embedded Computing Systems, January 2023
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
15 Mendeley
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Title
AdaTest: Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection
Published in
ACM Transactions on Embedded Computing Systems, January 2023
DOI 10.1145/3544015
Authors

Huili Chen, Xinqiao Zhang, Ke Huang, Farinaz Koushanfar

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 20%
Unspecified 2 13%
Researcher 1 7%
Lecturer 1 7%
Student > Doctoral Student 1 7%
Other 0 0%
Unknown 7 47%
Readers by discipline Count As %
Engineering 4 27%
Computer Science 2 13%
Unspecified 2 13%
Unknown 7 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 July 2015.
All research outputs
#7,565,251
of 23,075,872 outputs
Outputs from ACM Transactions on Embedded Computing Systems
#69
of 310 outputs
Outputs of similar age
#74,899
of 251,971 outputs
Outputs of similar age from ACM Transactions on Embedded Computing Systems
#1
of 4 outputs
Altmetric has tracked 23,075,872 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 310 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 251,971 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them