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Transaction-level modeling for architectural and power analysis of PowerPC and CoreConnect-based systems

Overview of attention for article published in Design Automation for Embedded Systems, September 2006
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
5 Mendeley
Title
Transaction-level modeling for architectural and power analysis of PowerPC and CoreConnect-based systems
Published in
Design Automation for Embedded Systems, September 2006
DOI 10.1007/s10617-006-9586-7
Authors

Nagu Dhanwada, Reinaldo A. Bergamaschi, William W. Dungan, Indira Nair, Paul Gramann, William E. Dougherty, Ing-Chao Lin

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 60%
Student > Bachelor 1 20%
Professor > Associate Professor 1 20%
Readers by discipline Count As %
Engineering 4 80%
Computer Science 1 20%

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 17 September 2015.
All research outputs
#2,742,688
of 10,173,376 outputs
Outputs from Design Automation for Embedded Systems
#3
of 22 outputs
Outputs of similar age
#37,578
of 114,454 outputs
Outputs of similar age from Design Automation for Embedded Systems
#1
of 1 outputs
Altmetric has tracked 10,173,376 research outputs across all sources so far. This one has received more attention than most of these and is in the 55th percentile.
So far Altmetric has tracked 22 research outputs from this source. They receive a mean Attention Score of 2.9. This one scored the same or higher as 19 of them.
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 114,454 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 66% of its contemporaries.
We're also able to compare this research output to 1 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