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Model-Based Control of Soft Actuators Using Learned Non-linear Discrete-Time Models

Overview of attention for article published in Frontiers in Robotics and AI, April 2019
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2 X users

Citations

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52 Dimensions

Readers on

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81 Mendeley
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Title
Model-Based Control of Soft Actuators Using Learned Non-linear Discrete-Time Models
Published in
Frontiers in Robotics and AI, April 2019
DOI 10.3389/frobt.2019.00022
Pubmed ID
Authors

Phillip Hyatt, David Wingate, Marc D. Killpack

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 21%
Student > Master 17 21%
Student > Bachelor 7 9%
Student > Doctoral Student 5 6%
Researcher 5 6%
Other 5 6%
Unknown 25 31%
Readers by discipline Count As %
Engineering 41 51%
Computer Science 5 6%
Mathematics 1 1%
Economics, Econometrics and Finance 1 1%
Agricultural and Biological Sciences 1 1%
Other 2 2%
Unknown 30 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 10 April 2019.
All research outputs
#18,676,383
of 23,140,503 outputs
Outputs from Frontiers in Robotics and AI
#1,323
of 1,526 outputs
Outputs of similar age
#266,030
of 352,695 outputs
Outputs of similar age from Frontiers in Robotics and AI
#21
of 26 outputs
Altmetric has tracked 23,140,503 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,526 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.7. This one is in the 1st percentile – i.e., 1% 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 352,695 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.