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Twitter Demographics
Mendeley readers
Attention Score in Context
| Title |
Neuromorphic System Using Memcapacitors and Autonomous Local Learning
|
|---|---|
| Published in |
IEEE Transactions on Neural Networks and Learning Systems, May 2023
|
| DOI | 10.1109/tnnls.2021.3106566 |
| Pubmed ID | |
| Authors |
Mutsumi Kimura, Yuma Ishisaki, Yuta Miyabe, Homare Yoshida, Isato Ogawa, Tomoharu Yokoyama, Ken-Ichi Haga, Eisuke Tokumitsu, Yasuhiko Nakashima |
Twitter Demographics
The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 4 | 20% |
| Researcher | 3 | 15% |
| Student > Ph. D. Student | 2 | 10% |
| Student > Bachelor | 1 | 5% |
| Unknown | 10 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 4 | 20% |
| Engineering | 2 | 10% |
| Physics and Astronomy | 1 | 5% |
| Neuroscience | 1 | 5% |
| Materials Science | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 11 | 55% |
Attention Score in Context
This research output has an Altmetric Attention Score of 31. 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 September 2021.
All research outputs
#1,148,418
of 23,660,680 outputs
Outputs from IEEE Transactions on Neural Networks and Learning Systems
#13
of 2,330 outputs
Outputs of similar age
#10,279
of 208,567 outputs
Outputs of similar age from IEEE Transactions on Neural Networks and Learning Systems
#1
of 26 outputs
Altmetric has tracked 23,660,680 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,330 research outputs from this source. They receive a mean Attention Score of 1.7. This one has done particularly well, scoring higher than 99% of its peers.
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 208,567 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
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 has done particularly well, scoring higher than 99% of its contemporaries.