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Probabilistic fatigue damage prognosis using maximum entropy approach

Overview of attention for article published in Journal of Intelligent Manufacturing, October 2009
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About this Attention Score

  • Among the highest-scoring outputs from this source (#32 of 566)

Mentioned by

patent
1 patent

Citations

dimensions_citation
30 Dimensions

Readers on

mendeley
46 Mendeley
Title
Probabilistic fatigue damage prognosis using maximum entropy approach
Published in
Journal of Intelligent Manufacturing, October 2009
DOI 10.1007/s10845-009-0341-3
Authors

Xuefei Guan, Ratneshwar Jha, Yongming Liu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Unknown 44 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 37%
Student > Doctoral Student 5 11%
Professor 5 11%
Professor > Associate Professor 4 9%
Student > Master 3 7%
Other 4 9%
Unknown 8 17%
Readers by discipline Count As %
Engineering 32 70%
Nursing and Health Professions 1 2%
Business, Management and Accounting 1 2%
Materials Science 1 2%
Medicine and Dentistry 1 2%
Other 0 0%
Unknown 10 22%
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 17 April 2014.
All research outputs
#7,553,524
of 23,041,514 outputs
Outputs from Journal of Intelligent Manufacturing
#32
of 566 outputs
Outputs of similar age
#34,198
of 94,900 outputs
Outputs of similar age from Journal of Intelligent Manufacturing
#2
of 6 outputs
Altmetric has tracked 23,041,514 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 566 research outputs from this source. They receive a mean Attention Score of 1.4. This one has gotten more attention than average, scoring higher than 74% 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 94,900 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.