Title |
AcceleRater: a web application for supervised learning of behavioral modes from acceleration measurements
|
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Published in |
Movement Ecology, December 2014
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DOI | 10.1186/s40462-014-0027-0 |
Pubmed ID | |
Authors |
Yehezkel S Resheff, Shay Rotics, Roi Harel, Orr Spiegel, Ran Nathan |
Abstract |
The study of animal movement is experiencing rapid progress in recent years, forcefully driven by technological advancement. Biologgers with Acceleration (ACC) recordings are becoming increasingly popular in the fields of animal behavior and movement ecology, for estimating energy expenditure and identifying behavior, with prospects for other potential uses as well. Supervised learning of behavioral modes from acceleration data has shown promising results in many species, and for a diverse range of behaviors. However, broad implementation of this technique in movement ecology research has been limited due to technical difficulties and complicated analysis, deterring many practitioners from applying this approach. This highlights the need to develop a broadly applicable tool for classifying behavior from acceleration data. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 33% |
Hungary | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 33% |
Members of the public | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Israel | 1 | <1% |
Spain | 1 | <1% |
United States | 1 | <1% |
Germany | 1 | <1% |
Unknown | 184 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 50 | 27% |
Student > Master | 35 | 19% |
Researcher | 33 | 18% |
Student > Bachelor | 14 | 7% |
Student > Doctoral Student | 12 | 6% |
Other | 19 | 10% |
Unknown | 25 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 98 | 52% |
Environmental Science | 30 | 16% |
Computer Science | 6 | 3% |
Engineering | 4 | 2% |
Medicine and Dentistry | 3 | 2% |
Other | 13 | 7% |
Unknown | 34 | 18% |