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X Demographics
Mendeley readers
Chapter title |
Machine Learning Techniques for Anomalies Detection and Classification
|
---|---|
Chapter number | 19 |
Book title |
Advances in Security of Information and Communication Networks
|
Published by |
Springer Berlin Heidelberg, January 2016
|
DOI | 10.1007/978-3-642-40597-6_19 |
Book ISBNs |
978-3-64-240596-9, 978-3-64-240597-6
|
Authors |
Amira Sayed Abdel-Aziz, Aboul Ella Hassanien, Ahmad Taher Azar, Sanaa El-Ola Hanafi, Abdel-Aziz, Amira Sayed, Hassanien, Aboul Ella, Azar, Ahmad Taher, Hanafi, Sanaa El-Ola |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Saudi Arabia | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 50% |
Unknown | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Thailand | 1 | 9% |
Egypt | 1 | 9% |
Unknown | 9 | 82% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 2 | 18% |
Lecturer > Senior Lecturer | 1 | 9% |
Other | 1 | 9% |
Professor | 1 | 9% |
Student > Doctoral Student | 1 | 9% |
Other | 2 | 18% |
Unknown | 3 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 5 | 45% |
Engineering | 2 | 18% |
Unknown | 4 | 36% |