Automated Author ProfileShannon Ryan
Shannon Ryan
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 4.7 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
A database of publicly available experimentally determined V50 ballistic limits (i.e., the impact velocity at which the target has a 50% probability of being perforated) for a range of projectile types, target materials, and impact conditions. Specifically, the database contains 1084 records from public sources, spanning 11 projectile types including armour piercing (AP), ball, and fragment simulators with calibres between 7.62 mm and 30 mm impacting aluminium, titanium, and steel targets of thicknesses ranging from 2.6 mm to 99 mm at impact obliquities between 0 and 45 degrees. Cite this database as:S Ryan, NM Sushma, A Kumar AV, J Berk, T Hashem, S Rana, S Venkatesh, "Machine Learning for Predicting the Outcome of Terminal Ballistics Events", Defence Technology (in-press), 2023
Authors
- Shannon Ryan
A database of publicly available experimentally determined V50 ballistic limits (i.e., the impact velocity at which the target has a 50% probability of being perforated) for a range of projectile types, target materials, and impact conditions. Specifically, the database contains 1084 records from public sources, spanning 11 projectile types including armour piercing (AP), ball, and fragment simulators with calibres between 7.62 mm and 30 mm impacting aluminium, titanium, and steel targets of thicknesses ranging from 2.6 mm to 99 mm at impact obliquities between 0 and 45 degrees. Cite this database as:S Ryan, NM Sushma, A Kumar AV, J Berk, T Hashem, S Rana, S Venkatesh, "Machine Learning for Predicting the Outcome of Terminal Ballistics Events", Defence Technology (in-press), 2023
Authors
- Shannon Ryan
A database of publicly available experimentally determined V50 ballistic limits (i.e., the impact velocity at which the target has a 50% probability of being perforated) for a range of projectile types, target materials, and impact conditions. Specifically, the database contains 1084 records from public sources, spanning 11 projectile types including armour piercing (AP), ball, and fragment simulators with calibres between 7.62 mm and 30 mm impacting aluminium, titanium, and steel targets of thicknesses ranging from 2.6 mm to 99 mm at impact obliquities between 0 and 45 degrees. Cite this database as:S , NM Sushma, A Kumar AV, J Berk, T Hashem, S Rana, S Venkatesh, "Machine Learning for Predicting the Outcome of Terminal Ballistics Events", Defence Technology (submitted), 2023
Authors
- Shannon Ryan