Automated Author ProfileDas, Amarendra
Das, Amarendra
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: 1.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Odisha, an eastern Indian state, has reported an increasing number of human-elephant conflicts in recent years. Odisha's economic survey (2014–15) reveals that, up until January 2014, about 42,371.86-hectares of forest land had been destroyed for developmental activities. The loss of natural habitat has increased the frequency of conflict. The household survey conducted in nine villages within the Nilagiri forest range, captured various costs of conflict such as crop damage, human fatalities and injury, property damage, and livestock depredation. Findings suggested that crop-raiding was persistent and severe, which threatened food security and livelihoods. Multivariate logistic regression analysis identified factors influencing perceptions of the adequacy of compensation. Results show that respondents were less likely to say that compensation amounts were adequate if they had attended more than five years of schooling; if they had an annual family income greater than INR 13,500; and if the amount of compensation was more than INR 12,500.
Authors
- Guru, Biplab Kumar ;
- Das, Amarendra
Odisha, an eastern Indian state, has reported an increasing number of human-elephant conflicts in recent years. Odisha's economic survey (2014–15) reveals that, up until January 2014, about 42,371.86-hectares of forest land had been destroyed for developmental activities. The loss of natural habitat has increased the frequency of conflict. The household survey conducted in nine villages within the Nilagiri forest range, captured various costs of conflict such as crop damage, human fatalities and injury, property damage, and livestock depredation. Findings suggested that crop-raiding was persistent and severe, which threatened food security and livelihoods. Multivariate logistic regression analysis identified factors influencing perceptions of the adequacy of compensation. Results show that respondents were less likely to say that compensation amounts were adequate if they had attended more than five years of schooling; if they had an annual family income greater than INR 13,500; and if the amount of compensation was more than INR 12,500.
Authors
- Guru, Biplab Kumar ;
- Das, Amarendra