Automated Author ProfileYoon, Gyoungsub
Seoul National University
Yoon, Gyoungsub
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: 0.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
DatasetThis dataset supplements the manuscript "Volumetric B1+ field homogenization in 7 Tesla brain MRI using metasurface scattering" (arXiv)Data StructureThe dataset is organized into two main folders: Code and Figure.The Code folder contains Python scripts that sequentially repeat the gradient-based optimization and pruning process for magnetic field homogenization inside the ROI. These scripts reproduce the results shown in Figure 1c of the manuscript.The Figure folder contains all individual figure pannels presented in the manuscript. These image files are the unedited versions of the figures without any processing.
Authors
- Yoon, Gyoungsub ;
- Yu, Sunkyu ;
- Lee, Jongho ;
- Park, Namkyoo
DatasetThis dataset supplements the manuscript "Volumetric B1+ field homogenization in 7 Tesla brain MRI using metasurface scattering" (arXiv)Data StructureThe dataset is organized into two main folders: Code and Figure.The Code folder contains Python scripts that sequentially repeat the gradient-based optimization and pruning process for magnetic field homogenization inside the ROI. These scripts reproduce the results shown in Figure 1c of the manuscript.The Figure folder contains all individual figure pannels presented in the manuscript. These image files are the unedited versions of the figures without any processing.
Authors
- Yoon, Gyoungsub ;
- Yu, Sunkyu ;
- Lee, Jongho ;
- Park, Namkyoo