Automated Author ProfileDONG, Bing
DONG, Bing
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: 4.9 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Open MATLAB and double click .mat file will load the data set. DataSet4.mat is the data set with input of 4 specific activities. DataSet6.mat is the data set with input of 6 specific activities. DataSet23.mat is the data set with input of 23 specific activities. After opening the file, input_norm is the normalized specific activities, input_max is the maximum specific activities, input_min is the minium specific activies, and the target is the corresponding one-hot encoding degree of failure. For example, {1,0,0,0,0,0} is failure of degree 1, {0,0,1,0,0,0} is failure of degree 3. Input of the function TrainN is number of neurons in the hidden layer1. For example, running TrainN(10) will train the neural network with 10 neurons in the hidden layer 1.
Authors
- DONG, Bing
Open MATLAB and double click .mat file will load the data set. DataSet4.mat is the data set with input of 4 specific activities. DataSet6.mat is the data set with input of 6 specific activities. DataSet23.mat is the data set with input of 23 specific activities. After opening the file, input_norm is the normalized specific activities, input_max is the maximum specific activities, input_min is the minium specific activies, and the target is the corresponding one-hot encoding degree of failure. For example, {1,0,0,0,0,0} is failure of degree 1, {0,0,1,0,0,0} is failure of degree 3. Input of the function TrainN is number of neurons in the hidden layer1. For example, running TrainN(10) will train the neural network with 10 neurons in the hidden layer 1.
Authors
- DONG, Bing
Open MATLAB and double click .mat file will load the data set. DataSet4.mat is the data set with input of 4 specific activities. DataSet6.mat is the data set with input of 6 sepcific activities. DataSet23.mat is the data set with input of 23 sepcific activities. After opening the file, input_norm is the normalized specific activities, input_max is the maximum specific activities, input_min is the minium specific activies, and the target is the corresponding one-hot encoding degree of failure. For example, {1,0,0,0,0,0} is failure of degree 1, {0,0,1,0,0,0} is failure of degree 3. Input of the function TrainN is number of neurons in the hidden layer1. For example, running TrainN(10) will train the neural network with 10 neurons in the hidden layer 1.
Authors
- DONG, Bing