Dataset Folder Structure: datasets/│├── README-for-all.txt├──Materials' Thicknesses Details├── C4001 - Dataset/│ ││ ├── C4001 Reflected Signal Dataset – Multiple Materials & Thickness Levels/│ │ ├── C4001_AllMaterials_AllThickness.csv│ │ └── README.txt│ ││ └── C4001 Reflected Signal Dataset – Multiple Materials/│ ├── C4001_FiveMaterials_Only.csv│ └── README.txt| |------ Raw Data| |----- All Materials Raw Data│└── URM09 - Dataset/ │ ├── URM09 Reflected Signal Dataset – Multiple Materials & Thickness Levels/ │ ├── URM09_AllMaterials_AllThickness.csv │ └── README.txt │ └── URM09 Reflected Signal Dataset – Multiple Materials/ ├── URM09_SixMaterials_Only.csv └── README.txt | |------ Raw Data | |----- All Materials Raw Data///////////////////////////////////////////////////////////////////////////////////////////// Notes:1- Check the file "Materials' Thicknesses Details" to know the materials thicknesses used in this experiment.2- Read the methodology for data collection in paper. -------------------------------------------------------------------------------------------------------------- \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\How to use datasets: 1- Download the CSV files from this dataset. 2- Load the CSV files into your preferred programming environment(Python, MATLAB, R, Weka, etc.). 3- Select one or more datasets depending on your experiment needs: A- AllMaterials_AllThickness → for general classification with multiple thickness levels. B- Five/SixMaterials_Only → cleaner classification without thickness effects. 4- The label column shows the material and thickness for each sample(e.g., Plastic-2). 5- Use the feature columns (Mean, RMS, Energy, etc.) as inputs to machine learning algorithms. 6- Split the dataset into training and testing sets (e.g., 80% / 20%) or use N-Folds Cross Validation. 7- Train your ML model and evaluate performance (accuracy, precision, recall). 9- Cite this dataset in your research/publication when using it.///////////////////////////////////////////////////////////////////////////////////////////////////////