## 4 Discussion  
Due to the significance of particle characteristics in the development of models explaining penetration depth and particle behaviour after entering the human body, especially from the material grinding process as one of the major sources of particles, significant attention has been devoted to the research of particle size and shape. In image analysis software packages, dimensionality is a common problem that can also be a factor in degrading the performance of a given algorithm with an increase in the number of features. Therefore, it is generally necessary to use models that reduce dimensions for large dimensional data sets. Dimension reduction techniques are often used as a step in data processing to reduce the complexity of the data picture. The particle analysis process collected from two types of grinding was carried out through several steps: (a) collection of particles with a personal sampler that analysed the amount of inhaled air during working hours; (b) acquisition of 2D micrographs using a scanning electron microscope; (c) characterisation of particles by numerical parameters using two image analysis software; and (d) reduction and se  
Figure 11: Dendrogram of the investigated geometric parameters. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Geometric Parameters**} & \multicolumn{4}{c}{**Factors**} \\ \cline{2-4}  & \(F1\) & \(F2\) & \(F3\) \\ \hline \(A\) & \(-0.001\) & \(-0.429\) & \(-0.042\) \\ \(P\) & \(-0.019\) & \(-0.362\) & \(0.071\) \\ \(\overline{D}_{F}\) & \(0.020\) & \(0.397\) & \(-0.011\) \\ \(L\) & \(0.082\) & \(0.372\) & \(-0.030\) \\ \(W\) & \(0.132\) & \(-0.400\) & \(0.039\) \\ \(D_{CE}\) & \(-0.003\) & \(-0.431\) & \(-0.047\) \\ \(EI\) & \(0.575\) & \(0.004\) & \(0.014\) \\ \(RT\) & \(0.091\) & \(-0.082\) & \(0.407\) \\ _CVX_ & \(-0.073\) & \(0.007\) & \(-0.460\) \\ _Circ_ & \(0.089\) & \(0.012\) & \(-0.426\) \\ \(AR\) & \(0.579\) & \(0.013\) & \(0.037\) \\ _RD_ & \(0.533\) & \(0.015\) & \(-0.051\) \\ _SLD_ & \(0.044\) & \(-0.174\) & \(-0.520\) \\ _CP_ & \(0.035\) & \(0.076\) & \(-0.393\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: PCA of geometric parameters after rotation. lection of representative parameters characterising particles from the process of grinding dental restorations. The correlation analysis revealed a high degree of correlation between parameters describing particle size. The correlations among these parameters were positive, indicating a harmonious growth of values within this data set. Particle size parameters did not show a high degree of correlation with particle shape parameters. Based on numerous Pearson correlation coefficient values, a certain degree of correlation was observed between parameters describing particle morphology and the equivalent circle diameter, perimeter, width, length, and mean Feret's diameter of the particle. Additionally, it is evident that elongation, convexity, circularity, roundness, solidity and compactness were negatively correlated with size parameters. On the other hand, aspect ratio and rectangularity were positively correlated with size parameters. Given that size parameters were positively correlated with each other, the uniformity regarding exclusively negative or positive correlations with shape parameters is understandable. Elongation exhibited a significant positive association with roundness and a negative correlation with aspect ratio. Convexity showed a remarkable positive correlation with circularity and compactness, as well as circularity with compactness, while there was a high negative correlation between rectangularity and compactness, as well as between aspect ratio and roundness. A strong association existed between circularity and solidity, and in the negative direction between rectangularity and convexity, circularity and solidity. A moderate positive correlation existed between convexity and solidity, circularity and roundness, and solidity and compactness.