## 4 Results
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Component Code**} & \multicolumn{6}{c}{**Perceptual Imagery Features**} \\ \cline{2-7}  & **A Technological** & **B Digified** & **C Minimalist** & **D Agile** & **E Minimalist** & **F Elegant** \\ \hline \multirow{2}{*}{K-01} & 0.385 * & 0.381 * & 0.308 & 0.329 & 0.436 * & 0.336 \\  & (0.036) & (0.038) & (0.098) & (0.076) & (0.016) & (0.069) \\ \hline \multirow{2}{*}{K-02} & 0.332 & 0.291 & 0.314 & 0.077 & 0.436 * & 0.318 \\  & (0.073) & (0.119) & (0.091) & (0.686) & (0.016) & (0.087) \\ \hline \multirow{2}{*}{K-03} & 0.256 & 0.449 * & 0.218 & 0.216 & 0.605 ** & 0.572 ** \\  & (0.173) & (0.013) & (0.247) & (0.252) & (0.000) & (0.001) \\ \hline \multirow{2}{*}{K-04} & 0.004 & 0.435 * & 0.091 & 0.069 & 0.312 & 0.153 \\  & (0.982) & (0.016) & (0.631) & (0.715) & (0.093) & (0.421) \\ \hline \multirow{2}{*}{K-05} & 0.601 ** & 0.495 ** & 0.458 * & 0.551 ** & 0.491 ** & 0.149 \\  & (0.000) & (0.005) & (0.011) & (0.002) & (0.006) & (0.432) \\ \hline \multirow{2}{*}{K-06} & 0.247 & 0.223 & 0.275 & 0.466 ** & 0.118 & 0.269 \\  & (0.188) & (0.237) & (0.142) & (0.009) & (0.533) & (0.151) \\ \hline \multirow{2}{*}{K-07} & 0.266 & 0.278 & 0.557 ** & 0.351 & 0.346 & 0.275 \\  & (0.156) & (0.137) & (0.001) & (0.057) & (0.061) & (0.142) \\ \hline \multirow{2}{*}{K-08} & 0.399 * & 0.107 & 0.488 ** & 0.676 ** & 0.015 & 0.555 ** \\  & (0.029) & (0.573) & (0.006) & (0.000) & (0.936) & (0.001) \\ \hline \multirow{2}{*}{K-09} & 0.095 & 0.481 ** & 0.405 * & 0.432 * & 0.624 ** & 0.139 \\  & (0.616) & (0.007) & (0.026) & (0.017) & (0.000) & (0.464) \\ \hline \multirow{2}{*}{K-10} & 0.025 & 0.414 * & 0.152 & 0.319 & 0.215 & 0.232 \\  & (0.895) & (0.023) & (0.422) & (0.086) & (0.253) & (0.216) \\ \hline \hline \end{tabular} Note: A single asterisk (*) indicates a significant association, and a double asterisk (**) denotes a highly significant association.  
\end{table} 
Table 8: The results of the image cognitive correlation of the bottom modeling samples. When \(0\leq p\leq 0.05\), significant correlations between imagery semantics and stylistic samples were confirmed. Sig-values indicated association strength through asterisk notation: no asterisk denoted weak association; single asterisk (*) indicated significant association; double asterisk (**) denoted highly significant association--all contingent upon valid \(p\)-values. Data from 30 participants' cognitive measurements were processed through SPSS, yielding comprehensive analytical results on cognitive mapping relationships between cleaning robot stylistic samples and imagery semantics. Prior to formal analysis of mapping relationships between industrial cleaning robot design samples and imagery semantics, samples failing to demonstrate significant \(p\)-values within valid ranges were excluded. Retained samples exhibited positive correlations with imagery-semantic descriptors across all components. Specifically: six top-component samples (X-01, X-04, X-05, X-08, X-09) showing no correlation with any of the six imagery-semantic descriptors were removed; six front-face samples (Y-02, Y-03, Y-06, Y-07, Y-10) uncorrelated to all six descriptors were eliminated; six side-profile samples (Z-01, Z-04, Z-05, Z-07, Z-09) without correlations were excluded; and six bottom-component samples (K-02, K-04, K-06, K-07, K-10) demonstrating zero correlations were discarded. Subsequent analysis proceeded as follows. First, correlation coefficients for the remaining 20 styling samples of industrial cleaning robot components all exhibited positive Sig. values, indicating positive correlations with target imagery semantic descriptors. Second, Table 8 demonstrates that 11 samples (exceeding 50% of the 20 valid samples) showed correlations with imagery descriptors corresponding to three perceptual requirement categories. This confirms that the sample styling elements generally align with users' collective perceptual preferences.