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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
In addition to applications, we draw their figures in order to reinforce the visualization in both spaces. ....... . .................... .
📌 3 Key Takeaways
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Objective & Hypothesis:In this study, we define a dual transformation between $G^{n}$ and $G^{n}_{1}$.
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Key Findings & Data:We define a dual transformation between $\widehat{G^{n}}$ and $\widehat{G^{n}_{1}}$ as well.
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Conclusion & Impact:In addition to applications, we draw their figures in order to reinforce the visualization in both spaces. ....... . .................... .
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Dual transformation · Galilean space · pseudo-Galilean space
Abstract
In this study, we define a dual transformation between $G^{n}$ and $G^{n}_{1}$. We examine the invariance of the plane where the shear motion is acting in Galilean and pseudo-Galilean spaces. We define a dual transformation between $\widehat{G^{n}}$ and $\widehat{G^{n}_{1}}$ as well. We provide applications in $G^{3}$ and $G^{3}_{1}$. In addition to applications, we draw their figures in order to reinforce the visualization in both spaces. ....... . .................... .
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Cite This Article
Yüca, G., Yaylı, Y. (2020). Dual Transformations in Galilean Spaces. International Electronic Journal of Geometry, Volume: 13 Issue: 2. https://doi.org/10.36890/iejg.683738