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A Machine Learning Approach for Investigating Spatial Structures between Spectral line Sources: Formaldehyde Absorptions versus Methanol MasersBy Okoh Daniel, Jarken Esimbek, Jianjun Zhou, Tang Xindi, Augustine Chukwude, Johnson Urama, Pius Okeke
Abstract: In this paper the authors present fascinating ideas on using machine learning algorithms to study connections in spatial distributions between observed spectral line sources. The method has been illustrated using observations of 4.8 GHz formaldehyde absorptions and 6.7 GHz methanol masers in the Galaxy. Both spectral line features have been well-observed in close associations with galactic star-formation regions, and we initiate this study to understand spatial connections between them. We …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 2, Issue 2, 2013 · pp. 1–11 Read article →