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PERCEPTION OF Nβ*gα-CLOSED SETS AND CONTINUOUS FUNCTIONS IN NANO-TOPOLOGICAL SPACE.

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Title: PERCEPTION OF Nβ*gα-CLOSED SETS AND CONTINUOUS FUNCTIONS IN NANO-TOPOLOGICAL SPACE.
Authors: Baby, K.1 babymanoharan31@gmail.com, Muthumani, R.1 muthumanir12@gmail.com
Source: Advances & Applications in Discrete Mathematics. Oct2025, Vol. 42 Issue 7, p689-711. 23p.
Subjects: Topological spaces, Continuous functions, Topology, Mathematics
Abstract: The aim of this study is to introduce and explore Nβ*gα-closed sets and Nβ*gα-continuous functions within the framework of nano-topological spaces. [ABSTRACT FROM AUTHOR]
Copyright of Advances & Applications in Discrete Mathematics is the property of Pushpa Publishing House and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: PERCEPTION OF Nβ*gα-CLOSED SETS AND CONTINUOUS FUNCTIONS IN NANO-TOPOLOGICAL SPACE.
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  Data: <searchLink fieldCode="JN" term="%22Advances+%26+Applications+in+Discrete+Mathematics%22">Advances & Applications in Discrete Mathematics</searchLink>. Oct2025, Vol. 42 Issue 7, p689-711. 23p.
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  Data: The aim of this study is to introduce and explore Nβ*gα-closed sets and Nβ*gα-continuous functions within the framework of nano-topological spaces. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Advances & Applications in Discrete Mathematics is the property of Pushpa Publishing House and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Oct2025
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