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<ArticleSet>
<Article>
<Journal>
<PublisherName>OICC Press</PublisherName>
<JournalTitle>Mathematical Analysis and its Contemporary Applications</JournalTitle>
<Issn></Issn>
<Volume>7</Volume>
<Issue>1</Issue>
<PubDate PubStatus="epublish">
<Year>2025</Year>
<Month>01</Month>
<Day>01</Day>
</PubDate>
</Journal>
<ArticleTitle>Geometry of norm attainability in Orlicz spaces</ArticleTitle>
<VernacularTitle></VernacularTitle>
<FirstPage></FirstPage>
<LastPage></LastPage>
<ELocationID EIdType="doi">10.30495/maca.2025.2052193.1127</ELocationID>
<Language>EN</Language>
<AuthorList>
<Author>
<FirstName>Mogoi N.</FirstName>
<LastName>Evans</LastName>
<Affiliation>
              Department of Pure and Applied Mathematics, Jaramogi Oginga Odinga University of Science and Technology, Kenya
            </Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Robert</FirstName>
<LastName>Obogi</LastName>
<Affiliation>
              Department of Mathematics and Actuarial Science, Kisii University, Kenya
            </Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
</AuthorList>
<PublicationType>Journal Article</PublicationType>
<History>
<PubDate PubStatus="received">
<Year>2025</Year>
<Month>01</Month>
<Day>01</Day>
</PubDate>
</History>
<Abstract>This paper investigates norm attainability and modular properties in Orlicz spaces, which generalize Lp-spaces and are key in functional analysis and nonlinear problems. It presents theorems on norm attainment, orthogonality, weak compactness, and uniform convexity, and introduces a novel criterion connecting the convexity of the Orlicz function with the smoothness and reflexivity of the space. The research extends classical concepts such as the ∆2-condition to ensure completeness and separability. The results have practical applications in nonlinear optimization, variational analysis, machine learning, signal processing, image reconstruction, and solving PDEs with nonlinear boundary conditions, providing a strong foundation for future research in these areas.</Abstract>
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<Object Type="keyword">
<Param Name="value">Orlicz Spaces</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Norm Attainability</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Modular Properties</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Convexity</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Nonlinear Optimization</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Duality Theory</Param>
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