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Dr. Maham Aftab on Modal Integration

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Manage episode 247979299 series 2572690
Innhold levert av The Spotlight Report. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av The Spotlight Report eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
In this weeks episode we sit down with Maham Aftab, who has an extensive background in the sciences as well as activism for a variety of causes. We discuss her most recent publication, in which she used Chebyshev gradient polynomials as a basis set for modal integration. She discusses the recursive nature of the polynomial set which allowed for her method to generate a high number of fitting polynomials. The integration’s ortho-normality is discussed, as well as its unique benefits and how it fits into the general universe of integration methods for slope data. Additionally, Maham speaks about her academic experience and her work in activism. Resources: Aftab’s Paper: Maham Aftab, James H. Burge, Greg A. Smith, Logan Graves, Chang-jin Oh, and Dae Wook Kim, “Modal Data Processing for High Resolution Deflectometry,” Int. J. of Precis. Eng. and Manuf.-Green Tech. (2018). (in press) Southwell Integration Paper: https://www.osapublishing.org/josa/abstract.cfm?uri=josa-70-8-998 --- Support this podcast: https://podcasters.spotify.com/pod/show/the-spotlight-report/support
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45 episoder

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Manage episode 247979299 series 2572690
Innhold levert av The Spotlight Report. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av The Spotlight Report eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
In this weeks episode we sit down with Maham Aftab, who has an extensive background in the sciences as well as activism for a variety of causes. We discuss her most recent publication, in which she used Chebyshev gradient polynomials as a basis set for modal integration. She discusses the recursive nature of the polynomial set which allowed for her method to generate a high number of fitting polynomials. The integration’s ortho-normality is discussed, as well as its unique benefits and how it fits into the general universe of integration methods for slope data. Additionally, Maham speaks about her academic experience and her work in activism. Resources: Aftab’s Paper: Maham Aftab, James H. Burge, Greg A. Smith, Logan Graves, Chang-jin Oh, and Dae Wook Kim, “Modal Data Processing for High Resolution Deflectometry,” Int. J. of Precis. Eng. and Manuf.-Green Tech. (2018). (in press) Southwell Integration Paper: https://www.osapublishing.org/josa/abstract.cfm?uri=josa-70-8-998 --- Support this podcast: https://podcasters.spotify.com/pod/show/the-spotlight-report/support
  continue reading

45 episoder

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