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TZID:America/New_York
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DTSTART:20211107T020000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
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DTSTART:20220313T020000
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BEGIN:VEVENT
UID:calendar.432901.field_event_date.0@www.wright.edu
DTSTAMP:20260219T192050Z
CREATED:20211108T140008Z
DESCRIPTION:Speaker: Dr. Aihua Wood\, AFITHost: Dr. Qingbo HuangTime:  Meet
 -n-greet at 2:30 p.m.\, talk at 3 p.m.ABSTRACT:In this presentation\, we d
 iscuss a process for numerically reconstructing obstacles behind walls usi
 ng the scattered data from electromagnetic radiation. In particular\, we p
 rovide a reconstruction procedure that uses a source within the numerical 
 field\, so that the incoming field is not generated by a plane wave\, and 
 that the object is located within a set of walls that will interfere with 
 the ability to analyze the object normally. The data used for performing t
 his reconstruction is generated numerically\, but it is assumed that the s
 cattered field can be known at certain locations outside of the walled are
 a\, instead of known as a function. These conditions violate the assumptio
 ns of the known theoretical reconstructions\, so a different approach is n
 eeded. We develop an appropriate adjustment to the theoretical methods pre
 sented in the literature to analyze obstacles in this setting\, and presen
 t some numerical results towards this end. The reconstruction method seeks
  to discover the shape\, size\, and conductivity of the obstacles using a 
 behind-walls analysis. We will also present some experiments using machine
  learning and compare the results where applicable.SPEAKER BIO:Aihua Wood 
 received her B.S. from Peking University\, China\, M.S. and Ph.D. from the
  University of Connecticut\, all in Mathematics. She worked as a visiting 
 assistant professor at the Naval Postgraduate School in Monterey\, CA\, an
 d Penn State University–Erie before joining the faculty at the Air Force I
 nstitute of Technology where she has been a full professor since 2002.Dr. 
 Wood’s research interests include electromagnetic wave propagation\, raref
 ied gas dynamics\, and applications of machine learning in STEM areas.
DTSTART;TZID=America/New_York:20211112T143000
DTEND;TZID=America/New_York:20211112T160000
LAST-MODIFIED:20211109T034045Z
LOCATION:202 Mathematics and Microbiology Building
SUMMARY:Colloquium: 'Through-the-wall Object Reconstruction Via Radar Detec
 tion'
URL;TYPE=URI:/events/colloquium-through-wall-object-r
 econstruction-radar-detection
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