BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:US/Eastern BEGIN:DAYLIGHT DTSTART:20200308T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20201101T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20210114T051736Z UID:1DA38897-0F44-4B0D-B1CA-E0E9DDE31AD5 DTSTART;TZID=US/Eastern:20201030T163000 DTEND;TZID=US/Eastern:20201030T180000 DESCRIPTION:This will be a technical deep dive of a single piece of researc h work\, complete with questions about the existing methods\, proposed met hod\, materials/equipment used\, procedure\, analysis method\, and conclus ion. Think of this as practice for a proposal/progress seminar or defense presentation in front of committee members in preparation for graduating f rom a PhD or Master's program or completing a Capstone Project.\n\nResearc h Topic: Based on IEEE IUS 2020 Presentation: Ultrasound Flaw Detection of Medium-Density Polyethylene Fused Joints Using Chord Transducers and Impl ementation of Artificial Intelligence.\n\nTo make sure that pipes and pipe joints are built within a specification\, and that they do not have defec ts\, an instrument sends a signal to be bounced from the piping material t o be analyzed. That same instrument thus receives that signal and generate s a defect signature\, a picture that tells the person looking for a defec t as to whether or not there is a defect.\n\nThis method is not accurate\, so the instrument in use in this work is an ultrasonic transducer\, and t he analysis has been augmented by artificial intelligence.\n\nArtificial i ntelligence\, however\, is known mainly for analysis of the raw data after it has been collected\, and it is a game of statistics\, so its accuracy has to be tested as well.\n\nHow does artificial intelligence make detecti on of defects in pipe joints more accurate? Find out!\n\n(The presentation will be streamed live via Microsoft Teams.)\n\n(Please note: The presenta tion will be recorded. By viewing the event\, you agree to have your video and audio recorded if you choose to contribute to the discussion\, includ ing\, but not limited to\, the question-and-answer section.)\n\n[Click her e to view the event live](https://teams.microsoft.com/l/meetup-join/19%3am eeting_ODYxYmFjYWYtNDFlZC00Y2RlLTgxZDktM2Y0NzA4OGVmNWJi%40thread.v2/0?cont ext=%7b%22Tid%22%3a%2212f933b3-3d61-4b19-9a4d-689021de8cc9%22%2c%22Oid%22% 3a%221ad4941e-f82f-410f-82eb-cc59dc38ceee%22%7d)\n\nSpeaker(s): Maryam Sha fiei Ajavijeh\, Mechanical Engineering PhD Candidate and Secretary\, IEEE Women in Engineering Affinity Group\, IEEE Windsor Section \, \n\nWindso r\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/245956 LOCATION:Windsor\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.o rg/m/245956 ORGANIZER:maru@uwindsor.ca SEQUENCE:7 SUMMARY:Research Presentation Moderated by Ajay Maru - Non-destructive Asse ssment of Polyethylene Pipe Defects via Ultrasonic and AI URL;VALUE=URI:https://events.vtools.ieee.org/m/245956 X-ALT-DESC:Description: <br /><div>This will be a technical deep dive of a single piece of research work\, complete with questions about the existing methods\, proposed method\, materials/equipment used\, procedure\, analys is method\, and conclusion. Think of this as practice for a proposal/progr ess seminar or defense presentation in front of committee members in prepa ration for graduating from a PhD or Master's program or completing a Capst one Project.&nbsp\; &nbsp\;</div>\n<div>&nbsp\; &nbsp\;</div>\n<div>&nbsp\ ; &nbsp\;</div>\n<div>Research Topic: Based on IEEE IUS 2020 Presentation: &nbsp\;Ultrasound Flaw Detection of Medium-Density Polyethylene Fused Join ts Using Chord Transducers and Implementation of Artificial Intelligence.& nbsp\; &nbsp\;</div>\n<div>&nbsp\; &nbsp\;</div>\n<div>To make sure that p ipes and pipe joints are built within a specification\, and that they do n ot have defects\, an instrument sends a signal to be bounced from the pipi ng material to be analyzed. That same instrument thus receives that signal and generates a defect signature\, a picture that tells the person lookin g for a defect as to whether or not there is a defect.&nbsp\; &nbsp\;</div >\n<div>&nbsp\; &nbsp\;</div>\n<div>This method is not accurate\, so the i nstrument in use in this work is an ultrasonic transducer\, and the analys is has been augmented by artificial intelligence.&nbsp\; &nbsp\;</div>\n<d iv>&nbsp\; &nbsp\;</div>\n<div>Artificial intelligence\, however\, is know n mainly for analysis of the raw data after it has been collected\, and it is a game of statistics\, so its accuracy has to be tested as well.&nbsp\ ; &nbsp\;</div>\n<div>&nbsp\;</div>\n<div>How does artificial intelligence make detection of defects in pipe joints more accurate? Find out!&nbsp\; &nbsp\;&nbsp\;</div>\n<div>&nbsp\; &nbsp\;</div>\n<div>(The presentation w ill be streamed live via Microsoft Teams.)&nbsp\; &nbsp\;</div>\n<div><str ong>&nbsp\; &nbsp\;</strong></div>\n<div><strong>(Please note:</strong> Th e presentation will be recorded. By viewing the event\, you agree to have your video and audio recorded if you choose to contribute to the discussio n\, including\, but not limited to\, the question-and-answer section.)&nbs p\; &nbsp\;</div>\n<div>&nbsp\; &nbsp\;</div>\n<div><a title="https://team s.microsoft.com/l/meetup-join/19%3ameeting_odyxymfjywytndflzc00y2rlltgxzdk tm2y0nza4ogvmnwji%40thread.v2/0?context=%7b%22tid%22%3a%2212f933b3-3d61-4b 19-9a4d-689021de8cc9%22%2c%22oid%22%3a%221ad4941e-f82f-410f-82eb-cc59dc38c eee%22%7d" href="https://teams.microsoft.com/l/meetup-join/19%3ameeting_OD YxYmFjYWYtNDFlZC00Y2RlLTgxZDktM2Y0NzA4OGVmNWJi%40thread.v2/0?context=%7b%2 2Tid%22%3a%2212f933b3-3d61-4b19-9a4d-689021de8cc9%22%2c%22Oid%22%3a%221ad4 941e-f82f-410f-82eb-cc59dc38ceee%22%7d" target="_blank" rel="noopener nore ferrer" data-auth="NotApplicable">Click here to view the event live</a>&nb sp\; &nbsp\;</div> END:VEVENT END:VCALENDAR