BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Northeastern University College of Engineering - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Northeastern University College of Engineering
X-ORIGINAL-URL:https://coe.northeastern.edu
X-WR-CALDESC:Events for Northeastern University College of Engineering
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210104
DTEND;VALUE=DATE:20210201
DTSTAMP:20260517T104351
CREATED:20201208T145218Z
LAST-MODIFIED:20201208T145218Z
UID:23430-1609718400-1612137599@coe.northeastern.edu
SUMMARY:Lifelong Learning: On Demand – Innovative Uses of Artificial Intelligence
DESCRIPTION:The Office of Alumni Relations is hosting “Lifelong Learning: On Demand – Innovative Uses of Artificial Intelligence”. Be introduced to a few innovative uses of AI in the fields of healthcare\, computers\, and robotics. Learn from Northeastern faculty experts Craig Johnson and Taskin Padir. This complimentary\, online program is available to you on demand from January 4 to 31. An opportunity to earn a non-credit digital badge is available. \nRegister Now
URL:https://coe.northeastern.edu/event/lifelong-learning-on-demand-innovative-uses-of-artificial-intelligence/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210107
DTEND;VALUE=DATE:20210118
DTSTAMP:20260517T104351
CREATED:20201103T160300Z
LAST-MODIFIED:20210111T165144Z
UID:23023-1609977600-1610927999@coe.northeastern.edu
SUMMARY:Program-Specific Orientations
DESCRIPTION:Admitted students to Spring 2021 entry are invited to hold their calendars for their program-specific orientations which will take place between January 7-January 17th. \nOrientation Schedule
URL:https://coe.northeastern.edu/event/program-specific-orientations/
ORGANIZER;CN="Graduate School of Engineering":MAILTO:coe-gradadmissions@northeastern.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210112T100000
DTEND;TZID=America/New_York:20210112T110000
DTSTAMP:20260517T104351
CREATED:20201221T212618Z
LAST-MODIFIED:20201221T212618Z
UID:23548-1610445600-1610449200@coe.northeastern.edu
SUMMARY:ECE PhD Proposal Review: Haoqing Li
DESCRIPTION:PhD Proposal Review: Robust Processing against Interferences in GNSS Navigation \nHaoqing Li \nLocation: Zoom Link \nAbstract: Satellite-based navigation is prevalent as positioning applications among our lives\, how-ever\, this high reliance brings potential threats when different interferences and jamming signals are considered. Jamming devices\, although illegal in many countries\, can be easily to get. Those devices can broadcast high-power jamming signals in Global Navigation Satellite System (GNSS) frequency band to destroy receiver’s performance. While jamming signals are illegal and we may get rid of it with the power of law\, other kinds of interferences will cannot even be avoided. Distance Measuring Equipment (DME) signal is applied to measure the distance between aircraft and ground station\, significant in aircraft transport but interference in GNSS processing. Besides\, the GNSS signal itself can also be a interference after reflection and refraction. Since we couldn’t simply re-move those from the source\, methods to mitigate influences of interferences is necessary for stable performance of receiver. There are three main blocks in GNSS receiver: acquisition block\, tracking block and positioning block\, where influence of interferences could be eliminate to get an accurate Position\, Velocity\, and Time (PVT) solution. In this article\, robust statistics processing is applied as one of the interference mitigation methods. This method aims to lower influence of outliers\, which is the presence of many kinds of interferences in either time domain or transformed domain. Robust statistics processing can be used in pre-correlation in both acquisition block and tracking block\, while a robust Kalman filter is designed in positioning block to get rid of interferences. Deep learning\, achieving extraordinary performance in many application domains\, also provides improvement to tracking block against multipath problem. A deep neural network is built to substitute the whole tracking loop to bring robustness to receiver.
URL:https://coe.northeastern.edu/event/ece-phd-proposal-review-haoqing-li/
END:VEVENT
END:VCALENDAR