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Thursday, May 30, 2024
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Online Teaching and Learning Strategies
- Location: Online
- Contact: CITS Instructional Development
- Description: A rigorous four-week, fully online certification course that introduces faculty to the current research and best practices for online teaching and learning. Using their own discipline-specific course materials for activities, faculty will work independently, and collaboratively with peers from across campus, and with Instructional Designers to design and build one unit of online instruction in a myCourses site. This unit will meet the Quality Online Course Review Rubric criteria and be a model that faculty can reference and replicate as they continue to develop their upcoming fully online course(s).
- Topical Areas: Training, Workshop, audience: Faculty
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| All Day |
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Add/Drop Ends
- Location: Online
- Contact: Online & Continuing Education
- Description: Summer 2024 Add/Drop period for 100% refund ends for the 12-week session.
- Link: https://www.umassd.edu/online/
- Topical Areas: OCE Academic Calendar, OCE Summer, OCE 12-week session
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9:00 AM
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1:30 PM
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The EDGE Assembly Educate, Develop, Guide, Empower
- Location: Main Auditorium (Angus Bailey Auditorium)
, 285 Old Westport Road, Dartmouth, MA
- Cost: 0
- Contact: Office of Diversity, Equity & Inclusion
- Description: The New Bedford Shannon Program in partnership with the UMass Dartmouth Office of Diversity, Equity & Inclusion presents:
The EDGE Assembly Educate, Develop, Guide, Empower
Open to all local Middle & High School Students
Good decision-making equals great destiny,
Keynote speaker: "Motivated by Math, "Mathematics went from the darkness to the light. From Death to a life of discipline. From a life of crime to being a wise man. His passion is presenting a message that inspires those doubtful, lost and struggling and his words help them shine and change their state of mind."
Transportation and Lunch will be Provided
Speakers & Campus Tour
Parents are Welcome
- Topical Areas: General Public, University Community
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| All Day |
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Wait List Ends
- Location: Online
- Contact: Online & Continuing Education
- Description: Summer 2024 Wait List ends for the 12-week session.
- Link: https://www.umassd.edu/online/
- Topical Areas: OCE Academic Calendar, OCE Summer, OCE 12-week session
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10:00 AM
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12:00 PM
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ELE Master of Science Thesis Defense by Erika Caushi - ECE Department
- Location: > See description for location
- Cost: Free
- Contact: > See Description for contact information
- Description: Topic: EVALUATION OF THE SCALABILITY OF 1-D FR-CNN FOR SIGNAL IDENTIFICATION AND CLASSIFICATION OVER A WIDEBAND
Location: Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A
Zoom Conference Link: https://umassd.zoom.us/j/91700091674
Meeting ID: 917 0009 1674 Passcode: 888863
Abstract:
In the realm of Next Generation (NextG) wireless communication systems, spectrum sharing emerges as a solution to spectrum scarcity, catering to high data rates and improved quality of service. A critical aspect of enabling such spectrum sharing lies in sensing the electromagnetic spectrum (EMS) and characterizing surrounding wireless signals. Machine learning (ML) emerges as a key tool for this purpose. Leveraging established techniques like convolution neural networks (CNN), region-based convolution neural networks (R-CNN), fast region-based convolution neural networks (Fast R-CNN), and faster region-based convolution neural networks (FR-CNN), multiple signals can be identified and extracted simultaneously from a channel. This paper delves into optimizing the FR-CNN tailored for 1-dimensional (1-D) signal processing for EMS sensing over a wideband, testing and evaluating the scalability of the model as the bandwidth varies. Models are meticulously developed and compiled to operate across various platforms including CPU and GPU. Additionally, universal software radio peripheral (USRP), GNURadio, and RFNoC are used for wideband receiver design to perform the over-the-air tests. Through rigorous evaluation in simulation and over-the-air, it becomes evident that the optimized 1-D FR-CNN is highly scalable in terms of locating and characterizing the active signals within band of interest. Furthermore, while R-CNN demonstrates reduced classification time, a notable compromise is observed in classification accuracy. This optimization journey underscores the intricate balance between speed and precision, crucial for effective spectrum utilization and management in the dynamic landscape of wireless communication systems.
Advisor(s): Dr. Ruolin Zhou, Associate Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
Committee Members:Dr. Dayalan P. Kasilingam, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth; Dr. Hong Liu, Commonwealth Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
*For further information, please contact Dr. Ruolin Zhou email at rzhou1@umassd.edu
- Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering
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