Text mining plays a crucial role in data science by transforming unstructured textual data intomeaningful insights. This exploration delves into the methodologies and applications of text mining using theNatural Language Toolkit (NLTK), a powerful Python library for natural language processing. The talk willhighlight key techniques such as tokenization, stemming, lemmatization, part-of-speech tagging, and sentimentanalysis. By leveraging NLTK’s tools, data scientists can efficiently preprocess, analyze, and derive value fromtext data across various domains, making it an essential component in the broader landscape of data-driven<a href="http://decision-making.Speaker(s):" target="_blank" title="decision-making.Speaker(s):">decision-making.Speaker(s): , , Room: 4359, Bldg: ME, 1125 Colonel Dr, Ottawa, Ontario, Canada

Join us for the 2025 Winter Final Exam Revision: Part 2, where we revisit key concepts in algorithm, programming related questions, project management, and DSP. This session is designed to help you consolidate your knowledge, clarify doubts, and prepare confidently for the upcoming final exams. Whether you’re brushing up on basics or diving into complex problems, this is the perfect opportunity to boost your understanding and excel in your <a href="http://studies.Co-sponsored" target="_blank" title="studies.Co-sponsored">studies.Co-sponsored by: Carleton University - Bachelor of Information Technology SocietyBldg: Room Number: Nicole Building, 1125 Colonel By Dr, Ottawa, Ontario, Canada, K1S 5B6

Vehicle platooning involves a group of vehicles driving in close coordination, maintaining short inter-vehicle distances to improve road capacity, reduce fuel consumption for following vehicles, and enhance overall driving safety. Achieving this coordination requires continuous exchange and processing of environmental sensor data. To further enhance control and service performance without overloading individual vehicles, maintaining digital twins (DTs) of platooning vehicles has emerged as a promising approach. A platoon digital twin (PDT), which integrates the DTs of all platoon members, can serve as a unified interface for coordinated traffic management. However, the effectiveness of PDT-based applications relies heavily on the quality of the PDT, which in turn depends on timely and accurate synchronization with the physical platoon that requires robust communication and computation resources. In this talk, we present our recent work on joint communication and computation resource allocation to support high-quality PDTs under highly dynamic vehicle mobility. We model the problem as an M-th order Markov Decision Process (MDP) to better capture the temporal dynamics of the system. Our solution leverages a multi-agent Deep Deterministic Policy Gradient (DDPG) framework, enhanced with temporal feature extraction, to adapt to rapidly changing network conditions and improve resource allocation <a href="http://decisions.Speaker(s):" target="_blank" title="decisions.Speaker(s):">decisions.Speaker(s): Dongmei Zhao, Virtual: https://events.vtools.ieee.org/m/481625

Join us for a fun and impactful gathering to make our faculty a cleaner, greener place for everyone! "Let's Get Dirty for a Cleaner Earth" is an exciting event where members of IEEE PES Winnipeg Chapter and IEEE Student Branch, University of Manitoba come together to clean up our Engineering Faculty <a href="http://surroundings.Agenda:">surroundings.[]Agenda: Agenda:Where: Gather at the Engineering Atrium of the University of ManitobaActivities: Help us pick up trash and recyclables to beautify the outdoor space around the engineering <a href="http://faculty.What" target="_blank" title="faculty.What">faculty.What to Bring: Comfortable clothing and sturdy shoes, Reusable water bottle, A positive attitude and a willingness to get a little dirtyEngineering Atrium, 75 Chancellors Cir, Winnipeg, Manitoba, Canada, R3T 5V6