Investigation and Implementation of Integrated Electronic Scanning Automotive Radar Sensor front-end module at 77/79GHz band for Short and Long Range, High Angle and Range Resolution detection

The main objective of this project is to investigate, design, fabricate and characterize an integrated front end module for next generation of automotive radar sensors, which have the ability of pedestrian detection and detecting short-range and long-range objects
around the car. To meet such requirements and to reduce the size of the radar sensor, next generation of automotive radar sensors should be designed at millimeter wave (76-81 GHz) with sufficiently low production cost for mass market. This introduce several research
challenges in both transceiver and antenna array.

Routing and Spectral Assignment in Mesh Optical Networks

The project consists in the design, development and testing of algorithms that can solve the routing and wavelength assignment problem in optical networks, for data instances with up to 100 wavelengths and few hundred nodes. Indeed, for each demand between a source and destination, it consists in determining a route, and assigning it a wavelength such that no link supports 2 routes with the same wavelength.

A hybrid brain-computer interface (BCI) using tactile stimulus and motor imagery

Brain computer interfaces (BCI) allow for persons with severe motor impairment to communicate with the outside world. These systems work by either providing some stimulus (in the form of sound, touch or visual cues) or asking the user to imagine a certain motion. By analyzing the resulting brain activity using superficial electrodes on the scalp, a technique known as electroencephalography (EEG), selections on a computer may be made. Our research will combine motor imagery with tactile (touch) stimulus into one hybrid BCI.

Architecture for a 3D-Vision FPGA-based System for Real-Time Object Tracking

Object tracking using stereo video is a field of research applicable to a large number of applications. However, most proposed methods are complex, and require significant computing resources to be implemented. As a result, the number of applications and environments where object tracking systems can be realistically deployed is limited.

Improved Automated Tracking of Workouts for Fitness Facilities

Fitness tracking is the process of tracking the fitness-related activity and metrics of a person such as heart rate, distance walked, and consumption of calories. Emerging and specialized wireless sensors and devices also enable the tracking of movements performed during workouts in gyms. This project will help improve the motion tracking experience by reporting workout activities to gym customers, in real-time and in usable ways (via new auditory feedback and enhanced user interfaces) on their Android smart phones.

Network Function Virtualization (NFV) Driven Micro Service Architecture for Value Added Video Streaming Services in Content Delivery Networks

The NSERC Strategic Network for Smart Applications on Virtual Infrastructures is a five-year partnership between Canadian industry, universities, researchers, research and education (R&E) networks, and high performance computing centres to investigate the design of future application platforms that will deliver software applications of greater capability and intelligence.

GPU Performance Auto-tuning Using Machine Learning

Optimizing a program for Graphics Processing Units (GPUs) is critical for performance, yet remains a challenge due to the non-intuitive interactions among the optimizations and the GPU architecture. Automatic optimization tuning for a GPU is demanding particularly given the exploding number of mobile GPU variants in the market.

Robust identification of protected heath information in unstructured data

A large amount of health-related data is available only in unstructured form (“free-form text”). To share this data for secondary purposes, it is necessary to de-identify it to protect against inappropriate disclosure of personal health information (PHI). PARAT Text is Privacy Analytics’ de-identification software for unstructured data. It automatically discovers and marks PHI in a variety of document formats using gazetteers and a bunch of rules. The primary problem of this tool is that it is limited by the knowledge of human experts, gazetteer lists, and lack of contextual knowledge.

En Route to 5G: Long-term Evolution (LTE) Enhancements for the Internet of Things (IoT)

Cellular wireless communication has reached a level of coverage and reliability that it is considered a commodity. However, the dramatic increase in Internet traffic to and from wireless devices poses significant challenges for network operators. While the current growth of traffic is mostly due to consumers communicating more frequently and larger amounts of data over the wireless infrastructure, much of the future growth is predicted to come from non-human operated devices or so-called machine-to-machine (M2M) communication.

A Knowledge Management System for Knowledge-Intensive SMEs

Knowledge-intensive enterprises (KIE) play an important role in the knowledge-based economy (OECD, 2007). Knowledge-intensive enterprises can be loosely and preliminary defined as organizations that offer to the market the use of fairly sophisticated knowledge or knowledge-based products and services (Doloreux & Shearmur, 2011). Knowledge management is important for both large enterprises and small and medium-size enterprises (SME). As a matter of fact, many topics related to knowledge management in SMEs have not been well studied yet (Durst & Edvardsson, 2012).

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