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).

Energy management of multi fuel cell vehicles

Power train electrification is currently one of the best solutions in order to design cleaner vehicles. Nevertheless, the internal combustion engine is still essential to ensure high vehicle autonomy (over 500 km) and fast re-fuel (under 5 minutes). To obtain a commercially-competitive electric vehicle, important progress must still be realized concerning the energy storage and especially the batteries (power density, lifetime, and cost).

Video Analytics to Rescue: Privacy Preserving Video Surveillance

Video surveillance is ubiquitous, which has severe implications for an individual's privacy and personal freedom. Consequently there is an increasing interest to design video surveillance systems with built-in privacy protections. This is part of the larger "privacy by design" initiative led by the Office of the Information and Privacy Commissioner of Ontario. This project specifically focuses on event-driven video encryption and decryption. The encrypted footage can only be decrypted and viewed with proper legal authorization.

Novel Nanodevices for Spectroscopy and Nonlinear Optics

One of the next frontiers of integrated photonics is surely represented by the challenge of extending the use of optical techniques to nanometer length scales, overcoming the limit imposed by diffraction, which does not allow focusing light on dimensions smaller than roughly half a wavelength. Metallic nanostructures have proven to be an efficient way to "squeeze" light on such dimensions, significantly enhancing the local field at the same time.

Direct georeferencing of unmanned aerial vehicle photography and radar imagery with a low-cost real-time kinematic GPS.

The conventional (indirect) georeferencing of remote sensing imagery requires the use of control points that link known positions in the imagery to known positions in map coordinates. The number of control points depends on the amount of distortion in the imagery, method of transformation and desired level of accuracy, but it is often large. Overall, the collection of ground control points is a cumbersome and time-consuming operation, and almost an unrealistic one when it comes to the georeferencing and mosaicking of a set of images acquired from a small unmanned aerial vehicle (UAV).

Small unmanned aerial vehicles (UAVs) for high-resolution environmental remote sensing: a soil moisture case study.

Successful research in environmental remote sensing relies on multiple-view approaches to data collection. In multi-stage remote sensing, data are collected at different geographic scales. Low-altitude, high-resolution aerial observations bridge the gap between in situ and satellite-based observations. These can be achieved by unmanned aerial vehicles (UAVs), with minimum logistical support and lower operation/maintenance costs than manned aircrafts.

UAVs (also known as drones) are remotely-controlled or autonomous aircrafts without a pilot aboard.

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