Research on Robust Face Recognition Algorithms

In recent years, face recognition algorithms based on deep neural networks have achieved human-level performance when tested on face recognition database. However, when put into real-world application, those algorithms are not robust enough, due to factors such as different lighting conditions, camera distance, and face orientations.

Dynamic Bandwidth Management

In the telecommunications industry, many schemas exist to cap or limit bandwidth at certain levels for clients. However, there are no real options available to allow clients to intelligently utilize spare bandwidth above their committed purchase rates. We propose to design, implement and evaluate novel bandwidth allocation mechanisms for high speed networks like the Cybera network. Cybera is a not-for-profit, technology-neutral organization responsible for driving Alberta’s economic growth through the use of digital technology.

Legal Question Answering with Machine Comprehension

ROSS Intelligence enables legal professionals to find analyze legal issues and find hidden information and cuts down on research time by using artificial intelligence specialized in legal research. Recent advances in neural networks applied to
natural language processing have brought results that are close to human performance in some tasks. However, this approach is still nascent in legal research and it has been identified as potentially fruitful.

Email Mining, Modeling, and Visualization

For this project, a data mining, visualization, and modeling technique will be developed and tested specifically for emails, using publicly available datasets. The mining will consist of gathering email and other potentially related datasets and cleaning those datasets. Cleaning will consist of removing duplicate or unnecessary information, as well as labeling data with basic information in order to ease training in the later steps. Next that data will be visualized in some form (graphs, charts, etc.) so that it may be more easily understood and a training model can be development.

Cited: Partnered Knowledge Mobilization Between Research and Media Organizations

Cited is a multimedia knowledge mobilization project that tells stories about research and academia to a general audience. It is experimenting with a unique co-creative approach that puts students, journalists, and researchers together on the same team. Mitacs interns will work with Cited media partners to conduct original research that builds interviews, documentaries, and other media related to research and academia—particularly in the social sciences and humanities. These will be distributed widely through a network of partners across North America.

Sparse Multivariate Polynomial Factorization

Factoring large polynomials is one of the main tools provided by mathematical software packages like Maple. It is used by scientists, engineers and mathematicians directly to simplify and study large formulas. It is also used inside Maple to do other tasks such as solving systems of polynomial equations. This project proposes to dramatically improve the speed of polynomial factorization so that larger polynomials can be factored and factored quickly, for example, in minutes instead of
days.

Mix-and-Match Pipeline to Ease the Creation of New Facial Models for Video Game Applications

Ubisoft has an extensive database of character’s heads represented as polygonal meshes. Those come from two primary sources: processed 3D scans and models made by artists. It would be convenient to use this database to mix-and-match parts of characters to create new human-like character heads. Let’s say we wish to replace the nose of one character with another nose. We want the junction between the nose and the surrounding areas to be as seamless as possible while accommodating for the new nose, which could have a different size.

CCHP multi-criteria optimization in a bottom-up, decentralized control system with top-down centralized objective and query based control

ElectroMotion Energy has created an all in one AC, heating, hot water, and electricity unit to serve industrial and residential needs. This unit requires optimization algorithms and an advanced control system to optimize performance of the deployed unit around multiple objectives. These objectives consist of: meeting onsite electricity demands, meeting on site heating or AC demands, taking advantage of economical times to sell power to the grid, and to assist the municipal grids in providing electricity during peak demands.

Ultra-low power connectivity platform for low power Internet of Things (IoT) sensor nodes

In this project we address the problem of power consumption for wireless sensor nodes. This is where among different components of a sensor, RF transceivers consume a significant amount of power e.g. approximately 80%. Hence the main objective is this project is to tackle the power consumption problem at the RF transmitter, where we aim to reduce the power consumption to micro-watts of power, with minimal sacrifice in achievable data rate and by keeping the connectivity range within an acceptable radius.

Optimization of Impact Diverting Membrane on Bicycle Helmet

Head Injury Prevention (HIP) Lab at Simon Fraser University in collaboration with Shield-X Technology Inc. had previously developed an impact diverting mechanism in the form of a thin multi-layered-membrane. The technology has been successfully integrated onto the exterior of a football helmet (external version) to reduce linear and rotational acceleration experienced during impact to the head. The research will focus mainly on how to adopt the technology by adding it into the interior of a single-impact helmet such as bicycle helmet without changing the exterior appearance of the helmet. A

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