Innovative Projects Realized

Learning Partnership for Community Development and MinoBimaadiziwin in Brokenhead Ojibway Nation

Post-secondary education, if community-led and projects-based, has the potential to transform education, food and housing policy, as well as build capacity locally in Brokenhead First Nation compared to two First Nations lacking road access. This partnership will explore optimal solutions to resolve development challenges through applied adult education, particularly applied to housing, food and community development. By conducting participatory action research we will collaborate to leapfrog Indigenous development and post-secondary education from colonially imposed to self-determined and community-led educational development. Students evaluation of programming and surveys of workplace integration.

Évaluation des pratiques de communication du Festival de musique émergente en Abitibi-Témiscamingue

Le Festival de musique émergente en Abitibi-Témiscamingue est en reconfiguration de ses communications. Il est entendu ici que tous les outils de communication, que ce soit la stratégie sur les réseaux sociaux, le site Web, l’application mobile ou encore les communiqués de presse et les infolettres, sont en évaluation afin de déterminer quelles sont les pratiques sur lesquelles miser, et lesquelles doivent être optimisées. Pour ce faire, des recherches documentaires seront réalisées afin de déterminer les pratiques d’excellence d’autres festivals à travers le monde. Ensuite, il faudra déterminer quelles pratiques d’excellence sont applicables aux communications du festival afin de les optimiser et rejoindre un grand nombre de personnes.

La numérisation du contrat d’édition et la technologie de la chaîne de blocs

Le présent projet de recherche s’intéresse à la numérisation des contrats d’édition entre les éditeurs et les auteurs. En effet, les éditeurs rencontrent principalement trois problèmes dans leurs relations avec les auteurs. Le premier concerne le contenu du contrat d’édition ; le deuxième est relié à la rétribution financière des auteurs ; et enfin le troisième a trait à la numérisation des conventions. L’objectif de cette demande de financement est de proposer des solutions à ces problèmes. Pour ce faire, il s’avère important pour l’éditeur de numériser les contrats afin d’en garder la trace et d’en assurer la pérennité, d’où la question de la nature de la solution technologique qui pourrait être développée afin d’assurer cette numérisation algorithmique.

La recherche aura comme objectif de développer un contrat d’édition type et d’analyser l’utilisation de la technologie de la chaîne de blocs dans le contexte de l’industrie du livre. Cette recherche se doit d’être transférable et l’entreprise doit tirer profit des résultats obtenus.

Forecasting Profitability of Real Estate Assets using Machine Learning

This research project aims at applying machine learning over the existing financial forecasting methods currently employed in the commercial real estate industry. Businesses are actively collecting more data than what can be analyzed effectively using the standard spreadsheet models which have become industry standard over the past few decades. Machine learning algorithms are known to be able to extract complex relationship between many variables in data which make them perfect for an application geared towards forecasting the financial performance of commercial real estate assets. This task involves aggregating large amounts of data specific to the asset in question such as revenue, expense and leasing information as well as relevant economic data including rent growth and employment figures. This project will evaluate the performance of some of the most common machine learning algorithms and their relevance to predicting the performance of commercial real estate. Much of the research that currently exists at the intersection of finance and machine learning revolves around the public financial markets or the mass appraisal of residential real estate.

Improvement of Geotechnical Resistance Factors (GRF) derived from PDA testing results for use in pile design

Piles are implemented as foundation to support the structure by aim of transferring load to the surrounding soil and/or to a firmer stratum. Pile foundation supports majority of structural elements of oil and gas and infrastructure projects in Alberta. In most of these projects, driven steel pipes or H-piles are used.
This research is aim to reduce pile foundation cost r reduction in the numbers, length, and the size of the piles through using lower Geotechnical Resistance Factor (GRF). In order to optimize the GRF value, the field data from several historical cases and mathematical models will be used.

Antibacterial activity of silicone porphyrins

Porphyrins and phthalocyanines are important biological molecules that, for example, control respiration of plants (chlorophyll helps convert C02 to oxygen) and heme controls the 02/C02 balance in human blood. Such compounds possess many other regulatory roles. In the presence of light some of these compounds convert oxygen into ‘reactive oxygen species’ (ROS). ROS aggressively attack biological molecules. In some cases, the ROS can destroy pathogens, including fungi and bacteria. Silicones are widely used in applications ranging from bathtub sealants to contact lenses; they are very resistant to oxidation. In this project, we will combine porphyrins and silicones with the objective to create antibacterial rubber interfaces. Porphyrins will be tethered to silicone elastomers at or near the air interface. Bacteria (models – E. coli) will be exposed to the surface and the ability to kill the microorganisms in light and dark will be optimized.

Development of Advanced Process Control for the Production of Specialty Nickel Powder Products

With the global movement towards electric vehicles (EVs) to combat pollution and climate change, one of the potential limiting factors for public embracement of the technology is the limited vehicle range and high cost largely due to the current state of battery technology. Battery makers require high-purity nickel in an appropriate physical form (e.g. powder), but the availability of such nickel is limited to a small number of producers in the world. This project investigates increasing the yield of nickel powder from a production process through the use of in-plant experimentation, modelling, and advanced process control and optimization techniques.

Feasibility analysis of printing a drug-eluting flexible antibacterial mesh for treatment of post-surgical infections

Surgical site infections (SSIs) are caused by germs after surgery. Germs such as Staphylococcus, Streptococcus, and Pseudomonas can infect a surgical wound through various forms of contact, such as from the touch of a contaminated caregiver or surgical instrument, through germs in the air, or through germs that are already on or in your body and then spread into the wound. The development of an SSI leads to a substantial increase in the clinical and economic burden of surgery due to the direct costs incurred by prolonged hospitalization of the patient, diagnostic tests, and treatment. Eupraxia Pharmaceuticals Inc. has developed a proprietary controlled?release system that reduces the side effects of intravenous injection of antibiotics. In this work, will perform a feasibility study on the use of 3D printing to manufacture patient-specific meshes using Eupraxia’s formulation. To achieve this goal, we will perform a series of studies on the characterization of different formulations of Eupraxia’s polymer to determine the best formulation that is printable using extrusion-based printers. We will also fabricate a costume-made 3D printer with components that are compatible with the used materials.

Rethinking Byzantine Fault Tolerant (BFT) Protocols in the Age of Blockchains

Blockchain technology is gaining an increasing amount of attentions in the past few years, partially due to the popularity of Bitcoin and other cryptocurrencies. It has the potential to profoundly disrupt a wide range of industries. Despite its great potential, today’s blockchain has several major hurdles. First, it can be slow. Second, it can be costly. Third, it has scalability issues. In this proposed research, we aim to create a blockchain testnet for evaluating different blockchain algorithms, such as Tendermint, Casper, Thunderella, Honey Badger, and Algorand. The testnet will not only serve as a fair means of comparison but also provide us with an in-depth understanding of design space and tradeoffs among different blockchain algorithms. The research outcomes are expected to provide the partner company with substantial insights into the security and performance of various blockchain algorithms.

Robust Inventory Routing Problem Under Uncertainty

We dedicate to inventory routing problems with uncertain demand, arising from supply chain systems. We determine replenishment times, quantities, and vehicle routes to serve customers. To predict customer demand, we use machine learning techniques to extract information from historical data, which is normally available in big data era. We use distributionally robust optimization method to build mathematical models and develop software packages that can directly be used by suppliers to plan their supply chain activities. The outcomes of our project can help suppliers effectively control inventories and allocate transportation vehicles, thereby optimizing resource allocations, reducing operation costs, and better serving customers. Furthermore, optimizing vehicle schedules makes a good environmental sense, because transportation produces most of the CO2 in supply chain activities.

Quantum Optical Experiment to Understand Black Holes

Black holes are very intriguing astronomical objects. They do not emit light, so we can only get indirect evidence about their existence. When it comes down to understanding how they change in time, things get more complicated. Stephen Hawking argued that black holes have a finite lifetime. The question that arises then is, what happens to the objects swallowed by a black hole and, in particular, the information carried by them when the black hole evaporates away? Does the information disappear? If so, this would be in contradiction with quantum mechanics, which preserves information. This is known as the information paradox and it is an unresolved problem in physics.

Our project focuses on an quantum optical process, parametric amplification, that is equivalent to the evaporation of a black hole. By using powerful lasers and special crystals we push parametric amplification to a new high-gain regime that might teach us where the information goes in black hole evaporation.

The aim of this overseas collaboration is to exploit the expertise of the German group in high gain parametric amplifcation and our theoretical knowledge on the black hole dynamics. TBC

BIM-based Component-level Construction Sequence Planning for Precast Concrete Building

Precast concrete building is one type of prefabricated construction, in which some of the building components are produced in factories and transported to construction site for assembly. Because it focuses more on individual building components rather than the whole floor or construction area, traditional construction scheduling based on the floor or area level is not appropriate for precast concrete building, considering the duration, cost and resource of the project. A component-level construction scheduling is then needed. This research aims to develop a Building Information Modeling (BIM)-based component-level construction sequence planning method. The scheduling required information of building components is extracted from BIM model and being used for generating a component-level schedule network, which describes the technical precedence relationships of components. This research lays the foundation for subsequent resource-constraint project scheduling for precast concrete building and will improve the construction management level of precast concrete building.