Innovative Projects Realized

Next Generation Catalyst Layer Design for PEM Fuel Cells

The performance of non-precious metal catalysts (NPMCs) for proton exchange membrane fuel cell (PEMFC) has now reached a stage at which they can be considered as possible alternatives to expensive Pt, especially for low power applications. However, despite significant efforts on catalyst development in the past, only limited studies have been performed on NPMC-based electrode designs. Thus, it is required to develop an effective NPMC-based electrode that can correctly balance the complex parameters to maximize the performance it can bring. Herein, we propose the research and development of cost-effective NPMC electrodes with enhanced performance from hierarchical nanoarchitectures. This work entails a unique and promising approach in the advanced manufacturing of nanostructured NPMCs and electrodes with accurate engineering of their nanostructures.

Développement d’un modèle prédictif de la valeur globale future d’un client dans le secteur b

Le Mouvement Desjardins, coopérative financière appartenant à plus de 4 millions de membres au Québec et en Ontario, évolue dans le contexte très compétitif du secteur bancaire. De plus, ce secteur voit apparaître de nouveaux concurrents non traditionnels dans plusieurs sphères des services financiers (financement participatif, solutions de paiement, transferts de fonds, etc.). Afin d’être en mesure de demeurer compétitif face à ces concurrents et de générer à long terme de la valeur pour ses membres et la collectivité, l’organisation doit évoluer constamment afin d’offrir les meilleurs services financiers en fonction des besoins particuliers de ses membres. La rétention et la satisfaction des membres sont au coeur des préoccupations de l’organisation, de même que la rentabilité des offres qui leur sont faites, élément indispensable à la santé à long terme de l’organisation.
TO BE CONT’D

Validation of the educational impact of a holographic lecture

UBC and Microsoft intend to collaborate on an applied research project where 3D models of the brain will be used to create an interactive Holographic lecture using Microsoft’s new augmented reality device, the HoloLens. The will form the basis for a lesson or “HoloLecture,” and will feature new interactions to take advantage of the HoloLens’s technology. The ability to manipulate the 3D objects and dynamically adapt them to a live lecture format will form the basis of a HoloLecture prototype that can be applied across disciplines. The investigation and validation of this approach will include not only an evaluation of the student learning experience and their learning outcomes, but also the ease of use for instructional staff to ensure that barriers to adoption of this new technology are lowered. TO BE CON’T

Feasibility and usability of ultrasound in aiding breast tumor detection Proposed period of internship

n this research we propose to carry out a feasibility study to identify an ultrasound transducer that can be used specifically for breast cancer tumor detection. This transducer will be interfaced with the available Ultrasonix Elastrography System at SFU. This will be the most significant part of the proposed research. It will include assimilation of the transducer with the ultrasound machine along with data capturing and analysis. Fast algorithms are necessary in this kind of imaging. Strains between frames are small, thus the sensitivity of the algorithms is also very important.

The data capturing will be done using breast phantoms. The breast tissue phantoms and tumor phantoms will be developed with material which has elastic properties similar to breast tissue and tumors. A preliminary probe design will also be proposed after the assessment for the suitability of use of the probe to make it available to wider audience.

Advanced Manufacturing of Graphene Oxide Membranes for Acoustic Drivers

The Graphene Audio group at TandemLaunch is working to revolutionize loudspeaker design through the use of graphene composite materials (Graphene-CMs) in loudspeaker membranes. Graphene is a newly discovered material with exceptional mechanical and electrical characteristics. Its low mass and high strength make it ideal for use in acoustic transducers offering an immediate benefit over existing loudspeaker technologies.
This project seeks to improve the manufacturing techniques and acoustic characteristics of these Graphene-CMs. Student researchers will focus on developing scalable industrial processes for making the Graphene-CM materials and for assembling loudspeakers from this unique new material. The project will involve students from Electrical Engineering, Material Sciences, Chemistry, and Sound Recording to help change how we hear the world around us. From micro-speakers in laptops and cell phones to subwoofers at rock concerts, this work will advance loudspeaker technology and improve the sound quality and efficiency of the speakers we use every day.

Interactive preference elicitation application for book recommendations

Kobo is an online e-book retailer that provides recommendations for future purchases to its user base. One difficulty that recommendation systems face is what is known as the “cold-user” problem. In this scenario, when we know so little of a user’s preferences (for example, if they are new to the platform), we do not have any basis for recommendations. The goal of this project is to develop an interactive application that can elicit such preferences from users about whom we have little information, and that can help improve recommendations for power users. For new users, the preference elicitation process during onboarding can help them find books of interest much faster; for established users, it gives them the ability to refine their recommendations. Such improvements facilitate a more streamlined discovery experience.

Évaluation préliminaire des scénarios de restauration du parc principal à résidus minier de la mine LaRonde

Une grande partie des rejets produits par l’industrie minière est souvent entreposée en surface. En contact avec l’oxygène atmosphérique et l’eau, les minéraux sulfureux contenus dans ces rejets s’oxydent et génèrent un drainage minier acide (DMA) comportant des contaminants préjudiciables pour l’environnement. Une des techniques utilisées pour contrôler ce phénomène est les recouvrements à plusieurs couches. Ces couvertures sont habituellement constituées des matériaux meubles d’origine naturelle. Ces derniers ne sont pas dans tous les cas, en quantité et qualité utiles localisés à proximité des sites à restaurer. Notre projet de stage à la mine LaRonde (Québec, Canada) a pour objectif d’évalue de façon préliminaire, à partir de parcelles expérimentales, la possibilité d’utiliser que des matériaux miniers dans de tels couvertures. TO BE CONT’D

Analysis of TGF-? traps as effective immunostimulating cancer treatments

AVID200 is a TGF-? trap that specifically sequesters TGF-?I and TGF-?III to enhance antitumour immunity to inhibit tumor growth. AVID200 also avoids adverse side effect of depleted of TGF-?II. AVID200 is relatively short-lived in circulation, decreasing its capacity to exert desirable enhancement of anti-tumour immunity. To increase the effectiveness of TGF-? traps, a panel of candidate molecules that retain TGF-? isoform specificity and inactivating capacity, but with projected increased stability, have been generated by Formation Biologics. To support an investigational new drug (IND) application, mouse models of breast, melanoma and ovarian cancers will be treated with these TGF-? traps. Their effect on the immune system and tumor inhibition will be determined both as single agents and in combination with immune stimulating drugs. These experiments will provide preclinical evidence of the effectiveness of candidate TGF-? inhibitors on mouse models of cancer in preparation for an IND application and clinical trials.

Development and Demonstration Engine Technology for Class 8 Heavy Duty Trucks Fueled by Waste Hydrogen

Hydra Energy Corporation Commercial Demonstration Project will be based in Prince George, British Columbia 12.4 MT/day of waste hydrogen will be captured, purified and transported to an onsite hydrogen refueling station from which (at least) 53 Class 8 tractor-trailer trucks will refuel daily. Hydra’s demonstration project can provide a significant reduction in fleet greenhouse gas(GHG) emissions, Particulate Matter and other air emissions. Hydra is currently testing the first prototype dual-fuel hydrogen/diesel heavy-duty class 8 truck in North America. And, in collaboration with the University of British Columbia (UBC) is conducting thorough experimental investigation of the potential fuel efficiency improvements and emissions reductions that may be realized by fueling an internal combustion engine with hydrogen and diesel fuel at various. The R&D project results will advance the scientific knowledge of hydrogen in internal combustion engines, and will help to expand the availability of clean energy transportation technologies in and beyond B.C.

Prediction Improvement on User’s Consumption

The goal of the research is to implement different data mining algorithms in order to improve the prediction on a user’s electricity consumption. The research will be dedicated to improve the existing algorithms or implementing new algorithms for the improvement of the prediction accuracy. Besides application of the prediction algorithms, different data pre-processing methods will be used. Research will include supervised and unsupervised modelling of the dataset by using the R programming language. As well, the segmentation of the customers based on the similarity measures in order to increase the prediction accuracy will be investigated. This research will lead to the improvement of the prediction accuracy which will bring more customers to the company as well as help the existing customers to save more energy, therefore more money.

Applied Machine Learning for Malware and Network Intrusion Detection

Wedge Networks is a leading cybersecurity solution provider in Canada. In this project, we aim to investigate the application of statistical machine learning and deep learning to cyber threat detection, aiming to detect both network intrusions and malware binaries transmitted in the network. Based on the big data collected from Wedge’s system logs and anonymized domain-specific data gathered from the clients of Wedge Networks distributed worldwide, we will investigate: 1) Distributed Denial-of-Service prevention and network intrusion detection based on both supervised and unsupervised machine learning techniques, and 2) shallow and deep neural network models for malware detection and prevention. To scale up to the big data at Wedge Networks, we will implement the developed machine learning and deep learning algorithms on distributed processing platforms such as Spark and TensorFlow. We will also integrate the learning-based threat detection module in the WedgeARP product line.

Resource potential of the Post Creek Property, Sudbury, Ontario

Sudbury represents the site of a meteorite impact structure originally greater than 200 km in diameter and that formed 1.85 billion years ago. Despite the proven and potential economic benefits of resource development at Sudbury, there are still major outstanding questions concerning our understanding of the structure and its ore deposits. A series of objectives have been composed concerning the origin of Sudbury Breccia, host to footwall vein deposits, and Offset Dykes at the Post Creek locality and their mineralization. Fieldwork forms the basis for this proposed research, coupled with sample investigation using a range of micro-analytical techniques. The results of the proposed research will address significant gaps in our current knowledge of the origin and emplacement of Offset Dykes and Sudbury Breccia and will enable the resource potential of the Post Creek Property to be determined.