Projets novateurs réalisés

Changing children’s awareness and behavior toward environmentally sustainable practices through educative programs

In order to improve the understanding and awareness for students about the management of energy efficiency and environmentally sustainable practices, this study will evaluate the effectiveness on changing children’s awareness and behavior toward those aspects through of the implementation of educative material, previously developed by Nature’s Ride, by way of scholastic workshops on primary school children. This study is foreseen helping students gain a clearer understanding of energy-saving practices in their everyday life, to achieve a greater awareness level. A stage of the collection of research data will be done through the use of questionnaires, at the beginning and the end of the fall and winter semesters, to identify the effectiveness of the educative program on their awareness and behavioral change about environmentally sustainable practices. Consequently, according to the responses provided by each child, it will be determined the methodology that will allow an improvement in the educative program delivery to reach a superior grade of learning and consciousness by those students who will attend workshops.

Understanding Montreal festival soundscapes

Quartier des spectacles is a dense multi-cultural hub with large outdoor festivals, also housing an ever-growing residential population due to new high-rise development projects. Given the need to balance vitality with quality of life, this project focuses on expectations of residents and festivalgoers in terms of their sound environment. We implement a methodology to assess the needs of multiple stakeholders and investigate the role that sound plays in the holistic experience of urban spaces.

This project, using Quartier des spectacles as a living laboratory for original collaborative research, is essential to balance the needs of various stakeholders (event promoters, residents, workers, etc.) in order to consolidate this model, unique to Montreal. The findings will be used to create a sound management plan for recreational activities in public places in the Quartier des spectacles and beyond.

An investigation of the occlusive properties of smart polymeric particles usingquantitative image analysis of dentin microtubules

Many young adults are affected by tooth sensitivity stimulated by eating or drinking something hot, cold, sweet or acidic, which impacts their life quality. Tooth sensitivity can start when the softer, inner part of the tooth called dentin becomes exposed. The dentin contains a large number of parallel microtubules that run from the outside of the tooth to the nerve in the center. When it is exposed, these microtubules can be stimulated by changes in temperature or certain foods resulting in the sharp pain. The common treatment is application of occluding agents to block the exposed microtubes. In this project, in collaboration with BTI, we propose to fabricate, optimize and characterize an ‘in vitro dentin model’ using a 3D printing process suitable for evaluation of occlusive particles made by BTI based-on smart polymers and microparticres, potentially able to occlude/penetrate into dentin microtubules to address teeth hypersensitivity.

An Evaluation of Targeted Physical Environmental Interventions in Louis Brier Home & Hospital

In response to the number of residents at Louis Brier Home living with dementia, this project seeks to implement environmental modifications to support resident orientation (specifically related to the hallways and door frames). Based on the data analysis from the observations and focus groups, recommendations will be made for modest physical environmental modifications to promote residents’ quality of life. The partner organization will not only increase quality of care for their residents, but also promote environmental designs other older long term care facilities can implement while awaiting building upgrades.

Alloy and process optimization for improved mechanical properties in age-hardenable and work-hardenable Al sheet manufactured via a new production process termed thin strip casting, TSC

Conventionally, structural Al sheets are produced via casting thick ingots using Direct Chill (DC) technique, followed by an energy-intensive reduction procedure to the final thickness. A new production process developed by CASTechnology, termed Thin Strip Casting (TSC) technique, can directly output thin sheets, thus reducing the cost as well as the carbon foot print associated with the sheet production. The fundamental differences in the TSC vs. DC processing routes, however, impose a widely different metallurgical response in the sheet material, which may drastically affect the optimized processing conditions (e.g., rolling/heat-treating sequences and individual conditions) and thus the final mechanical properties. The proposed internship projects aim at establishing a relationship between the alloy/process conditions and the evolution of mechanical/performance properties of various age-hardenable and work-hardenable Al alloys. A comprehensive alloy/process design can potentially lead to manufacturing cost-effective Al sheets with superior mechanical properties to conventional DC counterparts.

Efficient Detection and Mutli-Target Tracking of Persons in Real-Time Video Surveillance

Locating and identifying multiple individuals in a scene are challenging tasks in real-time video surveillance applications. Although tracking allows to locate a person over time, automatically tracking multiple targets under real-world conditions is a challenging problem due to changes in appearance, occlusions and complex backgrounds. Target models are typically adapted for robust discriminative tracking, although representative training samples must be selected on-line such that knowledge corruption is avoided. This project seeks to develop adaptive systems that can robustly detect and track a variable number of people captured in video sequences for real-time visualization and person re-identification applications. Multi-target tracking methods will autonomously create, associate and remove person tracks based on information extracted from the appearance of each person’s head. For efficiency, different heads being tracked will be associated from frame to frame over constrained target search regions. Tracking-by-detection approaches will be developed for robust tracking, where head appearances are modeled using classifiers that are continuously adapted to changes in the operational domain though on-line and incremental learning. In particular, the proposed systems will incorporate accurate head detection using adaptive ensembles of classifiers based on diverse head representations.

Social Innovation Language and Narratives in Edmonton, Alberta: An Intersectional Approach

This project seeks to build on existing research regarding the current challenges in social innovation work in Alberta, as articulated in Alberta Social Innovation (ABSI) Connect’s 2016 Report on the Future of Social Innovation.

To accomplish this, the intern will interview people in Edmonton who are from multiple marginalized identities (e.g. racialized, identifying as a gender or sexual minority, working class, disabled, etc.) who do work that’s considered as social innovation work through Frances Westley’s definition of social innovation, but may not have the same visibility or recognition as those who do social innovation work in mainstream networks. The intern will then gain a better understanding of the language and narratives that marginalized individuals and/or communities use when talking about social innovation work.

This project will employ an intersectional theoretical framework by seeking and centering individuals or communities doing social innovation work from multiple marginalized identities. An intersectional theoretical lens centers and analyzes the experiences of the most disadvantaged, while using this knowledge to design interventions that are rooted in social justice.

oN DuTy! – Innovative Program on NonDestructive Testing (NDT) – Part 3

NonDestructive Testing (NDT) is a key discipline in major industrial sectors to ensure quality and safety. Several methods are regularly employed in areas ranging from x-ray or ultrasound testing of metallic or composite components in the automotive and aerospace industries, to the inspection of petrochemical ducts using eddy currents or acoustical emissions. The present proposal combines different NDT-related subjects under the oN DuTy! training initiative supported by the NSERC CREATE, whose main objectives are of developing an enriched, unique and innovative Technical and Professional training experience in NDT for students and postdoctoral fellows through a network of leading NDT universities and industrial partners, thereby facilitating the transition of new researchers from trainees to productive employees in the Canadian workforce. The investigated subjects are at the forefront of current worldwide research efforts in NDT and deal with a variety of applications and challenges according to the actual needs of the partners.

Measuring the Contribution of Equipment to Performance: Using portable inskateinstrumentation to optimize skate boot/blade set up, training andperformance in world class speed skaters.

Evolution of the on-ice sport equipment, namely skate boots and blades, has been primarily driven by the users;
however, there is a lack of scientific evidence supporting the link between skate boot/blade design and set up as
it translates to optimal on ice skating technique and performance. We are proposing a new academic-industrialsport
research collaboration that will explore the use of unique performance measurement tools for equipment
managers, coaches, and athletes to support their expertise and augment day to day practices of skate boot/blade
set up and implementation. A series of targeted projects are being proposed to develop, validate, and implement
the use of a portable measurement device and protocol to obtain meaningful metrics of skate boot/blade set up,
technical analysis, and training that translation to producing faster skaters.

Réduction des GES, des odeurs et des composés organiques volatils émis par desbâtiments agricoles par traitement des émissions gazeuses (biofiltration)

La réalisation de ce projet de recherche mènera à l’obtention

d’informations pertinentes relatives à la conception et à l’opération d’une technologie simple de

biofiltration permettant l’abattement des émissions de méthane (un puissant gaz à effet de

serre), des odeurs et des composés odorants émis par des bâtiments agricoles. Cette

technologie est 1) construite à partir de matériaux simple et peu onéreux, 2) simple à opérer et

3) efficace sur une vaste gam me de conditions operationnelles. L’objectif de ce projet est

d’identifier I’impact des conditions d’operations des biofiltres (ex: type de substrat, temperature,

debits de gaz, etc.) sur la reduction des emissions de methane et des odeurs provenant de ces

batiments. Dans un premier temps, des essais en laboratoire seront realises. Ces derniers

serviront a concevoir un reacteur a I’echelle pilote qui sera utilise sur une ferme laitiere.

Establish relationship between productivity and raw material properties to control of a Ferrosilicon furnace

This project will investigate the efficiency of the ferrosilicon smelting process by determining electrical resistance of the raw materials. Ferrosilicon is produced in a submerged-arc furnace, and requires large amounts of electrical energy. The process requires quartz, iron, and carbon as the raw materials. Each of the three input materials have different electrical properties that determine the electrical resistance and therefore efficiency of the furnace. The electrical resistivity of the furnace charge must be controlled to avoid overheating the furnace, generating slag, and increasing the need for maintenance. This project aims to identify the different material properties of each input type and the electrical resistance experienced by the furnace charge as a result of the input materials. A model will be made to relate the effect of the material properties to the electrical resistance of the materials, and then integrated into the operator’s diagnostic tool. An analysis of current on-line feed property measurement technologies will be prepared. Recommendations for integration within the ferrosilicon smelter’s process flowsheet will be made based on the suitability of the technology to the smelter’s specific needs.

Improving Resource Estimation with Machine Learning

The proposed project aims to improve the prediction of mineral resources for better decision making throughout a mining project, that is, to decide whether to reject or to process extracted material using machine learning algorithms. This will help maximize profit for mining companies while minimizing environmental impact as the correct material will be processed more often. The use of machine learning algorithms has become popular recently due to the ability to learn important features from a large amount of data. This will be used to add financial value to mining projects by correctly classifying material mined.