Innovative Projects Realized

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.

Evaluating Gradients of Natural and Induced Stress on Fish Blood Parameters; Developing more accurate results from Point-of-Care Devices

The point-of-care i-STAT and VETSCAN units are easily portable blood-based assessment tools that can produce relevant blood parameters within minutes with only 2-3 drops of blood. The objective of this study is to examine both natural and investigator-applied stress gradients in fishes and compare blood chemistry of fishes from a range of environments (e.g., low to high stress). Investigations will occur in the lab and in the field at IISD- Experimental Lakes Area (ELA), where field data from devices will be compared to standard laboratory methods in the University of Manitoba in order to produce a point-of-care instrument better suited for fish. With the completion of this project, IIED-ELA will have greater knowledge about the current fish population within lakes, as well as access to devices that can be used in the field collect fish health data.

Manipulation de l’environnement lumineux pour optimiser le contrôle biologique des ravageurs sous serres ainsi que la croissance et la productivité des plantes

L’alimentation durable est une composante essentielle de l’économie durable visant à un développement économique apte à répondre aux besoins du présent sans compromettre la capacité des générations futures à répondre aux leurs. Pour ce faire, l’alimentation durable préconise la consommation de produits locaux et, en ce qui concerne les produits maraîchers, cultivés dans le respect de l’environnement. En milieu urbain, la culture en serre et plus particulièrement la culture verticale (rendue possible grâce à l’éclairage DEL), constitue une option des plus intéressantes.

L’objet de la présente étude sera la manipulation du spectre lumineux afin d’optimiser la saine croissance de végétaux sans l’utilisation de pesticides. Positionner le Canada en tant que leader de la culture biologique et durable en milieux contrôlés (serres et bâtiments : plant factory) aura un effet bénéfique tant sur l’économie que sur la santé de l’ensemble des Canadiens.

Reducing the carbon footprint at Hydro One

The purpose of the research project is to develop options for the reduction of the carbon footprint at

Hydro One Networks Inc. (HONI).The research will focus on helping HONI meet a reduction goal of

half of current emission levels over the next decade. The company has taken preliminary steps to

assess and plan for reduction of the company’s carbon footprint, including the collection of

preliminary data and the outlining of programs to reduce their impact on the environment. The research

project will further contribute to those efforts by focusing on providing three outputs: 1) process maps

whereby HONI may systematically identify its current carbon footprint, 2) scenario analyses to help

HONI project its future carbon emissions over varied timelines, and 3) a set of recommended actions

to reduce carbon emissions over the next decade. Completing the research will address an identifiedneed at HONI and will provide a tangible demonstration of the company’s commitment to reducing its

impact on…TOBECONTINUED

Assessing and Identifying Clinical Checklists in Intensive Care Settings

type of treatment they will provide to patients. With technological improvements and the availability of a significant volume of data, it is increasingly difficult for care providers to properly evaluate and analyze the options available to them. The current health condition of the patient–reflected in the monitored observations which are recorded in EMR–may depend on all the relevant information from all prior observations and selected treatments, not just those most immediate (e.g., the trend of various health measures). This project is focused on developing algorithms that disentangle this history, physician decisions and the outcome (patient survival or death) to assess and identify when actions may lead to irrecoverable negative outcomes. With the identification of these suboptimal actions, correctly associated with the time they are taken, the algorithm can actively discourage doctor’s from repeating such actions when they encounter similar patient histories in the future.

Caractérisation nutritionnelle et détermination des taux d’incorporation optimaux de farine de viande (pork meal) pour une utilisation efficace chez le poulet de chair

Dans une optique de durabilité, les filières animales sont à la recherche d’alternatives pouvant remplacer le maïs et le tourteau de soya très utilisés pour alimenter les animaux et qui entrent en compétition avec l’alimentation de l’homme. Dans ce cadre, les farines animales, riche en protéines, gras, phosphore et calcium, sont déjà utilisées pour substituer une partie du maïs, du tourteau de soya et des minéraux ajoutés chez le poulet de chair. En effet, celles ayant une teneur élevée en protéine (58-60%) et gras (12%) comme la farine de porc remplace avantageusement le tourteau de soya. Les taux d’incorporation demeurent cependant faibles (5-7%) compte tenu du peu d’informations de cet ingrédient sur les performances de croissance des oiseaux. L’objectif du projet est donc de caractériser la valeur nutritionnelle du produit en termes de composition et utilisation par les poulets et de mesurer l’impact de différents taux d’incorporation sur les performances de croissance, l’humidité des fientes et la composition corporelle en lipides et protéine et contenu minéral osseux, ainsi que l’efficacité d’utilisation de ces nutriments.

A Survey on Application of Visualization and AI Algorithm-Driven Technology for Healthcare

Healthcare facilities collect and produce vast amounts of clinical-relevant data. Various AI-related methods (like computer-aided detection for mammography and the learning and visualization of clinical pathways) are applied to healthcare these days, and visualization techniques are also used to support clinicians due to the complexities of clinical data. This self-contained survey focuses on the assessment of healthcare providers’ acceptance of and interaction with the AI algorithm-driven technology, along with the related visualization methods used in practice.
Historically, researchers have been concerned about the trust issue in computer-aided healthcare. For this reason,clinicians’ aversion and appreciation about algorithmic approaches in this field has been widely discussed. Some published studies have investigated physicians’ attitudes about technologies driven by AI algorithms, and generally, medical professionals seem to be somewhat skeptical about how well AI algorithms can perform in diagnostic tasks. Also, studies have been done on how healthcare providers indeed interact with algorithmic support systems in prognosis, diagnostics, and treatment recommendations, along with the visualization skills that are applied in practice.