Projets novateurs réalisés

Occupational; Health and Safety

The SDI Group was founded by Mr. David A. Williamson in 2006 focusing on providing “Safety Design and Innovation”, exceptional service through partnership and innovation. SDI Group has 10 Divisions and more recently, in seeing the need for more innovative ways to service the clients opened up SDI Mobile Company with majority owner, Rosalie Gray who is a First Nation member of Enoch Cree Nation. Moreover, in partnership with our clients SDI strives to find solutions that meet non-traditional needs. We build and manage customized systems for clients in many sectors that enhance their current business model. Together our staff serve over 150 partnerships across North America. We are CRSP’s (Canadian Registered Safety Professionals) along with our team of Audiometric and Substance Screening technicians. Whether it is certified COR Auditors, Trainers or Occupational Hygiene, the SDI Group supports all organizations to meet their goals.

During their four month intern they will be engaged in several objectives both within SDI and for our client base. Our challenge and opportunity are to review key clients health and safety management systems and provide solutions on where we can improve performance. This is through training and procedural updates.

First and Last Smiles: Consumer Experiences of Fun in E-Scooter Adoption

This research project aims to understand what factors are driving the increased usage of shared micromobility vehicles – e-scooters – in city centres. In particular, this research seeks to understand the notion of fun as it influences how people chose to get around within a city. The findings of this inquiry will help cities understand and in turn be better prepared in planning for and in incorporating new modes into transportation strategies. Ultimately, this research intends to help cities become more integrated and better equipped to meet demands around sustainability, congestion, affordability and increased population density. In partnering with Candler Chase Inc. to complete the research project, the results will provide new avenues of revenue and relevance among their client group.

The Impact of Ether Ring Formation via Mechanochemistry

Mechanochemistry uses physical, mechanical mixing in order to break and forms bonds in solvent-free conditions, which can yield different mechanistic outcomes compared to the traditional solution-based method. The highly concentrated mixing of reagents would be typically the last method thought to synthesize medium-sized ether rings, as the molecules require high dilution to promote ring closure and prevent unintended polymerization. However, solid mixing can orientate selectively based on weak interactions that may be negligible in a stirring solution. This project hopes to explore the viability of preparing small to medium ether rings by ball-milling. Ring closing is a common strategy in drug development and if this proves possible, a new branch of organic synthetic mechanochemically will emerge. Investigating alternative and environmentally-friendly methods of standard reactions is crucial as the global pandemic has highlighted the instability and huge price spike in the supply of solvents that Canada currently relies on to continue the production of medicine and research.

Cross-functional teams to develop and commercialize AI-powered solutions – Part A

AltaML is an innovative company capitalizing on a major technological trend: artificial intelligence (AI) technologies, enabled by big data, are driving a fourth industrial revolution. AI will transform all industries, but traditional industries face challenges in implementing AI. AltaML has a unique business model to overcome barriers to adoption of AI solutions by industry, which is to bring the innovating startup together with the large organization, thereby bringing together rich datasets, AI talent with a playbook for industry application and the close collaboration of subject matter experts and AI experts–with a mindset for change. In addition to AI expertise, we bring agility that our large, corporate partners often lack, and which is so essential for innovation. With a strategic focus on AI adoption and product, AltaML works across industries as well as with the public sector using a co-development approach to create applied AI solutions as well as joint AI ventures. This rich, complex multisectoral environment provides the breadth that enables insights in one area to be applied in new areas, leading to ever increasing opportunities for innovation.

The project comprises internships in a variety of technical and business roles, which are: associate machine learning developer, business development associate, communications associate, finance associate, associate business solutions consultant, and project delivery associate. Outcomes will include algorithm creation and deployment, data visualizations, market research reports, sales collateral, competitive landscape analysis, feasibility analysis; key messages and content writing such as case studies and feature articles, financial model development, data analysis, financial reports and variance analysis, customer workflow mapping, business case reports, resource allocation plans, project update reports, and project plans.

Signals of Opportunity-based Positioning Techniques for Challenging GNSS Environments Year Two

The availability and accuracy of GPS in some environments, such as indoors, is limited. Positioning utilizing radio frequency (RF) signals intended for communication, broadcasting, or networking is an attractive alternative or complement to GPS in such environments. The proposed research will develop novel methods to use RF signals of opportunity (SoO), such as WiFi signals and cellular telephone signals, for accurate and robust positioning in GPS challenged environments. This necessitates an investigation of the effects of RF signal characteristics on positioning performance. Detailed mathematical models will be developed to compensate for the negative impacts of such characteristics on positioning performance. The sponsoring company (RxNetworks Inc.) is deeply involved in utilizing SoO for positioning. This research will directly contribute to algorithmic improvements required by the company to enhance the accuracy and robustness of its SoO based positioning products. The development of such algorithms is of utmost importance to the company.

Machine Learning Developer intern within cross-functional teams to develop and commercialize AI-powered solutions – Part 4

AltaML is an innovative company capitalizing on a major technological trend: artificial intelligence (AI) technologies, enabled by big data, are driving a fourth industrial revolution. AI will transform all industries, but traditional industries face challenges in implementing AI. AltaML has a unique business model to overcome barriers to adoption of AI solutions by industry, which is to bring the innovating startup together with the large organization, thereby bringing together rich datasets, AI talent with a playbook for industry application and the close collaboration of subject matter experts and AI experts–with a mindset for change. In addition to AI expertise, we bring agility that our large, corporate partners often lack, and which is so essential for innovation. With a strategic focus on AI adoption and product, AltaML works across industries as well as with the public sector using a co-development approach to create applied AI solutions as well as joint AI ventures. This rich, complex multisectoral environment provides the breadth that enables insights in one area to be applied in new areas, leading to ever increasing opportunities for innovation.

The project comprises internships in a variety of technical and business roles, which are: associate machine learning developer, business development associate, communications associate, finance associate, associate business solutions consultant, and project delivery associate. Outcomes will include algorithm creation and deployment, data visualizations, market research reports, sales collateral, competitive landscape analysis, feasibility analysis; key messages and content writing such as case studies and feature articles, financial model development, data analysis, financial reports and variance analysis, customer workflow mapping, business case reports, resource allocation plans, project update reports, and project plans.

Going Beyond Thin Credit, the use of Account Data

The business partner is interested in finding ways to further automate small business lending and annual renewals. In recent years, with the improvement in efficient computing and data storage and movement, the use of deposit data in lending has become more prevalent in the industry. Within industry risk managers, it is widely accepted that deposit account information has a strong predictive ability for predicting borrower risk level. However, there are no widespread industry tools similar to credit scores making use of deposit data. This project aims to employ machines techniques to develop credit scores based on deposit lending data.

Developing balanced, wellness, cannabis-based natural products through extraction or cold press

The research will help the partner organization expand their in-house capacity for new product development and commercialization. Focused on wellness and sustainability, the partner aims to leverage green technologies to develop their patient-preferred variety of cannabis, which is current available as dried flower, as a cannabis oil. The partner also seeks to address the underutilization of the vegetative parts of the cannabis plant, which generally go to waste, by repurposing these materials for use in natural health products. The intern will bring expertise in extracting cannabis and, at the university, they will measure the levels of key chemicals (e.g., THC and CBD) in the oils and extracts to compare quality based on different extraction methods. The partner will benefit directly from the collaboration by improving production efficiency and advancing their R&D strategy. The intern will benefit by gaining new industry-relevant experience and providing career opportunities through networks and references.

Developing a Robust Synthetic and Characterization Procedures for Biopolymers in the Pulp and Paper Industry

Cascades is one of the most renowned multinational Canadian companies with nearly 80 production units and employs more than 10,500 individuals spread across Canada and the United States. The company was founded in 1964 in Kingsey Falls, Quebec, and specializes in the pulp and paper production, processing and marketing in packaging and hygiene solutions made primarily from recycled fibres. Recently, the R&D team identified one specific biopolymer that is particularly promising for designing new added-value products. From a chemical point of view, the biopolymer constitutes a promising platform to develop additives given its high degree of functionality. The research team at Cascades tried to utilize this biopolymer as strengthening agent in the fabrication of paper, but they rapidly faced important challenges preventing them to achieve a performant and scalable strengthening agent. These includes low molecular weight of the biopolymers, low charge density and difficult characterization. Building from the existing relationship, the goal of this NSERC Alliance partnership is the development and optimization of this novel functionalized biopolymers prepared from the biopolymeric platform generated at Cascades….

Theft of Crypto Assets

Decentralized Finance (DeFi) stands for a paradigm shift in digital financial services. The innovative blockchain technology of the cryptocurrency platform Ethereum provides the ability to deploy software programs, which enables the development of virtual cryptoassets and financial services, to lend or exchange them. DeFi services are a rapidly growing ecosystem, with more than 30 billion total of value locked on Ethereum. Such worth, coupled with the transparency of DeFi software and users’ pseudonymity have made this ecosystem attractive to crime. Indeed, crime events against DeFi projects have been reported daily in the past year. The objective of this research is to map, quantify, and understand DeFi crime events from an on-chain perspective. Systematic investigations of transaction flows and smart contract functions calls will be conducted for each crime event. These will be supplemented with an analysis on the crimes’ modus operandi. This interdisciplinary study, mixing computer science and criminology, will shed light on criminal activities within the DeFi ecosystem.

Composites cimentaires avec inclusion d’asclépiade

Le retrait est un phénomène de contraction volumétrique des matériaux cimentaires lors de leur prise et durcissement. Il est dû à l’évaporation de l’eau du béton. Ce phénomène n’est pas sans impact sur la fonctionnalité et la durabilité des ouvrages. Car il se caractérise le plus souvent par des fissures qui nuisent aux aspects esthétiques du béton d’une part. D’autre part, ces fissures favorisent la pénétration d’agents agressifs dans le béton et accélèrent la corrosion des armatures. Pour éviter ce problème, dans cette étude, l’asclépiade sera utilisée comme réservoir d’eau pour réduire le phénomène de retrait de la matrice cimentaire. Le remplacement des produits de cure synthétiques par des fibres d’asclépiades offre des avantages écologiques vu que sa culture ne nécessite pas d’engrais ni de pesticides.

Signals of Opportunity-based Positioning Techniques for Challenging GNSS Environments

The availability and accuracy of GPS in some environments, such as indoors, is limited. Positioning utilizing radio frequency (RF) signals intended for communication, broadcasting, or networking is an attractive alternative or complement to GPS in such environments. The proposed research will develop novel methods to use RF signals of opportunity (SoO), such as WiFi signals and cellular telephone signals, for accurate and robust positioning in GPS challenged environments. This necessitates an investigation of the effects of RF signal characteristics on positioning performance. Detailed mathematical models will be developed to compensate for the negative impacts of such characteristics on positioning performance. The sponsoring company (RxNetworks Inc.) is deeply involved in utilizing SoO for positioning. This research will directly contribute to algorithmic improvements required by the company to enhance the accuracy and robustness of its SoO based positioning products. The development of such algorithms is of utmost importance to the company.