Projets novateurs réalisés

BSI – Shravan & Francois

OBJ 1 Identify overall process to be used for the front end & backend of the payment integration process of Oliver POS
OBJ 2 Integrate Oliver POS with Moneris payment app, Moneris checkout app, Authorize.net Payment app, Stripe Payment app and SaRoadshow Product X development
OBJ 3 Integrate Oliver POS with Moneris payment app, Moneris checkout app, Authorize.net Payment app, Stripe Payment app and SaRoadshow Product X development
For approach to be used, please see below.

HTTP/2 anomaly detection in 5G service-based architecture

The Fifth Generation (5G) mobile networks is currently being deployed by telecommunication operators and is designed to provide multiple services with new and variable quality of service requirements. 5G networks design is based on the communications between different network functions using the HTTP/2 protocol. HTTP/2 protocol has multiple vulnerabilities that can be exploited to launch attacks on the 5G network. This project aims at empowering 5G network with intelligent anomaly detection solution to secure it against HTTP/2 attacks using machine learning techniques and a 5G network testbed. As a major player in 5G mobile network and service, the partner organization will benefit from this project by leveraging the innovative ideas and the outcome of this research such as proof of concept and publications. These can be used to directly contribute to the partner’s business and reputation.

Analyse modale harmonique des roues de turbine hydroélectriques par l’étude de régimes permanents

La connaissance du comportement dynamique des turbines hydroélectriques est capitale pour estimer les sollicitations que l’écoulement hydraulique exerce sur les surfaces d’une roue et améliorer ainsi leur fiabilité opérationnelle. Une estimation précise de ces efforts est essentielle lors de la conception de la roue et aussi durant l’exploitation. Deux sources indépendantes nous procurent des informations sur le comportement de la roue. La première est obtenue avec la simulation numérique et la deuxième source est obtenue empiriquement; il s’agit des données collectées in situ par des capteurs installés sur la turbine. Ces deux sources sont complémentaires et aucune n’est suffisante à elle seule. Le présent projet a pour but de développer un outil pour identifier les caractéristiques durant le fonctionnement de la turbine sur les différents régimes (à vide, charge partiel, charge complète). L’objectif pratique est d’apporter une meilleure connaissance de la réponse modale de la machine en régime de production, afin d’accéder aux paramètres modaux réels et à leurs incertitudes.

Crisis management lessons from the pandemic: Assessing leader’ skills readiness and relevance

The coronavirus pandemic has presented business leaders with one of the most protracted crises in recent years. From the time the World Health Organization declared a global pandemic in March of 2020 to the present, leaders in all types of organizations have had to manage through uncertain, volatile conditions. This study seeks to understand how well prepared these leaders were to face this crisis in 2020 and 2021. What crisis management skills were key? What skills did not serve them well, and what gaps in their crisis management training became apparent? By understanding the competencies required for leaders to be effective during long-term crises, this study can identify how universities, private training companies, and organizational learning and development teams can evolve the ways in which Canadian leaders are prepared to lead in times of crisis.

Investigating the characteristics of reinforced compressed earth block

Around half of the world’s population are living in some form of earthen building. Compressed earth blocks are widely known as a low-cost material that has high thermal capacity, low environmental impact, and ease of construction. The project will address three items: material characterization, development length of steel reinforcing bars and performance under freeze-thaw cycles. The material characterization work will focus on testing a series of CEBs under concentric compression as well as prisms of the same materials in four-point bending to get the compressive and the tensile strengths. The specimens will be subjected to freeze-thaw cycles to measure the durability of the material. Also, pull-out tests will be conducted on the reinforced compressed earth blocks to find an appropriate equation for the development length and compare it the reinforced concrete ones.

Développement de méthodes d’optimisation pour la planification des maintenances des turbines en coordination avec les opérations dans les systèmes de production hydroélectrique

Le vieillissement des systèmes de production hydroélectrique nécessite la réfection des groupes turboalternateurs
dans les centrales. Considérant que l’arrêt de turbines pour des périodes de maintenance impacte
directement la production hydroélectrique, il est nécessaire de considérer ces maintenances dans les plans de
production. Actuellement, les modèles d’optimisation de la production hydroélectrique et les modèles de
planification des maintenances sont résolus indépendamment, alors qu’ils gagneraient à être modélisés
ensemble. Le but de ce projet est de modéliser la production et la planification des maintenances en un seul
problème d’optimisation afin de résoudre les deux problématiques simultanément. Des méthodes de
décomposition, comme Dantzig-Wolfe, sont envisagées afin de résoudre le problème et d’accélérer le temps de
calcul. De plus, ces méthodes n’ont pas encore été utilisées spécifiquement pour ce type de problème.

Knowledge Recombination and Alliance Strategy in Science-based Businesses

Project Objectives: 1. To identify the best practices in knowledge recombination by comparing science-based multinational corporations and start-up firms. 2. To suggest refinements in alliance strategies for science-based multinational corporations and start-up firms. 3. To uncover processes and organizational structures to productively exploit the confluence of biotechnology and nanotechnology by MNCs. Post Doctoral Fellow Name: Dr. Varkey Jon Thomas Motivation for Research: Successful organizations create new knowledge by recombining knowledge from multiple sources and disciplines (Grant, 1996; Kogut & Zander, 1992). Firms in science-based industries, such as biotechnology for example, create radical new products and processes based on scientific knowledge from multiple disciplines. Biotechnology firms, which originated in the 1980s (Zucker et al., 1998), are now incorporating nanotechnology to create new products and processes with the potential to transform an industry in search of new therapies (Sharp et al., 2011). For example, biotechnology based drugs, which until recently could not cross membrane barriers inside the human body, can now be designed on the nano-scale, leading to a new class of targeted drug delivery therapies, particularly in oncology. Recombining knowledge from diverse disciplines is inherently uncertain and requires large, consistent financial commitments over long periods of time.

Web based GUI for Data and Machine Learning Modeling

AI Dynamics is building an end to end data platform for managing datasets used in machine learning workloads. The end goal is to provide a web based interface where users can import datasets with a variety of different data types (audio, image, video, DICOM, DNA, RNA, amino acid, text, numbers) and add annotations in preparation for machine learning model generation. The platform further provides an analysis of data by displaying data summarization and visualization and uses heuristics to suggest various data cleaning possibilities. When a user accepts these suggestions, the platform prepares the data for machine learning. The platform then recommends initial deep learning architectures and provides a visual interface for reconfiguration including advice on creating the most appropriate architecture for the dataset on hand. The platform then helps train the models and analyzes the results. The user has an opportunity to make changes to the data cleaning and deep learning (DL) architecture and study its impact on the results. While the end-to-end platform is now in place, there are many additional data cleaning, data preparation, and reconfiguration of deep learning options that need to be explored and tested on different types of datasets.

Developing an Indigenous Land Trust Model

Land trusts are not-for-profit organizations that are able to hold and protect private lands for long-term conservation purposes. They are one approach for Indigenous nations to protect their traditional territories, especially in areas dominated by private land. Different Indigenous nations are interested in establishing their own land trusts but various legal, financial and administrative issues make it challenging for them to be effective and support reconciliation. Outcomes from this research will help to alleviate barriers and propose better land trust models that can support Indigenous rights and long-term conservation while helping to build a conservation economy. Conservation is becoming an important economic driver in Indigenous communities, with benefits such as ecotourism, conservation finance and nature-based solutions, ecosystem services payments and sustainable resource use being incorporated into conservation plans. The Nature Conservancy of Canada will benefit directly from this exploratory work through learning how to better support Indigenous nations through amending its own land trust practices, concepts, and models, as well as from the partnerships that will be developed through this work.

Development of Edible Casings for Vegan Meat Applications

Plant based or vegan meat applications in the marketplace is experience a large market push, as demand for vegan products increases. To produce vegan sausages, casings are typically produced out of seaweed polysaccharides (e.g., carrageenan). However, this has limitations as clients are demanding increased criteria, such as locally grown or made from local Saskatchewan ingredients. This research project aims to develop a plant-based edible casing for potential vegan meat applications. Specifically, the project looks at using hemp and pulse protein ingredients as the main biopolymer in the development of an edible film, along with other film additives (e.g., plasticizer, crosslinking agents, etc.) The film will have sufficient mechanical strength and stretchability to withstand processing, have good control over water migration and good colour. The films will be prepared by casting, and then tested out for potential in a vegan sausage application at the Food Centre.

A Novel Bone Anabolic Treatment for critical size defects in rats

Often fractures don’t heal properly or large defects must be repaired in the bone due to accidents or disease. The drugs and treatments that are currently used to repair fractures are only partially effective. Mesentech Inc has developed a new drug that has shown a strong effect on bone formation in rats. In this project, we will test the effect of this drug in a rat model of normal healing and challenging healing. We will assess the effect of this drug, to accelerate normal healing and enhance challenging healing. We expect that the new drug will make the bones heal faster and better. This will open new treatment approaches to improve fracture healing.

Stock Investment Model

Investing has never been easier, but the majority of individuals still are reluctant to invest and those that do still face a fundamental problem. “What should I invest in?” It’s because the investment journey for a retail investor is broken and Utradea is proven to solve it.

For an average investor, prior to making an investment, they would conduct the following steps: ideation, comprehension, validation, and execution from different platforms – each servicing a specific need and is overcomplicated for the average user. On top of that, it would take months before someone found their suite of tools, platforms, and brokerages they’d like to work just to place one confident trade.

Investors require investment models to support their investment decision and investment process. Models should be automated to an extent, allow investors to spend time review the results, as opposed to trying to source the data and calculate in outcomes themselves. This investment model will help retail investors have a better understanding of investing, investment strategies, and will improve their investment outcomes.