Commercialization of agrifood waste conversion innovation

The circular economy is an important component of sustainability in this present economy. This project requires the intern to develop a commercialization plan for an innovative technology-driven process of extracting proteins and nutrients from organic waste generated by food and beverage manufacturers. The partner organization possesses intellectual know-how and process expertise in converting organic waste […]

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AI-driven Predictive Models and Consumer Insight for Trade Optimization Improvement

The proposed project is to develop AI strategies to provide precision marketing through consumer segmentation and recommender systems, as well as to promote events that shall meet various business goals for retailers and Unilever. Successful outcomes will feed into an On-Demand AI Engine aimed at improving consumer engagement and pricing strategy in the consumer packaged […]

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Modelling of Asset Health and Risk Matrix for Rotating Assets in Sawmill

Weyerhaeuser Drayton Valley Lumber Mill has employed continuous monitoring of vibration for all the critical rotating assets in the mill to detect failures in early stage and prevent failures. Continuous monitoring is achieved through sensors mounted on the equipment and each sensor collects real-time vibration data of the equipment. Real-time vibration data give an understanding […]

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Robotic-based methodology for synthetic seizure dataset generation for machine learning-driven medical devices.

This research project aims to improve epilepsy treatment by developing a robotic-based method for testing wearable seizure detection devices. The project will create a robotic system that can simulate seizures, providing realistic data to help refine and test machine learning algorithms for detecting seizures more accurately. The goal is to address the limitations of current […]

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Développement du biocarbone pour des applications à haute température – QC-655

Le changement climatique représente l’un des plus grands défis auxquels nous devons faire face. Ce phénomène est causé par le réchauffement de la planète en conséquence des concentrations élevés des gaz à effet de serre (GES) dans l’atmosphère liée aux activités humaines telles que l’utilisation des combustibles fossiles dans le secteur industriel. Les acteurs métalliques […]

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Automating Insider Threat monitoring and detection

Advanced persistent threat (APT) groups, as well as those sponsored by a nation-state, often aim to gain undetected access to a network and then remain silently persistent, establish a backdoor, and steal data, as opposed to causing damage. APT groups use different tactics, techniques, and procedures (TTPs) at various stages of cyberattacks. The continuous and […]

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Edge-Cloud Video Streaming Pipeline for Video Action Recognition

Streaming Cameras have become ubiquitous in the urban and industrial landscape. This research project aims to improve the AI-based action recognition capability of consumer-class home camera streams, which often have limited bandwidth and degraded video quality. The project proposes to develop a network-aware, video-action recognition AI pipeline that pushes key operations of traditional action recognition […]

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Développement et validation des méthodes de contrôle non-destructif de pièces métalliques fabriquées par fusion laser sur lit de poudre

Le but de cette recherche est d’établir un protocole de contrôle pour détecter efficacement les défauts présents dans des pièces métalliques produites par une méthode appelée “fabrication additive”. Le contrôle de qualité des pièces produites est une étape cruciale avant leurs mises en service. Différentes techniques de contrôle sont disponibles ayant chacune des avantages et […]

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Exploration of RL-based agents in the context of space robotic systems

This research will explore machine learning methods in order to devise a control scheme for robotic manipulators(Candarm3) in the context of space exploration. The objective is to develop an early prototype for an autonomous learning agent which can carry out standard control tasks without any operator supervision. The primary machine learning methods that will be […]

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The development of predictive capabilities in terms of pH and solubility for complex mixtures of organic acids and organic acid salts

This project will require a combination of theoretical and empirical modeling based on extensive experimentation to develop a predictable solubility model in organic acids and salts mixture systems. The successful completion of the project will allow the company to predict capability of the complex mixtures during products development. It can be used by formulators & […]

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