Projets novateurs réalisés

Sea Cucumber Processing for Optimized Product Value

Sea cucumbers are found in both benthic areas and deep seas and have been used as a source of food and drug for decades. During the past decade, several scientific research initiatives explored various species of sea cucumber. However, not much research has been done on Atlantic species. As an emerging fishery in Atlantic Canada, the sea cucumber fishery is currently enduring sustainability and viability issues. The most common sea cucumber species found in northwest Atlantic is Cucumaria frondosa. Newfoundland and Labrador (NL) is particularly concerned about the over exploitation of Cucumaria frondosa and as a result, the province is enforcing more stringent policies compared to other Canadian provinces which are currently in the developmental stages in Sea cucumber fishery. This project will explore the sustainable harvesting, processing and utilization of this benthic marine invertebrate for the Canadian market.

Systeme de vision artificielle pour inspection d’inventaire dans un contexte de soinsde sante

Le personnel hospitalier utilise quotidiennement de centaines d’items comme des panscments, tubes,

seringues et gants. Ces items doivent etrc disponibles 100% dl! temps atin d’ assurer la qualite-dcs soins

de sante fournis aux patients. L’organisation partenaire Logi-D offre des solutiolls d’automatisation de

la chaine logistiquc pour les h0pitaux, dont Ie produit 2BIN-iD, pour lequel la gcstion d’inventaire

passe par des operations manuclles entre cabinets d’entreposage at tableaux de commandes. Ceci cst

une sOllrce d’inefftcacite et par/ois une cause d’elTeur. Le but elu projet de recherche consiste it

remplacer Ie ~y~tellle manuel par un systeme de vision arti ficielle. Le systcl11c pcnnettra de rcperer les

items manquants sans avoir 11 dcpcndre d’une action de la part du personnel. Les avancees techniques

innovatrices decoulant elu projct amcliorcront signiticativcmcnt la maniere avec laquelle les h6pituux

et cliniques medicales gerent l’utilisation quotieliemlc des fournitures medicalcs, et tOllrniront it Logi-D

lin avantage commercial intercssant par rapport il scs competiteul’s.

Dairy Policy and Dairy Cooperatives in Germany

The student’s PhD research focuses on the relationship between the dairy policy and dairy cooperatives in Germany in the context of agricultural industrialization and globalization. Traditionally, dairy cooperatives and producers were regarded as “sitting in the same boat” because dairy cooperatives are owned by producers and help producers collectively bargain to gain a fair price for their milk. Recently, however, this relationship has featured friction and divergent discourse, which poses internal governance challenges to the cooperatives. At the same time, dairy cooperatives, together with their producer-owners, have experienced major policy changes in the last three decades. Are these two issues – the cooperatives’ internal governance challenges and the policy changes – interrelated? What are the underlying political and economic forces driving the changes? Focusing on these questions, the student would like to draw on the expertise of Prof. Dr. Hanisch at the Humboldt University of Berlin to develop a PhD research proposal, literature review, and initial data collection during her stay in Germany.

Innover en acrobatie au trampoline pour Paris 2024 par la synthèse optimale et un simulateur en réalité virtuelle

Le Canada est un leader international en trampoline depuis plusieurs olympiades. Afin de maintenir ces performances, il convient d’innover dans les techniques des saltos vrillés. En collaboration avec l’INS Québec, nous allons créer, pour des trampolinistes, une variété de techniques optimales de vrilles aériennes au moyen de simulation informatique. Le défi est de développer 1) un modèle mathématique fidèle aux capacités physiques des trampolinistes et 2) un algorithme d’optimisation pour des mouvements si complexes. Les techniques retenues seront introduites dans un environnement de réalité virtuelle afin que les trampolinistes puissent apprendre les gestes. Dans ce simulateur, les mouvements de l’athlète seront captés en temps réel et les conséquences de ces mouvements sur les rotations dans l’espace seront calculées en temps réel et affichées sur un écran ou dans un casque de réalité virtuelle. Les athlètes pourront ainsi apprendre à prendre des repères lorsqu’ils effectuent des saltos avec des vrilles.

Adaptation du modèle d’affaires aux différentes turbulences externes

Ce projet vise à optimiser la rapidité de prise de décision dans les entreprises suite à un meilleur système de collecte et traitement de l’information lors de l’acquisition de données stratégiques via différentes veilles économiques (système de recherche d’informations stratégiques pour les décisions de l’entreprise). Par la suite cela permettra d’adapter plus rapidement la conception et structure de l’entreprise, et ce, de manière plus proactive et optimale.

Building community partnerships to foster the wellbeing of young children and families

The early years are optimal for investing in the future of our society, as early experiences are critical for brain development, lifelong learning, and wellbeing. BC data show that 1-in-3 children are vulnerable at school entry. To change this, we need to enhance capacities to locally identify families’ and children’s needs and provide supports to families with young children early. This partnership project will test the feasibility of a universal early child development data platform in BC communities to inform community-level decision making, strategic planning, and resource allocation in the local early years sector.

Private Secure Blockchain Transactions

IDENTOS and the University of Ottawa will collaborate in the research and development of cryptographic techniques for secure and privacy-respecting blockchain transactions. This project has research, design and implementation aspects. The project builds on the strengths of IDENTOS and The University of Ottawa in the areas of Mobile Security Privacy and Blockchain. The students will receive valuable experience in applied cryptography on a leading edge enterprise solution. IDENTOS will gain access to specialized skillsets of the students and their Supervisor.

GaN Power Transistor Modelling and Experimental Verification

Crosslight Software Inc. is a leading provider of technology CAD (TCAD) tools for the design and simulation of semiconductor devices. They are specialized in innovative III-V compound materials which are considered as the next generation materials for power semiconductor devices. Crosslight has on-going activities in developing accurate simulation models for gallium nitride (GaN) material and devices. In particular, this is critical for the design of GaN based power transistors. This project aims to evaluate a variety of widely used processes involved in the fabrication of GaN power transistors to assist Crosslight in improving their GaN TCAD models. Specifically, we wish to focus on the metal semiconductor alloying process under high temperature annealing, including surface morphology, alloying product and temperature dependent crystallization mechanisms.

Brain-Inspired Artificial Intelligence for Sound-Aware Robotics

The lack of robust sound awareness in robotics and autonomous machines is a crucial limiting factor in their usefulness and adoption. Taking a biologically inspired approach offers novel computational mechanisms to solve a variety of challenges in this field. The primary objective of this proposal is to finalize and evaluate a Bayesian auditory artificial intelligence (AI) for robotics and collect data for a subsequent publication. This expands on work done in a successful Canada-Italy Innovation award in 2017. A second but equally important objective is to lay the foundations of a next generation auditory AI that will leverage new techniques in deep-learning neural networks. Preliminary theoretical and pilot work is already underway on these neural networks at the U of L, and the proposed visit will enable initial planning about how to implement these networks in the computational architecture of the cognitive robotics platform iCub.

Self-Assembly of Amphiphilic Metal-Organic Polyhedra for Membrane applications

Metal-organic polyhedra (MOPs) are discrete molecular capsules formed by coordination of metal ion and organic linkers. They possess a nanoscale cavity which can have potential applications in gas storage, separations, drug delivery or sensing. To enhance their usage for practical purposes, these materials need to be translated into membranes. MOP-polymer composites where MOPs are blended with easily processable and mechanically strong polymers serve as a solution. However, there are shortcomings of this process such as integration and integrity of MOPs in the membrane, which can affect selectivity of gas separations. In this project MOPs with both polar and non-polar linkers would be synthesized which show amphiphile-like self-assembly and would be used for making composites. The amphiphilic MOP aggregates would have better integration with the amphiphilic polymers which are commonly used for preparing the membranes. These MOP aggregates, being bigger in size, shall not be easily entombed by the polymer and should result in membranes with high MOP loading and selectivity.

Iterative learning control to cancel beam loading effect in particle accelerators

Iterative learning control (ILC) is an approach to improve the performance of a system that carries out the same operation repeatedly. It stores error and control output throughout every iteration, and incorporates the stored information into generating new control output. In a cavity resonator, a standing wave electromagnetic field is formed to accelerate charged particles passing through the cavity. In the process of the acceleration, energy is transferred from the accelerating field to the beam. As a result, the cavity voltage drops. This effect is referred to as beam loading. A feedback controller is responsible to maintain constant amplitude and phase for the cavity field oscillation. However, for certain applications, a feedback controller is not fast enough. In this project, we aim to use ILC to reduce beam loading effect in cavity resonators. Since beam loading is a repeating disturbance, the error is repetitive as well, and the controller can use a non-causal learning function to pre-emptively counteract beam loading effect.

Machine learning applied to drilling in open pit mines

The project involves identifying changes in mineralization during the drilling of the blast holes. During drilling, an experienced driller is able, to a certain extent, to detect signals that indicate that a zone change is occurring: vibration in the cabin, rotation rate, etc. The aim of this research project is to use data collected by the various sensors installed on the drill (specific energy, rotation rate, penetration rate, horizontal and vertical vibrations) to determine patterns among these data which would make it possible to identify a zone change and eventuallly automate this process. Machine Learning techniques are proposed to identify these patterns. The detection of these geological changes is particularly important in coal mines to stop drilling just before reaching the coal bed. This is to prevent blasting from fracturing the coal bed.