Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

30 508 projets complétés

2882
AB
5105
C.-B.
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projets par catégorie

Software quality monitoring using AI/ML techniques

This project aims at employing AI and machine learning techniques to monitor and improve software quality. The quality of the system is to be measured by several metrics including the number of existing software defects, the normal/abnormal behavior of the system, test quality, test coverage, etc. The project focuses on studying historical data and trends of software defects with the goal of using these data to predict software quality. Machine learning approaches leveraged in this work would allow Ericsson to better monitor software quality of their systems, which would result in more effective and easier software maintenance. The interns involved in this project will be trained in building robust ML pipelines and solving industrial problems. By collaborating with the worldwide 5G equipment and services leader Ericsson, the interns will gain industrial experience and validate research advances on industrial data.

Voir la description complète du projet
Superviseur du corps professoral :

Olga Baysal

Étudiant :

Partenaire :

Ericsson Canada Inc (Ottawa, ON)

Discipline :

Computer science

Secteur :

Information and cultural industries; Manufacturing; Professional, scientific and technical services

Université :

Carleton University

Programme :

Accelerate

Migration assistée, évènements climatiques extrêmes et changements climatiques: Étude de cas des populations d’épinettes blanches de l’est du Canada

L’épinette blanche est une espèce particulièrement sensible au gel printanier et automnal. En endommageant les méristèmes responsable de la croissance, le gel entraîne de fréquents échecs de régénération, surtout en zone boréale. Puisque le réchauffement moyen de la température de l’air déclenche plus hâtivement le débourrement des bourgeons, les méristèmes s’exposent davantage aux évènements de gel, ce qui pourrait intensifer le problème de retard de croissance et met en péril la gestion durable des forêts du Québec. En plantant des provenances du sud vers le nord, la migration assistée pourrait maintenir la productivité des plantations d’épinettes blanches. Nous proposons donc de développer un modèle prédictif de la susceptibilité aux gels de plusieurs populations d’épinettes blanches du Québec en fonction de leur climat d’origine, du climat de plantation et des changements climatiques. Puisque la rentabilité économique de notre partenaire (Matériaux Innovants Rayonier – RYAM Gestion forestière) est directement lié à sa capacité à s’approvisionner avec le bois coupé à l’écotone de la forêt tempérée et boréale du Québec, nos résultats permettant de maximiser la productivité des plantations établies à cet endroit l’intéresse fortement.

Voir la description complète du projet
Superviseur du corps professoral :

Mebarek Lamara

Étudiant :

Partenaire :

Rayonier A.M. Canada S.E.N.C.;Chantiers de Chibougamau Ltée

Discipline :

Earth science

Secteur :

Agriculture; Manufacturing; Professional, scientific and technical services

Université :

Université du Québec en Abitibi-Témiscamingue

Programme :

Accelerate

Investigation of Lactocaseibacillus rhamnosus HA-114 and its underlying mechanisms as therapeutics for neurodegeneration – Year two

Many studies suggest that genes, environment, and age contribute to the onset of late-life neurodegenerative disease like amyotrophic lateral sclerosis. Epidemiological studies have shown correlations between environmental chemical exposure and neurodegeneration, but no direct and causal relationships have been established. Conversely, there may be environmental actors that suppress or delay neurodegeneration outcomes. The human body is the natural habitat for many microbes, including hundreds of bacterial species referred to as the microbiota. A growing body of work suggests that gut microbiota has a profound effect on health including for neurodegenerative diseases. Our laboratory uses the nematode C. elegans, and its genetic methodologies to model aspects of human neurodegenerative diseases. As part of previous therapeutic discovery program, findings from our worm model have been successfully translated to preclinical and clinical settings for human neurodegenerative disorders. We discovered a probiotic bacteria strain that suppresses neurodegeneration in C. elegans models of ALS. Using a combination of chemical-genetic approaches we propose to identify the neuroprotective molecules originating with the probiotic bacteria, and the genes and pathways essential for suppressing neurodegeneration in our C. elegans models. Along this project, we will explore whether homologue key molecules can be identified and validated in more advanced vertebrate.

Voir la description complète du projet
Superviseur du corps professoral :

Nicole Leclerc;Alex Parker

Étudiant :

Partenaire :

Lallemand Bio Ingredients

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Université de Montréal

Programme :

Elevate

Investigation of Lactocaseibacillus rhamnosus HA-114 and its underlying mechanisms as therapeutics for neurodegeneration

Many studies suggest that genes, environment, and age contribute to the onset of late-life neurodegenerative disease like amyotrophic lateral sclerosis. Epidemiological studies have shown correlations between environmental chemical exposure and neurodegeneration, but no direct and causal relationships have been established. Conversely, there may be environmental actors that suppress or delay neurodegeneration outcomes. The human body is the natural habitat for many microbes, including hundreds of bacterial species referred to as the microbiota. A growing body of work suggests that gut microbiota has a profound effect on health including for neurodegenerative diseases. Our laboratory uses the nematode C. elegans, and its genetic methodologies to model aspects of human neurodegenerative diseases. As part of previous therapeutic discovery program, findings from our worm model have been successfully translated to preclinical and clinical settings for human neurodegenerative disorders. We discovered a probiotic bacteria strain that suppresses neurodegeneration in C. elegans models of ALS. Using a combination of chemical-genetic approaches we propose to identify the neuroprotective molecules originating with the probiotic bacteria, and the genes and pathways essential for suppressing neurodegeneration in our C. elegans models. Along this project, we will explore whether homologue key molecules can be identified and validated in more advanced vertebrate.

Voir la description complète du projet
Superviseur du corps professoral :

Alex Parker;Nicole Leclerc;Alex Parker

Étudiant :

Partenaire :

Lallemand Bio Ingredients;Lallemand Health Solutions Inc (Montreal, QC)

Discipline :

Life Sciences

Secteur :

Manufacturing

Université :

Université de Montréal

Programme :

Elevate

High heat flux microprocessor cooling using binary fluid mixtures – Year two

As the heat fluxes produced by modern high-performance microprocessors continue to rise, so too must the effectiveness of the removal of these fluxes. Accordingly, a large amount of research has focused on developing techniques to enhance cooling in computer systems. A novel method of doing so involves replacing the single-phase liquid or two phase-liquid vapor coolants typically employed in such systems with binary fluid mixtures. Previous studies indicate that this may increase mixing within the flow and/or improve the critical heat flux (CHF) of the system, potentially leading to significant increases in heat transfer. The proposed project will therefore investigate the use of such mixtures in microprocessor cooling technologies in greater detail. The first part of the project will use experiments performed in simple flows to study heat transfer in fluid mixtures and identify the mixtures capable of significantly enhancing heat transfer. In the second part of the project, these mixtures will be tested in existing microprocessor cooling technologies, including both spray cooling and microgap cooling technologies. Should the research be successful, this may allow the partner organization to increase the clock speeds, and thus the performance, of their high-performance servers.

Voir la description complète du projet
Superviseur du corps professoral :

Laurent Mydlarski

Étudiant :

Partenaire :

Hypertechnologie CIARA Inc

Discipline :

Engineering

Secteur :

Manufacturing

Université :

McGill University

Programme :

Elevate

High heat flux microprocessor cooling using binary fluid mixtures

As the heat fluxes produced by modern high-performance microprocessors continue to rise, so too must the effectiveness of the removal of these fluxes. Accordingly, a large amount of research has focused on developing techniques to enhance cooling in computer systems. A novel method of doing so involves replacing the single-phase liquid or two phase-liquid vapor coolants typically employed in such systems with binary fluid mixtures. Previous studies indicate that this may increase mixing within the flow and/or improve the critical heat flux (CHF) of the system, potentially leading to significant increases in heat transfer. The proposed project will therefore investigate the use of such mixtures in microprocessor cooling technologies in greater detail. The first part of the project will use experiments performed in simple flows to study heat transfer in fluid mixtures and identify the mixtures capable of significantly enhancing heat transfer. In the second part of the project, these mixtures will be tested in existing microprocessor cooling technologies, including both spray cooling and microgap cooling technologies. Should the research be successful, this may allow the partner organization to increase the clock speeds, and thus the performance, of their high-performance servers.

Voir la description complète du projet
Superviseur du corps professoral :

Laurent Mydlarski

Étudiant :

Partenaire :

Hypertechnologie CIARA Inc

Discipline :

Engineering

Secteur :

Manufacturing

Université :

McGill University

Programme :

Elevate

The impact of climate change on individual and compound extreme events across Eastern Canada – Application to Intensity-Duration-Frequency curves in Labrador City – Year two

The possible failure of surface water management systems is one of the main concerns in the design, construction and management of critical infrastructures such as dams, nuclear facilities and mining activities, especially in northern latitudes. Extreme rainfall and sudden snowmelt events exert major controls on surface runoff and flooding events in cold regions such as Canada. Climate variability and change can alter the severity, magnitude and concurrence of such extreme events. Although the temporal variations of individual extreme events such as temperature and rainfall have been the subject of many recent studies, their joint representation as well as the spatiotemporal variations in these multivariate components are neither well-documented nor fully understood. This research aims at understanding the nonstationarity of individual and compound hazards in Eastern Canada and more specifically in Labrador City, the mining site of Rio Tinto – Iron Ore Company of Canada (IOC), through a high-dimensional statistical framework. Downscaled future climatic data records will be used as input to a statistical projection method for modeling future snow water equivalents across the studied domain. Using predicted temperatures, rainfall and snow water equivalents, univariate and multivariate future trends of the studied extremes will be quantified.

Voir la description complète du projet
Superviseur du corps professoral :

Jan Franklin Adamowski

Étudiant :

Partenaire :

Iron Ore Company of Canada (QC)

Discipline :

Engineering

Secteur :

Mining

Université :

McGill University

Programme :

Elevate

The impact of climate change on individual and compound extreme events across Eastern Canada – Application to Intensity-Duration-Frequency curves in Labrador City

The possible failure of surface water management systems is one of the main concerns in the design, construction and management of critical infrastructures such as dams, nuclear facilities and mining activities, especially in northern latitudes. Extreme rainfall and sudden snowmelt events exert major controls on surface runoff and flooding events in cold regions such as Canada. Climate variability and change can alter the severity, magnitude and concurrence of such extreme events. Although the temporal variations of individual extreme events such as temperature and rainfall have been the subject of many recent studies, their joint representation as well as the spatiotemporal variations in these multivariate components are neither well-documented nor fully understood. This research aims at understanding the nonstationarity of individual and compound hazards in Eastern Canada and more specifically in Labrador City, the mining site of Rio Tinto – Iron Ore Company of Canada (IOC), through a high-dimensional statistical framework. Downscaled future climatic data records will be used as input to a statistical projection method for modeling future snow water equivalents across the studied domain. Using predicted temperatures, rainfall and snow water equivalents, univariate and multivariate future trends of the studied extremes will be quantified.

Voir la description complète du projet
Superviseur du corps professoral :

Jan Franklin Adamowski

Étudiant :

Partenaire :

Iron Ore Company of Canada (QC)

Discipline :

Engineering

Secteur :

Mining

Université :

McGill University

Programme :

Elevate

Multi-scale Image integration for Surgical Guidance – Year two

During surgery, a neurosurgeon must refer to three levels of image information: macroscopic from the patient’s MRI or CT, providing anatomical context of the surgical target; mesoscopic information from a surgical microscope or exoscope providing a highly magnified view of the region surrounding the surgical target; and the most important microscopic information provided by histology samples of excised tissue that must be analyzed in a pathology laboratory. Through precise image registration, this project will integrate MR/CT images, exoscope images, and images from a novel hand-held scanning laser confocal neuro endoscope device that provides histology-equivalent microscopic (AKA Digital Biopsy) images in real time. When integrated within a common framework, these multi-scale data will be visualized using an augmented reality display in real time during the surgical procedure. By registering the Stereoscopic exoscope image with the patient’s 3D MR/CT data, this approach will, for the first time, provide the surgeon with the means to immediately relate data from macroscopic MRI (target points, nerve bundles) to the mesoscopic exoscope view, and will also provide real-time imaging at the cellular level via the Digital Biopsy images. (See Figure 1 Attached).

Voir la description complète du projet
Superviseur du corps professoral :

Terry Peters

Étudiant :

Partenaire :

Synaptive Medical Inc

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology; Manufacturing; Professional, scientific and technical services

Université :

The University of Western Ontario

Programme :

Elevate

Multi-scale Image integration for Surgical Guidance

During surgery, a neurosurgeon must refer to three levels of image information: macroscopic from the patient’s MRI or CT, providing anatomical context of the surgical target; mesoscopic information from a surgical microscope or exoscope providing a highly magnified view of the region surrounding the surgical target; and the most important microscopic information provided by histology samples of excised tissue that must be analyzed in a pathology laboratory. Through precise image registration, this project will integrate MR/CT images, exoscope images, and images from a novel hand-held scanning laser confocal neuro endoscope device that provides histology-equivalent microscopic (AKA Digital Biopsy) images in real time. When integrated within a common framework, these multi-scale data will be visualized using an augmented reality display in real time during the surgical procedure. By registering the Stereoscopic exoscope image with the patient’s 3D MR/CT data, this approach will, for the first time, provide the surgeon with the means to immediately relate data from macroscopic MRI (target points, nerve bundles) to the mesoscopic exoscope view, and will also provide real-time imaging at the cellular level via the Digital Biopsy images. (See Figure 1 Attached).

Voir la description complète du projet
Superviseur du corps professoral :

Terry Peters

Étudiant :

Partenaire :

Synaptive Medical Inc

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology; Manufacturing; Professional, scientific and technical services

Université :

The University of Western Ontario

Programme :

Elevate

Low-cost Machine Type Communication User Equipments for LTE (part 3)

Machine-to-machine (M2M) devices are defined as the equipments which do not require a direct human interaction for communicating to each other. M2M networks are predicted to have a large end-user market in the near future with numerous potential applications, such as home automation, patient monitoring, transportation, and smart metering. Currently, the main bottleneck is to reduce the overall cost of these equipments in order to enable a practical implementation of densely-deployed M2M networks which can cover an area of interest and, for example, connect different regions of a city. The proposed research will be part of Sierra Wireless’ ongoing activities to develop such low-cost machine-type communication devices compliant with the long-term evolution (LTE) communications standard.

Voir la description complète du projet
Superviseur du corps professoral :

Lutz Lampe

Étudiant :

Partenaire :

Semtech

Discipline :

Engineering

Secteur :

Information and Communications Technology

Université :

The University of British Columbia

Programme :

Accelerate

Impact of a protected essential oils on the intestinal microbiota of dairy cows

The intestinal microbiota is essential for enhanced gut health and adequate fiber digestion. Factors such as diet transition and the stress of parturition are associated with changes in the normal microbiota of cows. Microbiota manipulation to improve performance can be achieved by the use of feed additives, such as and essential oils and vitamins, but its mechanisms of action are not completely understood. Furthermore, changes in the fecal microbiota can directly influence the vaginal microbiota of cows, which has been indicated as a major player in fertility. This study aims to investigate the consequences of a new coated additive on the intestinal microbiota of dairy cows. To do that, 30 Holstein cows will be divided in 2 subsequent groups (treatment and non-treatment). Supplementation will start when cows are moved into a transition diet (21 days before estimated calving). Fecal samples and vaginal swabs will be collected before supplementation (D-21), and at D-7, D7 and D21. Blood samples will be taken at D7 and D21 for beta-hydroxy butyrate and cortisol levels. Next generation DNA sequencing will be used for microbiota characterization to investigate the potential of the additive to enhance beneficial bacteria and control stress-related imbalances.

Voir la description complète du projet
Superviseur du corps professoral :

Marcio Costa

Étudiant :

Partenaire :

JEFO Nutrition

Discipline :

Life Sciences

Secteur :

Agriculture

Université :

Université de Montréal

Programme :

Accelerate

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