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

Integrity Monitoring of Motion Estimation and Hazard Detection Algorithms in Environmentally-Impacted Scenarios

Imagine some of the difficult driving conditions experienced by vehicle operators. In these conditions, the sun might be blindingly bright, or the snow might obfuscate what is going on around the vehicle. Surprisingly, the sensors used by autonomous vehicles to understand the environment they are in suffer from similar effects. As a field, robotics has yet to tackle integrity monitoring of the sensors used in autonomous applications. In order to transport safety critical loads, such as people or train freight, it is imperative to know when the data the autonomous vehicle receives is corrupted by environmental effects and adjust the behaviour of the autonomous vehicle accordingly. In this project, we aim to develop an algorithm that uses a sensor’s datastream and the outputs of the algorithms that rely on that sensor’s datastream to monitor the integrity of the data collected by the sensor.

Voir la description complète du projet
Superviseur du corps professoral :

Jonathan Kelly

Étudiant :

Partenaire :

Thales Canada Inc (North York, ON)

Discipline :

Engineering

Secteur :

Professional, scientific and technical services; Transportation and warehousing

Université :

University of Toronto

Programme :

Accelerate

Awechigewin: Developing a Virtual Approach to Community-Based Planning with Michipicoten First Nation

The proposed research project will use a combination of Participatory Action Research and Indigenous Research Methods to create an online engagement tool to gather Michipicoten First Nation (MFN) member’s perspectives on draft planning strategies and policies regarding six priority areas. Engagement is a challenge for MFN as a displaced and widely dispersed community, challenges which are heightened by the COVID-19 pandemic. Online engagement is an important tool for reaching Michipicoten citizens on- and off-reserve, particularly during the pandemic. Findings from the intern’s research will be used by MFN to support their ongoing Community Land Use Planning Process. The research could also be use by other Indigenous communities to inform their planning and engagement efforts during the pandemic and beyond.

Voir la description complète du projet
Superviseur du corps professoral :

Janice Barry

Étudiant :

Partenaire :

The First Nation of Michipicoten Cultural Association

Discipline :

Sociology

Secteur :

Other services (except public administration)

Université :

University of Waterloo

Programme :

Accelerate

Dimension reduction for microbiome data

Vast amounts of new data, including sequencing data from microbiome, generated by researchers and industry present challenging problems for extracting meaningful information. The main goal of this project is to develop a convenient software package to reduce the complexity of microbiome data, and more generally any kind of datasets showing similar properties. As this tool will help to efficiently study imperfect and complex datasets which are ubiquitous in particular in biology and health, we will consider other potential applications, e.g. studying health records from intensive care units. A utilization in data collected from sensors present in connected objects could also be valuable. In a nutshell, this project will help analyse data for which there is no real alternative currently, and this applies notably to some of the newest kinds of data, which have important potential in biology, health and industry.

Voir la description complète du projet
Superviseur du corps professoral :

Khanh Dao Duc

Étudiant :

Partenaire :

École Polytechnique

Discipline :

Mathematics

Secteur :

Education

Université :

The University of British Columbia

Programme :

Globalink Research Award

Infrastructure Sensor-based Automated Driving: Development and Demonstration

In this proposal, we intend to answer how infrastructure sensors can be used for autonomous driving. Using infrastructure sensors make automated driving safer, more simplified, and cost effective especially for multiple autonomous vehicles operating in known environments such as large residential/commercial complexes and resorts. Infrastructure sensors replace the main onboard vehicle perception sensors with infrastructure sensors mounted on the side of the road, for example on light posts. The information sent by all the sensor nodes to the cloud is used to localize all the autonomous and non-autonomous vehicles, pedestrians, and all other objects on the road for path planning and path tracking of any number of autonomous vehicles on the road. To enable infrastructure sensor-based automated driving, we will extend our navigation, object detection/classification, and motion planning/control modules from vehicle-installed sensors to infrastructure-installed sensors.

Voir la description complète du projet
Superviseur du corps professoral :

Amir Khajepour;Ehsan Hashemi

Étudiant :

Partenaire :

S2E Technologies Developments Inc;Canadian Urban Transit Research and Innovation Consortium (ON)

Discipline :

Engineering

Secteur :

Agriculture; Professional, scientific and technical services

Université :

University of Waterloo

Programme :

Accelerate

Deuil et covid-19: besoins et interventions possibles

Le contexte des mortalités survenues pendant la pandémie actuelle semble constituer un facteur de risque majeur de complication du deuil, d’autant que les pratiques rituelles funéraires ont été empêchées ou réduites. Pour évaluer le deuil de ces personnes et élaborer de meilleures mesures de soutien à celles-ci, l’organisme Deuil-02 du Saguenay réalisera une étude quantitative et qualitative. Ainsi, une enquête en ligne assortie d’entretiens semi-dirigés seront menés par une étudiante en travail social. Avec les résultats de ce cette étude, l’organisme partenaire sera mieux en mesure d’accompagner les personnes endeuillées dans le contexte de la pandémie. Et l’étudiante pourra utiliser ces données probantes pour ses études supérieures; elle pourra également mieux connaître la réalité de l’intervention communautaire pour soutenir les endeuillés, notamment en temps de pandémie.

Voir la description complète du projet
Superviseur du corps professoral :

Jacques Cherblanc

Étudiant :

Partenaire :

Deuil 02

Discipline :

Sociology

Secteur :

Health and Related Sciences & Technology

Université :

Université du Québec à Chicoutimi

Programme :

Accelerate

Identifying and Modeling Families of Serial Tests

Ciena is a leading corporation supplying IT products. Before delivering any product, the company makes sure all products go through a set of tests which are recorded into log files. Operating in a crowded and highly competitive market, Ciena is continuously running after innovation for remaining highly competitive. Therefore, the company wants to increase their data analytical solutions capabilities by exploring the huge amount of log data that are continuously gathered. The diversity and the time evolving aspect of the generated log information yield complex and massive data which are difficult to handle. Digging into such data pose new challenges in elaborating effective mining algorithms. The aim of this project is to devise analytical tools to fully grab the massive heterogeneous generated data. To this end, we intend developing novel datamining / machine learning models that extract useful patterns that offer insight to track the status of products tests over different time stamps. The goal is to infer the hidden inter-dependencies between test cases and thus build a dynamic multidimensional heterogeneous network structures for mimicking the logs ecosystem environment to first identify families of tests. Then, model these families to finally predict early symptoms of failure products.

Voir la description complète du projet
Superviseur du corps professoral :

Mohamed Bouguessa

Étudiant :

Partenaire :

Ciena Canada (Saint-Laurent, QC)

Discipline :

Computer science

Secteur :

Information and cultural industries; Manufacturing

Université :

Université du Québec à Montréal

Programme :

Accelerate

The Economic Transitions of Refugees Resettling in Rural Nova Scotia Since 2015: Learning from Refugee Newcomers, Sponsorship Groups, and Employers

The project explores the facilitators and barriers to the successful economic transitions of privately sponsored refugees resettled in rural areas of Nova Scotia since 2015. While acknowledging differences in pre-migration experiences, we seek to better understand 1) the post-migration factors shaping their economic transitions, such as gender, parental status, race, age and health; 2) how refugees’ transitions are informed by cultural, intercultural, economic, and social variables; and 3) how resettlement by private sponsors in rural settings influences refugees’ economic transitions. A qualitative research design will be used to learn from refugees resettled in rural and remote areas of Nova Scotia, the volunteers who provide/d resettlement support, and the employers who hire/d newcomers. This study will help explain why privately sponsored refugees tend to integrate into the economy more rapidly and securely compared to government-sponsored refugees. This project is done in partnership with Syria Antigonish Families Embrace, SAFE, a community-based refugee sponsorship group established in Antigonish Nova Scotia in 2015.

Voir la description complète du projet
Superviseur du corps professoral :

Norine Verberg

Étudiant :

Partenaire :

Syria Antigonish Families Embrace

Discipline :

Sociology

Secteur :

Health and Related Sciences & Technology; Other services (except public administration)

Université :

St. Francis Xavier University

Programme :

Accelerate

Advanced Signal Processing and Machine Learning for Autonomous Screening in Unconstrained Environments

The COVID-19 pandemic has abruptly and undoubtedly changed the world as we knew at the end of the second decade of the 21st century. Of particular interest to this research program is development of advanced autonomous screening (thermographic and cognitive) systems via integration of signal processing and deep learning models to address the following three requirements and challenges of the project’s industrial partner: (i) Development of an AI-empowered avatar that autonomously performs their Cognistat assessments. The objective is to convert Cognistat technician administered solution to an autonomous AI-based solution; (ii) Addressing the industrial partner’s challenges for development of thermographic screening solutions in unconstrained environments for real-life environments such as clinics and hospitals, and; (iii) Validation of duplicated medical documents, which is a general challenge faced across the scope of the project. One specific requirement is development of an autonomous and AI-driven duplicated medical record matching engine.

Voir la description complète du projet
Superviseur du corps professoral :

Arash Mohammadi

Étudiant :

Partenaire :

Novatek International

Discipline :

Engineering

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

Concordia University

Programme :

Accelerate

Closing the Gap: A Study of Implementation and Effectiveness of the Youth in Transition (YouIT) Intensive Case Management Services

The proposed research will consist of an evaluation of both the implementation and effectiveness of the YouIT program for youth and young adults with mental health and addiction problems. An implementation evaluation will be conducted to document whether the program has been implemented as intended (based on best practices) and how the program is actually implemented. The outcome evaluation will examine the outcomes of clients over the course of their participation in the YouIT program. This evaluation will provide CMHA ways to improve program delivery and will identify changes to effectively provide ICM services to youth. An outcome evaluation will help the organization understand the effectiveness of the YouIT program. Through this evaluation, the organization will have a better understanding of the demographics and needs of their clients in the program. Deliverables for the project will include two written reports and a community forum.

Voir la description complète du projet
Superviseur du corps professoral :

Tim Aubry;John Sylvestre

Étudiant :

Partenaire :

Canadian Mental Health Association (Ottawa)

Discipline :

Sociology

Secteur :

Health and Related Sciences & Technology

Université :

University of Ottawa

Programme :

Accelerate

A Study of Sgr A*’s X-ray variability

This project will investigate the duty cycle of the Milky Way’s supermassive black hole Sagittarius A* (Sgr A*), by studying the Xray
features present in the inner regions of our Galaxy. The X-ray light emitted by Sgr A* over the last several centuries is still
propagating in the central molecular zone, generating X-ray echoes. The variability and the spectral properties of this reflected
emission reveals the existence of several short outbursts from Sgr A* over the corresponding period. Despite an increasing
precision in the description of these past events, their exact nature is still unknown. Our work will connect present-day monitoring
of Sgr A*’s flaring activity to reconstructed evidence of its past activity. This effort will help constrain the energy budget required
for each variability epoch, and its impact on the black hole’s environment.

Voir la description complète du projet
Superviseur du corps professoral :

Daryl Haggard

Étudiant :

Partenaire :

Université Grenoble Alpes

Discipline :

Physics

Secteur :

Education

Université :

McGill University

Programme :

Globalink Research Award

Training of sensorimotor skills in stuttering children

Stuttering is a neurodevelopmental speech motor disorder characterized by dysfluencies. There is no consensus yet on the underlying causes of this disorder, but one hypothesis suggests that people who stutter have impaired rhythmic and timing abilities. Stuttering symptoms can be reduced for example when speaking to a metronome or reading aloud with other people. This reduction in stuttering may be explained by an external rhythmization of speech which may result in improved speech fluency, and compensate for impaired internal timing mechanisms. Recent research shows that people who stutter have deficits in integrating auditory and motor information during speech production. They also show alterations of auditory-motor integration in non-verbal tasks, such as manual sensorimotor synchronization (SMS; for example tapping with the index finger to the rhythm of music or tones). However, studies regarding non-verbal SMS tasks in adults who stutter and their fluent peers reveal inconsistent findings and only a few results have been obtained with children who stutter so far. The first aim of the present project is to determine whether or not children who stutter from the ages of eight to twelve show impaired sensorimotor synchronisation abilities.

Voir la description complète du projet
Superviseur du corps professoral :

Simone Falk

Étudiant :

Partenaire :

Ludwig-Maximilians-Universität München

Discipline :

Sociology

Secteur :

Health and Related Sciences & Technology; Information and Communications Technology; Education

Université :

Université de Montréal

Programme :

Globalink Research Award

Knowledge extraction and organization to support question-answering

The project aims at developing a question answering system for the National Bank of Canada, which can be used to answer the questions by users in the domain of banking and financial services, as well as human resources. The NBC currently uses a generic QA system from which some limitations have been observed, namely the limited coverage of domain-specific entities and concepts and low accuracy of the question answering. The project will develop and test approaches to solve these problems, by collecting more concepts in the domain and organizing them into a knowledge graph. The question answering system will then leverage the domain-specific knowledge graph.

Voir la description complète du projet
Superviseur du corps professoral :

Jian-Yun Nie

Étudiant :

Partenaire :

Banque Nationale du Canada

Discipline :

Computer science

Secteur :

Finance and Insurance; Professional, scientific and technical services

Université :

Université de Montréal

Programme :

Accelerate

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