Understanding and predicting brain activity is the main objective of computational neuroscience. Neuronal cells are the building blocks of the brain and responsible for electrical signaling and cognitive ability. Recent studies indicate that another cell type, called astrocyte, plays an important role as well. These cells have been proposed to interact with neurons and modulate […]

The project investigates the transformation of anonymity in times of networked-data by looking into the history of urban neighborhood design and its relation to neighborhood-related machine learning algorithms, such as k-nearest-neighbor (KNN). This method analyzes behavioral patterns to form groups (neighborhoods) of actors with the same characteristics (neighbors). This groupingis then deployed to understand and […]

Barriers to mental health care include distance, cost, wait times and more (Moroz, Moroz & D’Angelo, 2020). Canadian mental health systems are also becoming increasingly burdened with demand. To prevent ever-increasing wait list times, mental health care systems require a focus on preventative care. A stronger prevention system, one that supports Canadians so they learn […]

The Mitacs intern will support the community-based project Direct[Message] to develop and undertake research to develop a final technology-based model that will help older adults connect with arts online. The intern will assist in the data collection and analysis of 30 older adult participants’ experiences using and testing an easy-to-use keyboard prototype and an accessible […]

The proposed research is to develop a method for making valid, representative estimates of public opinion from sufficiently large and diverse non-probability samples such as social media data. We aim to demonstrate the theoretical, methodological, and practical contributions to the field of public opinion research by demonstrating the reliability and utility of this method in […]

This research will determine which combinations of metrics sets and machine learning algorithms provide the most accurate outcomes when analyzing the data produced in the CSE-IDC-IDS2018 dataset.

Anessa is developing software that assesses the feasibility of an anaerobic digestion facility at the earliest stages when trying to determine if a facility should be constructed. The challenge is that little information is fully known and there are a lot of factors that can affect the outcome to be positive or negative in the […]

Ferme d’Hiver propose de bâtir un système décisionnel basé sur les données visant à augmenter la productivité et à minimiser les coûts en énergie en agriculture verticale. Le projet innovateur suggère de regrouper l’ensemble des fonctionnalités d’un complexe en salle fermée/serre traditionnelle en un seul et unique système de production et de décision automatisé. L’un […]

Developing subject-based social media requires proper interaction with the users by learning and analyzing their profile and dynamically incorporating their opinion. In this project, a crowd-based profiling of users with respect to their peers will be developed and confidence factor calculated based on the collective opinion of the crowd will be assigned to the individuals’ […]

Le développement rapide des technologies de l’information et des capteurs au cours des dernières années a eu un essor de plus en plus important dans le secteur automobile afin de rendre la conduite plus sécuritaire. Les systèmes de sécurité active en milieu automobile visent à éviter les collisions plutôt que de mitiger leur impact sur […]

A project to help the company explore and adopt new sales, investment and outreach strategies.

Ce projet consiste à innover en offrant aux consommateurs un outil de calcul des coûts de leurs entretiens et réparations automobiles, qui sont aujourd’hui très différents d’un garage à l’autre. En ayant une estimation des coûts réels que les entretiens devraient lui coûter dans les prochaines années, le consommateur ne se fera pas avoir, paiera […]