Projets novateurs réalisés

FOREX Geocoding System for Foreign Currency Market Monitoring

An existing Forex currency trading system has demonstrated a proof of concept on a static data set. The current project proposes to implement the trading system for real-time applications taking advantage of available geospatial information which can influence currency markets. The novel methodology will be based on building a high-dimensional weighted autocorrelation model between real-time news and their spatio-temporal geographic locations. This would require development of sophisticated methods in the areas of data mining, geocoding and spatio-temporal pattern matching. The developed technology will be incorporated into CTS Forex trading software which will improve its monitoring and predictive capabilities by allowing to change the system trading behavior, i.e. exiting the trade, moving the stop loss and take profit in real-time.

Recherche sur l’adaptation des jeunes en lien avec la pandémie de la Covid- 19 : évaluation de l’utilisation et de la satisfaction d’un guide d’intervention pour la reprise du développement psychosocial

La Covid-19 a été déclarée pandémie par l’Organisation mondiale de la santé le 11 mars 2020, résultant d’abord en un
confinement général de la province du Québec de mars à mai 2020, et depuis à des mesures sanitaires restrictives dans le but
de diminuer la propagation du virus. Ce projet de recherche porte sur l’adaptation des jeunes et des familles dans le contexte
de la pandémie de la Covid-19. Il s’agit de poursuivre une recherche qui a débutée à l’été 2020 auprès de parents d’enfants
âgés entre 6 et 17 ans et auprès d’adolescents âgés de 14 à 17. Les résultats issus de ce projet de recherche permettront de
mieux comprendre les facteurs personnels et familiaux liés à l’adaptation des jeunes et des familles lorsque confrontés à une
situation susceptible d’amener une grande charge de stress sur la famille et les individus. Ces résultats pourront mener au
développement d’outils afin de favoriser une meilleure adaptation des jeunes et des familles.

Ultrasound Nerve-block Guidance using Machine Learning

One of the most critical components of ultrasound-guided nerve blocks is the accurate detection of a nerve within an ultrasound image. Trying to classify the various types of tissue in a noisy, greyscale ultrasound feed is a very daunting task. Therefore, a software solution would help doctors to perform the procedure in a precise and effective manner. To date, there have not been many improvements in terms of nerve detection, often resulting in the application of more anesthetic than required. This is problematic because doctors aim to use the minimum amount of anesthetic which poses less of a risk for the patient’s health. This study will present a software-based solution for the detection of nerves in ultrasound images. The software will take advantage of machine learning and image processing techniques to detect the location of the various nerves in the body within an ultrasound feed.

Application of Machine Learning in Radiation Oncology Scheduling

Cancer incidence rates in Canada are increasing steadily every year which puts a strain on the treatment system. In Quebec, the waiting time to start treatment of cancer patients is enforced by law, however, it is difficult to meet with limited resources and personnel. Efficient planning is hence vital in
reducing the long waiting time of cancer patients as well as improving resources’ utilization and wellness
of medical staff.
Gray is a company founded with the ambition of applying Operations Research and Machine
Learning solutions to improve healthcare quality. Their product GrayOS, which provides multiple
functionalities such as modelling patient flows, automatically scheduling cancer treatments, real-time
optimization, has been deployed and is in the testing phase at the cancer center of CHUM. In this project,
the intern is expected to work with Gray to develop a novel approach for scheduling radiotherapy
treatments.
Scheduling in healthcare is challenging due to the stochastic nature of the field. Future arrivals of
patients are not known in advance, yet have a huge impact on the current scheduling decision. Many
techniques have been developed to take into account future arrivals such as stochastic programming or
Markov Decision Process. However, those techniques usually are algorithmically heavy and might be
difficult to implement and maintain in real-world applications.

Optimal building community operation using data-driven mixed-integer convex model predictive control

We propose a new approach to coordinate the energy consumption of the rooftop unit (RTU) heating, cooling, ventilation, and air conditioning (HVAC) system of commercial buildings within an aggregation, e.g., building or units of a shopping center. Our approach uses a new specialized solver for neural network-constrained integer programs to optimize the energy consumption while ensuring that (i) temperature preferences are respected in each building and (ii) electric network constraints like voltage magnitude or maximum line current are satisfied in the vicinity of the aggregation. The latter is important when taking part to demand response programs as can induce a sudden drop in power consumption or if the aggregation includes electric vehicle charging stations or solar panels that can significantly alter its power consumption. The expected benefit to BrainBox AI is a readily implementable approach that can (i) optimally, efficiently, and safely be used on one of their main client types, commercial buildings, and (ii) be built on to integrate new, refined building specificities by the partner.

Minimization of Switching Power Converter Ripples in RF Power Amplifier Circuits

As the power processing density in new technologies such as 5G and 6G increases, reduction of ripples caused by switching power converter operation becomes a gradually more difficult design problem to solve. Analysis of these ripples and exploring various methods for the ripple reduction in the RF power amplifier circuits are the main topics for this project. Except of developing and evaluation of various HW solutions for the ripple reduction, additional benefits for the partner organization include improving the design process by reusing algorithms developed for i) analysis of ripple voltage in circuits with switching power converters, ii) analysis of currents through electrolytic capacitors, and iii) design of the switching power converters. On the intern’s side, working on the project will create opportunity to gain industrial experience, specifically learning new skills and acquiring knowledge in the power supply area, and also learning the design process from the industry leader.

Réduction du bruit dans la ventilation minière souterraine

Le bruit des ventilateurs est une problématique de santé et sécurité au travail importante. Ainsi, des mesures effectuées sur des ventilateurs installés dans des mines du Québec ont montré des niveaux de bruit supérieurs à 100 dB(A), ce qui peut entrainer des lésions auditives majeures. D’autre part, dans les mines, le bruit des ventilateurs peut masquer le bruit des alarmes de recul de certains engins [Trudel 2011]. Le bruit des ventilateurs peut donc conduire à des situations dangereuses pour la santé et la sécurité des travailleurs. Le contrôle du bruit des ventilateurs est un donc un enjeu majeur dans l’industrie minière, qui est demandeuse d’équipements de ventilation plus silencieux. Dans ce contexte général, des études plus spécifiques concernant la mesure de la puissance acoustique des ventilateurs chez Équipements KN et l’étude de différents dispositifs de réduction du bruit, comme les silencieux seront menées.

An Investigation into Travel Demand Management Policies for Land Development

Single occupancy vehicle travel leading to congestion in urban areas is a significant problem. Congestion has numerous economic, social, and environmental impacts that negatively impact the prosperity and vitality of an urban area. One method for counteracting these negative impacts is known as travel demand management (TDM). TDM is a broad set of strategies that work to improve the efficiency of the transportation system by prioritizing the efficient movement of people instead of motor vehicles. This project will investigate how effective a set of TDM policies are at reducing congestion for new urban developments to allow land developers to implement these strategies into their projects. This investigation will involve the use of a type of travel survey. The survey will collect information about respondents’ current travel patterns as well as how those travel patterns might shift in response to hypothetical scenarios. These scenarios will involve some or all the TDM strategies under investigation being implemented and then will ask how the respondents travel behaviour will change.

Les nouveaux contours de la demande dans le secteur de la restauration : exploration des changements de comportement des consommateurs après la crise de la COVID-19

La crise de la COVID-19 a frappé durement le secteur de la restauration au Québec. Les fermetures de salles et le télétravail ont conduit les consommateurs à adopter de nouvelles pratiques d’achat. En réponse, les restaurateurs ont adapté leurs offres et se tourner, notamment, vers la restauration livrée. La valeur que les consommateurs accordent à ce qu’ils achètent au restaurant s’est ainsi transformée.

Parmi ces changements, lesquels vont perdurer à la levée des restrictions?

Aujourd’hui, à l’aube de la sortie de crise, les restaurateurs ont besoin d’anticiper les évolutions de la demande à venir afin d’adapter au plus vite leurs modèles d’affaires à ce nouveau contexte et saisir les opportunités.

Cette étude s’appuie sur une enquête réalisée auprès de 800 consommateurs québécois, afin d’examiner les nouvelles caractéristiques de la demande pour les produits de la restauration, et de proposer des scénarios d’évolution possible des comportements, à court et moyen terme.

Assessing the effects of neurofeedback through a comprehensive systematic review

Recently, principles gleaned from research on learning have been applied to change people’s brains. Specifically, there is evidence that how the brain communicates can be changed through the application of positive and negative reinforcement, a concept known as neurofeedback. Importantly, researchers claim that by changing how the brain communicates, neurofeedback can change behaviour and reduce clinical symptoms. As these techniques have grown in popularity, companies such as Neurotech Forty have applied neurofeedback to serve Canadians. However, due to variations in research quality, it is difficult for companies to discern quality research and where true neurofeedback effects are present. In the present work, we will undertake a systematic investigation of the literature to determine where consistent neurofeedback effects lie and provide an assessment of the quality of this work. The review undertaken for Neurotech Forty will allow the company to produce scientifically sound neurofeedback services, which in turn will allow Neurotech Forty to remain innovative and cutting edge.

Leviers de changement pour une transition du secteur alimentaire canadien vers une offre de produits zéro déchet pour les consommateurs

Ce projet cherche à mieux comprendre les freins à l’intégration du zéro déchet (ZD) dans la chaîne d’approvisionnement et les solutions les plus appropriées pour l’ensemble des parties prenantes. Ce projet va permettre de:

1. identifier les leviers de transition pour l’implantation de solutions ZD dans la chaîne d’approvisionnement des aliments;
2. dresser une liste préliminaire des produits les mieux adaptés au ZD, de recommandations et de pistes de solutions;
3. ouvrir le débat entre les acteurs clés sur l’intégration de la hiérarchisation des déchets dans leurs pratiques.

La recherche comprend une recension de la littérature, un sondage et des entrevues de groupe semi-dirigées, l’observation d’une recherche-expérimentation par études de cas. L’étude aidera à développer des pistes de solutions concrètes adaptées aux besoins du consommateur et des épiceries et sans créer de déplacements d’impacts, ainsi que des recommandations de politiques publiques qui guideront le gouvernement dans ses programmes de formation et de soutien des consommateurs et détaillants alimentaires.

Developing cultivars for the plant-based sector in Quebec: Phase i – breeding program construction and agronomy trials

It is critical for farmers to have cultivars so that they can make decisions on the best practices to undertake when growing a new crop and maintain productivity and competitiveness in the marketplace. Pulse production is growing in demand and is an established market in Canada. In addition, plant based protein products are growing in popularity. We are working on developing a set of tools and information and varieties that will enable farmers to grow more pulses in Quebec. We will also determine basic agronomic parameters that will maximize crop yield and minimize risk of crop failure.