Projets novateurs réalisés

UX Application Marchant et Centre de données

Tastet est un guide de bonnes adresses ! Notre mission est de promouvoir le milieu de l’hospitalité, soutenir son essor et contribuer à sa vitalité. Nos critères d’analyse des établissements permettent d’offrir un contenu de qualité le plus objectivement possible. Tastet est basé sur la confiance mutuelle des gens du milieu avec les actrices et auteurs, le professionnalisme, l’intégrité et la créativité. Le site est suivi et lu par les influenceurs du milieu, ce qui amène une touche personnelle et des contenus exclusifs.

Après avoir vécu la fermeture des restaurants pendant la pandémie, le rôle de Tastet est encore plus d’actualité, car les restaurateurs ont aujourd’hui plus que jamais besoin de l’aide d’un média comme Tastet pour mettre de l’avant le côté gastronomique de la ville. Alors, ce projet apportera une contribution au secteur culturel de la ville en plus d’aider le secteur privé de la restauration et de guider les particuliers dans leur choix de sortie.

Ce projet en particulier aiderait grandement à améliorer l’expérience de nos utilisateurs sur les 2 nouvelles plateformes pour qu’elle soit à la hauteur de nos attentes.

Synthesis and Evaluation of Reversible Covalent-Binding AntiCancer Drugs

Designing new anticancer agents using structure based drug design and the 3D structure of the biological target
is becoming an increasingly important field of study. The main objective of this project is to develop and identify
anticancer drug candidate(s) for advanced preclinical testing, with the end goal of identifying drug candidates
suitable for clinical trials and commercialization. Currently, we have synthesized several novel drug candidates
designed to mitigate the increased toxicological effects observed in a significant proportion of patients receiving
current therapies. Meanwhile we will also investigate whether our designer molecules will have enhanced
anticancer properties over similar anticancer agents during early phase pre-clinical testing. This research project
will provide a better understanding on how our designer molecules behave as anticancer agents.

Developing a trading strategy for Bitcoin Market using Long Short-term Memory (LSTM) architecture

Prediction of financial markets time series market direction is a challenging task mainly due to the unprecedented changes in economic trends and conditions in one hand and incomplete information on the other hand. Therefore, developing different forecasting, like LSTMs, have been employed by quantitative traders recently.
Long Short Term Memory networks (LSTMs”) – are a special kind of recurrent neural network (RNN), capable of learning long-term dependencies. LSTMs are explicitly designed to avoid the long-term dependency problem, with additional features to memorize the sequence of data.
The purpose of this project is to use LSTMs to develop trading and day-trading strategies for Bitcoin Spot market. The inputs to the LSTM models are found through a supervised feature selection process over a pool of various features. These features include a set of technical indicators, and another feature obtained from market sentiment analysis.

Design improvement and prototyping of an upper limb rehabilitation device

Upper limb rehabilitation devices mirror the skeletal structure of patients’ limbs and moves patients’ arms for recovery in rehabilitation exercises. Existing rehabilitation devices in the market have problems of adaptability and portability, which cannot meet different requirements of rehabilitation. This project will improve the design and build a prototype the device. The detail design will be improved in dimensions and specifications based on relation of design parameters and functions. The device prototype will be made by 3D printing. The solution will be tested and evaluated in the device test operation using the motion sensor and kinematic analysis. The improvement will be made based on the required velocity and acceleration of joints of the patient arm in rehabilitation. It is expected that an adaptable and portable rehabilitation device developed in this project will benefit the rehabilitation exercise of patient recovery.

A model retrieval system for efficient bolus shaping

Bolus covers patient’s skins to correct varying surface contours for desired dose distribution in cancer care. The existing method of bolus shaping is a manual process by cutting the bolus material into 2D pieces and wrapping the pieces on the targeted body area, which is inaccuracy and time-consuming. An accurate and efficient bolus shaping method is proposed to increase the bolus shaping accuracy and reduce air gaps by applying a 3D-2D-3D process. In order to improve the efficiency, a model retrieval system will be developed based on feature extracting and image-based matching methods. The system consists of a human body model base and a user interface to accurately and efficiently form bolus for patients in cancer care treatment.

The role of automobility engagement in consumer response to fully automated vehicles

This project’s objective is to help improve knowledge regarding consumer perspectives of conventional car mobility and transport innovations in Canada, with particular focus on fully automated vehicles (FAVs), or vehicles that can drive themselves without requiring a driver to be paying attention. Innovations can alter the transport sector’s environmental sustainability – for example, electric vehicles are key in lowering greenhouse gas emissions, while FAV impacts are uncertain. The Sustainable Transportation Action Research Team (START) and Navius Research Incorporated are leaders in analyzing impacts from such innovations in Canada. The prevalence of car use as the main transport mode, also referred to as “automobility”, has led to several societal problems and may lower innovations’ sustainability benefits. This project aims to investigate consumer perspectives of FAVs and their expected impacts on how consumers engage with mobility by private cars by conducting semi-structured interviews with households in British Columbia.

Colorimetric test strips for oil/fuel/ethanol mixtures

There is a need for customers to use a simple test method to determine if the fuel blends they are using are of the proper composition for fuel efficiency, environment- friendliness and engine cylinder compatibility. But it is difficult to determine the composition of oil/fuel/ethanol mixtures without detailed and expensive chemical analysis. It is because the different hydrocarbons in oils or in fuels are hard to differentiate by physical change or by simple chemical reactions such as pH change. In order to perform a simple test such as a colorimetric analysis, it may be necessary to find out the additives present in the oils and fuels for detection. There are many colorimetric tests available in the literature for the detection of these additives. However, these tests are all tedious that are not amendable to the simple test format such as the test strip. On the other hand, nanomaterials have been synthesized to test for viscosity and wettability of organic liquids. However, these nanomaterials have not been used to test oil/fuel/ethanol mixtures. Therefore, in this proposal, a series of nanomaterials called inverse opal films will be prepared.

Coastal Convection Modeling

Global warming is a major issue faced by society nowadays and to fight it we need to be able to make global climate projections
with less uncertainty. Despite numerous progresses in theoretical and computational modelling, there are still climatic
phenomena that remain partially unresolved because of the coarseness of the grid resolutions used in global climate and
numerical weather prediction models. Indeed, current do not capture well intense storms and precipitation events that occur in
coastal areas and around many tropical islands, which are known to impact in return the global climate variability and weather
patterns. We propose a simple model that is able to capture the key characteristics of coastal convection and its impact on the
global atmospheric circulation. For that purpose, we will use the multicloud model proposed by Khouider and his collaborators that
represents various cloud types based on a stochastic lattice model. The model has two uniform columns, one for the land and one
for the ocean, that interact with each other. Preliminary runs showed that the model is able to capture features of coastal
convection such the ability of rain systems to propagate from the land to the ocean column and vise-versa.

A Toolkit for Affordability Driven Home Energy Efficiency Retrofits Through Local Improvement Charge Programs

Climate change will cause increasing temperature fluctuations and longer heat waves. This will make home cooling essential, but adding and using cooling can be too expensive for low-income homeowners, including seniors. Incentive programs exist to help people make energy-efficient retrofits to their homes, but they can increase housing costs. This does not work for many low or fixed-income and senior households. The Affordable home energy retrofit toolkit demonstration will explore making energy-efficient retrofits affordable for more households. It will work within Toronto’s existing Home Energy Loan Program to provide innovative retrofits to low-income and senior households. This approach aims to reduce energy costs, improve health and safety, and allow seniors to age in place for longer.

Les mécanismes moléculaires des interactions virus-hôte du virus de la diarrhée épidémique porcine (PEDV)

Nous étudierons les mécanismes moléculaires des interactions virus-hôte du virus de la diarrhée épidémique porcine (PEDV), un
important coronavirus porcin à ARN enveloppé. Ce virus est responsable de graves pertes économiques et constitue le principal
agent pathogène émergent du porc au Canada et dans le monde. Nous proposons d’étudier les mécanismes moléculaires des
interactions hôte-PEDV, car nous pensons que notre compréhension insuffisante de ces interactions entrave le développement
de nouvelles stratégies pour un contrôle efficace du PEDV.
Récemment, l’épidémie de SRAS-CoV-2 a relancé l’intérêt pour l’étude des coronavirus animaux. Il est donc essentiel de
comprendre la biologie des coronavirus porcins afin d’améliorer notre capacité à prédire et à contrôler les futures pandémies.

Development of an intelligent decision model to support the occupational health and safety in the manufacturing industry

CONFORMiT seeks to prevent serious injuries and fatalities and high potential events by providing administrative
control solutions that can enable businesses to manage critical risks within their operations. To accomplish its
main mission, the firm uses its consulting experience in the design of safety programs according to standards; the
design and provision of training; identification and labeling of equipment; management of entrances and exits for
confined spaces; the development of lockout and tagging procedures (LOTO); and the design of compliance audit
schedules.
CONFORMiT’s vision is to digitize the management of risks for humans and the environment, through an intelligent
and comprehensive business solution, that allows the management of Environmental Health & Safety from
strategy to production, scheduling operations plant and maintenances.
This internship project will concentrate on developing a “roadmap” towards an intelligent strategy for integrating
LOTO processes of a production system for its maintenance operations using AI strategies, based on available,
practical data.

Creating sustainable Food Systems for Local Food in Newfoundland and Labrador

We will be gathering, analyzing and sharing publically detailed information about the current state of food production at the community level and examining the potential for rebuilding food security based on local production and distribution. We have already begun interviews across the province to gather the relevant data. During this internship, interview data will be analyzed, extended through further enquiry and used to define the potential for innovative approaches to local food production and distribution. We plan to use Nvivo and GIS (Geographic Information Systems) mapping for qualitative analysis of data. This work will involve creation of a database derived from interview responses, a second round of data gathering and analysis followed by public engagement to share the results. Through this work, we hope to generate a cohesive picture of key components needed to rebuild food security across our province.