Projets novateurs réalisés

Visualizing complex building analysis data to increase comprehension of public audience

This research study focuses on the communication and transmission of technical and industrial analytic data, developed by our research partner, ioAirFlow. Because the current recipients of ioAirFlow data reports are not always data- or engineering-trained professionals, complex data is not often understood or acted upon. This research internship focuses on ways in which to develop information design to communicate ioAirFlow’s data more effectively and efficiently. Using design methodologies of mixed methods and action research, we will develop information design and data visualization as a means to communicate, inform, visually analyze or compare, and prototype scenarios and challenges within ioAirFlow systems. Information design and data visualization can generate greater readability and accessibility in data interpretation and analysis. Communicating the ill health and inefficiencies of building environments through information design creates agency for its users or receivers, allowing building inhabitants to better understand their own health in relation to air quality.

Data Science Intern

Computer Vision – Business and Product Engineering Focus
Applying Artificial Intelligence and Machine Learning to solve outlier, merging, and segmentation problems for use-cases with laser scan and point cloud data.

Improvement of a Portable Assistive Device Concept for Hand Rehabilitation

As the number of patients with stroke and Parkinson’s Disease (PD) increases, it is essential to obtain treatment progress data efficiently for the home rehabilitation. For the therapy of hand disabilities, a system is required to collect data, process and control hand motions during rehabilitation. Current rehabilitation devices that are available in the market are costly and not portable. Existing hand training devices use contact-based sensing approaches that are expensive and inaccurate. As capturing hand motion data using the free joint interaction for rehabilitation and self-exercises still remains a challenge, we propose a low-cost portable system to measure joint motions quantitatively. It uses an electromagnetic driven hand exoskeleton to help patients follow treatment guidelines, which is integrated to a developed module for assessment of the recovery performance to record, analyze and visualize rehabilitation processes in real time.

Secure Communication Based on Public Key Distribution with Imbalanced Twin-Field-QKD-like Infrastructure in Classical Coherent Optical Fiber Network

In quantum key distribution (QKD), the twin-field has been proposed as a means to overcome the linear key rate
bound, and hence the key generation rate, as well as to enable repeaterless QKD transmission. Despite
significant progress in TF-QKD and its variations in recent times, the key rates are still significantly low compared
to practical optical fiber networks. Recently, we demonstrated a new approach for phase-encoded public key
distribution based on randomized Glauber states in a classical coherent optical communication system for secure
optical communications (we refer to this as coherent public key distribution CPKD). Establishing how our
previously proposed framework can be thought of as the coherent equivalent of TF-QKD can lead us to ensure
data-security at high speed over long distance without being limited by the rate-distance barrier of QKD
transmission. This project focuses on investigating the equivalence between our recently demonstrated CPKD
approach and twin-field quantum key distribution (TF-QKD). If successful, the proof-of-principle demonstrations
will provide a pathway for enabling secure data transmission in the telecommunication infrastructures that form
the backbone of smart cities, industries, and economies.

Subsea Pipeline Remnant Life Assessment

Many of the pipelines either offshore or onshore are nearing the end of their design life. Some of the pipelines show signs of deterioration and ageing as a result of corrosion and fatigue. There are situation where the operators desire to extend the life of an ageing pipeline beyond its life expectancy due to increased oil and gas demand or due to unforeseen increased oil and gas reserve. Other situations that force the operators to maintain the pipeline’s design life are the premature ageing of the pipe caused by the increased time-dependent deterioration. The key objective of the business for any oil and gas operator is to have a pipeline system that performs the intended function in a safe and cost effective manner. The objective of this research is to develop a structured and probabilistic model to assess and predict the useful and safe remaining life of subsea pipeline system. Applying this model will insure that the pipeline will perform satisfactorily, (i.e. complying with codes, maintaining integrity, etc.) and in line with predefined operating conditions.

Digital Strategy Internship

Top Sixty over Sixty, is a for-profit social enterprise supporting workplaces as they combat ageism. Ageism hinders opportunities for individuals and the productivity of businesses. This organizational and workforce development consultancy educates and empowers employers and individuals to understand and adapt to an ageing workforce and population. Currently, the organization is looking to expand their impact by increasing its number of B2B relationships and seeking digital strategies to scale Top Sixty over Sixty.

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.