Multi-modal Defect Detection of Fillet Joints in Gas Metal Arc Welding

Failure in pipelines may have financial and life-threatening consequences. High-quality weld joints in pipelines can avoid these consequences and improve the company’s productivity and reputation. To improve the weld quality, an efficient solution is to detect the defects. A collaboration of human and robots can provide an accurate, robust defect detection system. This system requires sensors to observe and record the information during the welding process. It also requires an Artificial Intelligence (AI) model to distinguish the defective and normal data.

Epictrode - Customizable Printed Medical Tattoo Electrodes for Bio-signal Acquisition

The proposed research project is focused on customizable medical tattoo electrodes used on patients in different clinical settings. These electrodes are placed in specific places on the body and are connected to medical signal acquisition systems to collect different medical signals. The signals can include ECG (heart) signals and EMG (muscle) signals, and these signals can be used to diagnose or simply monitor the respective systems (cardiac and skeletomuscular) in the body. This project is part of the Lab2Market program.

Artificial Intelligence driven/powered noninvasive blood glucose monitoring system by integrated multi-spectroscopic platform

Diabetes mellitus, commonly known as diabetes, has been estimated to affect 450 million people in the global population. To date, there is no cure for diabetes; however, it can be controlled by regulating the sugar intake in the blood. The traditional self-monitoring devices are invasive and require the user to prick their fingers and extract blood drops to measure blood glucose based on chemical reactions, which is a painful process and processes a risk of infection.

Anonymous Age Verification Using Electrocardiogram (ECG) Obtained from Smart Wearables

Age-verification mandatory procedure for delivering certain services and products. Traditionally, identification documents have been a common mechanism of age-verification. However, this current strategy is subject to certain risks regarding privacy protection and online forgery. This demonstrates the value in anonymous age verification schemes using biometrics. Considering its age-dependent attributes, Electrocardiogram (ECG) is a potential solution. Preliminary experiments have been conducted regarding age estimation- classification from ECG obtained in clinical settings.

MEV protection through delayed execution and time-locked puzzles

Blockchain technology is, by nature, transparent and decentralized. However, transparency can sometimes be a direct threat to the system's decentralization when most of the profitable transactions get stolen by several high-power entities. This de-incentivizes new users from using the system and renders the whole system useless. In this project, we aim to guard decentralization against destructive and unfair effects of transparency. We reason that transparency can harm the system when it enables users to easily front-run each other.


Maya HTT développe actuellement une solution de corrélation automatique des modèles numériques thermiques complexes permettant d’améliorer la précision et la fiabilité des modèles et de créer des jumeaux numériques temps réel et fiables, en particulier pour les applications aérospatiales (moteurs d’avion et satellites).
Dans le cadre du développement de cet outil plusieurs défis technologiques importants ont été identifiées, dont la réduction des modèles numériques (« Reduced Order Models ») et l’utilisation de la technologie « Graphic Processing Units (GPU) » pour réaliser les calculs scienti

Design and development of electrochemical sensors for detection of specific cannabis terpene constitutes validated by liquid chromatography hyphenated with tandem mass spectrometry (LC-MS/MS)

The fast growth of the cannabis industry has been impacting the regulatory sector. Governments and private regulatory organizations have been working hard to make sure the industry grows based on proper regulations and testing procedures. The problem is that all of the regulations that are currently designed for the cannabis industry are based on procedures and testing methods that have been used in the pharmaceutical industry.

Partial Discharge Propagation Model for Power Transformer Winding

Transformers are one of the key elements in electric power systems whose health ensures reliable, stable electric power for the economy and society. Partial discharge (PD) is known to be a symptom of defects in electrical insulation systems, such as those employed in transformers. Detection and localization of PD in transformers are critical to develop a mitigation strategy. The main objective of the proposed research is to develop an artificial intelligence model that is able to predict the location of PD in transformers.

Sales Micro-Patterns: ML-driven detection of deviant Store/SKU sales patterns

For almost a century, Canadian Tire has been offering products and services to help Canadians with the jobs and joys of life in Canada. Today, with a network of over 1,700 retail locations, Canadian Tire is dedicated to improving products and services offered to the community they serve. With this project, the company aims to examine the patterns of sales among its stores to identify anomalous product sales patterns. The objective is to design and develop a system capable of generating high-confidence automated notification to the stores.

Predicting falls based on a 2-minute walk test

Falls are the leading cause of injuries in older adults. Identifying older adults with risk for falls prior to discharge home from the Emergency Department (ED) could help direct fall prevention interventions, yet ED-based tools to assist risk stratification are under-developed. The aim of this study was to compare the performance of our proposed machine learning algorithms with existing screening tools to predict future falls in the 90-days post ED discharge for 150 older adults aged 65 years and older.