With the COVID-19 pandemic, there is a huge demand for advanced face masks and air filtration systems that could not only prevent transmission of respiratory droplets but having the ability to kill pathogens. Meltblown filters are widely used in these systems for enhanced filtration efficiency but currently they are limited by fouling and have no inherent antimicrobial properties. Here, we propose to add these two features to meltblown filters and make them more competent to combat disease transmission.

Currently, the service provided by Axya links manufacturers and buyers of manufactured goods. In order to find aperfect match between a manufacturer and a buyer, the computer-aided design (CAD) files they share need to beanalyzed. However, manual analysis of large amounts of CAD files is too time-consuming while requiring highengineering expertise. Based on this, it is proposed 1) to investigate ways of automating the analysis of CAD fileswith data mining; 2) to retrieve and analyze crucial features from CAD files; and 3) to identify future venues forCAD data mining system development.

The blown plastic film industry is constantly evolving, and the simpler products of just a few years ago are being displaced by new technical films. Market pressures have demanded a lower cost of plastic film with higher quality and thinner gauges. As a result of these trends, the demand for improvements in gauge control of the film increases dramatically, especially for manufacturers with older generations of equipment.

Additive manufacturing (AM) has gained significant interest of aerospace and biomedical industries to produce light weight components with complex geometries. Laser powder bed fusion (LPBF) technology is an AM, process which can improve the productivity and the material efficiency of low volume-high variety manufacturing.

While newer, advanced Filament Fused Deposition Modeling (FFDM) 3D printing systems for additive manufacturing of plastics products have been designed in order to increase rate productions similar to conventional plastic transformation processes.

Bearings are typically located in the heart of all rotating applications, with rotational speeds, forces, and vibrations impacting them somehow. Due to various reasons, such as fatigue, bearings encounter abrupt operation failure that damages surrounding components. In some applications, such as wind turbines and high-speed trains, it is expensive to replace the bearing and other damaged parts, despite the threat to humans’ lives. Since condition monitoring requires expensive sensors, many small industries still use conventional methods like run-to-break.

Composite structures are very popular in industries due to their lightweight and high strength. They degrade and cause huge economic losses or even serious disasters. Structure health monitoring has a great significance in the operation and maintenance of industrial assets. Current commercial software for structural health monitoring uses traditional and common methods which are only effective in constant loading conditions and require a large amount of historical data to train models. The intern has developed an unsupervised structural damage detection technique.

Automated essay scoring (AES) task involves using computer technology to grade written assessment and assigning a score based on its perceived quality. AES has been among the most significant Natural Language Processing (NLP) applications especially due to its educational and commercial value. Accordingly, AES is a well-studied topic with previous studies focusing on improving the performance via state-of-the-art deep learning and NLP methods to more accurately score the essays. The majority of these studies rely on publicly available corpora and limited datasets.

In the proposed project, we will investigate a solution for increasing the safety of construction workers at heights using an intelligent sensor-based system. A real-time monitoring system will be developed for alerting workers who are getting close to hazardous conditions and areas. The objective is to lower the chance of accidents by enhancing supervision of workers for their safety based on regulations and working practices in a construction site.

Helical steel piles are commonly used structural elements that anchor building foundations deep in the soil. Recently, it has been demonstrated that they can be used as ground heat exchangers with ground source heat pumps (GSHPs). These dual use geo-piles (structural and thermal) have the potential to significantly reduce GSHP installation costs, leading to greater adoption of sustainable energy technology. A potential application of geo-pile heat exchangers has been identified in the remote Canadian North.