Events

Abstract

Muscle Torque Generators (MTGs) have been developed as an alternative to muscle-force models, reducing the complexity of muscle-force models to a single torque at the joint. Current MTGs can only be applied to single Degree of Freedom (DOF) joints, leading to complications in modeling joints such as the shoulder. Therefore, this project aimed to develop, for the first time, an MTG model that accounts for the coupling between 2 DOF at the shoulder joint.

Abstract

Coherent structures (CS), i.e., regions of flowing fluid that exhibit significant spatio-temporal coherence, have long been observed in turbulent fluid flow. These CS offer an opportunity to gain insights on fluid behaviour by bypassing the non-linear complexities associated with turbulent flows. Historically, the identification of CS in turbulent flows has involved using manual thresholds to label regions of interest.

Abstract

Moderate to severe traumatic brain injury is the leading cause of injury-induced death and disability. For patients with traumatic brain injuries (TBI), in the first 48 hours, 48% of patients show a clinically relevant neurological worsening and therefore, it is critical that clinicians can identify neurological worsening quickly and act on treatment accordingly. 

Abstract

The Atomic Force Microscope (AFM) is an instrument for measuring, in fact “seeing”, phenomena at nanoscale (10−9m) and all the way down to the atomic scale (<10−10m). It was borne out of a need to observe physical reality below the resolution of optical microscopes. Invented in 1986 by Binnig, it has aided scientists, researchers, and engineers spanning many scientific and industrial domains. The typical sensing apparatus of the AFM is a very sharp tip (a few atoms wide) attached to the free-end of a fixed-free micro-beam.

Abstract

Sea ice mapping on synthetic aperture radar (SAR) imagery is important for various purposes, including ship navigation and usage in environmental and climatological studies. Although a series of deep learning-based models have been proposed for automatic sea ice classification on SAR scenes, most of them are flat N-way classifiers that do not consider the uneven visual separability of different sea ice types. To further improve classification accuracy with limited training samples, a hierarchical deep learning-based pipeline is proposed for sea ice mapping from SAR.

Abstract

Inflammatory Bowel Disease (IBD) refers to a group of conditions that primarily affect the gut and cause inflammation. In contrast, Hidradenitis Suppurativa (HS) is a chronic immune-mediated condition characterized by boils in a person's underarms, groyne, and/or under their breasts. In recent years, the research on HS has been gaining a growing level of interest in light of reliable recognition of these two diseases (i.e., IBD and HS) becoming crucial in clinical settings.

Abstract

Achieving reliable and robust performance of visual perception systems with Artificial Intelligence (AI) in real-world industrial applications can be challenging due to highly dynamic conditions and requirements. Traditional AI-based solutions require offline training on high-quality data, making it difficult to accommodate new technologies, data, hardware, tasks, and customer needs without retraining.

Abstract

Cauvery River, in the southern part of India, has experienced conflict about the right to use water for the last 130 years. Historically, the states/provinces in conflict have used the water from the river for agricultural purposes. In our research, we are developing a novel scenario-based approach for analyzing the conflict from a system of systems point of view.

Abstract

With an increasing demand for better medical diagnostic systems, improving the efficiency and effectiveness of medical diagnostics have never been more crucial. Field electron emission (FE) based X-ray source which is a more responsive and controllable alternative to traditional thermionic-emission-based X-ray sources has stimulated much research interest. Among the materials for FE, carbon nanotube (CNT) is one of the most promising candidates due to exceptional properties such as a high aspect ratio and good electrical and thermal conductivities.

Hear from a panel of engineers from Ontario Hydro Networks on how the energy system works from an engineering perspective. The panellists will also share aspects of their career journey and the skills that allow them to develop innovative solutions that keep our lights on!