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Parsing genetic models
(2022-01-01)
Applications of computer vision have seen great success recently, yet there are few approaches dealing with visual illustrations. We propose a collection of computer vision applications for parsing genetic models. Genetic ...
Simulating a virtual drilling task using audio, visual, and mouse movement cues during the COVID-19 pandemic
(2021-04-01)
This work examined whether a real-world drilling task can be successfully simulated using combinations of appropriate audio, visual cues, and basic haptic stimuli obtained with mouse movements instead of a haptic device. ...
Enhanced knowledge distillation by auxiliary classifiers
(2021-08-01)
Deep neural models have shown promising results in various areas, e.g., computer vision and natural language processing, at the cost of high computation and storage resource consumption. These characteristics of deep neural ...
Automatic fall risk detection based on imbalanced data
(2021-08-01)
In recent years, the declining birthrate and ageing population have gradually brought countries into an ageing society. In regards to the accidents that occur amongst the elderly, falls are an important problem that quickly ...
Assessing the memorability of familiar vocabulary for system assigned passphrases
(2021-08-01)
Text-based secrets are still the most commonly used authentication mechanism in information systems. Initially introduced as more secure authentication keys that people could recall, passphrases are tokens consisting of ...
Effect of copper contamination at the cathode in Cu-Cl electrolyzers for hydrogen production
(2020-04-01)
In this work the effects of copper contamination on the coulombic and voltage efficiency of the hydrogen evolution reaction (HER) via the Cu-Cl thermochemical cycle are investigated. A novel proton pump configuration was ...
On deep learning in physics
(2021-04-01)
Machine learning, and most notably deep neural networks, have seen unprecedented success in recent years due to their ability to learn complex nonlinear mappings by ingesting large amounts of data through the process of ...
Investigating the distribution of Nitellopsis obtusa in Ontario Lakes and its role as an ecosystem engineer
(2021-08-01)
Nitellopsis obtusa is a non-native macrophyte introduced into the Laurentian Great Lakes in 1974. Over the last decade, increasing reports emerged for N. obtusa within lakes in the Great Lakes Basin. Despite N. obtusa being ...
A deep learning approach to focal cortical dysplasia segmentation in children with medically intractable epilepsy
(2021-08-01)
Paediatric epilepsy is one of the most common neurological disorders and has major impact on the cognition and quality of life of children. Focal Cortical Dysplasia (FCD) is one of the most common causes of medically ...
Water quality and biotic community response to an urban – rural land-use gradient in the Lake Simcoe watershed
(2020-06-01)
Most research in the Lake Simcoe watershed (LSW) has focused on how the lake has responded to changes in nutrients sourced by agriculture, particularly after mitigation measures have been put in place to remedy the lake’s ...