Innovative Projects Realized

Remote Sensing of the forest biomass available for energy productionin central Ontario

As part of Ontario’s Climate Change Action Plan, Ontario Power Generation seeks to increase

the supply of renewable energy, including wind, solar, and biomass. It is estimated that 7.6-9.5

million metric tons of unused wood is available to produce bioenergy in Ontario, above that

which is currently harvested for wood products. Yet, the exact magnitude and spatial distribution

of this untapped resource is not well known. In central Ontario, a considerable amount of

unmerchantable wood (including small trees, large branches, diseased trees, and undesirable tree

species) is left behind after harvesting. But much of this unmerchantable wood is not inventoried

because traditional ground-based inventory methods are not designed to quantify this new

resource. The objective of this project is to test the feasibility of using a remote sensing

technology called Light Detecting and Ranging (LiDAR) to measure the amount unmerchantable

wood in hardwood forests of central Ontario.

Improving Primary Care in Older Patients: a Focus on Safe and Appropriate Medications

Seniors take many medications during their lifetime. As seniors age, some of these medications may become unnecessary or even harmful. The process of stopping a medication that has the potential to cause more harm than benefit is called deprescribing. Physicians are more in the habit of prescribing than deprescribing, even though patients like the idea of getting off some of their pills if they can. The goal of this project is to use technology to support physicians in the deprescribing process. We intend to create a new program in the Omnimed electronic medical record system that will remind physicians to deprescribe, will provide them with tools and education on deprescribing, and that will automatically send patients educational material on drug safety. We will evaluate the utility of the software by tracking how many patients end up discontinuing unnecessary medication. TO BE CONT’D

Virtual testing of composites in aerospace

Canada’s aerospace industry relies on expensive and time-consuming testing campaigns to introduce new composites or obtain baseline material properties. Design allowables (e.g., strength used in design phases) are obtained from empirical knock-down factors that account for temperature, environment, etc. This approach is over-conservative and disconnected from physical grounds; it also leads to situations where different teams in the same company (e.g., Bombardier) use different factors for the same part. Having accurate predictive models could reduce testing and decrease knock-down factors. Composites failure is a complex multi-scale process and no “simple” theory can accurately predict composites failure. At this stage, no framework seems to emerge as more suitable.
The principal objective of this project is to plan how using existing and novel composite failure predictive models and techniques can reduce testing and determine more accurate design factors. TO BE CONT’D

Acoustic and Speaker Modeling Using Deep Learning

There is a rapidly growing need for voice powered human-machine interaction modalities for varieties of devices. Despite enormous investment in research and development in this area by a number of companies, significant limitations remain which prevent the ubiquitous proliferation of speech recognition. These limitations include poor performance in the presence of noise, inability to handle variability in accents, and not reliably recognizing the speaker. Fluent.ai is investigating novel neural network architectures for solving aforementioned issues with a primary target market of personal smart devices such as wearables, smart-toys and smart-home devices. Two key aspects of a successful voice user interface solution for such devices include high recognition accuracy even in the presence of noise and ability to adapt to speakers with difference speaking styles and accents. It is crucial for Fluent.ai’s business that these challenges are addressed effectively. TO BE CONT’D

Développement et validation de nouvelles cibles épigénétiques de la douleur chronique chez l’animal arthrosique – Year two

La douleur arthrosique est la première cause de morbidité et de douleur chronique dans nos sociétés occidentales, source de pertes économiques et de productivité énormes. L’arthrose est aussi la maladie dégénérative la plus commune chez les animaux de compagnie et un sujet de consultation vétérinaire fréquent. Malgré des analyses extensives, l’origine et le développement de cette douleur demeurent mal compris. Ce projet de stage post-doctoral en partenariat entre ArthroLab Inc. et le GREPAQ de l’Université de Montréal a pour objectif de détecter des cibles épigénétiques de la douleur arthrosique sur des modèles expérimentaux rongeurs, de tester différentes voies de signalisation cellulaire suspectées d’être impliquées dans la genèse de la douleur et modulées par ces éventuelles cibles épigénétiques. Par la suite, les résultats les plus probants seront transférés sur les modèles naturels d’arthrose rencontrés chez le chat et le chien. TO BE CONT’D

Développement et validation de nouvelles cibles épigénétiques de la douleur chronique chez l’animal arthrosique

La douleur arthrosique est la première cause de morbidité et de douleur chronique dans nos sociétés occidentales, source de pertes économiques et de productivité énormes. L’arthrose est aussi la maladie dégénérative la plus commune chez les animaux de compagnie et un sujet de consultation vétérinaire fréquent. Malgré des analyses extensives, l’origine et le développement de cette douleur demeurent mal compris. Ce projet de stage post-doctoral en partenariat entre ArthroLab Inc. et le GREPAQ de l’Université de Montréal a pour objectif de détecter des cibles épigénétiques de la douleur arthrosique sur des modèles expérimentaux rongeurs, de tester différentes voies de signalisation cellulaire suspectées d’être impliquées dans la genèse de la douleur et modulées par ces éventuelles cibles épigénétiques. Par la suite, les résultats les plus probants seront transférés sur les modèles naturels d’arthrose rencontrés chez le chat et le chien. TO BE CONT’D

Modelling successional dynamics in the boreal mixedwoods – Year two

A thorough understanding of the effects of the natural disturbances on successional dynamics is essential when developing silvicultural approaches. If applied correctly, this understanding should ensure the sustainable management of the wood resources, as well as the conservation of the biological attributes and ecological functions of forest ecosystems. With respect to the spatial and temporal complexity of the successional dynamics of forest ecosystems, simulation models are powerful tools as they are able to address many factors simultaneously. In this respect, forest simulators can process a large amount of data and parameters which are required to better understand and predict species and structural succession occurring at the stand and landscape levels. TO BE CONT’D

Modelling successional dynamics in the boreal mixedwoods

A thorough understanding of the effects of the natural disturbances on successional dynamics is essential when developing silvicultural approaches. If applied correctly, this understanding should ensure the sustainable management of the wood resources, as well as the conservation of the biological attributes and ecological functions of forest ecosystems. With respect to the spatial and temporal complexity of the successional dynamics of forest ecosystems, simulation models are powerful tools as they are able to address many factors simultaneously. In this respect, forest simulators can process a large amount of data and parameters which are required to better understand and predict species and structural succession occurring at the stand and landscape levels. TO BE CONT’D

Conception and automatisation of a tunable Phase-Mask Interferometer for Fiber Bragg Grating inscription – Year two

Optical fiber Bragg gratings (FBG) have become ubiquitous in many products such as lasers, filters and sensors. However, typical commercial products are becoming more complex, ones that require highly competent operators since many parameters need to be fine-tuned during the writing of quality FBGs. A previous Mitacs project successfully addressed several challenges in the conception of a FBG writing system based on scanning tunable Phase-Mask Interferometer, marketed by PhotoNova as the BraggTune, using different UV lasers. However, many challenges remain to make the commercial unit more versatile, precise and easier to use with semi-automation, removing the uncertainty of manual mechanical tuning, as in the present product. In the first phase, the flexibility and the ease of use of the device by automating the existing product enabling fabrication of different types of FBGs will be researched. TO BE CONT’D

Towards energy efficient MURB (Multi unit residential buildings)

MURBs are responsible for approximately 20% of residential energy consumption and are as energy

intensive as single family homes (on a kWh/m2 floor area basis). The energy performance of MURBs,

combined with an overall aging of the stock, is beginning to result in more effort on the part of industry

and government to develop measures to make MURBs more energy efficient.

This is a multi-disciplinary research program that will provide background material for the

development of a MURB sustainability best practice guide. The research will look at the issue of

energy saving and efficiency from different aspects: social-psychological and behavioural aspects,

energy simulation, energy labelling and energy benchmarking, indoor environment and building

envelope retrofit. The outcomes of the proposed project will be used for the development of a best

practice guide on resource efficiency for MURBs.

Conception and automatisation of a tunable Phase-Mask Interferometer for Fiber Bragg Grating inscription

Optical fiber Bragg gratings (FBG) have become ubiquitous in many products such as lasers, filters and sensors. However, typical commercial products are becoming more complex, ones that require highly competent operators since many parameters need to be fine-tuned during the writing of quality FBGs. A previous Mitacs project successfully addressed several challenges in the conception of a FBG writing system based on scanning tunable Phase-Mask Interferometer, marketed by PhotoNova as the BraggTune, using different UV lasers. However, many challenges remain to make the commercial unit more versatile, precise and easier to use with semi-automation, removing the uncertainty of manual mechanical tuning, as in the present product. In the first phase, the flexibility and the ease of use of the device by automating the existing product enabling fabrication of different types of FBGs will be researched. TO BE CONT’D

Efficient and low-complexity video coding for virtual reality and 360-degree video streaming – Year two

Virtual reality (VR) and augmented reality (AR) offer a unique immersive video experience by providing 360-degree video in a panoramic view. Limited bandwidth, demanding high quality, encoder delay, network latency and lack of standards are the main problems to deliver true VR immersive experience. To address these challenges, in this research, we intend to design a VR system based on learning concepts to provide efficient bandwidth usage where the encoder makes smart decisions to assign different qualities to different parts of the spherical frame based on the user’s view using features such as video content and user’s movement patterns. The 360 frame is split into segments such as tiles where the size, number and the quality of tiles are determined adaptively and on-line. TO BE CONT’D