Innovative Projects Realized

Development of an NLP Sales Assistant using Machine Learning Techniques

The main goal of this project is to develop machine learning and natural language processing approaches to help customers to communicate their preferred brands and/or retailers via Heyday solutions. These approaches will automate answers and help to humanely engage with customers. In order to reach these objectives, some challenges will be tackled such as automatically recognizing the users intent and replying to frequently asked questions. Recognizing ambiguous words is another challenging task to provide accurate answers. In order to reduce the risk related to sensitive subjects and questions (e.g. health related questions), a machine learning approach will be developed and integrated, also.

Cyclic Freeze-Thaw Behavior of Geocell-Reinforced Bases

Geocells are a type of three-dimensional honeycomb geosynthetics that are widely used to improve the performance of paved and unpaved roads by reinforcing the base/subbase courses. It is approved to benefit the long-term performance of roadways and reduction of construction cost. Although geocell has been widely used in roadway construction in cold regions, showing measurable improvements, research regarding the cyclic freeze-thaw behavior of geocell-reinforced roadways is rather scarce. A good understanding of factors influencing the cyclic freeze-thaw performance of geocell-reinforced bases is vital to the design and construction of roadways. This project aims to perform field monitoring and a series of experimental investigations of the behavior of geocell-reinforced bases subjected to the freeze-thaw cycles. The final goal is to improve the design practices for construction of the durable roadways in Canada.

Exploring race representation and the racial wage gap in Southern Ontario’s Tech Industry

There is a lack of “diversity” in Canada’s tech industry and this is what the research is based on. The lack of research considering racial diversity in the tech industry in Canada leaves a significant gap in understanding issues that would be critical in addressing such a lack of diversity. This research will explore how, to what extent, race is represented in Southwestern Ontario’s tech industry. In so doing, it will determine if, and if so, to what extent, there is there is a race equity pay gap. It will provide a baseline assessment of to what extent race is represented in SWO’s tech industry. Important to this research is understanding how intersection race, gender, age and other such factors intersect. The research will take place in three phases over a one-year period using both qualitative and quantitative measures. The research will have three potential outputs with relevance to both the tech industry and academia.

Sodium Manganese Oxide Coated with Polymers as Zinc and Sodium Dual Ions Battery Cathode

Rechargeable aqueous zinc sodium dual-ions batteries are considered as alternatives of lithium ion batteries because of their safety and low-cost. As an available cathode for the zinc sodium dual-ions batteries, sodium manganese oxide (NMO) shows relatively high specific discharge capacity. Polyaniline (PANI) is promising for coating NMO to stabilize the NMO system because it can supress the crystalline structure collapse. Metanilic acid is promising for doping PANI to increase the conductivity of PANI. In this research, we will modify different parameters such as the molar ratio of Na and Mn, the weight percentage of PANI coated on NMO to obtain better cycling performance than bare N

Steering the Innovation Process: Accelerating “Ideas to Impact” in Water Treatment

Demand for water and wastewater treatment equipment has grown substantially over the last several

years, leading to a significant increase in the market size for technology providers such as Trojan. To

maintain the cutting-edge nature and quality of Trojan products, it is essential that the research and

testing performed at Trojan match this expansion in demand. Historically, one of the distinguishing

features of Trojan’s products has been the rigorous analysis and testing that the products undergo

during the design and development phase. Trojan uses cutting-edge tools for modeling fluid flow, UV

radiation distribution, and biological and chemical kinetics to predict reactor performance. Computerbased

experiments are accomplished by using Computer Aided Engineering tools such as

Computational Fluid Dynamics (CFD) models. Trojan also performs extensive physical testing to

validate integrated CFD-optical-kinetic models used during product development to optimize design

and to validate completed designs and control algorithms. The strategic objective of this research

program is to determine a holistic algorithm able to guide….TOBECONTINUED

Modèle d’occupation individualisé pour le secteur résidentiel – Partie 2

Le marché énergétique est en transition. La demande et la consommation d’énergie dans le secteur résidentiel seront impactées par l’adoption de nouvelles technologies et l’évolution des comportements. Le projet de recherche vise le développement d’un modèle statistique générant des profils temporels individualisés de présence des individus à leur résidence en fonction des attributs des individus. Le modèle retenu sera construit à partir des données de l’Enquête sociale générale de Statistique Canada de 2010 et de 2015. À terme, les résultats du modèle d’occupation développé pourront alimenter des modèles de consommation énergétiques de résidences pour quantifier l’impact de scénarios d’évolution technologiques et comportementales sur la demande et la consommation d’énergie.

Evaluation of a radiomic approach based on hyperspectral retinal imaging to predict the cerebral amyloid status for the diagnosis of Alzheimer’s disease

The project will help Optina validate and further develope a novel technology to predict the presence of significant amyloid (A?) deposition in the brain from a simple, non-invasive hyperspectral retina scan in combination with an artificial intelligence algorithm. Accumulation of A? plaques in the brain is a key hallmark of Alzheimer’s disease (AD), but current methods to evaluate its presence in vivo (A? positron emission tomography imaging and quantification of A? proteins in the cerebrospinal fluid obtained) are not practically implementable as screening methods due to cost, availability and/or invasiveness nature. The continued development of the device and the design of a clinical study is an important milestone towards raising the required capital (possibly 15-20M$) to reach the AD diagnostic market. The project will train individuals who are specialized in medical device development, clinical trial design and coordination, project management and regulatory affairs.

Machine Learning and Data Mining Approaches for Smart Buildings

The goal of this project is to develop machine learning and data mining algorithms relying on non-intrusive common sensor data to estimate and predict smart buildings’ occupancy and activities. Efficient feedbacks are automatically supplied to the end user to involve occupants and increase their awareness about energy systems. This consists of generating reports helping the occupant to understand his/her energy management system and thus to be involved in the decision-making process. The project directly aligns with Ericsson’s IoT mission and expands its operator potential opportunities by exploring a dimensionality in real-time automation, monitoring and tracking, and smart surveillance. It also further strengthens Ericsson’s position in the IoT market which has a projected additional revenue potential of up to 36% (USD 619 billion) by 2026. Moreover, the machine learning techniques to be developed can be easily adapted to other problems of interest to Ericsson.

Optimisation de la qualité des images et visualisation des tissus mous en Cone Beam Computed Tomography (CBCT)

L’imagerie cone beam CT (CBCT) prend une place de plus en plus importante dans l’exploration des structures osseuses du complexe dento-maxillo-facial. Cette modalité d’imagerie, moins irradiante que l’imagerie par tomodensitométrie conventionnelle (TDM), procure des images de qualité similaire, voire supérieure, à celle des images TDM. Toutefois, les rapports Signal/Bruit ne sont pas assez élevés, et les doses, bien qu’inférieures à celles en TDM, pourraient encore être diminuées. Un des objectifs de ce projet est donc d’optimiser la qualité des images tout en cherchant à réduire davantage la dose de radiation ionisante. Pour atteindre ce double objectif, nous proposons de mettre en œuvre de nouveaux algorithmes de reconstruction/rétroprojection, notamment en faisant appel à des méthodes de reconstruction itératives. Le rehaussement qualitatif obtenu, associé à une prise en charge des propriétés spectrales du processus d’acquisition, devrait nous permettre d’accéder, pour la première fois en imagerie CBCT, à une visualisation nettement améliorée des tissus mous, laissant entrevoir ainsi de très larges perspectives pour cette modalité d’imagerie très prometteuse.

Personalizing gamification strategies to improve young adult life skills training. Part 2; support worker needs analysis and design of clinical interface

Facing Dragons is a mobile health game that gives quests and challenges to young adults (17-29) to help them figure out what to do with their lives, gain an empowered sense of self and unlock their purpose in life.

One of the key research innovations in this game is the addition of a special interface for support workers and caregivers that helps them get to know the young adults they work with.
In this project we will match young adult mobile gameplay preferences with game design elements in order to teach life skills in a fun and engaging way that maximizes the motivational power of gamification. We will also be creating a useful clinical interface to assist those who help young adults face their dragons every day.
This project is an important next step in the design of a mobile life coaching game that empowers young adults through playful learning.

Assessing the effectiveness of customer management efforts on profitability in the insurance industry

To have a strategic advantage over competitors, companies have been encouraged to adopt customer-centric, value added processes and capabilities. Firms allocate resources to train their employees in the necessary skills to build and maintain healthy relationships with their customers, yet little is understood on how investments in training impacts a firm’s performance. The objective of the proposed research is to investigate (1) Which customer management training activities have a positive impact on profitability? (2) How frequently should companies offer training to their employees? and (3) Who will benefit from more (less) training activities? To answer these questions, we will develop a model to estimate growth in profitability as a function of training efforts while controlling for economic factors. This research will help understand how investments in customer management training will enhance the firm’s overall performance and competitiveness in business markets.

Modelisation et tarification des couts en assurances dommages

La modelisation des couts par assure en assurances dommages constitue la base du processus de tarification. Les couts peuvent provenir des trois couvertures d’un contrat d’assurance automobile dommages materiels au vehicule,dommages corporels subits par I’assure et dommages corporels subits par les tierces parties. Bien qu’un accidentpeut engendrer des couts pour ces trois couvertures, la modelisation actuelle de ces couts est faite separement en supposant I’independance entre les experiences des trois couvertures.

et ignore la decomposition classique des couts en assurance automobile en fonction de la frequence (nombre de sinistres) et de la seve rite (montant d’un sinistre). L’objectif principal du projet est d’ameliorer la tarification des couts pour un assure en assurance automobile en Ontario en tenant compte des recents developpements en actuarial. L’approche proposee permettra de tarifer les produits d’assurance qui refleteront davantage Ie risque inherent aux assures et seront plus equitables.