Innovations Realized

Machine Learning for Cancer Treatment Plan Benchmarking

Oncology specialists are few in numbers and cannot be present within every hospital or clinic providing their guidance and support. There are institutions in this world with oncology experts that can provide the best possible care and the knowledge of these experts is stored in medical case files within the hospital. With the power of machine learning and the internet, an organization without any experts can compare their cancer treatment plans to the top performing institutions in the world and receive constructive feedback on where their plan needs improvement. Bridge7 AI is developing a platform that allows clinicians around the world to compare and improve their plans with the help of experts in all medical fields.

A Wide Bandgap Based Step-up Power Converter With Enhanced Self-Reconfigurability for Medium Voltage Renewable Power Network

Wind and solar photovoltaic energy are the fastest growing sources of electricity in Canada, targeting to reach 10% of Canada’s total generation by 2040. Aligned with Canada’s energy transition, this research aims at developing a novel, highly efficient, compact, and reliable power electronics interfaces for high power renewable energy resources. The use of power electronics converters is an attractive solution to significantly reduce the weight and size of the step-up voltage conversion unit in today’s high power renewable energy systems. However, the existing converters fail to maintain a stable grid voltage efficiently against a wide range of solar irradiation level or wind speed. To address this issue, a high frequency converter with four modes of operations is proposed that employs newly available high voltage wide bandgap (WBG) transistors. The structure of the proposed converter can be changed according to the atmospheric conditions by using a single switch. Hence, high efficiency for a wide range of solar irradiation level or wind speed can be obtained.

Development of ballistic/knife resistant composite panels for personal protective equipment (PPE)

In the wake of recent school shootings in U.S. and increasing gun crimes in Canada, parents consider taking additional measures to protect themselves and children safe. We aimed at the development/manufacture of affordable and flexible bullet/knife resistant backpacks for civilians. The backpacks could be used as a shield against bullets/knife to save life. Current available products are expensive and not affordable for everyone. Additionally, they are not flexible/comfortable for everyday use and lack protection against knife attacks. Another potential product development for us will be the design and manufacture of ballistic suits and protective garments for civilians (especially those who travel to dangerous places) which provide reliable resistance against a multitude of threats (including knife attacks), while enhancing the flexibility and lightness for comfort and mobility of the wearer over current solutions. The available protective products in the market cost thousands of dollars lack protection against knife attacks. We invented a novel technology to make lightweight and flexible composite panels and they have successfully passed preliminary ballistic/knife tests according to standard protocols. The objective of this project is to gain a competitive edge in personal protective market and bring affordable and high-quality protective backpacks and clothing into Canadian/U.S. markets.

Using Social Media to Address Misinformation about HPV and Influenza Vaccines: An Intervention on Facebook

Vaccination is a widely accepted public health intervention, yet public confidence in vaccines is affected by misinformation about vaccine safety shared mainly on Facebook. This project aims to increase availability of credible information about HPV vaccines and influenza vaccines on Facebook. It includessix phases: 1) identify the most relevant approaches for marketing campaigns; 2) conduct pre-campaign surveys with parents and health professionals; 3) prepare advertisements to address misinformation; 4) publish advertisements on Facebook; 5) conduct post-campaign surveys to assess the success of the campaigns; 6) assess the relevance of the campaign strategies for long-term outcomes. This study focuses on the phase 2. We will conduct two pre-campaign surveys: one with parents to gather their knowledge and attitudes regarding HPV vaccines and vaccination, and another one with health professionals to gather their knowledge and attitudes regarding influenza vaccines and vaccination. This study will help prepare advertisements addressing misinformation on Facebook.

Towards quantum?encoded optical communications over existing fiber networks

Two fundamental pillars of communications/communications networks are trust and truth; in particular, we must ensure that the message (or data) that a sender wishes to transmit does indeed reach the intended receiver without being altered or eavesdropped by an unwanted party. This project focuses on demonstrating one concept of the quantum internet. The quantum internet is not based on quantum communications per se, but rather considers exploiting quantum principles for encoding and decoding data transmitted over existing fiber networks as a means for obtaining secure transmission. Quantum encoding is thus used as a means of implementing optical steganography for hiding the transmitted data. If successful, the proof?of?principle demonstrations will provide a pathway for developing a quantum internet, which will provide secure data transmission in the telecommunication infrastructures that form the backbone of smart cities, industries, and economies.

Artificial Intelligence in Mass Transit

Transportation systems are evolving towards intelligent transportation systems and ISR Transit is a leading provider of these systems providing solutions in fleet management. In these systems, one of the enabling technologies is wireless sensor networks in which sensors are used to obtain information about the fleets. For example, sensors are deployed on motor, brake modules, doors, emergency buttons and passenger stop request. The information captured by these sensors is transmitted to a central controller to optimize productivity by tracking, monitoring, and managing mass transit elements and static operational data such as vehicle numbers, drivers, routes, schedules, timetables, and so on.

One of the main challenges in these systems is that since sensors have limited power resources, they cannot perform monitoring tasks over a long period of time. To address this issue, the energy consumption at sensors should be reduced which can be achieved by minimizing the number of data transmissions. More specifically, As sensory observations are highly correlated in time and space domain, some of the collected readings might be redundant. The objective of this project is to propose data reduction schemes that while they minimize the energy consumption of sensors, the quality of data is preserved.

Multi-SNP prediction model for lung function decline

Chronic obstructive pulmonary disease (COPD) is a 3rd leading cause of death (1) which decreases lung function due to irreversible airway obstruction. The main indicator of the progression of COPD is a rate of the forced expiratory volume of 1 second (FEV1) decline. The intern will build the prediction model for the slope of FEV1 decline and find the genetic variants that affect these FEV1 changes. Some variable selection machine learning algorithms will be applied to screen important genetic variants and the performance of prediction on FEV1 change will be compared. The multi-SNP prediction model can be used to classify individuals who are expected to have a rapid decline of FEV1 based on their genetic information. These pre-screened patients can be targeted for frequent medical examinations.

Grid-Forming Techniques for Converter-Dominated Power Systems

Modern electric power systems are moving rapidly towards large-scale adoption of renewable energy resources. While this is immensely beneficial for sustainability and the environmental impact of energy systems, it challenges the ways we have developed to operate our continent-wide power systems. In particular we will face large frequency swings that come about as we replace conventional generators with renewable resources. This research aims to study, devise, and assess new methods for the operation of modern, renewable-intensive power systems using a host of mathematical, computer simulation, and experimental approaches. The outcomes of this research will enable us to continue to develop renewable energy resources without hampering the security and operability of our strategic power systems.

Hardware and Software Integration for Automated Drone Surveillance

Unmanned Arial Surveillance is rapidly gaining acceptance for various applications, such as monitoring of long power transmission lines, pipelines and mass transit systems that extend for hundreds of kilometers. Unmanned Aerial Vehicles (UAVs) such as drones provide the flexibility to reduce costs. In the case of natural disaster occurrence such as earthquake, flood or hurricane, drones can quickly fly over to high risk areas where human access would be impossible or dangerous and provide information for rescue operations, etc. In this project, the goal is to develop an automated drone for surveillance purposes that can provide real-time monitoring for the target application. Hardware and software provided by AirMarket will be integrated in this project. The solution will be used to generate a framework for the next stage drone technology that can make drones fly beyond visual line of sight.

AI in Ophthalmology triage automation

There are currently 18 retina specialists in the province of Alberta, approximately half in Calgary and half in Edmonton. Retinal diseases are common. For example, approximately 6.5 percent of people age 40 and older have some degree of macular degeneration. Diabetes retinopathy affects approximately 500,000 Canadians. Many retinal conditions are treatable when detected early, however retinal specialists are concentrated in large urban centres. There are 700+ optometrists across the province today capable of taking and transmitting retinal images for consultation with a retinal specialist. Consultations have significant wait times and the current consultation processes are suboptimal, in terms of ease of triage and prioritization of patients.

Calgary Retina Consultants (CRC) is the largest retina practice in Alberta and among the most respected in Canada. CRC has established a platform to receive retinal images directly from optometrists, as part of the referral process. CRC has accumulated 6000+ low-resolution 2D images from historical referrals. CRC would like to develop a process to automate identification of the diagnosis and severity from images in referrals sent from optometrists, in order to accelerate triage and workflows, and to decrease wait times for patients who would benefit from treatment.

Graduate Research Assistant for the TRANSFORM Project

The proposed internship will take place in the TRANSFORM Research Hub located at the University of Waterloo in Ontario, Canada. The TRANSFORM Project comprises a global network of researchers committed to building the capacity of small and medium-sized enterprises (SMEs) in adopting truly sustainable business practices. The primary objective of this internship will be to support the development of a comprehensive database for the first phase of the TRANSFORM Project. During this phase, each research hub is expected to contribute to the database through the completion of 10-15 in-depth case studies of SMEs that have already implemented significant sustainable business practices. This internship role will contribute to the completion of 4-5 case studies through both desktop research and interviews with personnel in identified SMEs. This work will contribute directly to the future phases of the TRANSFORM Project, which include the creation of sustainability tool-kits and the development of government policy recommendations.

Casting and Production of HT9 for Advanced Reactor Fuel Cladding

In recent years there has been renewed interest in nuclear power for the purposes of combating climate change. ARC Nuclear’s ARC-100 reactor design requires extensive research and development to deploy a prototype. Significant effort is needed to develop the materials to be used in the reactor’s core. HT9 is a specialty steel alloy which has shown some promising results in the past and therefore has been selected for use in the ARC-100. The main objective of this project is to manufacture a batch of HT9 and test its properties, to ensure that it can withstand the environment of a nuclear reactor core. This knowledge will allow ARC Nuclear to make an informed choice: whether they should use HT9 and begin its commercial production; or, pursue different materials instead.