Innovative Projects Realized

Online Public Consultation in the Real Estate Development Market

Over the years, the methodology for public consultation has evolved to include public information

meetings and hearings, telephone polls and surveys, and most recently online engagement.

Increasingly, government is emphasizing evidence-based decision-making. They recognize that

existing methods are lacking in reaching a broad demographic. Internet communication technology

has made it possible to reach a broader spectrum of the public however until recently, that interaction

has been anonymous and anecdotal at best. The objective of the proposed research is to explore

the use of online public consultation technology to advance best practices within the real estate

development industry. The project aims to investigate the ways online consultation generally, and the

PlaceSpeak platform with location-based authentication in particular, can enrich public development

consultation bringing together current and traditional outreach methods.

Development of assays to detect biostasis activity in synthetic intrinsically disordered proteins

Tardigrades are among the hardiest organisms known, with some species being able to withstand high doses of radiation, desiccation, lack of nutrients, and extremes in both pressure and temperature. Humans, conversely, are extremely susceptible to such conditions. The tardigrade’s ability to readily survive for long periods in the harsh environment of space has been well documented in both scientific literature and popular sources. Tardigrade desiccation resistance is facilitated by a unique class of intrinsically disordered proteins (IDPs), which essentially pause cellular processes until environmental conditions are again favorable. This phenomenon is currently being studied in Dr. Pamela Silver’s laboratory at Harvard University, as part of a larger project, as a means of preventing organ and tissue damage during traumatic injuries and transplants. Biostatic IDPs from tardigrades and other organisms are being studied to determine the structural patterns which confer activity. Advanced computer simulations are also being completed to design new synthetic IDPs, and are being screened for their ability to induce biostasis in various cultured human cells types with minimal endogenous inflammatory responses. The proposed project will aim to assist in both the design and development of assays for candidate biostasis IDPs.

Antigen Tracking of the DPX-R9F immunotherapy using MRI – Part 2

IMV Inc. is developing injectable cancer immune therapy using the company’s DPXTM technology. DPX is a patented formulation that displays excellent tumor control and provides a long lasting and specific effect. The way by which this therapy exerts its effect is unclear but the translational team at IMV is determined to discover its mechanism of action and why their proprietary DPX technology delivers superior responses in comparison to other forms of injectable therapies. This project will aim to figure out, using preclinical models, how the DPX components are being transported within the immune system and which cells are responsible for this transport. The components will be labeled so that it can be tracked using magnetic resonance imaging (MRI) in the presence or absence of immune cells at the frontline of the immune system, like dendritic cells and macrophages. Figuring out where the components are going into the body and which cells are responsible for their transport will help decipher why DPX’s technology is so efficient. It will also help further develop IMV’s DPX and help Canadians through the development of good, efficient, cancer immune therapies.

Progressive Cybernetics Decentralized Autonomous Organization (PCDAO)

Digitization of assets is becoming a dominant form of business operations today; the Internet of Things and increased connectedness to consumers and citizens alike is creating a decentralized virtual marketplace for digital services and assets. The potential for sharing technology assets is high due to digitization (the new way of referring to digital transformation). Principles being applied in the general industry are now being adopted by civic and academic entities as a means of interacting directly with citizens, businesses and start-ups alike, fostering innovation and acceleration to market and commercialize digital assets. This opportunity is to research the potential of a Decentralized Autonomous Organizations (DAO) to facilitate crowdsourcing, pooling of objectives and resources based on shared desires across multi-disciplinary industries including civic, distance education and academic programs.

Determining the value of community based police teams

In an era where the costs of policing are constantly under scrutiny, the time has come for policing organizations to re-evaluate the services they provide. To do this, these organizations need to answer questions relating to the value these services create in the communities they serve and change the focus of the conversation from “what does this service cost?” to “what value does this service provide to key stakeholders?” In the summer of 2019, in response to pressure from the community, the Ottawa Police Service (OPS) decided to reintroduce community-oriented police (COP) teams back into three Ottawa neighborhoods. This decision gives us a unique opportunity to conduct research to determine the value COP programs create (if any) and for whom. We propose to work in partnership with the Boys and Girls Club of Ottawa and a variety of community groups and social service providers to undertake a longitudinal, multi-method case study to identify the value COP teams provide to a variety of key stakeholders.

Indirect effects of predator control: Examining predator habitat selection and competitive interactions following wolf control in northeastern Alberta

Global demand for natural resources is resulting in unprecedented landscape change. In northeastern Alberta, woodland caribou persistence is threatened by habitat loss associated with natural resource extraction, and increased predaiion by grey wolves as a result, due to their ability to capitalize upon landscape disturbance via increased movement on linear features. Wolf control via culling is a common wildlife management strategy to conserve woodland caribou. While previous research has sought to understand prey response to wolf control, indirect impacts on the ecological community have not been measured to the same extent, despite evidence to suggest that predator control has repercussions at multiple trophic levels. Using camera trap data collected discontinuously between 2011 and 2019, this project will examine the impacts ·of a government wolf control program beginning in 2016 on predator habitat selection and competitive interactions. This project will provide critical information to the partner organization on the community-wide effects of predator control in an increasingly
human-disturbed landscape, and help to inform woodland caribou recovery.

Performance Degradation and Failure Detection Methods for Optical Networks Based on Machine Learning

Large network operators have to deal with dynamic network service changes, including scheduled or unscheduled outages, while keeping efficient service levels with different requirements. Currently available restoration techniques remain limited to after the fact detection of hard or catastrophic failures when the service has already been impacted. Machine learning technologies have been explored as a potential solution to enable proactive fault management and performance prediction. This project will develop innovative machine learning methods in the context of optical networks, which will allow accurate prediction ahead of time for proactive fault management and maintenance, before actual degradation and failure occur.

Non-invasive automated assessment of tonic attention (vigilance) of commercial airline pilots during simulated flights

With the goal of increasing the safety of civilian air flight, the detection of a decrease in pilot attention is becoming an important need in civilian aeronautics. Multiple models used for the detection of hypovigilant states have been developed over the years in experimental conditions, but barriers still exist limiting current use. First, some of these models require the execution of behavioral tasks that can disrupt pilot workflow. .Second, other models relying on the use of physiological monitoring devices are still too cumbersome. The main objective of this project is to review all of the scientific publications about hypovigilance detection models so that future functional models can integrate the best evidence available. Although the main domain of application is aeronautics, other domains would also benefit from such technologies such as ground transportation and medical care.

Vibration-Based Health Monitoring of Critical Airport Facilities

The basic objective of the proposed research is to undertake diagnostic assessment of

critical airport systems, specifically the baggage handling system, passenger boarding

tunnels and pedestrian bridges using vibration measurements. The underlying premise is that

the overall health of these systems is manifested in their vibration measurements. By

undertaking such an interrogation, it will be possible to predict their failure ahead of time and

to plan replacements without unplanned outages. The industry partner, GTAA will benefit by

reducing their overall maintenance costs and stay competitive with airports such Chicago and

New York, using such a system. More importantly, they can optimize their inspection on

these systems so that there are no sudden and costly breakdowns.

Cosmic radiation In-flight Measurement and real-time analysis for Electronic Systems and passenger protection (CIMES) – Part 2

The main objective of this internship is to build a software tool, which will be incorporated on board a test aircraft, in order to indicate to the pilot areas where the cosmic radiation intensity and energy could affect the immunity of electronic modules installed onboard aircraft.
For analysis and design purposes, the measurement system inside the airplane is modeled in the cosmic radiations’ environment by using a specialized software, to determinate the theoretical light pulses number for all

Quantum dots labelling technology to assess polysaccharides disposition profile and innate immune function

In the past decade, sales of several natural health products (NHPs), including Canadian grown American ginseng, have seen an unprecedented spike due to their wide health benefits. One of the key bioactive constituents in ginseng is polysaccharide(s) (PS) known to significantly boost the immune system by modulating a host of immune cells. Unfortunately, there is no specific analytical tools at present to elucidate their disposition and pharmacology. We have been successful in synthesizing and characterizing Ginseng-PS conjugated to carbon dot. This proposal will focus on extending our study to the Ginseng-PS, lipopolysaccharides (LPS), and non-pathogenic bacteria with silicon quantum (Si QDs). The labelled G-PS will provide more understanding of their disposition in biological system as well as their interaction with therapeutic targets. This will enable the refinement of design of novel polysaccharide-based immunomodulation nutraceuticals, such as PS nanoparticles, and provide scientific and clinically relevant evidence to support their health claims.

Advanced Applied Probabilistic Programming

Autonomous cars are one example of a compelling next-generation artificial intelligence technology. In order to safely navigate through the world, cars must plan long-range routes and short-range paths, perceive the world around them, and act according to a safety-first policy that takes into account the intent of agents in their surrounding world. While not strictly AI-complete, the challenge of autonomous driving in urban and unstructured environments is substantial, as-yet unsolved, and of paramount economic importance. This research is relating to the most significant challenges remaining to be solved before it becomes possible to make unrestricted autonomous cars a reality. In particular, this research will focus on theory of mind, inference of driver, pedestrian, and cyclist intent, and robust, computationally efficient solutions to these and other inference problems. The aim of this research will be to build the probabilistic programming software systems and tools that will make it possible to efficiently build models that predict what the various agents near and on the roadway will do up to two to three seconds into the future, or at least long enough to allow for contingencies that ensure that the controlled vehicle behaves safely.