Innovations Realized

Remediating the AIDS Archive: Networks of AIDS Video Activism

From its particular focus on HIV/AIDS, Remediating the AIDS Archive looks to historical methods of activist information-sharing through filmmaking and film festivals. This project is not simply historical in nature, however. It also interrogates the ways in which the history of HIV/AIDS is remembered through LGBT2Q+-based cultural representation, the ways in which the HIV/AIDS crisis persists today, and the ways in which media activism continues to address the crisis. To do this, the project uses archival research about the history of four Canadian LGBT2Q+ film festivals. In partnership with Reelout Arts Festival Inc. in particular, the research will result in public-facing projects such as a short film program on the topic of HIV/AIDS at their annual film festival and an online interactive exhibition.

Novel sensing and actuating technology for gaseous fuel systems

The participants listed below confirm that the information presented accurately reflects their intention to apply to the Mitacs Accelerate program. The participants have also agreed to set in place an internship based upon the attached proposal. The participants acknowledge that they have read, understood and agreed to abide by and uphold the Project Responsibilities applicable to each of them, available for reference at https://www.mitacs.ca/en/programs/accelerate/project-responsibilities which include and are not limited to the following: It is understood that the partner organization contribution shall be provided to Mitacs Inc. in Canadian dollars prior to commencement of the internship; in the event that the sponsor organization funds are at the academic institution, the academic institution shall forward these funds to Mitacs. Upon research approval and the receipt of the partner funds at Mitacs, Mitacs shall forward the funds to the Canadian academic institution as a research grant to the Canadian supervising professor, and the internship stipend/salary will be paid to the student by the academic institution from the grant. Costs associated with this proposal as outlined in the budget can only be incurred after research approval of the proposal and the receipt of the partner funds at Mitacs.

Industrial Safety Management using Control Theory and Machine Learning

Optimizing plant processes is of prime importance now more than ever. With stricter infrastructures being placed on safety, environmental effect, and corporate social responsibility, more complex systems that optimize these factors are needed. These complex systems with advanced algorithms are intended to further streamline the existing process while mitigating issues leading to a safer workplace, and environment, while creating cost savings potentially in the millions. Two of the biggest problems that are hindering this growth are process optimization and management of alarm systems. This proposal aims to incorporate a methodology that combines traditional safety analysis techniques with recent data-driven techniques such as machine learning and reinforcement learning to minimize and manage the alarm system and suggest operational set points to increase throughput while optimizing safety. The proposed research will use data from the plant process at NTWIST Inc will be used to obtain optimal policies that minimize cost associated with the unsafe operation.

Graphics Processing Unit Solutions for Power Systems Computer Aided Design: Advanced Development with the University of Winnipeg

Graphics Processing Units (GPUs) are usually employed to quickly render images on everyday computer screens, and do so quickly and efficiently for relatively little cost compared to the use of Central Processing Units (CPUs) that make up the “brain” of the computer. Modern GPUs are able to do hundreds or thousands of simultaneous calculations; rewriting conventional computer problems in the language of GPUs offers the po-tential to dramatically decrease the computation time for complex problems such as Electromagnetic Trans-mission (EMT) simulations. EMTs are used to model large electrical systems — such as city power grids — and are fundamental to power engineering software. This project will focus on how to integrate the power of GPUs into established software for EMTs, with the aim of providing power engineers around the globe with a cutting-edge tool to help design ever greater electrical systems.

Nutrient removal using a solid state glass adsorbent for treating agricultural waste, waters, and public effluents

Agricultural waste and public effluents often contain elevated levels of phosphorous and nitrogen that limit its ability to be directly repurposed as crop fertilizer or irrigation spray. Removal of soluble nutrients from waste water is difficult. Current treatment options have high investment costs and are often not well suited for smaller farm sizes common in Canada. This research intends to characterize the utility of a solid state absorbent material engineered by NPower Clean Tech Corporation that shows promise for removing anionic forms of phosphorous and nitrogen. If the product economically recovers these nutrients, then this research may directly benefit Canadian farmers, public sewer utilities, and waste generating industries by offering an additional means of controlling their waste stream profiles.

Predicting Warfarin Sensitivity after Cardiovascular Surgery

Anticoagulation with Warfarin is indicated and required for post-operative cardiovascular patients. However, it is a high-risk medication with a narrow therapeutic range where sub-optimal dosing can lead to complications and even death. While multiple risk factors have been associated to Warfarin sensitivity, the prediction of optimal Warfarin dosing strategies remains ineffective and requires trial and error and close patient monitoring. This work proposes the use of machine learning and reinforcement learning algorithms to more accurately predict Warfarin requirements in post-operative cardiovascular patients, leading to decreased hospital stay and re-admission rates and increasing cost savings at cardiovascular surgery centers globally.

Assessing and Identifying Clinical Dead-ends in Intensive Care Settings

type of treatment they will provide to patients. With technological improvements and the availability of a significant volume of data, it is increasingly difficult for care providers to properly evaluate and analyze the options available to them. The current health condition of the patient–reflected in the monitored observations which are recorded in EMR–may depend on all the relevant information from all prior observations and selected treatments, not just those most immediate (e.g., the trend of various health measures). This project is focused on developing algorithms that disentangle this history, physician decisions and the outcome (patient survival or death) to assess and identify when actions may lead to irrecoverable negative outcomes. With the identification of these suboptimal actions, correctly associated with the time they are taken, the algorithm can actively discourage doctor’s from repeating such actions when they encounter similar patient histories in the future.

Understanding Montreal festival soundscapes

Quartier des spectacles is a dense multi-cultural hub with large outdoor festivals, also housing an ever-growing residential population due to new high-rise development projects. Given the need to balance vitality with quality of life, this project focuses on expectations of residents and festivalgoers in terms of their sound environment. We implement a methodology to assess the needs of multiple stakeholders and investigate the role that sound plays in the holistic experience of urban spaces.

This project, using Quartier des spectacles as a living laboratory for original collaborative research, is essential to balance the needs of various stakeholders (event promoters, residents, workers, etc.) in order to consolidate this model, unique to Montreal. The findings will be used to create a sound management plan for recreational activities in public places in the Quartier des spectacles and beyond.

Classifying Innovation Management Forms Using Ontology Reasoning

In this project, the goal is first to design a domain ontology that models the innovation management forms semantically. At this step, the ontology contains domain-specific background knowledge, which is expressed using terminological statements. Then every completed form and the value of its fields are asserted as instances of different concepts of the ontology. Afterwards, an ontology reasoning algorithm is deployed to classify every completed form into various categories defined in the ontology. This method enables us to determine a form’s category based on its fields, even if it is not associated with a form name or number. The company will use the designed ontology and the devolved system as part of its intelligent innovation management.

Preliminary investigation into the use of biocomposites for a solar panel support truss system

Global hurricanes create a unique clean energy production opportunity – namely to build electricity resiliency into solar energy infrastructure for weather ravaged areas of the world. Terrasol is an industry leader in the design and construction of truss systems to support such solar panel systems for energy generation. In particular, the company’s flagship system is designed to be Category 5 Hurricane resilient and have a 20-year life expectancy. This MITACS research explores different bio-derived fibres and bio-resin material options for design and manufacture of the solar systems. Unlike current solar products in the hurricane belt that are often destroyed during violent storms, the new, environmentally-friendly, lightweight composite solar canopy is aimed to withstand hurricane winds and remain electrically sound after being completely submersed during storm surge floods.

Accelerate development of new technologies and applications for advanced water treatment

Global population growth, urbanization and changing climate patterns have increased the demand for potable water, wastewater reuse and value recovery from wastewater, and treatment of industrial process water. Population growth also results in increased demand for the shipping of goods by ocean freight, with the associated risk of the transport of unwanted marine life from one location to another by the discharge of ballast water. Also, the increasing sophistication of food and drug production requires a corresponding development of fluid protection technologies to prevent contamination by undesirable microbes. Consequently, there is increased demand for improved technologies that can provide sustainable treatment of water and wastewaters, protection of the water supply, and development of new fluid treatment methods. This research project will develop knowledge and technologies to allow the development of new Trojan Technologies products in these three areas. Treatment technologies to harvest energy from wastewater, treat ballast water with ultraviolet light and filtration to treat invasive species, and remove harmful bacteria from liquid foods and drug fluids, are examples of proposed outcomes of this project.

Stratifying colorectal cancer liver metastases using unsupervised clustering of quantitative imaging phenotypes

Personalized and precise treatments are the keys to improve prognosis of cancer patients and are also the main strategy of Sunnybrook Hospital. This project aims to stratify patients with colorectal cancer liver metastases (CRM) based on their disease subtype and risk using magnetic resonance imaging, which is routinely used in the diagnosis, staging and operative planning. Machine learning models that identify subtypes of CRM will be built By understanding how and why CRM differs in different groups of patients, scientists and clinicians can better understand how CRM develop and how to better match CRM patients to the targeted therapy most likely to cure their disease. This research will be vital for improving the care and treatment of CRM patients in Sunnybrook hospital.