Exploring the drivers of innovation diffusion for virus-resistant grape vines

Increasing exports of value-added agricultural products is a priority set out by Canada’s Advisory Council on Economic Growth. Upper Canada Growers has developed novel technology to produce grape vines with improved disease resistance to red blotch, a virus that has been significantly reducing grape quality and harvest globally, and this project will investigate how this […]

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Test Automation with TTCN-3

Development of an Avionics system test methodology, based on the Test and Test Control Notation (TTCN-3). This will include (1) a gap analysis between TTCN-3 and current avionics test languages and environments and (2) a large scale case study. Of particular interest, will be the ability to model and verify both continuous control and discrete […]

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Low-Code Software Development 2.0

In this project, we will explore the new ways to design and implement a Low-Code Software Development platform that is easy to use, requires minimum software knowledge, is business logic oriented, and robust to dependency change. Specifically, we provide functional templates with detailed configuration flexibility to cover the high frequency requirements from the expected business […]

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Analytical Characterization of JZP-341 (Higher Order Structure)

York University and Jazz Pharmaceuticals are undertaking a project to accelerate development of their Leukemia drug candidate. The project will take advantage of unique technologies developed at York by Drs. Wilson and Krylov, Millisecond Hydrogen Deuterium eXchange (msHDX) mass spectrometry and Kinetic Capillary Electrophoresis (KCE), to provide a high-detail picture of Jazz Pharmaceutical’s candidate, including […]

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Certified Defense Framework against Patch Attacks on Images

Adversarial perturbation of all the image pixels is computationally intensive and may not be realized in practice. In contrast, an adversarial patch attack where an adversary can choose to perturb a specific subset of pixels in an image, is more practical in fooling a trained image classifier or hiding a person from an object-detection model. […]

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Temporary Migrant Farmworkers in Essex County: Building Community Inclusion in a Post-COVID-19 Context

Temporary migrant farm workers make essential contributions to our national food supplies as evidenced during COVID-19. Their exclusion from rights to labour mobility, family unity and the absence of systemic supports, however, undermines workers’ wellbeing and belonging, and the inclusions to which migrant workers are entitled. There is less attention to how communities support their […]

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Using AI to Increase Diversity in the Talent Pool

Canada is having a youth unemployment crisis that has only worsened post-COVID. At the same time, an untapped pool of young, diverse talent exists to fill entry-level positions. However, difficulties arise when trying to match youth with employers. In particular, youth have indicated that job postings can be unfamiliar or intimidating and ask for unrealistic […]

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Business-Oriented User Persona Construction and Preference Prediction: A Big Data-Based Machine Learning Approach

In this project, a group of scholars in computer science and business proposes using state-of-the-art machine learning methods for secondary-data-based persona construction and preference prediction. Specifically, the researchers will use recent data dimension reduction methods to process the raw data, use new machine learning models to achieve better learning results, and use self-supervised technology and […]

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