The digital e-commerce logistics and supply chains management using block chain technologies

E-commerce has become one major marketing channel for many firms in Canada and world-wide and has increased dramatically in recent years. As firms migrate from traditional physical retail channels to combined physical and virtual channels, the shift brings new significant challenges to supply chain and logistics management. Blockchain is able to maintain authoritative records in […]

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Machine learning in the operating room: focus, performance, and the medical record

This proposed study will significantly enhance our current understanding of how specific intra-operative factors can impact patient outcomes. Our proposed work will provide a proof of concept that machine learning can objectively predict a specific, high-impact post-operative complication, allowing us to move forward with scaling this work to a wide variety of surgical settings. Moreover, […]

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Multi-institute domain adaptation by adversarial constrained medical time series representation learning

Hospitals strive to perform cutting edge medical treatment, treat all patients fairly, and reduce operating costs, while also enabling caregivers to spend more time interacting with patients. Artificial intelligence and machine learning promise these things. However, medical data provides unique challenges for machine learning. Currently, if a hospital wants to include an algorithm for automated […]

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Predicting Treatment Sensitivity in Hypotensive Patients

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 […]

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Application of Machine Learning to Vision-Based Pose Data for Exercise Classification

The research will be using visual information from the phone’s camera as well as demographic information from participants and implement various machine learning algorithms such as random forests, support vector machines, etc. to provide feedback regarding different exercises to the participant. Specifically, the algorithms will classify the exercise types. Furthermore, these algorithms will be optimized […]

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Development, optimization and production of fiber-based strain sensors for aerospace, automotive and health

The project will employ three undergraduate coop students and one post-doctoral fellow to work with the MesoMat team to improve the sensing capabilities of the fiber technology that has been developed at MesoMat and develop robust production methods. MesoMat has developed a fiber-based sensor manufactured from plastics and nanoparticles. These materials change their resistance when […]

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A Survey on Application of Visualization and AI Algorithm-Driven Technology for Healthcare

Healthcare facilities collect and produce vast amounts of clinical-relevant data. Various AI-related methods (like computer-aided detection for mammography and the learning and visualization of clinical pathways) are applied to healthcare these days, and visualization techniques are also used to support clinicians due to the complexities of clinical data. This self-contained survey focuses on the assessment […]

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Assessing and Identifying Clinical Checklists 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 […]

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Reducing the carbon footprint at Hydro One

The purpose of the research project is to develop options for the reduction of the carbon footprint at Hydro One Networks Inc. (HONI).The research will focus on helping HONI meet a reduction goal of half of current emission levels over the next decade. The company has taken preliminary steps to assess and plan for reduction […]

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Evaluating Gradients of Natural and Induced Stress on Fish Blood Parameters; Developing more accurate results from Point-of-Care Devices

The point-of-care i-STAT and VETSCAN units are easily portable blood-based assessment tools that can produce relevant blood parameters within minutes with only 2-3 drops of blood. The objective of this study is to examine both natural and investigator-applied stress gradients in fishes and compare blood chemistry of fishes from a range of environments (e.g., low […]

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Identifying Questions for Game-Based Learning through Deep Learning

Game-based learning tools often make use of questions to measure and encourage learning, but generating questions can be challenging, especially at the scale that companies like Axonify are required to do. In this project, the intern will design, implement, and evaluate a system that can apply machine-learning on a corpus of text (e.g., a textbook) […]

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