PREDICT: Parallel Resources for Early Detection of Immediate Causes of Tsunamis

With this project we propose a re-thinking of ICT infrastructure to include a framework that exploits commodity many-core systems to evaluate models. The framework permits comparison, evaluation and improvement of competing and complementary models and appear to hold promise. Our proposal focuses on the computationally intensive tasks associated with near-field Tsunami detection, leveraging parallelism to […]

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Assessing how Differences in Implementation Technologies and Platforms Affect Application-level Mobile Device Quality of Experience Measures

With the growth of mobile device platforms such as smartphones and tablets, users now primarily experience the wireless networks they uses, whether cellular or WiFi based, through the context of the apps that they use. Hence, a heavy 8kype user may perceive a given network to be of substantially different quality than would be perceived […]

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Interactive Image Segmentation for the DiyoramaMobile Engine

Hololabs Studio Inc. is developing a mobile platform called Diyorama, which enables users to arrange images into interactive 3-~ scenes with an aesthetic similar to paper craft and collage art. Users can include images from their photo libraries, social networks, or image search results in order to create customized playable scenes from existing content. The […]

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Understanding Empirical Risk Minimization via Information Theory

Deep neural network (DNN) is a class of machine learning algorithms which is inspired by biological neural networks. Learning with deep neural networks has enjoyed huge empirical success in recent years across a wide variety of tasks. Lately many researchers in machine learning society have become interested in the generalization mystery: why do overparameterized DNN […]

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Using machine learning to identify and contextualize residential rainwater downspouts and guide stormwater outreach programming

Municipalities are seeking ways to reduce the effects of uncontrolled rainwater and one of the primary contributors to the problem is residential downspouts. Downspout disconnections and redirections are low-cost ways to reduce the overall imperviousness of urban and suburban landscapes and ameliorate stormwater issues. This project will use machine learning to analyze Google street view […]

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A Scalable Solution for Sensing and Sorting Orein the Mineral Mining Process

This project intends to research the building of scalable, low-cost and robust alternatives andimprovements to existing systems for mineral sensing and sorting in order to achieve greaterproductivity and efficiency by means of improving speed and accuracy in the process of miningminerals from low grade rocks. The project will combine developments in embedded and streamingsystems, parallel […]

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RVezy AI & Analytics Research Project

RVezy is a technology company that brings explorers and RV Owners together: Think Airbnb for RV’s. This project will involve two main components, both driven by AI and analytic solutions: 1) Search Optimization: Improving RVezy’s search algorithm to better tailor their customer experiences. 2) Marketing Spend Ratio: Integrating shallow machine learning models to improve return-on-marketing-investment. […]

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Measurement and Modeling of Pandemic Effects on Door-to-Door Bottle Recycling

SkipTheDepot is a door-to-door bottle collection service based in Calgary which allows users in Calgary and Edmonton areas to request bottle recycling pickups, and the COVID 19 pandemic has caused demand for these services to increase. In order to meet rising demand, it is important to develop a clear understanding of how the service is […]

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Scalability of an Autonomous Trading Platform

This project will build on the work previously completed in the MITACS project done by Dr. Michael Bauer, Omid Mola and Cyborg Trading Systems (CTS) – Integration of an Autonomous Trading Platform. The previous project formed the foundation of developing an autonomic system in an algorithmic trading application. The initial project was successful in determining […]

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Design Science et PME : modernisation des systèmes d’information de Projet Point Final

Le projet en question est de type Design Science. Il éclot dans un contexte d’expansion où le système d’information (SI) de l’entreprise expose ses limites. Plus spécifiquement, son caractère manuscrit lui proscrit coordination et automatisation : coordination car l’information demeure figée sur feuille et donc inaccessible à des parties éloignées; automatisation, dans la mesure où […]

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Random bin picking with industrial robot

Materials with different sizes, shapes, or materials come into the process every day, they need to be sorted, placed, and usually fed into a machine for processing. Traditionally, this task is very hard to be automated because of the non-fixed position of the part and frequent part changes. For this random bin picking project, we […]

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