Forecasting Vehicle Maintenance Needs and Breakdowns using Predictive Maintenance

Improving road safety has a direct impact on the lives of drivers as well as the costs incurred by companies operating commercial vehicles. One important aspect of road safety is timely and effective vehicle maintenance. By forecasting vehicle maintenance needs and predicting breakdowns before they occur, valuable insights can be provided to drivers and fleet […]

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Using analytic hierarchy processes to resolve multi-criteria decision making

Many real life decision consider a multitude of criteria, one such example is in healthcare where the patient’s condition, available resources, chance of recovery, cost etc all need to be consider when administrating care. An analytic hierarchy process makes the multi-criteria decisions by first converting the problem into a set of mathematical constraints by pair-wise […]

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Ai-based musical intervention to improve emotion through a personalized speaker

Mental disorders have a significant influence on the daily activities of Canadians. Musical intervention can provide a non-invasive treatment through changing emotional state and creating positive mood. The main objective of this project is to provide a long-term solution for musical intervention through an optimized machine learning framework for an intelligent real-time emotion recognition and […]

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Establishing Travel Needs of Older Adults

Many older adults in Canada are becoming increasingly isolated from their communities. This is largely due to the fact that Canadian cities are built with cars in mind, and many older adults rely heavily on driving to get around. However, as they age and lose their ability to drive, many older adults often are unable […]

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A Study on the Effectiveness of Computer Vision Models for Addressing Environmental Problems Using UAVs and USVs

The research project, guided by Professor Stephen Smith, focuses on addressing environmental challenges related to water pollution and debris detection in the water areas, with a specific emphasis on garbage and waste detection on the water surface. The project entails a systematic literature review and analysis of various computer vision models to detect and classify […]

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Two-step personalized federated learning algorithm in reality

Machine learning attempts to model high-level abstractions in data using multiple processing layers with complex structures or non-linear transformations. Federated learning is a distributed machine learning approach that allows multiple parties to collaborate on training while preserving user data privacy. However, the data from each party is typically non-independent and identically distributed (Non-IID), which can […]

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Preparation of Quantum Machine Learning Datasets with Quantum Advantage and Challenges using State-of-the-art Classical Machine Learning

Machine Learning (ML) approaches generally consist of training an algorithm on a given dataset containing data which has to be analyzed or otherwise understood. For an ML application to be successful, careful thought must be given to ensuring that the architecture of the algorithm chosen is fit for the task at hand: some architectures are […]

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NEGF based Cryogenic MOSFET simulation including inelastic scattering

The project aims to develop a state-of-the-art numerical simulator to compute transistor’s physical behaviors at deep cryogenic temperatures. First of its kind, the simulator will incorporate physical effects critical for transistor’s operations at cryogenic temperature such as inelastic scattering, while maintaining computational efficiency and robustness. The successful outcome will provide the research community a widely […]

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Investigating Smart Wearable Systems for Workplace Wellness Management

Japan is a leading example of a nation with a rapidly ageing society and currently consists of the highest proportion of elderly adults worldwide. Among others, this has led to a series of downstream concerns, including labour shortage issues and reduced ability of working individuals to finance those who are retired. As one of the […]

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3D computer vision

Monocular depth estimation aims to infer the distance information of objects in a 2D image. It is an integral part of many computer vision tasks and has applications to autonomous driving, robotics, and virtual reality, among others. This project focuses on developing a new deep-learning-based monocular depth estimation method with high efficiency, competitive performance, and […]

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Free radical polymerization of lignin and PCL for 3D printing materials

The main goal of her study is to make sustainable polymers from lignin that can be used in three dimensional (3D) printing material production. The student will work on making 3D printing materials from polymerized lignin and polycaprolactone (PCL). At Abo Akademi, the student will use different monomers to generate composites of lignin and PCL. […]

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Carboxyalkylated and sulfoalkylated nano lignin as an emulsifier for coating application

The overall objective of this study is to generate lignin-derived sustainable emulsion systems for coating applications. The main focus of this study is on the generation of functional lignin derivatives and then the conversion of these lignin derivatives to lignin nanoparticles. Afterward, the use of lignin nanoparticles in oil-water emulsions will be studied for coating […]

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