Integrating AI with 4D Flow MRI for Advanced Cardiovascular Diagnostics

This project is dedicated to enhancing the safety and reliability of cardiovascular disease diagnosis through the innovative integration of Artificial Intelligence (AI) with 4D Flow MRI technology. By applying advanced machine learning algorithms, we aim to improve the precision and dependability of 4D Flow MRI analyses, ensuring more accurate assessments of complex heart blood flow […]

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Unveiling the Structure of Science: An Information-Theoretic Approach to Co-citation Analysis

The project “Unveiling the Structure of Science: An Information-Theoretic Approach to Co-citation Analysis” aims to advance our understanding of the interconnected landscape of scientific research by applying principles of information theory to co-citation networks. By identifying significant intellectual linkages across disciplines, countries, and institutions, this research seeks to illuminate the underlying patterns and dynamics that […]

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Computational Analysis of Main Group Complexes Containing Cyclopentadienyl-Carbene Ligands

The upcoming research internship will explore how a specific class of ligands incorporating cyclopentadienyl and carbene moieties can stabilize less common, low oxidation states of certain heavier elements like germanium, tin, antimony, and bismuth. This computational study aims to understand the unique bonding and reactivity patterns of these compounds. By simulating these reactions computationally, the […]

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Beyond Elections: what can Brazil tell us about democracy?

Representation and accountability are essential for the proper functioning of democracy. Through a close examination of Brazil since the 1990’s, this project investigates the conditions that make a country move toward stronger representation and accountability. Like many Latin American countries, Brazil was neither an institutionalized nor a representative democracy in the 1990s. Although the president […]

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The Research on the Positioning of Virtual Humans in AR Collaboration Systems

Our research expands the paradigm of 1:1 AR collaboration systems to multi-party AR collaboration systems, enabling more flexible control over the positioning of the RU. We investigate multi-party conversations involving two or more participants and one VH replacing the RU. Specifically, we vary the distance between the two LUs and the VH to examine RU’s […]

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L2M – Development of a Capillary Microfluidic Design Automation Module for Three-Electrode Electrochemical Biosensors

This project is developing an innovative tool that accelerates the design process of lab-on-a-chip devices, which are crucial for the analysis of tiny liquid samples to detect the presence of pathogens or chemical substances, a process known as biosensing. The tool employs a sophisticated algorithm that leverages data from previous designs to optimize and suggest […]

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The impact of user and virtual agent dominance in collaborative work

Our research project aims to explore two interconnected objectives: understanding the impact of dominance in the collaboration between virtual assistants and human operators, and examining how an individual’s level of dominance affects their perception of a virtual assistant’s dominance during initial interactions. To achieve these goals, we will conduct a user study where participants, interacting […]

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L2M – Revolutionizing Human Movement Analysis: A 3D Markerless, AI-Powered Approach with Mokapp

Mokapp is a revolutionary tool designed to streamline human movement analysis for healthcare providers. Our specialized motion capture (mocap) technology offers a portable, accessible solution that significantly reduces analysis time from hours to just 5-10 minutes. Using only two cameras and a web-based system, Mokapp stands out for its efficiency and convenience compared to traditional […]

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L2M – Virtual Reality Nursing Experience (VRNEX)

When newly registered nurses start their careers in hospitals, they face severe transition shock due to the huge gap between their learning from educational institutions and real-life healthcare environments. Due to insufficient resources for training these new nurses, hospitals suffer from a high new-nurse turnover rate and more frequent medical errors caused due to the […]

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L2M – Asphaltenes-Derived Carbon Dots for Friction Reduction

Water-based lubricants have emerged as substitutes for petroleum-based lubricants in various applications such as hydraulic fluids, cooling fluids for metal cutting, and stern tube bearings in ship propeller shafts. My STEM tech business proposes an asphaltenes-derived carbon dots (AsphaDots) lubricant which intends to solve the friction and wear problems in steel and allied materials, which […]

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L2M – A Modular and Low-Cost Carbon Capture Solution for Rapid Deployment

This project will support the development of a business strategy for a startup company based around the rollout of low-cost carbon dioxide capture technology. Through a series of workshops and from access to mentorship from individuals well versed in the start-up space, the intern/founder will gain crucial knowledge pertaining to the potential end users, structuring […]

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L2M- Biomass-derived solvent for sustainable bitumen recovery

The collaboration between BioOilSolv and Innovate Calgary aims to revolutionize bitumen recovery processes in the oil sands sector by developing biomass-derived solvents as a more sustainable and effective alternative to traditional methods. Through this project, an intern will undertake several key objectives to propel the commercialization of biomass-derived solvent technology. Firstly, the intern will focus […]

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