Projets novateurs réalisés

Small Business Management Intern

This project will be focused on the advancement of DH Fencing in the market.
Primary duties:
Sales, Advertising & Promotion

• Involvement in day to day customer service with an understanding of how it relates to the overall success of the business.
• Improved promotion of DH Fencing on platforms such as Linked In, Google Business, Instagram etc.
• Involvement in the leadership of the DH Fencing Booth at the Home and Garden Show in Lethbridge for the 2021 year
• Involvement/shadowing in the development of quotes and job costing for projects with the Sales Coordinator and the Operations Director.
• Assist/shadow the Project Coordinator with the daily planning required to organize and dispatch the crews. Understanding of the costing implications of such.
• Assist in the development of an inventory management system that works effectively with existing software.
• Research costing related to materials and equipment.

Safety Program – Review and Update

• Review existing policies for accuracy
• Create new policies or programs to complete the safety program
• Prepare educational presentations for new employee on boarding
• Prepare educational presentation for existing employees
• Monitor employee safety forms for completion and adherence with rules and regulation
• Assist in investigation reporting from safety accidents, near misses and violation and determines the root cause.
• Assist in workplace inspections to determine hazards and corrections
• Oversee the completion of corrections

imYEG

The work being done will contribute to the overall ecosystem success and will help the University advance innovation. There is a real opportunity to help expand the reputation of the University and provide tremendous value to the innovators. For Brass Dome Ventures clients/projects: The efforts will help provide efficiencies and improve processes.

Funding breakdown: The internship is valued at $10,000 with $2500.00 contribution from Brass Dome Ventures and $2500.00 contribution from the University of Alberta which is matched by a $5000.00 contribution by MITACS totaling to $10,000.00

Access to Urban First Nations Wellness Services

Using Indigenous methods including storytelling and arts, the research will explore the complexities of the Indigenous population in British Columbia; narrowing the scope to specific programming in an Urban community on Vancouver Island. The research question regards whether First Nations people that live off-reserve have adequate access to health services. This is based on the health inequities for Indigenous people across Canada. By doing this work, Tillicum Lelum Aboriginal Friendship Centre can have scholarly material to disseminate in order to raise awareness about the system’s inequities for Indigenous health services as well as have a program impact assessment to share with local partners. Finally, the art-based component can assist with possible revenue for early years’ programs in the future.

Mapping Indigenous Businesses in the Agriculture/Agri-food Sector in Canada

This research project sets out to conduct a comprehensive literature review on Indigenous agriculture in Canada. We collect information about different sources of data that could be put in use to provide insight into Indigenous engagement in the Agriculture/Agri-food sector across the country. We will review the current Statistics Canada’s databases to explore data overlaying options to compile new datasets on Indigenous engagement in the Agriculture/Agri-food sector. Using these data, we will map Indigenous agribusinesses across Canada. The results will inform policy makers of what data is available and what information will need to be collected in the future.

Investigation into methods and materials to simulate neuroanatomical structures for MR Imaging applications

During their tenure at Preoperative Performance Inc. the interns will focus on the research, design, fabrication and testing of a number of novel MRI phantom assemblies to be used as calibration equipment and research tools for diffusion weighted imaging systems. The conclusions drawn from this research will contribute to interventional planning to provide better healthcare to patients suffering from several conditions including brain tumours, TBI, and neurodegenerative disorders.

Prediction of AL Amyloidosis Using Machine Learning

AL amyloidosis is a rare protein disorder that can be often fatal if it is not diagnosed and managed early. This disorder is caused by misfolding of proteins that clump together and form amyloid fibril deposits in major body organs. Diagnosis of AL amyloidosis is often not easy as the signs and symptoms can be mistaken for common diseases. The median survival rate after diagnosis is less than six months when the underlying plasma cell dyscrasia is left untreated in AL amyloidosis patients. Hence, it is paramount to develop novel diagnostic methodologies that are not based on the signs and symptoms of AL amyloidosis, but are based on the underlying molecular mechanisms of amyloidogenic clone, which can provide evidences for predisposition much long before the disease sets its course on the body. We propose to develop a machine learning technique to predict whether a light chain amino acid sequence will form proteins that misfold and produce amyloid fibrils, leading to AL amyloidosis.

Modeling Commodity Marketplace for Proof of Work Networks

Recent market instability, volatility, and Bitcion (BTC) halving event combined to create significant challenges for this sector, resulting in many hashing power producers being forced into bankruptcy. The sector has grown very rapidly and has been plagued with boom-bust cycles that have been difficult for producers to weather due to the lack of hedging tools/financial instruments at their disposal.
Pow.re Corporation offers clearinghouse-type services providing hashing power producers the ability to sell their risk to speculators. We are building an unprecedented clearing and settlement system for new financial instruments based off of the underlying commodity to proof of work networks. Concurrently, providing speculators with an ample arbitrage opportunity and the ability to hedge against unique market dynamics.
Digital asset issuance relies on proof of work consensus. Production capacity and value of goods produced of any one network participant is a multi-variable problem with continuous fluctuations.
The goal of this research is to model the market dynamics impacting these new instruments and designing levers to mitigate adverse effects.

Validating RSK as a molecular target for the treatment of cancer

Relapses in cancer usually result in the tumour becoming resistant to chemotherapy. This leaves a treatment gap that needs to be filled for these patients. One such cancer is triple negative breast cancer, this type of breast cancer is very aggressive with a high death rate. Dr. Sandra Dunn’s research group want to find new drug targets which we can then find drug inhibitors to use in cancer treatment. One such drug target is the protein RSK, this protein has been implicated in causing drug resistance and giving patients expressing this protein in their tumours a poor prognosis. We currently want to test the concept that inhibiting RSK2 in triple negative breast cancer cells will reduce growth and make previously drug resistant cells sensitive to chemotherapy again.

Integrity Monitoring of Motion Estimation and Hazard Detection Algorithms in Environmentally-Impacted Scenarios

Imagine some of the difficult driving conditions experienced by vehicle operators. In these conditions, the sun might be blindingly bright, or the snow might obfuscate what is going on around the vehicle. Surprisingly, the sensors used by autonomous vehicles to understand the environment they are in suffer from similar effects. As a field, robotics has yet to tackle integrity monitoring of the sensors used in autonomous applications. In order to transport safety critical loads, such as people or train freight, it is imperative to know when the data the autonomous vehicle receives is corrupted by environmental effects and adjust the behaviour of the autonomous vehicle accordingly. In this project, we aim to develop an algorithm that uses a sensor’s datastream and the outputs of the algorithms that rely on that sensor’s datastream to monitor the integrity of the data collected by the sensor.

Awechigewin: Developing a Virtual Approach to Community-Based Planning with Michipicoten First Nation

The proposed research project will use a combination of Participatory Action Research and Indigenous Research Methods to create an online engagement tool to gather Michipicoten First Nation (MFN) member’s perspectives on draft planning strategies and policies regarding six priority areas. Engagement is a challenge for MFN as a displaced and widely dispersed community, challenges which are heightened by the COVID-19 pandemic. Online engagement is an important tool for reaching Michipicoten citizens on- and off-reserve, particularly during the pandemic. Findings from the intern’s research will be used by MFN to support their ongoing Community Land Use Planning Process. The research could also be use by other Indigenous communities to inform their planning and engagement efforts during the pandemic and beyond.

Dimension reduction for microbiome data

Vast amounts of new data, including sequencing data from microbiome, generated by researchers and industry present challenging problems for extracting meaningful information. The main goal of this project is to develop a convenient software package to reduce the complexity of microbiome data, and more generally any kind of datasets showing similar properties. As this tool will help to efficiently study imperfect and complex datasets which are ubiquitous in particular in biology and health, we will consider other potential applications, e.g. studying health records from intensive care units. A utilization in data collected from sensors present in connected objects could also be valuable. In a nutshell, this project will help analyse data for which there is no real alternative currently, and this applies notably to some of the newest kinds of data, which have important potential in biology, health and industry.

Infrastructure Sensor-based Automated Driving: Development and Demonstration

In this proposal, we intend to answer how infrastructure sensors can be used for autonomous driving. Using infrastructure sensors make automated driving safer, more simplified, and cost effective especially for multiple autonomous vehicles operating in known environments such as large residential/commercial complexes and resorts. Infrastructure sensors replace the main onboard vehicle perception sensors with infrastructure sensors mounted on the side of the road, for example on light posts. The information sent by all the sensor nodes to the cloud is used to localize all the autonomous and non-autonomous vehicles, pedestrians, and all other objects on the road for path planning and path tracking of any number of autonomous vehicles on the road. To enable infrastructure sensor-based automated driving, we will extend our navigation, object detection/classification, and motion planning/control modules from vehicle-installed sensors to infrastructure-installed sensors.