Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Development of a Space-time Finite Element Formulation for fast AC Loss Calculation in High Temperature Superconductors

The intern will develop a new space-time finite element formulation to solve steady state problems involving high temperature superconductors in order to evaluate rapidly the losses in a given application. This space-time formulation will also be coupled to a mesh adaption program used to refine the solution only where it is really necessary. This formulation is expected to be advantageous over current formulation since it will avoid using very fine spatial and geometric discretization in the entire simulated domain. If this project completes successfully, it will provide a new and powerful tool to optimize the design of high temperature superconducting wires and applications. Such optimization tools are the key to economically-competitive applications, such as power transformers and generators.

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Faculty Supervisor:

Dr. Frédéric Sirois

Student:

Francesco Grilli

Partner:

Los Alamos National Laboratory

Discipline:

Engineering

Sector:

Manufacturing

University:

Polytechnique Montréal

Program:

Accelerate

Computational/Experimental Protocol for Development of a Therapeutic Agent for Treatment of Tuberculosis

It is estimated that one third of the world’s population is infected by Mycobacterium tuberculosis. With the emergence of drug resistant tuberculosis, the World Health Organization has declared tuberculosis a global health emergency. UDP-galactopyranose mutase, an enzyme essential for tuberculosis bacterial growth and infection, will be studied by a protocol which combines advanced NMR and computational modeling techniques. By combining computational models with experimental data from NMR, critical binding interactions of the natural substrates and inhibitors to UDP-galactopyranose mutase can be observed. The information from the binding interactions will be used in the design of novel drugs effective against drug resistant tuberculosis strains. Advancement of the computational/experimental protocol will allow more rapid assessment of drug targets and interactions by research groups around the world.

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Faculty Supervisor:

Dr. B. Mario Pinto

Student:

Yue Yuan and Dustin Bleile

Partner:

Zymeworks Inc.

Discipline:

Chemistry

Sector:

Life sciences

University:

Simon Fraser University

Program:

Accelerate

Consumer Activity Segmentation in Marketing

This project will require the intern to use statistical techniques such as a K-means to cluster customers into different groups based upon their relationship to Kraft and how those relationships drive business value for Kraft. The intern will also use logistical progression and decision trees to create models that will be able to predict the business value of future customers.

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Faculty Supervisor:

Dr. Mu Zhu

Student:

Stefan Pintilie

Partner:

Digital Cement

Discipline:

Statistics / Actuarial sciences

Sector:

Finance, insurance and business

University:

University of Waterloo

Program:

Accelerate

Component-based Detection for 3D Objects

This project in collaboration with Lockheed Martin Canada and University Laval is on aerial surveillance. The goal is to develop and implement algorithms for the automatic object detection using electro-optics data to be used in conjunction with standard operation with the aim of enhancing the speed and accuracy of the regular detection of objects from aerial images. The challenge is to recognize 3D objects in real-world 2D imagery. The objectives of this project are 1) to develop both innovative and efficient methods and theories for the detection of 3D object and 2) to acquire and implement the aerial detection of 3D objects with state-of-the-art techniques.

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Faculty Supervisor:

Dr. Yunlong Sheng

Student:

Bora Ung

Partner:

Lockheed Martin Canada

Discipline:

Engineering

Sector:

Aerospace and defense

University:

Université Laval

Program:

Accelerate

Basic Design Considerations for Implanted and Embedded Antennas

Nokia is interested in research of both in-body (implanted) antennas and antennas in close proximity to the human body. Nokia is particularly interested in making positive use of the electromagnetic coupling between the antenna and the human body, know as positive body effects. The internship research will focus on fundamental antennas, electric and magnetic dipoles in lossy matter, with a goal to show, quantitatively, that the magnetic dipole is better suited to implanted applications.

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Faculty Supervisor:

Dr. Rodney Vaughan

Student:

Andrew Lea

Partner:

Nokia Research Center

Discipline:

Engineering

Sector:

Information and communications technologies

University:

Simon Fraser University

Program:

Accelerate

Antibody Modeling Using a Combined Computational/Experimental Protocol

The proposed project combines structural biochemistry with high-performance molecular simulations to generate valuable insight into the development of the next generation of ligands that can be used to develop vaccines. The collaboration between the academic and industry partner creates an ideal opportunity to combine theoretical and experimental approaches for better lead generation and development of scientific knowledge. Zymeworks will have an opportunity to validate its ZymeCAD™ platform for pharmaceutical applications.

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Faculty Supervisor:

Dr. B. Mario Pinto

Student:

Monica Szczepina

Partner:

Zymeworks Inc.

Discipline:

Chemistry

Sector:

Life sciences

University:

Simon Fraser University

Program:

Accelerate

Analysis of Katzie Archaeological Lithic Collections

This project will involve the analysis of a collection of stone artifacts retrieved from a recent archaeological excavation conducted by the Katzie Development Corporation and Katzie First Nations members at a very signification archaeological site located in the Fraser Valley of British Columbia. The artifacts will be classified according to their technological and functional characteristics and the results of this data gathering process will be used to interpret the nature of occupation and social structure at the archaeological site. This information will also be compared to collections from other sites in the region with a view towards identifying patterns and timing of the emergence of complex societies of the Northwest Coast. This project will be complete in cooperation with the Katzie First Nation within whose traditional territorial the site is located. In addition to providing valuable data for dissemination within the wider archaeological community, the research will provide details about Katzie ancestors’ lifeways, about which the First Nation is very interested in learning.

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Faculty Supervisor:

Dr. David Pokotylo

Student:

Emily Ann Wilkerson

Partner:

Katzie Development Corporation

Discipline:

Anthropology

Sector:

University:

University of British Columbia

Program:

Accelerate

Real-time Supervision of Electric Arc Duration in a High Voltage Circuit Breaker Based on the Analysis of Electromagnetic Emissions

The detection of a power circuit breaker's operation through measuring electromagnetic emissions produced by the arc in the interruptor tube is a promising method for ensuring the remote supervision of these devices and for identifying operation faults before they lead to an explosion. Project researchers will develop an algorithm to determine computationally the position of the faulty interruptor tube. This algorithm will use as inputs a minimal number of measure points and will have to deduce the position based on the signals' arrival times at each of the measure points. Experimental data will allow researchers to determine the statistical variance of the phenomenon from one measure to the other. This random component will also need to be part of the model, as there is always a certain amount of uncertainty with these measures.

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Faculty Supervisor:

Dr. Frédéric Sirois

Student:

Sébastien Poirier

Partner:

IREQ

Discipline:

Engineering

Sector:

Manufacturing

University:

Polytechnique Montréal

Program:

Accelerate

Multi-class and Multicriteria Classification Models

This project will develop classification models in a multi-class and multicriteria context. These models will be based in part on multicriteria decision-making support techniques and statistical learning techniques. The first stage of the project will develop and validate performance measures of the multiclass classifiers. The second stage will develop classification models based on these performance measures of multi-class classifiers as objective functions of the mathematical model. Solving this type of problem will require developing heuristics. An application is planned to empirically validate these theoretical results.

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Faculty Supervisor:

Dr. Pascal Lang

Student:

Loubna Benabbou

Partner:

LTI Inc.

Discipline:

Operations research

Sector:

University:

Université Laval

Program:

Accelerate

A New Decision-Support Tool for the Treatment of Patients Suffering from a Torn Anterior Cruciate Ligament

After a ligament injury to the knee, clinicians must decide on an optimal treatment for their patient. In most cases, they prescribe either conservative therapies (physiotherapy with or without orthotics) or surgery (which allows doctors to use two different grafts). The Centre du genou Emovi proposes a biomechanical assessment to better understand the functional status of the knee and to determine more accurately the appropriate treatment option. The purpose of this proposed project is to develop a decision-support system that reduces uncertainty regarding the optimal treatment option for patients suffering from a ligament injury. To this end, we plan to develop hybrid methods based on the use of neuron networks and fuzzy logic. Ultimately, this will allow doctors to identify the optimal treatment option for their patients based on biomechanical tests.

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Faculty Supervisor:

Dr. Jacques de Guise

Student:

Alexandre Fuentes

Partner:

Emovi Inc.

Discipline:

Medicine

Sector:

Life sciences

University:

École de technologie supérieure

Program:

Accelerate

The Health and Safety of Children Living in Marijuana Grow-Operations

Marijuana grow-operations are an increasing phenomenon in BC and of concern are the children who are found to be living in these dangerous and toxic environments. This study, in partnership with the BC Mental Health and Addictions Research Network and the BC Child and Youth Health Research Network as well as the BC Ministry of Children and Family Development, will build upon the intern’s extensive experience in the field of child protection and her decade-long commitment to working with these children to ensure their safety from the hazards that indoor marijuana grow-operations present. Using secondary-source data, this project will examine the health and safety of the children found living in marijuana grow-operations, the outcomes for these children and parents and the role that child welfare professionals have in this evolving problem. A policy analysis and examination of the alternate approaches considered by other jurisdictions to address the problem will round out the final report.

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Faculty Supervisor:

Dr. Richard Sullivan

Student:

Janet Douglas

Partner:

BC Ministry of Children and Family Development

Discipline:

Social work

Sector:

University:

University of British Columbia

Program:

Accelerate

Semi-Automatic Video Motion Capture: Lifting 2D Estimates to 3D

Motion Capture (mocap) is a very powerful technology that allows one to digitize natural motion and use it in many areas. Currently, mocap is expensive and intrusive. The core of this project is to develop a pipeline for semi-automatic extraction of 3D motion data from ordinary video sequences. Besides being able to avoid many of the expensive and time consuming aspects of traditional motion capture, the intern will be able to extract motion data in a non-intrusive fashion from readily obtainable video data. Further, he will be able to reach back to archival footage and capture motion of artists, athletes, etc. who have either retired or passed away.

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Faculty Supervisor:

Dr. Greg Mori

Student:

Muntaseer Salahuddin

Partner:

Koolhaus Games

Discipline:

Computer science

Sector:

Digital media

University:

Simon Fraser University

Program:

Accelerate

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