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

An Innovative Modular Network Architecture Approach for Network Engineering

The goal of this internship project is to optimize Bell Canada’s network engineering processes to better support the complexity of the company’s network technologies. In this project, to maximize network flexibility and scalability and to minimize the costs, the intern proposes to explore an innovative modular approach for network engineering. Each module will have specific network functions and configurations with the objective of minimizing design and network management costs. It would be then possible to design custom networks for specific clients rapidly with standardized modules. Considering that each module will be tested as well as the interoperability between them, the resulting network will be more secure, reliable and manageable, and the quality of service will be improved.

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Faculty Supervisor:

Dr. Steven Chamberland

Student:

Charles Gagnon

Partner:

Bell Canada

Discipline:

Engineering

Sector:

Information and communications technologies

University:

Polytechnique Montréal

Program:

Accelerate

A Physically-based Approach to Dynamically Model Hydrological Sensitive Areas and Run-off Source Area Contributions in Snowmelt-dominated Catchments

Alberta-Pacific Forest Industries Inc. is a leading producer of quality kraft pulp. Working with the company, the intern will develop a field-based conceptualization of snowmelt run-off source area dynamics with particular attention given to process-controls, spatial hydraulic connectivity, the importance of geomorphology and the influence of forest cover removal. This “hydrogeomorphic” conceptualization will be used to develop a physically-based snowmelt run-off model followed by application to the model to predict the spatial-temporal dynamics of hydrological-sensitive areas in response to intra- and inter-annual climate forcing. Hydrological-sensitive areas are those with periodic hydrologic conditions that interfere with environmentally sound and economical executions of forest development.

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Faculty Supervisor:

Dr. Markus Weiler

Student:

Russell Smith

Partner:

Alberta-Pacific Forest Industries Inc.

Discipline:

Geography / Geology / Earth science

Sector:

Forestry

University:

University of British Columbia

Program:

Accelerate

Separation Methods for Carbon Nanotubes and Amorphous Carbon

This internship project has been initiated to support an emerging technology for hydrogen production that is being developed by Atlantic Hydrogen, a Fredericton, NB-based company conducting research into a technology to produce hydrogen from natural gas without the generation of greenhouse gases. This emerging technology produces nanoscale carbon as a mixture of carbon nanotubes, Fullerenes and amorphous carbon. This research will develop methods to separate the highly valuable nanotubes and Fullerenes from the amorphous carbon. These methods will, initially, be scaled to laboratory separations with later work aimed at the development of a commercially-viable separation technology.

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Faculty Supervisor:

Dr. Thomas Whidden

Student:

Wen Wen Niu

Partner:

Atlantic Hydrogen Inc.

Discipline:

Engineering

Sector:

Mining and quarrying

University:

University of New Brunswick

Program:

Accelerate

Rate-Distortion Optimized Streaming of Fine-Grained Scalable Video Sequences

Video streaming over the Internet is increasing in popularity. Many video objects are made available online and many users are streaming video everyday. In addition, the increasing processing power of personal computers, and the availability of high-speed Internet services, encourages users to demand more, higher-quality video content. To provide high-quality and to accommodate clients with various resources, fine-grained scalable (FGS) video coding has been proposed as part of the recent MPEG-4 and H.264 standards. While FGS encoding improves rate scalability and error resiliency, it introduces new, challenging problems that need to be addressed to make FGS usable in practical video streaming systems. In this project, we consider one of the main research problems with FSG: optimal allocation of streaming rates to multiple senders streaming in a single receiver. Streaming from multiple senders is necessary in peer-to-peer streaming environments because of the limited capacity and unreliability of peers. Multiple senders are also desired in distributed streaming systems to achieve disjoint network path streaming and hence better quality. The intern will address this problem in several steps: 1) The quality of individual frames in the sequence will be optimized; 2) The sequence will be divided into blocks of frames each with a fixed number of frames; 3) The optimization problem for each block will be formulated and solved. Solving the allocation problem at the block level is important because it will allow the research team to prioritize parts from all frames to maximize the video quality. Significant quality improvement is expected to be achieved because of the optimal allocation of bit rates to senders.

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Faculty Supervisor:

Dr. Mohamed Hefeeda

Student:

ChengHsin Hsu

Partner:

CBC Radio

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Simon Fraser University

Program:

Accelerate

Improving Throughput of the LZ77 Compression and AES Algorithms Decryption

SPIELO is a Moncton, NB-based company which designs, manufactures and distributes high-tech gaming products. The intern’s project will focus on analyzing the LZ77 compression algorithm and the AES encryption algorithm from a mathematical standpoint in order to identify any potential performance bottlenecks. This analysis will enable changes to be made to existing implementations of AES and LZ77 in order to increase their real-world performance. This research has potential impacts in the embedded systems community where mobile devices, such as cellular phones, require compression due to limited memory and encryption for privacy. While these devices require such services, their limited processing capabilities combined with their processor-intensive compression and decryption algorithms make research into improving their efficiency an important contribution to the field.

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Faculty Supervisor:

Dr. Kenneth Kent

Student:

Ryan Proudfoot

Partner:

SPIELO

Discipline:

Computer science

Sector:

Digital media

University:

University of New Brunswick

Program:

Accelerate

Fusing Structural, Functional and Diffusion Tensor MR Image for Neurological Disorders

Structural Magnetic Resonance Imaging (sMRI) provides high-quality images of soft tissue through the use external magnetic fields and electromagnetic radio-frequency pulses to excite protons abundant in the human body. Diffusion Tensor MRI (dtMRI) is a unique, non-invasive imaging technique capable of measuring the anisotropic diffusion of water molecules in biological tissues. The resulting image reflects both the tissue structure (including fiber orientation) and the architecture at the microscopic level which makes it suitable for observing the development in the human cerebral white matter. dtMRI imaging modality results in a 3D field of 2nd order rank 3 tensors where a 3×3 symmetric positive definite matrix is associated with each voxel. The eigenvalues of the tensor at each voxel give the magnitude of diffusion of water molecules at that voxel and its eigenvectors depict the diffusion direction. Standard image processing and analysis techniques are not useful for dtMRI images due to the different data at each voxel and this is the challenge being faced and new techniques for averaging, smoothing, segmentation, visualization and analysis of such images are being developed. Functional MRI (fMR) produces images highlighting active areas of the brain by measuring quantities proportional to the level of oxygenation in the blood. The different MR sub-modalities have presented several challenging problems which occupied researchers in different disciplines including medicine, computing, mathematics, statistics, and visualization during the past few decades. In this project, the intern proposes to develop mathematical and computational algorithms to extract, align, and fuse complementary neurological disease information from the different modalities allowing for mapping brain wiring (DTMRI) and communication (fMRI) over anatomy (sMRI).

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Faculty Supervisor:

Dr. Ghassan Hamarneh

Student:

Yonas Weldeselassie

Partner:

TRIUMF

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Simon Fraser University

Program:

Accelerate

Computation of Second-Order Wave Forces on Offshore Structures

The objective of the intern’s research is to develop a computer program based on a panel-free method to predict the second-order wave loads on floating offshore structures which are critical for coupled mooring analysis. Integration of the mooring analysis computer program with a second-order wave loading analysis tool will allow for the coupled mooring line and vessel dynamics computation. Validation studies will be carried out for various platforms. The project will provide the offshore industry with a numerical tool to assess if a mooring system is designed for survival under operational and extreme conditions.

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Faculty Supervisor:

Dr. Wei Qiu

Student:

Hui Yin

Partner:

Oceanic Consulting Corporation

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

Memorial University of Newfoundland

Program:

Accelerate

Correlating Intrusion Scenarios with an Unsupervised Learning Model

The increasing sophistication of distributed attacks on networked infrastructure has resulted in a requirement for tools capable of abstracting and alerting network managers of network status across multiple data sources. The basic objective of this project is to provide a framework for correlating information from multiple network sources into a cohesive picture of system status. As such, it is necessary to provide a model capable of correlating information from both spatial and temporal information sources. To this end, an unsupervised model will be investigated using hierarchical abstraction to integrate and summarize data from multiple sources. Moreover, the efficient training of such a system will be addressed through the use of appropriate active learning models.

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Faculty Supervisor:

Dr. Nur Zincir-Heywood

Student:

Patrick LaRoche

Partner:

Telecom Applications Research Alliance (TARA)

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Dalhousie University

Program:

Accelerate

User Behavior Modeling and Scalabitliy Analyzing for VoIP Network

Eyeball Networks is a leading developer of software for the VoIP, video telephony and instant messaging industry. In this project, the intern will investigate and model user behavior of VoIP networks developed by the company. Based on a statistical user behavior model, he will then develop a test tool to collect specific Quality-of-Service performance metrics, so as to analyze the scalability of system, and to formulate its relation with the user behavior model. Such results will help the company to improve the scalability of the systems, as well as to design appropriate admission and pricing models for this new type of service.

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Faculty Supervisor:

Dr. Jiangchuan Liu

Student:

Carl Wang

Partner:

Eyeball Networks

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Simon Fraser University

Program:

Accelerate

Transliteration from Arabic to English

Machine translation has been an active field in Natural Language Processing. Although the quality of translation cannot reach that of a human, it is getting closer. One of the major sub-tasks in this field is ‘transliteration’, which is mapping the letters from the source language to the letters of target language. It would be useful for translating the proper names, location names and any out-of-vocabulary word found in the source text. The abundance of names and the lack of a comprehensive bilingual dictionary compel us to find methods to automatically transliterate the names in the given text and not rely on lookup tables. This research mainly focuses on the task of transliteration and by using statistical and dictionary approaches tries to obtain the best transliterations. The language pair under study is Arabic and English.

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Faculty Supervisor:

Dr. Fred Popowich

Student:

Mehdi Kashani

Partner:

NRC - Institute for Information Technology

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Simon Fraser University

Program:

Accelerate

Study of Connection Times for Air Canada

The objective of the internship is to develop better thresholds for minimum connection times between flights. These thresholds must be large enough to reduce the risk of passengers missing their connecting flights due to flight delays. On the other hand, lengthier connection times lead to increased costs as planes and crews must wait longer between flights. The best compromises will be found by using historical data on flight delays to evaluate the effect of varying thresholds on the plane and crew costs using optimization models.

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Faculty Supervisor:

Dr. François Soumis

Student:

Samira Ait-Benali

Partner:

Air Canada

Discipline:

Engineering

Sector:

Aerospace and defense

University:

Polytechnique Montréal

Program:

Accelerate

Segment Pool Allocation Strategy

Video games must be able to present things in ‘real time’, with no delays thus performance is critical. A modern processor can deal much quicker with information that is in one continuous section of memory as opposed to divided into smaller chunks. When information is split, it causes a delay in processing. The intern’s research will focus on optimizing a new system for memory management that will attempt to achieve greater performance through a system that organizes memory into collections of whole blocks in order to prevent the need for data to be split. The research will use algorithmic and statistical techniques to derive appropriate sizes and attributes of these blocks.

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Faculty Supervisor:

Dr. Ramesh Krishnamurti

Student:

Micah Best

Partner:

Radical Entertainment

Discipline:

Computer science

Sector:

Digital media

University:

Simon Fraser University

Program:

Accelerate

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