Innovative Projects Realized

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

29670 Completed Projects

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Projects by Category

Filament quality control system for FFF 3D printing

Additive manufacturing, also referred to as 3D printing, gains increasing popularity in many industrial sectors. Fused filament fabrication is one 3D printing technology that is suitable for a variety of different applications in the field of aerospace, transportation and automotive. One major challenge in implementing this technology at an industrial scale is to guarantee consistent quality of the 3D printed product. Many printed parts have defects or fail during printing due to inconsistent material quality. The objective of this project is to develop a system to monitor the incoming material in real time to assure the 3D printed part quality remains constant for every printed part. Developing such a system will advance the maturity of the 3D printing process and forms the first step to aid the industrial partner in the integration of 3D printing into its current manufacturing portfolio.

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Faculty Supervisor:

Daniel Therriault

Student:

Partner:

Hutchinson Aerospace & Industry Ltd

Discipline:

Engineering

Sector:

Manufacturing

University:

Polytechnique Montréal

Program:

Accelerate

An optical function analysis for thin-film device structures

Informed thin-film device design, wherein layers of thin-films are deposited onto an underlying substrate, requires an understanding of the spectral dependence of the optical functions associated with the thin-film layers which constitute such a device. In this project, we aim to further understand the form of the optical functions for the various types of thin-film materials and then use this knowledge in order to aid in the interpretation of experimentally acquired transmittance and reflectance spectra. We will start with the assembly of a library of optical functions corresponding to the various types of thin-film materials. A series of models that aims to capture this physicality will then be devised. Finally, we will use these models in order to narrow the parameter space that must be probed in determining the spectral dependence of the optical functions associated with the thin-film layers from measurements of the transmittance spectrum at normal incidence and the reflectance spectrum at near-normal incidence. The company sponsoring this project aims to commercialize a software offering capturing the results of this project. They also aim to exploit the results in order to develop new solar-based products.

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Faculty Supervisor:

Stephen O'Leary

Student:

Partner:

Solar Adventure Ltd

Discipline:

Engineering

Sector:

Utilities

University:

The University of British Columbia - Okanagan

Program:

Accelerate

Plugging Machine Learning into Mobile Cloud/Edge Computing

The central role of the Internet in modern society creates challenges of efficiency, flexibility, and security, especially as usage intensifies due to proliferation of mobile devices and the Internet of Things (IoT). Wireless network-based technologies such as Mobile Cloud Computing (MCC) and Mobile Edge Computing (MEC), introduce new challenges. In particular, shifting locations and hardware constraints often lead to unsatisfactory network security and undesirable transmission delay/cost. In the proposed project, we attempt to utilize machine learning techniques to solve two challenging problems in mobile cloud/edge computing: intrusion detection in mobile cloud computing and resource allocation in mobile edge computing.

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Faculty Supervisor:

Qiang Ye

Student:

Partner:

Ericsson Canada Inc (Quebec)

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Fast and Accurate Computation of Wasserstein Adversarial Examples

Machine learning (ML) has recently achieved impressive success in many applications. As ML starts to penetrate into safety-critical domains, security/robustness concerns on ML systems have received lots of attention lately. Very surprisingly, recent work has shown that current ML models are vulnerable to adversarial attacks, e.g. by perturbing the input slightly ML models can be manipulated to output completely unexpected results. Many attack and defence algorithms have been developed in the field under the convenient but questionable Lp attack model. We study an alternative attack model based on the Wasserstein distance, which has rich geometric meaning and is better aligned with human perceptron. Existing algorithm for computing Wasserstein adversarial example is very time-consuming. The goal of this project is to significantly speed up the generation process for Wasserstein adversarial examples by carefully reformulating the problem and by exploiting better optimization techniques.

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Faculty Supervisor:

Yaoliang Yu

Student:

Partner:

Royal Bank of Canada (Borealis)

Discipline:

Computer science

Sector:

Information and Communications Technology; Technology; Finance and Insurance

University:

University of Waterloo

Program:

Accelerate

Adaptive Information Extraction from Clinical Patient Records

Among the applications of computer science in the field of health care and biomedicine, the processing of clinical patient records is one of the increasingly important topics for improving the Electronic Health Records (EHR) systems. A practical use of EHR systems is to help improve the decision making process for the physicians. The goal of this project is to develop an information extraction tool that extracts the relevant information with respect to the patient disease/symptoms, which help the physicians in their decision making process. In order to extract the relevant information with respect to diseases, we plan to cluster the patient’s records into groups according to their diseases and symptoms, and apply data mining tools to discover meaningful patterns per group. Patterns could refer to procedures or surgeries, frequent symptoms; treatments related diseases associated with specific diseases. The usefulness of such tool is primary based on recommending a list of….tobecontinued

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Faculty Supervisor:

Jimmy Huang

Student:

Partner:

Alpha Global IT

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

York University

Program:

Accelerate

Innovative Sustained High Strength Silicate Based Shotcretes

Due to early strength requirements, shotcrete mix must incorporate rapid set accelerating agents to speed up mix set time and accelerate hardening. Silicate-based shotcrete accelerators have demonstrated good early compressive strength, short set time and good stiffening properties at relatively low cost. The silicate-based shotcrete mix also has minimal impacts on health, environment and improved safety. However, it can exhibit relatively significant loss of compressive strength over 28 days, which presents a critical challenge. The aim of this project is to develop low-cost and environmentally-friendly silicate-based accelerators that exhibit rapid setting, strength gain and minimal 28-day loss of strength. This will rely on understanding the interactions between silicate accelerators and cement, and compatibility issues. The research will focus on enhancing mechanical, hydraulic and microstructure properties of shotcrete mixtures at different curing temperatures and ages, as well as evaluating durability privilege of silicate-based shotcrete mixtures over alkali-free shotcrete mixture accelerators.

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Faculty Supervisor:

Hesham El Naggar

Student:

Partner:

National Silicates

Discipline:

Engineering

Sector:

Construction; Natural Resources; Mining

University:

Western University

Program:

Accelerate

Prédiction en temps réel du nombre d’occupants d’un bâtiment en vue d’améliorer l’opération des systèmes CVCA

L’objectif du projet et d’améliorer l’efficacité énergétique d’un bâtiment en proposant le contrôle prédictif des équipements CVCA (Chauffage Ventilation et Climatisation de l’air) de ce dernier. Cette amélioration devra être basée sur la prédiction du nombre d’occupants dans un bâtiment. Nous utiliserons les capteurs standards et spécialisés pour estimer et déterminer l’occupation en temps réel du bâtiment afin d’établir un profil. Les équipements de ventilations étant par ailleurs énergivores, on cherche à minimiser les pics de demandes énergétiques au cours de la vie du bâtiment. L’anticipation et la prédiction de la demande future permettent alors de lisser l’utilisation des équipements et donc de faire des économies énergétiques et financières.

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Faculty Supervisor:

Stanislaw Kajl

Student:

Partner:

Ecosystem (Montreal, QC)

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

Soil-structure interaction and design limit states for large-span Ultra-Cor steel bridges

Arched culverts are widely used nowadays as a solution for numerous roadways and railways overpassing as they are cheaper and easy to construct in comparison to conventional concrete and steel bridges. The current study involves three-dimensional numerical simulation for three full-scale field monitored large-span arched culverts (including the largest span arched culvert in the world of 32 m). The verified numerical model will then be used to investigate the impact of several parameters such as the supported soil and truck loading on performance of large span culverts. The results from this study will be used to develop design guidelines and recommendations for large-span arched culverts. Lastly, the validated numerical model will be utilized in investigating different methods to strengthen the large-span culverts in addition to simulating the welded connections between the segments of the culvert and demonstrate their impact on the performance of the culvert.

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Faculty Supervisor:

Hesham El Naggar

Student:

Partner:

Atlantic Industries Limited (ON)

Discipline:

Engineering

Sector:

Manufacturing

University:

Western University

Program:

Accelerate

Identification des problèmes phytosanitaires de la vigne au sein de la parcelle : association de l’imagerie à ultra-haute résolution spatiale et de l’apprentissage profond.

Du fait des changements environnementaux en cours, il est nécessaire de faire évoluer les pratiques agricoles pour qu’elles soient plus respectueuses de l’environnement. Pour avoir une agriculture plus durable et tout autant productive, il est essentiel d’accompagner les agriculteurs dans cette transition, notamment en développant de nouveaux outils.
Le but de ce projet est de développer un outil d’analyse d’images permettant d’identifier des maladies de la vigne. Le dépistage est en effet une pratique déterminante pour détecter l’arrivée et la propagation de maladies. Cependant, cette pratique est peu souvent réalisée car elle demande beaucoup de temps. Automatiser le dépistage le rendrait moins contraignant. Il pourrait ainsi être effectué plusieurs fois dans l’année, délivrant de précieuses informations sur l’état de santé des cultures et permettant, entre autres, au viticulteur de moduler les doses de traitement appliquées dans la parcelle selon l’état de santé réel des plantes – limitant ainsi l’usage de pesticides.

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Faculty Supervisor:

Jérôme Théau

Student:

Partner:

Centre de géomatique du Québec

Discipline:

Earth science

Sector:

Agriculture and Food; Sustainability & the Environment; Environmental Science and Technology

University:

Université de Sherbrooke

Program:

Accelerate

Ancient DNA Analysis of Archaeological Aurochs Remains from China

As the wild progenitor of modern domestic cattle, aurochs became extinct in the 17th century in Europe. Their extinction in China was once thought to start at the beginning of the Neolithic due to some climatic changes. However, our recent ancient DNA analysis (Cai et al., 2018) has confirmed the aurochs had in fact survived to the end of the Late Neolithic and many of them were mistakenly identified as another species in the past.This research will apply the next-generation-sequencing analysis to obtain more informative DNA data to examine the population changes of aurochs in ancient China,in terms of the adaption to climatic changes and the impacts by human hunting and over hunting. The new research will involve in detailed genomic analysis and also multi-disciplinary integration with archaeology, SFU is one of the few places with the dedicated ancient DNA lab and the required multi-disciplinary expertise.

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Faculty Supervisor:

Dongya Yang

Student:

Partner:

Jilin University

Discipline:

Sociology

Sector:

Education

University:

Simon Fraser University

Program:

Globalink Research Award

Using neural networks to learn the folding landscape of DNA

The human genome is composed of billions of base pairs coding for genetic information. DNA is scattered through our chromosomes that all get packed in the nucleus of a cell. Different conformations of DNA folding can be informative of cell type and lead to regulation of specific expression programs by modifying physical accessibility to transcription. The tight structure and its conformations are controlled by multiple DNA binding proteins. Advanced molecular techniques now give information on the spatial contact and interactions of sequences, and their binding proteins and factors distributions along these sequences. Recent work showed that neural networks can predict the structure given binding proteins presence/absence on sequence but the introduction of mutations in the sequence doesn’t give steady predictions yet. The goal of this project is to build another type of neural network, variational autoencoders to the DNA folding problem.

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Faculty Supervisor:

Eldon Emberly

Student:

Partner:

Université Paul Sabatier

Discipline:

Life Sciences

Sector:

Education

University:

Simon Fraser University

Program:

Globalink Research Award

Re-claiming the neighborhood. Exploring the limits and possibilities of citizen participation in Mexico City.

This research project explores how citizen participation can either reproduce or resist the role of the state as the central actor in public decision-making processes – this is done by comparing two participatory social programs in Mexico City: a neighborhood improvement program (PMByC) and a participatory budgeting program (PP). During the field-trip, the student will conduct participatory observation in public spaces financed through these programs and will interview around 40 beneficiaries, policy makers and representatives from civil society organizations that have been involved in the design and implementation of the PMByC and the PP. The hypothesis guiding the research is that for more democratic forms of governance to materialize, citizen participation needs to be institutionalized from below – a process that requires grassroot involvement in the design of participatory mechanisms as well as a shared responsibility of state and civil society actors in the implementation of participatory programs. The findings will serve to shed light into the limits and possibilities of conceptualizing citizen participation as a democratizing practice.

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Faculty Supervisor:

Laura MacDonald

Student:

Partner:

Universidad Nacional Autónoma de México

Discipline:

Sociology

Sector:

Education

University:

Carleton University

Program:

Globalink Research Award

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