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Projets par catégorie

Production planning at Wesgar

Wesgar is a factory that produces metal sheets for its customers. After a product is ready, it will be delivered to the customer. The objective of this project is to improve the On Time Delivery. At Wesgar they have different machines in their production system. These machines are able to process different products based on the shape, size and material. Each product must pass some specific machines to be processed through the production plan. A schedule that determines which product must pass which machine at what time is required for the production system at Wesgar. Currently they use a software everyday to schedule their production system. They are basically using a traditional forward and backward technique to schedule their system. In order to reach the objective we are planning to improve the scheduling technique. Other scheduling methods and software packages must be evaluated to find an alternative that creates a better schedule that leads us to a more efficient system.

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Superviseur du corps professoral :

Tamon Stephen

Étudiant :

Partenaire :

Wesgar Inc

Discipline :

Mathematics

Secteur :

Manufacturing

Université :

Simon Fraser University

Programme :

Accelerate

Embroidery Automation and Optimization for Mass Customization

Embroidery is a very popular art and a method of customization in the fashion industry. The method of embroidery has changed little since the advent of programmable sewing machines in the 20th century. Today, there is high demand for mass customization: consumers want their personalized embroidery patterns on their clothing. Technology already allows consumers to submit a picture while placing an order for clothing, and to receive the clothing with an embroidered pattern matching the picture. However, this process is time-consuming and human labour-intensive: a human worker takes the picture, picks out the thread colors, and creates a sequence of embroidery-machine instructions to create the pattern. We propose to use machine learning to automate and optimize this process. We will develop algorithms to pick the appropriate thread colors, generate previews of the final embroidered pattern, and minimize the stitch count subject to symmetry and quality constraints.

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Superviseur du corps professoral :

Jia Yuan Yu

Étudiant :

Partenaire :

Monsieur Stitches Inc

Discipline :

Computer science

Secteur :

Retail trade

Université :

Concordia University

Programme :

Accelerate

Contribution à la modélisation et la prédiction de la fiabilité résiduelle d’une roue de turbine hydraulique

Ce projet a pour but de proposer aux exploitants des centrales hydroélectriques d’Hydro-Québec un modèle d’estimation et de prédiction de la dégradation de leurs turbines hydrauliques. Celui-ci pourra être régulièrement mis à jour en se basant sur des inspections planifiées et réalisées de façon logique. L’estimation de la dégradation des systèmes est essentielle à la planification de la maintenance. En effet, afin de réduire au maximum les coûts liés au maintien en bon état des équipements, une maintenance (préventive de préférence) doit être réalisée aux moments opportuns ; que ce soit du point de vue du seuil critique de dégradation ou de celui des pertes d’exploitations qui sont les conséquences d’un arrêt de production. Les retombées espérées du projet se traduisent en une réduction des coûts liés à la maintenance et une meilleure disponibilité des équipements de l’exploitant.

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Superviseur du corps professoral :

Souheil-Antoine Tahan;Mitra Fouladirad

Étudiant :

Partenaire :

Institut de Recherche Hydro-Québec

Discipline :

Engineering

Secteur :

Professional, scientific and technical services; Utilities

Université :

École de technologie supérieure

Programme :

Accelerate

A model of larval mosquito habitat productivity for Metro Vancouver

To improve mosquito control and public planning, we will identify places and times that mosquitoes are likely to flourish. A local mosquito control company, Culex Enviornmental Ltd., has been counting and identifying species of mosquito larvae across Metro Vancouver for more than 10 years. We will use their valuable data to create maps of potential mosquito hot spots for the entire area, taking into account weather, land use, elevation, and other features that control numbers of mosquito larvae. There are several different species of mosquitoes found in Metro Vancouver. Some bite people and some bite animals, some spread disease and some don’t. Because of this we will produce different maps for each species. When done, Culex will be able to use the methods we’ve developed to offer similar services to other places, including countries where mosquito-bourne diseases such as malaria commonly take lives and devastate communities.

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Superviseur du corps professoral :

Bernard Roitberg

Étudiant :

Partenaire :

Culex Environmental Ltd

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

Simon Fraser University

Programme :

Accelerate

Unmanned Aerial Vehicles for quantifying natural disaster damages in crops of Alberta

The agriculture sector is one of the major pillars in the Canadian economy based in cereal, pastureland for cattle, and biofuel (wheat, canola and barley), and was estimated to be a $7 billion industry in 2015 in Alberta. It is also one of the most economically risky activities since the value of the yield is affected by market fluctuations and it is often affected by extreme weather episodes, especially hail storms in the summer, that provoke important yield losses. These yield losses cause important economic burden not only to farmers but also to the Canadian government and public taxpayers, since agriculture is subsidized. Moreover, adjusters are generally overwhelmed with claims after a hail storm. In 2015 alone, there was $1.2 billion in loss payouts and thousands of crop insurance claims were processed by the provincially backed insurer. In this scenario, drones arise as an efficient tool for supporting the evaluation of damages in crops caused by weather inclemency by reducing time and field adjusting costs of inspection and providing accurate estimations of yield losses. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Arturo Sanchez-Azofeifa

Étudiant :

Partenaire :

Skymatics Ltd

Discipline :

Earth science

Secteur :

Professional, scientific and technical services

Université :

University of Alberta

Programme :

Accelerate

Alberta High Resolution Wetland Inventory Methodology Development – Year two

This project aims to operationalize innovative methods for developing cost effective wetland inventories across Alberta by use of numerous sources of remote sensing data, namely light detection and ranging (LiDAR), synthetic aperture Radar (SAR), and optical imagery. The project will formalize a mapping specification, develop training and validation datasets (available in-kind from the academic supervisor and industry partner), and review literature to identify candidate data platforms and mapping methodologies that have the potential to meet the requirements of the Alberta Wetland Classification System (AWCS) and the Canadian Wetland Inventory (CWI) data model. A workflow will be developed to integrate candidate data sources and methodologies to yield high resolution wetland mapping and attribution. Project deliverables will support the implementation of Alberta Wetland Policy and North American Waterfowl Management Plan (NAWMP) Habitat Restoration and mitigation programs.

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Superviseur du corps professoral :

Christopher Hopkinson

Étudiant :

Partenaire :

Ducks Unlimited Canada (AB);University of Lethbridge

Discipline :

Earth science

Secteur :

Other services (except public administration); Professional, scientific and technical services

Université :

University of Lethbridge

Programme :

Elevate

Evaluating the effectiveness of real time image filtering in multi-platform live broadcasting and interactive VR installations as means for artistic expression

There are several platforms that allow users to share real time video with the public. However, these platforms lack the tools that would allow creative professionals to create artistic video compositions extemporaneously. Our prior research assessed the potential for artistic expression within live video broadcasting by developing and integrating new creative tools within the Generate platform, a mobile tool for dynamic artistic video compositions. Behavioral analysis provided the information to determine the effectiveness and relevance of video art in an online real time nature. This research proposal will focus on two areas of investigation: (1) multi-platform live broadcasting and (2) interactive VR installations.

Voir la description complète du projet
Superviseur du corps professoral :

David Fracchia

Étudiant :

Partenaire :

Generate Software Inc

Discipline :

Sociology

Secteur :

Information and cultural industries

Université :

Simon Fraser University - Centre for Digital Media

Programme :

Accelerate

Alberta High Resolution Wetland Inventory Methodology Development

This project aims to operationalize innovative methods for developing cost effective wetland inventories across Alberta by use of numerous sources of remote sensing data, namely light detection and ranging (LiDAR), synthetic aperture Radar (SAR), and optical imagery. The project will formalize a mapping specification, develop training and validation datasets (available in-kind from the academic supervisor and industry partner), and review literature to identify candidate data platforms and mapping methodologies that have the potential to meet the requirements of the Alberta Wetland Classification System (AWCS) and the Canadian Wetland Inventory (CWI) data model. A workflow will be developed to integrate candidate data sources and methodologies to yield high resolution wetland mapping and attribution. Project deliverables will support the implementation of Alberta Wetland Policy and North American Waterfowl Management Plan (NAWMP) Habitat Restoration and mitigation programs.

Voir la description complète du projet
Superviseur du corps professoral :

Christopher Hopkinson

Étudiant :

Partenaire :

Ducks Unlimited Canada (AB);University of Lethbridge

Discipline :

Earth science

Secteur :

Other services (except public administration); Professional, scientific and technical services

Université :

University of Lethbridge

Programme :

Elevate

Development of a hybrid seismic data inversion method for determining well-drilling location at complex geophysical area – Year two

Due to the current economic downturn, especially the lower crude oil price, the drilling success rate become the most important goal for any oil/gas company. For a start-up company, any failure in drilling will be a disaster. To this end, the Deep Treasure Corp wishes that through the combination of mature hydrocarbon prediction techniques and new research results in seismic inversion, the success rate of hydrocarbon prediction, the theoretical basis for well placement can be provided in Roncott field, which will improve the success rate in drilling. The University of Calgary is one of Canada’s top research institutes, especially in the areas of exploration geophysics, seismic data processing and petroleum engineering. On the other hand, Deep Treasure Corp, with a short operating history, is lack of expertise in . TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Wenyuan Liao

Étudiant :

Partenaire :

Deep Treasure Corp;University of Calgary

Discipline :

Mathematics

Secteur :

Mining

Université :

University of Calgary

Programme :

Elevate

Development of a hybrid seismic data inversion method for determining well-drilling location at complex geophysical area

Due to the current economic downturn, especially the lower crude oil price, the drilling success rate become the most important goal for any oil/gas company. For a start-up company, any failure in drilling will be a disaster. To this end, the Deep Treasure Corp wishes that through the combination of mature hydrocarbon prediction techniques and new research results in seismic inversion, the success rate of hydrocarbon prediction, the theoretical basis for well placement can be provided in Roncott field, which will improve the success rate in drilling. The University of Calgary is one of Canada’s top research institutes, especially in the areas of exploration geophysics, seismic data processing and petroleum engineering. On the other hand, Deep Treasure Corp, with a short operating history, is lack of expertise in . The company will collaborate with researchers from University of Calgary to access the most up-to-date research results in seismic waveform inversion, and the most advanced technology available in precise well placement, so that the drilling success rate can be improved to reduced drilling cost and environment impact. TO BE CONT’D

Voir la description complète du projet
Superviseur du corps professoral :

Wenyuan Liao

Étudiant :

Partenaire :

Deep Treasure Corp;University of Calgary

Discipline :

Mathematics

Secteur :

Mining

Université :

University of Calgary

Programme :

Elevate

Building and testing the prototype of newly developed compressed air vehicle power system

The construction of a recently developed pneumatic vehicle prototype is planned aiming at concept proof through light vehicle prototyping. The system considered is described in patent application for a novel compressed air / electric vehicle (ANCHEV) having a pneumatic system which works independently, but in conjunction with the electric system. There are air motors and electric drives installed at the shaft of each wheel. The vehicle is equipped with a large size battery and a compressed air tank.

Voir la description complète du projet
Superviseur du corps professoral :

Ibrahim Dincer

Étudiant :

Partenaire :

Antrobus Consulting Ltd

Discipline :

Engineering

Secteur :

Manufacturing

Université :

University of Ontario Institute of Technology

Programme :

Accelerate

Malicious Traffic Predictive Indicators in Content Delivery Networks: a Big Data Analytics Approach

Content Delivery Networks (CDNs) represent the up-to-date standard to transfer data through on-growing Internet. They are designed to manage traffic streams to avoid network problems. Despite the fact that CDNs attempt to satisfy security requirements (authentication, data privacy and integrity), they face rising innovative threats, observable in the cyber-space. The main objective of this project is to design, implement and test new methods to detect and prevent maliciousness in CDNs. We aim at building an alternative solution to classical Web Application Firewalls (WAFs). We intend to leverage new technologies based on the big data analytics using network traffic streams. The project objectives fall into the use of big data analytical framework to extract key features from CDNs’ logs to identify existing and new cyber-threats. Additionally, we intend to use the specificities of Telecom networks such as the availability of user IDs and flow control in EPC networks to further complete our approach. As being one of the key player in CDNs’ market, the partner organization has a high interest to integrate a data analytical approach to corroborate security in such networks.

Voir la description complète du projet
Superviseur du corps professoral :

Mourad Debbabi

Étudiant :

Partenaire :

Ericsson Canada Inc (Montreal, QC)

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

Concordia University

Programme :

Elevate

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