Innovative Projects Realized

Cinema VR: between borders

The aim of this research is to understand the recent encounter of cinema with a specific type of technology called Virtual Reality (VR) and which gives rise to new arrangements: cinema remakes itself or becomes another and the virtual environment lends to cinema its orthogonal ability to elevate the senses. Therefore, if this recent mode of storytelling is being called cinema, does it interest us to know if the works produced for VR use the classic language of cinema in favor of the virtual environment or work in the formation of a new language? Evidently in Cinema VR the picture decompresses and presents itself in full 360-degree; the editing takes place in layers that overlap and not between one frame and another; and the purpose of the narrative is to be shared in a three-dimensional space where the viewer is co-creator of a story that now requires to be experienced from the inside. From these interactions, new instances arise, altering the processes of work, creation and autonomy. The creator needs so many other areas, from engineering to computer graphics, to compose their work.

Meta-information Extraction from Large-scale Streaming News for Entity-level Media Intelligence and Reporting – Year two

Gnowit is an Ottawa-based information services company that employs artificial intelligence and machine learning to automate the process of monitoring web sources at scale to provide real-time briefings and notifications for the purposes of competitive intelligence, evidence-based policy research and media monitoring. The company currently monitors more than 40 thousand web sources and generates atleast 1.2 million fully analysed documents daily. Gnowit’s customers currently only employ traditional Boolean full-text queries and simple meta-information-based filters to extract documents that are of interest to them. The current technology allows an undesirable quantity of noise and requires substantial improvement. Our main goal is to create (i) new set of customer-facing filters based on the geographic location of news publications, genres, central topics and themes (ii) extract meta-information that can be applied to web-sources, individual articles and segments of documents and (iii) develop entity-level analytics pipelines. Applying these tags to individual sources and documents is beyond the capacity of human effort, and so could benefit from techniques from the field of natural language processing and deep learning. Additionally, we will contribute to the field of machine learning research by developing innovative methods for tackling interpretability challenges associated with deep learning models.

Meta-information Extraction from Large-scale Streaming News for Entity-level Media Intelligence and Reporting

Gnowit is an Ottawa-based information services company that employs artificial intelligence and machine learning to automate the process of monitoring web sources at scale to provide real-time briefings and notifications for the purposes of competitive intelligence, evidence-based policy research and media monitoring. The company currently monitors more than 40 thousand web sources and generates atleast 1.2 million fully analysed documents daily. Gnowit’s customers currently only employ traditional Boolean full-text queries and simple meta-information-based filters to extract documents that are of interest to them. The current technology allows an undesirable quantity of noise and requires substantial improvement. Our main goal is to create (i) new set of customer-facing filters based on the geographic location of news publications, genres, central topics and themes (ii) extract meta-information that can be applied to web-sources, individual articles and segments of documents and (iii) develop entity-level analytics pipelines. Applying these tags to individual sources and documents is beyond the capacity of human effort, and so could benefit from techniques from the field of natural language processing and deep learning. Additionally, we will contribute to the field of machine learning research by developing innovative methods for tackling interpretability challenges associated with deep learning models.

A New Way Forward: Using Biocultural Approaches to Conservation in Key Biodiversity

Canada is a signatory to global conservation agreements to increase the number and coverage of protected areas in the country. Key Biodiversity Areas (KBAs) are a science-based planning tool that can help governments, industry, environmental groups and Indigenous Nations target the right places to protect in terms of habitat for wildlife and to ensure these areas are connected on the landscape. The proposed research will expand on the concept of KBA’s by integrating Indigenous bio-cultural information, such as traditional knowledge on cultural keystones or culturally-significant species like caribou, salmon and wild berries, to help identify and prioritize candidate protected areas with local Indigenous Nations. The intern will work with WCS Canada and Indigenous partner communities to develop a framework for incorporating biocultural information into KBA planning to identify potential areas that should be protected for their ecological and cultural significance.

Optimized Design of Building-Integrated Photovoltaic Sunshades

The proposed project involves the creation of a computational framework to optimize the design of building integrated photovoltaic sunshades. Such shades would allow improved lighting conditions within the indoor environment, while generating power through the photovoltaic panels. The design framework takes in design constraints such as the allowable size of the shade, the location and orientation of the building, and properties of the photovoltaics of interest, and provides the user with a design maximizing power generation, while providing improved daylighting conditions within the building, both spatially and temporally, and reducing cooling loads. Following the model development, a case study on a specific implementation of such a solar shade will be prototyped. The research will be a collaboration between an academic group, a PV supplier, and an architectural firm, including structural and electrical engineers, to implement the design soluti

Summer-season streamflow prediction model for the Oldman River Basin

Reliable monthly and seasonal streamflow predictions are essential for optimal planning of water resources, particularly for reservoir operation and planning applications. Streamflow predictions can also improve water use efficiency and provide early drought and flood warning. The importance of streamflow forecasting is rising with climate change, causing more frequent and hazardous flood and drought events. Current streamflow forecasts in the Oldman River Basin are uncertain, which poses a risk to irrigators, who rely on them to plan for the next irrigation season.
Our project aims to develop machine learning models for reliable summer-season and monthly streamflow predictions in the Oldman River Basin of Alberta. We will also study the risks associated with issuing predictions earlier in the year, up to three months ahead of the irrigation season. Reliable summer-season streamflow predictions in Alberta can help water managers and stakeholders make better-informed decisions on seasonal water allocation, flood and drought mitigation strategies, and environmental flow management.

Advancing municipal natural asset management through monitoring & engagement

Canadian local governments are seeking new strategies to deliver their core services in more financially and environmentally sustainable ways, including turning to infrastructure asset management as a key tool to manage infrastructure. Municipalities are increasingly recognizing that natural assets such as aquifers, forests, streams and foreshores can provide equivalent or better services to many engineered assets. Municipal natural asset management offers a sustainable solution to the multifaceted problems of supplying municipal services in the face of aging infrastructure, urban growth, and declining budgets. As this approach is being implemented in a growing number of Canadian municipalities, it is important to monitor results and outcomes in a rigorous manner to facilitate widespread adoption of municipal natural asset management. This project will address this issue by developing a framework to monitor, track results, and evaluate outcomes, and reporting to stakeholders and the public on what is happening in key local governments with which the Municipal Natural Assets Initiative is involved.

Industrialisation des méthodes de compensation d’erreur d’usinage

Ce projet vise la mise en application de certaines techniques d’anticipation des défauts de

fabrication par la modification de la commande de coupe de machine-outil. Ces techniques

sont développées dans le cadre du projet de doctorat de l’étudiant. Après discussion avec

notre partenaire, nous constatons qu’il est envisageable de mettre en oeuvre ces techniques

de compensation de la trajectoire de l’outil de coupe. L’objectif est l’amélioration de la

précision d’usinage de certaines pièces mécaniques que propose le partenaire industriel.

Des tests et des analyses sont planifiés pour évaluer les possibilités d’adoption et

d’intégration de ces techniques dans le processus de fabrication du partenaire.]

Printability of H13 tool steel by powder-fed laser additive manufacturing

The scope of this research is to provide a comprehensive recipe for powder-fed laser additive manufacturing (PF-LAM) of H13 tool steel. The H13 components manufactured by PF-LAM can potentially show superior mechanical properties as compared to H13 steel manufactured by conventional methods; however, the process optimization is requisite to achieve the additively manufactured H13 tool steel with satisfactory properties. The process is optimized to acquire the printed parts with minimum defects. This process is capable of remanufacturing and repair of worn and damaged dies sets, offering a complete overhaul with good mechanical properties. The partner organization is benefited from the recipe to tailor the printed parts properties to the industry needs.

Santé et bien-être des veaux laitiers de la ferme laitière à l’engraissement

Les veaux mâles issus des fermes laitières sont généralement transportés vers les encans en jeune âge où ils sont vendus puis transportés vers les fermes de veaux lourds du Québec (veaux de lait ou de grain). La santé et les caractéristiques zootechniques de ces jeunes veaux sont un enjeu majeur pour le bien-être animal et afin de limiter les problèmes associés aux maladies (utilisation des antibiotiques, risque de mortalité). Ce projet veut dresser un portrait de la santé des veaux durant l’ensemble des étapes de la ferme laitière à la ferme d’engraissement en incluant les conditions de transport. En mettant en évidence les principaux facteurs de risque associés à ces problèmes, les Producteurs Bovins du Québec disposeront d’informations pratiques permettant d’améliorer le bien-être et la santé des veaux ce qui aidera à pérenniser l’ensemble de filière veau au Québec.

High Performance Clustered Secure Storage Solution

45 Drives—a Nova Scotia based company—offers a high-density, low-cost data storage solution called the Storinator. While this product has been very successful, clients have indicated they would like a clustered solution which offers similar performance and redundancy, without sacrificing security or drastically increasing the cost. Researchers at the University of New Brunswick have been identified as a good fit for creating a clustered software-architecture in tandem with 45 Drives’ hardware-architecture. This software solution will be created from other software products which release their code for free called Free Open-Source software, or FOSS. The software-architecture must keep data secure, be resilient to failure and perform its tasks quickly. To the best of our knowledge, no one offers a storage solution with the properties described above.

Profil économique de l’agriculture urbaine commerciale au Québec

L’agriculture urbaine commerciale est un domaine en plein effervescence, mais l’impact de celle-ci demeure encore aujourd’hui peu documenté. L’agriculture urbaine commerciale se définie par la production, la distribution et/ou la transformation alimentaire et/ou horticole en milieu urbain par des entreprises privées ou d’économie sociale, des organismes ou des individus. Le Laboratoire sur l’agriculture urbaine (AU/LAB), principal partenaire de cette étude, contribue depuis plusieurs années à faire croître, par la recherche, l’accompagnement et la formation, le domaine de l’agriculture urbaine au Québec et tout particulièrement au niveau commercial. Ayant dressé un premier portrait avec le Carrefour de Recherche, d’Expertise, de Transfert en Agriculture Urbaine (CRETAU), AU/LAB aimerait approfondir les connaissances, c’est pourquoi la présente recherche vise à évaluer la contribution de l’agriculture urbaine commerciale au Québec. Cette étude économique détaillée permettra à AU/LAB et au gouvernement du Québec de mieux cerner l’apport du domaine et faciliter sa croissance.