Innovative Projects Realized

Taking a bite out of our City’s Natural Areas: Busy beavers and how to manage them.

The City of Edmonton supports research, educational and professional development experience for University of Alberta
graduate students. The program immerses students in a real world learning experience where they can apply their skills and contribute to building a thriving, sustainable and welcoming home for the Edmontonians of today and tomorrow. This will be a joint project between the City of Edmonton’s Natural Areas group and Pest Management group. The Natural Areas group is responsible for preserving ecological integrity while maintaining public safety in the River Valley and natural tree stands within City Limits. While the Pest Management group is responsible for advising, managing and controlling animal and insect populations that may be considered “pests” in an urban area. This may include structural pests, such as those found in buildings or environmental pests such as those whose populations may result in compromises to public assets or human health. Currently there is no integrated pest management plan for beavers. This project will aim to develop management and monitoring plans for beavers in an urban setting and influence City work in the coming years.

Predictive Timing in Speech and Music Production

The project tests musicians and non-musicians with auditory feedback perturbation paradigms in speech and music. In auditory feedback perturbation studies, speakers speak or sing a sequence into a microphone and hear their own productions via special in-ear headphones, while specific parameters in the feedback signal are altered in real-time. In the two speech conditions, parts of the spoken signal are temporally altered in the auditory feedback, hence stretched or compressed. The music conditions focally alter either pitch in a sung sequence or the rhythm in the same sequence. Responses to the speech and music conditions will be analyzed, and the comparison between the group of musicians and non-musicians will give insight into common underlying mechanisms in music and speech production and how musical training shapes the feedback-feedforward loop in music and speech production. Additionally, the participants will perform rhythmic finger-tapping tasks to assess their general motor stability, and their auditory acuity (perceptual ability) will be evaluated with adaptive staircase perception tasks. We expect musicians to be more sensitive to the shifts in general and to show faster responses; however, since we expect them to have a more stable representation of the predicted outcome.

Water Balance Guidelines for Sustaining Natural Areas within the Urban Environment

Edmonton’s natural features (forests/treestands and natural wetlands) provide core service functions such as water treatment, rainwater management, flood protection, recreation, habitat, and pollination. Maintaining the ecological and hydrological function of natural areas within the urban environment is a major challenge. Urbanization can alter the natural pattern of hydrology that can impact sustainability of natural features through vegetation shifts, altered habitat conditions, flooding, and erosion. Measures to protect the natural water balance are necessary when there is a likelihood that a proposed development will impact the hydrological functions of a natural area. Water Balance Guidelines are required to standardize the review and assessment of natural features with respect to hydrological functions, and ensure the pre-development hydrology of the natural feature will be maintained following the development.

Understanding the best available science with respect to the effects of urbanization on natural features, and the associated hydrological threshold in a local context, will be a first step in developing Water Balance Guidelines. This project will improve our understanding of natural area hydrological requirements and how urbanization could alter these patterns.

Route Optimization for Waste Collection vehicles at the City of Edmonton

Route Optimization for Waste Collection vehicles at the City of Edmonton

Étude de la planification des opérations d’ordonnancement de Tecnickrome Aéronautique Inc.

Pour TEC la problématique est que l’ordonnancement de ses opérations de production n’est pas optimisée pour assurer la productivité, l’efficacité, la rentabilité et ne répond pas non plus à la demande client, soit des délais fixes d’exécution et surtout des livraisons à temps. L’optimisation de l’ordonnancement (macro et micro) nécessite trop la connaissance technique détaillée sur les méthodes de fabrication, les temps d’exécution et la complexité de chacune des pièces à procéder (préparation et réalisation) afin d’obtenir une cédule de production maximisées (balancement de la charge par poste de travail). Le fait que les commandes rentrent au jour le jour et qu’elles sont de complexité et de durée différentes, rend la tâche de planification optimisée beaucoup trop ardue pour un humain.
Pour le projet, les objectifs sont de i) comprendre le processus de production et ordonnancement chez Tecnickrome, ii) analyser les données des temps d’opérations pour chaque type de poste et pour chaque type d’item, iii) proposer des opportunités d’optimisation du processus de planification de production et ordonnancement.

Stable isotope and lipid assessment of Atlantic salmon (Salmo salar) smolt across regional populations in North America

Atlantic salmon (Salmo salar) are anadromous salmonids; they inhabit both marine and freshwater habitats during distinct stages in their life cycle. Anadromy allows Atlantic salmon to play a vital role in connecting freshwater and marine ecosystems by facilitating nutrient transport and trophic interactions. This project will examine the stable isotope and lipid composition of Atlantic salmon smolt from combined archived data and new tissue samples collected from smolt wheel mortalities in North America. This project uses non-invasive techniques to gain information on an economically important and culturally significant species at risk. The goal of this project is to examine the ecology and condition of Atlantic salmon smolt populations through stable isotope analysis across regional populations in North America. Assessing the carbon and nitrogen stable isotope signatures of Atlantic salmon smolt tissues will give us insight into their trophic ecology, diets, habitat selection, and potentially the health and productivity of their freshwater habitats. The project will also examine the condition of the smolts through various condition measurements including lipid content analysis. This information will allow us to examine if smolt condition and isotopic ratios are related to the origin population or the productivity of the smolts freshwater rearing habitat.

Developmental Evaluation of the STAR Recovery Centre

This research project centres on a new recovery centre for vulnerable adults with complex mental health and addictions issues in Toronto. Recovery is an approach to mental health that values personcentred care and self-direction. Recovery centres are educational centres, based in the community, that provide programs that help people live normal, meaningful lives in their communities. This research project will be an evaluation of the early stages of a recovery centre. The evaluation asks: 1) what are the key components of a recovery centre and how do these lead to positive outcomes, and; 2) what is working well with the recovery centre? These questions will be answered through interviews and focus groups conducted by the intern in addition to substantive on-site observation. Findings will be communicated through monthly reports and a final report. This evaluation will provide real-time feedback on what is working well that will help with strategic planning and documenting innovation for decision makers at the recovery centre. Additionally, this research will add to the the emerging academic literature on recovery centres through the creation of a model that identifies key components of this approach and connects these components with outcomes.

Deep Learning Models for Principled Causal Forecasting

Numerous Machine Learning (ML) tasks are forecasting problems, used to make downstream decisions. Acting on ML forecasts however can changes the distribution of observations relevant to the forecast. The implication is downstream decision optimization procedures implicitly expect the ML model to generalize outside of the observational distribution. Unfortunately, this is often not the case, and ML models tend to be brittle outside of their training distribution. ML models will thus produce unreliable extrapolations, leading to poor downstream decisions based on wrong forecasts.

Causal models, which aim to learn the structural causal models underlying the data generation process, are a natural fit for such use-cases. This is because causal mechanisms are more robust to superficial changes in the data distribution, and can be expected to extrapolate better to new environments. This project aims to combine deep learning and causal inference to develop causal forecasting models adapted to two important applications. Students will start by implementing existing approaches on one of three applications, before working on improvements to core causal modeling techniques.

Hierarchical Connectivity Maintenance in Swarm Systems

The organization and control of swarm systems have been either completely decentralized where all the robots use only local observation and simple rules for coordination and cooperation which leads to emergent behavior. There are advantages to using this decentralized paradigm such as redundancy, scalability, and simplicity, but such systems tend to be slow and difficult to manage. On the other hand, using centralized systems in multi-robotic systems gives the ability to have a leader which makes managing the swarm easier and allows for faster task completion, but such systems tend to be difficult to scale and prone to failures. All in all, both methods’ disadvantages have hindered swarms to be widely applied in practice. Using a combination of these two points of view, we propose a hierarchical approach where the top-level agents are specialized in terms of hardware or compute power, and bottom-level agents are relatively simple. We plan to investigate this in the context of connectivity maintainance where agents in top level are intermittently connected and agents in the bottom level are continously connected.

The latent of Spectra fusion of X-Ray Fluorescence (XRF) and Mid-Infrared (MIR) Spectroscopy for detection and management of the Aluminium (Al) and Manganese (Mn) content in Canadian Soils for Potato (Solanum tuberosum L) cultivation.

The successful agronomic strategy relies on nutrient detection and estimation. Adequate management of nutrients is an important concern for the whole growth period of Potato (Solanum tuberosum L.) cultivation. In this work, we try to analyze the situation of potential harmful elements for potato production such as Aluminium (Al) and Manganese (Mn) in soil and plant, using spectroscopy, and find soil conditions that suppress their intake to the plants. based on soil attributes like pH, Nitrogen, Organic and Inorganic Carbon, water content and Cation exchange capability. The expected outcomes are :
i) To Detect and estimate Al and Mn concentrations in Soil and Potato plant
ii) To find the relationship between the situation of Al and Mn in the plant and soil and the effect of soil conditions on the uptake.
iii) To Develop prediction models of Al and Mn based on different machine learning techniques.

Conductive polymer deposition for textile strain sensors

Body movements are an important biomedical parameter that can be measured using wearable devices. Notable applications of wearable sensors range from monitoring individuals suffering from loss of autonomy to monitoring athletes’ performance. These movements can include breathing, speech, limb motion as well as heartbeat. Accurate measurement of these movements requires precise and sensitive strain and pressure sensors. In turn, the production of these sensors requires the development of reliable, robust, and highly conductive smart materials. Conductive polymers have been used to produce flexible and stretchable sensors and are popular in flexible electronics. They are therefore excellent candidates for conductive smart materials. By the end of the internship, the student will have developed an optimized method to polymerize monomers onto textiles for their use as electronic textile. Optimization of the method would lead to upscaled production of highly reproducible and reliable conductive threads usable for strain sensors.

Degradation of disposable face masks in the landfill leachate

The use of disposable face masks as preventive measures significantly increased in the past years. Overloading
landfills with disposable face mask wastes will raise certain environmental concerns. However, their degradation
in landfill leachate is poorly studied. The objective of this study is to investigate the degradation process of the
mask in landfill leachate and quantify the number of microparticles and chemical pollutants released into the landfill
leachate. This project will give the industry and government more detailed information about how to make more
improvements and act more Environmentally friendly in the future about the development and production of the
more degradable and biodegradable materials, considering the process of degradation.