Projets novateurs réalisés

Enhancing smart thermostat performance through customer data analysis and the integration of AI techniques

Enhancing the efficiency of expanding HVAC systems is a complex task. Utilizing Artificial Intelligence (AI) techniques like Machine Learning (ML) and Deep Learning offers promising solutions. ENA Solution’s smart thermostats provide the potential to employ AI methods for temperature control and energy optimization. In recent years, the company has made efforts to integrate AI for automated solutions in their smart products, but the research is still in its early stages. Moreover, considering recent advancements in AI algorithms, active R&D is essential to maintain product accuracy and performance leadership in the market.
The goal enhancing the efficiency of HVAC systems can be achieved by studying available methods, analyzing company resources, proposing practical solutions, and monitoring small-scale candidate approaches. Analysis of customer feedback and prototype data, recognizing vulnerabilities and technology bottlenecks, and applying stable, optimized methods on a large scale are also vital. The study will leverage practical knowledge of complex systems, thermodynamics, and statistical mechanics to understand influential factors and design AI models based on scale and complexity. Potential approaches may include Convolution Neural Networks (CNNs) for large-scale data or techniques like k-nearest neighbors algorithm (KNN) and decision tree algorithms for smaller scales. Alternative solutions will also be explored based on study outcomes.

Towards Production of Industrial Oils from Camelina

In addition to food uses, vegetable oils are increasingly a source for renewable biomaterials and biofuels. Recent progress in the development of a biobased economy is focused on introduction and improvement of novel crop plants for non-food applications. The proposed project is part of an international collaborative effort to develop camelina as a new industrial oil platform. Our role is to increase oil content of camelina by (1) using a directed-evolution technique and our unique high-throughput screening system to boost the activity of the key enzymes in seed oil accumulation, and (2) introduce these variants into camelina. This project further advances the sponsor’s existing camelina development program aimed at developing a new crop alternative with economic benefits for producers and the emerging bioproducts industry. It has the potential to create new intellectual property and germplasm for both the sponsor and academic partner.

Development of standard sample processing procedure for multi-omics analysis of small intestinal samples collected by an ingestible capsule and understanding of relationship between gut microbiota and IgA production

Recent studies have shown that the gut microbiome works as an organ of the human body which produces bioactive molecules and metabolites. Since the gut microbiome is in close interaction with the human internal environment and changes in the compositions of gut microbiota can impact host physiology through many pathways. Precise determination of gut microbiota compositions depends on the ideal sampling methods which are non-invasive, has little cross-contamination, and collect samples at different sites. The current investigational swallowable SIMBA capsule by Nimble Science can provide a non-invasive, inexpensive, and convenient sampling method to collect small intestine microbiota. The aim of this study is to optimize and evaluate the efficiency of SIMBA sampling capsule using optimization of sample processing procedures and the determination of microbial diversity followed by metabolomic profiling of samples from healthy controls and patients compared with samples obtained by endoscopy and feces.

Building a Digital Twin for the Pearson Airport

“THIS IS A GENERIC TEXT PUT IN PLACE AS THERE WAS NO PROJECT OVERVIEW”

Performance issues for embedded and random problems in adiabatic quantum optimization

Current and near-future D-Wave processors implement optimization using quantum effects on a fixed processor layout. This layout can be modeled as a graph with certain constraints, and the optimization is applied to a specific problem: fixed-topology Ising spin optimization. It is therefore important to study how best to use this hardware to solve combinatorial optimization problems in various forms, and to study performance versus conventional optimizers. The intern will study problems in this area, as well as the problem of predicting performance of proposed processor topologies. D-Wave expects to benefit from this partnership by gaining a clearer view of these issues, which are of fundamental importance to designing software applications for quantum annealers.

A Comprehensive Approach to Automated Essay Scoring through Weak Supervision, AutoML, and Interpretability

Scoring essays is important for learning and business. With AI and machine learning, we can save time and resources by automating the process. This project looks at automatic essay grading from three angles. First, we generate more data using automatic methods called data programming. This helps improve the machine learning models. Then, we refine the data using NLP techniques. Second, we will use Auto Machine learning techniques to easily determine the parameter for training. Third, we make the model more understandable. Deep learning models are often hard to understand, so we’ll use methods to explain the decisions made by the algorithm. We’ll focus on local and post-hoc explainability models. For data programming, we’ll use weak supervision. For interpretability, we’ll use methods like SHAP and LIME.

Methodology to Collect, Calibrate and Process Thermal RPAS Imagery into Radiometric Orthomosaics for Salmon Habitat Preservation

This project proposes to create a standardized methodology to collect, calibrate and process thermal drone imagery into ortho-rectified maps showing accurate temperature data for streams and rivers. These temperature maps are quickly becoming a useful tool with which to detect influxes of cold water that are critical for the preservation of salmon habitat. As our streams and rivers become increasingly hotter due to the effects of climate change, it imperative that new, efficient methods are developed to identified stream reaches that help to cool the stream and preserve salmon-rearing habitat.

PandoPartner Internship Project

This project will help PandoPartner train its clients on how to use our software to better their sponsorship marketing operations, as well as help PandoPartner promote its software. It will involve the creation of User Guide Content & client resources, Marketing materials, and more to help clients and prospects understand how they can leverage PandoPartner’s software.

Prey Availability and Predation as Limiting Factors of Burrowing Owl Population Growth in British Columbia

Alison’s research, conducted in partnership with the Burrowing Owl Conservation Society of BC, aims to better understand what is limiting the endangered burrowing owl’s population recovery in British Columbia. The Burrowing Owl Conservation Society of BC has implemented a species reintroduction program that includes breeding and releasing owls. They then track how many owls survive, reproduce, and return from migration. Alison’s research will focus on understanding whether release site prey availability and predation rate are potentially limiting burrowing owl reproductive success and survival during the breeding season. Analysis of data collected via wildlife cameras, insect sampling and direct observations will provide critical information on how prey availability and predation rates differ between release sites. This information will be useful in guiding where future releases occur, as well as making informed management decisions regarding the habitat currently used to maximize burrowing owl population growth.

Feasibility and Initial Efficacy of Remote Home-Based CardiacRehabilitation— A Pilot Study

Cardiac rehabilitation (CR) is proven beneficial for patients with cardiovascular diseases. Currently, most healthcare systems in China provides limited CR program toward patients after the cardiac intervention. This is particularly true among the rural areas. Home-based cardiac rehabilitation (HBCR) is used to alternative center (hospital) based in many developed countries. In this proposed research, a pilot study will be carried out to investigate the feasibility and effectiveness of using emergent mobile and information technology to deliver monitoring and feedback function in HBCR program. We aim at establishing the understanding the determinants of a successful home-based rehab program in terms of serviceability, reliability and adaptability of such mobile Health program in China. The findings from this pilot study are hoped to be compared with similar programs in Canada and other developed countries. The sensors used to monitor patients’ health indicators include Heart Rate (HR), Electrocardiography (ECG) and built-in geological sensors in smartphones. The rehabilitation programs will be customized according to the information collected from these sensors, and responses from the patient’s self-assessment. After the 3 months intervention, the participants’ health indicators and the program’s operational data are analyzed to assess the acceptability, feasibility and initial efficacy of the proposed HBCR program.

Stratégie de valorisation des techniques et technologies environnementales d’Écoboeuf

Peu de solutions sont accessibles aux agriculteurs pour adresser la problématique de l’adaptation et la lutte aux changements climatiques. Écoboeuf aspire à développer un portfolio de techniques et technologies propres applicables dans le contexte des régions périphériques boréales et à valoriser les réductions de gaz à effet de serres (GES) par la mise en marché de la production de ces fermes avec des marques alimentaires à valeur ajoutée environnementale (‘insetting’).
Le modèle de production d’Écoboeuf adresse simultanément plusieurs enjeux éthiques et environnementaux, ce qui résulte en une proposition de valeurs multifactorielle pour son produit. Cependant, les différents éléments de la proposition de valeur n’ont possiblement pas tous la même valeur aux yeux des consommateurs.
Ce projet vise à déterminer la meilleure approche pour capturer la marge de revenu supplémentaire atteignable par la commercialisation de produits alimentaires à valeur ajoutée environnementale. Une analyse de la valeur perçue des différents avantages du produit sera réalisée afin de cibler les composantes de la proposition de valeur ayant une forte propension à être payées des consommateurs. Les segments de clientèle sensibles aux éléments générant la plus forte propension de payer de la proposition seront ensuite identifiés et décrits. Une stratégie de distribution et de communication sera alors élaborée afin de choisir les canaux et messages les mieux adaptés pour ces segments de clientèle. Ce projet structura la stratégie de croissance d’Écoboeuf, participant ainsi à la transformation du secteur de l’élevage canadien et l’atteinte de ses cibles de réduction de gaz à effet de serre.

Empowering Literacy On-Demand with Interactive Multimedia

The project develops innovative delivery of beginning literacy lessons.
While learning to read and write stories of their own choosing, early learners have many urgent questions. Many of these questions have answers that can be easily explained using a multimedia demonstration. Children can access the answers independently, on demand, when the answers are in a digital repository with straightforward navigation.

In conjunction with outside educators and software developers, this project develops engaging multimedia explanations for Words, Sentences, and Texts, and tests the content with early learners, parents, and teachers.