Projets novateurs réalisés

Evaluating dining improvements in Schlegel Villages

This project is focused on evaluating dining improvements being implemented by the partner organization, Schlegel Villages (SV). The first study involves one SV where the CHOICE+ Program is currently being piloted. CHOICE+ is a team-based approach to making physical and psychosocial improvement. The team is guided by Champions to make these changes over time; changes include small physical improvements (e.g. music), as well as education and training to support relationship-centred principles for dining. Interviews and questionnaires with residents, families and staff will be completed to determine their perceptions of these improvements. A second study will be conducted to compare the impact of blue and white dishware on resident food intake (the primary outcome). It is hypothesized that the darker colour dishes will provide greater contrast and will thus improve intake. Evaluation is timely for these initiatives as the partner organization and will support its scale and spread across 19 homes.

Noise estimation in real world video signals and its integration into noise reduction

The project is about removing noise from video signals, for example,

those taken by a professional cinema camera. In this project, we propose to develop a

commercially capable noise reduction framework based on one of our patents to noise

reduction. A commercial noise reduction is required to automatically recognize the type of

noise piesent in the input video signal. Then it should adapt the way the noise reduction is

done to this recognized type of noise. Also a noise reducer should work on both gray-scale

and color images and be capable to accept input image from different color spaces (for

example, RGB or YUV). Finally, a commercial noise reducer should be effective on images of

different numerical precision such as 8-bits or 16-bits. Our proposal outline how we plan to

achieve such a commercial noise reducer.

Visualization of lipid and protein deposition on contact lenses in a sophisticated in vitro eye-blink model

Contact lens discomfort is one of the primary reasons that cause people to stop wearing them. The discomfort may be due to the buildup of tear film components on the lenses during lens wear. The purpose of this project is to understand where most of the tear film components are depositing on the lens, such as the back or front of the lens. These findings will help researchers and companies develop better and more comfortable contact lens materials in the future.

Paper-Based Weather Resistant Membrane for Building Applications

Currently, petroleum-based water resistance membranes are used in the construction industry in order to create a barrier against water. These make recycling a challenge during building demolition, as well as create a significant carbon footprint of their own. The purpose of this project is to develop a paper-based water barrier to replace the petroleum-based alternatives. In partnership with FPInnovations, two postdoctoral scholars will develop and benchmark the technology, working both at UBC and FPInnovations in Vancouver and Pointe-Claire. One postdoc will focus on the water repellent barrier technology development while the other focuses on forming the paper basesheet with the physical properties necessary to be used as a weather membrane. FPInnovations, whose mission involves the use and valourization of forest products, benefits from this project by opening up a new use for paper – in the building envelope space.

WP 2.1.2: Advanced, Intelligent, Analytics Driven Apps for Software Defined and Functionally Virtualized Networks

Networks are moving towards being adaptive. This means that automation will be used to replace processes which are today highly manual. This project proposes a development of knowledge in the area of algorithms required to enable adaptive networks. The project will train two PhD students to understand optical networks and devise optimization algorithms in the areas of interest. In particular, the algorithms will be devised to be fast and near-optimal to enable their implementation in the network in accordance with operator’s goals of making the network near-optimal and adaptive. We anticipate that the algorithms will be implemented in the network and used to make 5G networks work near-optimality.

Living More with SMART Technology: Exploring the feasibility, usability, sustainability and scalability of SMART solutions to support increased quality of life in Continuing Care.

Older adults value autonomy and independence as key features of healthy aging. SMART technology has enormous potential to foster healthy aging and independence by combining elements of gerontology and rehabilitation with technology to create solutions for disability related to impairment and/or aging. The goal of Living More with SMART Technology (LivMoreSMARTech) is to support technology development and use that is transdisciplinary and ‘fit for purpose’ for improving the independence, functioning, wellbeing and quality of life of older adults in continuing care. Our aims are: 1) to understand the lived experience, needs and desires for well-being among older adults with complex conditions in continuing care; 2) to implement and evaluate off-the-shelf technology solutions, individually customized to maximize well-being, that are supported and sustainable; and 3) to understand how best to incorporate sustainable, person-centred technology solutions into long term care and continuing care settings that result in scalable outcomes including adoption into organizational policies, procedures, programs and care planning.

Oncology Nursing Training: Innovating for Quality of Care in Mumbai, India

Given the complex issues related to the Indian health care systems, the need for excellent nursing training and quality of care, the objectives of the proposed internship are to explore the contribution of simulation training to provide optimal oncology nursing care at the Prince Aly Khan Hospital (PAKH), Mumbai. The research activities will include : 1. A critical review of the literature in order to identify best practices guidelines of simulation nursing oncology training; 2. Individual and focus group interviews with health care (medical and nursing) experts in simulation training, in nursing training and in oncology care. Nursing Competencies Framework developed by the School of Nursing at the Université de Montréal will provide the backdrop for the integration of simulation and care competencies in oncology nursing. PAKH has been committed to carry out general simulation training for quality of nursing care on the one hand and oncology specific training on the other over the past few year. The proposed objectives will be directly anchored within these mandates for optimal oncology and general care.

Assessment of Climate Change-induced Geohazards for Ice-clad Canadian Volcanoes and Mountains

In Canada’s mountains, climate change is leading to the retreat of glaciers, permafrost thawing and accelerated snowmelt. These factors contribute to a significant increase in slope stability hazards and the risk of landslides, placing numerous communities and critical infrastructure at risk. Volcanoes are particularly vulnerable as they are commonly hydrothermally altered and weakened, thereby compounding the effects of climate change and further increasing the associated risk of collapse. Municipal, regional, provincial and federal agencies recognize the critical importance of effectively monitoring unstable slopes on ice-clad volcanoes and mountains in order to more effectively mitigate and respond to these potentially catastrophic hazards. By coupling satellite-based Earth Observation data with ground-based geological and geotechnical information, this project will help TRE Altamira develop a framework for a semi-automatic satellite monitoring service to monitor ice-clad volcanoes and mountains within the Garibaldi Volcanic Belt and ore broadly throughout the Pacific Northwest.

Notification Mat

Glocal Linearization for Feedback Control for Significantly Nonlinear Systems

Closed-loop control of nonlinear systems is typically performed by combining a number of linear controllers, each designed to perform well around an operating point. Although this solution generally works in many cases, there are some important practical applications, e.g. in diesel engine control or in robotics in which it fails and leads to serious performance degradation or outright instability during rapid transition between two operating points. This project aims at developing a systematic way to design a readily and easily applicable solution to this important practical problem.

An information-theoretic framework for understanding generalization in neural networks

Deep neural network (DNN) is a class of machine learning algorithms which is inspired by biological neural networks. DNNs are themselves general function approximations, which is the reason they can be applied to almost any machine learning problem. Their applications can be found in visual object recognition in computer vision, translating texts in unsupervised learning, etc. DNNs are prone to overfitting because DNNs usually have many more parameters than the available training data. However, they usually have a low error on the test data. This surprising fact has motivated the scientific community to study the generalization performance of DNNs. Nevertheless, the previous attempts do not lead to a satisfying answer to the aforementioned question. In this project, we aim to introduce an information-theoretic framework which let us find a promising answer to the question of why DNNs generalize well in practice.

The Contribution of Invertebrates to the Seasonal Diets of Walleye in Lake St. Joseph – year 2

The aim of this project is to better understand the onshore and offshore feeding habits and movement of walleye on Lake St. Joseph. There is special emphasis on answering the question: if, when and how much do Walleye rely on invertebrates in general, and Mayflies in particular. Walleye are an economically and ecologically significant sport fish and Mayflies are an important bioindicator of ecosystem health and potentially have an intricate predator prey relationship. To better understand these interactions, we will reconstruct the seasonal diet of walleye, across many age classes and determine their foraging habits both onshore and offshore. Biological information will be collected from the walleye to determine any specific foodweb interactions and transient movements that may exist. To conserve and protect ecological processes in an everchanging world understanding natural interactions has never been more important.