Financial institutions ensure borrowers’ ability to repay the loan before lending them for the pursuing projects. The ESSAFIN Logic 1.0 software tool is available for evaluating loan proposals based on the Environment, Social, and Governance (ESG) criteria. The tool has a potential for improvement to account for the lack of critical practical application and evidence-based literature support.
Enabling Analog Artificial Intelligence by the systematic generation of Analog Neural Networks from well-known Artificial Intelligence software tools. The circuits and methodologies developed here enable “AI at the Edge” meaning local, low power, analog AI that provides, for example, medical devices that analyse signals to asses the need for intervention; voice recognition devices that do not send recordings to the internet; smoke detectors that recognise the chemical composition of gas in the air and similar.
The COVID-19 pandemic sparked an urgent need for innovation in all aspects of our lives – and researchers rose to the challenge. From COVID-19 diagnostics and treatments to changes in how we work and receive healthcare, the pandemic has fast-tracked innovation across sectors.
High-potential researchers and businesses around the world did a pandemic pivot, shifting their work and resources to respond to the world’s pressing need for solutions. In Canada, Seyyedarash (Arash) Haddadi’s story is a standout example of innovation partnerships helping to counter the COVID-19 threat.
Fast-charging Li-ion batteries have great potential for electricity storage from renewables, frequency regulation, and peak shaving in large-scale grid applications. The Li-ion batteries must have a fast response, high rate performance, high power capability, and low cost to meet this increasing demand for grid applications. This project between Dr. Jian Liu’s group at the University of British Columbia (UBC) and Tycor UPS will develop a hybrid Li4Ti5O12/hard carbon anode to enable Li-ion batteries fast-charging capability and low cost.
Several de-icing systems have been developed to reduce economic losses and safety hazards due to ice and snow accretion on home pathways. These de-icing systems need to be energy-efficient, and therefore, must be accompanied by high-performance sensors capable of accurately detecting ice and snow to control the de-icing system. In addition to this application, recent industrial developments have shifted the paradigm of ice sensors towards extreme environment applications requiring sensors be operated in harsh conditions.
The aim of this research project is to observe the difference in function between the dominant and non-dominant lower limb in elite youth hockey athletes. Further, to observe how this difference is altered when the athlete is fatigued. Reducing or eliminating limb imbalances is thought to have a positive outcome on reducing injury risk, ensuring optimal development, and allowing for the greatest functional capabilities.
Chronic pain (CP) is a prevalent, disabling, and costly disorder. The gold standard treatment for chronic pain is care from an interdisciplinary pain clinic (IPC) - a rare resource in Canada that is often associated with long wait times (up to five years). These long wait times increase the risk of physical and mental deterioration for the patient and so there need to develop tools to assist CP patients who are on an IPC waitlist. Research suggests that the use of web-based clinical platforms are helpful in health domains (e.g., migraine management).
The generation of a huge amount of plastic waste creates serious social and environmental concerns. As such, there has been a movement to develop fully biodegradable compostable biocomposites in recent years. To join this initiative, Nanomaterials and Polymer Nanocomposites Laboratory (NPNL) at UBCO, in collaboration with Advanced BioCarbon 3D (ABC3D) seeks to develop fully biodegradable polymer biocomposites filaments with appropriate physical properties for 3D printing.
The data centre management is paramount to ensure the uptime operation. This research aims to develop a digital twin platform using the industrial Internet of Things, edge and cloud computing, and artificial intelligence for predictive maintenance of data centre. The facilitate maintenance scheduling and data centre energy consumption could be further optimized through the digital twin platform, which enables the prediction with a virtual representation of the physical asset or a process. The interns will have the chance to work with industry partner in a multi-disciplinary team.
As oxygen demand increases (e.g., exercise), the availability of oxygen decreases (e.g., high altitude) or cardiopulmonary function is impaired (e.g., respiratory disease), our cardiopulmonary system works at a greater percentage of its maximal capacity to supply oxygenated blood to tissues. Currently, there is no reliable way of determining the blood flow to the respiratory muscles. The current technique (near-infrared spectroscopy with injectable dyes) has conflicting data and limitations which hinders our understanding of respiratory muscle blood flow.