Ananda Devices has developed an innovative technology to produce high-throughput organ-on-chip technology for commercialization in the pharma industry and cosmetic industry. For cost effective and fast commercializing the device, semi automation/automation is required for the high throughput data analysis. Further validation of the automation algorithm is required for data accuracy.
Most academic literature and practices in the real estate industry use traditional valuation models to predict house prices. While machine learning models have been used more heavily in the finance literature, it is less applied among real estate researchers. While traditional property valuation models rely on simple relationships between the price of a property and each property characteristic, machine learning models allow for complex relationships and can solve such relationships.
A verifier-prover — where a “prover” suggests an answer to a question, which is then checked by a “verifier” — is a powerful analytical tool in computer science. As an example, understanding the number of transactions required to answer a computational question in a prover-verifier setting offers insights into the difficulty of that computational problem. Problems that can be solved with few transactions between a quantum prover and classical verifier is said to have complexity “QMA”.
Open science is the concept of freely sharing data to the public. With large-scale data becoming more easily accessible to everyone, it is important to create a platform where the public can visit to analyze and interpret data. And although open science increases the accessibility of data and reports to the public, it does not reduce readers’ language barriers or increase statistical literacy.
Our goal is to research, develop and commercialize an advanced biosensor that detects many different pathogen infections and immunity for diseases such as COVID-19. We are using a new sensor technology realized with semiconductor manufacturing technology (silicon photonics) and integrated optics and electronics. Our hope is that our sensors can provide answers to individuals, to industries, to governments, and to policy makers.
The lack of scientific data on the potential effects of instream tidal power extraction on migratory fishes is delaying the decision-making process on a technology that shows promise for reducing carbon emissions, and for which Canada could become a global leader in the production of infrastructure. It remains unclear if fishes that occupy Canada’s leading tidal energy test site (Fundy Ocean Research Centre for Energy [FORCE], in Minas Passage, Nova Scotia) will be negatively affected by turbine installations.
Flying air vehicles, most commonly referred to as “drones” come in many different forms. The type of drone required to accomplish a task is dependent on the mission profile. Overcoming the barriers towards fully autonomous operations requires addressing the concerns and complying with the requirements of regulators. The objective of the research is to identify barriers and facilitators private aerospace companies have in flying fully autonomous drones in Canadian airspace.
This project will allow us to develop a microelectronic chip prototype of an energy-efficient AI processor. The AI processor exhibits a 1000 times reduction in power profile compared to standard cloud-based GPUs. Tasks that can be transferred from server GPUs to this solution and deploying our AI-Processor solution to EDGE can estimate substantial energy savings when evaluated over ten years under realistic assumptions. We estimate a net reduction of 83K tonnes of CO2 equivalent over ten years, helping Quebec significantly achieve its clean environment objectives.
This research project aims to improve the quality of life and facilitate the early detection of some health conditions by enabling wearabale devices that have a very small form factor, are highly reliable and provide continuous health tracking and monitoring.
Zirconium alloys are used extensively in nuclear reactor cores for key components such as fuel assemblies and pressure tubes. It is extremely important that the in-service behavior of these components is well characterized to ensure they remain fit-for-service. This work will investigate the relationship between harmful impurity elements, specifically chlorine, and the fracture toughness of a zirconium alloy, Zr-2.5Nb. It is known that chlorine results in the formation of tiny precipitates, which are particularly damaging because they tend to cluster and form elongated voids, termed fissures.