After introducing deregulated power markets and small scale distributed generation (DG) in power distribution systems, the probabilistic evaluation gained much attention to quantify the uncertainties due to parameters such as wind speed, solar irradiation, power market price etc. Meanwhile, due to increasing penetration of electric vehicles (EVs), the load demand due to EV charging has become very relevant information needed for power system planning studies.
A well-maintained hydration status is important for the well-being of human body. Significant deviation from the proper hydration state, either dehydration or hyper hydration, could lead to neurologic complications or even fatal results. Existing hydration measurement carried out in laboratory settings, such as blood and urine test, though accurate, require both expensive equipment and professional experiences. Some newly developed devices which measure saliva, sweat, or bio-impedance improved measurement flexibility but either with compromised accuracy or limited to specific activities.
The goal of the study is to research, test and compare imaging, diagnostic, and quantitative assessment capabilities of the high-frequency ultrasound (HFU) technology and the optical coherent tomography (OCT) for dental applications. A set of samples (possibly hard and soft tissues) will be specifically prepared by the research team from the host university and then imaged, and analyzed in order to determine anatomical features and possible diseases conditions. A newly developed scanning acoustic microscope as well as a prototype of a dental ultrasonic system will be used in this study.
Air pollution is one of the main environmental applications where Wireless Sensor Networks (WSN) are widely used. Using WSN for air pollution monitoring usually targets two main applications: 1) regular mapping and 2) the detection of high pollution concentrations. Both of these applications need a careful deployment of sensors in order to get better knowledge of air pollution.
The goal of this proposal is to make the most advantage of the recently developed technique of Frequency domain Optical Parametric Amplification (FOPA) by pushing this technology to unprecedented levels. The IP has been protected by the group of prof. François Légaré from INRS_EMT. The main inventor, Bruno Schmidt, has founded few-cycle Inc. to commercialize this disruptive technology in Canada. Prof. Légaré and few-cycle Inc.
There is an increase in commercial subsea activity, as well as a growing need to monitor the health of our oceans and rivers. Remote sensors must be deployed underwater. Because of the high level of activity along the coast, in harbours, and even in rivers, the sensors are often deployed in shallow environments. To reduce the costs, small untethered nodes are preferable, and the remote data is transmitted to the surface via a wireless technology. In this work, underwater ultra-sonic communication is proposed to enable a short range telemetry link.
Traditionally, the microchips that power our communications technology use electrical signals to compute, transfer, and store information. Silicon photonics (SiP) is an emerging field, where structures fabricated on those same microchips replace electrical signals with optical ones, enabling exciting new applications such as optical and wireless communications, bio/environment-sensing, and computing.
In order to produce orthopedic knee prostheses for a patient, it is necessary to produce an accurate three-dimensional model of the knee cartilage. The overall goal of the project is to develop a new segmentation method of knee cartilage on MRI images that is both automatic and robust. Laboratoires Bodycad inc. is currently developing innovative technology for orthopedic domain. In this way, the company is a leader for image processing, CAD software development, and manufacturing domains.
Machine learning is a subfield of artificial intelligence that aims at producing computing models from observations (data), with no explicit coding made by humans. Recent advances have illustrated a strong potential of machine learning, with the potential of being a disruptive technology in many domains. For the current project, we are investigating techniques for making practical machine learning.
The NSERC Strategic Network for Smart Applications on Virtual Infrastructures is a five-year partnership between Canadian industry, universities, researchers, research and education (R&E) networks, and high performance computing centres to investigate the design of future application platforms that will deliver software applications of greater capability and intelligence.