The focus of the project is to develop an packet-optical network resource optimization model that minimizes the total network cost across IP-optical platform while meeting the following requirements: (i) Offers full protection from any network node and link level failure. (ii) Ability to handle large scale networks and traffic demand (i.e., network scalability). (iii) Meets end-to-end latency requirement. (iv) Provides efficient link utilization across the packet-optical networks. (v) Ability to forecast network capacity augment requirement.
Developed advanced carbonaceous materials from processed biomass is of interest for integration into a variety of high performance applications including, plastics, rubbers, adsorbents, and chemicals. Origin Materials has a patented process that converts waste biomass into 5-chloromethlyfurfural (CMF), furfural and hydrothermal carbon (HTC) as a by-product.
To ensure effective cancer treatment, it is vital to match the drug with the molecular characteristics of the patients tumor. This research project is focused on developing functional diagnostic assays that may be used eventually in the clinic to stratify patients for targeted therapies. The project will provide a unique opportunity for the interns to work with a clinician at the forefront of cancer treatment and scientists of a partner organization that is developing innovative tools to enable precision cancer medicine.
This proposal deals with the pricing and risk management considerations of a property and casualty (P&C) insurance company. These considerations are within the context of a new accounting standard called IFRS 17, in which liabilities in insurance contracts will be measured prior to and during the exposure periods. We propose an implementable and accurate methodology, which is also compliant with the new standard in generating risk measures and margin adjustments.
The 21st century has witnessed an increased prevalence of men and women removing unwanted body hair for cosmetic, social, cultural, or medical reasons. When not done properly, the removal of unwanted hair can lead to injuries to the skin and can cause ingrown hairs, also known as razor bumps. The prevention of ingrown hairs is highly dependent on utilizing post-hair removal treatments (e.g.
Bank Swallows (Riparia riparia), a threatened species in Ontario, breed primarily in either banks at lakeshores or at exposed surfaces in man-made aggregate pits that occur with and without waterbodies. Pits are suspected to be ecological traps for this species but the relative trade-offs in nesting at pits vs. natural sites are poorly known. Availability of aquatic emergent insects is expected to be highest at lakeshore colonies with associated nutritional benefits including Omega-3 fatty acids. However, Bank Swallows may experience differential mercury exposure depending on habitat use.
Internet of Things (IOT) enabled communication devices have become a ubiquitous commodity in the smart metering solutions world for the purposes of getting the data off the meter". Many of these devices have little to no measurable security, aside from the infamous security through obscurity which we can no longer rely on, as the average individual has access to off-the-shelf discovery tools to infiltrate any such device within physical distance.
Global population growth, urbanization and changing climate patterns have increased the demand for potable water, wastewater reuse and value recovery from wastewater, and treatment of industrial process water. Population growth also results in increased demand for the shipping of goods by ocean freight, with the associated risk of the transport of unwanted marine life from one location to another by the discharge of ballast water.
This study will focus on an alternative remote sensing method for crop long-term biomass monitoring and prediction of final yield using Unmanned Aerial Vehicle (UAV) based 3D point cloud data in Southwestern Ontario. Currently, biomass and yield are estimated from statistical and crop growth models. However, statistical models are only applicable for specific area or environmental conditions; crop growth models require many input parameters which are impractical for individual farmers. The allometric method could be an alternative for crop biomass estimation.
In the steelmaking industry, process control models need to be based on a sound physical understanding of the process but should also account for many uncertainties due to the nature and complexity of the environment in which the process is carried out. As a result, it is crucial to extract useful process control information from the raw data stream acquired by the industrial sensors.