In this project, the intern will design a community health care scheduling system for the allocation of home visits to care givers in community health care. The system adopts an agent-based distributed system architecture which take patients scheduling preferences on time, location and care givers into account when assigning care givers to home visit appointments. In addition, the system will also provide care givers with the opportunity to express their preferences and availability constraints in taking service appointments.
In a multi-tenant cloud environment, several tenants share the same physical resources. To ensure security of tenants data and process, appropriate security measures should be implemented by the cloud provider at multiple layers. Particularly, appropriate controls for end-to-end network isolation must be put in place. The proposed research project aims at elaborating innovative and efficient approaches and methods to audit end-to-end network isolation in the cloud.
Mentorina is launching an intelligent learning system that helps teachers observe, measure, and improve each students individual performance in the classroom. Teachers can design individualized assignments or exams and through cognitive and metacognitive assessments, they can accurately measure how quickly students are learning the material and can determine each students level of comprehension. Through an interactive social media platform, teachers can then help improve a students performance on an individual basis.
Morphodynamic models are increasingly used in watershed management to predict the evolution of river channels and to test management scenarios prior to their implementation. The impact of plants in riparian zones is particularly critical to better document, but the current models rarely integrate this component. This project will use a bank erosion module and a vegetation module, recently developed during the interns PhD research to address some of the weaknesses of existing morphodynamic models, to develop knowledge on the effects of riparian plants on bank erosion.
In this project, the intern will develop an integrated patients and care givers scheduling system for the allocation of health care resources in community health care. This system provides patients with an online preference collecting interface for them to express their preferences on time, location, and care givers when estimating their service costs and booking a service appointment. In addition, the system will also provide care givers with the opportunity to express their preferences and availability constraints in taking service appointments.
This project aims at developing control strategies under the paradigm of Demand Response (DR) in the context of the Smart Grid in order to improve energy efficiency and to reduce operational cost in commercial buildings and communities. The emphasis is put on consumer side energy management strategies that able to balance energy demand and supply and to reduce the overall operational cost while providing an enhanced performance.
In this project we aim to study means of development of a new concept of the thermal energy storage (TES) technology which allows for the collection of thermal energy for later use. With the Solar Power System it is necessary to balance energy demand between day and night time. On the one hand, TES can help improve the performance of a power generating system by achieving full load operation of the thermodynamic cycle at high efficiency. On the other hand, demand for energy for personal needs is unsteady during the day.
S2E Technologies is a consulting company leading the design and implementation of two Smart communities, to be located in London and Guelph, Ontario. The aim of this research collaboration is to assist S2E with the modeling, design, and analysis of rooftop solar greenhouses integrated with grocery stores, anaerobic digesters and livestock barns. The analysis will consider advanced energy design measures capable of reducing energy demand and generating renewable energy on-site, such as from solar and biomass resources.
Composite materials have been increasingly used in todays aerospace products such as Bombardier CSeries and Boeing787 airplanes. A widely used composite manufacturing process is Automated Fiber Placement (AFP) utilizing robotics, precision control, and other high tech tools. Quality requirements for aerospace products are at very high level for product safety and performance. Statistical quality control have been widely used for many decades in automotive, aerospace and other manufacturing as well as service industries.
This project targets the design of a highly accurate proximity sensing system that is capable of operating in a wide distance range under wide variations in temperature and for different sensor characteristics. The system is based on passive inductive proximity sensors that can withstand harsh environments, and, therefore, are widely used in avionic applications. Our design methodology consists of implementing a sensor excitation logic and a low-complexity response processing logic in FPGA.