Beyond the spectrum of visible light lies a window of frequencies called the W-Band which illuminates a world normally unseen to the naked eye and can be the vessel for energy without wires. In order to see this world normally unseen, we have developed a unique circuit topology which has shown signs of truly state-of-the-art performance while consuming zero energy, occupying less area than the head of a sewing needle, and costing less than any of its competitors. Although promise has been shown by this new device, further investigation is demanded.
Identity fraud is spreading fast and causing more and more damages both financially and sociologically. Identity fraud occurs when a criminal impersonates another individual by taking on that person's identity or by creating a fake identity for whatever reason. The project will investigate and develop a new model for identity fraud detection based on login sequence, history and context. Analysis of such information using data mining will allow tracking individual login behaviors and identifying anomalies and inconsistencies in login occurrences that potentially point to fraudulent activities.
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.
Most of today's computers, from cell phones to supercomputers, are heterogeneous: they integrate processors that are optimized to quickly execute a few tasks (CPU
cores), and processors that can perform many independent tasks in parallel (GPU cores). GPU cores and CPU cores have different instruction sets: they understand
different languages. A task written for CPUs cannot run on GPUs, and vice versa. As a result, programming current heterogeneous architectures is challenging and few
applications can take advantage of the processing power offered by GPU cores.
Degenerative brains diseases such as Parkinson?s disease (PD), are getting more common as the population ages. Ways to assess brain diseases, so that disease progression can be predicted and effects of treatment can be measured, are important. Brain imaging technologies are widely available, but extracting the important information from brain images is still a challenge. One way to extract important information from brain images is to examine how different brain networks ?talk? to one another.
Malaria is a mosquito-borne infectious disease affecting humans with more than 214 million cases worldwide. The most dangerous (and most common) form of malaria is caused by Plasmodium falciparum. Understanding the fundamental biological mechanisms of this parasite is crucial for developing therapies to combat the humanitarian crisis caused by the spread of this disease. In order to unravel the mechanisms of how proteins are transported within the cellular environment of this parasite we must first understand how various proteins interact with one another (a network of interactions).
This project is a collaboration between MMSENSE Technologies and the Centre for Intelligent Antenna and Radio Systems (CIARS) at the University of Waterloo to research, investigate, and design an integrated radar module at millimeter-waves.
From cell phones to laptops, from electric vehicles to medical portable devices, from renewable energy storage to emergency backup units, batteries have become an integral part of modern day electronic devices and systems. As batteries get aged, due to repeated charge and discharge cycles, the health of the battery deteriorates. The poor health of a battery can result in malfunctioning of electronic devices and therefore, it is pertinent to accurately predict the state of health of the battery so that a timely replacement could be performed.
Microneedles are hollow needle structures made out of metal, polymer, or silicon which can be manufactured at any height up to one millimetre, with arrays from one to hundred microneedles, depending on the required playload for delivery. Microneedles platform technology can be applied in medical, cosmetic, biotechnology, and industrial applications. The partner
organization has developed a low-cost process for manufacturing hollow microneedle arrays.