In the era of BIG DATA and Internet of Everything, in order to provide the meshed data network with high capacity, advanced optical short reach interconnect technology are eagerly required. Silicon photonics has attracted intensive interest as it succeeded to provide highly energy efficient and broadband width integrated photonic devices on one chip to satisfy the requirements of optical interconnect. One of the problems is that silicon always requires an off-chip light source as silicon cannot emit efficiently.
The smart hybrid DC-AC microgrid is an emerging technology with remarkable potential benefits such as (i) facilitating integration of distributed energy resources and renewables, (ii) improving reliability and quality of the electrical energy supplied to the consumers, (iii) increasing the efficiency of power generation, transmission, and distribution systems, and (iv) facilitating implementation of Electric Vehicle (EV) charging infrastructure.
Work conducted during this project will involve the extension and further development of existing methods for detailed measurement and subsequent modelling of radiowave propagation characteristics in indoor environments at extremely high frequencies. Results will enable the determination of the powers, time delays, and angles of arrival of waves incident upon a receive antenna over direct, reflected, and diffracted paths between a transmit antenna and a receive antenna.
Discovery Agents is a leader in mobile, augmented reality educational technology, with products and services intended to enhance student and teacher experiences within informal and formal educational settings. With a growing industry demand for diverse science, technology, engineering and mathematics (STEM) professionals, this study proposes to examine the impact of the Discovery Agents Mission Builder tool on STEM learning and perceptions among middle school students.
When light interacts with matter, different effects may take place, depending on the particular characteristics of both light and matter. The result of this interaction, typically a quantitative change in the characteristics of the light (i.e., intensity, wavelength, phase), can be used to measure the presence of a particular specimen of interest. Specifically, Surface-enhanced Raman Scattering (SERS) has demonstrated to be able to detect accurately very low concentrations of chemical species.
The aerospace industry is experiencing a quiet revolution fueled by intense technology developments. Major engine improvements are coming to the market, composites and other advanced materials have now become mainstream.
By creating real-time and hardware porotypes, the proposed research provides opportunities for better investigation of these converters and for development of advanced and effective methods for their control. The three interns that will be trained during this research partnership will gain in-depth knowledge of modern power system equipment and knowledge of the latest developments in real-time simulation of such systems.
The scope of this project is to develop a modern Railway signaling system using LED technology to replace the old system employing incandescent bulb. We propose a novel design and control to avoid using low-lifetime components as the existing commercial systems. The current and voltage monitoring functionalities are added to detect exactly which LED that fault occurs, it helps to maintain system and easily adjust light intensity efficiently.
Software failures are catastrophic. For example, a software failure resulted in the 2003 northeast blackout which lasted 7 hours and took over 55 million people in Ontario and U.S. out of power. Unfortunately, it is dauntingly difficult to diagnose such failures because the underlying software systems are extremely complex. This research is the first to propose non-intrusive failure diagnosis that does not require any modifications to the software.
The intern will develop and evaluate new algorithms to improve the accuracy of short-term wind power forecast. The algorithm will be fed with near real-time data (wind speed, wind direction, air temperature, power production, turbine availability) from wind farms in order to improve the forecast over the next 24h. Once the best algorithm has been selected, the intern will then apply this new algorithm directly into WPreds IT infrastructure and will train WPreds scientific staff to use the algorithm.