An electrical power system is designed to provide safe and reliable supply to customers. However well designed the system, disturbances are unavoidable during the operation and the system should be able to continue secure operation. In fact, if it can be early determined that the system is moving towards an unsecure region, the operators can take necessary safety actions to keep the system secure. Thus, the main goal of this study is to develop novel techniques to monitor the stability of an electrical power system in real time.
Ultra large software systems play an increasing important role in our lives. They are systems such as the world wide banking system, mobile communications systems, social networks, online retailers and online gaming systems. Ultra large software systems are critical and failures in the systems can critically impact the economic health of companies, markets and even countries.
This proposal presents research projects to evaluate a new technology, Electrovestibulography (EVestGTM) that holds potential to objectively, quickly and quantitatively measure the severity of concussion, thus aiding in its diagnosis. EVestG signals are recorded painlessly and non-invasively from the external ear in response to a vestibular stimulus; they are the brain signals modulated by the vestibular response. When concussed, people commonly experience balance (vestibular) problems and dizziness, as well as confused thinking.
The proposed internship, developed between the University of Waterloo and Philip Beesley Architect Inc. (PBAI), will develop and validate prototypes for novel expressive interactive sculpture environments. The work incorporates human perceptual studies and machine learning techniques for generating models for perception and generation of affective expression within experimental architecture and installations, and systematically deriving the relationship between affect and structure.
The ultimate aim of this project is to design and develop methods and tools for classifying attributes of books such as genre, style, tone, and likelihood of being popular. Towards this end we will make use of various information types available on books and users of the Kobo catalog, including the text, meta-data associated with the text, and user features associated with readers of the text. This is a large undertaking.
Point-of-Care DNA tests have grown in importance throughout recent years. Incorporation of devices in patient beside treatment requires fast turn-around times for results as well as economic feasibility. Spartan Bioscience, a local biotechnology company, has developed a technology that can detect abnormalities in a person’s DNA. In an effort to develop next generation technology, Spartan Bioscience has collaborated with several faculties at Carleton to develop a platform that will have improved performance.
Wireless technologies offer new opportunities in the field of telecommunications and computer networks. Wireless sensor networks are a new technology that has emerged after the great technological progress in the development of smart sensors and powerful processors. The city of Trois-Rivieres is currently in the heart of a project to develop a smart public lighting system subject to motion detection. The system will be equipped with vision-audio capabilities for public safety.
The proposed research project “Cloud based hybrid low-cost appliance control and monitor system” is an appliance automation system consisting of an arrangement of different channels of communication. The main idea behind the proposed work is to provide a real time control and monitoring for industrial appliances located in workplaces where internet accessibility is not immediate. The focus of this project is to record the important parameters of operation for an electric motor and then provide data driven smart recommendations to help improve the efficiency of an electric motor.
Big data is a collection of data sets so large and complex that it becomes difficult to process using onhand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization. In this internship, we analyze a real-world big data set(s) to make sensible inferences by taking into account a selected range of criteria. A number of methods and algorithms are investigated, evaluated and evolved to advance the development of specialized tools and processes.
This project will attempt to explore the solution space around a number of key issues related to passive underwater acoustic monitoring. Namely the mitigation of acoustic flow noise in turbulent environments, digital compression techniques for underwater acoustic data and the implementation of real time signal processing algorithms related to the detection of marine mammals on ultra low power processors.