This project uses machine learning algorithms to better understand back movement and low back pain. We apply supervised learning time series algorithms to data collected from Backtracks’ wearable de-vice — which consists of a malleable think curve that reads data collected from the participants’ spine movements. At each time step, such movements are represented as a curve; the dynamic evolution of this curve in time represents an individual’s spinal movements.
The rapid technological evolution of telecommunication networks demands service providers to regularly update their technology, with the aim of remaining competitive in the marketplace. However, upgrading the technology in a network is not a trivial task. When modernizing a network, the existing infrastructure and network components need to be taken into account. The design exercise must not only take into consideration the overall desired functionality and capacity but also the existing network properties.
The rapid technological evolution of telecommunication networks demands service providers to regularly update their technology, with the aim of remaining competitive in the marketplace. However, upgrading the technology in a network is not a trivial task. New hardware components need to be installed in the network and during the installation, network connectivity may be temporary compromised.
The research focuses on development and implementation of advanced software algorithms designed for the automated analysis of skin lesion images. The algorithms will be designed to run on mobile computing devices such as smartphones and tablets, and could be used by the general users as well as doctors for computer-assisted screening and diagnosis of skin cancer. For users, our computer program will automatically compute the risk score for skin lesions based on the previously diagnosed cases, and for doctors, it will use machine learning to assist in making the best diagnostic decision.
Mining companies have a need to sort rocks based on mineral type. MineSense is researching and developing sorting equipment for this task. Intern will model the problem using probabilistic modelling techniques from the area of artificial intelligence applied to the area of mineral processing using electromagnetic sensors. He will create computer algorithms for automatically interpreting sensor data and intelligently controlling diverters which will identify and divert good rocks into a keep pile and leave the waste in a discard pile.
Embedded systems are small low-power computing units designed for specific applications, often with real-time constraints. These systems can be found in cell-phones, portable video games, automobiles, home appliances, digital cameras where they perform specific tasks. The objective of this research is to participate to the development of the embedded software algorithms and tools that will facilitate the embedding of new software solutions to the Synopsys embedded vision system.
In this project, we will design a set of communication protocols dedicated for linear wireless sensor networks, which have promising applications in the real world for environment and infrastructure monitoring. The protocols will be implemented and evaluated by using the multimode, enhanced wireless senor nodes developed in the host academic supervisor's lab.
S’inscrivant dans la continuité du premier stage, ce projet vise à unifier les langages de description de structures argumentatives GSN et TCL et à adapter la théorie de Dempster-Shafer au langage unifié. Cette théorie est la plus adéquate pour intégrer à une structure argumentative les évaluations de ses noeuds. Notre objectif est d’arriver à déterminer de bonnes règles servant à propager avec précision les évaluations des noeuds enfants vers le noeud racine.
Social media websites (e.g. Facebook, Twitter, etc.) are widely used by the general public and also by businesses to promote their product and services. Due to the nature of these websites, marketed content by businesses does not always reach their desired target. This can be improved by providing useful information to the businesses, such as the times their audience is using social media or their most active users. This information is not readily available, but can be derived by analyzing the available data on social media websites.