Analysis of the implementation of a Model-Based Systems Engineering approach for the conceptual design of advanced aircraft high-lift system architectures

Today, the development of complex products such as aircraft systems is still mainly based on a paper-based requirements and development process which leads to delays, cost overrun and sometimes failure to respond to customer needs. A structured, model-based design approach is considered promising to bring innovation and optimization in systems architectures. The project aims to demonstrate the value of a model-based systems engineering approach opposed to a traditional bottom-up approach for the example of advanced aircraft high-lift system architectures.

Malicious Traffic Predictive Indicators in Content Delivery Networks: a Big Data Analytics Approach

Content Delivery Networks (CDNs) represent the up-to-date standard to transfer data through on-growing Internet. They are designed to manage traffic streams to avoid network problems. Despite the fact that CDNs attempt to satisfy security requirements (authentication, data privacy and integrity), they face rising innovative threats, observable in the cyber-space. The main objective of this project is to design, implement and test new methods to detect and prevent maliciousness in CDNs. We aim at building an alternative solution to classical Web Application Firewalls (WAFs).

Multi-agent Quadrotor Control and Distributed Intelligence in GPS Denied Environments

Networks are ubiquitous in our world. In broad terms, a networked control system consists of sensors, actuators and controllers interconnected and coordinated through a communication network. Networked control with distributed intelligence can open new directions in the industry of robotic entertainment allowing for pursuer-evader games to be played with multiple robots. The research proposed here will give a first step in this direction.

Comparing and Improving Approaches to Topic Modeling

The proposed research project aims at evaluating and improving a technique in Statistical Natural Processing called Topic Modelling in order to apply it to real-life scenarios. Topic modeling is a techniques that allows the quick discovery of what the main topics of a document collection are, and thus automatically answers the question “What do these documents talk about?”.
Several approaches have been proposed to implement topic modeling, but their evaluation have rarely taken the end-use into account.

An Interdisciplinary Approach to Investigating Innovative Online and Blended Pedagogical Practices - Duplicated

This proposal outlines an interdisciplinary, multi-method program of research to develop evidence-based frameworks for implementation and evaluation of innovative instructional practices offered by KnowledgeOne, an international online learning provider for post-secondary institutions, and its elearning partner, Concordia University.

Agent-based scheduling in community health care

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.

Auditing in the cloud, Using OpenStack Congress

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.

Interactive Agent-based eLearning Environment

Mentorina is launching an intelligent learning system that helps teachers observe, measure, and improve each student’s 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 student’s level of comprehension. Through an interactive social media platform, teachers can then help improve a student’s performance on an individual basis.

Morphodynamic model development to better integrate the impact of riparian vegetation on bank erosion

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 intern’s PhD research to address some of the weaknesses of existing morphodynamic models, to develop knowledge on the effects of riparian plants on bank erosion.

Enhancing service quality in community health care through preference-based scheduling

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.

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