Projets novateurs réalisés

AI-driven approach for the cyber defence of additive manufacturing management system

Additive manufacturing is rapidly employing the Internet of Things and cyber-physical systems to facilitate its reliability and relieve human supervision. However, with 5G network and cloud computing intertwining with the physical machines placed locally, the service is vulnerable to prospective cyberattacks. Various researchers have already stressed the urgent need to ensure the users’ and businesses’ web safety. As the old traditional cybersecurity precautions and procedures are gradually out of date, this increasingly disturbing concern in cybersecurity can be assisted by AI to ensure a safely cloud-based manufacturing system. This paper analyzes various threats posed upon cloud-based manufacturing system by using an existing framework as an example and select the best method from several potential models to implement AI to ensure the safe use of this server platform.

Collective dynamics of interacting cells during development

Multicellular organisms begin as a single cell with instructions encoded by the genome. During development this cell multiplies many times generating an enormous number of cells, each with its own specialized role. For example, developed humans are composed of trillions of cells but our organs and limbs have the right form, location, and function with little variability. It remains poorly understood how a process so complex and seemingly delicate can be so robust. Importantly, the assembly rules which guide development also govern how our bodies heal, age, and respond to disease. The goal of this project is to develop a novel predictive model of multicellular assembly by integrating mathematical modelling of gene regulation with data and expertise from leading experimentalists. By advancing our understanding of gene regulation in multicellular development, homeostasis, and disease, the long term goals of this research will enable innovations in drug design and tissue engineering.

Setpoint attacks detection in cyber-physical systems: experimental validation using unmanned vehicles

he objective of this project is to investigate, theoretically and experimentally, the problem of detecting setpoint (reference) cyber-attacks against Cyber-Physical Systems (CPSs).

In the first phase of the project, the student (Mattia Cersullo) will develop a novel setpoint attack detection and mitigation scheme based on a supervisory control scheme known as the Command Governor (CG).
In the second phase, the student will build an experimental setup where the proposed strategies will be tested. In particular, the student will create a testbed using a drone (Quanser Qdrone) and an indoor localization system (Vicon Cameras) both available at the host supervisor (Dr. Walter Lucia) laboratory. The testbed will be used to emulate the effect of setpoint attacks on the flying drone, to experimentally validate the propose attack detection/mitigation solution and to contrast it against other state-of-the-art schemes.
Finally, during the final phase, the student, under the guidance of the home supervisor (Dr. Giuseppe Franze’) and host (Dr. Walter Lucia) supervisors will prepare a research manuscript. The writing of the research paper is expected to be started in the last weeks of the student permanence at Concordia University, and it will be completed at the student’s home institution.

ICaRN-II: Investigation of Stress and Subsidence Hazards in Cave Mining for Improved Safety and Geo-Risk Management

The proposed project aims to develop and verify new knowledge, technologies and engineering tools aimed at identifying and mitigating geological hazards encountered on deep cave mining projects. The research will integrate laboratory testing, mine data and advanced computer modelling to better understand the underlying influencing factors. The research will see four interns working closely with industry partner to help ensure worker safety and protect value in deep underground mass mining projects. This project will also contribute to the International Caving Research Network, a Canadian initiative directed at maintaining Canada’s competitiveness in the international mining industry. The research network includes a multi-disciplinary group of representatives from industry and academia covering the fields of geology, cave mining, geomechanics, and mineral processing.

Online Data Imputation by Modified Mixture Density Networks

In the era of big data, software based on artificial intelligence has greatly improved the quality of people’s lives. Although data is not a scarce resource, the data we collected are usually incomplete due to many reasons, i.e. they contain some missing values. Simply deleting these missing data will not only cause great waste, but may also make trained models biased. To address this problem, data imputation algorithms can predict the missing values based on all the observed data, making the data set complete, so that the collected data can be used more efficiently. In the meanwhile, based on the same idea, we can apply this algorithm to data compression. We can estimate how much information is lost during the compression process, and evaluate whether the compressed data retains enough information for further usage.

Wastewater Testing of SARS-Co-V2 in treatment plants in First Nation Communities

SARS-CoV-2, the virus causing COVID-19, is found in the stool of the infected individuals and eventually ended up at the wastewater treatment plants. Since COVID-19 pandemic started, researchers all around the world have been investigating SARS-CoV-2 in wastewater to understand fate of SARS-CoV-2 and predict a potential outbreak by monitoring wastewater for the detection and quantitation of SARS-CoV-2. Wastewater treatment plants, especially which don’t have disinfection processes, may not able to remove SARS-CoV-2 from wastewater. When it is not removed, it can reach natural water bodies and people. Our aim is to understand if SARS-CoV-2 is removed in wastewater treatment plants employed for the wastewater treatment of small communities and to gain insights into the potential use of wastewater surveillance of COVID-19 for small communities. Partner organization will have the chance to see if their submerged attached growth reactor (SAGR) system are effective in eliminating SARS-CoV-2 in wastewater.

La finance solidaire au service du développement local : Le cas de la revitalisation du vieux Pointe-aux-Trembles

Les actions philanthropiques visant le développement des communautés locales sont de plus en plus fréquentes. Cette recherche s’intéresse aux effets de ces actions philanthropiques sur les communautés locales en étudiant le processus de revitalisation du vieux Pointe-aux-Trembles. Ce secteur peine à se dynamiser depuis plusieurs années et plusieurs locaux de l’artère commerciale principale sont vacants. Le processus de revitalisation est porté par la Société de développement Angus qui vise un développement inclusif et s’effectuant dans le respect la population locale. Par le fait même, une des stratégies employées pour favoriser ce type de développement est l’occupation transitoire des locaux vacants ce qui permet d’avoir une offre commerciale qui vient combler les besoins de la population locale en attente du développement immobilier. Cette recherche aura comme objectif de documenter les interventions et pratiques mises de l’avant dans le processus de revitalisation pour des fins de modélisation.

Investigation of enhanced superplastic forming behaviour of Ti-6Al-4V alloy sheets for aerospace applications

Titanium alloys are used to manufacture aerospace components that require high strength at high operating temperatures such fan blades, heat shields and jet engine exhaust cones. Parts that have complex geometries are commonly formed at high temperature (around 900°C) so as to achieve maximum ductility during the forming process. By applying a small oscillating load during the forming process, the titanium alloy is expected to deform more uniformly and to a greater extent than during conventional superplastic forming. The objective of this investigation is to determine the ranges of amplitude and frequency of the oscillating load that will optimize the formability of the titanium sheet. The results of this research will ultimately be applied to industrial processes in order to improve process robustness and part quality while reducing cycle time and manufacturing costs.

Travail sur des polymères interface pour développer des surfaces multi-stimulables

Le projet à pour but d’obtenir une surface avec des propriétés qui peuvent changer grâce à une stimulation. Dans notre cas une stimulation à une longueur d’onde précise.
Dans un premier temps je dois synthétiser un polymère qui va permettre de changer la nature de la surface de silice. Ce processus ce fait en plusieurs étapes et avec différentes techniques en laboratoire.
Je dois ensuite greffer ce polymère sur la surface, avec encore une fois plusieurs étapes à effectuer en laboratoire.
Pour finir il faut caractériser cette surface pour conclure de l’efficacité ou non de notre projet. Plusieurs technique seront utilisé, pour caractériser l’épaisseur, la nature et l’efficacité de notre surface face à la stimulation extérieure.

Nurturing Good Beginnings: Evaluating and Assessing the YWCA’s community care program for new mothers/birthing parents

The YWCA aims to evaluate, through partnership with McMaster University, the impact of Good Beginnings, a program providing support for mothers/birthing parents who are vulnerable, precarious, and at-risk for postpartum depression. The program provides service for approximately 70 postpartum people and their babies annually, for a total of 500 people since 2014. During these six years, the YWCA has collected entrance, mid, and exit data from program participants. The research partnership will analyze these data, determine the strengths of the program, and set the foundations for ongoing evaluation and best practices to further meet the needs of the community. The primary goal of this project is to maximize positive social impact among vulnerable populations through quantitative and qualitative impact assessments which will inform the expansion of this and similar programs. This project assessment will provide the YWCA with leverage in the form of tangible results in obtaining sustained program funding.

Elaboration d’un sytème polymerique d’encapsulation d’ARN messager

Le projet consiste à synthétiser un nouveau système d’encapsulation d’ARN messager. L’objectif est donc de développer un matériau polymère plus stable et moins coûteux pour son utilisation dans des applications comme les vaccins à ARN messager. Grâce à ce nouveau système nous espérerons rendre les traitements plus efficace lors de leur insertion dans le corps humain.

Pour qu’un système d’encapsulation soit efficace il faut qu’il respecte trois grands points :
– le premier est la protection du l’ARN car ce dernier doit pourvoir atteindre les cellules sans être dégradé dans le corps.
– le second est une bonne fonction de ciblage puisque l’ARN doit pouvoir être conduit vers un certain type de cellules pour pouvoir déclencher une bonne réponse immunitaire.
– le troisième est une bonne libération de l’ARN messager dans le cytoplasme de la cellule lorsque notre système d’encapsulation atteint les cellules.

C’est donc à partir de ces trois conditions primordiales que nous allons élaborer un nouveau système polymérique qui, nous l’espérons, sera plus efficace et moins coûteux que ceux utiliser aujourd’hui.

3D Object Detection, Lane Detection and Pose Estimation using RGB Images and LIDAR

The goal of this project is to use information from color cameras, greyscale cameras and LiDARs to detect objects of interest at the farm,as well as estimate the location and orientation of those objects. This research would allow Mojow to develop a 3D object detection system which can be used in their decision making systems. The expertise from the research team at the University of Alberta helps the Mojow team to evaluate the feasibility and reliability of different approaches and algorithms and quickly prototype and test the most promising ones. This ultimately saves significant time for the Mojow development team and allows them to focus on proven concepts with more predictable outcomes.