Innovative Projects Realized

Re-inhabiting Lives, Uncomfortable Histories: Armenian Women Immigrants in Turkey

The research I wish to pursue for my research in Turkey seeks to explore following questions: How are the subjectivities of undocumented Armenian women immigrants shaped in the face of multi-layered discrimination and exclusion? What is the role of Turkish media and Turkish cinema in this discrimination? My inquiry into the ways in
which undocumented Armenian women immigrants are rejected at an institutional level yet welcomed in the domestic work sector and the sex trade will illuminate how historical forces, such as the genocide, and social forces, such as attitudes of the Church and Turkish Armenians, shape gendered experience. For this purpose, I plan to
conduct a discourse analysis on how this issue is represented in Turkish media and Turkish cinema. Secondly I will investigate the legal arrangements regarding Armenian women immigrants, scrutinizing the latest arrangements regarding irregular migration in Turkey.

L2M – ACTIVELY SOBER AI MODEL FILTER FOR INFLUECES IN SUPPORT OF ALCOHOL CONSUMPTION

The Actively Sober app is an ambitious project that combines advanced artificial intelligence with a keen understanding of cultural nuances to address the widespread issue of alcohol misuse. By employing AI algorithms that continuously scan digital platforms to identify and block alcohol-related content, the app aims to create a supportive environment for users, helping them make healthier choices in their specific cultural and social contexts. With a clear set of objectives, including target population profiling, user needs assessment, and prototype development, this project is positioned to be a powerful tool in the global effort to promote sobriety and combat the negative impacts of alcohol misuse, ultimately contributing to improved public health and well-being.

Integrating Deep Learning and Machine Learning Techniques for Maize Yield Monitoring with Earth Observation and Climate Data to Ensure Food Security in Dry Regions

Our project aims to improve maize production efficiency and mitigate the impacts of climate change. By combining advanced computing, artificial intelligence, and remote sensing techniques, we will analyze data on maize cultivation, climate patterns, and soil health. This collaboration between institutions in both countries seeks to enhance agricultural sustainability, increase food security, and contribute valuable insights to global efforts addressing climate challenges. The participating institutions stand to benefit from shared expertise, fostering innovation in agricultural practices, and establishing a foundation for ongoing collaboration in addressing shared environmental concerns.

Static and Fatigue Properties of FDM-3D Printed Metallic Materials and Lattice Structures

3D printing is versatile and time-saving to fabricate parts with complex structures. It is an essential supplement to conventional processes for metal components. But, the high cost of metal 3D printing severely limits their industrial applications. Recently, the Fused Deposition Modeling (FDM) method can 3D print metals at a lower price. The composite filament contains metal powder evenly distributed within the binder matrix. The melting filament is then deposited onto a build platform. In 3D printing, each layer hardens as it is deposited and bonds to the previous layer. The full metal parts are obtained by the following debinding and sintering process. Yet, metal FDM-3D printing has not been thoroughly studied. This project will unveil the mechanical performance of FDM-3D printed metal components. Their static and fatigue properties will be studied analytically, numerically, and experimentally. The fabrication defects and their impact on material performance will be identified. The knowledge gained will be applied in lattice structure development. The research outcome will improve metal 3D printing and reduce manufacturing costs.

Automation of next generation photovoltaic measurement capabilities

The proposed research project at the Turak Functional Nanomaterials Research group at Concordia aims to enhance the efficiency of solar energy data measurement and analysis from emerging solar cell technologies. In a world increasingly focused on sustainable energy sources, efficient utilization of solar power is paramount. The lab manages vast data, including complex images of nanoparticle arrays, mapping “dark” spots in active layers, and high-throughput current-voltage data crucial for optimizing solar cells. However, the measurement and analysis methods are time-consuming and often require manual intervention at multiple points in the process.

The primary objective of this project is to simplify and automate these processes. User-friendly graphical interfaces will make data measurement and analysis accessible to all. Additionally, program reliability will be enhanced with a universal control system for efficient management of various tools. The team also plans to explore machine learning techniques to extract design rules for optimal nanoparticle arrays used as interfacial tuning layers, promising a leap in the efficiency and precision of solar cell development. This project is a step toward an era where harnessing solar power is not only efficient but seamlessly integrated into our lives, furthering the global shift toward sustainable energy solutions.

Governance, Diversity, and Social Justice – The 1991 Soviet Putsch attempt

The overarching goal of the Globalink research project is to gain a comprehensive understanding of the 1991 Soviet coup attempt by delving into the motivations, strategic decisions, and enduring implications of this pivotal event.
The central research question guiding this endeavor will have answers to such questions: What were the underlying motivations and strategic decisions made by the plotters of the 1991 Soviet coup, and how did the coup’s failure shape the trajectory of the Soviet Union and subsequently, post-Soviet Russia?

International collaboration between Canada and Australia integrating STEM education in schools

The objective of the SILO research project is to bridge the gap between theory and practice in STEM education by trialing the various STEM units in classrooms. A sub-objective of the SILO research project is to critique and refine the units according to the principles of Provisional Multimodal Research (PMR) in the context of creating artefacts.
Recognizing the global priority of enhancing STEM education outcomes, the SILO project aims to address the fragmented landscape of STEM initiatives by introducing a cohesive scope and sequence of STEM concepts. Currently undergoing a trial in a K to 6 state school in NSW, this initiative is built upon Bruner’s (1960) spiral curriculum, emphasizing the iterative nature of STEM education. The central focus of this proposal is to contribute provisional data that reflects the ongoing refinement of STEM concepts.
Trialing the SILO project in Canada will result in two different versions of the same project as they will start with a duplicate version of the existing project. Any variations between the two contexts will constitute new knowledge as the chosen methodology requires access to all iterations of the 28 units and a rationale for any changes made.

Improving stream temperature simulation in UK rivers by adding shading effects into a coupled hydrological/water temperature model

Le projet a pour objectif de modéliser l’ombrage et la température de l’eau sur des cours d’eau du Royaume Uni. Différents algorithmes seront testé et comparés. Ce projet permettra d’offrir aux gestionnaires de ressources hydriques un outil permettant de prioriser les cours d’eau à protéger en fonction de leur propension à maintenir un eau plus froide.

Vulnérabilité de l’eau souterraine en zone amont de bassin versant au moyen des temps de séjour et de la qualité de l’eau souterraine – Exemple du mont Covey Hill

Les territoires qui alimentent les aquifères et la dynamique de renouvellement de l’eau souterraine sont encore peu connus, ce qui entraîne de grandes incertitudes sur la vulnérabilité de la ressource. Les objectifs de ce projet sont de tester de nouvelles méthodes pour 1) comprendre combien de temps l’eau souterraine a circulé avant de refaire surface et 2) pour évaluer s’il est possible de mieux évaluer les polluants entraînés dans l’eau souterraine et qui font résurgence dans les milieux humides et les sources. Le projet se déroulera au Laboratoire naturel du mont Covey Hill, situé au Québec à la limite des Adirondacks. Certaines portions du site sont protégées par Conservation de la nature Canada, tandis que d’autres sont utilisées pour la pomiculture. Le projet permettra de mieux identifier la vulnérabilité de l’eau souterraine, et de cibler les secteurs à protéger pour assurer le renouvellement de l’eau souterraine, assurer sa qualité et maintenir les habitats d’espèces vulnérables.

Fallback food foraging skills for survival: capuchins in captive release and wild habitats

Our research project aims to contribute to capuchin monkey conservation in Brazil. These monkeys are struggling due to the loss of their natural habitats and the illegal pet trade. We are looking at how they use fallback foods (FBF) — things they eat when their usual food isn’t available — to survive. We will map where these foods are, study how capuchins find and eat them in the wild, and observe how capuchins in rescue centers use these foods. By doing this, we hope to learn how to protect capuchins better and make sure they can find enough to eat, both in the wild and when they’re released back into nature after being rescued. This project will contribute to the developing partnership between primatologists Dr. Sarah Turner in Canada and Dr. Renata Ferriera in Brazil. It is expected to yield a series of peer-reviewed publications that will showcase the joint expertise and research findings of both teams, fostering an international exchange of knowledge and methodologies in primatology and conservation science.

The development of a targeted delivery system for saRNAs for immunotherapy of monocyte-derived leukemia

Immunotoxins (ITs) are representing a subset of antibody drug conjugates where the synthetic toxin is replaced by a bacterial protein toxin. Major drawback is related to the immunogenicity of the protein not allowing repeated application. Consequently targeted human cytolytic fusion proteins (hCFPs) have been developed to replace the foreign protein toxin by a human apoptosis inducing enzyme exemplified by human angiogenin (hAng). Currently such hCFPs show reduced cytotoxicity compared to ITs, as it depends on efficient delivery of sufficient amounts into the cytosol. Therefore, this collaboration research planned to develop a targeted saRNA delivery system to introduce hAng encoding saRNA into the cytosol of an antigen-positive target cell. saRNA produces copies of itself which should increase the amount of enzyme to effectively kill a cancer cell.

Methods: eGFP/hAng encoding saRNA sequence will be cloned into a plasmid. The linearized vector will be transcribed and purified using LiCl. Purified saRNA will be encapsulated in a lipid nanoparticle decorated with CD64-specific antibody fragments. The LNP-eGFP-saRNA conjugates will be delivered into CD64-positive leukemia cell lines. Once proof of concept is confirmed the saRNA encoding eGFP will be replaced by saRNA encoding hAng for selective elimination of monocyte-derived leukemia cells.

Automated Software Vulnerability Patching using Dynamic Symbolic Traces

Deep learning (DL) has emerged as a viable means for identifying software bugs and vulnerabilities. The success of DL relies on having a suitable representation of the problem domain. However, existing DL-based solutions for learning program representations have limitations – they either cannot capture the deep, precise program semantics or suffer from poor scalability. We plan to provide a DL system to learn program presentations by combining static source code information and dynamic program execution traces. By collaborating in two diverse multicultural research groups, participating institutions in Canada and United Kingdom will benefit from sharing knowledge and expertise in this cutting-edge field of cybersecurity and software engineering. This collaboration will enhance the reputation of these institutions in the security and software engineering communities, attracting top talent and opportunities. Moreover, participants will have the chance to develop new technical skills and social skills, and learn about the state-of-the-art technological innovations in vulnerability detection.