The project will investigate how common distractions, such as cell phone use, impact drivers’ ability to stay attentive and respond appropriately on the road. Using electroencephalography (or EEG) to monitor brain activity, we will look for patterns indicating attention or fatigue during simulated human-vehicle interaction, and classification algorithms will also be used to recognize these […]

Soil and groundwater pollution with harmful petroleum contaminants such as BTEX is a global concern. BTEX has carcinogenic and mutagenic properties, therefore, it is essential to remove such contaminants for a healthy ecosystem. Microorganism-mediated bioremediation is an extremely promising technique that is cost-effective, efficient, and safe for the environment. However, limited biological knowledge about the […]

Recent studies in the field of biodiesel production emphasize the use of waste materials, such as used cooking oils and agricultural by-products like banana peels, to enhance sustainability and reduce environmental impacts. Researchers are exploring innovative methods to utilize these waste materials both as raw materials and catalysts, thereby promoting a circular economy. The latest […]

Potato (Solanum tuberosum) molecular defense response to microbial fungicide Bacillus amyloliquefaciens under greenhouse conditions This project is a collaboration between Dalhousie University and the Arctic University of Norway. Under the tutelage of Dr. Laura Jaakola, Research Leader and professor of plant biology at the Climate Laboratory, the intern will attend the Environmental Molecular Genetics course […]

Prévot : Conception d’un drone multi-tâches d’urgence santé qui inclue un générateur d’oxygène automatisé : initier les bases du programme R&D drone ambulance-brancard qui intègre des composantes monitoring et de traitement comme le générateur d’O2 et produire les premiers plans/plans génériques du drone et du générateur d’O2 automatisé. Poulet : Amélioration des inventions de Stéphane […]

La consommation d’énergie résidentielle est responsable d’une part considérable des émissions de gaz à effet de serre (GES) des ménages. La majeure partie de cette consommation provient de sources d’énergies fossiles. Une transition rapide et profonde de la consommation des énergies fossiles vers des énergies renouvelables et de l’adoption des technologies facilitatrices peut contribuer de […]

This research project will systematically evaluate data-driven mode decomposition techniques (POD, Spectral POD (SPOD), finite impulse response SPOD (FIR-SPOD) and a machine-learning (ML) based nonlinear method) for separating and reattaching flows using existing experimental and numerical databases of a laminar boundary layer approaching an FFS. There will provide three significant results: (1) critical insight as […]

My doctoral research aims to understand the emerging contentions on common good and citizenship in Turkey as an implication of Turkey’s adoption of free market mechanisms in energy production. In my research, I analyze the different legal (courts), material (public participation meetings) and conceptual (posing livelihoods as an alternative to private property) sites these contentions […]

This project is dedicated to enhancing the safety and reliability of cardiovascular disease diagnosis through the innovative integration of Artificial Intelligence (AI) with 4D Flow MRI technology. By applying advanced machine learning algorithms, we aim to improve the precision and dependability of 4D Flow MRI analyses, ensuring more accurate assessments of complex heart blood flow […]

Ce projet vise à développer différents modèles d’algorithmes d’apprentissage automatique afin de planifier la production hydroélectrique à court terme. La résolution de ce problème permet d’obtenir les débits, les volumes et les turbines en marche pour toutes les centrales d’un système de production hydroélectrique. Ayant accès à plusieurs années de données historiques, celles-ci seront exploitées […]

This research project, to be undertaken during a 4-month internship at Arizona State University, aims to develop an artificial chemistry system to investigate the influence of pore system topology on molecular complexity, using Assembly Theory as a measure. The project’s significance lies in its potential to enhance our understanding of Assembly Theory, with implications for […]

The project “Unveiling the Structure of Science: An Information-Theoretic Approach to Co-citation Analysis” aims to advance our understanding of the interconnected landscape of scientific research by applying principles of information theory to co-citation networks. By identifying significant intellectual linkages across disciplines, countries, and institutions, this research seeks to illuminate the underlying patterns and dynamics that […]