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This project focuses on enhancing agricultural resilience to climate change by incorporating neural network-based optimization into weather index insurance designs. By utilizing advanced machine learning techniques, the initiative aims to improve the accuracy and appeal of insurance products for the agricultural sector, which is highly vulnerable to climate-induced weather unpredictability. The collaboration involves academia and […]

ICG has developed proprietary LiDAR based software to quantify carbon sequestration in every individual tree across large landscapes. This technology promises to bring unbiased and verifiable accounting to the rapidly evolving forest carbon offset sector. The Intern will work with ICG software developers to incorporate and optimize allometric equations for specific areas of interest. The […]

The PACMAN Study seeks to understand experiences and satisfaction with care and outcomes of children and youth who used mental health services as well as their parents and caregivers at the above-mentioned hospitals, including an economic evaluation conducted by the IHE on the impact of the intervention on healthcare resource use and costs in youth […]

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The objective of the research project is to study an efficient and fast way to calculate values of some parameters which are hard to be estimated in nature in relation to dengue, they are: the biting rate, probability that a host to get infected, probability that a vector to get infected. These parameters are needed […]

Through a method of mathematical modeling, we intend to obtain essential data to determine the risk of non-immune tourists acquiring dengue during the stay of these tourists in Brazil in the 2014 FIFA World Cup in 12 host cities, and in the 2016 Summer Olympics that is Rio de Janeiro as the host. In 2014, […]

Visceral leishmaniasis is one of the world deadliest and neglected infectious diseases. Therefore, it is important elaborating a good strategic control for this disease. In this project, our general objectives include how to plan the optimization of visceral leishmaniasis control, taking into account the economic approach. This research will not involve experiments and clinical study. […]

During the previous Mitacs PhD internship (IT11500), a long short-term memory encoder-decoder (LSTM-ED) neural network survival model was developed to predict time to debt repayment for ATB collections customers. This model is novel from both methodological and practical perspectives. The LSTM-ED simultaneously predicts the probability that debt will be repaid within the first 90 days […]

Ion-exchanged or chemically tempered glass such as Corning’s Gorilla glass was a break-through in the design and production of high toughness glass. However, the pace of improvements brought in by this technology is levelling off. Recently, the industry has turned to another approach to product tough glass: the addition of small crystalline inclusions. However, this […]

The aim of this internship is to carry out an analysis of the equations modelling the distribution function of sea ice thickness, particularly in the case of large deformations such as ridges. Among other things, we will be interested in the numerical solutions of these equations, their stability and their consistency.

Le département de Prévision et Analytique de TD Assurance est actuellement en charge de prédire les ventes et les revenues des différents produits d’assurance sur une base annuelle et mensuelle. Prédire les revenues, et ceci de manière précise, est crucial pour l’entreprise et son bon fonctionnement. Les modèles jusqu’alors utilisés ont étés construits il y […]