Published:
We present Bézier Evolve and Refine Strategy (BERS), a two-stage framework that combines global evolutionary search with local variational refinement for maritime weather routing.
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Published:
A transparent, scenario-based method to adjust projected life tables for temperature-related mortality, with uncertainty carried through to annuities, life insurance and reserves.
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This paper presents statistical and machine learning analyses over a large dataset of LNG and LPG ships to improve the accuracy of early-stage vessel design.
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HADAD conducts a global exploration using an A* search on a hexagonal grid with higher-order neighbors, then refines the solution using a discrete Newton-Jacobi variational method.
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A novel Hybrid Search algorithm is introduced to address Zermelo’s Navigation Problem, demonstrating improved efficiency and real-world applicability.
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In this study we apply Tun-AI to study the aggregation times and behavioural patterns of tuna around drifting Fish Aggregating Devices (dFADs).
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Published:
We estimated the association between the level of restriction in nine different fields of activity and SARS-CoV-2 transmissibility in Spain, from 15th September 2020 to 9th May 2021.
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Non-Intrusive Load Monitoring (NILM) aims to predict the status or consumption of domestic appliances in a household only by knowing the aggregated power load.
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In this work we introduce NeoCam , an open source hardware-software platform for video-based monitoring of preterms infants in Neonatal Intensive Care Units (NICUs).
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Published:
Tun-AI is a Machine Learning model aimed at predicting tuna biomass under a given buoy, using echo-sounder and oceanography data.
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