Predicting Vessel Motions: A Comparative Analysis of Machine Learning and Conventional Approaches

Founded in 1910, Boskalis, a leader in offshore operations, contends with limitations in ABB's Ability Marine Advisory System 'OCTOPUS' in predicting maximum vessel motions for heavy-transport vessels (HTVs). Accurate prediction of these motions, especially roll and pitch, is vital for transporting large, heavy structures, as exceeding...

An AI algorithm to predict intubations in ICU patients: Predicting intubation to aid medical personnel in the decision to switch from High Flow Nasal Oxygen therapy to intubation

Maasstad Hospital is a member of the Santeon hospital group. The ambition of Santeon is to improve healthcare for patients. The project in this internship also aims to improve patients’ health, specifically patients in the Intensive Care Unit (ICU).<br/>The treatment of respiratory insufficient patients in the ICU consists of High Flow Nasal...

Predicting the stability of distal radius fractures with a small dataset and machine learning

Purpose. Distal radius fractures are common fractures of the wrist. These fractures are often displaced and need reduction, after adequate reduction, the patients will have follow-up X-rays to check if the fracture stays stable. This is important because surgery might be required if the fracture becomes unstable. This can lead to delayed surgery...

COVID-19 Prediction and Mitigation

With the world in grasp of the COVID-19 pandemic, models predicting the spread of the virus can give indications to what extent a country is controlling the pandemic. Policymakers can decide to install so-called mitigation strategies to limit the spread of the virus. To aid the decision-making process, this report describes how a web application...

Modeling Inference Time of Deep Neural Networks on Memory-constrained Systems

Deep neural networks have revolutionized multiple fields within computer science. It is important to have a comprehensive understanding of the memory requirements and performance of deep networks on low-resource systems. While there have been efforts to this end, the effects of severe memory limits and heavy swapping are understudied. We have...

Prediction of flow-fields by combining high-fidelity CFD data and Machine Learning algorithms

High-fidelity optimisation studies are a useful asset in the design of critical components for large gas turbines. These studies require the computation of numerous computationally expensive CFD simulations and result in predominantly optimisation graphs of design objectives (e.g. Pareto-front figure). The quantity of generated data is...

Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction

Being capable to foresee the future of a given financial asset as an investor, may lead to significant economic profits. Therefore, stock market prediction is a field that has been extensively developed by numerous researchers and companies. Recently, however, a new branch of financial assets has emerged, namely cryptocurrencies. As a...

ETA prediction: Predicting the ETA of a container vessel based on route identification using AIS data

Container vessels arriving in a port before or after their scheduled time can cause problems in the container terminal planning and planning of hinterland transportation. This in turn leads to an increase of the costs in the supply chain. Vessels communicate their Estimated Time of Arrival via Automatic Idetification System(AIS) data to the port...