Vessel Performance Evaluation Using A Digital Twin: A Black-box Model Approach

An important step in determining the performance of a commercial ship is to determine the vessel fuel consumption in offdesign conditions. In previous studies, the vessel fuel consumption is obtained using machine learning algorithms which use navigational data and meteorological data to train the models. Due to the inaccuracy of the weather...

Classification Algorithm for Early Detection of Atrial Fibrillation: The Development of a Supervised Learning Method Using Photoplethysmography Signals for an ARM Processor

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia occurring in around 0.5% of the world population. AF is characterized by the rapid and irregular beating of the atrial chambers of the heart, which can cause lead to strokes and other heart-failures. To prevent these consequences the early detection of AF is paramount. Using...

Detecting Rumors in Twitter for Humanitarian Activities

In this Master Thesis project, the objective is to study how can Supervised Machine Learning be used to detect text-based rumours for humanitarian activities in Twitter. A model was developed in this project in order to classify a tweet at question whether is a rumour or not and whether is relevant to humanitarian activities or not. The findings...