SARS-CoV-2 lineage abundance quantification in wastewater: a benchmark study for the identification of optimal reference set design

Lineage abundance estimation of SARS-CoV-2 in wastewater is a technique that aims to monitor the lineage prevalence in communities and help contain the COVID-19 pandemic. Lineages are collections of closely related mutants of a virus. It is suggested that the genome sequences of lineages differ across the globe due to random mutations or...

Assessing the Suitability of Panako for Music Identification in Movies

Audio fingerprinting is a technique that allows for fast identification of music. Research concerning this technique first emerged around the 2000s and has lead to several applications, like Shazam. More recently, developments in this area have slowed down, even though there are still new challenges emerging. This paper investigates one of these...

Self-­Supervised Learning for Visual Obstacle Avoidance

With a growing number of drones, the risk of collision with other air traffic or fixed obstacles increases. New safety measures are required to keep the operation of Unmanned Aerial Vehicles (UAVs) safe. One of these measures is the use of a Collision Avoidance System (CAS), a system that helps the drone autonomously detect and avoid obstacles....

A Benchmark Study on Operational Modal Analysis System Identification Algorithms for Operating Offshore Wind Turbines

Recently, Offshore Wind Turbines (OWT) have attracted great attention in an effort to make a shift from fossil-based energy sources towards an enhanced sustainable and renewable energy production. In order to achieve the renewables targets and reduce the cost of wind energy, OWTs are consistently increasing in size. Therefore, research has...

Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms

In this paper, a novel modeling framework for forecasting electricity prices is proposed. While many predictive models have been already proposed to perform this task, the area of deep learning algorithms remains yet unexplored. To fill this scientific gap, we propose four different deep learning models for predicting electricity prices and...