Data-analisten van de KNLTB voeren wedstrijdanalyses uit op video’s van tenniswedstrijden van concurrenten. Dit wordt gedaan om inzicht te krijgen in de tactiek zodat trainers en coaches eigen tennissers kunnen voorbereiden. De resultaten uit de analyses worden door de data-analisten met de trainingsstaf …

Inleiding: Uit wetenschappelijk onderzoek blijkt dat er variatie bestaat in de interne belasting die voetbalspelers ervaren, zelfs bij een gelijke externe belasting(Castagna et al., 2011). De fysieke capaciteiten van professionele voetballers kunnen hier invloed op hebben (Rabbani, et al., 2021). Dit …

Here, we delve into Demand Forecasting via Machine Learning, dissecting how to predict future demand using time-sensitive data. Westveer highlights key forecasting models, from the basic Simple Exponential Smoothing to the advanced SARIMA, applied to an electricity production dataset. The session, encapsulating …

This chapter takes a closer look at the case of Amsterdam as a particular manifestation of a film festival city. Drawing from a new dataset on festivals in the Netherlands, the data supports the view of film festivals as a highly dynamic cultural sector: Internationally acclaimed film festivals exist …

With the proliferation of misinformation on the web, automatic methods for detecting misinformation are becoming an increasingly important subject of study. If automatic misinformation detection is applied in a real-world setting, it is necessary to validate the methods being used. Large language models …

This paper presents data-driven insights from a case study that was carried out in an University EV charging plaza where EV charging demand is met with the combination of the University campus grid and installed solar capacity. First, we assessed the plaza dependency on the grid for meeting EV charging …

Background Physical exercise in cancer patients is a promising intervention to improve cognition and increase brain volume, including hippocampal volume. We investigated whether a 6-month exercise intervention primarily impacts total hippocampal volume and additionally hippocampal subfield volumes, cortical …

Although causal inference has shown great value in estimating effect sizes in, for instance, physics, medical studies, and economics, it is rarely used in sports science. Targeted Maximum Likelihood Estimation (TMLE) is a modern method for performing causal inference. TMLE is forgiving in the misspecification …

Estimating the remaining useful life (RUL) of an asset lies at the heart of prognostics and health management (PHM) of many operations-critical industries such as aviation. Mod- ern methods of RUL estimation adopt techniques from deep learning (DL). However, most of these contemporary tech- niques deliver …

Completeness of data is vital for the decision making and forecasting on Building Management Systems (BMS) as missing data can result in biased decision making down the line. This study creates a guideline for imputing the gaps in BMS datasets by comparing four methods: K Nearest Neighbour algorithm …