Efficient hydrogen (H2) storage remains a major challenge for clean energy applications. This study presents an AI-driven methodology to optimize H2 storage in porous carbon adsorbents. A comprehensive dataset of 917 literature-derived entries was used to develop two machine learning models: Random Forest …

Methane, the primary component of natural gas, emits less carbon dioxide than other petroleum-based fuels but faces challenges in efficient storage and transportation. Advanced adsorption materials provide a safe and cost-effective solution, with metal–organic frameworks (MOFs) emerging as promising …

In this study, eye-tracking and deep learning are employed to classify pilot experience during a twin-engine Piper Seneca flight simulator based on the potential to enhance aviation training and safety through the integration of human cognitive behaviors with artificial intelligence to optimize inter-cognitive …

This paper presents a case study where a model predictive control (MPC) logic is developed for energy flexible operation of a space heating system in an educational building. A Long Short-Term Memory Neural Network (LSTM) surrogate model is trained on the output of an EnergyPlus building simulation model. …

The tourism industry is a major economic sector worldwide, significantly contributing to job creation and GDP growth. However, the rapid expansion of this industry, along with rising environmental and social concerns, underscores the critical need for sustainable strategies. This paper presents a novel …

The increasing interest in Aronia melanocarpa berries for their antioxidant properties sets the necessity to define sustainable strategies to valorize the by-products. This study investigates the use of supercritical carbon dioxide (scCO2) extraction, with and without ethanol as a co-solvent, for recovering …

This research explored the use of deep learning to classify impact events on wind turbine blades using spectrogram images. Audio data were recorded through indoor and outdoor simulations using smartphones. The data preparation process involved converting stereo recordings to mono, applying downcasting …

Dit project richt zich op de ontwikkeling van een robuust en energiezuinig Automatic Meter Reading (AMR)-systeem voor analoge meters in industriële omgevingen. Het systeem maakt gebruik van beeldherkenning om meterstanden automatisch uit te lezen, zelfs onder uitdagende omstandigheden zoals slechte verlichting, …

Designing lead-free piezoelectric ceramics with tailored electrical properties remains a critical challenge for various applications. In this paper we present a novel methodology integrating Machine Learning (ML) and optimization procedures to fine-tune electrical properties in lead-free (1-x) Na0.5 …

Continuous brain function monitoring in a pediatric intensive care unit is often done using electroencephalography (EEG) for the detection of epileptic seizures in comatose patients. Monitoring an EEG is a time-intensive task for medical professionals, especially when the seizures manifest in a subtle …