Though the problem of water risks is growing and becoming more evident, there is a lack of structured information about how these risks are managed through the certification process. While there are certain credits dedicated to managing water risks and implementing measures in regard to them in the …

Background/Objectives: Digital technologies and data-driven approaches are rapidly transforming healthcare practice and enabling more personalized and preventive care. As personal health data becomes increasingly embedded in healthcare systems, understanding how future healthcare professionals interpret …

This thesis investigates the development of internal shear stresses in stiffened-core deep composite pile foundations, with particular focus on the FUNDEX Combi Pile system. These piles are widely used in urban environments due to their vibration-free installation and ability to perform under challenging …

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 …

Power-to-X technologies play a crucial role in accelerating the energy and material transition. A key opportunity lies in integrating these systems with existing bio-based infrastructures such as anaerobic digesters, providing a reliable source of biogenic carbon. Developing effective Power-to-Methanol …

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 …

Industrial Cyber-Physical Systems (CPS) are sensitive infrastructure from both safety and economics perspectives, making their reliability critically important. Machine Learning (ML), specifically deep learning, is increasingly integrated in industrial CPS, but the inherent complexity of ML models results …

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 …

Aviation safety relies greatly on understanding human factors and pilot behaviour. This study uses innovative eye-tracking biometrics and predictive analytics to enhance aviation landing performance in a twin-engine Piper Seneca simulation. With a Tobii Glass 3 eye tracker, gaze patterns from two pilots …

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 …