Nicotine is a well-known and highly addictive substance with complex effects on cognition, anxiety, and neurophysiology. Despite its short-term anxiolytic effects, this drug often exacerbates anxiety symptoms. It disrupts emotional regulation through its impact on the central nucleus of the amygdala …

A report of an internship done at the University of Aberdeen. I solo developed a mixed reality VR game for a research paper about how cognitively demanding tasks impact long and short term memory. The paper covers topics like: How to help people interact with objects in VR, How to guide novice players …

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. …

This paper investigates the application of neural basis expansion analysis with exogenous variables (NBEATSx) in the prediction of daily stock realized volatility for various time steps. It compares NBEATSx’s forecasting accuracy and robustness with several commonly used models, namely Long-Short Term …

Anomalies in Heating, Ventilation, and Air Conditioning (HVAC) systems of buildings can lead to performance degradation, energy inefficiencies, and occupant discomfort. Automated anomaly detection is essential to prevent these issues. Machine learning based anomaly detection techniques are effective …

This paper introduces and examines a novel realized volatility forecasting model that makes use of Long Short-Term Memory (LSTM) neural networks and the risk metric financial turbulence (FT). The proposed model is compared to five alternative models, of which two incorporate LSTM neural networks and …

In this paper, artificial intelligence tools are implemented in order to predict trajectory positions, as well as channel performance of an optical wireless communications link. Case studies for industrial scenarios are considered to this aim. In a first stage, system parameters are optimized using a …

Machine learning models have proven to be reliable methods in classification tasks. However, little research has been conducted on the classification of dwelling characteristics based on smart meter and weather data before. Gaining insights into dwelling characteristics, which comprise of the type of …

Passenger flow management is an important issue at many airports around the world. There are high concentrations of passengers arriving and leaving the airport in waves of large volumes in short periods, particularly in big hubs. This might cause congestion in some locations depending on the layout of …

Passenger flow management is an important issue at many airports around the world. There are high concentrations of passengers arriving and leaving the airport in waves of large volumes in short periods, particularly in big hubs. This might cause congestion in some locations depending on the layout of …