News
Regression-Based Machine Learning Approaches for Estimating Discharge from Water Levels in Microtidal Rivers
The challenges of managing water resources in tidal rivers, exacerbated by climate change and anthropogenic impacts, require innovative approaches for accurate estimation of hydrological parameters. In tidal rivers and estuaries, water levels depend primarily on river discharge and tidal dynamics. Microtidal estuaries are particularly complex due to the strong stratification and two-layer structure, which also […]
Interpretable Machine Learning: A Case Study on Predicting Fuel Consumption in VLGC Ship Propulsion
The integration of machine learning (ML) in marine engineering has been increasingly subjected to stringent regulatory scrutiny. While environmental regulations aim to reduce harmful emissions and energy consumption, there is also a growing demand for the interpretability of ML models to ensure their reliability and adherence to safety standards. This research highlights the need to […]
Recursively Autoregressive Autoencoder for Pyramidal Text Representation
We introduce Pyramidal Recursive learning (PyRv), a novel method for text representationlearning. This approach constructs a pyramidal hierarchy by recursively building representations of phrases, starting from tokens (characters, subwords, or words). At each level, N representations are recursively combined, resulting in N-1 representations on the level above, abstracting the input text from characters or subwords […]
Artificial Intelligence as a Challenge for European Patent Law
The development of AI, particularly complex systems like deep neural networks, sharply cuts into the fabric of patent law, leading to a constant reassessment of existing principles and provisions and their interpretation. Patent law provisions, including the European Patent Convention, were not written with computer programs, let alone AI systems, in mind. While the law […]
Presentation of the NPOO project Peoplet
On June 7th, a presentation was held for the NPOO project Peoplet, funded under the program “Start-up/Spin-off Companies of Young Researchers”. The project leader is Dr. Dino Pitoski, a Ph.D. candidate at the AIRI Center. A ResearchClass was conducted titled “Introduction to CBS NL and the SSW Survey | Peoplet Project: Concept Networks & Organizational […]
Ana Vranković Lacković defended her doctoral thesis
We are happy to announce that on 16th of May, 2024. Ana Vranković Lacković has successfully defended her doctoral thesis, titled “Digital Signal Classification Utilizing Adaptive Information Entropy Measures and Machine Learning,” at the Faculty of Engineering RITEH University of Rijeka.Ana’s thesis is the result of hard work and represents a significant advancement in the […]
Estimating Water Levels and Discharges in Tidal Rivers and Estuaries: Review of Machine Learning Approaches
Understanding the dynamics of tidal rivers and estuaries is critical for reliable water management. Recently, the use of Machine Learning (ML) has increased in favor of hydrologic and hydraulic models. The advantages of ML over physically based models are most evident in modeling complex and nonlinear hydrologic processes and inverse problems. This study provides a […]
Building Individual Player Performance Profiles According to Pre-Game Expectations and Goal Difference in Soccer
Soccer player performance is influenced by multiple unpredictable factors. During a game, score changes and pre-game expectations affect the effort exerted by players. This study used GPS wearable sensors to track players’ energy expenditure in 5-min intervals, alongside recording the goal timings and the win and lose probabilities from betting sites. A mathematical model was […]
Aiming at Well-Being with Brain Implants: Any Risk of Implanting Unprecedented Vulnerabilities?
Many experimental brain-computer interfaces (BCIs) are currently being medically tested in paralyzed patients. While the new generations of implantable BCIs move rapidly ahead at trying to increase the patients’ well-being, ethical concerns about their potential effects on patients’ psychological dimensions (e.g. sense of agency and control) are growing. An important ethical concern to explore is […]
