The development of common European data spaces is the bedrock of the future European data economy, which could bring huge benefits, but also poses significant challenges and risks. Hence, it is vital to perform research on how common European data spaces should be governed by appropriate rules. DGIP-CEDS aims to map, analyse and further develop […]
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Enhancing Biophysical Muscle Fatigue Model in the Dynamic Context of Soccer
In the field of muscle fatigue models (MFMs), the prior research has demonstrated success in fitting data in specific contexts, but it falls short in addressing the diverse efforts and rapid changes in exertion typical of soccer matches. This study builds upon the existing model, aiming to enhance its applicability and robustness to dynamic demand […]
Anna Maria Mihel defended her PhD dissertation topic
PhD student Anna Maria Mihel, mag. ing. comp. has defended her PhD dissertation topic entitled “Estimation and prediction of discharges in tidal rivers and estuaries using machine learning” with expected scientific contributions of the proposed research being: A machine learning-based approach for estimation and prediction of water levels and discharges in tidal rivers and estuaries. […]
Prof. dr. sc. Renato Filjar participated at the meeting of the 31st National Space-Based Positioning, Navigation and Timing US Advisory Board
Prof. dr. sc. Renato Filjar, as a representative of Croatia, participated at the 31st National Space-Based Positioning, Navigation and Timing US National Advisory Board Meetingat the Sonesta Redondo Beach, Redondo Beach, California, USA (https://www.youtube.com/watch?v=zWwuq6jIIE4&t=6834s)
Pravna tehnologija (Legal Tech) i njezina (ne)prikladnost za zamjenu pravne struke
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 […]
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 […]
