Improved frameworks for delivering both intelligence and effectiveness under strict constraints on resources are required due to the Internet of Things’ (IoT) devices’ rapid expansion and the resulting increase in sensor-generated data. In response, this research considers a joint learning-offloading optimization approach and presents an improved framework for energy-efficient distributed intelligence in sensor networks. Our […]
Research Papers
Forecasting the Trajectory of Personal Watercrafts Using Models Based on Recurrent Neural Networks
Monitoring and predicting personal watercraft trajectories is a novel and largely unexplored research area where any development is valuable for various rental services. Unlike existing work focused on specific maritime routes, this study introduces a location-agnostic deep-learning approach capable of generalizing across diverse environments. This is achieved by using an innovative preprocessing approach including offset […]
A System for Real-Time Detection of Abandoned Luggage
In this paper, we propose a system for the real-time automatic detection of abandoned luggage in an airport recorded by surveillance cameras. To do this, we use an adapted YOLOv11-s model and a proposed algorithm for detecting unattended luggage. The system uses the OpenCV library for the video processing of the recorded footage, a detector, […]
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 […]
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 […]
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 […]
