Inspired by the recent development of autonomous artificial intelligence (AI) systems inmilitary and medical applications I envision the use of one such system, an AI-empowered exoskeleton smart-suit called the Praetor Suit, to question the important ethical issues stemming from its use. The Praetor Suit would have the ability to monitor the service member’s physiological and […]
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European Network for assuring food integrity using non-destructive spectral sensors
There is an increasing need for the food industry to provide information on their products in order to satisfy quality standards and to protect their products from food fraud. Recent developments in technology, and advances in big data analytics, provide the opportunity for step-changes that can transform the role of food integrity assurance from one […]
Rapid prediction of earthquake ground shaking intensity using raw waveform data and a convolutional neural network
This study describes a deep convolutional neural network (CNN) based technique to predict intensity measurements (IMs) of earthquake ground shaking. The input data to the CNN model consists of multistation, 3C acceleration waveforms recorded during the 2016 Central Italy earthquake sequence for M ≥ 3.0 events. Using a 10 s window starting at the earthquake origin time, we find […]
AIRI Center at the CroAI (Croatian AI Association)
How to increase collaboration between the academia and (IT) industry? Discussed at the CroAI (Croatian AI Association) online meeting while presenting the UNIRI Center for AI and Cybersecurity.
Online meeting of the AIRI Center
Online meeting of the UNIRI Center for Artificial Intelligence and Cybersecurity held on 27th of May, 2020 with an exciting presentation of the research on ML-based computer vision done by the team of Assoc. prof. Dr. sc. Marina Ivašić-Kos
Corpus-Based Paraphrase Detection Experiments and Review
Paraphrase detection is important for a number of applications, including plagiarism detection, authorship attribution, question answering, text summarization, text mining in general, etc. In this paper, we give a performance overview of various types of corpus-based models, especially deep learning (DL) models, with the task of paraphrase detection. We report the results of eight models […]
National Competence Centres in the Framework of EuroHPC (EUROCC)
H2020-JTI-EuroHPC-2019-2
A Novel Approach to Extracting Useful Information From Noisy TFDs Using 2D Local Entropy Measures
The paper proposes a novel approach for extraction of useful information and blind source separation of signal components from noisy data in the time-frequency domain. The method is based on the local Rényi entropy calculated inside adaptive, data-driven 2D regions, the sizes of which are calculated utilizing the improved, relative intersection of confidence intervals (RICI) […]
Time-dependent numerical model for simulating internal oscillations in a sea organ
This paper presents a one-dimensional time-dependent numerical model of a sea organ, which generates music driven by the motion of the sea. The governing equations are derived by coupling hydrodynamic and thermodynamic equations for water level and air pressure oscillations in a sea organ pipe system forced by irregular waves. The model was validated by […]
Cyber Security of Maritime ICT-Based Systems
With the growing reliance on the Information and Communication Technologies (ICT) technologies, maritime cyber risk management becomes increasingly important. Managing the maritime cyber risk would allow not only data protection, but as well as safe and reliable ship operations and maritime transport. Recently, the International Maritime Organization (IMO) has published the Guidelines on high-level recommendations […]
