Background: Online media plays an important role in public health emergencies and serves as a communication platform. Infoveillance of online media during the COVID-19 pandemic is an important step toward a better understanding of crisis communication. Objective: The goal of this study is to perform a longitudinal analysis of the COVID-19 related content based on natural language […]
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Assoc. prof. dr. sc. Jonatan Lerga presented AIRI Center at the IEEE Rijeka : Computer Society Congress 2021
AIRI Center participated in the IEEE Rijeka: Computer Society Congress 2021 on 15th of November, 2021, with Assoc. Prof. Jonatan Lerga, Ph.D. presenting Center and research results in 2020-2021.
Multivariate Decomposition of Acoustic Signals in Dispersive Channels
We present a signal decomposition procedure, which separates modes into individual components while preserving their integrity, in effort to tackle the challenges related to the characterization of modes in an acoustic dispersive environment. With this approach, each mode can be analyzed and processed individually, which carries opportunities for new insights into their characterization possibilities. The […]
Cast suppression in radiographs by generative adversarial networks
Injured extremities commonly need to be immobilized by casts to allow proper healing. We propose a method to suppress cast superimpositions in pediatric wrist radiographs based on the cycle generative adversarial network (CycleGAN) model. We retrospectively reviewed unpaired pediatric wrist radiographs (n = 9672) and sampled them into 2 equal groups, with and without cast. […]
Deep Semi-Supervised Algorithm for Learning Cluster-Oriented Representations of Medical Images Using Partially Observable DICOM Tags and Images
The task of automatically extracting large homogeneous datasets of medical images based on detailed criteria and/or semantic similarity can be challenging because the acquisition and storage of medical images in clinical practice is not fully standardised and can be prone to errors, which are often made unintentionally by medical professionals during manual input. In this […]
Postoji li potreba pravnog uređenja umjetne inteligencije u europskoj uniji – razlozi za i protiv
Umjetna inteligencija je sve više dio naše svakodnevnice. Sastavni je dio našega poslovnog okruženja, obrazovanja, kućanstva, svakodnevnog iskustva i slobodnog vremena. Predviđa se da će biti jedan od najvećih pokretača gospodarskoga rasta. Dok je prije nekoliko desetljeća možda i bila dvojba treba li ta pitanja uopće regulirati, današnji ubrzani razvoj nameće potrebu razmatranja pristupa i […]
Exploiting Peptide Self-Assembly for the Development of Minimalistic Viral Mimetics
Implementing M-Learning System for Learning Mathematics Through Computer Games and Applying Neural Networks for Content Similarity Analysis of an Integrated Social Network
In order to make e-learning systems widely available, the majority of new systems are being developed in a form suitable for m-learning. The system implemented in this research uses educational computer games for learning Mathematics in primary schools and has an integrated social network, which is used for communication and publishing game-related content. The system […]
Cognitive Predispositions of Students for STEM Success and Differences in Solving Problems in the Computer Game for Learning Mathematics
STEM education forms a basis for an innovation-based society, and Mathematics is, besides being an integral part of STEM, also a prerequisite for success in mastering remaining STEM constituents. With the aim of early detection of gifted students, who would be able to follow advanced forms of teaching and be successful in STEM, this paper […]
Detecting Students Gifted in Mathematics with Stream Mining and Concept Drift Based M-Learning Models Integrating Educational Computer Games
One of the problems of individualized classes which adapt contents and methods of teaching to students of different cognitive capabilities is early and widely available detection of students gifted in certain educational fields. The paper proposes models which are based on stream mining and which can detect students gifted in Mathematics solely on the basis […]
