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 […]
Research Papers
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 […]
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 […]
From Time–Frequency to Vertex–Frequency and Back
The paper presents an analysis and overview of vertex–frequency analysis, an emerging area in graph signal processing. A strong formal link of this area to classical time–frequency analysis is provided. Vertex–frequency localization-based approaches to analyzing signals on the graph emerged as a response to challenges of analysis of big data on irregular domains. Graph signals […]
Motivational Elements in Computer Games for Learning Mathematics
One of the main drawbacks of delivering new teaching lessons in e-learning systems is the lack of motivation for using those systems. This paper analyses which elements of computer games for learning mathematics have a beneficial effect on intrinsic motivation and give students continuous feedback in order to improve the learning process. While the control […]
Towards A Regulatory Framework for Artificial Intelligence – An EU Approach
The digital revolution facilitates innovation models that generate new markets and business models. Together with Internet, it has opened up a vast array of new possibilities. Latest reappearance of the artificial intelligence has created further potentials and types of market participation. Artificial intelligence is understood as a cutting-edge technology and a key-driver of transition of […]
Augmenting Around-Device Interaction by Geomagnetic Field Built-in Sensor Utilization
In this paper, we investigate the possibilities for augmenting interaction around the mobile device, with the aim of enabling input techniques that do not rely on typical touch-based gestures. The presented research focuses on utilizing a built-in magnetic field sensor, whose readouts are intentionally affected by moving a strong permanent magnet around a smartphone device. […]
Predicting Seagoing Ship Energy Efficiency from the Operational Data
This paper presents the application of machine learning (ML) methods in setting up a model with the aim of predicting the energy efficiency of seagoing ships in the case of a vessel for the transport of liquefied petroleum gas (LPG). The ML algorithm is learned from shipboard automation system measurement data, noon logbook reports, and […]
