Training researchers with the MOVING platform

The MOVING platform enables its users to improve their information literacy by training how to exploit data and text mining methods in their daily research tasks. In this paper, we show how it can support researchers in various tasks, and we introduce its main features, such as text and video retrieval and processing, advanced visualizations, and the technologies to assist the learning process

A historical perspective of biomedical explainable AI research

The black-box nature of most artificial intelligence (AI) models encourages the development of explainability methods to engender trust into the AI decision-making process. Such methods can be broadly categorized into two main types: post hoc explanations and inherently interpretable algorithms. We aimed at analyzing the possible associations between COVID-19 and the push of explainable AI (XAI) to the forefront of biomedical research. We automatically extracted from the PubMed database biomedical XAI studies related to concepts of causality or explainability and manually labeled 1,603 papers with respect to XAI categories. To compare the trends pre- and post-COVID-19, we fit a change point detection model and evaluated significant changes in publication rates. We show that the advent of COVID-19 in the beginning of 2020 could be the driving factor behind an increased focus concerning XAI, playing a crucial role in accelerating an already evolving trend. Finally, we present a discussion with future societal use and impact of XAI technologies and potential future directions for those who pursue fostering clinical trust with interpretable machine learning models.</p

Cardiovascular reactions to exam situations

The aim of this study was to examine whether the parameters of cardiac R-R intervals reflect the changes in the emotional and mental components of stress during a difficult and an easy exam. Twelve subjects, 18 to 19 years of age, with no previous experience with exams at university level, took part in the study. The levels of anxiety, high activation and exam apprehension were assessed before a difficult and an easy exam. Subjects’ cardiac R-R intervals were continuously registered in the period of five minutes before the exam, during the whole exam, and five minutes after the exam by the Power Lab polygraph. The level of anxiety, high activation and exam apprehension were higher before the difficult exam than before the easy exam. Shorter and more regular R-R intervals were found dur- ing the difficult exam as compared to the easy exam. No significant differences in the spectral analyses parameters were found between the difficult and the easy exam, while the differences were significant between the pre-exam, exam and the post-exam periods

Method for Sizing of a PV System for Family Home Using Economic Indicators

This paper presents a method for finding an optimal photovoltaic (PV) system according to Croatian legislation. The PV sizing model, in which a decision on investment is made according to economic indicators, is made using MATLAB Software. Based on the input data, the monthly PV system production is calculated, and electricity price formed. According to the PV system production and electricity price, economic indicators are calculated and obtained as output data. The model input data are solar irradiation, load diagram, PV system costs and market price of electricity while the model output data are PV system production, savings, profit, incomes, Net Present Value (NPV) and Levelized Cost of Electricity (LCOE). The obtained economic indicators are presented graphically and used for decision making on an optimal PV system size. The presented model is applied and presented in a case study