Due to the growing number, diversity and spreading of magnetic field sources, an increasing need to determine the field levels of human exposure has arisen. Some of the most encountered sources are the overhead power lines (OPL) and the determination of spatial and temporal variation of the magnetic fields produced by OPLs is a challenge. In this paper a hybrid method for the estimation of the temporal and spatial distribution of the magnetic flux density B caused by OPLs, based on experimental measurements and on numerical and analytical simulations, is presented. Thus, using a small number of simultaneous spot measurements correlated with a long-term survey, maps of the magnetic flux density distribution on extended areas are established, for several time instances. The proposed method is verified using two sets of different measurements and the results obtained through simulation. The difference between the estimated and simulated values of B is under 5.5%, which is considered acceptable considering that B spans over a large set of values (724 nT ÷ 1375 nT) in the location of the long-term survey procedure. The possibilities and limitations of the proposed method are discussed.

In this paper, we present a simple way to determine the heart rate variability (HRV) parameters. We designed a device which is capable of simultaneously recording three biological signals, namely the electrocardiographic signal (ECG), the photoplethysmographic signal (PPG) and a pulse signal acquired from the earlobe, graphically represented by the rectangular form. We recorded and processing these signals from 14 subjects. All data was recorded in the same way, namely with the participant sitting on a chair and by using the same sampling frequency. We determined the heart rate variability (HRV) parameters from the electrocardiographic signal, the pulse rate variability (PRV) parameters from the photoplethysmographic signals, and earlobe PRV from the pulse signal (ePRV). We calculated the Pearson coefficient in three ways, first between the HRV and the PRV parameters, second, using the HRV and the ePRV parameters and the last one using the PRV and the ePRV parameters. Both in case of the time-domain and frequency-domain parameters, the Pearson correlation coefficients were above 0.97, that means a strong link between HRV and ePRV/PRV.

The continuing achievements in Information Technology and Computer science in recent decades provide new tools for engineers in the design of devices and systems, with significant advances both in numerical and in analytical methods of analysis

The topic “Modeling and Simulation in Engineering”, proposed in 2021 as part of the section “Engineering Mathematics”, and later as part of “Control Theory and Mechanics”, covers a large array of technical fields, thus arousing much interest among researchers