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Maribor, Slovenia

Jazbinsek V.,Institute Za Matematiko | Begus S.,Fakulteta za elektrotehniko | Trontelj Z.,Institute Za Matematiko
Elektrotehniski Vestnik/Electrotechnical Review | Year: 2012

We present results of our study in localization of the auditory evoked magnetic field measured by a noncryogenic potassium vapour atomic magnetometer (PVAM) [5]. The magnetometer was operating in a spin-exchange relaxation- free (SERF) regime at low magnetic flux densities and high alkali-metal vapour density [1]. Audio stimulation of short 1 kHz pulse trains was applied by a pneumatic earphone. After rejecting the subject's heart-beat signals, signals originating from eye movements and disturbances due to mechanical vibrations, the N100m could be seen in several channels of the 256-channel atomic magnetometer. This was achieved by combining the magnetometer channels into a gradiometer configuration: one magnetometer was selected as a reference channel and other channels were subtracted from this reference. Using ten gradiometric channels with the best signal-tonoise ratio the approximate source localization of the auditory evoked field was determined by applying two methods: i) non-linear least-square fitting procedure using a current dipole source model in a conducting sphere model, and ii) minimum norm estimaton (MNE) method. Source


Trbusic M.,Fakulteta za elektrotehniko | Pihler J.,Fakulteta za elektrotehniko
Elektrotehniski Vestnik/Electrotechnical Review | Year: 2014

The paper presents a comprehensive method of designing a model of the Tesla transformer. The Tesla transformer is a device that works on the principle of magnetic-coupled oscillating circuits producing very high voltages at the resonance. The presented model is an example of the basic transformer design, which is defined by two magnetic-coupled oscillating circuits with no magnetic core. The methods to determine the lumped parameters of the supply transformer are described and calculation and design of the primary capacitor of the Tesla transformer are shown. The ground capacitance of the secondary coil and coil inductances are calculated using FEMM 4.2. The response of the Tesla transformer is obtained by using MATLAB 7. The design guidelines for the Tesla transformer elements are given and comparison between the calculated and measured values is shown. The Tesla transformer model was made in the Powerlab at the Faculty of Electrical Engineering and Computer Science of the University of Maribor to visually present some electromagnetic phenomena. Source


Berkopec A.,Fakulteta za elektrotehniko | Slivnik T.,Fakulteta za elektrotehniko
Journal of Electrostatics | Year: 2010

The aim of this paper was to obtain the quantitative estimation of the W0/WT (initial electric energy/atmospheric parameter of a surrounding medium) ratio for CG lightnings initiated with a stepped leader process. The results of analytical and numerical models show that the W0/WT ratio for CG lightnings spans the range of approximately two orders of magnitude 20 ≤ W0/WT ≤ 2000. The results also suggest that CG lightnings differ significantly from small-scale discharges in the laboratories: the thundercloud CG lightnings occur at considerably lower initial electric energy, higher atmospheric parameter of the surrounding medium or a combination of both. © 2010 Elsevier B.V. Source


It Is essential for Earth's environment to predict natural disasters like fires, floods, earthquakes, etc. Our goal is to asses quality of empirical models used in soil moisture parameter retrieval. In this paper we assessed Dubois and Shi empirical model over the river Drava next to the city of Maribor, Slovenia. These models were applied to TerraSAR-X satellite, which is a German national space satellite operating at X-band radar frequency. In order to compare and validate results, field measurements were done with a Pico64 sensor at the time of image capture. As we have concluded, Shi model is preferred when it comes to accuracy of estimated volumetric soil moisture. Source


Kseneman M.,Fakulteta za elektrotehniko | Gleich D.,Fakulteta za elektrotehniko
Informacije MIDEM | Year: 2011

Licence plate recognition presented in this paper is used to identify vehicles by their licence plate numbers. This technology can be widely used for paying pay-rolls, in opening parking garage door, traffic control /1/, etc. This paper presents an algorithm for licence plate recognition, shown in Fig. 1. The algorithm itself is divided into two parts, the first part extracts licence plate and the optical character recognition is described in the second part of the paper. In the first part of the paper three methods for licence plate recognition are presented. White pixels in an image can be detected using threshold method. Reference photo is shown in Fig. 2; meanwhile the experimental result of threshold method is shown in Fig. 3. The second method is based on 2D correlation, which uses segmentation in order to limit search area. The segmentation technique is performed using (1), but it is computationally very demanding (2). The result of this phase is shown in Fig 4. The method with Euclidian norm (3) uses Freeman chain code with interior pixels, but it is user dependent, because the user has to input one licence plate pixel (the result is shown in Fig. 5). The first method is used as method for licence plate recognition. The dilatation algorithm is used to fill up the whole plate with the same pixels. The dilated picture is shown in Fig 6. The algorithm detects the angle of licence plate, as shown in Fig. 7. Rotated and isolated licence plate is quantised and rescaled using a histogram method. The extracted licence plate is further shown in Fig. 8. The edges cut from detected licence plate and extracted binary images are shown in Figs. 9-10, respectively. A method called peak-to-valley is used to extract each individual character, which sums picture's columns and creates a histogram. By comparing sums to specified threshold, characters are detected. Characters are recognised using feed-forward neural networks. This network has 200 input neurons and 36 output neurons. Learning is accomplished through supervised learning of back-propagation technique. The whole structure of neural network is shown in Fig. 11. The results presented in Table 1 show that the overall efficiency of OCR engine is 96% when the recognition is applied on extracted licence plate. Source

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