Student EEICT 2017

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    Automated Detection Of Retinal Venous Pulsations From Video Sequences
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2017) Hracho, Michal
    The aim of this paper is to propose a method of automated detection and parametrization of spontaneous venous pulsations, that can occur in patients with various degrees of glaucoma. The method uses uncompressed video sequences acquired from fundus video-ophthalmoscope. A parameter of pulsation is then acquired and tested for correlation with occurrence of spontaneous venous pulsations.
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    Neural Network For Testing
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2017) Smetana, Bedřich
    This article describes basics of neural networks, specifically aimed at usage of freeware to test freeware for creation simple neural network. Discussion focuses on the use of generally available programs and problems with use of freeware applications. Attention is devoted to a comparison of real and theoretical conditions connected with practical computer support.
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    Silicon Solar Cell Parameters Change After Focused Ion Beam Milling
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2017) Gajdos, Adam
    Silicon is still one of the most used materials for fabrication of solar cells. Some imperfections and defects may appear during production process. These local imperfections could be eliminated by focused ion beam (FIB). Nevertheless, FIB milling process modifies the crystal structure of the material by ions implantation. Samples under investigation are monocrystalline silicon solar cells. The impact of FIB milling is shown and discussed through current-voltage measurement before and after milling process.
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    Lead-Acid Battery Evaluation Based On Opencircuit Voltage Fluctuation Measurement
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2017) Kuparowitz, Tomáš; Kuparowitz, Martin
    The state of charge and the state of health are two crucial parameters of batteries. Current state of the art methods of their estimation include some as simple as measuring open circuit voltage, all the way to fuzzy logic estimation and constant online battery overview. Some main problems of such methods are either the length of single parameter evaluation cycle, or their inherent inaccuracy due to limitations in battery manufacture precision. This article proposes novel method of the lead-acid battery state of the health estimation, based on open circuit noise measurement. It reports the nature of changes in low frequency noise spectral density, that occur after catastrophic self-discharge failure or avalanche voltage drop in lead-acid batteries.
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    Chalcopyrite Solar Cells
    (Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2017) Škvarenina, Ľubomír
    Thin-film chalcopyrite based Cu(In;Ga)Se2 solar cells with a metal wrap through interconnection were investigated by non-destructive methods in our research. The primary focus of this investigation was a detection and a localization of microstructural defects in this type of Cu(In;Ga)Se2 solar cells. A combination of a visible and near infrared electroluminescence with a lock-in thermography was used for these purposes. Mainly the electroluminescence was a very sensitive tool for an indication of pre-breakdown sites influenced by a trap-assisted tunneling or stress-induced leakage currents. A strong correlation between electroluminescence maps and lock-in thermograms was obtained after a local breakdown accompanied by a creation of permanent defect.