Majlingová, Zuzana

This invention relates to the power device for the autonomous production, storage and supply for using the heat and cold, wherein this device comprises the core for heat storage; the heating system for the core heating; the circulation hydraulic system comprising the heat-bearing medium for the transfer of the heat from the core for heating, and the water system for the preparation of the hot water and production of the cold; the regulation system for the regulation of the core temperature and the heat-bearing medium flow; measuring system for the measuring of the core temperature and the heat-bearing medium flow; wherein this device comprises the core comprising heat-absorption filling having the grit of ≤ 0.1 mm, at least 0.025 mm, while the heat-absorption filling is adapted for permanent heat storage up to 350 °C; the heating system is adapted for heating of the heat-absorption filling to 350 °C; the regulation system comprises the control unit adapted for the control of the heating system and for the regulation of the heat-bearing medium flow; and wherein the part of the circulation system passes through the core and said part comprises the circulation element for the circulation of the heat-bearing medium, wherein the circulation element preferably represents the transport of the medium through the threat transport system placed in the core.

The invention relates to a computer-implemented method for non-destructive determination of the porosity of a thin layer, which comprises the following steps: (a) acquiring static visual data of the Laser type and the LED type from a laser speckle photometry device arranged to illuminate the surface of the thin layer by a laser and an LED and to capture the reflected light field; and (b) processing the acquired data in a computing unit, wherein the processing includes a spatial synchronization of the Laser-type data and the LED-type data; a reduction of channels of the Laser-type data and the LED-type data into monochromatic single-channel data if the acquired data are in a multichannel format; a generation of three-channel data, wherein one channel comprises monochromatic Laser-type data, a second channel comprises monochromatic LED-type data, and a third channel is null; an extraction of data patterns; a normalization of data patterns; and processing of the normalized data patterns using a trained, validated and tested regression neural network, wherein the output of processing is the porosity value of the thin layer.

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