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Mixážní pult pro audio signály
Ryšavý, Ondřej ; Kufa, Jan (oponent) ; Kratochvíl, Tomáš (vedoucí práce)
Bakalářská práce na téma „Mixážní pult pro audio signály“ se zabývá návrhem a výrobou mixážního pultu pro směšování několika nezávislých audio signálů. V prvním kroku je navrženo blokové schéma a poté i obvodové schéma. Celková konfigurace mixážního pultu je řešena následovně: Čtyři monofonní vstupy, řešené jako kombinovaný XLR/Jack 6,3 mm vstup, kam je možné připojit mikrofon nebo jiný monofonní zdroj signálu (nikoli oba současně), dva stereofonní vstupy RCA (CINCH). Každý kanál umožňuje pětipásmovou frekvenční korekci, panoramu, regulaci úrovně signálu a detekci úrovně signálu. Výstup je realizován pomocí linkových konektorů (pro připojení do zesilovače), sluchátkového výstupu a sluchátkového zesilovače. Po navržení je mixážní pult vyroben, oživen a následně měřen v laboratoři audio techniky.
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Indoor positioning system using UWB signals
Sadleková, Simona ; Kufa, Jan (oponent) ; Rozum, Stanislav (vedoucí práce)
This bachelor thesis deals with the indoor object localization by using Ultra Wide Band signals (UWB). Physical layer for determination of the distances, which are needed for localization, is built from DW 1000 integrated chips in demonstration system TREK1000. The thesis describes the library for communication with TREK1000 system in C# language, to enable intuitive aplication of this system in various projects based on .NET framework. Subsequently, the thesis deals with the trilateration implemented in C# language, which brings the new method compared to the original feature and solves the problem with finding the tag position in case the spheres are not crossed in one point, but in the area of possible appearance.
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Photovoltaic Battery Charger with Sun Tracking
Knob, Martin ; Kufa, Jan
This paper describes the design of a photovoltaicbattery charger. The charger can track the sun and tilt the panelin azimuth and elevation. The device includes an Maximum PowerPoint Tracking (MPPT) regulator to maximise the energy from thephotovoltaic panel. This photovoltaic charger is designed for Liionbatteries and is equipped with appropriate battery protection.The system is battery-powered and therefore energy selfsufficient.Another purpose of the device is to measure accuratedata for further processing. It will measure the energyconsumption required for its operation and the energy producedby the photovoltaic panel. The device communicates wirelessly viaWi-Fi and sends the measured data to the Thingspeak server.
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Fotovoltaický nabíječ akumulátoru se sledováním slunce
Knob, Martin ; Frýza, Tomáš (oponent) ; Kufa, Jan (vedoucí práce)
Tato práce se zabývá návrhem fotovoltaického nabíječe akumulátoru. Nabíječ dokáže sledovat Slunce a naklánět panel v azimutu i elevaci. Zařízení obsahuje MPPT regulátor kvůli optimalizaci energie ze Slunce vyrobenou za pomoci fotovoltaického článku. Tato fotovoltaická nabíječka je určena pro nabíjení Li-ion baterií a obsahuje vhodné nabíjecí a ochranné obvody. Nabíječ je energeticky soběstačný, což znamená, že nepotřebuje další zdroj energie. Dalším účelem tohoto zařízení je měření elektrických veličin. Zařízení odesílá měřená data bezdrátově pomocí Wifi.
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Deep Learning based compression of 360° images
Budáč, Adam ; Boleček, Libor (oponent) ; Kufa, Jan (vedoucí práce)
This diploma thesis deals with 360° image compression based on deep learning. The thesis describes the representation and deformations of a 360° image. It then describes conventional compression methods and methods using machine learning, deep learning and deep neural networks for 360° image compression. Part of the work is the creation of a dataset, which consists of ten 360° images, and the design of a framework that enables image compression using conventional codecs and algorithms based on machine learning, deep learning, and deep neural networks. Images from the dataset are compressed using five conventional codecs and four deep learning algorithms. The quality of compressed images is measured using seven objective metrics and one subjective test. As a result of the experiment, the conventional methods achieved higher compression quality than the methods using deep learning, and the computational complexity of the conventional methods is lower compared to the methods using deep learning.
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Weight sensing of beehives with IoT connectivity
Havránek, Daniel ; Kufa, Jan
This paper focuses on designing a device that can measure some beehive parameters, that can inform users about the conditions in a beehive. These parameters are beehive weight, internal and ambient temperature, internal and ambient humidity, and air pressure. The device allows sending the measured data wirelessly through the GSM network and interpreting the results in appropriate way. Low power consumption is desirable due to working without the reach of the distribution network.
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Advanced Algorithms for Compression of Videos with Ultra High Resolution
Soukenik, Ondrej ; Polak, Ladislav ; Kufa, Jan
In this paper, attention is devoted to advanced video codecs (HEVC, VVC, VP9 and AV1) and their utilization for compression of videos with Ultra High Resolution (UHD), also marked as 4K and 8K. A Python-based program employing FFmpeg multimedia framework is created to explore compression performances of such video codecs. It allows to automate encoding process and record all important information during the video compression (e.g. the required CPU time, time consumption, RAM usage). The performance of the video compression algorithms is evaluated in terms of objective quality metrics. First experimental results show that video codecs VVC and AV1 could replace HEVC and VP9 for 4K and 8K videos in the future.
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System of gas and fire detectors in living spaces
Sedláček, Marek ; Kufa, Jan (oponent) ; Frýza, Tomáš (vedoucí práce)
This bachelor thesis focuses on sensors and microcontrollers connecting via Wi-Fi to IoT networks. For that purpose, monitoring devices were designed. These devices monitor the presence of gases that can occur in households and in the case of exceeding the limits, they send an acoustic signalisation. The measured values and capacity of the battery are then sent by microcontrollers to the Internet via Wi-Fi.
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