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Compact datalogger with flash memory
Vágner, Martin ; Hynčica, Ondřej (referee) ; Bradáč, Zdeněk (advisor)
This thesis deals with design of small datalogger with flash memory card. At first are discussed parameters, functions and features of dataloggers. The second part deals with a problem of digital measurement of analog signals. The rest of this thesis gives attention to main goal which is design of datalogger. It consists of circuit diagram, layout of printed circuit board, firmware for microcomputer and software for PC.
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Audio Saving Module
Strašil, Ivo ; Kouřil, Jiří (referee) ; Říha, Kamil (advisor)
The aim of this thesis was to design and construct an autonomous, hardware voice recorder/player module. The device is made as a compact, built-in component for a motherboard of a target appliance. During recording, the incoming analog voice signal is converted to a digital stream by an ADC with 16 bits resolution and 24 kHz sample rate. Microcontroller LPC2103 (ARM7TDMI core) processes data, recalculates resolution and sample rate, encodes and converts to WAV format and save into a FAT/FAT32 filesystem on a Secure Digital memory card. At playback, the process is opposite: the microcontroller reads file from the memory card, decodes the stream and sends it to a DAC and then to a reconstruction filter. So there is an analog voice signal at the output again. The firmware allows control by logic inputs or by a serial bus, processing of uncompressed WAV files or WAV files with A-law or IMA ADPCM compression, continual recording including automatic freeing of card space by deleting the oldest records and a usage of a voice emphasis filter or of a signal dynamic compression circuit.
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Improving Accuracy of Detection and Recognition of Traffic Signs with GANs
Glos, Michal ; Musil, Petr (referee) ; Smrž, Pavel (advisor)
The goal of this thesis was to extend a dataset for traffic sign detection. The solution was based on generative neural networks PatchGAN and Wasserstein GAN of combined DenseNet and U-Net architecture. Those models were designed to synthesize real looking traffic signs from images of their norms. Model for object detection SSD, trained on synthetic data only, achieved mean average precision of 59.6 %, which is an improvement of 9.4 % over the model trained on the original data. SSD model trained on synthetic and original data combined achieved mean average precision of 80.1 %.
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Using of SD Memory Card for FITkit Platform
Gazda, Martin ; Slaný, Karel (referee) ; Vašíček, Zdeněk (advisor)
Reconfigurable hardware architectures represent a modern trend in development of new circuits. A lot of embedded systems is used as mobile devices with high demands on data capacity and power consumption of peripheral devices. This demands are suited with FLASH based memory, like SecureDigital memory card. This bachelors thesis deals with the problem of usage of this memory card on FITkit development platform.
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Connecting SD Memory Card to Microcontroller
Laurinc, Pavel ; Kubek, Ján (referee) ; Škarvada, Jaroslav (advisor)
Author concerns with SD memory cards and microcontroller Atmel ATmega128. He describes their architecture, features, properties and technology used in devices. He is mentioning principle of communication protocols used by SD card, through that cards can communicate with other connected devices. He analyzes the functionality of FAT file system. He describes the design and implementation of interfaces to connect the SD cards to microcontroller. He explains software solutions of this project and gives impartial view to usage and comparisons of implemented modes of communication witch card.
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Improving Accuracy of Detection and Recognition of Traffic Signs with GANs
Glos, Michal ; Musil, Petr (referee) ; Smrž, Pavel (advisor)
The goal of this thesis was to extend a dataset for traffic sign detection. The solution was based on generative neural networks PatchGAN and Wasserstein GAN of combined DenseNet and U-Net architecture. Those models were designed to synthesize real looking traffic signs from images of their norms. Model for object detection SSD, trained on synthetic data only, achieved mean average precision of 59.6 %, which is an improvement of 9.4 % over the model trained on the original data. SSD model trained on synthetic and original data combined achieved mean average precision of 80.1 %.
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Corporate social responsibility and sustainable development in chosen company
Smejkal, Štěpán ; Plášková, Alena (advisor) ; Buchta, Josef (referee)
This bachelor thesis deals with corporate social responsibility and sustainable development, which are both much discussed topics nowadays. Thesis is divided into two parts. In the theoretical part I deal with the meaning of concepts of corporate social responsibility and sustainable development including the history, evolution, actual meaning and benefits. Practical part of the bachelor thesis researches corporate social responsibility and sustainable development in the specific construction company FATO Plc, which is situated in Hradec Králové. There were made interviews and surveys with company employees and headquarters within practical part. I made a summary and an evaluation of activities in three CSR pillars followed by the recommendation into the future based on obtained information.
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