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Design and optimization of a low beam LED headlamp reflector
Varhaníková, Alžbeta ; Kapusta, Martin (referee) ; Novotný, Jan (advisor)
The diploma thesis deals with the optical design of low beam LED reflector. The thesis aims to optimize the existing low beam LED reflector with an emphasis on achieving a legal and homogeneous light distribution. The theoretical part contains the essay of light sources and optical systems used in headlights, as well as the description of the production technology of LED reflector for different polymeric materials. The experimental part presents a detailed methodology for the optical design of low beam LED reflector in the company software. The thesis also contains a description of the original low beam LED reflector and its problematic parts. The optimization of LED reflector was performed by changing its construction and by the replacement of the light source which increased the robustness of the whole system. In the conclusion, the optimization of LED reflector is evaluated by comparing final light distributions for individual LED reflectors.
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Laboratory exercises for network technologies education
Kapusta, Martin ; Langhammer, Lukáš (referee) ; Dvořák, Jan (advisor)
The aim of the diploma thesis is to choose network simulator suitable for network technologies laboratory tasks for educational use. Theoretical part of thesis describes basics of network communication, addressing, reference models. Thesis also describes standards Wi Fi, Ethernet and routing protocol OSPF - technologies which are discussed in laboratory tasks. The practical part of diploma thesis describes a few available network simulators suitable for creating two laboratory tasks. Finally, the NS-3 simulator was chosen. Both laboratory tasks include theoretical introduction, detailed description of source code, individual tasks, expected outputs and control questions which senses understanding of discussed technologies.
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Convolution neural networks on the Windows platform
Kapusta, Martin ; Rajnoha, Martin (referee) ; Přinosil, Jiří (advisor)
The aim of the bachelor thesis is the latest knowledge of convolution neural networks and their application. The thesis describes the history, biological neuron and analogous mathematical model of a neuron. It also deals with the areas where neural networks are used, as well as the areas in which they expand gradually, the ways of learning and training, the differences between convolution neural networks and classical neural networks and their architecture. The thesis consists of two parts. The first part is the selection of the framework for working with convolution neural networks, which is suitable for implementation in the Windows operating system, the installation of the framework and its troubleshooting. The second part is aimed at creating an automated installation tool for the Windows 7 and Windows 10 operating system, created in JavaFX.
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