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Measurements of the intensity of traffic within a fixed interval of the AP
Kubík, Pavel ; Trzos, Michal (referee) ; Matocha, Tomáš (advisor)
The thesis analyzes the network traffic on a router with open source firmware. First is chosen a software platform, based on compatibility with available equipment. Then are assessed properties necessary for the development of custom applications. Support for various programming languages provided by the SDK, development environment and the available modules and libraries, for working with network interface. Based on these factors is then chose method to realize the program. He is implemented on the OpenWRT firmware in C / C + + using network library pcap. These funds are used to capture and analyze network traffic. Obtained data are processed using methods of technical analysis, namely on the basis of moving averages, Stochastic oscillator and Bollinger bands. Based on results of these methods are generated and verified estimates of traffic. They are based on linear extrapolation, simplified for fixed intervals. The validity of each method is verified on base of the estimated value. Method is verified if estimated value of the traffic volume is in the Bollinger band, which is given by the standard deviation. Each method is tested several times in real traffic with different input parameters. Then is evaluated the influence of parameters on the error rate of methods. Individual methods are compared and evaluated based on the behavior in different scenarios and based on the average relative error.
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Data compression
Krejčí, Michal ; Havlíková, Marie (referee) ; Čejka, Miloslav (advisor)
This thesis deals with lossless and losing methods of data compressions and their possible applications in the measurement engineering. In the first part of the thesis there is a theoretical elaboration which informs the reader about the basic terminology, the reasons of data compression, the usage of data compression in standard practice and the division of compression algorithms. The practical part of thesis deals with the realization of the compress algorithms in Matlab and LabWindows/CVI.
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Fitting and Extrapolation of Turbocharger Turbine Maps
Vondrák, Adam ; Babák, Martin (referee) ; Novotný, Pavel (referee) ; Štětina, Josef (advisor)
Modelování turbínových charakteristik je nutným předpokladem pro detailní simulaci výměny náplně válce turbodmychadlem přeplňovaných spalovacích motorů. Kromě toho je možnost stanovení účinnosti a průtokové kapacity v libovolných pracovních bodech klíčová pro porovnání různých turbínových stupňů. Cílem této práce je předložit jednotnou metodu pro oba účely tak, aby bylo možné provést porovnání použitím přesně stejných modelů turbín jako při následné simulaci pracovního oběhu motoru. Zdrojem vstupních dat je obvykle měření na plynové zkušebně, které však umožňuje zachycení pouze omezeného pracovního rozsahu turbíny. V této práci jsou navrženy metody umožňující zvýšení věrohodnosti a robustnosti extrapolace turbínových charakteristik, přičemž optimalizace je využita k určení takových parametrů hledaných funkcí, které vedou k nejlepší shodě mezi modelem a vstupními daty.
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Advanced Methods of Audio Signals Interpolation
Pospíšil, Jiří ; Rajmic, Pavel (referee) ; Mach, Václav (advisor)
This diploma thesis deals with the theoretical analysis of the predictive methods of signal interpolation and signal modeling using sinusoidal model. On the basis of this theory the algorithm for the reconstruction of the missing sections in the audio signal is implemented in computing environment MATLAB. Results of mass testing reconstructions are displayed using objective methods SNR and PEMO-Q. Further experiments are carried out on single signals and their evaluation is described.
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Image extrapolation methods
Ješko, Petr ; Špiřík, Jan (referee) ; Rajmic, Pavel (advisor)
The thesis deals with addition of pixels outside the image. Lists some methods for inpainting using computers and highlights the pitfalls that appear here. Examines methods for interpolation and approximation of functions in order to find the best method for extrapolating the image beyond its borders. Describes the basics of Wavelet transformation and Multiresolution analysis. It is proposed several methods for replenishment of pixels outside the image. PSNR and SSIM are used to compare achieved results. These methods are explained and compared. Briefly discusses the algorithm OMP, falling within the sparse representation of signals, and used in one of the methods. Also discussed is the development environment of MATLAB as a tool for the implementation of algorithms that practically solves the given problem. The practical part describes the implemented methods for adding pixels outside the image.
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Fatigue evaluation methods for pressure equipment utilising numerical analysis results
Boleloucký, Václav ; Lošák, Pavel (referee) ; Létal, Tomáš (advisor)
Diplomová práce se zabývá hodnocením únavové životnosti v okolí konstručního uzlu tlakové nádoby, kde vzniká výrazná koncentrace napětí a je zde předpoklad primárního vlivu na únavu materiálu. Konkrétně se jedná o místo přechodu kontrolního otvoru do pláště analyzovaného zařízení. Práce obsahuje teoretickou a praktickou část. V teoretické části jsou představeny pojmy a metody hodnocení, související s danou problematikou. Na základě těchto metod je provedena analýza konstrukčního uzlu tlakové nádoby. Analýza je provedena metodou konečných prvků na skořepinovém a objemovém modelu nádoby v softwaru ANSYS Workbench, její výsledky dále zpracovány a vyhodnoceny dle aktuálního návrhu úpravy evropské harmonizované normy EN 13445--3, kapitoly 18. Výsledky analýz jsou hodnoceny v závěru práce.
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Image extrapolation methods
Ješko, Petr ; Špiřík, Jan (referee) ; Rajmic, Pavel (advisor)
The thesis deals with addition of pixels outside the image. Lists some methods for inpainting using computers and highlights the pitfalls that appear here. Examines methods for interpolation and approximation of functions in order to find the best method for extrapolating the image beyond its borders. Describes the basics of Wavelet transformation and Multiresolution analysis and briefly discusses about spatial filtering, edge detection and the algorithm OMP, falling within the sparse representation of signals. Theoretical knowledge of these areas are used in the design of several methods for adding pixels outside the image. PSNR and SSIM are used to compare achieved results. Also discussed is the development environment of MATLAB as a tool for the implementation of algorithms that practically solves the given problem.
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Rain Prediction Using Meteo-Radar
Gerych, Petr ; Hradiš, Michal (referee) ; Szőke, Igor (advisor)
This paper deal with the rain prediction in the short time interval. The static pictures from meteo-radar serves as input data. The principle of meteo-radar is explained. The possible methods of the object detection and registration, motion interpolation and extrapolation is described. The flood fill algorithm and Lagrange extrapolation is applied to rain prediction. Application is written in C++ language under OS Linux. The example of the software application results is included.
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Determining the optimal patch size for sparse image representation
Šuránek, David ; Zátyik, Ján (referee) ; Špiřík, Jan (advisor)
Introduction of this thesis is dedicated to the description of basic concepts and algorithms for image processing using sparse representation. Furthermore there is mentioned neural network model called Restricted Boltzmann machine, which is in the practical part of the thesis subject of behaving observation in the task of determining the optimal block size for extrapolation using K-SVD algorithm
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Estimation of Algorithm Execution Time Using Machine Learning
Buchta, Martin ; Chlebík, Jakub (referee) ; Jaroš, Jiří (advisor)
This work aims to predict the execution time of k-Wave ultrasound simulations on supercomputers based on a given domain size. The program uses MPI and can be run on multiple nodes. Prediction models were developed using symbolic regression and neural networks, both of which trained on captured data and compared against each other. The results demonstrate that the models outperform existing solutions. Specifically, the symbolic regression model achieved an average error of 5.64% for suitable tasks, while the neural network model achieved an average error of 8.25% on unseen domain sizes and across all tasks, including those not optimized for k-Wave simulations. This work contributes a new, more accurate model for predicting execution time, and compares the effectiveness of neural networks and symbolic regression for this specific type of regression problem. Overall, these findings suggest that new models will have important practical applications in the field of k-Wave ultrasound simulations.
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