Předložená práce se zabývá problematikou slepé filtrace obrazů z transmisního elektronového mikroskopu. V úvodu práce je uveden popis transmisního elektronového mikroskopu. Navazující část popisuje mechanismy interakce elektronů se zkoumaným vzorkem a z toho vyplývající zobrazovací techniky elektronové mikroskopie. Poslední kapitola teoretické části práce zahrnuje popis vybraných metod slepé filtrace obrazu zejména s využitím dekompozice obrazu na charakteristické složky. Taktéž je zde uveden výčet metod pro zhodnocení úspěšnosti filtrace. V praktické části jsou popsány aplikované metody slepé filtrace obrazů a výsledky filtrování. Jednotlivé metody jsou mezi sebou porovnány. Získané výsledky a využitelnost aplikovaných metod jsou zhodnoceny v diskuzi.

The aim of this master’s thesis is analysis of the multidimensional data. Three dimensionality reduction algorithms are introduced. It is shown how to manipulate with text documents using basic methods of natural language processing. The goal of the practical part of the thesis is to process real-world data from the internet forum. Posted messages are transformed to the numerical representation, then to two-dimensional space and visualized. Later on, topics of the messages are discovered. In the last part, a few selected algorithms are compared.

To protect the the copyright of multimedia works have been developed watermarking techniques, that insert an invisible watermark to the original data. The aim of this thesis was to explore modern watermarking techniques, choose three of them and realize them. Also test them, evaluate their properties and possibly improve them. All methods insert a watermark into luminance component of the original image, and work with binary or black and white watermark. All techniques work in the frequency domain using discrete wavelet transform. For the implementation of methods, have been developed software named "Watermarking" that has been programmed in JAVA Version 7. The first chapter describes the types of watermarks, the general process of insertion and extraction, watermarking systems and important feature requests of embedded water- marks. In addition, qualitative methods are mentioned for their comparisons and testing. The chapter also contains a theoretical description of the used transformations and functions. In the second chapter is described the user interface of the software "Water- marking". Chapters three and four contain a theoretical description of the implemented methods and description of implementation of insertion and extraction processes of the watermark. Also there are discussed the exact procedures for testing, the sample data, and the results which are clearly displayed in the tables. The fifth chapter discusses in detail the results obtained in testing the robustness of the watermark, using the software StirMark. In the conclusion are evaluated the advantages and disadvantages of methods and quality parameters.

This work describes development of a diff tool working with audio files containing general sound such as music, speech and other sounds. There are presented facts from different domains of science related to sound, such as psychoacoustics, speech recognition and automatic music genre categorisation. This paper also contains description of some diff algorithms and external tools needed for development of the goal application. Moreover, there is introduced design and implementation of the application, settings used for sound features extraction and evaluation of attained results.

This thesis deals with algorithms of visual odometry and its application on the experimental vehicle Car4. The first part contains different researches in this area on which the solution process is based. Next chapters introduce theoretical design and ideas of monocular and stereo visual odometry algorithms. The third part deals with the implementation in the software MATLAB with the use of Image processing toolbox. After tests done and based on real data, the chosen algorithm is applied to the vehicle Car4 used in practical conditions of interior and exterior. The last part summarizes the results of the work and address the problems which are asociated with the application of visual obmetry algorithms.

The Polar Decomposition (PD) of a dense matrix is an important operation in linear algebra, while being a building block for solving the Symmetric Eigenvalue Problem (SEP) and computing the Singular Value Decomposition (SVD). It can be directly calculated through the SVD itself, or iteratively using the QR Dynamically-Weighted Halley (QDWH) algorithm. The former is difficult to parallelize due to the preponderant number of memory-bound operations during the bidiagonal reduction. The latter is an iterative method, which performs more floating-point operations than the SVD approach, but exposes at the same time more parallelism. Looking at the roadmap of the hardware technology scaling, algorithms perform- ing floating-point operations on locally cached data should be favored over those requiring expensive horizontal data movement. In this context, this thesis investigates new high-performance algorithmic designs of QDWH algorithm to compute the PD. Originally introduced by Nakatsukasa et al. [1, 2], our algorithmic contributions include mixed precision techniques, task-based formulations, and parallel asynchronous executions. Moreover, by making the PD competitive, its application to the SEP and the SVD becomes practical. In particular, we introduce for the first time new algorithms for partial SVD decomposition using QDWH. By the same token, we extend the QDWH to support partial eigen decomposition for SEP. We present new high-performance implementations of the QDWH-based algorithms relying on fine-grained computations, which allows exploiting the sparsity of the underlying data structure. To demonstrate performance efficiency, portability and scalability, we conduct benchmarking campaigns on some of the latest shared/distributed-memory systems. Our QDWH-based algorithm implementations outperform the state-of-the-art numerical libraries by up to 2.8x and 12x on shared and distributed-memory, respectively. The task-based QDWH has been integrated into the Chameleon library (https://gitlab.inria.fr/solverstack/chameleon) for support on shared-memory systems with hardware accelerators. It is also currently being used by astronomers from the Subaru telescope located at the summit of Mauna Kea, Hawaii, USA. The distributed-memory software library of QDWH and its SVD extension are freely available under modified-BSD license at https: //github.com/ecrc/qdwh.git and https://github.com/ecrc/ksvd.git, respectively. Both software libraries have been integrated into the Cray Scientific numerical library LibSci v17.11.1 and v19.02.1.

Heavy crushing machines under their production shifts, creates various levels of vibration, noise and dynamic forces which can be transferred to other parts of the industrial unit. Such kind of factors applies continuous forces on machine parts which can cause gradual fatigue, creep and eventually failure of machine. In this thesis work we are studying Jaw crusher machine from Sandvik company, since the company has a high focus on safety and quality, this thesis is aiming to estimate the dynamic foundation loads that are transmitted to substructure of the jaw crusher. The thesis is based on estimating power spectral density transmissibility matrix-single value decomposition (PSDTM-SVD), between jaw crusher foot (CRF), side wall (SW) and substructure (SS) in x, y, z positions to identify model parameters including damped eigenfrequencies and mode shapes. This research has concluded that it is possible to estimate the transmitted load force by finding the relation between displacement transmissibility and force transmissibility by employing (PSDTM-SVD) method. In fact (PSDTM-SVD) is a sufficient method to estimate the damped eigenfrequencies and mode shapes during operation.  Nevertheless, it is majorly important to have good coherence between measured data, in this case data that have been conducted in Y direction had a good coherence of 0.9.

Modeling and design of high frequency electronic systems such as antennas and microwave devices require the rigorous numerical solution of Maxwell’s equa- tions. The frequency-domain (time-harmonic) tangential vector finite element method (TVFEM) for Maxwell equations results in a second-order dynamical electromagnetic model that must be repeatedly solved for multiple frequencies, excitation or material parameters each design loop. This leads to extremely long design turnaround that often is not optimal. This work will propose an accurate, error controllable and ef- ficient multi-parametric model order reduction scheme that significantly accelerate these parameters sweep. At the core of this work is the proper orthogonal decompo- sition (POD) sampling technique and balanced truncation (BT) algorithm that are used to reduce multi-parameter spaces that include frequency, material parameters and infinite array scan angles. The proposed methodology employs a novel computa- tional scheme based on adaptive POD sampling and the singular value decomposition (SVD) of the low-rank Hankel matrix. Numerical examples confirm the significant time savings and good accuracy of the method for a diverse set of high-frequency electromagnetic systems.

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