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Single particle analysis of size-segregated aerosol in Prague city center
Marvanová, S. ; Skoupý, Radim ; Kulich, P. ; Bendl, J. ; Hovorka, J. ; Machala, M.
Particulate matter (PM) is omnipresent pollutant in the ambient air known to cause cardiovascular and respiratory diseases (WHO 2004). Recently, outdoor air pollution and particulate matter in outdoor air pollution were classified as carcinogenic to humans, Group 1 (IARC 2015). Especially, ambient PM of aerodynamic diameter < 100 nm, ultrafine particles, appears to be of great importance due to its high specific surface area and high number concentration (Hughes et al. 1998). Ultrafine particles also easily enter and are being transferred in organisms, and interact with cells and subcellular components (Oberdorster et al. 2005). As the evidence of ultrafine PM significance increased, size-fractionated PMs sampled by various cascade impactors have been employed into the toxicological studies on cell cultures or isolated cells, using the organic extracts of size-fractionated PMs (Topinka et al. 2013, Topinka et al. 2015) or directly the size-fractionated particles (Becker et al. 2003, Ramgolam et al. 2009, Reibman et al. 2002, Loxham et al. 2013, Jalava et al. 2006, Thomson et al. 2015, Jalava et al. 2015). The aim of this study was to evaluate shape and composition of size-segregated aerosol particles, sampled by high volume cascade impactor, using electron microscopy and energy dispersive X-ray spectroscopy (EDX).
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Evaluating a Structural Model Forecast: Decomposition Approach
Brázdik, František ; Humplová, Zuzana ; Kopřiva, František
Při prezentaci výsledků makroekonomické prognózy musí prognostici často vysvětlovat příspěvky revizí dat, podmiňujících informací nebo expertních úprav k aktualizaci prognózy. V této práci představujeme obecný způsob, kterým je možné rozložit rozdíly mezi dvěma prognózami vytvořenými lineárním strukturálním modelem do příspěvků prvků informační množiny prognózy při aplikaci podmiňujících informací provedené v očekávaném i neočekávaném módu. Prezentovaný systém rozkladu je založen na souboru podpůrných prognóz, které rozklad aktualizace prognózy zjednodušují. Vlastnosti tohoto systému demonstrujeme ukázkou rozkladu rozdílu dvou prognóz se stejným počátečním obdobím predikce, avšak založených na rozdílných předpokladech. Plné možnosti navrženého způsobu rozkladu prezentujeme pomocí příkladu hodnocení prognózy ze Zprávy o inflaci České národní banky III/2012, která je vyhodnocena vzhledem k aktualizované prognóze ze Zprávy o inflaci III/2013.
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Frekvenčně stabilizovaný polovodičový laserový zdroj pro interferometrii s vysokým rozlišením
Řeřucha, Šimon ; Hucl, Václav ; Holá, Miroslava ; Čížek, Martin ; Pham, Minh Tuan ; Pravdová, Lenka ; Lazar, Josef ; Číp, Ondřej
Sestavili jsme experimentální laserový systém, založený na laserové diodě typu DBR (Distributed Bragg Reflector), frekvenčně stabilizovaný na absorpční čáry v parách molekulárního jodu. Laserový systém operuje na vlnové délce ležící v blízkosti vlnové délky stabilizovaných helium-neonových (HeNe) laserů (tj. 633 nm), které představují de-facto standardní laserový zdroj v oblasti metrologie délek. Cílem bylo ověřit, že parametry takového systému umožní jej využít jako náhradu právě He-Ne laserů, která navíc umožní větší rozsah a větší šířku pásma přeladění optické frekvence a vyšší výkon. Experimentálně jsme ověřili základní charakteristiky laserového zdroje, které jsme dále porovnali s charakteristikami typického frekvenčně stabilizovaného He-Ne laseru. K tomu jsme využili experimentální uspořádání blízké typickým využitím laserové interferometrie v metrologii délky. Výsledky prokazují, že laserový systém, založený na laserové diodě DBR představuje vhodný zdroj pro aplikace v (nano) metrologii délky tím, že zachovává fundamentální požadavky na laserový zdroj jako frekvenční stabilita a koherenční délka a zároveň umožňuje přeladění optické frekvence o více než 0.5 nm s šířkou pásma modulace až několik MHz, vyšší výkon v řádu několika mW a díky stabilizaci i fundamentální metrologickou návaznost.
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Možnosti monitorování laserového svařovacího procesu
Horník, Petr ; Mrňa, Libor
Se zvyšujícími se nároky na kvalitu svarů se běžně používá automatické strojní svařování s monitorováním procesu. Výsledná kvalita svaru je do značné míry ovlivněna chováním paroplynové dutiny - keyhole. Nicméně, její přímé pozorování během svařovacího procesu je prakticky nemožné a je nutné použít nepřímé metody. V ÚPT vyvíjíme optické metody sledování procesů založené na analýze záření laserem indukovaného plazmatu pomocí Fourierovy a autokorelační analýzy. Pozorovat vstupní otvor keyhole je částečně možné prostřednictvím koaxiální kamery umístěné na svařovací hlavě a následného zpracování obrazu. Vysokorychlostní boční kamera pomáhá pochopit dynamiku plazmového obláčku. Prostřednictvím optické spektroskopie plazmatu, lze studovat excitaci prvků v materiálu. Proud ochranné atmosféry může být vizualizován za použití schlierové metody.\n\n
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Noise, Transport and Structural Properties of High Energy Radiation Detectors Based on CdTe
Šik, Ondřej ; Lazar, Josef (oponent) ; Navrátil, Vladislav (oponent) ; Grmela, Lubomír (vedoucí práce)
Because of demands from space research, healthcare and nuclear safety industry, gamma and X-ray imaging and detection is rapidly growing topic of research. CdTe and its alloy CdZnTe are materials that are suitable to detect high energy photons in range from 10 keV to 500 keV. Their 1.46 -1.6 eV band gap gives the possibility of high resistivity (10^10-10^11 cm) crystals production that is high enough for room temperature X-ray detection and imaging. CdTe/CdZnTe detectors under various states of their defectiveness. Investigation of detector grade crystals, crystals with lower resistivity and enhanced polarization, detectors with asymmetry of electrical characteristics and thermally degenerated crystals were subject of my work in terms of analysis of their current stability, additional noise, electric field distribution and structural properties. The results of the noise analysis showed that enhanced concentration of defects resulted into change from monotonous spectrum of 1/f noise to spectrum that showed significant effects of generation-recombination mechanisms. Next important feature of deteriorated quality of investigated samples was higher increase of the noise power spectral density than 2 with increasing applied voltage. Structural and chemical analyses showed diffusion of metal material and trace elements deeper to the crystal bulk. Part of this work is also focused on surface modification by argon ion beam and its effect on chemical and morphological properties of the surface.
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New Methods for Increasing Efficiency and Speed of Functional Verification
Zachariášová, Marcela ; Dohnal, Jan (oponent) ; Steininger, Andreas (oponent) ; Kotásek, Zdeněk (vedoucí práce)
In the development of current hardware systems, e.g. embedded systems or computer hardware, new ways how to increase their reliability are highly investigated. One way how to tackle the issue of reliability is to increase the efficiency and the speed of verification processes that are performed in the early phases of the design cycle. In this Ph.D. thesis, the attention is focused on the verification approach called functional verification. Several challenges and problems connected with the efficiency and the speed of functional verification are identified and reflected in the goals of the Ph.D. thesis. The first goal focuses on the reduction of the simulation runtime when verifying complex hardware systems. The reason is that the simulation of inherently parallel hardware systems is very slow in comparison to the speed of real hardware. The optimization technique is proposed that moves the verified system into the FPGA acceleration board while the rest of the verification environment runs in simulation. By this single move, the simulation overhead can be significantly reduced. The second goal deals with manually written verification environments which represent a huge bottleneck in the verification productivity. However, it is not reasonable, because almost all verification environments have the same structure as they utilize libraries of basic components from the standard verification methodologies. They are only adjusted to the system that is verified. Therefore, the second optimization technique takes the high-level specification of the system and then automatically generates a comprehensive verification environment for this system. The third goal elaborates how the completeness of the verification process can be achieved using the intelligent automation. The completeness is measured by different coverage metrics and the verification is usually ended when a satisfying level of coverage is achieved. Therefore, the third optimization technique drives generation of input stimuli in order to activate multiple coverage points in the veri\-fied system and to enhance the overall coverage rate. As the main optimization tool the genetic algorithm is used, which is adopted for the functional verification purposes and its parameters are well-tuned for this domain. It is running in the background of the verification process, it analyses the coverage and it dynamically changes constraints of the stimuli generator. Constraints are represented by the probabilities using which particular values from the input domain are selected. The fourth goal discusses the re-usability of verification stimuli for regression testing and how these stimuli can be further optimized in order to speed-up the testing. It is quite common in verification that until a satisfying level of coverage is achieved, many redundant stimuli are evaluated as they are produced by pseudo-random generators. However, when creating optimal regression suites, redundancy is not needed anymore and can be removed. At the same time, it is important to retain the same level of coverage in order to check all the key properties of the system. The fourth optimization technique is also based on the genetic algorithm, but it is not integrated into the verification process but works offline after the verification is ended. It removes the redundancy from the original suite of stimuli very fast and effectively so the resulting verification runtime of the regression suite is significantly improved.
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Exploitation of GPU in graphics and image processing algorithms
Jošth, Radovan ; Svoboda, David (oponent) ; Trajtel,, Ľudovít (oponent) ; Herout, Adam (vedoucí práce)
This thesis introduces several selected algorithms, which were primarily developed for CPUs, but based on high demand for improvements; we have decided to utilize it on behalf of GPGPU. This modification was at the same time goal of our research. The research itself was performed on CUDA enabled devices. The thesis is divided in accordance with three algorithm’s groups that have been researched: a real-time object detection, spectral image analysis and real-time line detection. The research on real-time object detection was performed by using LRD and LRP features. Research on spectral image analysis was performed by using PCA and NTF algorithms and for the needs of real-time line detection, we have modified accumulation scheme for the Hough transform in two different ways. Prior to explaining particular algorithms and performed research, GPU architecture together with GPGPU overview are provided in second chapter, right after an introduction. Chapter dedicated to research achievements focus on methodology used for the different algorithm modifications and authors’ assess to the research, as well as several products that have been developed during the research. The final part of the thesis concludes our research and provides more information about the research impact.
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Packet Classification Algorithms
Puš, Viktor ; Lhotka,, Ladislav (oponent) ; Dvořák, Václav (vedoucí práce)
This thesis deals with packet classification in computer networks. Classification is the key task in many networking devices, most notably packet filters - firewalls. This thesis therefore concerns the area of computer security. The thesis is focused on high-speed networks with the bandwidth of 100 Gb/s and beyond. General-purpose processors can not be used in such cases, because their performance is not sufficient. Therefore, specialized hardware is used, mainly ASICs and FPGAs. Many packet classification algorithms designed for hardware implementation were presented, yet these approaches are not ready for very high-speed networks. This thesis addresses the design of new high-speed packet classification algorithms, targeted for the implementation in dedicated hardware. The algorithm that decomposes the problem into several easier sub-problems is proposed. The first subproblem is the longest prefix match (LPM) operation, which is used also in IP packet routing. As the LPM algorithms with sufficient speed have already been published, they can be used in out context. The following subproblem is mapping the prefixes to the rule numbers. This is where the thesis brings innovation by using a specifically constructed hash function. This hash function allows the mapping to be done in constant time and requires only one memory with narrow data bus. The algorithm throughput can be determined analytically and is independent on the number of rules or the network traffic characteristics. With the use of available parts the throughput of 266 million packets per second can be achieved. Additional three algorithms (PFCA, PCCA, MSPCCA) that follow in this thesis are designed to lower the memory requirements of the first one without compromising the speed. The second algorithm lowers the memory size by 11 % to 96 %, depending on the rule set. The disadvantage of low stability is removed by the third algorithm, which reduces the memory requirements by 31 % to 84 %, compared to the first one. The fourth algorithm combines the third one with the older approach and thanks to the use of several techniques lowers the memory requirements by 73 % to 99 %.
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Generic Reverse Compilation to Recognize Specific Behavior
Ďurfina, Lukáš ; Šaloun, Petr (oponent) ; Zahradnický,, Tomáš (oponent) ; Kolář, Dušan (vedoucí práce)
Thesis is aimed on recognition of specific behavior by generic reverse compilation. The generic reverse compilation is a process that transforms executables from different architectures and object file formats to same high level language. This process is covered by a tool Lissom Decompiler. For purpose of behavior recognition the thesis introduces Language for Decompilation -- LfD. LfD represents a simple imperative language, which is suitable for a comparison. The specific behavior is given by the known executable (e.g. malware) and the recognition is performed as finding the ratio of similarity with other unknown executable. This ratio of similarity is calculated by a tool LfDComparator, which processes two sources in LfD to decide their similarity.
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High-Quality Shadow Rendering from Complex Light Sources
Navrátil, Jan ; Sochor, Jiří (oponent) ; Navrátil, Jan (oponent) ; Zemčík, Pavel (vedoucí práce)
In interactive applications, shadows are traditionally rendered using the shadow mapping algorithm. The disadvantage of the algorithm is limited resolution of depth texture which may lead to unpleasant visual artifacts on shadow edges. This work introduces an approach that is based on the improved texture warping. It allows for rendering a scene with the complex light sources, reduce the artifacts on the shadow boundaries and also improve the quality of the shadows regardless of the type of the scene and its configuration.
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