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Ekonomická diplomacie České republiky - současná podoba a nové výzvy do budoucna
Polednik, Petr ; Peterková, Jana (vedoucí práce) ; Trávníčková, Zuzana (oponent)
Tato diplomová práce se věnuje ekonomické diplomacii České republiky. První kapitola se zaměřuje na teoretické vymezení ekonomické diplomacie, konkrétně na definici, funkce a úkoly, aktéry a modely řízení ekonomické diplomacie. Druhá kapitola charakterizuje z pohledu státních aktérů přístupy k ekonomické diplomacii ve vybraných zemí Evropy, které mohou sloužit jako inspirace pro Českou republiku. Třetí kapitola se pak detailně věnuje charakteristice současné podoby ekonomické diplomacie ČR, chystaným novinkám a jejímu možnému vývoji a výzvám v následujících letech.
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Sperm protein profiles of different mammalian species
Pohlová, Alžběta ; Zigo, Michal ; Jonáková, Věra ; Postlerová, Pavla
Proteins are a substantial equipment of the spermatic cell; therefore, the characterization of sperm proteins is crucial for explanation of molecular mechanisms in the reproduction process. We isolated sperm proteins from different mammalian species - pig, bull, human, mouse, dog and cat. Extracted proteins were separated by SDS-electrophoresis and protein/glycoprotein profiles from epididymal or ejaculated sperm were compared. Additionally, we tested cross-reactivity of antibodies prepared to sperm boar proteins on spermatozoa of other mammalian species using immunofluorescent technique. Our future plan is to compare the protein profiles of sperm during their functional development (epididymal, ejaculated, capacitated) in various mammalian species and identify species-specific sperm proteins with zona pellucida binding activity.
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Role of Psb28 proteins in the biogenesis of the Photosystem II complex in the cyanobacterium Synechocystis sp. PCC 6803
BEČKOVÁ, Martina
The thesis focuses on the role of Psb28 proteins, namely the Psb28-1 and its homolog Psb28-2, in the biogenesis of the Photosystem II complex (PSII) in the cyanobacterium Synechocystis PCC 6803. The aims of this work were to localize the proteins within the cells, and to determine their function. A fraction of both Psb28 proteins was identified in the monomeric PSII core complexes but most proteins were found in the unassembled protein fraction associated with thylakoid membranes. Psb28-1 was mostly detected as a dimer while Psb28-2 as a monomer. Psb28-1 also differed from Psb28-2 by its higher affinity to the PSII core complex lacking CP43 antenna. Characterization of Psb28-less mutants suggested regulatory function of the proteins in PSII biogenesis in connection with chlorophyll biosynthetic pathway. Analysis of preparations isolated using FLAG-tagged versions of Psb28 proteins showed their association with Photosystem II - Photosystem I supercomplexes, especially under increased irradiance, and supported a role of Photosystem I in the PSII biogenesis.
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Nájem bytu manželi a užívání družstevního bytu manželi v nové úpravě po 1.1.2014
Prantlová, Soňa ; Kadlecová, Eva (vedoucí práce) ; Pavla, Pavla (oponent)
Diplomová práce se věnovala tématu nájmu bytu manželi a jeho užívání tak, jak je to zakotveno v nové zákonné úpravě občanského zákoníku č. 89/2012 Sb. Ten nahradil do té doby fungující občanský zákoník z roku 1964. V nové právní úpravě je zakotvena řada nových institutů, jejichž cílem je především ochránit slabší stranu, v tomto případě nájemce. Diplomová práce byla rozčleněna na teoretickou a praktickou část. V teoretické části byla věnována pozornost základním pojmům, které zde byly definovány. Byla zde charakterizována práva nájemce a pronajímatele. Byla rozebrána právní úprava bydlení dle nového občanského zákoníku. Praktická část se věnovala interpretaci výsledků dotazníkového šetření. Byli osloveni nájemci několika bytových domů ve městě Kralupy nad Vltavou. Na základě dosažených zjištění byla navržena některá doporučení pro zvýšení informovanosti o právech a povinnostech nájemců, jakož i o celé problematice bydlení z právního hlediska.
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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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Inteligence skupiny
Winklerová, Zdenka ; Šaloun, Petr (oponent) ; Škrinárová,, Jarmila (oponent) ; Zbořil, František (vedoucí práce)
Záměrem disertační práce je aplikovaný výzkum skupinové ( kolektivní ) inteligence . K prokázání použitelnosti inteligence skupiny je zkoumán algoritmus na bázi roje částic ( Particle Swarm Optimization PSO ), v němž je problém inteligence skupiny převeden na matematickou optimalizaci, kdy roj částic ( particle swarm ) hledá globální optimum ve vymezeném prostoru problému a prohledávání je řízeno podle předem nadefinované účelové funkce ( objective function ), která zastupuje řešený problém. Byla navržena a experimentálně ověřena strategie prohledávání, v níž částice průběžně přizpůsobují své chování charakteristikám prostoru řešeného problému, a bylo experimentálně zjištěno, jak se vliv řídící účelové funkce zastupující řešený problém projevuje v chování částic. Výsledky experimentování s navrženou strategií prohledávání byly porovnány s výsledky experimentů s referenční verzí algoritmu PSO . Experimenty ukázaly, že klasické prohledávání, kde jedinou podmínkou je stabilní trajektorie, po níž se částice pohybuje v prostoru řešeného problému, a kde je ve výsledku eliminován vliv řídící účelové funkce, může selhat a že dynamická stabilita trajektorií částic sama o sobě není ukazatelem prohledávacích schopností algoritmu ani konvergence algoritmu ke správnému, globálnímu řešení. Byl navržen způsob prohledávání prostoru řešeného problému, v němž algoritmus PSO reguluje stabilitu algoritmu průběžným přizpůsobováním chování částic charakteristikám prostoru problému. Navržený algoritmus usměrňoval vývoj prohledávání prostoru problému tak, že vzrostla pravděpodobnost úspěšnosti řešení.
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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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Acceleration of Object Detection Using Classifiers
Juránek, Roman ; Kälviäinen, Heikki (oponent) ; Sojka, Eduard (oponent) ; Zemčík, Pavel (vedoucí práce)
Detection of objects in computer vision is a complex task. One of most popular and well explored approaches is the use of statistical classifiers and scanning windows. In this approach, classifiers learned by AdaBoost algorithm (or some modification) are often used as they achieve low error rates, high detection rates and they are suitable for detection in real-time applications. Object detection run-time which uses such classifiers can be implemented by various methods and properties of underlying architecture can be used for speed-up of the detection. For the purpose of acceleration, graphics hardware, multi-core architectures, SIMD or other means can be used. The detection is often implemented on programmable hardware. The contribution of this thesis is to introduce an optimization technique which enhances object detection performance with respect to an user defined cost function. The optimization balances computations of previously learned classifiers between two or more run-time implementations in order to minimize the cost function. The optimization method is verified on a basic example -- division of a classifier to a pre-processing unit implemented in FPGA, and a post-processing unit in standard PC.
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