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Optický rezonátor s nízkou disperzí pro účely délkového senzoru využivající optický frekvenční hřeben
Pravdová, Lenka ; Hucl, Václav ; Lešundák, Adam ; Lazar, Josef ; Číp, Ondřej
Ultra přesná měření délky jsou doménou laserových interferometrů. Na našem pracovišti jsme navrhli a experimentálně ověřili metodu měření s optickým rezonátorem, která využívá širokospektrálního záření optického frekvenčního hřebene. Měřená délka, tj. délka rezonátoru, je pak převedena na hodnotu opakovací frekvence pulsního laseru se synchronizací modů optického frekvenčního hřebene. V našem příspěvku nyní představujeme porovnání absolutní stupnice optického rezonátoru se stupnicí inkrementálního interferometru. Inkrementální interferometr je do sestavy implementován pro provedení požadované verifikace stupnice optického rezonátoru. Dvousvazkový inkrementální interferometr pracuje na vlnové délce 633 nm a měřicí zrcadlo rezonátoru vybavené piezo posuvem je s výhodou použito zároveň i jako zpětný odrážeč pro tento interferometr. Jako markantní chybový signál se zde projevuje periodická nelinearita stupnice inkrementálního interferometru. Relativní rozlišení naší metody tak dosahuje hodnoty až 10-9 při zachování absolutní stupnice měření.\n
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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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Subspace Modeling of Prosodic Features for Speaker Verification
Kockmann, Marcel ; Kenny, Patrick (oponent) ; Nöth, Elmar (oponent) ; Černocký, Jan (vedoucí práce)
The thesis investigates into speaker verification by means of prosodic features. This includes an appropriate representation of speech by measurements of pitch, energy and duration of speech sounds. Two diverse parameterization methods are investigated: the first leads to a low-dimensional well-defined set, the second to a large-scale set of heterogeneous prosodic features. The first part of this work concentrates on the development of so called prosodic contour features. Different modeling techniques are developed and investigated, with a special focus on subspace modeling. The second part focuses on a novel subspace modeling technique for the heterogeneous large-scale prosodic features. The model is theoretically derived and experimentally evaluated on official NIST Speaker Recognition Evaluation tasks. Huge improvements over the current state-of-the-art in prosodic speaker verification were obtained. Eventually, a novel fusion method is presented to elegantly combine the two diverse prosodic systems. This technique can also be used to fuse the higher-level systems with a high-performing cepstral system, leading to further significant improvements.
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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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Expozice dětí atmosférickému aerosolu ve školních tělocvičnách
Šafránek, Jiří ; Braniš, Martin (vedoucí práce) ; Holcátová, Ivana (oponent) ; Heller, Jan (oponent)
Výsledky výzkumu zaměřeného na vnitřní prostředí škol dokazují, že jsou to budovy s vysokými úrovněmi koncentrací aerosolu (PM). Jde především o školy v místech s hustým automobilovým provozem a v průmyslových oblastech. Negativní vliv expozice aerosolu na zdraví dospívající generace je rovněž dokumentován v řadě studií. Málo pozornosti bylo ale dosud věnováno mikroprostředí školních tělocvičen, kde má dynamika aerosolu svá specifika související s různorodostí tohoto prostředí a v ní prováděných lidských aktivit. Vlivem zvýšené plicní ventilace mohou expozice cvičících dosahovat hodnot s negativním dopadem na jejich zdraví. Velikostně rozlišené koncentrace aerosolu byly měřeny ve třech základních školách Prahy. V údolní poloze vysoce dopravně zatíženého centra města, na náhorní rovině dopravně středně zatíženého okraje města a na jihozápadním předměstí v lokalitě příměstského bydlení blízkého přírodě a dopravně málo zatížené. Koncentrace aerosolu byly měřeny současně v přirozeně větraných tělocvičnách a ve venkovním prostředí škol dvěma páry monitorů. Fotometrem DusTrak a gravimetricky, pětistupňovým kaskádovým impaktorem Personal Cascade Impactor Sampler. V letech 2005 až 2009 proběhlo na školách dohromady dvacet 7-11 denních kampaní v celkové délce 177 dnů. Metodami Scanning eloctron microscopy...
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On-line Data Analysis Based on Visual Codebooks
Beran, Vítězslav ; Honec, Jozef (oponent) ; Sojka, Eduard (oponent) ; Zemčík, Pavel (vedoucí práce)
This work introduces the new adaptable method for on-line video searching in real-time based on visual codebook. The new method addresses the high computational efficiency and retrieval performance when used on on-line data. The method originates in procedures utilized by static visual codebook techniques. These standard procedures are modified to be able to adapt to changing data. The procedures, that improve the new method adaptability, are dynamic inverse document frequency, adaptable visual codebook and flowing inverted index. The developed adaptable method was evaluated and the presented results show how the adaptable method outperforms the static approaches when evaluating on the video searching tasks. The new adaptable method is based on introduced flowing window concept that defines the ways of selection of data, both for system adaptation and for processing. Together with the concept, the mathematical background is defined to find the best configuration when applying the concept to some new method. The practical application of the adaptable method is particularly in the video processing systems where significant changes of the data domain, unknown in advance, is expected. The method is applicable in embedded systems monitoring and analyzing the broadcasted TV on-line signals in real-time.
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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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Security of Contactless Smart Card Protocols
Henzl, Martin ; Rosa, Tomáš (oponent) ; Staudek, Jan (oponent) ; Hanáček, Petr (vedoucí práce)
This thesis analyses contactless smart card protocol threats and presents a method of semi-automated vulnerability finding in such protocols using model checking. Designing and implementing secure applications is difficult even when secure hardware is used. High level application specifications may lead to different implementations. It is important to use the smart card correctly, inappropriate protocol implementation may introduce a vulnerability, even if the protocol is secure by itself. The goal of this thesis is to provide a method that can be used by protocol developers to create a model of arbitrary smart card, with focus on contactless smart cards, to create a model of the protocol, and to use model checking to find attacks in this model. The attack can be then executed and if not successful, the model is refined for another model checker run. The AVANTSSAR platform was used for the formal verification, models are written in the ASLan++ language. Examples are provided to demonstrate usability of the proposed method. This method was used to find a weakness of Mifare DESFire contactless smart card. This thesis also deals with threats not possible to cover by the proposed method, such as relay attacks.
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