The impact of swirl (i.e., flow with axial and azimuthal velocity components) on the turbulent flow in a pipe is studied using two-component laser-Doppler velocimetry (LDV). There are practical motivations for the flow geometry. For example, previous studies demonstrate that introducing swirl in the tube bank of a paper machine headbox can significantly increase mixing, and hence increase fiber dispersion and orientation isotropy in the finished paper product. The flow characteristics in a pipe downstream of a single straight tapered fin, a single fin with 180??ist but otherwise identical geometry, and four twisted fins were therefore studied at a pipe-based Reynolds number of 80,000. Radial profiles of the mean and rms fluctuations of the streamwise and azimuthal velocity components are measured; results for the straight and twisted single fin are compared to determine the effects of fin geometry and swirl on the turbulent wake downstream of the fin. From a practical viewpoint, it is also desirable to have adjustable swirl, where swirl can either be turned on or off depending upon the type of paper product being produced. The next generation swirler concept consists of fins fabricated from two-way shape memory alloys. Using the two-way memory effect, the fins will be in their straight configuration when cold and twisted configuration (hence acting as a swirler) when hot. This study is the initial phase in developing new active control mechanisms, known as the Vortigen concept, for increasing productivity, and hence reducing wasted raw material and energy, in the pulp and paper industry.

Traditional financial modeling is based on semimartingale processes with stationary and independent increments. However, empirical investigations on financial data does not always support these assumptions. This contradiction showed that there is a need for new stochastic models. Fractional Brownian motion (fBm) was proposed as one of these models by Benoit Mandelbrot. FBm is the only continuous Gaussian process with dependent increments. Correlation between increments of a fBm changes according to its self-similarity parameter H. This property of fBm helps to capture the correlation dynamics of the data and consequently obtain better forecast results. But for values of H different than 1/2, fBm is not a semimartingale and classical Ito formula does not exist in that case. This gives rise to need for using the white noise theory to construct integrals with respect to fBm and obtain fractional Ito formulas. In this thesis, the representation of fBm and its fundamental properties are examined. Construction of Wick-Ito-Skorohod (WIS) and fractional WIS integrals are investigated. An Ito type formula and Girsanov type theorems are stated. The financial applications of fBm are mentioned and the Black&amp / Scholes price of a European call option on an asset which is assumed to follow a geometric fBm is derived. The statistical aspects of fBm are investigated. Estimators for the self-similarity parameter H and simulation methods of fBm are summarized. Using the R/S methodology of Hurst, the estimations of the parameter H are obtained and these values are used to evaluate the fractional Black&amp / Scholes prices of a European call option with different maturities. Afterwards, these values are compared to Black&amp / Scholes price of the same option to demonstrate the effect of long-range dependence on the option prices. Also, estimations of H at different time scales are obtained to investigate the multiscaling in financial data. An outlook of the future work is given.

This thesis has two related goals: the first involves the concept of self-similarity of images. Image self-similarity is important because it forms the basis for many imaging techniques such as non-local means denoising and fractal image coding. Research so far has been focused largely on self-similarity in the pixel domain. That is, examining how well different regions in an image mimic each other. Also, most works so far concerning self-similarity have utilized only the mean squared error (MSE). In this thesis, self-similarity is examined in terms of the pixel and wavelet representations of images. In each of these domains, two ways of measuring similarity are considered: the MSE and a relatively new measurement of image fidelity called the Structural Similarity (SSIM) Index. We show that the MSE and SSIM Index give very different answers to the question of how self-similar images really are. The second goal of this thesis involves non-local image processing. First, a generalization of the well known non-local means denoising algorithm is proposed and examined. The groundwork for this generalization is set by the aforementioned results on image self-similarity with respect to the MSE. This new method is then extended to the wavelet representation of images. Experimental results are given to illustrate the applications of these new ideas.

OLIVEIRA, Erneson Alves de. Geração de fraturas autossimilares em meios desordenados: técnicas do caminho crítico e do caminho mínimo. 2008. 54 f. Dissertação (Mestrado em Física) - Programa de Pós-Graduação em Física, Departamento de Física, Centro de Ciências, Universidade Federal do Ceará, Fortaleza, 2008. / Submitted by Edvander Pires (edvanderpires@gmail.com) on 2014-11-03T20:05:53Z No. of bitstreams: 1 2008_dis_eaoliveira.pdf: 13308297 bytes, checksum: 51bfea9dc79470d1077454f8be1b593a (MD5) / Approved for entry into archive by Edvander Pires(edvanderpires@gmail.com) on 2014-11-03T20:12:15Z (GMT) No. of bitstreams: 1 2008_dis_eaoliveira.pdf: 13308297 bytes, checksum: 51bfea9dc79470d1077454f8be1b593a (MD5) / Made available in DSpace on 2014-11-03T20:12:15Z (GMT). No. of bitstreams: 1 2008_dis_eaoliveira.pdf: 13308297 bytes, checksum: 51bfea9dc79470d1077454f8be1b593a (MD5) Previous issue date: 2008 / In this work we propose two models for fracture generation in regular substrates. In the first model, we iteratively apply the concept of critical path to systematically determine the lower “conductivity” element in the connected spanning network. At each iteration, once these elements are identified as local “cracks ́ ́, they are permanently removed from the structure up to the point in which a macroscopic fracture can destroy the global network connectivity. This fracture is then topologically characterized as self-similar with fractal dimension Dp ≈ 1.21. In the second model, we employ the algorithm of Dijkstra to determine the minimal path in a random energy landscape and remove its highest energy element. As in the previous model, these elements are considered to be local “cracks ́ ́ till a subset of them can be identified as a macroscopic fracture. The average over many samples of fractures calculated for different system sizes reveals the presence of a self-similar structure with fractal dimension Df ≈ 1.21. The resemblance between the two exponents Dp e Df suggests that the two models belong to the same universality class. / Neste trabalho propomos dois modelos para a geração de fraturas em substratos regulares. No primeiro modelo, empregamos iterativamente o conceito de caminho crítico para determinar sistematicamente o elemento de menor “condutividade” da rede. Estes elementos são então identificados como “falhas” e removidos permanentemente da estrutura até que uma fratura macroscópica destrua a conectividade global da rede. Uma vez detectada, esta fratura é caracterizada topologicamente como uma estrutura auto-similar de dimensão fractal Dp ≈ 1.21. No segundo modelo, empregamos iterativamente o algoritmo de Dijkstra para determinar o caminho mínimo em uma paisagem aleatória, retirando sistematicamente desta estrutura o elemento de maior energia. Como no modelo anterior, estes elementos são identificados como “falhas” até que um conjunto conecto deles resulte em uma fratura macroscópica. A média realizada sobre várias amostras de fraturas em diferentes tamanhos de substratos revela a presença de uma estrutura auto-similar de dimensão fractal Df ≈ 1.21. A semelhança numérica entre os expoentes Dp e Df sugere que os dois modelos pertencem à mesma classe de universalidade.

The rising power demands and cost motivates us to explore low power solutions in electronics. In nanometer Complementary Metal Oxide Semiconductor (CMOS) processes with low threshold voltages and thin gate oxides, subthreshold leakage power dominates total power of a circuit. As technology scales, Negative Bias Temperature Instability (NBTI) emerged as a major limiting reliability mechanism. It causes a threshold voltage shift which, over time, results in circuit performance degradation. Hence, leakage power and NBTI degradation are two key challenges in deep sub micron regime. In this dissertation, interval arithmetic based interval propagation technique is introduced as an effective leakage optimization technique in high level circuits with little overhead. The concept of self similarity from fractal theory is adopted for the first time in VLSI research to handle large design space. Though there are some leakage and NBTI co-optimization techniques in literature, our vector cycling approach combined with a back tracking algorithm have achieved better results for ISCAS85 benchmarks. We did not find any previous research works on NBTI optimization of finite state machines (FSMs). The optimization techniques of NBTI optimization in FSMs is introduced in this dissertation as well and substantial NBTI optimization is reported. Input vector control has been shown to be an effective technique to minimize subthreshold leakage. Applying appropriate minimum leakage vector (MLV) to each register transfer level (RTL) module instance results in a low leakage state with significant area overhead. For each module, via Monte Carlo simulation, we identify a set of MLV intervals such that maximum leakage is within (say) 10% of the lowest leakage points. As the module bit width increases, exhaustive simulation to find the low leakage vector is not feasible. Further, we need to search the entire input space uniformly to obtain as many low leakage intervals as possible. Based on empirical observations, we observed self similarity in the leakage distribution of adder/multiplier modules when input space is partitioned into smaller cells. This property enables uniform search of low leakage vectors in the entire input space. Also, the time taken for characterization increases linearly with the module size. Hence, this technique is scalable to higher bit width modules with acceptable characterization time. We can reduce area overhead (in some cases to 0) by choosing Primary Input (PI) MLVs such that resultant inputs to internal nodes are also MLVs. Otherwise, control points can be inserted. Based on interval arithmetic, given a DFG, we propose a heuristic with several variations for PI MLV identification with minimal control points. Experimental results for DSP filters simulated in 16nm technology demonstrated leakage savings of 93.8% with no area overhead, compared to existing work. Input vector control can also be adopted to reduce NBTI degradation as well as leakage in CMOS circuits. In the prior work, it is shown that minimum leakage vector of a circuit is not necessarily NBTI friendly. In order to achieve NBTI and leakage co-optimization, we propose an input vector cycling technique which applies different sub-optimal low leakage vectors to primary inputs at regular intervals. A co-optimal input vector for a given circuit is obtained by using simulated annealing (SA) technique. For a given input vector, a set of critical path PMOS transistors are under stress. A second input vector is obtained using a back tracking algorithm such that most of the critical path PMOS transistors are put in recovery mode. When a co-optimized input vector is assigned to primary input, critical path nodes under stress with high delay contribution are set to recovery. Logic 1 is back propagated from the nodes to the primary inputs to obtain the second input vector. These two vectors are alternated at regular time intervals. The total stress is evenly distributed among transistor sets of two vectors, as the intersection of the two sets is minimized. Hence, the overall stress on critical path transistors is alleviated, thereby reducing the NBTI delay degradation. For ISCAS85 benchmarks, an average of 5.3% improvement is achieved in performance degradation at 3.3% leakage overhead with NBTI-leakage co-optimization with a back tracking algorithm compared to solely using co-optimization. A 10.5% average NBTI improvement is obtained when compared to circuit with minimum leakage input vector for 18% average leakage overhead. Also, an average NBTI improvement of 2.13% is obtained with 6.77% leakage improvement when compared to circuit with minimum NBTI vector. Vector cycling is shown to be more effective in mitigating NBTI over input vector control. Several works in the literature have proposed optimal state encoding techniques for delay, leakage, and dynamic power optimization. In this work, we propose, for the first time, NBTI optimization based on state code optimization. We propose a SA based state code assignment algorithm, resulting in minimization of NBTI degradation in the synthesized circuit. A PMOS transistor when switched ON for a long period of time, will lead to delay degradation due to NBTI. Therefore, in combinational circuits, an NBTI friendly input vector that stresses the least number of PMOS transistors on the critical path can be applied. For sequential circuits, the state code can significantly influence the ON/OFF mode of PMOS transistors in the controller implementation. Therefore, we propose to focus on state encoding. As the problem is computational intractable, we will focus on encoding states with high state probability. The following SA moves are employed: (a) code swap; and (b) code modification by flipping bits. Experiments with LGSYNTH93 benchmarks resulted in 18.6% improvement in NBTI degradation on average with area and power improvements of 5.5% and 4.6% respectively.

Theses deals with network traffic modeling focused on elaboration by time series analysis. The nature of network traffic is discussed above all http traffic. First three chapters are theoretical, which describes time series and basic models, linear AR, MA, ARMA, ARIMA and nonlinear ARCH. Other chapters define terms like self-similarity and long range dependence. It is demonstrated a failure of conventional models which cannot capture these specific properties of network data traffic. On the basis of study in chapter 6. is closely described the combined ARIMA/GARCH model and its parameter estimation procedure. Applied part of this theses deals with procedure of estimation and fitting the estimation model to observed network traffic. After an estimation a few future values are predicted on the basis of estimated model. These predicted values are consequently compared with real data.

Title: Source Parameters of Microearthquakes and their Uncertainty Author: Jan Michálek Department: Department of Geophysics Supervisor: Doc. RNDr. Tomáš Fischer, PhD., Institute of Hydrogeology, Engineering Geology and Applied Geophysics, Charles University in Prague Abstract: The aim of this thesis is to analyze the spectral methods used for the determination of the earth- quake source parameters like the seismic moment M0 and the corner frequency fc and to apply these meth- ods to seismic data from the West Bohemian region. Considering some assumptions about the source the other important parameters like the source radius r or the stress drop in the source ∆σ can be evaluated. Determination of the parameters is performed in the spectral domain by comparing a simple Brune's source model (non-causal slip on a circular rupture; spectral slope ω−2) with the displacement of the P or S wave. The methods were applied to 56 selected earthquakes of the West Bohemian swarms from 2000 and 2008 by the absolute and relative approach in several modifications. The absolute method allows to determine not only the source parameters but also the quality factor Q (attenuation), which significantly affects the deter- mination of fc. Therefore, the absolute method was applied also as the joint inversion when Q is stabilized....

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Technical advancements allow for embodied virtual agents to not only be increasingly human-like, but also to behave and look like particular individuals. As biases towards self-similarity have been found in human-human studies, it is of interest to explore to what extent this applies to virtual characters (VCs). This work set out to extend on previous research that has investigated the effects of facial self-similarity in VCs, and explore it in the context of empathic emotion. For this aim, a method for creating facially similar virtual characters was developed and a user study conducted where 13 participants were told autobiographical stories by a virtual character that either did or did not resemble them facially and/or in gender category. The participants' first impressions and emotional responses were measured. The results showed that even though similarity was not explicitly perceived, a bias might exist towards more positive impressions of self-similar characters, especially in terms of gender category. Regarding the emotional responses, the results did not allow for discovering any difference between conditions but pointed to some interesting differences in comparison to what was hypothesized. The immense ways in which the appearances of virtual characters can be altered provides possibilities to influence the interaction with them. However, although biases might exist on a general level, it is difficult to predict the human responses in individual cases. Virtual characters might make possible a more human-like interaction with technology, however, it might also mean that our reactions to them are influenced by more parameters and our relations to them become even more like those with other humans: complex. / Den tekniska utvecklingen möjliggör numera att virtuella agenter kan göras inte bara människolika, utan även lika specifika individer i hur de beter sig och ser ut. Då tidigare studier påvisat att människor ofta föredrar personer som i någon mån liknar dem själva, är det intressant att utforska i vilken utsträckning detta även gäller virtuella karaktärer. Detta arbete hade som mål att undersöka effekterna av visuella likheter mellan människor och virtuella karaktärer, med fokus på ansikten och genus och i en kontext där empati är betydande. En metod för att konstruera virtuella karaktärer som hade visuella likheter med specifika användare utvecklades, och en användarstudie med 13 deltagare genomfördes. I det konstruerade scenariot berättade en karaktär, som hade likheter med användaren antingen gällande ansiktets utseende och/eller genus, självbiografiska historier. Intrycket av karaktären och den emotionella responsen mättes. Resultaten visade att den visuella likheten inte uppfattades explicit. Dock fanns tendenser som pekar på att likheter framför allt när det gäller sociala kategorier som genus, kan ha en positiv påverkan på hur virtuella karaktärer uppfattas. Det gick inte att upptäcka några skillnader mellan betingelserna gällande den emotionella responsen, men resultaten påvisade intressanta avvikelser från de förväntade reaktionerna. Möjligheterna att designa och anpassa virtuella karaktärer till olika individer och situationer ökar, vilket kan utnyttjas för att försöka påverka hur människor förhåller sig till och interagerar med dem. Det är dock svårt att förutsäga hur människor kommer att reagera och relatera till en virtuell karaktär utifrån generella tendenser, vilket denna studie visar. Virtuella karaktärer kan möjliggöra en mer människolik interaktion med teknik, men det innebär också att många parametrar är inblandade och att relationerna med tekniken blir liksom relationerna mellan människor: komplexa.

No / Many recent studies have convincingly demonstrated that network traffic exhibits a noticeable self-similar nature which has a considerable impact on queuing performance. However, the networks used in current multicomputers have been primarily designed and analyzed under the assumption of the traditional Poisson arrival process, which is inherently unable to capture traffic self-similarity. Consequently, it is crucial to reexamine the performance properties of multicomputer networks in the context of more realistic traffic models before practical implementations show their potential faults. In an effort toward this end, this paper proposes the first analytical model for wormhole-switched k-ary n-cubes in the presence of self-similar traffic. Simulation experiments demonstrate that the proposed model exhibits a good degree of accuracy for various system sizes and under different operating conditions. The analytical model is then used to investigate the implications of traffic self-similarity on network performance. This study reveals that the network suffers considerable performance degradation when subjected to self-similar traffic, stressing the great need for improving network performance to ensure efficient support for this type of traffic.