Opportunistic communication techniques have shown to provide significant performance improvements in centralised random access wireless networks. The key mechanism of opportunistic communication is to send back-to-back data packets whenever the channel quality is deemed "good". Recently there have been attempts to introduce opportunistic communication techniques in distributed wireless networks such as wireless ad hoc networks. In line of this research, we propose a new paradigm of medium access control, called Channel MAC based on the channel randomness and opportunistic communication principles. Scheduling in Channel MAC depends on the instance at which the channel quality improves beyond a threshold, while neighbouring nodes are deemed to be silent. Once a node starts transmitting, it will keep transmitting until the channel becomes "bad". We derive an analytical throughput equation of the proposed MAC in a multiple access environment and validate it by simulations. It is observed that Channel MAC outperforms IEEE 802.11 for all probabilities of good channel condition and all numbers of nodes. For higher number of nodes, Channel MAC achieves higher throughput at lower probabilities of good channel condition increasing the operating range. Furthermore, the total throughput of the network grows with increasing number of nodes considering negligible propagation delay in the network. A scalable channel prediction scheme is required to implement the practical Channel MAC protocol in practice. We propose a mean-value based channel prediction scheme, which provides prediction with enough accuracy to be used in the Channel MAC protocol. NS2 simulation result shows that the Channel MAC protocol outperforms the IEEE 802.11 in throughput due to its channel diversity mechanism in spite of the prediction errors and packet collisions. Next, we extend the Channel MAC protocol to support multi-rate communications. At present, two prominent multi-rate mechanisms, Opportunistic Auto Rate (OAR) and Receiver Based Auto Rate (RBAR) are unable to adapt to short term changes in channel conditions during transmission as well as to use optimum power and throughput during packet transmissions. On the other hand, using channel predictions, each source-destinations pair in Channel MAC can fully utilise the non-fade durations. We combine the scheduling of Channel MAC and the rate adaptive transmission based on the channel state information to design the 'Rate Adaptive Channel MAC' protocol. However, to implement the Rate adaptive Channel MAC, we need to use a channel prediction scheme to identify transmission opportunities as well as auto rate adaptation mechanism to select rates and number of packets to transmit during those times. For channel prediction, we apply the scheme proposed for the practical implementation of Channel MAC. We propose a "safety margin" based technique to provide auto rate adaptation. Simulation results show that a significant performance improvement can be achieved by Rate adaptive Channel MAC as compared to existing rate adaptive protocols such as OAR.

Opportunistic communication techniques have shown to provide significant performance improvements in centralised random access wireless networks. The key mechanism of opportunistic communication is to send back-to-back data packets whenever the channel quality is deemed "good". Recently there have been attempts to introduce opportunistic communication techniques in distributed wireless networks such as wireless ad hoc networks. In line of this research, we propose a new paradigm of medium access control, called Channel MAC based on the channel randomness and opportunistic communication principles. Scheduling in Channel MAC depends on the instance at which the channel quality improves beyond a threshold, while neighbouring nodes are deemed to be silent. Once a node starts transmitting, it will keep transmitting until the channel becomes "bad". We derive an analytical throughput equation of the proposed MAC in a multiple access environment and validate it by simulations. It is observed that Channel MAC outperforms IEEE 802.11 for all probabilities of good channel condition and all numbers of nodes. For higher number of nodes, Channel MAC achieves higher throughput at lower probabilities of good channel condition increasing the operating range. Furthermore, the total throughput of the network grows with increasing number of nodes considering negligible propagation delay in the network. A scalable channel prediction scheme is required to implement the practical Channel MAC protocol in practice. We propose a mean-value based channel prediction scheme, which provides prediction with enough accuracy to be used in the Channel MAC protocol. NS2 simulation result shows that the Channel MAC protocol outperforms the IEEE 802.11 in throughput due to its channel diversity mechanism in spite of the prediction errors and packet collisions. Next, we extend the Channel MAC protocol to support multi-rate communications. At present, two prominent multi-rate mechanisms, Opportunistic Auto Rate (OAR) and Receiver Based Auto Rate (RBAR) are unable to adapt to short term changes in channel conditions during transmission as well as to use optimum power and throughput during packet transmissions. On the other hand, using channel predictions, each source-destinations pair in Channel MAC can fully utilise the non-fade durations. We combine the scheduling of Channel MAC and the rate adaptive transmission based on the channel state information to design the 'Rate Adaptive Channel MAC' protocol. However, to implement the Rate adaptive Channel MAC, we need to use a channel prediction scheme to identify transmission opportunities as well as auto rate adaptation mechanism to select rates and number of packets to transmit during those times. For channel prediction, we apply the scheme proposed for the practical implementation of Channel MAC. We propose a "safety margin" based technique to provide auto rate adaptation. Simulation results show that a significant performance improvement can be achieved by Rate adaptive Channel MAC as compared to existing rate adaptive protocols such as OAR.

[Formulae and special characters can only be approximated here. Please see the pdf version of the abstract for an accurate reproduction.] This thesis reviews, extends and applies to urban traffic analysis the entropy concept of Shannon and Luce's mathematical psychology in a fairly complex and mathematically demanding model of human decision making, if it is solved as a deeply nested structure of logit calculus. Recognising consumers' different preferences and the universal propensity to seek the best choice when going to some desired goal (k), a transparent mathematical program (MP) is developed: the equivalent of a nested multinomial logit model without its inherent computational difficulty. The MP model makes a statistical assessment of individual decisions based on a randomised (measurable) utility within a given choice structure: some path through a diagram (Rk, Dk), designed a priori, of a finite number of sequential choices. The Equivalence Theorem (ET) formalises the process and states a non-linear MP with linear constraints that maximises collective satisfaction: utility plus weighted entropy, where the weight (1/θn) is a behavioural parameter to be calibrated in each case, eg for the Perth CBD. An optimisation subject to feasible routes through the (Rk, Dk) network thus captures the rational behaviour of consumers on their individually different best-choice decision paths towards their respective goals (k). This theory has been applied to urban traffic assignment before: a Stochastic User Equi-librium (SUE). What sets this thesis apart is its focus on MP models that can be solved with standard Operations Research software (eg MINOS), models for which the ET is a conditio sine qua non. A brief list of SUE examples in the literature includes Fisk's logit SUE model in (impractically many) route flows. Dial's STOCH algorithm obviates path enumeration, yet is a logit multi-path assignment procedure, not an MP model; it is nei-ther destination oriented nor an optimisation towards a SUE. A revision of Dial's method is provided, named STOCH[k], that computes primal variables (node and link flows) and Lagrangian duals (the satisfaction difference n→k). Sheffi & Powell presented an unconstrained optimisation problem, but favoured a probit SUE, defying closed formulae and standard OR software. Their model corresponds to the (constrained) dual model here, yet the specifics of our primary MP model and its dual are possible only if one restricts himself to logit SUE models, including the ET, which is logit-specific. A real world application needs decomposition, and the Perth CBD example is iteratively solved by Partial Linearisation, switching from (measured) disutility minimisation to Sheffi & Powell's Method of Successive Averages near the optimum. The methodology is demonstrated on the Perth Central Business District (CBD). To that end, parameter Θ is calibrated on Main Roads' traffic count data over the years 1997/98 and 1998/99. The method is a revision of Liu & Fricker's simultaneous estimation of not only Θ but an appropriate trip matrix also. Our method handles the more difficult variable costs (congestion), incomplete data (missing observations) and observation errors (wrong data). Finally, again based on Main Roads' data (a sub-area trip matrix), a Perth CBD traffic assignment is computed, (a) as a logit SUE and - for comparison - (b) as a DUE (using the PARTAN method of Florian, Guélat and Spiess). The results are only superficially similar. In conclusion, the methodology has the potential to replace current DUE models and to deepen transport policy analysis, taking into account individual behaviour and a money-metric utility that quantifies 'social benefits', for instance in a cost-benefit-analysis.

A compreensão dos fenômenos de adsorção e difusão em superfícies é fundamental no desenvolvimento de materiais de alto rendimento utilizados em uma série de processos de grande relevância industrial. A modelagem de materiais adsorventes porosos através de modelos de rede tem seu potencial uma vez que se pode estudar os fenômenos a nível microscópico incorporando uma série de parâmetros estatísticos importantes na compreensão dos mecanismos nessa escala. Neste trabalho de dissertação de mestrado, em um primeiro momento, foram utilizadas redes bidimensionais quadradas com abordagem de percolação de sítio-sítio para modelar superfícies sujeitas às condições de adsorção em tempo infinito, com o intuito de se estudar as isotermas de adsorção em processos batelada. Numa primeira parte foi observada uma relação estatística na determinação das isotermas de adsorção, em que a probabilidade de adsorção estava condicionada ao número de moléculas na fase líquida. Na segunda parte foram incorporados diferentes tipos e tamanhos de moléculas, sendo observados diferentes comportamentos das isotermas de adsorção de acordo com a variação dessas moléculas adsorvidas. Outro fenômeno de interesse foi o estudo do Limiar de Percolação utilizando diferentes tipos e tamanhos de moléculas, sendo observados comportamentos específicos para cada caso. Desta forma, pode-se obter parâmetros das isotermas relacionados com os tipos e tamanhos moleculares estudados, sendo observado uma forte dependência daqueles com o tamanho da molécula, uma vez que a seletividade à adsorção aumenta com o tamanho da molécula. Ainda nesta primeira parte foram calculados também a probabilidade de ocupação relacionada com a entropia, observando comportamentos na probabilidade de ocupação a cada etapa de tempo. Em um segundo momento, foi estudado a dinâmica de difusão, mediante random walk ou passeadores aleatórios, em redes quadradas e cúbicas, em que foram obtidas leis de potência para cada dimensão. Aspectos como dispersão axial e porosidade foram incorporadas nas simulações, sendo abservados comportamentos específicos para cada caso.

A compreensão dos fenômenos de adsorção e difusão em superfícies é fundamental no desenvolvimento de materiais de alto rendimento utilizados em uma série de processos de grande relevância industrial. A modelagem de materiais adsorventes porosos através de modelos de rede tem seu potencial uma vez que se pode estudar os fenômenos a nível microscópico incorporando uma série de parâmetros estatísticos importantes na compreensão dos mecanismos nessa escala. Neste trabalho de dissertação de mestrado, em um primeiro momento, foram utilizadas redes bidimensionais quadradas com abordagem de percolação de sítio-sítio para modelar superfícies sujeitas às condições de adsorção em tempo infinito, com o intuito de se estudar as isotermas de adsorção em processos batelada. Numa primeira parte foi observada uma relação estatística na determinação das isotermas de adsorção, em que a probabilidade de adsorção estava condicionada ao número de moléculas na fase líquida. Na segunda parte foram incorporados diferentes tipos e tamanhos de moléculas, sendo observados diferentes comportamentos das isotermas de adsorção de acordo com a variação dessas moléculas adsorvidas. Outro fenômeno de interesse foi o estudo do Limiar de Percolação utilizando diferentes tipos e tamanhos de moléculas, sendo observados comportamentos específicos para cada caso. Desta forma, pode-se obter parâmetros das isotermas relacionados com os tipos e tamanhos moleculares estudados, sendo observado uma forte dependência daqueles com o tamanho da molécula, uma vez que a seletividade à adsorção aumenta com o tamanho da molécula. Ainda nesta primeira parte foram calculados também a probabilidade de ocupação relacionada com a entropia, observando comportamentos na probabilidade de ocupação a cada etapa de tempo. Em um segundo momento, foi estudado a dinâmica de difusão, mediante random walk ou passeadores aleatórios, em redes quadradas e cúbicas, em que foram obtidas leis de potência para cada dimensão. Aspectos como dispersão axial e porosidade foram incorporadas nas simulações, sendo abservados comportamentos específicos para cada caso.

Diese Dissertation widmet sich der Untersuchung singulärer stochastischer partieller Differentialgleichungen (engl. SPDEs). Wir entwickeln Erweiterungen der bisherigen Lösungstheorien, zeigen fundamentale Beziehungen zwischen verschiedenen Ansätzen und präsentieren Anwendungen in der Finanzmathematik und der mathematischen Physik. Die Theorie parakontrollierter Systeme wird für diskrete Räume formuliert und eine schwache Universalität für das parabolische Anderson Modell bewiesen. Eine fundamentale Relation zwischen Hairer's modellierten Distributionen und Paraprodukten wird bewiesen: Wir zeigen das sich der Raum modellierter Distributionen durch Paraprodukte beschreiben lässt. Dieses Resultat verallgemeinert die Fourierbeschreibung von Hölderräumen mittels Littlewood-Paley Theorie. Schließlich wird die Existenz von Lösungen der stochastischen Schrödingergleichung auf dem ganzen Raum bewiesen und eine Anwendung Hairer's Theorie zur Preisermittlung von Optionen aufgezeigt. / This thesis is concerned with the study of singular stochastic partial differential equations (SPDEs). We develop extensions to existing solution theories, present fundamental interconnections between different approaches and give applications in financial mathematics and mathematical physics. The theory of paracontrolled distribution is formulated for discrete systems, which allows us to prove a weak universality result for the parabolic Anderson model. This thesis further shows a fundamental relation between Hairer's modelled distributions and paraproducts: The space of modelled distributions can be characterized completely by using paraproducts. This can be seen a generalization of the Fourier description of Hölder spaces. Finally, we prove the existence of solutions to the stochastic Schrödinger equation on the full space and provide an application of Hairer's theory to option pricing.

The presented paper deals with a theoretical analysis of the ultimate limit state. The results of experimental research carried out at the Institute of Metal and Timber Structures headed by Assoc. Prof. Karmazinová and Professor Melcher were applied. The geometrically and materially nonlinear solution based on the Timošenko’s solution is verified by the FEM model in the computer programme system ANSYS. The random influence of initial imperfections is taken into consideration. The FEM model also includes the influence of residual stress. In the parametric study, the influence of residual stress on the cross-section plastification is researched into, its influence on the load carrying capacity limit is, together with the influence of other imperfections, the subject of the stochastic analysis, applying the Latin Hypercube Sampling (LHS). Further on, the study proves a direct effect of the concrete part of the cross-section (combination of materials steel-concrete) on the decrease of load carrying capacity limit of the beam caused by influence of the residual stress of steel. With regard to the importance of time dependent phenomena of the concrete creep for the load carrying capacity, the studies given in the Ph.D. thesis are oriented in this respect. The parametric studies of the influence of the concrete creep having applied the Standard Eurocode 2 provide both a comparison of load carrying capacity limits when using common and high-strength concrete types, and also the variability of load carrying capacities. It follows from the comparison of the statistical analysis outputs according to the design reliability conditions of the Standard EN1990 and of the approach of Eurocode 4 that the Eurocode 4 can be recommended for dimensioning of this member type. According to the studies which we carried out, the design in compliance with Eurocode 4 can be evaluated as the reliable one. A larger set of experimental data is necessary to determine the economy.

<p> The Bias-Variance Trade-off, where restricting the size of a hypothesis class can limit the generalization error of a model, is a canonical problem in Machine Learning, and a particular issue for high-variance models like Neural Networks that do not have enough parameters to enter the interpolating regime. Regularization techniques add bias to a model to lower testing error at the cost of increasing training error. This paper applies quantum circuits as activation functions in order to regularize a Feed-Forward Neural Network. The network using Quantum Activation Functions is compared against a network of the same dimensions except using Rectified Linear Unit (ReLU) activation functions, which can fit any arbitrary function. The Quantum Activation Function network is then shown to have comparable training performance to ReLU networks, both with and without regularization, for the tasks of binary classification, polynomial regression, and regression on a multicollinear dataset, which is a dataset whose design matrix is rank-deficient. The Quantum Activation Function network is shown to achieve regularization comparable to networks with L2-Regularization, the most commonly used method for neural network regularization today, with regularization parameters in the range of λ ∈ [.1, .5], while still allowing the model to maintain enough variance to achieve low training error. While there are limitations to the current physical implementation of quantum computers, there is potential for future architecture, or hardware-based, regularization methods that leverage the aspects of quantum circuits that provide lower generalization error. </p>

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis focuses on optimization of wind power tracking control systems in order to capture maximum wind power for the generation system. In this work, a mathematical simulation model is developed for a variable speed wind turbine power generation system. The system consists a wind turbine with necessary transmission system, and a permanent magnet synchronous generator and its vector control system. A new fuzzy based hill climbing method for power tracking control is proposed and implemented to optimize the wind power for the system under various conditions. Two existing power tracking control methods, the tip speed ratio (TSR) control method and the speed sensorless control method are also implemented with the wind power system. The computer simulations with a 5 KW wind power generation system are performed. The results from the proposed control method are compared with those obtained using the two existing methods. It is illustrated that the proposed method generally outperforms the two existing methods, especially when the operating point is far away from the maximum point. The proposed control method also has similar stable characteristic when the operating point is close to the peak point in comparison with the existing methods. The proposed fuzzy control method is computationally efficient and can be easily implemented in real-time.

Работа содержит описание построения доверительной полосы стохастического хаоса и реализацию алгоритмов исследования n-мерных моделей. В работе рассматривается дискретная модель, представленная в виде нелинейной динамической системы разностных уравнений, которая описывает динамику взаимодействия потребителей. Выделяются две задачи, которые были поставлены и выполнены в рамках данной работы для расширения программного инструментария исследования динамических систем такого рода. Для двумерного случая осуществляется стохастический анализ чувствительности хаоса через построение доверительной области с использованием критических линий. Помимо этого, описывается разработанный и реализованный алгоритм построения внешней границы хаоса. Производится переход к n-мерному варианту модели (взаимодействие n потребителей). Выделяется 4 алгоритма для исследования n-мерной модели: 1. построение фазовой траектории, 2. построение бифуркационной диаграммы, 3. построение карты режимов, 4. построение показателей Ляпунова. Описывается реализация данных алгоритмов с уклоном в параллельные вычисления. Реализация алгоритмов выполнена на языке программирования C# (платформа .NET) в виде консольного приложения для запуска параллельных вычислений на вычислительном кластере УрФУ. / The work contains description of confidence band construction of a stochastic chaos and realization of algorithms for n-dimensional models studying. The thesis considers a discrete model presented in the form of a nonlinear dynamic system of difference equations, which describes the dynamic of consumer interaction. There are two task that were set and performed in this work to expand the software tools for research dynamic sys-tems of this kind. For the two-dimensional case, a stochastic analysis of the sensitivity of chaos is carried out through the construction of a confidence band using critical lines. In addition, there is description and implementation of algorithm, that can build outer boundary of chaos. A transition is made to the n-dimensional version of the model (interaction of n consumers). There are 4 algorithms for studying the n-dimensional model: 1. phase trajectory building, 2. bifurcation diagram building, 3. mode map building, 4. Lyapunov components building. Algorithm implementation is described with a bias in parallel computations. The algorithms are implemented with C# programming language (.NET platform) in the form of a console application for running parallel computations on the computing cluster of the Ural Federal University.