Estudos empíricos [1],[2] demonstraram que o trafego das redes Internet Protocol (IP) possui propriedades fractais tais como impulsividade, auto-similaridade e dependência de longa duração em diversas escalas de agregação temporal, na faixa de milissegundos a minutos. Essas características tem motivado o desenvolvimento de novos modelos fractais de teletráfego e de novos algoritmos de controle de trafego em redes convergentes. Este trabalho propõe um novo modelo de trafego no espaço de estados baseado numa aproximação finito-dimensional do processo AutoRegressive Fractionally Integrated Moving Average (ARFIMA). A modelagem por meio de processos auto-regressivos (AR) também é investigada. A analise estatística de series simuladas e de series reais de trafego mostra que a aplicação de modelos AR de ordem alta em esquemas de previsão de teletráfego é fortemente prejudicada pelo problema da identificação da ordem do modelo. Também demonstra-se que a modelagem da memória longa pode ser obtida as custas do posicionamento de um ou mais pólos nas proximidades do circulo de raio unitário. Portanto, a implementação do modelo AR ajustado pode ser instável devido a efeitos de quantização dos coeficientes do filtro digital. O modelo de memória longa proposto oferece as seguintes vantagens: a) possibilidade de implementação pratica, pois não requer memória infinita, b) modelagem (explícita) da região das baixas freqüências do espectro e c) viabilização da utilização do filtro de Kalman. O estudo de caso apresentado demonstra que é possível aplicar o modelo de memória longa proposto em trechos estacionários de sinais de teletráfego fractal. Os resultados obtidos mostram que a dinâmica do parâmetro de Hurst de sinais de teletráfego pode ser bastante lenta na pratica. Sendo assim, o novo modelo proposto é adequado para esquemas de previsão de trafego, tais como Controle de Admissão de Conexões (CAC) e alocação dinâmica de banda, dado que o parâmetro de Hurst pode ser estimado em tempo real por meio da aplicação da transformada wavelet discreta (Discrete Wavelet Transform (DWT)). / Empirical studies [1],[2] demonstrated that heterogeneous IP traffic has fractal properties such as impulsiveness, self-similarity, and long-range dependence over several time scales, from miliseconds to minutes. These features have motivated the development of new traffic models and traffic control algorithms. This work presents a new state-space model for teletraffic which is based on a finite-dimensional representation of the ARFIMA random process. The modeling via AutoRegressive (AR) processes is also investigated. The statistical analysis of simulated time series and real traffic traces show that the application of high-order AR models in schemes of teletraffic prediction can be highly impaired by the model identification problem. It is also demonstrated that the modeling of the long memory can be obtained at the cost of positioning one or more poles near the unit circle. Therefore, the implementation of the adjusted AR model can be unstable due to the quantization of the digital filter coefficients. The proposed long memory model has the following advantages: a) possibility of practical implementation, inasmuch it does not require infinite memory, b) explicit modeling of the low frequency region of the power spectrum, and c) forecasts can be performed via the Kalman predictor. The presented case study suggests one can apply the proposed model in periods where stationarity can be safely assumed. The results indicate that the dynamics of the Hurst parameter can be very slow in practice. Hence, the new proposed model is suitable for teletraffic prediction schemes, such as CAC and dynamic bandwidth allocation, given that the Hurst parameter can be estimated on-line via DWT.

Long-range dependence in discrete and continuous time Markov chains over a countable state space is defined via embedded renewal processes brought about by visits to a fixed state. In the discrete time chain, solidarity properties are obtained and long-range dependence of functionals are examined. On the other hand, the study of LRD of continuous time chains is defined via the number of visits in a given time interval. Long-range dependence of Markov chains over a non-countable state space is also carried out through positive Harris chains. Embedded renewal processes in these chains exist via visits to sets of states called proper atoms. Examples of these chains are presented, with particular attention given to long-range dependent Markov chains in single-server queues, namely, the waiting times of GI/G/1 queues and queue lengths at departure epochs in M/G/1 queues. The presence of long-range dependence in these processes is dependent on the moment index of the lifetime distribution of the service times. The Hurst indexes are obtained under certain conditions on the distribution function of the service times and the structure of the correlations. These processes of waiting times and queue sizes are also examined in a range of M/P/2 queues via simulation (here, P denotes a Pareto distribution).

Sound transmission through a fluctuating deep ocean environment is considered. It is assumed that the environment consists of a range-independent background, on which a small-scale perturbation, due for example to internal waves, is superimposed. The modal description of underwater sound propagation is used extensively. The temporal spread of modal group arrivals in weakly range-dependent deep ocean environments is considered. The phrase "modal group arrival" refers to the contribution to a transient wavefield corresponding to a fixed mode number. It is shown that there are three contributions to modal group time spreads which combine approximately in quadrature. These are the reciprocal bandwidth, a deterministic dispersive contribution, and a scattering-induced contribution. The latter two contributions are shown to be proportional to the waveguide invariant beta, a property of the background sound speed profile. The results presented are based mostly on asymptotic theory. Some extensions of the asymptotic modal theory are developed. These theoretical results are shown to agree well with full-wave numerical wavefield simulations and available exact mode theoretical results. Theoretical predictions of modal group time spreads are compared to estimates derived from data that was collected during the 2004 LOAPEX experiment. The effects of deficiencies in the receiving array on estimates of modal group time spreads are discussed. It is shown that in spite of array deficiencies in the LOAPEX measurements it is possible to estimate modal group time spreads for almost all propagating modes and these estimates agree well with results obtained from numerical simulations and the developed theory. The effect of ocean internal waves on sound speed fluctuations is also considered, motivated by the observation that the amount of energy being scattered along the propagation path is sometimes greater in the experimental data than predicted by numerical simulations and theory. It is shown that the usual assumption that the potential sound speed gradient is proportional to the squared buoyancy frequency is often not a good approximation.

Today, the Internet is growing exponentially, with traffic statistics that mathematically exhibit fractal characteristics: self-similarity and long-range dependence. With these properties, data traffic shows high peak-to-average bandwidth ratios and causes networks inefficient. These problems make it difficult to predict, quantify, and control data traffic. In this thesis, two analytical methods are used to study fractal network traffic. They are second-order self-similarity analysis and multifractal analysis. First, self-similarity is an adaptability of traffic in networks. Many factors are involved in creating this characteristic. A new view of this self-similar traffic structure related to multi-layer network protocols is provided. This view is an improvement over the theory used in most current literature. Second, the scaling region for traffic self-similarity is divided into two timescale regimes: short-range dependence (SRD) and long-range dependence (LRD). Experimental results show that the network transmission delay separates the two scaling regions. This gives us a physical source of the periodicity in the observed traffic. Also, bandwidth, TCP window size, and packet size have impacts on SRD. The statistical heavy-tailedness (Pareto shape parameter) affects the structure of LRD. In addition, a formula to estimate traffic burstiness is derived from the self-similarity property. Furthermore, studies with multifractal analysis have shown the following results. At large timescales, increasing bandwidth does not improve throughput. The two factors affecting traffic throughput are network delay and TCP window size. On the other hand, more simultaneous connections smooth traffic, which could result in an improvement of network efficiency. At small timescales, in order to improve network efficiency, we need to control bandwidth, TCP window size, and network delay to reduce traffic burstiness. In general, network traffic processes have a Hlder exponent a ranging between 0.7 and 1.3. Their statistics differ from Poisson processes. From traffic analysis, a notion of the efficient bandwidth, EB, is derived. Above that bandwidth, traffic appears bursty and cannot be reduced by multiplexing. But, below it, traffic is congested. An important finding is that the relationship between the bandwidth and the transfer delay is nonlinear.

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The thesis entitled "Studies on N-Hetero cyclic Compounds: (a) Reaction of 5,6,7,8-Tetrahydroisoquinolines with Vilsmeier Reagent and (b) Amide Induced in situ Alkylation of 5,6-Dihydroisoquinolines" is presented in two parts. Part I involves a study of the Vilsmeier reaction of 4-cyano-1,3-dihydroxy-5,6,7,8 tetrahydroisoquinoline derivatives, while Part II concerns the in situ alkylation of l-alkyl-4-cyano-3-methoxy-5,6- dihydroisoquinolines in presence of KNH2/liq.NH3.

Broad spectral tunability is a desired feature of many photonic and plasmonic components, such as optical filters, semiconductor lasers, and plasmonic materials. Here I show that unique properties of long-range surface plasmon polaritons (LR SPP) allow one to produce optical components with very wide tuning range using small variations in the refractive index of the dielectric cladding material. As a proof-of-concept demonstration, I present operation of LR-SPP-based bandpass optical filters in which a 0.004 variation in the refractive index of the cladding dielectric translates into 210 nm of bandpass tuning at telecom wavelengths. The tuning mechanism proposed here may be used to create monolithic bandpass filters with tuning range spanning over more than an optical octave, compact and widely-tunable diode and quantum cascade laser systems, multi-spectral imagers, and other plasmonic components with broadly-tunable optical response. / text

The purpose of this thesis is to introduce a novel method of dry micro-object manipulation and to demonstrate predictable vision-based control. The Lift and slide conveyors presented utilize three main components: pads, lifters and a floating platform. The pads have a small planar displacement in the XY axis and lifters have a small Z axis displacement. Together they can be used to create minute displacements per cycle while carrying a floating platform that can hold the desired objects to be moved. These platforms can be handed off to other pad-lifter groups to create an unlimited planar envelope. Two degree of freedom control was established using LabView with open and closed loop routines. A model is presented that predicts the resonance frequencies with different loading and geometric characteristics to aid in design optimization for various applications. Parameters such as velocity, drift and traction are well characterized for different operating conditions.

A novel surface plasmon resonance sensor is fabricated to evaluate its use in biochemical sensing. The sensor can differentiate between bulk refractive index changes and surface binding reactions of interest. There has been a great interest in developing sensors to differentiate biological or chemical agents from interfering effects, but they still remain in research phase. In this work, a prism coupler is used to simultaneously excite both long and short range surface plasmon modes of the sensor. The differing sensitivities of the long and short range modes allow one to distinguish surface binding reactions of interest from refractive index fluctuations. In this thesis, we have demonstrated the sensors self referencing capability by detecting the formation of an octadecanethiol self assembled monolayer while varying solution refractive index.

The communication range between a civilian Unmanned Aerial Vehicle (UAV) and a Ground Control Station (GCS) is affected by the government regulations that determine the use of frequency bands and constrain the amount of power in those frequencies. The application of multiple UAVs in search and rescue operations for example demands a reliable, long-range inter-UAV communication. The inter-UAV communication is the ability of UAVs to exchange data among themselves, thus forming a network in the air. This ability could be used to extend the range of communication by using a decentralized routing technique in the network. To provide this ability to a fleet of autonomous dirigible UAVs being developed at the University of Ottawa, a new communication framework was introduced and implemented. Providing a true mesh networking based on a novel routing protocol, the framework combines long-range radios at 900 MHz Industrial, Scientific and Medical (ISM) band with the software integrated into the electronics platform of each dirigible. With one radio module per dirigible the implemented software provides core functionalities to each UAV, such as exchanging flight control commands, telemetry data, and photos with any other UAV in a decentralized network or with the GCS. We made use of the advanced networking tools of the radio modules to build capabilities into the software for route tracing, traffic prioritization, and minimizing self-interference. Initial test results showed that without acknowledgements, packets can be received in the wrong order and cause errors in the transmission of photos. In addition, a transmission in a presence of a third broadcasting node slows down by 4-6 times. Based on these results our software was improved to control to flow of transmit data making the fragmentation, packetization, and reassembly of photos more reliable. Currently, using radios with half-wavelength dipole antennas we can achieve a one-hop communication range of up to 5 km with the radio frequency line-of-sight (RF LOS). This can be extended further by adding as many radio nodes as needed to act as intermediate hops.