The overarching theme of my thesis is understanding observed variations of northern hemisphere atmospheric carbon dioxide (CO2) and methane (CH4) concentrations. I focus my analysis on high-latitude observations of these gases, as there are large stores of carbon in boreal vegetation and tundra which are vulnerable to rapid warming in the Arctic. My thesis is split into two parts. First, I use the wavelet transform to spectrally decompose observed multi-decadal timeseries for CO2 and CH4. I perform a series of numerical experiments based on synthetic data in order to characterise the errors associated with the analysis. For CO2, I analyse the phase and amplitude of the detrended seasonal cycle of CO2 to infer changes about carbon uptake by northern vegetation. I do not find a long-term change in the length of the carbon uptake period despite significant changes in the spring and autumn phase. I do find an increase in the rate of peak uptake which coincides with the observed increase in seasonal amplitude. These results suggest that the carbon uptake period of boreal vegetation has become more intense but has not changed in length, which provides evidence for an increase in net uptake of CO2 in the high latitudes. For CH4, I test the hypothesis that an increase in Arctic wetland emissions could result in a decrease in the seasonal amplitude of CH4 in the high latitudes. This hypothesis is based on the fact that the seasonal minima of CH4 roughly coincides with the peak of high latitude wetland CH4 emissions. I find that the CH4 seasonal amplitude has significantly decreased at a number of high-latitude sites. However I also find that atmospheric transport appears to drive much of the variability in high-latitude CH4 and that transport could also be responsible for the observed changes in amplitude. I show that an increase in wetland emissions is likely to have a more pronounced effect on the high-latitude CH4 seasonal cycle in the future. In the second section of my thesis, I describe a series of experiments in collaboration with the UK Astronomy Technology Centre, in which I characterise a new instrument technology for satellite applications to observe changes in CO2 from low-Earth orbit. The proof of concepts experiments were performed with a bench top hyperspectral imager. I show that the instrument is able to capture clean spectra at the wavelengths required for CO2 with low levels of scattered light between spectra.

Este trabalho apresenta uma nova aplicação de wavelets em sistemas de espalhamento espectral. A aplicação apresentada foi realizada no contexto de detecção multiusuário e pode ser empregada em sistemas de acesso múltiplo por divisão de código. A detecção e a estimação são realizadas através de um algoritmo de inferência bayesiana, empregando o Amostrador de Gibbs e utilizando as wavelets para melhorar a relação sinal ruído na recepção. Na transmissão, um código específico, baseado na wavelet de Haar, modula o sinal contendo a informação preparando-o contra alterações que possam ocorrer devido a características intrínsecas do canal de ruído branco, gaussiano e aditivo. Esta técnica foi aqui denominada de modulação wavelet. Na recepção, uma transformada wavelet de Haar é aplicada ao sinal, gerando coeficientes wavelets. A ortogonalidade da wavelet de Haar torna possível executar um procedimento de cancelamento de ruído, em inglês denoising, que melhora a qualidade da recepção. Para validar a abordagem apresentada neste trabalho, foi executada uma série de simulações. Os resultados mostraram um melhor desempenho sistêmico com o emprego de wavelets. Nas simulações foram observados vários parâmetros de sistema, dentre eles e amplitude do sinal, a taxa de erro de bits (BER, bit error rate) e a variância do sinal. Os resultados foram bastante satisfatórios, indicando uma redução do ruído da ordem de 3dB em relação ao valor sem cancelamento de ruído. Este trabalho abre novas oportunidades de pesquisa para o uso de wavelets em sistemas de espalhamento espectral e telecomunicações em geral. / This work presents a new application of wavelets to spread spectrum systems. The presented application was made in the context of multiuser detection and can be used in code-division multiple access systems. Detection and estimation are performed through a Bayesian inference algorithm and, employing the Gibbs sampler and utilizing wavelets to improve the signal-to-noise ratio at the reception. At the transmission, a specific code based on the Haar wavelet modulates the signal containing the information, preparing it to alterations that may occur due to the intrinsic characteristics of the additive Gaussian noise channel. This technique was here denominated wavelet modulation. At the reception, a Haar wavelet transform is applied to the signal, generating wavelet coefficients. The orthogonality of the Haar wavelet makes it possible to perform a noise cancelling process, called denoising, which enhances the receiving quality. To validate the approach presented in this work, a number of simulations were performed. The results showed a better system performance with the use of wavelets. Several parameters were monitored in the simulations, among them the signal amplitude, de BER (bit error rate), and the signal variance. The results were very satisfactory, indicating a noise reduction of approximately 3dB referred to the value without noise cancelling. This work opens new research opportunities for the use of wavelets in spread spectrum systems and Telecommunications in general.

Aims: To explore and inform current water immersion recovery practice of high performance athletes; and to compare recovery interventions of 5 minutes cold water immersion, warm water immersion and passive rest, in trained subjects, following intense exercise replicating the demands of game-sports. Methods: Study 1: In a repeated measures design, a measurement approach for use in the evaluation of water immersion efficacy was piloted. The within-day and between-day reliability of surface electromyelography (sEMG), particularly functional wavelet analysis, was evaluated in human lower limb muscles. Functional wavelet analysis provides the opportunity to measure neuromuscular function at the greatest level of detail by differentiating the relative intensity of low and high frequency motor unit recruitment. On 2 consecutive days (Trial 1 & Trial 2), 12 participants performed 3x5 second isometric 80% maximal voluntary contractions (MVC) on a Biodex® dynamometer in each of 150 ankle plantarflexion, 200 knee extension and 200 knee flexion. sEMG was obtained from the medial gastrocnemius (MG), vastis medialis (VM), vastis lateralis (VL) and biceps femoris (BF) muscles. Joint position and force production were controlled. Electrodes remained in situ during each trial. Electrodes were removed upon completion of Trial 1 and replaced in the same position the next day for Trial 2. Simultaneous sEMG metrics for intervals of consistent force production were compared between contractions in Trial 1 and Trial 2 (between-day) and contractions within Trial 2 (within-day). Study 2: 11 trained participants completed the 90 minute Loughborough Intermittent Shuttle Test (LIST). Five minutes of COLD water immersion (8.8 ± 0.30C), WARM water immersion (35.1 ± 1.80C) and REST were compared in a repeated measures randomised cross over design. Recovery was evaluated at 2, 4 and 24 hours post exercise using circulating markers of muscle damage, muscle dynamometry, drop jump and repeated single leg hop performance tests and perceived recovery. Study 3: Current water immersion practice of high performance athletes, practice implications stemming from this study’s findings, and the rationale were explored. In a purposive, theoretical sampling approach of expert consultation, 8 professionals advising internationally competing athletes on water immersion recovery practice were provided with a research brief of this project in advance of a scribed, semi-structured interview. Participants were of Sports Coach, Strength & Conditioning Coach and Sports Physiotherapist professions with a minimum of 5 years’ experience working with internationally competing athletes; and differed in international location and sporting disciplines.

Este trabalho apresenta uma nova aplicação de wavelets em sistemas de espalhamento espectral. A aplicação apresentada foi realizada no contexto de detecção multiusuário e pode ser empregada em sistemas de acesso múltiplo por divisão de código. A detecção e a estimação são realizadas através de um algoritmo de inferência bayesiana, empregando o Amostrador de Gibbs e utilizando as wavelets para melhorar a relação sinal ruído na recepção. Na transmissão, um código específico, baseado na wavelet de Haar, modula o sinal contendo a informação preparando-o contra alterações que possam ocorrer devido a características intrínsecas do canal de ruído branco, gaussiano e aditivo. Esta técnica foi aqui denominada de modulação wavelet. Na recepção, uma transformada wavelet de Haar é aplicada ao sinal, gerando coeficientes wavelets. A ortogonalidade da wavelet de Haar torna possível executar um procedimento de cancelamento de ruído, em inglês denoising, que melhora a qualidade da recepção. Para validar a abordagem apresentada neste trabalho, foi executada uma série de simulações. Os resultados mostraram um melhor desempenho sistêmico com o emprego de wavelets. Nas simulações foram observados vários parâmetros de sistema, dentre eles e amplitude do sinal, a taxa de erro de bits (BER, bit error rate) e a variância do sinal. Os resultados foram bastante satisfatórios, indicando uma redução do ruído da ordem de 3dB em relação ao valor sem cancelamento de ruído. Este trabalho abre novas oportunidades de pesquisa para o uso de wavelets em sistemas de espalhamento espectral e telecomunicações em geral. / This work presents a new application of wavelets to spread spectrum systems. The presented application was made in the context of multiuser detection and can be used in code-division multiple access systems. Detection and estimation are performed through a Bayesian inference algorithm and, employing the Gibbs sampler and utilizing wavelets to improve the signal-to-noise ratio at the reception. At the transmission, a specific code based on the Haar wavelet modulates the signal containing the information, preparing it to alterations that may occur due to the intrinsic characteristics of the additive Gaussian noise channel. This technique was here denominated wavelet modulation. At the reception, a Haar wavelet transform is applied to the signal, generating wavelet coefficients. The orthogonality of the Haar wavelet makes it possible to perform a noise cancelling process, called denoising, which enhances the receiving quality. To validate the approach presented in this work, a number of simulations were performed. The results showed a better system performance with the use of wavelets. Several parameters were monitored in the simulations, among them the signal amplitude, de BER (bit error rate), and the signal variance. The results were very satisfactory, indicating a noise reduction of approximately 3dB referred to the value without noise cancelling. This work opens new research opportunities for the use of wavelets in spread spectrum systems and Telecommunications in general.

Le principal objectif de ce travail est l’étude de l’influence de la pesanteur sur la mécanique respiratoire et le contrôle de la respiration, ainsi que sur les interactions cardio-respiratoires pendant les différents stades du sommeil. Le chapitre introductif présente le contexte général et les objectifs de la thèse. Des sections abordant le sommeil, la respiration, et l’interaction cardio-respiratoire y sont présentées, résumant l’état actuel des connaissances sur les effets de la pesanteur sur chacun de ces systèmes. Dans le deuxième chapitre, l’expérience “Sleep and Breathing in microgravity”, qui constitue la source des données à la base de ce travail, est présentée en détail. L’étude des signaux de longue durée requiert avant tout de disposer d’outils performants d’analyse des signaux. La première partie de la thèse présente en détail deux algorithmes : un algorithme de détection automatique d’événements respiratoires (inspiration / expiration) basé sur des réseaux neuronaux artificiels, et un algorithme de quantification de l’amplitude et de la phase de l’arythmie sinusale pendant le sommeil, utilisant la méthode des ondelettes. La validation de chaque algorithme est présentée, et leur performance évaluée. Cette partie inclut aussi des courtes introductions théoriques aux réseaux de neurones artificiels ainsi qu’aux méthodes d’analyse temps–fréquence (Fourier et ondelettes). Une approche similaire à celle utilisée pour la détection automatique d’événements respiratoires a été appliquée à la détection d’événements dans des signaux de vitesse du sang dans l’artère cérébrale moyenne, mesures obtenues par Doppler transcrânien. Ceci est le sujet de la thèse annexe. Ces deux algorithmes ont été appliqués aux données expérimentales pour extraire des informations physiologiques quant à l’impact de la pesanteur sur la mécanique respiratoire et l’interaction cardio-respiratoire. Ceci constitue la deuxième partie de la thèse. Un chapitre est consacré aux effets de l’apesanteur sur la mécanique respiratoire pendant le sommeil. Ce chapitre a mis en évidence, pour tous les stades de sommeil, une augmentation de la contribution abdominale en microgravité, suivi d’un retour progressif vers des valeurs observées avant le vol. L’augmentation initiale était attendue, mais l’adaptation progressive observée ne peut pas être expliquée par un effet purement mécanique, et nous suggère la présence d’un mécanisme d’adaptation central. Un deuxième chapitre présente les résultats comparant l’arythmie sinusale pendant le sommeil avant le vol, en apesanteur et après le retour sur terre. Le rythme cardiaque pendant le sommeil dans l’espace présente une moindre variabilité. Les différences NREM–REM observées sur terre pour les influences vagales et sympathiques sont accentuées dans l’espace. Aucun changement significatif n’est présent pour le gain et la différence de phase entre les les signaux cardiaque et respiratoire en comparant le sommeil sur terre et en apesanteur. La dissertation termine par une discussion générale du travail effectué, incluant les prin- cipales conclusions ainsi que les perspectives qui en découlent.

This dissertation develops a "neighborhood" based neural network model utilizing wavelet analysis and Self-organizing Map (SOM) to predict building baseline energy use. Wavelet analysis was used for feature extraction of the daily weather profiles. The resulting few significant wavelet coefficients represent not only average but also variation of the weather components. A SOM is used for clustering and projecting high-dimensional data into usually a one or two dimensional map to reveal the data structure which is not clear by visual inspection. In this study, neighborhoods that contain days with similar meteorological conditions are classified by a SOM using significant wavelet coefficients; a baseline model is then developed for each neighborhood. In each neighborhood, modeling is more robust without unnecessary compromises that occur in global predictor regression models. This method was applied to the Energy Predictor Shootout II dataset and compared with the winning entries for hourly energy use predictions. A comparison between the "neighborhood" based linear regression model and the change-point model for daily energy use prediction was also performed. We also studied the application of the non-parametric nearest neighborhood points approach in determining the uncertainty of energy use prediction. The uncertainty from "local" system behavior rather than from global statistical indices such as root mean square error and other measures is shown to be more realistic and credible than the statistical approaches currently used. In general, a baseline model developed by local system behavior is more reliable than a global baseline model. The "neighborhood" based neural network model was found to predict building baseline energy use more accurately and achieve more reliable estimation of energy savings as well as the associated uncertainties in energy savings from building retrofits.

The Texas-Louisiana Shelf Circulation and Transport Study featured moorings that covered the shelf during 1992 to 1994, and captured the oceanic response on the shelf to category 4 Hurricane Andrew in August of 1992. Eighty-one current meters distributed over 31 moorings along several contours of isobaths provided excellent spatial and temporal coverage over the shelf. The low-frequency variability (2 days and longer) of current observations and tide gauges to the West of the storm are analyzed after the passage of Andrew, focusing on the region outside of direct hurricane forcing. Wavelet analyses are utilized to investigate the dominant periods excited by the storm over the shelf and their temporal evolution after forcing has subsided. Subsequent to the storm's passage, the observations and wavelet transforms show a two-to-four day period coastal trapped wave that propagate westward at speeds near 6 m/s and then around the Texas bend along the bathymetry. The signal remains detectable in observations as far south as Port Isabel, Texas. The prominent frequencies determined from wavelet analysis are compared with predicted coastal trapped wave dispersion modes and show good agreement in the predicted group speed and cross-shelf structure of the first mode. The energies calculated from the data indicate a largely barotropic shelf wave response which is corroborated in the observed currents and by theory.

This research provides insight into changes in volumetric flushing of the Tampa Bay estuary caused by synoptic scale wind events. The two main studies of this dissertation involve 1) using wavelet analysis to investigate the link between the El Niño-Southern Oscillation (ENSO) and the frequency and strength of volumetric flushing driven by synoptic variability and 2) using a multi-decadal model simulation to examine how extratropical/winter storms and hurricanes affect the overall flushing rates for Tampa Bay, FL. In the first study, two analyses are performed on 55 years of observational data to investigate the effect of multiple small wind events on estuarine flushing. First I use subtidal observed water level as a proxy for mean tidal height to estimate the rate of volumetric bay outflow. Second, I use wavelet analysis on sea level and wind data to isolate the synoptic sea level and surface wind variance. For both analyses the long-term monthly climatology is removed to focus on the volumetric and wavelet variance anomalies. The overall correlation between the Oceanic Niño index and volumetric anomalies is small (r2=0.097) due to the seasonal dependence on the ENSO response. The mean monthly climatology between the synoptic wavelet variance of elevation and axial winds have similar seasonal behavior. During the winter, El Niño (La Niña) increases (decreases) the synoptic variability, but decreases (increases) it during the summer. The difference in winter El Niño/La Niña wavelet variances is about 20% of the climatological value. ENSO can swing the synoptic flushing of the bay by 0.22 bay volumes per month. These changes in circulation associated with synoptic variability have the potential to impact mixing and transport within the bay. In the second study, volumetric changes from large scale weather events are investigated using a numerical circulation model simulation (1975-2006) to find the cumulative impact of flushing on the bay by extreme events. The strong wind speeds, duration of high winds and wind direction during these events all affect the amount of water flushed in and out of the estuary. Normalized volume anomalies are largest when wind components blow up/down the estuary in the NE/SW direction. Wind induced normalized flushing rates for all 10 extratropical/winter storms range from 12% to 40% and from 14% to 40% for all 10 hurricanes. All storms discussed in this study caused winds greater than 15 m s-1 (~30 knots). The direction of the winds had an impact on the flushing rates during these extreme events. Storm9 (February 1998) and Hurricane Gabrielle (September 2001) experienced the smallest total volume changes (14% and 13%). Both storms experienced weak axial and co-axial winds causing volume changes to be small. The Storm of the Century (March 1993) and Hurricane Frances (September 2004) saw the largest total volume changes of 40%. They both had strong winds blowing in the NE direction. Hurricane Frances had two wind peaks and lingered in the area for approximately 48 hours, so both strength and duration of winds played a large role in the total volume change. Total inflow and outflow rates per year show that there is year to year variability of flushing in Tampa Bay.

Forest disturbances and the spatial patterns they create affect ecosystem processes through their influence on forest vegetation from individual trees to landscapes. In the boreal and mixed-wood forests of eastern Canada the main agents of disturbance are logging, fire, and defoliation by the spruce budworm (SBW, Choristoneura fumiferana). These disturbances are similar in that they remove forest biomass and influence forest succession but also distinct in that logging creates patterns that are different than those created by natural disturbances. All disturbances are indirectly linked to each other through their mutual effects on forest spatial structure and succession. Through such feedbacks, spatial disturbance legacies can facilitate or constrain further disturbances, including forest management. Surprisingly, the long term spatial consequences of interactions among multiple natural and anthropogenic disturbances remain largely unexplored. This thesis investigates how, and at what spatial scale, legacies in forest composition and age structure influence natural disturbance dynamics, and how natural disturbances constrain forest management. I address four specific questions: (i) For how long do spatial legacies of different forest management strategies persist on the landscape? (ii) How do interactions among logging, fire, SBW, and succession affect timber availability and long term forest patterns in age and composition? (iii) How do these patterns differ from those created by each disturbance individually? And, (iv) How can management be used to reduce the extent and severity of fires and SBW defoliation through the manipulation of forest structure? The key scientific innovations of this thesis are: (i) Characterization of the duration and influence of spatial legacies on forest disturbances and sustainability; (ii) Development of a dynamic spatial forest simulation model that includes distinct successional rules that respond to different types of disturbance and shifts in disturbance regimes; and, (iii) Development and application of a wavelet-based significance testing framework to identify key scales of expression in forest spatial patterns. These innovations provide a scientific basis for landscape level forest management strategies designed to reduce the long term impacts of defoliating insects and to meet multiple objectives.

Made available in DSpace on 2014-06-11T19:25:32Z (GMT). No. of bitstreams: 0 Previous issue date: 2008-07-10Bitstream added on 2014-06-13T19:53:23Z : No. of bitstreams: 1 varanis_mvm_me_rcla.pdf: 4826016 bytes, checksum: ab2c8b052e0a038577280ce930b14260 (MD5) / O estudo de vibrações diz respeito aos movimentos oscilatórios de corpos e às forças que lhes são associadas. Todos os corpos dotados de massa e elasticidade são capazes de vibrar. Deste modo, a maior parte das máquinas e estruturas estão sujeitas a certos graus de vibração A maioria das atividades humanas envolve alguma forma de vibração. O estudo do comportamento dinâmico dessas oscilações mecânicas é o objetivo deste trabalho e para isto propomos um sistema de massas concentradas e com dois graus de liberdade. O sistema será excitado por forças externas, entre elas ondas de terremoto. Com simulações numéricas estudamos o sistema, usando a transformada rápida de Fourier, transformada wavelet. / The study of vibration concerns oscillatory movement of bodies and the forces they are associated. All bodies that have mass and elasticity are able to vibrate. Thus, most of the machines and structures are subject to certain degrees of vibration most human activities involve some form of vibration. The study of the dynamic behavior of these mechanical oscillations is the objective of this work and to propose that a system of weights and concentrated with two degrees of freedom. The system will be excited by external forces, including waves of earthquake. With numerical simulations studied the system, using the fast Fourier transform, wavelet transform.