Higher-order spectral analysis of acoustical waveforms can provide phase information that is not retained in calculations of power spectral density. In the propagation of high intensity sound, nonlinearity can cause substantial changes in the waveform as frequency components interact with one another. The bispectrum, which is one order higher than power spectral density, may provide a useful measure of nonlinearity in propagation by highlighting spectral regions of interaction. This thesis provides a review of the bispectrum, places it in the context of nonlinear acoustic propagation, and presents spectra calculated as a function of distance for numerically propagated acoustic waveforms. The calculated spectra include power spectral density, quad-spectral density, bispectrum, spatial derivative of the bispectrum, bicoherence, and skewness function. / text

<p>In recent years, there has been a great interest towards the higher order numerical methods for singularly perturbed problems. As compared to their lower order counterparts, they provide better accuracy with fewer mesh points. Construction and/or implementation of direct higher order methods is usually very complicated. Thus a natural choice is to use some convergence acceleration techniques, e.g., Richardson extrapolation, defect correction, etc. In this thesis, we will consider various classes of problems described by singularly perturbed ordinary and partial differential equations. For these problems, we design some novel numerical methods and attempt to increase their accuracy as well as the order of convergence. We also do the same for existing numerical methods in some instances. We &macr / nd that, even though the Richardson extrapolation technique always improves the accuracy, it does not perform equally well when applied to different methods for certain classes of problems. Moreover, while in some cases it improves the order of convergence, in other cases it does not. These issues are discussed in this thesis for linear and nonlinear singularly perturbed ODEs as well as PDEs. Extrapolation techniques are analyzed thoroughly in all the cases, whereas the limitations of the defect correction approach for certain problems is indicated at the end of the thesis</p>

We discuss the development of a number of algorithms and techniques to allow object oriented virtual machines to support many of the features needed by functional and other higher level languages. These features include non-strict evaluation, partial function application, higher ranked and higher kinded types. To test the mechanisms that we have developed we have also produced a compiler to allow the functional language Haskell to be compiled to a native executable for the Common Language Runtime. This has allowed us to demonstrate that the techniques we have developed are practically viable.

One of the most significant goals in coal mining technology research is the automation of underground coal mining machinery. A current challenge with automating underground coal mining machinery is measuring and maintaining a coal mining horizon. The coal mining horizon is the horizontal path the machinery follows through the undulating coal seam during the mining operation. A typical mining practice is to leave a thin remnant of coal unmined in order to maintain geological stability of the cutting face. If the remnant layer is too thick, resources are wasted as the unmined coal is permanently unrecoverable. If the remnant layer is too thin, the product is diluted by mining into the overburden and there is an increased risk of premature roof fall which increases danger. The main challenge therefore is to develop a robust sensing method to estimate the thickness of thin remant coal layers. This dissertation addresses this challenge by presenting a pattern recognition methodology to estimate thin remnant coal layer thickness using ground penetrating radar (GPR). The approach is based upon a novel feature vector, derived from the bispectrum, that is used to characterise the early-time segment of 1D GPR data. The early-time segment is dominated by clutter inherent in GPR systems such as antenna crosstalk, ringdown and ground-bounce. It is common practice to either time-gate the signal, disregard the clutter by rendering the early-time segment unusable, or configure the GPR equipment to minimise the clutter effects which in turn reduces probing range. Disregarding the early-time signal essentially imposes a lower thickness limit on traditional GPR layer thickness estimators. The challenges of estimating thin layer thickness is primarily due to these inherent clutter components. Traditional processing strategies attempt to minimise the clutter using pre-processing techniques such as the subtraction of a calibration signal. The proposed method, however, treats the clutter as a deterministic but unknown signal with additive noise. Hence the proposed approach utilises the energy from the clutter and monitors change in media from subtle changes in the signal shape. Two complementary processing methods important to horizon sensing have been also proposed. These methods, near-surface interface detection and antenna height estimation, may be used as pre-validation tools to increase the robustness of the thickness estimation technique. The proposed methods have been tested with synthetic data and validated with real data obtained using a low power 1.4 GHz GPR system and a testbed with known conditions. With the given test system, it is shown that the proposed thin layer thickness estimator and near-surface interface detector outperform the traditional matched filter based processing methods for layers less than 5 cm in thickness. It is also shown that the proposed antenna height estimator outperforms the traditional height estimator for heights less than 7 cm. These new methods provide a means for reliably extending layer thickness estimation to the thin layer case where traditional approaches are known to fail.

Obstructive sleep apnoea hypopnoea syndrome (OSAHS) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. The reference standard of clinical diagnosis, called Polysomnography (PSG), requires a full-night hospital stay connected to over 15 measuring channels requiring physical contact with sensors. The vast quantity of physiological data acquired during the PSG has to be manually scored by a qualified technologist to assess the presence or absence of the decease. The PSG is inconvenient, time consuming, expensive and unsuited for community screening. The limited PSG facilities around the world have resulted in long waiting lists and a large fraction of patients remain undiagnosed at present. There has been a flurry of recent activities in developing a portable technology to resolve this need. All the devices have at least one sensor that requires physical contact with the subject. Unattended systems have not led to sufficiently high sensitivity/specificity levels to be used in a routine home monitoring or a community screening exercise. OSAHS is a sleep respiratory disorder principally caused by functional deficiencies occurring in the upper airways during sleep. These conditions and the reduced muscle tone during sleep, cause the muscles in the upper airways to collapse partially or completely thus resulting in episodes of hypopnoea and apnoea respectively. During the process leading to collapse of upper airways, upper airways act as an acoustic filter frequently producing snoring sounds. The process of snore sound production leads us to hypothesise that snore sounds should contain information on changes occurring in the upper airways during the OSAHS. Snoring almost always accompanies the OSAHS and is universally recognised as its earliest symptom. At present, however, the quantitative analysis of snore sounds is not a practice in clinical OSAHS detection. The vast potential of snoring in the diagnosis/screening of the OSAHS remains unused. Snoring-based technology opens up opportunities for building community-screening devices that do not depend on contact instrumentation. In this thesis, we present our work towards developing a snore–based non-contact instrumentation for the diagnosis/screening of the OSAHS. The primary task in the analysis of Snore Related Sounds (SRS) would be to segment the SRS data as accurately as possible into three main classes, snoring (voiced non-silence), breathing (unvoiced non-silence) and silence. A new algorithm was developed, based on pattern recognition for the SRS segmentation. Four features derived from the SRS were considered to classify samples of the SRS into three classes. We also investigated the performance of the algorithm with three commonly-used noise reduction (NR) techniques in speech processing, Amplitude Spectral Subtraction (ASS), Power Spectral Subtraction (PSS) and Short Time Spectral Amplitude (STSA) Estimation. It was found that the noise reduction, together with a proper choice of features, could improve the classification accuracy to 96.78%. A novel model for the SRS was proposed for the response of a mixed-phase system (total airways response, TAR) to a source excitation at the input. The TAR/source model is similar to the vocal tract/source model in speech synthesis and is capable of capturing the acoustical changes brought about by the collapsing upper airways in the OSAHS. An algorithm was developed, based on the higher-order-spectra (HOS) to jointly estimate the source and the TAR, preserving the true phase characteristics of the latter. Working on a clinical database of signals, we show that the TAR is indeed a mixed phased signal and second-order statistics cannot fully characterise it. Nocturnal speech sounds can corrupt snore recordings and pose a challenge to the snore-based OSAHS diagnosis. The TAR could be shown to detect speech segments embedded in snores and derive features to diagnose the OSAHS. Finally presented is a novel technique for diagnosing the OSAHS, based solely on multi-parametric snore sound analysis. The method comprises a logistic regression model fed with a range of snore parameters derived from its features — the pitch and Total Airways Response (TAR) estimated using a Higher Order Statistics (HOS) based algorithm. The model was developed and its performance validated on a clinical database consisting of overnight snoring sounds simultaneously recorded during a hospital PSG using a high fidelity sound recording setup. The K-fold cross validation technique was used for validating the model. The validation process achieved an 89.3% sensitivity with 92.3% specificity (the area under the Receiver Operating Characteristic (ROC) curve was 0.96) in classifying the data sets into the two groups, the OSAHS (AHI >10) and the non-OSAHS. These results are superior to the existing results and unequivocally illustrate the feasibility of developing a snore-based non-contact OSAHS screening device.

Obstructive sleep apnoea hypopnoea syndrome (OSAHS) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. The reference standard of clinical diagnosis, called Polysomnography (PSG), requires a full-night hospital stay connected to over 15 measuring channels requiring physical contact with sensors. The vast quantity of physiological data acquired during the PSG has to be manually scored by a qualified technologist to assess the presence or absence of the decease. The PSG is inconvenient, time consuming, expensive and unsuited for community screening. The limited PSG facilities around the world have resulted in long waiting lists and a large fraction of patients remain undiagnosed at present. There has been a flurry of recent activities in developing a portable technology to resolve this need. All the devices have at least one sensor that requires physical contact with the subject. Unattended systems have not led to sufficiently high sensitivity/specificity levels to be used in a routine home monitoring or a community screening exercise. OSAHS is a sleep respiratory disorder principally caused by functional deficiencies occurring in the upper airways during sleep. These conditions and the reduced muscle tone during sleep, cause the muscles in the upper airways to collapse partially or completely thus resulting in episodes of hypopnoea and apnoea respectively. During the process leading to collapse of upper airways, upper airways act as an acoustic filter frequently producing snoring sounds. The process of snore sound production leads us to hypothesise that snore sounds should contain information on changes occurring in the upper airways during the OSAHS. Snoring almost always accompanies the OSAHS and is universally recognised as its earliest symptom. At present, however, the quantitative analysis of snore sounds is not a practice in clinical OSAHS detection. The vast potential of snoring in the diagnosis/screening of the OSAHS remains unused. Snoring-based technology opens up opportunities for building community-screening devices that do not depend on contact instrumentation. In this thesis, we present our work towards developing a snore–based non-contact instrumentation for the diagnosis/screening of the OSAHS. The primary task in the analysis of Snore Related Sounds (SRS) would be to segment the SRS data as accurately as possible into three main classes, snoring (voiced non-silence), breathing (unvoiced non-silence) and silence. A new algorithm was developed, based on pattern recognition for the SRS segmentation. Four features derived from the SRS were considered to classify samples of the SRS into three classes. We also investigated the performance of the algorithm with three commonly-used noise reduction (NR) techniques in speech processing, Amplitude Spectral Subtraction (ASS), Power Spectral Subtraction (PSS) and Short Time Spectral Amplitude (STSA) Estimation. It was found that the noise reduction, together with a proper choice of features, could improve the classification accuracy to 96.78%. A novel model for the SRS was proposed for the response of a mixed-phase system (total airways response, TAR) to a source excitation at the input. The TAR/source model is similar to the vocal tract/source model in speech synthesis and is capable of capturing the acoustical changes brought about by the collapsing upper airways in the OSAHS. An algorithm was developed, based on the higher-order-spectra (HOS) to jointly estimate the source and the TAR, preserving the true phase characteristics of the latter. Working on a clinical database of signals, we show that the TAR is indeed a mixed phased signal and second-order statistics cannot fully characterise it. Nocturnal speech sounds can corrupt snore recordings and pose a challenge to the snore-based OSAHS diagnosis. The TAR could be shown to detect speech segments embedded in snores and derive features to diagnose the OSAHS. Finally presented is a novel technique for diagnosing the OSAHS, based solely on multi-parametric snore sound analysis. The method comprises a logistic regression model fed with a range of snore parameters derived from its features — the pitch and Total Airways Response (TAR) estimated using a Higher Order Statistics (HOS) based algorithm. The model was developed and its performance validated on a clinical database consisting of overnight snoring sounds simultaneously recorded during a hospital PSG using a high fidelity sound recording setup. The K-fold cross validation technique was used for validating the model. The validation process achieved an 89.3% sensitivity with 92.3% specificity (the area under the Receiver Operating Characteristic (ROC) curve was 0.96) in classifying the data sets into the two groups, the OSAHS (AHI >10) and the non-OSAHS. These results are superior to the existing results and unequivocally illustrate the feasibility of developing a snore-based non-contact OSAHS screening device.

Διανύουμε μια εποχή, όπου οι ανάγκες για μετάδοση πληροφορίας αυξάνονται ταχύτατα, με αποτέλεσμα τα χάλκινα καλώδια να μην αρκούν για να μεταδώσουν το πλήθος αυτό της πληροφορίας. Έτσι, περάσαμε στις Οπτικές Τηλεπικοινωνίες, όπου τα χάλκινα καλώδια αντικαταστάθηκαν από οπτικές ίνες και φορείς μετάδοσης της πληροφορίας δεν είναι πλέον τα ηλεκτρόνια αλλά τα φωτόνια. Κατά τη μετάδοση της πληροφορίας υπάρχουν όμως, φαινόμενα εξασθένησης και παραμόρφωσης του σήματος. Τη λύση σε αυτά τα προβλήματα καλείται να δώσει η χρήση σολιτονίων. Στην παρούσα διπλωματική εργασία, θα μελετήσουμε τον τρόπο με τον οποίον επηρεάζουν τα φαινόμενα ανώτερης τάξης την αλληλεπίδραση δύο γειτονικών σολιτονιακών παλμών που διαδίδονται μέσα σε μία οπτική ίνα. Πιο συγκεκριμένα, με τη χρήση αλγόριθμου της Fortran θεωρήσαμε δύο θεμελιώδεις σολιτονιακούς παλμούς και μελετήσαμε πως επηρεάζεται η διάδοσή τους κατά μήκος μιας οπτικής ίνας, αλλά και η μεταξύ τους αλληλεπίδρασή, από τη μεταξύ τους απόσταση, το σχετικό τους πλάτος καθώς και από τη διαφορά φάσης. Επιπλέον περιορίζοντας τη μεταξύ τους αλληλεπίδραση μελετήσαμε το πώς επηρεάζουν τη διάδοσή τους φαινόμενα ανώτερης τάξης όπως η σκέδαση Raman, η αυτό-διαμόρφωση απότομων άκρων (self-steepening) και η διασπορά τρίτης τάξης. / We are in an era where the need to transmit information rapidly increases, making the copper wires not enough to convey the multitude of this information. Thus, we moved on Optical Communications, where the copper cables were replaced by optical fibers and broadcasters of information are no longer electrons but photons. During the transmission of information we come across with problems such as attenuation and signal distortion. The use of solitons has come to give the solution to these problems. In this paper, we studied how the higher order phenomena, affects the interaction of two neighboring soliton pulses propagating through an optical fiber. More specifically, using a Fortran algorithm considering two fundamental soliton pulses we have studied how the propagation and their interaction is affected by their relative amplitude and phase difference. Also limiting the interaction between them, we have studied how the propagation is affected by higher order phenomena such as Stimulated Raman Scattering, Self Steepening and third order dispersion.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In this study the possible use of smart structures for noise control in a higher order acoustic duct was considered. The best option for this control was the use of axial splitters in the duct in order to prevent higher order mode propagation. It is possible to perform the active noise control in each splitter section by using a single channel control system. The use of smart structures takes advantage of the splitter plate and uses it as the control source, which substitutes the traditional loudspeakers used in active noise control systems. In order to evaluate the possibility of the noise control using smart structures, an analytical model of a thin plate with piezoelectric actuators was built then the acoustic field generated by this vibrating structure inside of the duct was obtained. However, to obtain the acoustic field inside an splitted duct, a numerical method such as the Component Mode Synthesis has to be used. Using the equation of the acoustic field generated in the duct by the plate, it was possible to obtain the acoustic field inside the splitted duct. After that, the active noise control simulations for harmonic excitations were performed and the influence of the size of the plate excited by the PZT actuators was studied. Finally the active control for random noise was simulated, in which the number of actuators in the plate was changed. In conclusion, it is possible to say that the smart structures can be used in active noise control of ducts with splitters and the advantages and disadvantages of the conveyed technique were presented. / Neste trabalho, foi estudada a proposta da utilização de estruturas inteligentes para o controle de ruído em um duto acústico com propagação de modos de alta ordem. A técnica mais adequada para este controle foi o particionamento do duto a fim de planificar as ondas que se propagam. Nesta região particionada, é possível realizar o controle ativo de ruído utilizando apenas um sensor e um atuador para cada lado da partição. A aplicação das estruturas inteligentes é proposta no sentido de aproveitar a placa particionadora para que, com a sua vibração, atuará como a fonte secundária necessária para o controle. Para a avaliação da possibilidade de controle utilizando esta técnica, primeiramente foi modelado o comportamento de uma placa instrumentada com atuadores piezoelétricos e, em seguida, obtida a modelagem analítica do campo sonoro gerado por uma estrutura vibrante no interior de um duto. Porém, a obtenção do campo acústico em um duto particionado não é facilmente obtido, sendo, então, realizada através da técnica de Síntese Modal de Componentes. Utilizando as equações do duto excitado por uma estrutura vibrante na técnica de síntese modal, foi possível obter campo acústico gerado no interior de um duto particionado. A partir disto, foram realizados simulações de controle ativo de ruído variando o trecho da placa a ser excitado para tons puros e para ruídos de banda estreita. Nesta última situação também foi avaliada a influência da quantidade de atuadores instalados. Concluiu-se deste trabalho que é possível a utilização de estruturas inteligentes no controle ativo de ruído em dutos particionados, sendo apresentadas suas vantagens e desvantagens. / Mestre em Engenharia Mecânica

Two main questions are addressed in this dissertation, namely: 1. What is the correct higher-order modal theory; 2. What does it take for theories to be equivalent. The whole dissertation consists of an extended argument in defence of the joint truth of two higher-order modal theories, namely, Plantingan Moderate Contingentism, a higher-order necessitist theory advocated by Plantinga (1974) and committed to the contingent being of some individuals, and Williamsonian Thorough Necessitism, a higher-order necessitist theory advocated by Williamson (2013) and committed to the necessary being of every possible individual. The case for the truth of these two theories relies on defences of the following metaphysical theses: i) Thorough Serious Actualism, according to which no things could have been related and yet be nothing, ii) Higher-Order Necessitism, according to which necessarily, every higher-order entity is necessarily something. It is shown that Thorough Serious Actualism and Higher-Order Necessitism are both implicit commitments of very weak logical theories. Prima facie, Plantingan Moderate Contingentism and Williamsonian Thorough Necessitism are jointly inconsistent. The argument for their joint truth thus relies also on showing i) their equivalence, and ii) that the dispute between Plantingans and Williamsonians is merely verbal. The case for i) and ii) relies on the Synonymy Account, an account of theory equivalence developed and defended in the dissertation. According to the account, theories are equivalent just in case they have the same structure of entailments and commitments, and the occupiers of the places in that structure are the same propositions. An immediate consequence of the Synonymy Account is that proponents of synonymous theories are engaged in merely verbal disputes. The Synonymy Account is also applied to the debate between noneists and Quineans, revealing that what is in question in that debate is what are the expressive resources available to describe the world.

Métodos de simulação baseados em dinâmica de fluidos computacional (DFC) têm sido empregado em diversas areas de estudo, tais como aeroacústica, dinâmica dos gases, fluidos viscoelásticos, entre outros. Entretanto, a necessidade de maior acurácia e desempenho destes métodos têm dado origem a soluções representadas por conjuntos de dados cada vez mais complexos. Neste contexto, técnicas voltadas à extração de estruturas relevantes (features), e sua posterior visualização, têm um papel muito importante, tornando mais fácil e intuitiva a análise dos dados gerados por simulações. Os métodos de extração de estruturas detectam e isolam elementos significativos no contexto da análise dos dados. No caso da análise de fluidos, estas estruturas podem ser isosuperfícies de pressão, vórtices, linhas de separação, etc. A visualização, por outro lado, confere atributos visuais a estas estruturas, permitindo uma análise mais intuitiva através de sua inspeção visual. Tradicionalmente, métodos de DFC representam suas soluções como funções lineares definidas sobre elementos do domínio. Entretanto, a evolução desses métodos tem dado origem a soluções representadas analiticamente através de funções de alta ordem. Apesar destes métodos apresentarem características desejáveis do ponto de vista de eficiência e acurácia, os dados gerados não são compatíveis com os métodos de extração de estruturas ou de visualização desenvolvidos originalmente para dados interpolados linearmente. Uma alternativa para este problema consiste na redução da ordem dos dados através de reamostragem e posterior aplicação de métodos tradicionais para extração de estruturas e visualização. Porém, o processo de amostragem pode introduzir erros nos dados ou resultar em excessivo consumo de memória, necessária ao armazenamento das amostras. Desta forma, torna-se necessário o desenvolvimento de métodos de extração e visualização que possam operar diretamente sobre os dados de alta ordem. As principais contribuições deste trabalho consistem em dois métodos que operam diretamente sobre dados de alta ordem. O primeiro consiste em um método para extração e visualização de isosuperfícies. O método baseia-se em uma abordagem híbrida que, ao distribuir o esforço computacional envolvido na extração e visualização das isosuperfícies em operações executadas nos espaços do objeto e da imagem, permite a exploração interativa de isosuperfícies através da troca de isovalores. O segundo método consiste em uma técnica para extração de estruturas lineares, onde a avaliação da forma intervalar do operador parallel vectors, em conjunto com métodos de subdivisão adaptativa, é utilizada como critério de pesquisa destas estruturas. Ambos os métodos foram projetados para tirarem proveito do paralelismo do hardware gráfico. Os resultados obtidos são apresentados tanto para dados sintéticos quanto para dados de simulações gerados através do método de Galerkin discontínuo. / Computational fluid dynamics (CFD) methods have been employed in the studies of subjects such as aeroacoustics, gas dynamics, turbo machinery, viscoelastic fluids, among others. However, the need for accuracy and high performance resulted in methods whose solutions are becoming increasingly more complex. In this context, feature extraction and visualization methods play a key role, making it easier and more intuitive to explore and analyze the simulation data. Feature extraction methods detect and isolate relevant structures in the context of data analysis. In the case of flow analysis, these structures could be pressure isocontours, vortex cores, detachment lines, etc. By assigning visual attributes to these structures, visualization methods allow for a more intuitive analysis through visual inspection. Traditionally, CFD methods represent the solution as piecewise linear basis functions defined over domain elements. However, the evolution of CFD methods has led to solutions represented analytically by higher-order functions. Despite their accuracy and efficiency, data generated by these methods are not compatible with feature extraction and visualization methods targeted to linearly interpolated data. An alternative approach is resampling, which allows the use of existing low order feature extraction and visualization methods. However, resampling is not desirable since it may introduce error due to subsampling and increase memory consumption associated to samples storage. To overcome these limitations, attention has recently been given to methods that handle higher-order data directly. The main contributions of this thesis are two methods developed to operate directly over higher-order data. The first method consists of an isocontouring method. It relies on a hybrid technique that, by splitting the isocontouring workload over image and object space computations, allows for interactive data exploration by dynamically changing isovalues. The second method is a line-type feature extraction method. The search for features is accomplished using adaptive subdivision methods driven by the evaluation of the inclusion form of the parallel vectors operator. Both methods were designed to take advantage of the parallelism of current graphics hardware. The obtained results are presented for synthetic and real simulation higher-order data generated with the discontinuous Galerkin method.