Establishing a valid, reliable, and objective method for determining the number of functioning motor units in a muscle is important clinically, as it would provide a quantitative means of documenting changes in neuromuscular health over time. This thesis addressed the reliability of motor unit number estimates (MUNEs) derived using decomposition-based quantitative electromyography (DQEMG) from the extensor digitorum brevis (EDB) and abductor hallucis (AH) muscles. Additionally, the effect of the mean surface motor unit potential (SMUP) parameter averaging method (arithmetic/ensemble), the size-related parameter used to calculate MUNE (amplitude/area), and the type of SMUP marker editing (automatic/manual) was investigated in terms of MUNE values. Two separate analyses on a single data set collected from twenty healthy subjects on two occasions were conducted. MUNEs were calculated by dividing a size-related parameter (amplitude/area) of the compound muscle action potential (CMAP) by the same size-related parameter of a representative mean SMUP. First, paired t-tests investigated differences in MUNEs calculated using arithmetic and ensemble averaged SMUP parameters. Within- and between-day reliability of the two measurements was established using intra-class correlation coefficients (ICCs), coefficients of variation (CV), mean absolute differences (MAD), and Bland Altman limits of agreement (LOA). Second, MUNEs (using both parameters) derived from automated and manually edited SMUPs were compared. The effect of the size-related parameter and editing type was identified using a two-factor, repeated measures analysis of variance. Reliability was determined as described above. Arithmetic averaged SMUP parameters produced smaller MUNEs than those derived from ensemble averaging (p<0.001). SMUP area produced higher MUNEs than SMUP amplitude (p<0.05), except when using arithmetic averaged parameters in AH. Interaction effects between editing type and size parameter were present in both muscles (F>6.68, p<0.001). Between-day MUNEs had lower CVs and MADs, higher ICCs, and narrower LOAs than within-day MUNEs. MUNEs derived from arithmetic averaged SMUP parameters showed the highest reliability (ICCs>0.91). MUNEs calculated from automated SMUP marker placements were highly correlated (r>0.86) and displayed comparable reliabilities to those derived from manual marker placement (ICCs>0.90). To optimize the reproducibility of MUNEs calculated using DQEMG, while minimizing processing time, between-day automated estimates using arithmetic averaged SMUP amplitude is recommended. / Thesis (Master, Rehabilitation Science) -- Queen's University, 2012-08-30 08:32:06.141

Multifrequency averaging is one of the widely used modeling and simulation techniques today for the analysis and design of power electronic systems. This technique is capable of providing the average behavior as well as the ripple behavior of power electronic systems. Hysteresis current control has fast response and internal current stability through controlling switches to maintain the current within a given hysteresis band of a given current command. However the state space variables in a hysteresis controlled system cannot be directly approached by multifrequency averaging method because of time varing switching frequency. In this thesis, a method of applying multifrequency averaging to hysteresis current controlled dc-dc converters is proposed. A dc-dc converter model with the application of this method has been successfully developed and validated both in simulation and experiment.

Response and stability of vessel rolling motion with strongly nonlinear softening stiffness will be studied in this dissertation using the methods of stochastic dynamical systems. As one of the most classic stability failure modes of vessel dynamics, large amplitude rolling motion in random beam waves has been studied in the past decades by many different research groups. Due to the strongly nonlinear softening stiffness and the stochastic excitation, there is still no general approach to predict the large amplitude rolling response and capsizing phenomena. We studied the rolling problem respectively using the shaping filter technique, stochastic averaging of the energy envelope and the stochastic Melnikov function. The shaping filter technique introduces some additional Gaussian filter variables to transform Gaussian white noise to colored noise in order to satisfy the Markov properties. In addition, we developed an automatic cumulant neglect tool to predict the response of the high dimensional dynamical system with higher order neglect. However, if the system has any jump phenomena, the cumulant neglect method may fail to predict the true response. The stochastic averaging of the energy envelope and the Melnikov function both have been applied to the rolling problem before, it is our first attempt to apply both approaches to the same vessel and compare their efficiency and capability. The inverse of the mean first passage time based on Markov theory and rate of phase space flux based on the stochastic Melnikov function are defined as two different, but analogous capsizing criteria. The effects of linear and nonlinear damping and wave characteristic frequency are studied to compare these two criteria. Further investigation of the relationship between the Markov and Melnikov based method is needed to explain the difference and similarity between the two capsizing criteria.

Virus recognition by visual examination of electron microscope (EM) images is time consuming and requires highly trained and experienced medical specialists. For these reasons, it is not suitable for screening large numbers of specimens. The objective of this research was to develop a reliable and robust pattern recognition system that could be trained to detect and classify different types of viruses from two-dimensional images obtained from an EM. This research evaluated the use of radial spectra of higher order spectral invariants to capture variations in textures and differences in symmetries of different types of viruses in EM images. The technique exploits invariant properties of the higher order spectral features, statistical techniques of feature averaging, and soft decision fusion in a unique manner applicable to the problem when a large number of particles were available for recognition, but were not easily registered on an individual basis due to the low signal to noise ratio. Experimental evaluations were carried out using EM images of viruses, and a high statistical reliability with low misclassification rates was obtained, showing that higher order spectral features are effective in classifying viruses from digitized electron micrographs. With the use of digital imaging in electron microscopes, this method can be fully automated.

This thesis aims to develop an alternative expectations model to the Rational Expectations Hypothesis (REH) and adaptive-expectations models, which provides more accurate temporal predictive performance and more closely reflects recent advances in behavioural economics, the ‘science of complexity’ and network dynamics. The model the thesis develops is called Adaptive Interactive Expectations (AIE), a subjective dynamic model of the process of expectations formation. To REH, the AIE model provides both an alternative and a complement. AIE and REH complement one another in that they are diametrically opposite in the following five dimensions, agent intelligence, agent interaction, agent homogeneity, equilibrium assumptions and the rationalisation process. REH and AIE stress the importance of hyper-intelligent agents interacting only via a price signal and near zero-intelligent agents interacting via a network structure, respectively. The complementary nature of AIE and REH provide dual perspectives that enhance analysis. The Dun & Bradstreet (D&B 2008) profit expectations survey is used in the thesis to calibrate AIE and make predictions. The predictive power of the AIE and REH models is compared. The thesis introduces the ‘pressure to change profit expectations index’, px. This index provides the ability to model unknowns within an adaptive dynamic process and combine the beliefs from interactive-expectations, adaptive-expectations and biases that include pessimism, optimism and ambivalence. AIE uses networks to model the flow of interactive-expectations between firms. To overcome the uncertainty over the structure of the interactive network, the thesis uses model-averaging over 121 network topologies. These networks are defined by three variables regardless of their complexity. Unfortunately, the Bayesian technique’s use of the number of variables as a measure of complexity makes it unsuitable for model-averaging over the network topologies. To overcome this limitation in the Bayesian technique, the thesis introduces two model-averaging techniques, ‘runtime-weighted’ and ‘optimal-calibration’. These model-averaging techniques are benchmarked against ‘Bayes-factor model-averaging’ and ‘equal-weighted model-averaging’. In addition to the aggregate called all–firms, the D&B (2008) survey has four divisions, manufacturing durables, manufacturing non–durables, wholesale and retail. To make use of the four divisions, the thesis introduces a ‘link-intensity matrix’ based upon an ‘input-output table’ to improve the calibration of the networks. The transpose of the table is also used in the thesis. The two ‘link-intensity matrices’ are benchmarked against the default, a ‘matrix of ones’. The aggregated and disaggregated versions of AIE are benchmarked against adaptive-expectations to establish whether the interactive-expectations component of AIE add value to the model. The thesis finds that AIE has more predictive power than REH. ‘Optimal-calibration model-averaging’ improves the predictive performance of the better-fitting versions of AIE, which are those versions that use the ‘input-output table’ and ‘matrix of ones’ link-intensity matrices. The ‘runtime-weighted model-averaging’ improves the predictive performance of only the ‘input-output table’ version of AIE. The interactive component of the AIE model improves the predictive performance of all versions of the AIE over adaptive-expectations. There is an ambiguous effect on prediction performance from introducing the ‘input-output table’. However, there is a clear reduction in the predictive performance from introducing its transpose. AIE can inform the debate on government intervention by providing an Agent-Based Model (ABM) perspective on the conflicting mathematical and narrative views proposed by the Greenwald–Stiglitz Theorem and Austrian school, respectively. Additionally, AIE can provide a complementary role to REH, which is descriptive/predictive and normative, respectively. The AIE network calibration uses an ‘input-output table’ to determine the link-intensity; this method could provide Computable General Equilibrium (CGE) and Dynamic Stochastic General Equilibrium (DSGE) with a way to improve their transmission mechanism. Furthermore, the AIE network calibration and prediction methodology may help overcome the validation concerns of practitioners when they implement ABM.

This thesis aims to develop an alternative expectations model to the Rational Expectations Hypothesis (REH) and adaptive-expectations models, which provides more accurate temporal predictive performance and more closely reflects recent advances in behavioural economics, the ‘science of complexity’ and network dynamics. The model the thesis develops is called Adaptive Interactive Expectations (AIE), a subjective dynamic model of the process of expectations formation. To REH, the AIE model provides both an alternative and a complement. AIE and REH complement one another in that they are diametrically opposite in the following five dimensions, agent intelligence, agent interaction, agent homogeneity, equilibrium assumptions and the rationalisation process. REH and AIE stress the importance of hyper-intelligent agents interacting only via a price signal and near zero-intelligent agents interacting via a network structure, respectively. The complementary nature of AIE and REH provide dual perspectives that enhance analysis. The Dun & Bradstreet (D&B 2008) profit expectations survey is used in the thesis to calibrate AIE and make predictions. The predictive power of the AIE and REH models is compared. The thesis introduces the ‘pressure to change profit expectations index’, px. This index provides the ability to model unknowns within an adaptive dynamic process and combine the beliefs from interactive-expectations, adaptive-expectations and biases that include pessimism, optimism and ambivalence. AIE uses networks to model the flow of interactive-expectations between firms. To overcome the uncertainty over the structure of the interactive network, the thesis uses model-averaging over 121 network topologies. These networks are defined by three variables regardless of their complexity. Unfortunately, the Bayesian technique’s use of the number of variables as a measure of complexity makes it unsuitable for model-averaging over the network topologies. To overcome this limitation in the Bayesian technique, the thesis introduces two model-averaging techniques, ‘runtime-weighted’ and ‘optimal-calibration’. These model-averaging techniques are benchmarked against ‘Bayes-factor model-averaging’ and ‘equal-weighted model-averaging’. In addition to the aggregate called all–firms, the D&B (2008) survey has four divisions, manufacturing durables, manufacturing non–durables, wholesale and retail. To make use of the four divisions, the thesis introduces a ‘link-intensity matrix’ based upon an ‘input-output table’ to improve the calibration of the networks. The transpose of the table is also used in the thesis. The two ‘link-intensity matrices’ are benchmarked against the default, a ‘matrix of ones’. The aggregated and disaggregated versions of AIE are benchmarked against adaptive-expectations to establish whether the interactive-expectations component of AIE add value to the model. The thesis finds that AIE has more predictive power than REH. ‘Optimal-calibration model-averaging’ improves the predictive performance of the better-fitting versions of AIE, which are those versions that use the ‘input-output table’ and ‘matrix of ones’ link-intensity matrices. The ‘runtime-weighted model-averaging’ improves the predictive performance of only the ‘input-output table’ version of AIE. The interactive component of the AIE model improves the predictive performance of all versions of the AIE over adaptive-expectations. There is an ambiguous effect on prediction performance from introducing the ‘input-output table’. However, there is a clear reduction in the predictive performance from introducing its transpose. AIE can inform the debate on government intervention by providing an Agent-Based Model (ABM) perspective on the conflicting mathematical and narrative views proposed by the Greenwald–Stiglitz Theorem and Austrian school, respectively. Additionally, AIE can provide a complementary role to REH, which is descriptive/predictive and normative, respectively. The AIE network calibration uses an ‘input-output table’ to determine the link-intensity; this method could provide Computable General Equilibrium (CGE) and Dynamic Stochastic General Equilibrium (DSGE) with a way to improve their transmission mechanism. Furthermore, the AIE network calibration and prediction methodology may help overcome the validation concerns of practitioners when they implement ABM.

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: The objective of the thesis is the development of a phase noise measuring system that makes use of crosscorrelation and averaging to measure below the system hardware noise floor. Various phase noise measurement techniques are considered after which the phase demodulation method is chosen to be implemented. The full development cycle of the hardware is discussed, as well as the post processing that is performed on the measured phase noise. / AFRIKAANSE OPSOMMING: Die doel van hierdie tesis is die ontwikkeling van ’n faseruis meetstelsel wat gebruik maak van kruiskorrelasie en vergemiddeling om onder die ruisvloer van die meetstelsel se hardeware te meet. Verskeie faseruis meettegnieke word ondersoek en die fase demodulasie metode word gekies om geïmplementeer te word. Die volle ontwikkelingsiklus van die hardeware word bespreek, sowel as die naverwerking wat toegepas is op die gemete faseruis.

In this work we have examined different methods of averaging in general relativity and cosmology. We developed the method based on Cartan scalars. We computed the backreaction term for a flat LTB model with a special ansatz for the radial function. We found out that it behaves as a positive cosmological constant. In the next part of this thesis we were interested in averaging inside LRS class II dust model. For this family we averaged all the Einstein equations and the resulting system generalizes the Buchert equations. We numerically worked out two concrete examples where deceleration parameter changes its sign from positive to negative. Powered by TCPDF (www.tcpdf.org)

The underlying objective of this thesis was to perform GHG simulation studies to predict the dispersion and transport of greenhouse gases emitted from a thermal power plant in order to assess the extent of dangerous living environment for those surrounding it in case of an unforeseen calamity. The research carried out during this thesis was to investigate the method of wind averaging techniques to analyse column measurements (XCO2). The reason for adopting this method of analysis was to correlate the physical aspect of wind data to average over a certain period of time wherein the amount of XCO2 (in ppm) observed displays values greater than the background concentration. CFD simulations were performed using the open source code, OpenFOAM, and steady RANS models modified with turbulence boundary conditions for the urban environment case with previously validated simulation studies carried out for the same region in Munich, Germany. Initial results performed during the testing stage indicated that maximum average XCO2 value (in ppm) was recorded at the lowest value of mean wind speed and at a more downwind location of the measurement site. The results obtained from simulation studies on comparison with experimental values (arithmetic average) also suggest that for the same time interval, the difference in values for similar wind conditions as mentioned before makes this technique a more favourable choice for comparison and verification at another time instant.  There have been recent developments in GHG simulation based studies and however the current method does represent certain drawbacks, an insight into performing averaging analysis at time intervals representing peak XCO2 moments could be demonstrated which can also help in reducing the overall number of simulations as well as provide information with respect to mitigation measures based on transport and diffusion behavior.

Submitted by Yagor Romano Carvalho null (yagor.carvalho@hotmail.com) on 2016-04-04T19:03:47Z No. of bitstreams: 1 textodissertacaoyagor.pdf: 9363276 bytes, checksum: 53698da316cb818be41fc5908947f21c (MD5) / Rejected by Ana Paula Grisoto (grisotoana@reitoria.unesp.br), reason: Solicitamos que realize uma nova submissão seguindo as orientações abaixo: O arquivo submetido está sem a ficha catalográfica. A versão submetida por você é considerada a versão final da dissertação/tese, portanto não poderá ocorrer qualquer alteração em seu conteúdo após a aprovação. Corrija estas informações e realize uma nova submissão contendo o arquivo correto. Agradecemos a compreensão. on 2016-04-06T14:05:29Z (GMT) / Submitted by Yagor Romano Carvalho (yagor.carvalho@hotmail.com) on 2016-04-07T14:18:45Z No. of bitstreams: 1 textodissertacaoyagorversaofinal.pdf: 9575354 bytes, checksum: c75f034afb98d3b896799c71de05f703 (MD5) / Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-04-08T14:02:51Z (GMT) No. of bitstreams: 1 carvalho_yr_me_sjrp.pdf: 9575354 bytes, checksum: c75f034afb98d3b896799c71de05f703 (MD5) / Made available in DSpace on 2016-04-08T14:02:51Z (GMT). No. of bitstreams: 1 carvalho_yr_me_sjrp.pdf: 9575354 bytes, checksum: c75f034afb98d3b896799c71de05f703 (MD5) Previous issue date: 2016-03-04 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Neste trabalho temos como principal objetivo determinar quota inferior para o número máximo de ciclos limites de um sistema diferencial polinomial de Liénard descontínuo de grau n com m zonas, para m=2,4. A principal ferramenta é uma combinação da Teoria da Média de primeira ordem com o processo de regularização de sistemas descontínuos. Analisamos detalhadamente um caso particular de um sistema polinomial de Liénard de grau 3 com 4 zonas / In this work our main aim is to determine the lower upper bound for the maximum number of limit cycles of a m-piecewise discontinuous Liénard polynomial differential system of degree n, for m=2,4. The main tool is a combination of the first order Averaging Method with the regularization process of discontinuous systems. We analyzed in details a particular case of a 4-piecewise discontinuous Liénard polynomial differential system of degree 3.