Reducció de vibracions residuals en moviments transitoris. Definició de lleis de moviment per mitjà de corbes B-spline

Molts sistemes mecànics existents tenen un comportament vibratori funcionalment perceptible, que es posa de manifest enfront d'excitacions transitòries. Normalment, les vibracions generades segueixen presents després del transitori (vibracions residuals), i poden provocar efectes negatius en la funció de disseny del mecanisme. El mètode que es proposa en aquesta tesi té com a objectiu principal la síntesi de lleis de moviment per reduir les vibracions residuals. Addicionalment, els senyals generats permeten complir dues condicions definides per l'usuari (anomenats requeriments funcionals). El mètode es fonamenta en la relació existent entre el contingut freqüencial d'un senyal transitori, i la vibració residual generada, segons sigui l'esmorteïment del sistema. Basat en aquesta relació, i aprofitant les propietats de la transformada de Fourier, es proposa la generació de lleis de moviment per convolució temporal de polsos. Aquestes resulten formades per trams concatenats de polinomis algebraics, cosa que facilita la seva implementació en entorns numèrics per mitjà de corbes B-spline.

Autenticidade e inovação: factores de renovação dos destinos turísticos maduros

Os destinos turísticos maduros caracterizam-se pela redução da sua capacidade para garantir satisfação aos consumidores, declínio das taxas de crescimento dos fluxos turísticos, degradação da imagem e perda de competitividade. Nesta fase necessitam de proceder à sua renovação ou rejuvenescimento através de novos factores de competitividade. Entre eles incluem-se a autenticidade transformada, em factor de atracção (push-factor), e a inovação. Neste trabalho identificam-se as várias correntes relativas à análise da autenticidade e as categorias de inovação no processo de renovação dos destinos, concluindo que ambas fazem parte de um processo contínuo que deve constituir uma centralidade das políticas turísticas.

Estudios de una filosofía intercultural en la propuesta de Raúl Fornet Betancourt

La propuesta de Raúl Fornet está dividida en cuatro etapas y se profundiza en la tercera: la transformación intercultural de la filosofía1. Entonces, la filosofía transformada como intercultural, en lugar de acudir a una filosofía eminentemente monocultural- de donde brota una racionalidad hegemónica-, se sustenta sobre un quehacer filosófico como proceso polifónico. La filosofía intercultural en lugar de acudir a presupuestos euro-céntricos, nos propone potenciar una razón interdiscursiva en el nuevo filosofar. Cambia esa filosofía que se identifica con las perspectivas europeas, por una transfiguración de la filosofía como intercultural e interdisciplinar. Frente a aquella filosofía que acude a reflexiones descontextualizadas de tinte universal, nos propone una nueva filosofía que brote de lo inédito. Dicho programa lo constituyen tres momentos2: El primero es una relectura crítica del pensamiento iberoamericano; el segundo es el de reaprender apensar, donde subyace la reubicación cultural en el que la que se supera el horizonte de pensamiento monocultural2 ; el tercero es desarrollar filosofías pro-posicionales.

A la orilla del río, construyendo soberanía alimentaria. La experiencia de una asociación de campesinos, pescadores e indígenas del Bajo Sinú (Colombia)

Esta tesis se centra en la problemática de la crisis alimentaria y en el papel que juegan las experiencias campesinas, o lo que se ha llamado vía campesina', en su solución. Y lo hace combinando la reflexión general sobre las crisis, con un caso específico de una organización campesina del río Sinú, en el norte de Colombia: la Asociación de Productores de la Ciénaga Grande de Lorica, Asprocig. Este trabajo se introduce en el debate acerca del valor de lo campesino (implícito en el debate sobre la modernidad y el desarrollo) en la medida en que la reflexión sobre la crisis alimentaria va más allá del ámbito rural al que pertenece Asprocig y se introduce en los espacios urbanos, las industrias, en sectores sociales desligados de la tierra. Es decir, comprende, además de lo propiamente campesino, las relaciones de lo campesino con el mundo y el lugar que se le asigna en esas relaciones. La utilidad de este punto es que ayuda a establecer una plataforma de reconocimiento en el sentido que lo plantea Asprocig. La investigación opta por la mirada ambiental que considera la complejidad de relaciones de la naturaleza, la cultura, la sociedad; la cultura como naturaleza transformada y la naturaleza en un proceso de hominización, la adaptación adecuada y el territorio como el mejor escenario para comprender la complejidad en la relación de estos elementos. La lectura de la experiencia de Asprocig se hace sobre la base de la intuición de que experiencias locales como ésta dan pistas para solucionar el problema alimentario, las crisis alimentarias tal como se presentan hoy en el mundo. De esta manera, esta tesis traza relaciones entre agricultura, alimentación y desarrollo. Más en concreto, relaciones entre crisis alimentaria y crisis del desarrollo pero también ahonda en las propuestas de autonomía, seguridad y soberanía alimentaria que construyen las y los campesinos, y en particular, las que construye Asprocig en el Bajo Sinú (Colombia).

Estudio de tres novelas de literatura proyectiva: Guayaquil, novela fantástica de Manuel Gallegos Naranjo, Río de sombras de Jorge Velasco Mackenzie y El libro flotante de Caytran Dölphin de Leonardo Valencia

La rama proyectiva de la literatura, también llamada literatura de anticipación, elabora una crítica cultural, política, social, filosófica y económica del presente al realizar fabulaciones acerca de un futuro donde usualmente se desarrollan distopías. Estos ejercicios se han escrito empleando los códigos de género fantástico, maravilloso y la ciencia ficción para suponer cómo será el destino de las urbes modernas. Dentro de esta línea, la narrativa guayaquileña recrea en sus historias una ciudad en crisis inmanente donde sus habitantes han aprendido a convivir con la idea de la destrucción. Estableciendo un diálogo con el imaginario apocalíptico judeo-cristiano instaurado desde la conquista de América y que ha cobrado un carácter renovado en este continente debido a su contacto con fábulas locales, los textos Guayaquil, novela fantástica (1901) de Manuel Gallegos Naranjo, Río de sombras (2003) de Jorge Velasco Mackenzie y El libro flotante de Caytran Dölphin (2006) de Leonardo Valencia, abordan desde sus propuestas estéticas ligadas con el fin del mundo, el temor de los guayaquileños ante la posible destrucción de su metrópoli. En estas novelas, la principal sensación de amenaza proviene del río junto al cual se construyó y ha crecido la ciudad, por lo que el agua es transformada en una alegoría de la memoria guayaquileña y también de su necesidad de transformación permanente. El haber descubierto una línea de lectura apocalíptica desde la cual abordar estas novelas prospectivas, refresca la mirada sobre el canon ecuatoriano y también ensaya un diálogo diferente con nuestra identidad. Con este conocimiento del fin que se aproxima, los habitantes de la ciudad amenazada deambulamos por sus calles aguardando –a veces con recelo, a veces con esperanza, porque el apocalipsis es también renovación– la llegada de la inundación definitiva.

Can wavelets improve the representation of forecast error covariances in variational data assimilation?

Two wavelet-based control variable transform schemes are described and are used to model some important features of forecast error statistics for use in variational data assimilation. The first is a conventional wavelet scheme and the other is an approximation of it. Their ability to capture the position and scale-dependent aspects of covariance structures is tested in a two-dimensional latitude-height context. This is done by comparing the covariance structures implied by the wavelet schemes with those found from the explicit forecast error covariance matrix, and with a non-wavelet- based covariance scheme used currently in an operational assimilation scheme. Qualitatively, the wavelet-based schemes show potential at modeling forecast error statistics well without giving preference to either position or scale-dependent aspects. The degree of spectral representation can be controlled by changing the number of spectral bands in the schemes, and the least number of bands that achieves adequate results is found for the model domain used. Evidence is found of a trade-off between the localization of features in positional and spectral spaces when the number of bands is changed. By examining implied covariance diagnostics, the wavelet-based schemes are found, on the whole, to give results that are closer to diagnostics found from the explicit matrix than from the nonwavelet scheme. Even though the nature of the covariances has the right qualities in spectral space, variances are found to be too low at some wavenumbers and vertical correlation length scales are found to be too long at most scales. The wavelet schemes are found to be good at resolving variations in position and scale-dependent horizontal length scales, although the length scales reproduced are usually too short. The second of the wavelet-based schemes is often found to be better than the first in some important respects, but, unlike the first, it has no exact inverse transform.

Analysis of convectively-generated gravity waves in mesoscale model simulations and wind profiler observations

The characteristics of convectively-generated gravity waves during an episode of deep convection near the coast of Wales are examined in both high resolution mesoscale simulations [with the (UK) Met Oce Unified Model] and in observations from a Mesosphere-Stratosphere-Troposphere (MST) wind profiling Doppler radar. Deep convection reached the tropopause and generated vertically propagating, high frequency waves in the lower stratosphere that produced vertical velocity perturbations O(1 m/s). Wavelet analysis is applied in order to determine the characteristic periods and wavelengths of the waves. In both the simulations and observations, the wavelet spectra contain several distinct preferred scales indicated by multiple spectral peaks. The peaks are most pronounced in the horizontal spectra at several wavelengths less than 50 km. Although these peaks are most clear and of largest amplitude in the highest resolution simulations (with 1 km horizontal grid length), they are also evident in coarser simulations (with 4 km horizontal grid length). Peaks also exist in the vertical and temporal spectra (between approximately 2.5 and 4.5 km, and 10 to 30 minutes, respectively) with good agreement between simulation and observation. Two-dimensional (wavenumber-frequency) spectra demonstrate that each of the selected horizontal scales contains peaks at each of preferred temporal scales revealed by the one- dimensional spectra alone.

Wavelets and the generalization of the variogram

The experimental variogram computed in the usual way by the method of moments and the Haar wavelet transform are similar in that they filter data and yield informative summaries that may be interpreted. The variogram filters out constant values; wavelets can filter variation at several spatial scales and thereby provide a richer repertoire for analysis and demand no assumptions other than that of finite variance. This paper compares the two functions, identifying that part of the Haar wavelet transform that gives it its advantages. It goes on to show that the generalized variogram of order k=1, 2, and 3 filters linear, quadratic, and cubic polynomials from the data, respectively, which correspond with more complex wavelets in Daubechies's family. The additional filter coefficients of the latter can reveal features of the data that are not evident in its usual form. Three examples in which data recorded at regular intervals on transects are analyzed illustrate the extended form of the variogram. The apparent periodicity of gilgais in Australia seems to be accentuated as filter coefficients are added, but otherwise the analysis provides no new insight. Analysis of hyerpsectral data with a strong linear trend showed that the wavelet-based variograms filtered it out. Adding filter coefficients in the analysis of the topsoil across the Jurassic scarplands of England changed the upper bound of the variogram; it then resembled the within-class variogram computed by the method of moments. To elucidate these results, we simulated several series of data to represent a random process with values fluctuating about a mean, data with long-range linear trend, data with local trend, and data with stepped transitions. The results suggest that the wavelet variogram can filter out the effects of long-range trend, but not local trend, and of transitions from one class to another, as across boundaries.

Time series analysis of lava flux

We have applied time series analytical techniques to the flux of lava from an extrusive eruption. Tilt data acting as a proxy for flux are used in a case study of the May–August 1997 period of the eruption at Soufrière Hills Volcano, Montserrat. We justify the use of such a proxy by simple calibratory arguments. Three techniques of time series analysis are employed: spectral, spectrogram and wavelet methods. In addition to the well-known ~9-hour periodicity shown by these data, a previously unknown periodic flux variability is revealed by the wavelet analysis as a 3-day cycle of frequency modulation during June–July 1997, though the physical mechanism responsible is not clear. Such time series analysis has potential for other lava flux proxies at other types of volcanoes.

A shift to randomness of brain oscillations in people with autism

BACKGROUND: Resting-state functional magnetic resonance imaging (fMRI) enables investigation of the intrinsic functional organization of the brain. Fractal parameters such as the Hurst exponent, H, describe the complexity of endogenous low-frequency fMRI time series on a continuum from random (H = .5) to ordered (H = 1). Shifts in fractal scaling of physiological time series have been associated with neurological and cardiac conditions. METHODS: Resting-state fMRI time series were recorded in 30 male adults with an autism spectrum condition (ASC) and 33 age- and IQ-matched male volunteers. The Hurst exponent was estimated in the wavelet domain and between-group differences were investigated at global and voxel level and in regions known to be involved in autism. RESULTS: Complex fractal scaling of fMRI time series was found in both groups but globally there was a significant shift to randomness in the ASC (mean H = .758, SD = .045) compared with neurotypical volunteers (mean H = .788, SD = .047). Between-group differences in H, which was always reduced in the ASC group, were seen in most regions previously reported to be involved in autism, including cortical midline structures, medial temporal structures, lateral temporal and parietal structures, insula, amygdala, basal ganglia, thalamus, and inferior frontal gyrus. Severity of autistic symptoms was negatively correlated with H in retrosplenial and right anterior insular cortex. CONCLUSIONS: Autism is associated with a small but significant shift to randomness of endogenous brain oscillations. Complexity measures may provide physiological indicators for autism as they have done for other medical conditions.

Unsupervised segmentation using Gabor wavelets and statistical features in LIDAR data analysis

In this paper, we address issues in segmentation Of remotely sensed LIDAR (LIght Detection And Ranging) data. The LIDAR data, which were captured by airborne laser scanner, contain 2.5 dimensional (2.5D) terrain surface height information, e.g. houses, vegetation, flat field, river, basin, etc. Our aim in this paper is to segment ground (flat field)from non-ground (houses and high vegetation) in hilly urban areas. By projecting the 2.5D data onto a surface, we obtain a texture map as a grey-level image. Based on the image, Gabor wavelet filters are applied to generate Gabor wavelet features. These features are then grouped into various windows. Among these windows, a combination of their first and second order of statistics is used as a measure to determine the surface properties. The test results have shown that ground areas can successfully be segmented from LIDAR data. Most buildings and high vegetation can be detected. In addition, Gabor wavelet transform can partially remove hill or slope effects in the original data by tuning Gabor parameters.

Face verification using Gabor wavelets and AdaBoost

This paper presents a new face verification algorithm based on Gabor wavelets and AdaBoost. In the algorithm, faces are represented by Gabor wavelet features generated by Gabor wavelet transform. Gabor wavelets with 5 scales and 8 orientations are chosen to form a family of Gabor wavelets. By convolving face images with these 40 Gabor wavelets, the original images are transformed into magnitude response images of Gabor wavelet features. The AdaBoost algorithm selects a small set of significant features from the pool of the Gabor wavelet features. Each feature is the basis for a weak classifier which is trained with face images taken from the XM2VTS database. The feature with the lowest classification error is selected in each iteration of the AdaBoost operation. We also address issues regarding computational costs in feature selection with AdaBoost. A support vector machine (SVM) is trained with examples of 20 features, and the results have shown a low false positive rate and a low classification error rate in face verification.

Facial feature extraction and selection by Gabor wavelets and boosting

In this paper, we present a feature selection approach based on Gabor wavelet feature and boosting for face verification. By convolution with a group of Gabor wavelets, the original images are transformed into vectors of Gabor wavelet features. Then for individual person, a small set of significant features are selected by the boosting algorithm from a large set of Gabor wavelet features. The experiment results have shown that the approach successfully selects meaningful and explainable features for face verification. The experiments also suggest that for the common characteristics such as eyes, noses, mouths may not be as important as some unique characteristic when training set is small. When training set is large, the unique characteristics and the common characteristics are both important.

The application of the Hilbert spectrum to the analysis of electromyographic signals

This paper investigates the application of the Hilbert spectrum (HS), which is a recent tool for the analysis of nonlinear and nonstationary time-series, to the study of electromyographic (EMG) signals. The HS allows for the visualization of the energy of signals through a joint time-frequency representation. In this work we illustrate the use of the HS in two distinct applications. The first is for feature extraction from EMG signals. Our results showed that the instantaneous mean frequency (IMNF) estimated from the HS is a relevant feature to clinical practice. We found that the median of the IMNF reduces when the force level of the muscle contraction increases. In the second application we investigated the use of the HS for detection of motor unit action potentials (MUAPs). The detection of MUAPs is a basic step in EMG decomposition tools, which provide relevant information about the neuromuscular system through the morphology and firing time of MUAPs. We compared, visually, how MUAP activity is perceived on the HS with visualizations provided by some traditional (e.g. scalogram, spectrogram, Wigner-Ville) time-frequency distributions. Furthermore, an alternative visualization to the HS, for detection of MUAPs, is proposed and compared to a similar approach based on the continuous wavelet transform (CWT). Our results showed that both the proposed technique and the CWT allowed for a clear visualization of MUAP activity on the time-frequency distributions, whereas results obtained with the HS were the most difficult to interpret as they were extremely affected by spurious energy activity. (c) 2008 Elsevier Inc. All rights reserved.

EMG signal filtering based on Empirical Mode Decomposition

This paper introduces a procedure for filtering electromyographic (EMG) signals. Its key element is the Empirical Mode Decomposition, a novel digital signal processing technique that can decompose my time-series into a set of functions designated as intrinsic mode functions. The procedure for EMG signal filtering is compared to a related approach based on the wavelet transform. Results obtained from the analysis of synthetic and experimental EMG signals show that Our method can be Successfully and easily applied in practice to attenuation of background activity in EMG signals. (c) 2006 Elsevier Ltd. All rights reserved.