Time-frequency characterization of a sound propagation channel as an educational tool

This paper discusses the use of sound waves to illustrate multipath radio propagation concepts. Specifically, a procedure is presented to measure the time-varying frequency response of the channel. This helps demonstrate how a propagation channel can be characterized in time and frequency, and provides visualizations of the concepts of coherence time and coherence bandwidth. The measurements are very simple to carry out, and the required equipment is easily available. The proposed method can be useful for wireless or mobile communication courses.

Time-Frequency based Feature Selection for Discrimination of non stationary Biosignals.

This research proposes a generic methodology for dimensionality reduction upon time-frequency representations applied to the classification of different types of biosignals. The methodology directly deals with the highly redundant and irrelevant data contained in these representations, combining a first stage of irrelevant data removal by variable selection, with a second stage of redundancy reduction using methods based on linear transformations. The study addresses two techniques that provided a similar performance: the first one is based on the selection of a set of the most relevant time?frequency points, whereas the second one selects the most relevant frequency bands. The first methodology needs a lower quantity of components, leading to a lower feature space; but the second improves the capture of the time-varying dynamics of the signal, and therefore provides a more stable performance. In order to evaluate the generalization capabilities of the methodology proposed it has been applied to two types of biosignals with different kinds of non-stationary behaviors: electroencephalographic and phonocardiographic biosignals. Even when these two databases contain samples with different degrees of complexity and a wide variety of characterizing patterns, the results demonstrate a good accuracy for the detection of pathologies, over 98%.The results open the possibility to extrapolate the methodology to the study of other biosignals.

A mathematical framework for new fault detection schemes in nonlinear stochastic continuous-time dynamical systems

n this work, a mathematical unifying framework for designing new fault detection schemes in nonlinear stochastic continuous-time dynamical systems is developed. These schemes are based on a stochastic process, called the residual, which reflects the system behavior and whose changes are to be detected. A quickest detection scheme for the residual is proposed, which is based on the computed likelihood ratios for time-varying statistical changes in the Ornstein–Uhlenbeck process. Several expressions are provided, depending on a priori knowledge of the fault, which can be employed in a proposed CUSUM-type approximated scheme. This general setting gathers different existing fault detection schemes within a unifying framework, and allows for the definition of new ones. A comparative simulation example illustrates the behavior of the proposed schemes.

Development of a methodology for nuclear data uncertainty propagation on isotopic evolution calculations for advanced nuclear systems

Una apropiada evaluación de los márgenes de seguridad de una instalación nuclear, por ejemplo, una central nuclear, tiene en cuenta todas las incertidumbres que afectan a los cálculos de diseño, funcionanmiento y respuesta ante accidentes de dicha instalación. Una fuente de incertidumbre son los datos nucleares, que afectan a los cálculos neutrónicos, de quemado de combustible o activación de materiales. Estos cálculos permiten la evaluación de las funciones respuesta esenciales para el funcionamiento correcto durante operación, y también durante accidente. Ejemplos de esas respuestas son el factor de multiplicación neutrónica o el calor residual después del disparo del reactor. Por tanto, es necesario evaluar el impacto de dichas incertidumbres en estos cálculos. Para poder realizar los cálculos de propagación de incertidumbres, es necesario implementar metodologías que sean capaces de evaluar el impacto de las incertidumbres de estos datos nucleares. Pero también es necesario conocer los datos de incertidumbres disponibles para ser capaces de manejarlos. Actualmente, se están invirtiendo grandes esfuerzos en mejorar la capacidad de analizar, manejar y producir datos de incertidumbres, en especial para isótopos importantes en reactores avanzados. A su vez, nuevos programas/códigos están siendo desarrollados e implementados para poder usar dichos datos y analizar su impacto. Todos estos puntos son parte de los objetivos del proyecto europeo ANDES, el cual ha dado el marco de trabajo para el desarrollo de esta tesis doctoral. Por tanto, primero se ha llevado a cabo una revisión del estado del arte de los datos nucleares y sus incertidumbres, centrándose en los tres tipos de datos: de decaimiento, de rendimientos de fisión y de secciones eficaces. A su vez, se ha realizado una revisión del estado del arte de las metodologías para la propagación de incertidumbre de estos datos nucleares. Dentro del Departamento de Ingeniería Nuclear (DIN) se propuso una metodología para la propagación de incertidumbres en cálculos de evolución isotópica, el Método Híbrido. Esta metodología se ha tomado como punto de partida para esta tesis, implementando y desarrollando dicha metodología, así como extendiendo sus capacidades. Se han analizado sus ventajas, inconvenientes y limitaciones. El Método Híbrido se utiliza en conjunto con el código de evolución isotópica ACAB, y se basa en el muestreo por Monte Carlo de los datos nucleares con incertidumbre. En esta metodología, se presentan diferentes aproximaciones según la estructura de grupos de energía de las secciones eficaces: en un grupo, en un grupo con muestreo correlacionado y en multigrupos. Se han desarrollado diferentes secuencias para usar distintas librerías de datos nucleares almacenadas en diferentes formatos: ENDF-6 (para las librerías evaluadas), COVERX (para las librerías en multigrupos de SCALE) y EAF (para las librerías de activación). Gracias a la revisión del estado del arte de los datos nucleares de los rendimientos de fisión se ha identificado la falta de una información sobre sus incertidumbres, en concreto, de matrices de covarianza completas. Además, visto el renovado interés por parte de la comunidad internacional, a través del grupo de trabajo internacional de cooperación para evaluación de datos nucleares (WPEC) dedicado a la evaluación de las necesidades de mejora de datos nucleares mediante el subgrupo 37 (SG37), se ha llevado a cabo una revisión de las metodologías para generar datos de covarianza. Se ha seleccionando la actualización Bayesiana/GLS para su implementación, y de esta forma, dar una respuesta a dicha falta de matrices completas para rendimientos de fisión. Una vez que el Método Híbrido ha sido implementado, desarrollado y extendido, junto con la capacidad de generar matrices de covarianza completas para los rendimientos de fisión, se han estudiado diferentes aplicaciones nucleares. Primero, se estudia el calor residual tras un pulso de fisión, debido a su importancia para cualquier evento después de la parada/disparo del reactor. Además, se trata de un ejercicio claro para ver la importancia de las incertidumbres de datos de decaimiento y de rendimientos de fisión junto con las nuevas matrices completas de covarianza. Se han estudiado dos ciclos de combustible de reactores avanzados: el de la instalación europea para transmutación industrial (EFIT) y el del reactor rápido de sodio europeo (ESFR), en los cuales se han analizado el impacto de las incertidumbres de los datos nucleares en la composición isotópica, calor residual y radiotoxicidad. Se han utilizado diferentes librerías de datos nucleares en los estudios antreriores, comparando de esta forma el impacto de sus incertidumbres. A su vez, mediante dichos estudios, se han comparando las distintas aproximaciones del Método Híbrido y otras metodologías para la porpagación de incertidumbres de datos nucleares: Total Monte Carlo (TMC), desarrollada en NRG por A.J. Koning y D. Rochman, y NUDUNA, desarrollada en AREVA GmbH por O. Buss y A. Hoefer. Estas comparaciones demostrarán las ventajas del Método Híbrido, además de revelar sus limitaciones y su rango de aplicación. ABSTRACT For an adequate assessment of safety margins of nuclear facilities, e.g. nuclear power plants, it is necessary to consider all possible uncertainties that affect their design, performance and possible accidents. Nuclear data are a source of uncertainty that are involved in neutronics, fuel depletion and activation calculations. These calculations can predict critical response functions during operation and in the event of accident, such as decay heat and neutron multiplication factor. Thus, the impact of nuclear data uncertainties on these response functions needs to be addressed for a proper evaluation of the safety margins. Methodologies for performing uncertainty propagation calculations need to be implemented in order to analyse the impact of nuclear data uncertainties. Nevertheless, it is necessary to understand the current status of nuclear data and their uncertainties, in order to be able to handle this type of data. Great eórts are underway to enhance the European capability to analyse/process/produce covariance data, especially for isotopes which are of importance for advanced reactors. At the same time, new methodologies/codes are being developed and implemented for using and evaluating the impact of uncertainty data. These were the objectives of the European ANDES (Accurate Nuclear Data for nuclear Energy Sustainability) project, which provided a framework for the development of this PhD Thesis. Accordingly, first a review of the state-of-the-art of nuclear data and their uncertainties is conducted, focusing on the three kinds of data: decay, fission yields and cross sections. A review of the current methodologies for propagating nuclear data uncertainties is also performed. The Nuclear Engineering Department of UPM has proposed a methodology for propagating uncertainties in depletion calculations, the Hybrid Method, which has been taken as the starting point of this thesis. This methodology has been implemented, developed and extended, and its advantages, drawbacks and limitations have been analysed. It is used in conjunction with the ACAB depletion code, and is based on Monte Carlo sampling of variables with uncertainties. Different approaches are presented depending on cross section energy-structure: one-group, one-group with correlated sampling and multi-group. Differences and applicability criteria are presented. Sequences have been developed for using different nuclear data libraries in different storing-formats: ENDF-6 (for evaluated libraries) and COVERX (for multi-group libraries of SCALE), as well as EAF format (for activation libraries). A revision of the state-of-the-art of fission yield data shows inconsistencies in uncertainty data, specifically with regard to complete covariance matrices. Furthermore, the international community has expressed a renewed interest in the issue through the Working Party on International Nuclear Data Evaluation Co-operation (WPEC) with the Subgroup (SG37), which is dedicated to assessing the need to have complete nuclear data. This gives rise to this review of the state-of-the-art of methodologies for generating covariance data for fission yields. Bayesian/generalised least square (GLS) updating sequence has been selected and implemented to answer to this need. Once the Hybrid Method has been implemented, developed and extended, along with fission yield covariance generation capability, different applications are studied. The Fission Pulse Decay Heat problem is tackled first because of its importance during events after shutdown and because it is a clean exercise for showing the impact and importance of decay and fission yield data uncertainties in conjunction with the new covariance data. Two fuel cycles of advanced reactors are studied: the European Facility for Industrial Transmutation (EFIT) and the European Sodium Fast Reactor (ESFR), and response function uncertainties such as isotopic composition, decay heat and radiotoxicity are addressed. Different nuclear data libraries are used and compared. These applications serve as frameworks for comparing the different approaches of the Hybrid Method, and also for comparing with other methodologies: Total Monte Carlo (TMC), developed at NRG by A.J. Koning and D. Rochman, and NUDUNA, developed at AREVA GmbH by O. Buss and A. Hoefer. These comparisons reveal the advantages, limitations and the range of application of the Hybrid Method.

Control of a Teleoperation System by State Convergence with Variable Time Delay

In this paper, we propose a novel control scheme for bilateral teleoperation of n degree-of-freedom (DOF) nonlinear robotic systems with time-varying communication delay. We consider that the human operator contains a constant force on the local manipulator. The local and remote manipulators are coupled using state convergence control scheme. By choosing a Lyapunov-Krasovskii functional, we show that the local-remote teleoperation system is asymptotically stable. It is also shown that, in the case of reliable communication protocols, the proposed scheme guarantees that the remote manipulator tracks the delayed trajectory of the local manipulator. The time delay of communication channel is assumed to be unknown and randomly time varying, but the upper bounds of the delay interval and the derivative of the delay are assumed to be known.

Stability Analysis of Teleoperation System by State Convergence with Variable Time Delay

We propose a novel control scheme for bilateral teleoperation of n degree-of-freedom (DOF) nonlinear robotic systems with time-varying communication delay. A major contribution from this work lies in the demonstration that the structure of a state convergence algorithm can be also applied to nth-order nonlinear teleoperation systems. By choosing a Lyapunov Krasovskii functional, we show that the local-remote teleoperation system is asymptotically stable. The time delay of communication channel is assumed to be unknown and randomly time varying, but the upper bounds of the delay interval and the derivative of the delay are assumed to be known.

Forecasting Electricity Prices and their volatilities using Unobserved Components.

The liberalization of electricity markets more than ten years ago in the vast majority of developed countries has introduced the need of modelling and forecasting electricity prices and volatilities, both in the short and long term. Thus, there is a need of providing methodology that is able to deal with the most important features of electricity price series, which are well known for presenting not only structure in conditional mean but also time-varying conditional variances. In this work we propose a new model, which allows to extract conditionally heteroskedastic common factors from the vector of electricity prices. These common factors are jointly estimated as well as their relationship with the original vector of series, and the dynamics affecting both their conditional mean and variance. The estimation of the model is carried out under the state-space formulation. The new model proposed is applied to extract seasonal common dynamic factors as well as common volatility factors for electricity prices and the estimation results are used to forecast electricity prices and their volatilities in the Spanish zone of the Iberian Market. Several simplified/alternative models are also considered as benchmarks to illustrate that the proposed approach is superior to all of them in terms of explanatory and predictive power.

Automatic Bandwidth Estimation Strategy for High-Quality Non-Parametric Modeling based Moving Object Detection

Here, a novel and efficient moving object detection strategy by non-parametric modeling is presented. Whereas the foreground is modeled by combining color and spatial information, the background model is constructed exclusively with color information, thus resulting in a great reduction of the computational and memory requirements. The estimation of the background and foreground covariance matrices, allows us to obtain compact moving regions while the number of false detections is reduced. Additionally, the application of a tracking strategy provides a priori knowledge about the spatial position of the moving objects, which improves the performance of the Bayesian classifier

Regularization for sparsity in statistical analysis and machine learning

Pragmatism is the leading motivation of regularization. We can understand regularization as a modification of the maximum-likelihood estimator so that a reasonable answer could be given in an unstable or ill-posed situation. To mention some typical examples, this happens when fitting parametric or non-parametric models with more parameters than data or when estimating large covariance matrices. Regularization is usually used, in addition, to improve the bias-variance tradeoff of an estimation. Then, the definition of regularization is quite general, and, although the introduction of a penalty is probably the most popular type, it is just one out of multiple forms of regularization. In this dissertation, we focus on the applications of regularization for obtaining sparse or parsimonious representations, where only a subset of the inputs is used. A particular form of regularization, L1-regularization, plays a key role for reaching sparsity. Most of the contributions presented here revolve around L1-regularization, although other forms of regularization are explored (also pursuing sparsity in some sense). In addition to present a compact review of L1-regularization and its applications in statistical and machine learning, we devise methodology for regression, supervised classification and structure induction of graphical models. Within the regression paradigm, we focus on kernel smoothing learning, proposing techniques for kernel design that are suitable for high dimensional settings and sparse regression functions. We also present an application of regularized regression techniques for modeling the response of biological neurons. Supervised classification advances deal, on the one hand, with the application of regularization for obtaining a na¨ıve Bayes classifier and, on the other hand, with a novel algorithm for brain-computer interface design that uses group regularization in an efficient manner. Finally, we present a heuristic for inducing structures of Gaussian Bayesian networks using L1-regularization as a filter. El pragmatismo es la principal motivación de la regularización. Podemos entender la regularización como una modificación del estimador de máxima verosimilitud, de tal manera que se pueda dar una respuesta cuando la configuración del problema es inestable. A modo de ejemplo, podemos mencionar el ajuste de modelos paramétricos o no paramétricos cuando hay más parámetros que casos en el conjunto de datos, o la estimación de grandes matrices de covarianzas. Se suele recurrir a la regularización, además, para mejorar el compromiso sesgo-varianza en una estimación. Por tanto, la definición de regularización es muy general y, aunque la introducción de una función de penalización es probablemente el método más popular, éste es sólo uno de entre varias posibilidades. En esta tesis se ha trabajado en aplicaciones de regularización para obtener representaciones dispersas, donde sólo se usa un subconjunto de las entradas. En particular, la regularización L1 juega un papel clave en la búsqueda de dicha dispersión. La mayor parte de las contribuciones presentadas en la tesis giran alrededor de la regularización L1, aunque también se exploran otras formas de regularización (que igualmente persiguen un modelo disperso). Además de presentar una revisión de la regularización L1 y sus aplicaciones en estadística y aprendizaje de máquina, se ha desarrollado metodología para regresión, clasificación supervisada y aprendizaje de estructura en modelos gráficos. Dentro de la regresión, se ha trabajado principalmente en métodos de regresión local, proponiendo técnicas de diseño del kernel que sean adecuadas a configuraciones de alta dimensionalidad y funciones de regresión dispersas. También se presenta una aplicación de las técnicas de regresión regularizada para modelar la respuesta de neuronas reales. Los avances en clasificación supervisada tratan, por una parte, con el uso de regularización para obtener un clasificador naive Bayes y, por otra parte, con el desarrollo de un algoritmo que usa regularización por grupos de una manera eficiente y que se ha aplicado al diseño de interfaces cerebromáquina. Finalmente, se presenta una heurística para inducir la estructura de redes Bayesianas Gaussianas usando regularización L1 a modo de filtro.

Pulsatile blood flow-split in aortic arch dissection

Abnormalities of the aortic arch, as the most proximal site of the cardiovascular system, are of great interest due to its major role in blood distribution to all downstream members. Wall dissection is one of the disorders that an aorta may suffer due to hypertension or degradation of aortic wall properties. A geometrical change of the aortic arch caused by the dissected wall, and consequently the blood flow path, makes the time-varying flow curves to be different in comparison to the healthy aortic arch. This phenomenon modifies wall shear stress (WSS) history during the cardiac cycle. In the current work, the pulsatile blood flow in a typical Stanford A (DeBakey II) dissected aorta is simulated by CFD technique, STAR-CCM+. The boundary conditions are calculated based on a combination of the impedance boundary condition and the auto-regulation concept in the cardiovascular system.

Diseño de una interfaz de representación gráfica de la base de datos de HRTF

El actual proyecto consiste en la creación de una interfaz gráfica de usuario (GUI) en entorno de MATLAB que realice una representación gráfica de la base de datos de HRTF (Head-Related Transfer Function). La función de transferencia de la cabeza es una herramienta muy útil en el estudio de la capacidad del ser humano para percibir su entorno sonoro, además de la habilidad de éste en la localización de fuentes sonoras en el espacio que le rodea. La HRTF biaural (terminología para referirse al conjunto de HRTF del oído izquierdo y del oído derecho) en sí misma, posee información de especial interés ya que las diferencias entre las HRTF de cada oído, conceden la información que nuestro sistema de audición utiliza en la percepción del campo sonoro. Por ello, la funcionalidad de la interfaz gráfica creada presenta gran provecho dentro del estudio de este campo. Las diferencias interaurales se caracterizan en amplitud y en tiempo, variando en función de la frecuencia. Mediante la transformada inversa de Fourier de la señal HRTF, se obtiene la repuesta al impulso de la cabeza, es decir, la HRIR (Head-Related Impulse Response). La cual, además de tener una gran utilidad en la creación de software o dispositivos de generación de sonido envolvente, se utiliza para obtener las diferencias ITD (Interaural Time Difference) e ILD (Interaural Time Difference), comúnmente denominados “parámetros de localización espacial”. La base de datos de HRTF contiene la información biaural de diferentes puntos de ubicación de la fuente sonora, formando una red de coordenadas esféricas que envuelve la cabeza del sujeto. Dicha red, según las medidas realizadas en la cámara anecoica de la EUITT (Escuela Universitaria de Ingeniería Técnica de Telecomunicación), presenta una precisión en elevación de 10º y en azimut de 5º. Los receptores son dos micrófonos alojados en el maniquí acústico llamado HATS (Hats and Torso Simulator) modelo 4100D de Brüel&Kjaer. Éste posee las características físicas que influyen en la percepción del entorno como son las formas del pabellón auditivo (pinna), de la cabeza, del cuello y del torso humano. Será necesario realizar los cálculos de interpolación para todos aquellos puntos no contenidos en la base de datos HRTF, este proceso es sumamente importante no solo para potenciar la capacidad de la misma sino por su utilidad para la comparación entre otras bases de datos existentes en el estudio de este ámbito. La interfaz gráfica de usuario está concebida para un manejo sencillo, claro y predecible, a la vez que interactivo. Desde el primer boceto del programa se ha tenido clara su filosofía, impuesta por las necesidades de un usuario que busca una herramienta práctica y de manejo intuitivo. Su diseño de una sola ventana reúne tanto los componentes de obtención de datos como los que hacen posible la representación gráfica de las HRTF, las HRIR y los parámetros de localización espacial, ITD e ILD. El usuario podrá ir alternando las representaciones gráficas a la vez que introduce las coordenadas de los puntos que desea visualizar, definidas por phi (elevación) y theta (azimut). Esta faceta de la interfaz es la que le otorga una gran facilidad de acceso y lectura de la información representada en ella. Además, el usuario puede introducir valores incluidos en la base de datos o valores intermedios a estos, de esta manera, se indica a la interfaz la necesidad de realizar la interpolación de los mismos. El método de interpolación escogido es el de la ponderación de la distancia inversa entre puntos. Dependiendo de los valores introducidos por el usuario se realizará una interpolación de dos o cuatro puntos, siendo éstos limítrofes al valor introducido, ya sea de phi o theta. Para añadir versatilidad a la interfaz gráfica de usuario, se ha añadido la opción de generar archivos de salida en forma de imagen de las gráficas representadas, de tal forma que el usuario pueda extraer los datos que le interese para cualquier valor de phi y theta. Se completa el presente proyecto fin de carrera con un trabajo de investigación y estudio comparativo de la función y la aplicación de las bases de datos de HRTF dentro del marco científico y de investigación. Esto ha hecho posible concentrar información relacionada a través de revistas científicas de investigación como la JAES (Journal of the Audio Engineering Society) o la ASA (Acoustical Society of America), además, del IEEE ( Institute of Electrical and Electronics Engineers) o la “Web of knowledge” entre otras. Además de realizar la búsqueda en estas fuentes, se ha optado por vías de información más comunes como Google Académico o el portal de acceso “Ingenio” a los todos los recursos electrónicos contenidos en la base de datos de la universidad. El estudio genera una ampliación en el conocimiento de la labor práctica de las HRTF. La mayoría de los estudios enfocan sus esfuerzos en mejorar la percepción del evento sonoro mediante su simulación en la escucha estéreo o multicanal. A partir de las HRTF, esto es posible mediante el análisis y el cálculo de datos como pueden ser las regresiones, siendo éstas muy útiles en la predicción de una medida basándose en la información de la actual. Otro campo de especial interés es el de la generación de sonido 3D. Mediante la base de datos HRTF es posible la simulación de una señal biaural. Se han diseñado algoritmos que son implementados en dispositivos DSP, de tal manera que por medio de retardos interaurales y de diferencias espectrales es posible llegar a un resultado óptimo de sonido envolvente, sin olvidar la importancia de los efectos de reverberación para conseguir un efecto creíble de sonido envolvente. Debido a la complejidad computacional que esto requiere, gran parte de los estudios coinciden en desarrollar sistemas más eficientes, llegando a objetivos tales como la generación de sonido 3D en tiempo real. ABSTRACT. This project involves the creation of a Graphic User Interface (GUI) in the Matlab environment which creates a graphic representation of the HRTF (Head-Related Transfer Function) database. The head transfer function is a very useful tool in the study of the capacity of human beings to perceive their sound environment, as well as their ability to localise sound sources in the area surrounding them. The binaural HRTF (terminology which refers to the HRTF group of the left and right ear) in itself possesses information of special interest seeing that the differences between the HRTF of each ear admits the information that our system of hearing uses in the perception of each sound field. For this reason, the functionality of the graphic interface created presents great benefits within the study of this field. The interaural differences are characterised in space and in time, varying depending on the frequency. By means of Fourier's transformed inverse of the HRTF signal, the response to the head impulse is obtained, in other words, the HRIR (Head-Related Impulse Response). This, as well as having a great use in the creation of software or surround sound generating devices, is used to obtain ITD differences (Interaural Time Difference) and ILD (Interaural Time Difference), commonly named “spatial localisation parameters”. The HRTF database contains the binaural information of different points of sound source location, forming a network of spherical coordinates which surround the subject's head. This network, according to the measures carried out in the anechoic chamber at the EUITT (School of Telecommunications Engineering) gives a precision in elevation of 10º and in azimuth of 5º. The receivers are two microphones placed on the acoustic mannequin called HATS (Hats and Torso Simulator) Brüel&Kjaer model 4100D. This has the physical characteristics which affect the perception of the surroundings which are the forms of the auricle (pinna), the head, neck and human torso. It will be necessary to make interpolation calculations for all those points which are not contained the HRTF database. This process is extremely important not only to strengthen the database's capacity but also for its usefulness in making comparisons with other databases that exist in the study of this field. The graphic user interface is conceived for a simple, clear and predictable use which is also interactive. Since the first outline of the program, its philosophy has been clear, based on the needs of a user who requires a practical tool with an intuitive use. Its design with only one window unites not only the components which obtain data but also those which make the graphic representation of the HRTFs possible, the hrir and the ITD and ILD spatial location parameters. The user will be able to alternate the graphic representations at the same time as entering the point coordinates that they wish to display, defined by phi (elevation) and theta (azimuth). The facet of the interface is what provides the great ease of access and reading of the information displayed on it. In addition, the user can enter values included in the database or values which are intermediate to these. It is, likewise, indicated to the interface the need to carry out the interpolation of these values. The interpolation method is the deliberation of the inverse distance between points. Depending on the values entered by the user, an interpolation of two or four points will be carried out, with these being adjacent to the entered value, whether that is phi or theta. To add versatility to the graphic user interface, the option of generating output files in the form of an image of the graphics displayed has been added. This is so that the user may extract the information that interests them for any phi and theta value. This final project is completed with a research and comparative study essay on the function and application of HRTF databases within the scientific and research framework. It has been possible to collate related information by means of scientific research magazines such as the JAES (Journal of the Audio Engineering Society), the ASA (Acoustical Society of America) as well as the IEEE (Institute of Electrical and Electronics Engineers) and the “Web of knowledge” amongst others. In addition to carrying out research with these sources, I also opted to use more common sources of information such as Academic Google and the “Ingenio” point of entry to all the electronic resources contained on the university databases. The study generates an expansion in the knowledge of the practical work of the HRTF. The majority of studies focus their efforts on improving the perception of the sound event by means of its simulation in stereo or multichannel listening. With the HRTFs, this is possible by means of analysis and calculation of data as can be the regressions. These are very useful in the prediction of a measure being based on the current information. Another field of special interest is that of the generation of 3D sound. Through HRTF databases it is possible to simulate the binaural signal. Algorithms have been designed which are implemented in DSP devices, in such a way that by means of interaural delays and wavelength differences it is possible to achieve an excellent result of surround sound, without forgetting the importance of the effects of reverberation to achieve a believable effect of surround sound. Due to the computational complexity that this requires, a great many studies agree on the development of more efficient systems which achieve objectives such as the generation of 3D sound in real time.

Application of a Bayesian/Generalised Least-Squares method to generate correlations between independent neutron fission yield data

Fission product yields are fundamental parameters for several nuclear engineering calculations and in particular for burn-up/activation problems. The impact of their uncertainties was widely studied in the past and valuations were released, although still incomplete. Recently, the nuclear community expressed the need for full fission yield covariance matrices to produce inventory calculation results that take into account the complete uncertainty data. In this work, we studied and applied a Bayesian/generalised least-squares method for covariance generation, and compared the generated uncertainties to the original data stored in the JEFF-3.1.2 library. Then, we focused on the effect of fission yield covariance information on fission pulse decay heat results for thermal fission of 235U. Calculations were carried out using different codes (ACAB and ALEPH-2) after introducing the new covariance values. Results were compared with those obtained with the uncertainty data currently provided by the library. The uncertainty quantification was performed with the Monte Carlo sampling technique. Indeed, correlations between fission yields strongly affect the statistics of decay heat. Introduction Nowadays, any engineering calculation performed in the nuclear field should be accompanied by an uncertainty analysis. In such an analysis, different sources of uncertainties are taken into account. Works such as those performed under the UAM project (Ivanov, et al., 2013) treat nuclear data as a source of uncertainty, in particular cross-section data for which uncertainties given in the form of covariance matrices are already provided in the major nuclear data libraries. Meanwhile, fission yield uncertainties were often neglected or treated shallowly, because their effects were considered of second order compared to cross-sections (Garcia-Herranz, et al., 2010). However, the Working Party on International Nuclear Data Evaluation Co-operation (WPEC)

Robust control of underactuated wheeled mobile manipulators using GPI disturbance observers

This article describes the design of a linear observer–linear controller-based robust output feedback scheme for output reference trajectory tracking tasks in the case of nonlinear, multivariable, nonholonomic underactuated mobile manipulators. The proposed linear feedback scheme is based on the use of a classical linear feedback controller and suitably extended, high-gain, linear Generalized Proportional Integral (GPI) observers, thus aiding the linear feedback controllers to provide an accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and perturbation inputs. This information is used in the proposed feedback controller in (a) approximate, yet close, cancelations, as lumped unstructured time-varying terms, of the influence of the highly coupled nonlinearities, and (b) the devising of proper linear output feedback control laws based on the approximate estimates of the string of phase variables associated with the flat outputs simultaneously provided by the disturbance observers. Simulations reveal the effectiveness of the proposed approach.

Influence of Strouhal number on pulsating methane–air coflow jet diffusion flames

Four periodically time-varying methane–air laminar coflow jet diffusion flames, each forced by pulsating the fuel jet's exit velocity Uj sinusoidally with a different modulation frequency wj and with a 50% amplitude variation, have been computed. Combustion of methane has been modeled by using a chemical mechanism with 15 species and 42 reactions, and the solution of the unsteady Navier–Stokes equations has been obtained numerically by using a modified vorticity-velocity formulation in the limit of low Mach number. The effect of wj on temperature and chemistry has been studied in detail. Three different regimes are found depending on the flame's Strouhal number S=awj/Uj, with a denoting the fuel jet radius. For small Strouhal number (S=0.1), the modulation introduces a perturbation that travels very far downstream, and certain variables oscillate at the frequency imposed by the fuel jet modulation. As the Strouhal number grows, the nondimensional frequency approaches the natural frequency of oscillation of the flickering flame (S≃0.2). A coupling with the pulsation frequency enhances the effect of the imposed modulation and a vigorous pinch-off is observed for S=0.25 and S=0.5. Larger values of S confine the oscillation to the jet's near-exit region, and the effects of the pulsation are reduced to small wiggles in the temperature and concentration values. Temperature and species mass fractions change appreciably near the jet centerline, where variations of over 2% for the temperature and 15% and 40% for the CO and OH mass fractions, respectively, are found. Transverse to the jet movement, however, the variations almost disappear at radial distances on the order of the fuel jet radius, indicating a fast damping of the oscillation in the spanwise direction.

Fully adaptive gaussian mixture metropolis-hastings algorithm

Markov Chain Monte Carlo methods are widely used in signal processing and communications for statistical inference and stochastic optimization. In this work, we introduce an efficient adaptive Metropolis-Hastings algorithm to draw samples from generic multimodal and multidimensional target distributions. The proposal density is a mixture of Gaussian densities with all parameters (weights, mean vectors and covariance matrices) updated using all the previously generated samples applying simple recursive rules. Numerical results for the one and two-dimensional cases are provided.