Bicriteria data compression

The advent of massive datasets (and the consequent design of high-performing distributed storage systems) have reignited the interest of the scientific and engineering community towards the design of lossless data compressors which achieve effective compression ratio and very efficient decompression speed. Lempel-Ziv's LZ77 algorithm is the de facto choice in this scenario because of its decompression speed and its flexibility in trading decompression speed versus compressed-space efficiency. Each of the existing implementations offers a trade-off between space occupancy and decompression speed, so software engineers have to content themselves by picking the one which comes closer to the requirements of the application in their hands. Starting from these premises, and for the first time in the literature, we address in this paper the problem of trading optimally, and in a principled way, the consumption of these two resources by introducing the Bicriteria LZ77-Parsing problem, which formalizes in a principled way what data-compressors have traditionally approached by means of heuristics. The goal is to determine an LZ77 parsing which minimizes the space occupancy in bits of the compressed file, provided that the decompression time is bounded by a fixed amount (or vice-versa). This way, the software engineer can set its space (or time) requirements and then derive the LZ77 parsing which optimizes the decompression speed (or the space occupancy, respectively). We solve this problem efficiently in O(n log^2 n) time and optimal linear space within a small, additive approximation, by proving and deploying some specific structural properties of the weighted graph derived from the possible LZ77-parsings of the input file. The preliminary set of experiments shows that our novel proposal dominates all the highly engineered competitors, hence offering a win-win situation in theory&practice

A NEUROMORPHIC APPROACH TO TACTILE PERCEPTION

Ph.DDOCTOR OF PHILOSOPH

Spatially Resolved Terahertz Propagation

The focus of the research was to investigate the spatial behavior of near single cycle freely propagating terahertz radiation. The terahertz pulses were generated through optoelectronic means and the experimental systems based on established terahertz time domain spectroscopy techniques. By raster scanning the terahertz beam orthogonally to the optic axis with a fiber-coupled reduced aperture receiver, the electric field of the beam could be directly measured. This system was used to investigate the propagation of a broad bandwidth pulse through an optical tunneling barrier comprised of a matched pair of high resistivity silicon prisms cut at an incident angle above critical angle. Spectral analysis through numeric Fourier transforms was used to interpret the behavior and test claims of superluminal (faster than the speed of light) propagation through an optical tunneling barrier.Findings and Conclusions: Superluminal propagation does not occur in the case of frustrated total internal reflection. Linear dispersion theory, experimental evidence of a lateral beam shift (the Goos-Hanchen effect), and numeric simulation support the conclusion that propagation across an optical tunneling barrier is causal. Exposed receiver dipole antennas provide sufficient resolution to observe fine features in the propagating beam profile. The starting beam waist of the incident terahertz beam strongly influences the pulse profile after transiting an optical tunneling barrier. Standard silicon collimating lenses give rise to frequency dependent beam profiles due to interference caused by a complex temporal pulse structure. The complex pulse structure results from lens aberrations, antenna radiation patterns, and surface wave contributions. Aspheric lenses minimize the observed pulse structure due to spherical aberration and are a better choice of lens for measuring incident plane wave terahertz radiation.School of Electrical & Computer Engineerin

Information Bottleneck

The celebrated information bottleneck (IB) principle of Tishby et al. has recently enjoyed renewed attention due to its application in the area of deep learning. This collection investigates the IB principle in this new context. The individual chapters in this collection: • provide novel insights into the functional properties of the IB; • discuss the IB principle (and its derivates) as an objective for training multi-layer machine learning structures such as neural networks and decision trees; and • offer a new perspective on neural network learning via the lens of the IB framework. Our collection thus contributes to a better understanding of the IB principle specifically for deep learning and, more generally, of information–theoretic cost functions in machine learning. This paves the way toward explainable artificial intelligence

Wearable and Nearable Biosensors and Systems for Healthcare

Biosensors and systems in the form of wearables and “nearables” (i.e., everyday sensorized objects with transmitting capabilities such as smartphones) are rapidly evolving for use in healthcare. Unlike conventional approaches, these technologies can enable seamless or on-demand physiological monitoring, anytime and anywhere. Such monitoring can help transform healthcare from the current reactive, one-size-fits-all, hospital-centered approach into a future proactive, personalized, decentralized structure. Wearable and nearable biosensors and systems have been made possible through integrated innovations in sensor design, electronics, data transmission, power management, and signal processing. Although much progress has been made in this field, many open challenges for the scientific community remain, especially for those applications requiring high accuracy. This book contains the 12 papers that constituted a recent Special Issue of Sensors sharing the same title. The aim of the initiative was to provide a collection of state-of-the-art investigations on wearables and nearables, in order to stimulate technological advances and the use of the technology to benefit healthcare. The topics covered by the book offer both depth and breadth pertaining to wearable and nearable technology. They include new biosensors and data transmission techniques, studies on accelerometers, signal processing, and cardiovascular monitoring, clinical applications, and validation of commercial devices

Encodage d'un signal audio dans un électroencéphalogramme

Les interfaces cerveau-machine visent à établir un lien de communication entre le cerveau et un système externe à ce dernier. Les électroencéphalogrammes (EEG), dans ce contexte, ont l’avantage d’être non invasifs. Par contre, l’information sensorielle qui se retrouve dans un signal EEG est beaucoup moins ciblée que dans un signal neuronal acquis par une méthode invasive. De plus, étant donné que le cortex auditif est situé dans des repliements du tissu cortical, les neurones qui déchargent, suite à un stimulus auditif, sont parallèles à la surface corticale sur laquelle les EEG sont enregistrés. Par conséquent, l’information auditive qui se retrouve dans le canal EEG situé vis-à-vis du cortex auditif est faible. L’objectif principal de ce projet de recherche consiste donc à étudier la répartition de l’information auditive dans l’ensemble des canaux EEG. Pour ce faire, nous utilisons deux approches. Dans la première, nous tenterons d’estimer l’activité corticale sous-jacente à partir des signaux EEG en utilisant un modèle de couplage bande fréquence. En effet, certaines bandes de fréquences sont des bons prédicteurs des décharges neuronales. Cependant, cette approche n’a pas été validée pour le système auditif, nous confronterons donc l’estimation obtenue à une autre estimation en ayant recours à un modèle spécialisé pour l’encodage du signal de parole faisant appel aux processus ponctuels. Ce modèle prend en compte les dynamiques intrasèques des neurones et également des propriétés spectrotemporelles du stimulus d’entrée. Dans la seconde approche, nous étudierons la possibilité de classifier 3 voyelles (a, i et u) en fonction du nombre de canaux EEG utilisés ainsi que leur répartition sur le cuir chevelu. Nous aurons recours, pour cela, à un réservoir de neurone à décharge récurrent activé en entrée par les données EEG. Les résultats démontrent que l’information auditive se retrouve en fait dans l’ensemble des canaux EEG et qu’elle n’est pas confinée à un nombre restreint d’électrodes. Il est également montré que lorsque l’on utilise les 64 électrodes que comporte l’EEG pour classifier les 3 voyelles, on obtient une classification de l’ordre de 80%, mais aussi qu’un nombre limité de 10 électrodes suffit pour obtenir une classification satisfaisante et, qu’en plus, la position de ces électrodes sur le cuir chevelu est peu importante

Improving water network management by efficient division into supply clusters

El agua es un recurso escaso que, como tal, debe ser gestionado de manera eficiente. Así, uno de los propósitos de dicha gestión debiera ser la reducción de pérdidas de agua y la mejora del funcionamiento del abastecimiento. Para ello, es necesario crear un marco de trabajo basado en un conocimiento profundo de la redes de distribución. En los casos reales, llegar a este conocimiento es una tarea compleja debido a que estos sistemas pueden estar formados por miles de nodos de consumo, interconectados entre sí también por miles de tuberías y sus correspondientes elementos de alimentación. La mayoría de las veces, esas redes no son el producto de un solo proceso de diseño, sino la consecuencia de años de historia que han dado respuesta a demandas de agua continuamente crecientes con el tiempo. La división de la red en lo que denominaremos clusters de abastecimiento, permite la obtención del conocimiento hidráulico adecuado para planificar y operar las tareas de gestión oportunas, que garanticen el abastecimiento al consumidor final. Esta partición divide las redes de distribución en pequeñas sub-redes, que son virtualmente independientes y están alimentadas por un número prefijado de fuentes. Esta tesis propone un marco de trabajo adecuado en el establecimiento de vías eficientes tanto para dividir la red de abastecimiento en sectores, como para desarrollar nuevas actividades de gestión, aprovechando esta estructura dividida. La propuesta de desarrollo de cada una de estas tareas será mediante el uso de métodos kernel y sistemas multi-agente. El spectral clustering y el aprendizaje semi-supervisado se mostrarán como métodos con buen comportamiento en el paradigma de encontrar una red sectorizada que necesite usar el número mínimo de válvulas de corte. No obstante, sus algoritmos se vuelven lentos (a veces infactibles) dividiendo una red de abastecimiento grande.Herrera Fernández, AM. (2011). Improving water network management by efficient division into supply clusters [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11233Palanci

The NCOREL computer program for 3D nonlinear supersonic potential flow computations

An innovative computational technique (NCOREL) was established for the treatment of three dimensional supersonic flows. The method is nonlinear in that it solves the nonconservative finite difference analog of the full potential equation and can predict the formation of supercritical cross flow regions, embedded and bow shocks. The method implicitly computes a conical flow at the apex (R = 0) of a spherical coordinate system and uses a fully implicit marching technique to obtain three dimensional cross flow solutions. This implies that the radial Mach number must remain supersonic. The cross flow solutions are obtained by using type dependent transonic relaxation techniques with the type dependency linked to the character of the cross flow velocity (i.e., subsonic/supersonic). The spherical coordinate system and marching on spherical surfaces is ideally suited to the computation of wing flows at low supersonic Mach numbers due to the elimination of the subsonic axial Mach number problems that exist in other marching codes that utilize Cartesian transverse marching planes