Logarithmical hopping encoding: a low computational complexity algorithm for image compression

LHE (logarithmical hopping encoding) is a computationally efficient image compression algorithm that exploits the Weber–Fechner law to encode the error between colour component predictions and the actual value of such components. More concretely, for each pixel, luminance and chrominance predictions are calculated as a function of the surrounding pixels and then the error between the predictions and the actual values are logarithmically quantised. The main advantage of LHE is that although it is capable of achieving a low-bit rate encoding with high quality results in terms of peak signal-to-noise ratio (PSNR) and image quality metrics with full-reference (FSIM) and non-reference (blind/referenceless image spatial quality evaluator), its time complexity is O( n) and its memory complexity is O(1). Furthermore, an enhanced version of the algorithm is proposed, where the output codes provided by the logarithmical quantiser are used in a pre-processing stage to estimate the perceptual relevance of the image blocks. This allows the algorithm to downsample the blocks with low perceptual relevance, thus improving the compression rate. The performance of LHE is especially remarkable when the bit per pixel rate is low, showing much better quality, in terms of PSNR and FSIM, than JPEG and slightly lower quality than JPEG-2000 but being more computationally efficient.

Numerical issues in Lagrangian tracking and topological evolution of fluid particles in wallbounded turbulent flows

The determination of the local Lagrangian evolution of the flow topology in wall-bounded turbulence, and of the Lagrangian evolution associated with entrainment across the turbulent / non-turbulent interface into a turbulent boundary layer, require accurate tracking of a fluid particle and its local velocity gradients. This paper addresses the implementation of fluid-particle tracking in both a turbulent boundary layer direct numerical simulation and in a fully developed channel flow simulation. Determination of the sub-grid particle velocity is performed using both cubic B-spline, four-point Hermite spline and higher-order Hermite spline interpolation. Both wall-bounded flows show similar oscillations in the Lagrangian tracers of both velocity and velocity gradients, corresponding to the movement of particles across the boundaries of computational cells. While these oscillation in the particle velocity are relatively small and have negligible effect on the particle trajectories for time-steps of the order of CFL = 0.1, they appear to be the cause of significant oscillations in the evolution of the invariants of the velocity gradient tensor.

Entrainment Effects in Turbulent Boundary Layers

Esta tesis estudia el comportamiento de la región exterior de una capa límite turbulenta sin gradientes de presiones. Se ponen a prueba dos teorías relativamente bien establecidas. La teoría de semejanza para la pared supone que en el caso de haber una pared rugosa, el fluido sólo percibe el cambio en la fricción superficial que causa, y otros efectos secundarios quedarán confinados a una zona pegada a la pared. El consenso actual es que dicha teoría es aproximadamente cierta. En el extremo exterior de la capa límite existe una región producida por la interacción entre las estructuras turbulentas y el flujo irrotacional de la corriente libre llamada interfaz turbulenta/no turbulenta. La mayoría de los resultados al respecto sugieren la presencia de fuerzas de cortadura ligeramente más intensa, lo que la hace distinta al resto del flujo turbulento. Las propiedades de esa región probablemente cambien si la velocidad de crecimiento de la capa límite aumenta, algo que puede conseguirse aumentando la fricción en la pared. La rugosidad y la ingestión de masa están entonces relacionadas, y el comportamiento local de la interfaz turbulenta/no turbulenta puede explicar el motivo por el que las capas límite sobre paredes rugosas no se comportan como en el caso de tener paredes lisas precisamente en la zona exterior. Para estudiar las capas límite a números de Reynolds lo suficientemente elevados, se ha desarrollado un nuevo código de alta resolución para la simulación numérica directa de capas límite turbulentas sin gradiente de presión. Dicho código es capaz de simular capas límite en un intervalo de números de Reynolds entre ReT = 100 — 2000 manteniendo una buena escalabilidad hasta los dos millones de hilos en superordenadores de tipo Blue Gene/Q. Se ha guardado especial atención a la generación de condiciones de contorno a la entrada correctas. Los resultados obtenidos están en concordancia con los resultados previos, tanto en el caso de simulaciones como de experimentos. La interfaz turbulenta/no turbulenta de una capa límite se ha analizado usando un valor umbral del módulo de la vorticidad. Dicho umbral se considera un parámetro para analizar cada superficie obtenida de un contorno del módulo de la vorticidad. Se han encontrado dos regímenes distintos en función del umbral escogido con propiedades opuestas, separados por una transición topológica gradual. Las características geométricas de la zona escalan con o99 cuando u^/isdgg es la unidad de vorticidad. Las propiedades del íluido relativas a la posición del contorno de vorticidad han sido analizados para una serie de umbrales utilizando el campo de distancias esféricas, que puede obtenerse con independencia de la complejidad de la superficie de referencia. Las propiedades del fluido a una distancia dada del inerfaz también dependen del umbral de vorticidad, pero tienen características parecidas con independencia del número de Reynolds. La interacción entre la turbulencia y el flujo no turbulento se restringe a una zona muy fina con un espesor del orden de la escala de Kolmogorov local. Hacia el interior del flujo turbulento las propiedades son indistinguibles del resto de la capa límite. Se ha simulado una capa límite sin gradiente de presiones con una fuerza volumétrica cerca de la pared. La el forzado ha sido diseñado para aumentar la fricción en la pared sin introducir ningún efecto geométrico obvio. La simulación consta de dos dominios, un primer dominio más pequeño y a baja resolución que se encarga de generar condiciones de contorno correctas, y un segundo dominio mayor y a alta resolución donde se aplica el forzado. El estudio de los perfiles y los coeficientes de autocorrelación sugieren que los dos casos, el liso y el forzado, no colapsan más allá de la capa logarítmica por la complejidad geométrica de la zona intermitente, y por el hecho que la distancia a la pared no es una longitud característica. Los efectos causados por la geometría de la zona intermitente pueden evitarse utilizando el interfaz como referencia, y la distancia esférica para el análisis de sus propiedades. Las propiedades condicionadas del flujo escalan con 5QQ y u/uT, las dos únicas escalas contenidas en el modelo de semejanza de pared de Townsend, consistente con estos resultados. ABSTRACT This thesis studies the characteristics of the outer region of zero-pressure-gradient turbulent boundary layers at moderate Reynolds numbers. Two relatively established theories are put to test. The wall similarity theory states that with the presence of roughness, turbulent motion is mostly affected by the additional drag caused by the roughness, and that other secondary effects are restricted to a region very close to the wall. The consensus is that this theory is valid, but only as a first approximation. At the edge of the boundary layer there is a thin layer caused by the interaction between the turbulent eddies and the irroational fluid of the free stream, called turbulent/non-turbulent interface. The bulk of results about this layer suggest the presence of some localized shear, with properties that make it distinguishable from the rest of the turbulent flow. The properties of the interface are likely to change if the rate of spread of the turbulent boundary layer is amplified, an effect that is usually achieved by increasing the drag. Roughness and entrainment are therefore linked, and the local features of the turbulent/non-turbulent interface may explain the reason why rough-wall boundary layers deviate from the wall similarity theory precisely far from the wall. To study boundary layers at a higher Reynolds number, a new high-resolution code for the direct numerical simulation of a zero pressure gradient turbulent boundary layers over a flat plate has been developed. This code is able to simulate a wide range of Reynolds numbers from ReT =100 to 2000 while showing a linear weak scaling up to around two million threads in the BG/Q architecture. Special attention has been paid to the generation of proper inflow boundary conditions. The results are in good agreement with existing numerical and experimental data sets. The turbulent/non-turbulent interface of a boundary layer is analyzed by thresholding the vorticity magnitude field. The value of the threshold is considered a parameter in the analysis of the surfaces obtained from isocontours of the vorticity magnitude. Two different regimes for the surface can be distinguished depending on the threshold, with a gradual topological transition across which its geometrical properties change significantly. The width of the transition scales well with oQg when u^/udgg is used as a unit of vorticity. The properties of the flow relative to the position of the vorticity magnitude isocontour are analyzed within the same range of thresholds, using the ball distance field, which can be obtained regardless of the size of the domain and complexity of the interface. The properties of the flow at a given distance to the interface also depend on the threshold, but they are similar regardless of the Reynolds number. The interaction between the turbulent and the non-turbulent flow occurs in a thin layer with a thickness that scales with the Kolmogorov length. Deeper into the turbulent side, the properties are undistinguishable from the rest of the turbulent flow. A zero-pressure-gradient turbulent boundary layer with a volumetric near-wall forcing has been simulated. The forcing has been designed to increase the wall friction without introducing any obvious geometrical effect. The actual simulation is split in two domains, a smaller one in charge of the generation of correct inflow boundary conditions, and a second and larger one where the forcing is applied. The study of the one-point and twopoint statistics suggest that the forced and the smooth cases do not collapse beyond the logarithmic layer may be caused by the geometrical complexity of the intermittent region, and by the fact that the scaling with the wall-normal coordinate is no longer present. The geometrical effects can be avoided using the turbulent/non-turbulent interface as a reference frame, and the minimum distance respect to it. The conditional analysis of the vorticity field with the alternative reference frame recovers the scaling with 5QQ and v¡uT already present in the logarithmic layer, the only two length-scales allowed if Townsend’s wall similarity hypothesis is valid.

Análisis de la actividad neuronal y cerebral mediante técnicas de redes complejas

El cerebro humano es probablemente uno de los sistemas más complejos a los que nos enfrentamos en la actualidad, si bien es también uno de los más fascinantes. Sin embargo, la compresión de cómo el cerebro organiza su actividad para llevar a cabo tareas complejas es un problema plagado de restos y obstáculos. En sus inicios la neuroimagen y la electrofisiología tenían como objetivo la identificación de regiones asociadas a activaciones relacionadas con tareas especificas, o con patrones locales que variaban en el tiempo dada cierta actividad. Sin embargo, actualmente existe un consenso acerca de que la actividad cerebral tiene un carácter temporal multiescala y espacialmente extendido, lo que lleva a considerar el cerebro como una gran red de áreas cerebrales coordinadas, cuyas conexiones funcionales son continuamente creadas y destruidas. Hasta hace poco, el énfasis de los estudios de la actividad cerebral funcional se han centrado en la identidad de los nodos particulares que forman estas redes, y en la caracterización de métricas de conectividad entre ellos: la hipótesis subyacente es que cada nodo, que es una representación mas bien aproximada de una región cerebral dada, ofrece a una única contribución al total de la red. Por tanto, la neuroimagen funcional integra los dos ingredientes básicos de la neuropsicología: la localización de la función cognitiva en módulos cerebrales especializados y el rol de las fibras de conexión en la integración de dichos módulos. Sin embargo, recientemente, la estructura y la función cerebral han empezado a ser investigadas mediante la Ciencia de la Redes, una interpretación mecánico-estadística de una antigua rama de las matemáticas: La teoría de grafos. La Ciencia de las Redes permite dotar a las redes funcionales de una gran cantidad de propiedades cuantitativas (robustez, centralidad, eficiencia, ...), y así enriquecer el conjunto de elementos que describen objetivamente la estructura y la función cerebral a disposición de los neurocientíficos. La conexión entre la Ciencia de las Redes y la Neurociencia ha aportado nuevos puntos de vista en la comprensión de la intrincada anatomía del cerebro, y de cómo las patrones de actividad cerebral se pueden sincronizar para generar las denominadas redes funcionales cerebrales, el principal objeto de estudio de esta Tesis Doctoral. Dentro de este contexto, la complejidad emerge como el puente entre las propiedades topológicas y dinámicas de los sistemas biológicos y, específicamente, en la relación entre la organización y la dinámica de las redes funcionales cerebrales. Esta Tesis Doctoral es, en términos generales, un estudio de cómo la actividad cerebral puede ser entendida como el resultado de una red de un sistema dinámico íntimamente relacionado con los procesos que ocurren en el cerebro. Con este fin, he realizado cinco estudios que tienen en cuenta ambos aspectos de dichas redes funcionales: el topológico y el dinámico. De esta manera, la Tesis está dividida en tres grandes partes: Introducción, Resultados y Discusión. En la primera parte, que comprende los Capítulos 1, 2 y 3, se hace un resumen de los conceptos más importantes de la Ciencia de las Redes relacionados al análisis de imágenes cerebrales. Concretamente, el Capitulo 1 está dedicado a introducir al lector en el mundo de la complejidad, en especial, a la complejidad topológica y dinámica de sistemas acoplados en red. El Capítulo 2 tiene como objetivo desarrollar los fundamentos biológicos, estructurales y funcionales del cerebro, cuando éste es interpretado como una red compleja. En el Capítulo 3, se resumen los objetivos esenciales y tareas que serán desarrolladas a lo largo de la segunda parte de la Tesis. La segunda parte es el núcleo de la Tesis, ya que contiene los resultados obtenidos a lo largo de los últimos cuatro años. Esta parte está dividida en cinco Capítulos, que contienen una versión detallada de las publicaciones llevadas a cabo durante esta Tesis. El Capítulo 4 está relacionado con la topología de las redes funcionales y, específicamente, con la detección y cuantificación de los nodos mas importantes: aquellos denominados “hubs” de la red. En el Capítulo 5 se muestra como las redes funcionales cerebrales pueden ser vistas no como una única red, sino más bien como una red-de-redes donde sus componentes tienen que coexistir en una situación de balance funcional. De esta forma, se investiga cómo los hemisferios cerebrales compiten para adquirir centralidad en la red-de-redes, y cómo esta interacción se mantiene (o no) cuando se introducen fallos deliberadamente en la red funcional. El Capítulo 6 va un paso mas allá al considerar las redes funcionales como sistemas vivos. En este Capítulo se muestra cómo al analizar la evolución de la topología de las redes, en vez de tratarlas como si estas fueran un sistema estático, podemos caracterizar mejor su estructura. Este hecho es especialmente relevante cuando se quiere tratar de encontrar diferencias entre grupos que desempeñan una tarea de memoria, en la que las redes funcionales tienen fuertes fluctuaciones. En el Capítulo 7 defino cómo crear redes parenclíticas a partir de bases de datos de actividad cerebral. Este nuevo tipo de redes, recientemente introducido para estudiar las anormalidades entre grupos de control y grupos anómalos, no ha sido implementado nunca en datos cerebrales y, en este Capítulo explico cómo hacerlo cuando se quiere evaluar la consistencia de la dinámica cerebral. Para concluir esta parte de la Tesis, el Capítulo 8 se centra en la relación entre las propiedades topológicas de los nodos dentro de una red y sus características dinámicas. Como mostraré más adelante, existe una relación entre ellas que revela que la posición de un nodo dentro una red está íntimamente correlacionada con sus propiedades dinámicas. Finalmente, la última parte de esta Tesis Doctoral está compuesta únicamente por el Capítulo 9, el cual contiene las conclusiones y perspectivas futuras que pueden surgir de los trabajos expuestos. En vista de todo lo anterior, espero que esta Tesis aporte una perspectiva complementaria sobre uno de los más extraordinarios sistemas complejos frente a los que nos encontramos: El cerebro humano. ABSTRACT The human brain is probably one of the most complex systems we are facing, thus being a timely and fascinating object of study. Characterizing how the brain organizes its activity to carry out complex tasks is highly non-trivial. While early neuroimaging and electrophysiological studies typically aimed at identifying patches of task-specific activations or local time-varying patterns of activity, there has now been consensus that task-related brain activity has a temporally multiscale, spatially extended character, as networks of coordinated brain areas are continuously formed and destroyed. Up until recently, though, the emphasis of functional brain activity studies has been on the identity of the particular nodes forming these networks, and on the characterization of connectivity metrics between them, the underlying covert hypothesis being that each node, constituting a coarse-grained representation of a given brain region, provides a unique contribution to the whole. Thus, functional neuroimaging initially integrated the two basic ingredients of early neuropsychology: localization of cognitive function into specialized brain modules and the role of connection fibres in the integration of various modules. Lately, brain structure and function have started being investigated using Network Science, a statistical mechanics understanding of an old branch of pure mathematics: graph theory. Network Science allows endowing networks with a great number of quantitative properties, thus vastly enriching the set of objective descriptors of brain structure and function at neuroscientists’ disposal. The link between Network Science and Neuroscience has shed light about how the entangled anatomy of the brain is, and how cortical activations may synchronize to generate the so-called functional brain networks, the principal object under study along this PhD Thesis. Within this context, complexity appears to be the bridge between the topological and dynamical properties of biological systems and, more specifically, the interplay between the organization and dynamics of functional brain networks. This PhD Thesis is, in general terms, a study of how cortical activations can be understood as the output of a network of dynamical systems that are intimately related with the processes occurring in the brain. In order to do that, I performed five studies that encompass both the topological and the dynamical aspects of such functional brain networks. In this way, the Thesis is divided into three major parts: Introduction, Results and Discussion. In the first part, comprising Chapters 1, 2 and 3, I make an overview of the main concepts of Network Science related to the analysis of brain imaging. More specifically, Chapter 1 is devoted to introducing the reader to the world of complexity, specially to the topological and dynamical complexity of networked systems. Chapter 2 aims to develop the biological, topological and functional fundamentals of the brain when it is seen as a complex network. Next, Chapter 3 summarizes the main objectives and tasks that will be developed along the forthcoming Chapters. The second part of the Thesis is, in turn, its core, since it contains the results obtained along these last four years. This part is divided into five Chapters, containing a detailed version of the publications carried out during the Thesis. Chapter 4 is related to the topology of functional networks and, more specifically, to the detection and quantification of the leading nodes of the network: the hubs. In Chapter 5 I will show that functional brain networks can be viewed not as a single network, but as a network-of-networks, where its components have to co-exist in a trade-off situation. In this way, I investigate how the brain hemispheres compete for acquiring the centrality of the network-of-networks and how this interplay is maintained (or not) when failures are introduced in the functional network. Chapter 6 goes one step beyond by considering functional networks as living systems. In this Chapter I show how analyzing the evolution of the network topology instead of treating it as a static system allows to better characterize functional networks. This fact is especially relevant when trying to find differences between groups performing certain memory tasks, where functional networks have strong fluctuations. In Chapter 7 I define how to create parenclitic networks from brain imaging datasets. This new kind of networks, recently introduced to study abnormalities between control and anomalous groups, have not been implemented with brain datasets and I explain in this Chapter how to do it when evaluating the consistency of brain dynamics. To conclude with this part of the Thesis, Chapter 8 is devoted to the interplay between the topological properties of the nodes within a network and their dynamical features. As I will show, there is an interplay between them which reveals that the position of a node in a network is intimately related with its dynamical properties. Finally, the last part of this PhD Thesis is composed only by Chapter 9, which contains the conclusions and future perspectives that may arise from the exposed results. In view of all, I hope that reading this Thesis will give a complementary perspective of one of the most extraordinary complex systems: The human brain.

Analysing the complexity of the model-based decision making processes within the industrial management context

PURPOSE The decision-making process plays a key role in organizations. Every decision-making process produces a final choice that may or may not prompt action. Recurrently, decision makers find themselves in the dichotomous question of following a traditional sequence decision-making process where the output of a decision is used as the input of the next stage of the decision, or following a joint decision-making approach where several decisions are taken simultaneously. The implication of the decision-making process will impact different players of the organization. The choice of the decision- making approach becomes difficult to find, even with the current literature and practitioners’ knowledge. The pursuit of better ways for making decisions has been a common goal for academics and practitioners. Management scientists use different techniques and approaches to improve different types of decisions. The purpose of this decision is to use the available resources as well as possible (data and techniques) to achieve the objectives of the organization. The developing and applying of models and concepts may be helpful to solve managerial problems faced every day in different companies. As a result of this research different decision models are presented to contribute to the body of knowledge of management science. The first models are focused on the manufacturing industry and the second part of the models on the health care industry. Despite these models being case specific, they serve the purpose of exemplifying that different approaches to the problems and could provide interesting results. Unfortunately, there is no universal recipe that could be applied to all the problems. Furthermore, the same model could deliver good results with certain data and bad results for other data. A framework to analyse the data before selecting the model to be used is presented and tested in the models developed to exemplify the ideas. METHODOLOGY As the first step of the research a systematic literature review on the joint decision is presented, as are the different opinions and suggestions of different scholars. For the next stage of the thesis, the decision-making process of more than 50 companies was analysed in companies from different sectors in the production planning area at the Job Shop level. The data was obtained using surveys and face-to-face interviews. The following part of the research into the decision-making process was held in two application fields that are highly relevant for our society; manufacturing and health care. The first step was to study the interactions and develop a mathematical model for the replenishment of the car assembly where the problem of “Vehicle routing problem and Inventory” were combined. The next step was to add the scheduling or car production (car sequencing) decision and use some metaheuristics such as ant colony and genetic algorithms to measure if the behaviour is kept up with different case size problems. A similar approach is presented in a production of semiconductors and aviation parts, where a hoist has to change from one station to another to deal with the work, and a jobs schedule has to be done. However, for this problem simulation was used for experimentation. In parallel, the scheduling of operating rooms was studied. Surgeries were allocated to surgeons and the scheduling of operating rooms was analysed. The first part of the research was done in a Teaching hospital, and for the second part the interaction of uncertainty was added. Once the previous problem had been analysed a general framework to characterize the instance was built. In the final chapter a general conclusion is presented. FINDINGS AND PRACTICAL IMPLICATIONS The first part of the contributions is an update of the decision-making literature review. Also an analysis of the possible savings resulting from a change in the decision process is made. Then, the results of the survey, which present a lack of consistency between what the managers believe and the reality of the integration of their decisions. In the next stage of the thesis, a contribution to the body of knowledge of the operation research, with the joint solution of the replenishment, sequencing and inventory problem in the assembly line is made, together with a parallel work with the operating rooms scheduling where different solutions approaches are presented. In addition to the contribution of the solving methods, with the use of different techniques, the main contribution is the framework that is proposed to pre-evaluate the problem before thinking of the techniques to solve it. However, there is no straightforward answer as to whether it is better to have joint or sequential solutions. Following the proposed framework with the evaluation of factors such as the flexibility of the answer, the number of actors, and the tightness of the data, give us important hints as to the most suitable direction to take to tackle the problem. RESEARCH LIMITATIONS AND AVENUES FOR FUTURE RESEARCH In the first part of the work it was really complicated to calculate the possible savings of different projects, since in many papers these quantities are not reported or the impact is based on non-quantifiable benefits. The other issue is the confidentiality of many projects where the data cannot be presented. For the car assembly line problem more computational power would allow us to solve bigger instances. For the operation research problem there was a lack of historical data to perform a parallel analysis in the teaching hospital. In order to keep testing the decision framework it is necessary to keep applying more case studies in order to generalize the results and make them more evident and less ambiguous. The health care field offers great opportunities since despite the recent awareness of the need to improve the decision-making process there are many opportunities to improve. Another big difference with the automotive industry is that the last improvements are not spread among all the actors. Therefore, in the future this research will focus more on the collaboration between academia and the health care sector.

Intermittent pluri-sink model and the emergence of complex heterogeneity patterns: a simple paradigm for explaining complexity in soil chemical distributions

The spatial complexity of the distribution of organic matter, chemicals, nutrients, pollutants has been demonstrated to have multifractal nature (Kravchenco et al. [1]). This fact supports the possibility of existence of some emergent heterogeneity structure built under the evolution of the system. The aim of this note is providing a consistent explanation to the mentioned results via an extremely simple model.