An algorithm for graphical computer results in shells

A Finite Element technique to interpolate general data (function values and its derivatives) has been developped. The technique can be considered as a generalized solution of the classical polynomial interpolation, because the condition for the interpolating function to be a polynomial is replaced by a minimizing condition of a given “smoothing” functional. In this way it is possible to find interpolating functions with a given level of continuity according to the class of finite elements used. Examples have been presented in order to assess the accuracy and efficiency of the procedure.

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.

A Multi Ant Colony Optimization algorithm for a Mixed Car Assembly Line

This paper presents an ant colony optimization algorithm to sequence the mixed assembly lines considering the inventory and the replenishment of components. This is a NP-problem that cannot be solved to optimality by exact methods when the size of the problem growth. Groups of specialized ants are implemented to solve the different parts of the problem. This is intended to differentiate each part of the problem. Different types of pheromone structures are created to identify good car sequences, and good routes for the replenishment of components vehicle. The contribution of this paper is the collaborative approach of the ACO for the mixed assembly line and the replenishment of components and the jointly solution of the problem.

Mapping Dynamics into Graphs. The Visibility Algorithm

Si no tenemos en cuenta posibles procesos subyacentes con significado físico, químico, económico, etc., podemos considerar una serie temporal como un mero conjunto ordenado de valores y jugar con él algún inocente juego matemático como transformar dicho conjunto en otro objeto con la ayuda de una operación matemática para ver qué sucede: qué propiedades del conjunto original se conservan, cuáles se transforman y cómo, qué podemos decir de alguna de las dos representaciones matemáticas del objeto con sólo atender a la otra... Este ejercicio sería de cierto interés matemático por sí solo. Ocurre, además, que las series temporales son un método universal de extraer información de sistemas dinámicos en cualquier campo de la ciencia. Esto hace ganar un inesperado interés práctico al juego matemático anteriormente descrito, ya que abre la posibilidad de analizar las series temporales (vistas ahora como evolución temporal de procesos dinámicos) desde una nueva perspectiva. Hemos para esto de asumir la hipótesis de que la información codificada en la serie original se conserva de algún modo en la transformación (al menos una parte de ella). El interés resulta completo cuando la nueva representación del objeto pertencece a un campo de la matemáticas relativamente maduro, en el cual la información codificada en dicha representación puede ser descodificada y procesada de manera efectiva. ABSTRACT Disregarding any underlying process (and therefore any physical, chemical, economical or whichever meaning of its mere numeric values), we can consider a time series just as an ordered set of values and play the naive mathematical game of turning this set into a different mathematical object with the aids of an abstract mapping, and see what happens: which properties of the original set are conserved, which are transformed and how, what can we say about one of the mathematical representations just by looking at the other... This exercise is of mathematical interest by itself. In addition, it turns out that time series or signals is a universal method of extracting information from dynamical systems in any field of science. Therefore, the preceding mathematical game gains some unexpected practical interest as it opens the possibility of analyzing a time series (i.e. the outcome of a dynamical process) from an alternative angle. Of course, the information stored in the original time series should be somehow conserved in the mapping. The motivation is completed when the new representation belongs to a relatively mature mathematical field, where information encoded in such a representation can be effectively disentangled and processed. This is, in a nutshell, a first motivation to map time series into networks.

Energy-based Fair Queuing: Energy-centric Processor Scheduling Algorithm for Battery-limited Mobile Systems

Los dispositivos móviles modernos disponen cada vez de más funcionalidad debido al rápido avance de las tecnologías de las comunicaciones y computaciones móviles. Sin embargo, la capacidad de la batería no ha experimentado un aumento equivalente. Por ello, la experiencia de usuario en los sistemas móviles modernos se ve muy afectada por la vida de la batería, que es un factor inestable de difícil de control. Para abordar este problema, investigaciones anteriores han propuesto un esquema de gestion del consumo (PM) centrada en la energía y que proporciona una garantía sobre la vida operativa de la batería mediante la gestión de la energía como un recurso de primera clase en el sistema. Como el planificador juega un papel fundamental en la administración del consumo de energía y en la garantía del rendimiento de las aplicaciones, esta tesis explora la optimización de la experiencia de usuario para sistemas móviles con energía limitada desde la perspectiva de un planificador que tiene en cuenta el consumo de energía en un contexto en el que ésta es un recurso de primera clase. En esta tesis se analiza en primer lugar los factores que contribuyen de forma general a la experiencia de usuario en un sistema móvil. Después se determinan los requisitos esenciales que afectan a la experiencia de usuario en la planificación centrada en el consumo de energía, que son el reparto proporcional de la potencia, el cumplimiento de las restricciones temporales, y cuando sea necesario, el compromiso entre la cuota de potencia y las restricciones temporales. Para cumplir con los requisitos, el algoritmo clásico de fair queueing y su modelo de referencia se extienden desde los dominios de las comunicaciones y ancho de banda de CPU hacia el dominio de la energía, y en base a ésto, se propone el algoritmo energy-based fair queueing (EFQ) para proporcionar una planificación basada en la energía. El algoritmo EFQ está diseñado para compartir la potencia consumida entre las tareas mediante su planificación en función de la energía consumida y de la cuota reservada. La cuota de consumo de cada tarea con restricciones temporales está protegida frente a diversos cambios que puedan ocurrir en el sistema. Además, para dar mejor soporte a las tareas en tiempo real y multimedia, se propone un mecanismo para combinar con el algoritmo EFQ para dar preferencia en la planificación durante breves intervalos de tiempo a las tareas más urgentes con restricciones temporales.Las propiedades del algoritmo EFQ se evaluan a través del modelado de alto nivel y la simulación. Los resultados de las simulaciones indican que los requisitos esenciales de la planificación centrada en la energía pueden lograrse. El algoritmo EFQ se implementa más tarde en el kernel de Linux. Para evaluar las propiedades del planificador EFQ basado en Linux, se desarrolló un banco de pruebas experimental basado en una sitema empotrado, un programa de banco de pruebas multihilo, y un conjunto de pruebas de código abierto. A través de experimentos específicamente diseñados, esta tesis verifica primero las propiedades de EFQ en la gestión de la cuota de consumo de potencia y la planificación en tiempo real y, a continuación, explora los beneficios potenciales de emplear la planificación EFQ en la optimización de la experiencia de usuario para sistemas móviles con energía limitada. Los resultados experimentales sobre la gestión de la cuota de energía muestran que EFQ es más eficaz que el planificador de Linux-CFS en la gestión de energía, logrando un reparto proporcional de la energía del sistema independientemente de en qué dispositivo se consume la energía. Los resultados experimentales en la planificación en tiempo real demuestran que EFQ puede lograr de forma eficaz, flexible y robusta el cumplimiento de las restricciones temporales aunque se dé el caso de aumento del el número de tareas o del error en la estimación de energía. Por último, un análisis comparativo de los resultados experimentales sobre la optimización de la experiencia del usuario demuestra que, primero, EFQ es más eficaz y flexible que los algoritmos tradicionales de planificación del procesador, como el que se encuentra por defecto en el planificador de Linux y, segundo, que proporciona la posibilidad de optimizar y preservar la experiencia de usuario para los sistemas móviles con energía limitada. Abstract Modern mobiledevices have been becoming increasingly powerful in functionality and entertainment as the next-generation mobile computing and communication technologies are rapidly advanced. However, the battery capacity has not experienced anequivalent increase. The user experience of modern mobile systems is therefore greatly affected by the battery lifetime,which is an unstable factor that is hard to control. To address this problem, previous works proposed energy-centric power management (PM) schemes to provide strong guarantee on the battery lifetime by globally managing energy as the first-class resource in the system. As the processor scheduler plays a pivotal role in power management and application performance guarantee, this thesis explores the user experience optimization of energy-limited mobile systemsfrom the perspective of energy-centric processor scheduling in an energy-centric context. This thesis first analyzes the general contributing factors of the mobile system user experience.Then itdetermines the essential requirements on the energy-centric processor scheduling for user experience optimization, which are proportional power sharing, time-constraint compliance, and when necessary, a tradeoff between the power share and the time-constraint compliance. To meet the requirements, the classical fair queuing algorithm and its reference model are extended from the network and CPU bandwidth sharing domain to the energy sharing domain, and based on that, the energy-based fair queuing (EFQ) algorithm is proposed for performing energy-centric processor scheduling. The EFQ algorithm is designed to provide proportional power shares to tasks by scheduling the tasks based on their energy consumption and weights. The power share of each time-sensitive task is protected upon the change of the scheduling environment to guarantee a stable performance, and any instantaneous power share that is overly allocated to one time-sensitive task can be fairly re-allocated to the other tasks. In addition, to better support real-time and multimedia scheduling, certain real-time friendly mechanism is combined into the EFQ algorithm to give time-limited scheduling preference to the time-sensitive tasks. Through high-level modelling and simulation, the properties of the EFQ algorithm are evaluated. The simulation results indicate that the essential requirements of energy-centric processor scheduling can be achieved. The EFQ algorithm is later implemented in the Linux kernel. To assess the properties of the Linux-based EFQ scheduler, an experimental test-bench based on an embedded platform, a multithreading test-bench program, and an open-source benchmark suite is developed. Through specifically-designed experiments, this thesis first verifies the properties of EFQ in power share management and real-time scheduling, and then, explores the potential benefits of employing EFQ scheduling in the user experience optimization for energy-limited mobile systems. Experimental results on power share management show that EFQ is more effective than the Linux-CFS scheduler in managing power shares and it can achieve a proportional sharing of the system power regardless of on which device the energy is spent. Experimental results on real-time scheduling demonstrate that EFQ can achieve effective, flexible and robust time-constraint compliance upon the increase of energy estimation error and task number. Finally, a comparative analysis of the experimental results on user experience optimization demonstrates that EFQ is more effective and flexible than traditional processor scheduling algorithms, such as those of the default Linux scheduler, in optimizing and preserving the user experience of energy-limited mobile systems.

Personalized rule-based closed-loop control algorithm for type 1 diabetes

Type 1 diabetes-mellitus implies a life-threatening absolute insulin deficiency. Artificial pancreas (CGM sensor, insulin pump and control algorithm) is promising to outperform current open-loop therapies.

Variable threshold algorithm for division of labor analyzed as a dynamical system

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

Tools for mixed-criticality partitioned systems: partitioning algorithm and extensibility support

The development of mixed-criticality virtualized multicore systems poses new challenges that are being subject of active research work. There is an additional complexity: it is now required to identify a set of partitions, and allocate applications to partitions. In this job, a number of issues have to be considered, such as the criticality level of the application, security and dependability requirements, operating system used by the application, time requirements granularity, specific hardware needs, etc. MultiPARTES [6] toolset relies on Model Driven Engineering (MDE) [12], which is a suitable approach in this setting. In this paper, it is described the support provided for automatic system partitioning generation and toolset extensibility.

Feasibility assessment of the interactive use of a Monte Carlo algorithm in treatment planning for intraoperative electron radiation therapy

This work analysed the feasibility of using a fast, customized Monte Carlo (MC) method to perform accurate computation of dose distributions during pre- and intraplanning of intraoperative electron radiation therapy (IOERT) procedures. The MC method that was implemented, which has been integrated into a specific innovative simulation and planning tool, is able to simulate the fate of thousands of particles per second, and it was the aim of this work to determine the level of interactivity that could be achieved. The planning workflow enabled calibration of the imaging and treatment equipment, as well as manipulation of the surgical frame and insertion of the protection shields around the organs at risk and other beam modifiers. In this way, the multidisciplinary team involved in IOERT has all the tools necessary to perform complex MC dosage simulations adapted to their equipment in an efficient and transparent way. To assess the accuracy and reliability of this MC technique, dose distributions for a monoenergetic source were compared with those obtained using a general-purpose software package used widely in medical physics applications. Once accuracy of the underlying simulator was confirmed, a clinical accelerator was modelled and experimental measurements in water were conducted. A comparison was made with the output from the simulator to identify the conditions under which accurate dose estimations could be obtained in less than 3 min, which is the threshold imposed to allow for interactive use of the tool in treatment planning. Finally, a clinically relevant scenario, namely early-stage breast cancer treatment, was simulated with pre- and intraoperative volumes to verify that it was feasible to use the MC tool intraoperatively and to adjust dose delivery based on the simulation output, without compromising accuracy. The workflow provided a satisfactory model of the treatment head and the imaging system, enabling proper configuration of the treatment planning system and providing good accuracy in the dosage simulation.

Hybrid Monte Carlo dose algorithm for low energy X-rays intraoperative radiation therapy

Low energy X-rays Intra-Operative Radiation Therapy (XIORT) treatment delivered during surgery (ex: INTRABEAM, Carl Zeiss, and Axxent, Xoft) can benefit from accurate and fast dose prediction in a patient 3D volume.

Validation of a phase space determination algorithm for intraoperative radiation therapy

Monte-Carlo (MC) methods are a valuable tool for dosimetry in radiotherapy, including Intra-Operative Electron Radiotherapy (IOERT), since effects such as inhomogeneities or beam hardening may be realistically reproduced.

A genetic algorithm for slope stability analyses with concave slip surfaces using custom operators

Heuristic methods are popular tools to find critical slip surfaces in slope stability analyses. A new genetic algorithm (GA) is proposed in this work that has a standard structure but a novel encoding and generation of individuals with custom-designed operators for mutation and crossover that produce kinematically feasible slip surfaces with a high probability. In addition, new indices to assess the efficiency of operators in their search for the minimum factor of safety (FS) are proposed. The proposed GA is applied to traditional benchmark examples from the literature, as well as to a new practical example. Results show that the proposed GA is reliable, flexible and robust: it provides good minimum FS estimates that are not very sensitive to the number of nodes and that are very similar for different replications

Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming

In contrast to traditional push-based protocols, adaptive streaming techniques like Dynamic Adaptive Streaming over HTTP (DASH) fix attention on the client, who dynamically requests different-quality portions of the content to cope with a limited and variable bandwidth but aiming at maximizing the quality perceived by the user. Since DASH adaptation logic at the client is not covered by the standard, we propose a solution based on Stochastic Dynamic Programming (SDP) techniques to find the optimal request policies that guarantee the users' Quality of Experience (QoE). Our algorithm is evaluated in a simulated streaming session and is compared with other adaptation approaches. The results show that our proposal outperforms them in terms of QoE, requesting higher qualities on average.

An optimal yet fast pruning algorithm to reduce latency in multiview prediction structures

We propose a new algorithm for the design of prediction structures with low delay and limited penalty in the rate-distortion performance for multiview video coding schemes. This algorithm constitutes one of the elements of a framework for the analysis and optimization of delay in multiview coding schemes that is based in graph theory. The objective of the algorithm is to find the best combination of prediction dependencies to prune from a multiview prediction structure, given a number of cuts. Taking into account the properties of the graph-based analysis of the encoding delay, the algorithm is able to find the best prediction dependencies to eliminate from an original prediction structure, while limiting the number of cut combinations to evaluate. We show that this algorithm obtains optimum results in the reduction of the encoding latency with a lower computational complexity than exhaustive search alternatives.

Grouped sparsity algorithm for multichannel intracardiac ECG synchronization

In this paper, a new method is presented to ensure automatic synchronization of intracardiac ECG data, yielding a three-stage algorithm. We first compute a robust estimate of the derivative of the data to remove low-frequency perturbations. Then we provide a grouped-sparse representation of the data, by means of the Group LASSO, to ensure that all the electrical spikes are simultaneously detected. Finally, a post-processing step, based on a variance analysis, is performed to discard false alarms. Preliminary results on real data for sinus rhythm and atrial fibrillation show the potential of this approach.