815 resultados para Worm algorithm
Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming
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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.
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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.
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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.
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In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained
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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.
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Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.
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Vector reconstruction of objects from an unstructured point cloud obtained with a LiDAR-based system (light detection and ranging) is one of the most promising methods to build three dimensional models of orchards. The cylinder fitting method for woody structure reconstruction of leafless trees from point clouds obtained with a mobile terrestrial laser scanner (MTLS) has been analysed. The advantage of this method is that it performs reconstruction in a single step. The most time consuming part of the algorithm is generation of the cylinder direction, which must be recalculated at the inclusion of each point in the cylinder. The tree skeleton is obtained at the same time as the cluster of cylinders is formed. The method does not guarantee a unique convergence and the reconstruction parameter values must be carefully chosen. A balanced processing of clusters has also been defined which has proven to be very efficient in terms of processing time by following the hierarchy of branches, predecessors and successors. The algorithm was applied to simulated MTLS of virtual orchard models and to MTLS data of real orchards. The constraints applied in the method have been reviewed to ensure better convergence and simpler use of parameters. The results obtained show a correct reconstruction of the woody structure of the trees and the algorithm runs in linear logarithmic time
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Wave energy conversion has an essential difference from other renewable energies since the dependence between the devices design and the energy resource is stronger. Dimensioning is therefore considered a key stage when a design project of Wave Energy Converters (WEC) is undertaken. Location, WEC concept, Power Take-Off (PTO) type, control strategy and hydrodynamic resonance considerations are some of the critical aspects to take into account to achieve a good performance. The paper proposes an automatic dimensioning methodology to be accomplished at the initial design project stages and the following elements are described to carry out the study: an optimization design algorithm, its objective functions and restrictions, a PTO model, as well as a procedure to evaluate the WEC energy production. After that, a parametric analysis is included considering different combinations of the key parameters previously introduced. A variety of study cases are analysed from the point of view of energy production for different design-parameters and all of them are compared with a reference case. Finally, a discussion is presented based on the results obtained, and some recommendations to face the WEC design stage are given.
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New Fault-Resistance Estimation Algorithm for Rotor-Winding Ground-Fault Online Location in Synchronous Machines With Static Excitation
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Development of a Sensorimotor Algorithm Able to Deal with Unforeseen Pushes and Its Implementation Based on VHDL is the title of my thesis which concludes my Bachelor Degree in the Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación of the Universidad Politécnica de Madrid. It encloses the overall work I did in the Neurorobotics Research Laboratory from the Beuth Hochschule für Technik Berlin during my ERASMUS year in 2015. This thesis is focused on the field of robotics, specifically an electronic circuit called Cognitive Sensorimotor Loop (CSL) and its control algorithm based on VHDL hardware description language. The reason that makes the CSL special resides in its ability to operate a motor both as a sensor and an actuator. This way, it is possible to achieve a balanced position in any of the robot joints (e.g. the robot manages to stand) without needing any conventional sensor. In other words, the back electromotive force (EMF) induced by the motor coils is measured and the control algorithm responds depending on its magnitude. The CSL circuit contains mainly an analog-to-digital converter (ADC) and a driver. The ADC consists on a delta-sigma modulation which generates a series of bits with a certain percentage of 1's and 0's, proportional to the back EMF. The control algorithm, running in a FPGA, processes the bit frame and outputs a signal for the driver. This driver, which has an H bridge topology, gives the motor the ability to rotate in both directions while it's supplied with the power needed. The objective of this thesis is to document the experiments and overall work done on push ignoring contractive sensorimotor algorithms, meaning sensorimotor algorithms that ignore large magnitude forces (compared to gravity) applied in a short time interval on a pendulum system. This main objective is divided in two sub-objectives: (1) developing a system based on parameterized thresholds and (2) developing a system based on a push bypassing filter. System (1) contains a module that outputs a signal which blocks the main Sensorimotor algorithm when a push is detected. This module has several different parameters as inputs e.g. the back EMF increment to consider a force as a push or the time interval between samples. System (2) consists on a low-pass Infinite Impulse Response digital filter. It cuts any frequency considered faster than a certain push oscillation. This filter required an intensive study on how to implement some functions and data types (fixed or floating point data) not supported by standard VHDL packages. Once this was achieved, the next challenge was to simplify the solution as much as possible, without using non-official user made packages. Both systems behaved with a series of interesting advantages and disadvantages for the elaboration of the document. Stability, reaction time, simplicity or computational load are one of the many factors to be studied in the designed systems. RESUMEN. Development of a Sensorimotor Algorithm Able to Deal with Unforeseen Pushes and Its Implementation Based on VHDL es un Proyecto de Fin de Grado (PFG) que concluye mis estudios en la Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación de la Universidad Politécnica de Madrid. En él se documenta el trabajo de investigación que realicé en el Neurorobotics Research Laboratory de la Beuth Hochschule für Technik Berlin durante el año 2015 mediante el programa de intercambio ERASMUS. Este PFG se centra en el campo de la robótica y en concreto en un circuito electrónico llamado Cognitive Sensorimotor Loop (CSL) y su algoritmo de control basado en lenguaje de modelado hardware VHDL. La particularidad del CSL reside en que se consigue que un motor haga las veces tanto de sensor como de actuador. De esta manera es posible que las articulaciones de un robot alcancen una posición de equilibrio (p.ej. el robot se coloca erguido) sin la necesidad de sensores en el sentido estricto de la palabra. Es decir, se mide la propia fuerza electromotriz (FEM) inducida sobre el motor y el algoritmo responde de acuerdo a su magnitud. El circuito CSL se compone de un convertidor analógico-digital (ADC) y un driver. El ADC consiste en un modulador sigma-delta, que genera una serie de bits con un porcentaje de 1's y 0's determinado, en proporción a la magnitud de la FEM inducida. El algoritmo de control, que se ejecuta en una FPGA, procesa esta cadena de bits y genera una señal para el driver. El driver, que posee una topología en puente H, provee al motor de la potencia necesaria y le otorga la capacidad de rotar en cualquiera de las dos direcciones. El objetivo de este PFG es documentar los experimentos y en general el trabajo realizado en algoritmos Sensorimotor que puedan ignorar fuerzas de gran magnitud (en comparación con la gravedad) y aplicadas en una corta ventana de tiempo. En otras palabras, ignorar empujones conservando el comportamiento original frente a la gravedad. Para ello se han desarrollado dos sistemas: uno basado en umbrales parametrizados (1) y otro basado en un filtro de corte ajustable (2). El sistema (1) contiene un módulo que, en el caso de detectar un empujón, genera una señal que bloquea el algoritmo Sensorimotor. Este módulo recibe diferentes parámetros como el incremento necesario de la FEM para que se considere un empujón o la ventana de tiempo para que se considere la existencia de un empujón. El sistema (2) consiste en un filtro digital paso-bajo de respuesta infinita que corta cualquier variación que considere un empujón. Para crear este filtro se requirió un estudio sobre como implementar ciertas funciones y tipos de datos (coma fija o flotante) no soportados por las librerías básicas de VHDL. Tras esto, el objetivo fue simplificar al máximo la solución del problema, sin utilizar paquetes de librerías añadidos. En ambos sistemas aparecen una serie de ventajas e inconvenientes de interés para el documento. La estabilidad, el tiempo de reacción, la simplicidad o la carga computacional son algunas de las muchos factores a estudiar en los sistemas diseñados. Para concluir, también han sido documentadas algunas incorporaciones a los sistemas: una interfaz visual en VGA, un módulo que compensa el offset del ADC o la implementación de una batería de faders MIDI entre otras.
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In this paper we present a recurrent procedure to solve an inversion problem for monic bivariate Krawtchouk polynomials written in vector column form, giving its solution explicitly. As a by-product, a general connection problem between two vector column of monic bivariate Krawtchouk families is also explicitly solved. Moreover, in the non monic case and also for Krawtchouk families, several expansion formulas are given, but for polynomials written in scalar form.
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We propose a general procedure for solving incomplete data estimation problems. The procedure can be used to find the maximum likelihood estimate or to solve estimating equations in difficult cases such as estimation with the censored or truncated regression model, the nonlinear structural measurement error model, and the random effects model. The procedure is based on the general principle of stochastic approximation and the Markov chain Monte-Carlo method. Applying the theory on adaptive algorithms, we derive conditions under which the proposed procedure converges. Simulation studies also indicate that the proposed procedure consistently converges to the maximum likelihood estimate for the structural measurement error logistic regression model.
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Peer reviewed
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The database reported here is derived using the Combinatorial Extension (CE) algorithm which compares pairs of protein polypeptide chains and provides a list of structurally similar proteins along with their structure alignments. Using CE, structure–structure alignments can provide insights into biological function. When a protein of known function is shown to be structurally similar to a protein of unknown function, a relationship might be inferred; a relationship not necessarily detectable from sequence comparison alone. Establishing structure–structure relationships in this way is of great importance as we enter an era of structural genomics where there is a likelihood of an increasing number of structures with unknown functions being determined. Thus the CE database is an example of a useful tool in the annotation of protein structures of unknown function. Comparisons can be performed on the complete PDB or on a structurally representative subset of proteins. The source protein(s) can be from the PDB (updated monthly) or uploaded by the user. CE provides sequence alignments resulting from structural alignments and Cartesian coordinates for the aligned structures, which may be analyzed using the supplied Compare3D Java applet, or downloaded for further local analysis. Searches can be run from the CE web site, http://cl.sdsc.edu/ce.html, or the database and software downloaded from the site for local use.
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There is a need for faster and more sensitive algorithms for sequence similarity searching in view of the rapidly increasing amounts of genomic sequence data available. Parallel processing capabilities in the form of the single instruction, multiple data (SIMD) technology are now available in common microprocessors and enable a single microprocessor to perform many operations in parallel. The ParAlign algorithm has been specifically designed to take advantage of this technology. The new algorithm initially exploits parallelism to perform a very rapid computation of the exact optimal ungapped alignment score for all diagonals in the alignment matrix. Then, a novel heuristic is employed to compute an approximate score of a gapped alignment by combining the scores of several diagonals. This approximate score is used to select the most interesting database sequences for a subsequent Smith–Waterman alignment, which is also parallelised. The resulting method represents a substantial improvement compared to existing heuristics. The sensitivity and specificity of ParAlign was found to be as good as Smith–Waterman implementations when the same method for computing the statistical significance of the matches was used. In terms of speed, only the significantly less sensitive NCBI BLAST 2 program was found to outperform the new approach. Online searches are available at http://dna.uio.no/search/