44 resultados para Weibull probability distribution function


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Esta tesis se desarrolla dentro del marco de las comunicaciones satelitales en el innovador campo de los pequeños satélites también llamados nanosatélites o cubesats, llamados así por su forma cubica. Estos nanosatélites se caracterizan por su bajo costo debido a que usan componentes comerciales llamados COTS (commercial off-the-shelf) y su pequeño tamaño como los Cubesats 1U (10cm*10 cm*10 cm) con masa aproximada a 1 kg. Este trabajo de tesis tiene como base una iniciativa propuesta por el autor de la tesis para poner en órbita el primer satélite peruano en mi país llamado chasqui I, actualmente puesto en órbita desde la Estación Espacial Internacional. La experiencia de este trabajo de investigación me llevo a proponer una constelación de pequeños satélites llamada Waposat para dar servicio de monitoreo de sensores de calidad de agua a nivel global, escenario que es usado en esta tesis. Es ente entorno y dadas las características limitadas de los pequeños satélites, tanto en potencia como en velocidad de datos, es que propongo investigar una nueva arquitectura de comunicaciones que permita resolver en forma óptima la problemática planteada por los nanosatélites en órbita LEO debido a su carácter disruptivo en sus comunicaciones poniendo énfasis en las capas de enlace y aplicación. Esta tesis presenta y evalúa una nueva arquitectura de comunicaciones para proveer servicio a una red de sensores terrestres usando una solución basada en DTN (Delay/Disruption Tolerant Networking) para comunicaciones espaciales. Adicionalmente, propongo un nuevo protocolo de acceso múltiple que usa una extensión del protocolo ALOHA no ranurado, el cual toma en cuenta la prioridad del trafico del Gateway (ALOHAGP) con un mecanismo de contienda adaptativo. Utiliza la realimentación del satélite para implementar el control de la congestión y adapta dinámicamente el rendimiento efectivo del canal de una manera óptima. Asumimos un modelo de población de sensores finito y una condición de tráfico saturado en el que cada sensor tiene siempre tramas que transmitir. El desempeño de la red se evaluó en términos de rendimiento efectivo, retardo y la equidad del sistema. Además, se ha definido una capa de convergencia DTN (ALOHAGP-CL) como un subconjunto del estándar TCP-CL (Transmission Control Protocol-Convergency Layer). Esta tesis muestra que ALOHAGP/CL soporta adecuadamente el escenario DTN propuesto, sobre todo cuando se utiliza la fragmentación reactiva. Finalmente, esta tesis investiga una transferencia óptima de mensajes DTN (Bundles) utilizando estrategias de fragmentación proactivas para dar servicio a una red de sensores terrestres utilizando un enlace de comunicaciones satelitales que utiliza el mecanismo de acceso múltiple con prioridad en el tráfico de enlace descendente (ALOHAGP). El rendimiento efectivo ha sido optimizado mediante la adaptación de los parámetros del protocolo como una función del número actual de los sensores activos recibidos desde el satélite. También, actualmente no existe un método para advertir o negociar el tamaño máximo de un “bundle” que puede ser aceptado por un agente DTN “bundle” en las comunicaciones por satélite tanto para el almacenamiento y la entrega, por lo que los “bundles” que son demasiado grandes son eliminados o demasiado pequeños son ineficientes. He caracterizado este tipo de escenario obteniendo una distribución de probabilidad de la llegada de tramas al nanosatélite así como una distribución de probabilidad del tiempo de visibilidad del nanosatélite, los cuales proveen una fragmentación proactiva óptima de los DTN “bundles”. He encontrado que el rendimiento efectivo (goodput) de la fragmentación proactiva alcanza un valor ligeramente inferior al de la fragmentación reactiva. Esta contribución permite utilizar la fragmentación activa de forma óptima con todas sus ventajas tales como permitir implantar el modelo de seguridad de DTN y la simplicidad al implementarlo en equipos con muchas limitaciones de CPU y memoria. La implementación de estas contribuciones se han contemplado inicialmente como parte de la carga útil del nanosatélite QBito, que forma parte de la constelación de 50 nanosatélites que se está llevando a cabo dentro del proyecto QB50. ABSTRACT This thesis is developed within the framework of satellite communications in the innovative field of small satellites also known as nanosatellites (<10 kg) or CubeSats, so called from their cubic form. These nanosatellites are characterized by their low cost because they use commercial components called COTS (commercial off-the-shelf), and their small size and mass, such as 1U Cubesats (10cm * 10cm * 10cm) with approximately 1 kg mass. This thesis is based on a proposal made by the author of the thesis to put into orbit the first Peruvian satellite in his country called Chasqui I, which was successfully launched into orbit from the International Space Station in 2014. The experience of this research work led me to propose a constellation of small satellites named Waposat to provide water quality monitoring sensors worldwide, scenario that is used in this thesis. In this scenario and given the limited features of nanosatellites, both power and data rate, I propose to investigate a new communications architecture that allows solving in an optimal manner the problems of nanosatellites in orbit LEO due to the disruptive nature of their communications by putting emphasis on the link and application layers. This thesis presents and evaluates a new communications architecture to provide services to terrestrial sensor networks using a space Delay/Disruption Tolerant Networking (DTN) based solution. In addition, I propose a new multiple access mechanism protocol based on extended unslotted ALOHA that takes into account the priority of gateway traffic, which we call ALOHA multiple access with gateway priority (ALOHAGP) with an adaptive contention mechanism. It uses satellite feedback to implement the congestion control, and to dynamically adapt the channel effective throughput in an optimal way. We assume a finite sensor population model and a saturated traffic condition where every sensor always has frames to transmit. The performance was evaluated in terms of effective throughput, delay and system fairness. In addition, a DTN convergence layer (ALOHAGP-CL) has been defined as a subset of the standard TCP-CL (Transmission Control Protocol-Convergence Layer). This thesis reveals that ALOHAGP/CL adequately supports the proposed DTN scenario, mainly when reactive fragmentation is used. Finally, this thesis investigates an optimal DTN message (bundles) transfer using proactive fragmentation strategies to give service to a ground sensor network using a nanosatellite communications link which uses a multi-access mechanism with priority in downlink traffic (ALOHAGP). The effective throughput has been optimized by adapting the protocol parameters as a function of the current number of active sensors received from satellite. Also, there is currently no method for advertising or negotiating the maximum size of a bundle which can be accepted by a bundle agent in satellite communications for storage and delivery, so that bundles which are too large can be dropped or which are too small are inefficient. We have characterized this kind of scenario obtaining a probability distribution for frame arrivals to nanosatellite and visibility time distribution that provide an optimal proactive fragmentation of DTN bundles. We have found that the proactive effective throughput (goodput) reaches a value slightly lower than reactive fragmentation approach. This contribution allows to use the proactive fragmentation optimally with all its advantages such as the incorporation of the security model of DTN and simplicity in protocol implementation for computers with many CPU and memory limitations. The implementation of these contributions was initially contemplated as part of the payload of the nanosatellite QBito, which is part of the constellation of 50 nanosatellites envisaged under the QB50 project.

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The objective of this thesis is the development of cooperative localization and tracking algorithms using nonparametric message passing techniques. In contrast to the most well-known techniques, the goal is to estimate the posterior probability density function (PDF) of the position of each sensor. This problem can be solved using Bayesian approach, but it is intractable in general case. Nevertheless, the particle-based approximation (via nonparametric representation), and an appropriate factorization of the joint PDFs (using message passing methods), make Bayesian approach acceptable for inference in sensor networks. The well-known method for this problem, nonparametric belief propagation (NBP), can lead to inaccurate beliefs and possible non-convergence in loopy networks. Therefore, we propose four novel algorithms which alleviate these problems: nonparametric generalized belief propagation (NGBP) based on junction tree (NGBP-JT), NGBP based on pseudo-junction tree (NGBP-PJT), NBP based on spanning trees (NBP-ST), and uniformly-reweighted NBP (URW-NBP). We also extend NBP for cooperative localization in mobile networks. In contrast to the previous methods, we use an optional smoothing, provide a novel communication protocol, and increase the efficiency of the sampling techniques. Moreover, we propose novel algorithms for distributed tracking, in which the goal is to track the passive object which cannot locate itself. In particular, we develop distributed particle filtering (DPF) based on three asynchronous belief consensus (BC) algorithms: standard belief consensus (SBC), broadcast gossip (BG), and belief propagation (BP). Finally, the last part of this thesis includes the experimental analysis of some of the proposed algorithms, in which we found that the results based on real measurements are very similar with the results based on theoretical models.

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We have developed a new projector model specifically tailored for fast list-mode tomographic reconstructions in Positron emission tomography (PET) scanners with parallel planar detectors. The model provides an accurate estimation of the probability distribution of coincidence events defined by pairs of scintillating crystals. This distribution is parameterized with 2D elliptical Gaussian functions defined in planes perpendicular to the main axis of the tube of response (TOR). The parameters of these Gaussian functions have been obtained by fitting Monte Carlo simulations that include positron range, acolinearity of gamma rays, as well as detector attenuation and scatter effects. The proposed model has been applied efficiently to list-mode reconstruction algorithms. Evaluation with Monte Carlo simulations over a rotating high resolution PET scanner indicates that this model allows to obtain better recovery to noise ratio in OSEM (ordered-subsets, expectation-maximization) reconstruction, if compared to list-mode reconstruction with symmetric circular Gaussian TOR model, and histogram-based OSEM with precalculated system matrix using Monte Carlo simulated models and symmetries.

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This paper presents some of the results of a method to determine the main reliability functions of concentrator solar cells. High concentrator GaAs single junction solar cells have been tested in an Accelerated Life Test. The method can be directly applied to multi-junction solar cells. The main conclusions of this test carried out show that these solar cells are robust devices with a very low probability of failure caused by degradation during their operation life (more than 30 years). The evaluation of the probability operation function (i.e. the reliability function R(t)) is obtained for two nominal operation conditions of these cells, namely simulated concentration ratios of 700 and 1050 suns. Preliminary determination of the Mean Time to Failure indicates a value much higher than the intended operation life time of the concentrator cells.

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This paper presents a theoretical analysis and an optimization method for envelope amplifier. Highly efficient envelope amplifiers based on a switching converter in parallel or series with a linear regulator have been analyzed and optimized. The results of the optimization process have been shown and these two architectures are compared regarding their complexity and efficiency. The optimization method that is proposed is based on the previous knowledge about the transmitted signal type (OFDM, WCDMA...) and it can be applied to any signal type as long as the envelope probability distribution is known. Finally, it is shown that the analyzed architectures have an inherent efficiency limit.

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This paper deals with the detection and tracking of an unknown number of targets using a Bayesian hierarchical model with target labels. To approximate the posterior probability density function, we develop a two-layer particle filter. One deals with track initiation, and the other with track maintenance. In addition, the parallel partition method is proposed to sample the states of the surviving targets.

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Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

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Many existing engineering works model the statistical characteristics of the entities under study as normal distributions. These models are eventually used for decision making, requiring in practice the definition of the classification region corresponding to the desired confidence level. Surprisingly enough, however, a great amount of computer vision works using multidimensional normal models leave unspecified or fail to establish correct confidence regions due to misconceptions on the features of Gaussian functions or to wrong analogies with the unidimensional case. The resulting regions incur in deviations that can be unacceptable in high-dimensional models. Here we provide a comprehensive derivation of the optimal confidence regions for multivariate normal distributions of arbitrary dimensionality. To this end, firstly we derive the condition for region optimality of general continuous multidimensional distributions, and then we apply it to the widespread case of the normal probability density function. The obtained results are used to analyze the confidence error incurred by previous works related to vision research, showing that deviations caused by wrong regions may turn into unacceptable as dimensionality increases. To support the theoretical analysis, a quantitative example in the context of moving object detection by means of background modeling is given.

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The purpose of this paper is to present a program written in Matlab-Octave for the simulation of the time evolution of student curricula, i.e, how students pass their subjects along time until graduation. The program computes, from the simulations, the academic performance rates for the subjects of the study plan for each semester as well as the overall rates, which are a) the efficiency rate defined as the ratio of the number of students passing the exam to the number of students who registered for it and b) the success rate, defined as the ratio of the number of students passing the exam to the number of students who not only registered for it but also actually took it. Additionally, we compute the rates for the bachelor academic degree which are established for Spain by the National Quality Evaluation and Accreditation Agency (ANECA) and which are the graduation rate (measured as the percentage of students who finish as scheduled in the plan or taking an extra year) and the efficiency rate (measured as the percentage of credits which a student who graduated has really taken). The simulation is done in terms of the probabilities of passing all the subjects in their study plan. The application of the simulator to Polytech students in Madrid, where requirements for passing are specially stiff in first and second year subjects, is particularly relevant to analyze student cohorts and the probabilities of students finishing in the minimum of four years, or taking and extra year or two extra years, and so forth. It is a very useful tool when designing new study plans. The calculation of the probability distribution of the random variable "number of semesters a student has taken to complete the curricula and graduate" is difficult or even unfeasible to obtain analytically, and this is even truer when we incorporate uncertainty in parameter estimation. This is why we apply Monte Carlo simulation which not only provides illustration of the stochastic process but also a method for computation. The stochastic simulator is proving to be a useful tool for identification of the subjects most critical in the distribution of the number of semesters for curriculum vitae (CV) completion and subsequently for a decision making process in terms of CV planning and passing standards in the University. Simulations are performed through a graphical interface where also the results are presented in appropriate figures. The Project has been funded by the Call for Innovation in Education Projects of Universidad Politécnica de Madrid (UPM) through a Project of its school Escuela Técnica Superior de Ingenieros Industriales ETSII during the period September 2010-September 2011.

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Lately, several researchers have pointed out that climate change is expected to increase temperatures and lower rainfall in Mediterranean regions, simultaneously increasing the intensity of extreme rainfall events. These changes could have consequences regarding rainfall regime, erosion, sediment transport and water quality, soil management, and new designs in diversion ditches. Climate change is expected to result in increasingly unpredictable and variable rainfall, in amount and timing, changing seasonal patterns and increasing the frequency of extreme weather events. Consequently, the evolution of frequency and intensity of drought periods is of most important as in agro-ecosystems many processes will be affected by them. Realising the complex and important consequences of an increasing frequency of extreme droughts at the Ebro River basin, our aim is to study the evolution of drought events at this site statistically, with emphasis on the occurrence and intensity of them. For this purpose, fourteen meteorological stations were selected based on the length of the rainfall series and the climatic classification to obtain a representative untreated dataset from the river basin. Daily rainfall series from 1957 to 2002 were obtained from each meteorological station and no-rain period frequency as the consecutive numbers of days were extracted. Based on this data, we study changes in the probability distribution in several sub-periods. Moreover we used the Standardized Precipitation Index (SPI) for identification of drought events in a year scale and then we use this index to fit log-linear models to the contingency tables between the SPI index and the sub-periods, this adjusted is carried out with the help of ANOVA inference.

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We propose distributed algorithms for sampling networks based on a new class of random walks that we call Centrifugal Random Walks (CRW). A CRW is a random walk that starts at a source and always moves away from it. We propose CRW algorithms for connected networks with arbitrary probability distributions, and for grids and networks with regular concentric connectivity with distance based distributions. All CRW sampling algorithms select a node with the exact probability distribution, do not need warm-up, and end in a number of hops bounded by the network diameter.

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Several authors have analysed the changes of the probability density function of the solar radiation with different time resolutions. Some others have approached to study the significance of these changes when produced energy calculations are attempted. We have undertaken different transformations to four Spanish databases in order to clarify the interrelationship between radiation models and produced energy estimations. Our contribution is straightforward: the complexity of a solar radiation model needed for yearly energy calculations, is very low. Twelve values of monthly mean of solar radiation are enough to estimate energy with errors below 3%. Time resolutions better than hourly samples do not improve significantly the result of energy estimations.

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The paper discusses the dispersion relation for longitudinal electron waves propagating in a collisionless, homogeneous isotropic plasma, which contains both Maxwellian and suprathermal electrons. I t is found that the dispersion curve, known to have two separate branches for zero suprathermal energy spread,depends sensitively on this quantity. As the energy half-width of the suprathermal population increases, the branches approach each other until they touch at a connexion point, for a small critical value of that half-width. The topology of the dispersion curves is different for half-widths above and below critical; and this can affect the use of wave-propagation measurements as a diagnostic technique for the determination of the electron distribution function. Both the distance between the branches and spatial damping near the connexion frequency depend on the half-width, if below critical, and can be used to determine it. The theory is applied to experimental data.

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Using the Monte Carlo method the behavior of a system of true hard cylinders has been studied. Values of the length-to-breadth ratio L/D and packing fraction η have been chosen similar to those of real nematic liquid crystals. Results include radial distribution function g(r), structure factor S(k), and orientational order parameter M. These results lead to the conclusion that the hard cylinder model may be a useful reference for real mesomorphic phases.

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Motivated by the observation of spiral patterns in a wide range of physical, chemical, and biological systems, we present an automated approach that aims at characterizing quantitatively spiral-like elements in complex stripelike patterns. The approach provides the location of the spiral tip and the size of the spiral arms in terms of their arc length and their winding number. In addition, it yields the number of pattern components (Betti number of order 1), as well as their size and certain aspects of their shape. We apply the method to spiral defect chaos in thermally driven Rayleigh- Bénard convection and find that the arc length of spirals decreases monotonically with decreasing Prandtl number of the fluid and increasing heating. By contrast, the winding number of the spirals is nonmonotonic in the heating. The distribution function for the number of spirals is significantly narrower than a Poisson distribution. The distribution function for the winding number shows approximately an exponential decay. It depends only weakly on the heating, but strongly on the Prandtl number. Large spirals arise only for larger Prandtl numbers. In this regime the joint distribution for the spiral length and the winding number exhibits a three-peak structure, indicating the dominance of Archimedean spirals of opposite sign and relatively straight sections. For small Prandtl numbers the distribution function reveals a large number of small compact pattern components.