55 resultados para Aggregates , Friction , Image edge detection , Measurement by laser beam , Roads , Surface resistance , Surface texture
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We demonstrate site-controlled growth of epitaxial Ag nanocrystals on patterned GaAs substrates by molecular beam epitaxy with high degree of long-range uniformity. The alignment is based on lithographically defined holes in which position controlled InAs quantum dots are grown. The Ag nanocrystals self-align preferentially on top of the InAs quantum dots. No such ordering is observed in the absence of InAs quantum dots, proving that the ordering is strain-driven. The presented technique facilitates the placement of active plasmonic nanostructures at arbitrarily defined positions enabling their integration into complex devices and plasmonic circuits.
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The basics of the self-assembled growth of GaN nanorods on Si(111) are reviewed. Morphology differences and optical properties are compared to those of GaN layers grown directly on Si(111). The effects of the growth temperature on the In incorporation in self-assembled InGaN nanorods grown on Si(111) is described. In addition, the inclusion of InGaN quantum disk structures into selfassembled GaN nanorods show clear confinement effects as a function of the quantum disk thickness. In order to overcome the properties dispersion and the intrinsic inhomogeneous nature of the self-assembled growth, the selective area growth of GaN nanorods on both, c-plane and a-plane GaN on sapphire templates, is addressed, with special emphasis on optical quality and morphology differences. The analysis of the optical emission from a single InGaN quantum disk is shown for both polar and non-polar nanorod orientations
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he composition, strain and surface morphology of (0001)InGaN layers are investigated as a function of growth temperature (460–645 °C) and impinging In flux. Three different growth regimes: nitrogen-rich, metal-rich and intermediate metal-rich, are clearly identified and found to be in correlation with surface morphology and strain relaxation. Best epilayers’ quality is obtained when growing under intermediate metal-rich conditions, with 1–2 monolayers thick In ad-coverage. For a given In flux, the In incorporation decreases with increasing growth temperature due to InN thermal decomposition that follows an Arrhenius behavior with 1.84±0.12 eV activation energy.
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Platinum is the most used catalyst in electrodes for fuel cells due to its high catalytic activity. Polymer electrolyte and direct methanol fuel cells usually include Pt as catalyst in their electrodes. In order to diminish the cost of such electrodes, different Pt deposition methods that permit lowering the metal load whilst maintaining their electroactivity, are being investigated. In this work, the behaviour of electron beam Pt (e-beam Pt) deposited electrodes for fuel cells is studied. Three different Pt loadings have been investigated. The electrochemical behaviour by cyclic voltammetry in H2SO4, HClO4 and in HClO4+MeOH before and after the Pt deposition on carbon cloth has been analysed. The Pt improves the electrochemical properties of the carbon support used. The electrochemical performance of e-beam Pt deposited electrodes was finally studied in a single direct methanol fuel cell (DMFC) and the obtained results indicate that this is a promising and adequate method to prepare fuel cell electrodes.
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This work reports on the growth of (In, Ga)N core−shell micro pillars by plasma-assisted molecular beam epitaxy using an ordered array of GaN cores grown by metal organic vapor phase epitaxy as a template. Upon (In, Ga)N growth, core−shell structures with emission at around 3.0 eV are formed. Further, the fabrication of a core−shell pin structure is demonstrated.
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This work reports on the selective area growth mechanism of green-emitting InGaN/GaN nanocolumns. The evolution of the morphology of the InGaN segment is found to depend critically on the nominal III/V ratio as well as the diameter of the GaN section. In addition, the In distribution inside the InGaN segment is found to depend on the local III/V and In/Ga ratios.
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Based on laser beam intensities above 109 W/cm2 with pulse energy of several Joules and duration of nanoseconds, Laser Shock Processing (LSP) is capable of inducing a surface compressive residual stress field. The paper presents experimental results showing the ability of LSP to improve the mechanical strength and cracking resistance of AA2024-T351 friction stir welded (FSW) joints. After introducing the FSW and LSP procedures, the results of microstructural analysis and micro-hardness are discussed. Video Image Correlation was used to measure the displacement and strain fields produced during tensile testing of flat specimens; the local and overall tensile behavior of native FSW joints vs. LSP treated were analyzed. Further, results of slow strain rate tensile testing of the FSW joints, native and LSP treated, performed in 3.5% NaCl solution are presented. The ability of LSP to improve the structural behavior of the FSW joints is underscored.
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El estudio de materiales, especialmente biológicos, por medios no destructivos está adquiriendo una importancia creciente tanto en las aplicaciones cientÃficas como industriales. Las ventajas económicas de los métodos no destructivos son múltiples. Existen numerosos procedimientos fÃsicos capaces de extraer información detallada de las superficie de la madera con escaso o nulo tratamiento previo y mÃnima intrusión en el material. Entre los diversos métodos destacan las técnicas ópticas y las acústicas por su gran versatilidad, relativa sencillez y bajo coste. Esta tesis pretende establecer desde la aplicación de principios simples de fÃsica, de medición directa y superficial, a través del desarrollo de los algoritmos de decisión mas adecuados basados en la estadÃstica, unas soluciones tecnológicas simples y en esencia, de coste mÃnimo, para su posible aplicación en la determinación de la especie y los defectos superficiales de la madera de cada muestra tratando, en la medida de lo posible, no alterar su geometrÃa de trabajo. Los análisis desarrollados han sido los tres siguientes: El primer método óptico utiliza las propiedades de la luz dispersada por la superficie de la madera cuando es iluminada por un laser difuso. Esta dispersión produce un moteado luminoso (speckle) cuyas propiedades estadÃsticas permiten extraer propiedades muy precisas de la estructura tanto microscópica como macroscópica de la madera. El análisis de las propiedades espectrales de la luz laser dispersada genera ciertos patrones mas o menos regulares relacionados con la estructura anatómica, composición, procesado y textura superficial de la madera bajo estudio que ponen de manifiesto caracterÃsticas del material o de la calidad de los procesos a los que ha sido sometido. El uso de este tipo de láseres implica también la posibilidad de realizar monitorizaciones de procesos industriales en tiempo real y a distancia sin interferir con otros sensores. La segunda técnica óptica que emplearemos hace uso del estudio estadÃstico y matemático de las propiedades de las imágenes digitales obtenidas de la superficie de la madera a través de un sistema de scanner de alta resolución. Después de aislar los detalles mas relevantes de las imágenes, diversos algoritmos de clasificacion automatica se encargan de generar bases de datos con las diversas especies de maderas a las que pertenecÃan las imágenes, junto con los márgenes de error de tales clasificaciones. Una parte fundamental de las herramientas de clasificacion se basa en el estudio preciso de las bandas de color de las diversas maderas. Finalmente, numerosas técnicas acústicas, tales como el análisis de pulsos por impacto acústico, permiten complementar y afinar los resultados obtenidos con los métodos ópticos descritos, identificando estructuras superficiales y profundas en la madera asà como patologÃas o deformaciones, aspectos de especial utilidad en usos de la madera en estructuras. La utilidad de estas técnicas esta mas que demostrada en el campo industrial aun cuando su aplicación carece de la suficiente expansión debido a sus altos costes y falta de normalización de los procesos, lo cual hace que cada análisis no sea comparable con su teórico equivalente de mercado. En la actualidad gran parte de los esfuerzos de investigación tienden a dar por supuesto que la diferenciación entre especies es un mecanismo de reconocimiento propio del ser humano y concentran las tecnologÃas en la definición de parámetros fÃsicos (módulos de elasticidad, conductividad eléctrica o acústica, etc.), utilizando aparatos muy costosos y en muchos casos complejos en su aplicación de campo. Abstract The study of materials, especially the biological ones, by non-destructive techniques is becoming increasingly important in both scientific and industrial applications. The economic advantages of non-destructive methods are multiple and clear due to the related costs and resources necessaries. There are many physical processes capable of extracting detailed information on the wood surface with little or no previous treatment and minimal intrusion into the material. Among the various methods stand out acoustic and optical techniques for their great versatility, relative simplicity and low cost. This thesis aims to establish from the application of simple principles of physics, surface direct measurement and through the development of the more appropriate decision algorithms based on statistics, a simple technological solutions with the minimum cost for possible application in determining the species and the wood surface defects of each sample. Looking for a reasonable accuracy without altering their work-location or properties is the main objetive. There are three different work lines: Empirical characterization of wood surfaces by means of iterative autocorrelation of laser speckle patterns: A simple and inexpensive method for the qualitative characterization of wood surfaces is presented. it is based on the iterative autocorrelation of laser speckle patterns produced by diffuse laser illumination of the wood surfaces. The method exploits the high spatial frequency content of speckle images. A similar approach with raw conventional photographs taken with ordinary light would be very difficult. A few iterations of the algorithm are necessary, typically three or four, in order to visualize the most important periodic features of the surface. The processed patterns help in the study of surface parameters, to design new scattering models and to classify the wood species. Fractal-based image enhancement techniques inspired by differential interference contrast microscopy: Differential interference contrast microscopy is a very powerful optical technique for microscopic imaging. Inspired by the physics of this type of microscope, we have developed a series of image processing algorithms aimed at the magnification, noise reduction, contrast enhancement and tissue analysis of biological samples. These algorithms use fractal convolution schemes which provide fast and accurate results with a performance comparable to the best present image enhancement algorithms. These techniques can be used as post processing tools for advanced microscopy or as a means to improve the performance of less expensive visualization instruments. Several examples of the use of these algorithms to visualize microscopic images of raw pine wood samples with a simple desktop scanner are provided. Wood species identification using stress-wave analysis in the audible range: Stress-wave analysis is a powerful and flexible technique to study mechanical properties of many materials. We present a simple technique to obtain information about the species of wood samples using stress-wave sounds in the audible range generated by collision with a small pendulum. Stress-wave analysis has been used for flaw detection and quality control for decades, but its use for material identification and classification is less cited in the literature. Accurate wood species identification is a time consuming task for highly trained human experts. For this reason, the development of cost effective techniques for automatic wood classification is a desirable goal. Our proposed approach is fully non-invasive and non-destructive, reducing significantly the cost and complexity of the identification and classification process.
Resumo:
We present improved experimental transition probabilities for the optical Ca I 4s4p-4s4d and 4s4p-4p2multiplets. The values were determined with an absolute uncertainty of 10%. Transition probabilities have been determined by the branching ratios from the measurement of relative line intensities emitted by laser-induced plasma (LIP). The line intensities were obtained with the target (leadcalcium) placed in argon atmosphere at 6 Torr, recorded at a 2.5 µs delay from the laser pulse, which provides appropriate measurement conditions, and analysed between 350.0 and 550.0 nm. They are measured when the plasma reaches local thermodynamic equilibrium (LTE). The plasma is characterized by electron temperature (T) of 11400 K and an electron number density (Ne) of 1.1 x 1016 cm-3. The influence self-absorption has been estimated for every line, and plasma homogeneity has been checked. The values obtained were compared with previous experimental values in the literature. The method for measurement of transition probabilities using laser-induced plasma as spectroscopic source has been checked.
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Along the recent years, several moving object detection strategies by non-parametric background-foreground modeling have been proposed. To combine both models and to obtain the probability of a pixel to belong to the foreground, these strategies make use of Bayesian classifiers. However, these classifiers do not allow to take advantage of additional prior information at different pixels. So, we propose a novel and efficient alternative Bayesian classifier that is suitable for this kind of strategies and that allows the use of whatever prior information. Additionally, we present an effective method to dynamically estimate prior probability from the result of a particle filter-based tracking strategy.
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In this work we have realized plasma diagnosis produced by Laser (LPP), by means of emission spectroscopy in a Laser Shock Processing (LSP). The LSP has been proposed as an alternative technology, competitive with classical surface treatments. The ionic species present in the plasma together with electron density and its temperature provide significant indicators of the degree of surface effect of the treated material. In order to analyze these indicators, we have realized spectroscopic studies of optical emission in the laser-generated plasmas in different situations. We have worked focusing on an aluminum sample (Al2024) in air and/or in LSP conditions (water flow) a Q-switched laser of Nd:YAG (λ = 1.06 μm, 10 ns of pulse duration, running at 10 Hz repetition rate). The pulse energy was set at 2,5 J per pulse. The electron density has been measured using, in every case, the Stark broadening of H Balmer α line (656.27 nm). In the case of the air, this measure has been contrasted with the value obtained with the line of 281.62 nm of Al II. Special attention has been paid to the self-absorption of the spectral lines used. The measures were realized with different delay times after the pulse of the laser (1–8 μs) and with a time window of 1 μs. In LSP the electron density obtained was between 1017 cm−3 for the shortest delays (4–6 μs), and 1016 cm−3 for the greatest delays (7,8 μs).
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Illumination uniformity of a spherical capsule directly driven by laser beams has been assessed numerically. Laser facilities characterized by ND = 12, 20, 24, 32, 48 and 60 directions of irradiation with associated a single laser beam or a bundle of NB laser beams have been considered. The laser beam intensity profile is assumed super-Gaussian and the calculations take into account beam imperfections as power imbalance and pointing errors. The optimum laser intensity profile, which minimizes the root-mean-square deviation of the capsule illumination, depends on the values of the beam imperfections. Assuming that the NB beams are statistically independents is found that they provide a stochastic homogenization of the laser intensity associated to the whole bundle, reducing the errors associated to the whole bundle by the factor  , which in turn improves the illumination uniformity of the capsule. Moreover, it is found that the uniformity of the irradiation is almost the same for all facilities and only depends on the total number of laser beams Ntot = ND × NB.
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Here, a novel and efficient moving object detection strategy by non-parametric modeling is presented. Whereas the foreground is modeled by combining color and spatial information, the background model is constructed exclusively with color information, thus resulting in a great reduction of the computational and memory requirements. The estimation of the background and foreground covariance matrices, allows us to obtain compact moving regions while the number of false detections is reduced. Additionally, the application of a tracking strategy provides a priori knowledge about the spatial position of the moving objects, which improves the performance of the Bayesian classifier
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Este Proyecto Fin de Carrera trata sobre el reconocimiento e identificación de caracteres de matrÃculas de automóviles. Este tipo de sistemas de reconocimiento también se los conoce mundialmente como sistemas ANPR ("Automatic Number Plate Recognition") o LPR ("License Plate Recognition"). La gran cantidad de vehÃculos y logÃstica que se mueve cada segundo por todo el planeta, hace necesaria su registro para su tratamiento y control. Por ello, es necesario implementar un sistema que pueda identificar correctamente estos recursos, para su posterior procesado, construyendo asà una herramienta útil, ágil y dinámica. El presente trabajo ha sido estructurado en varias partes. La primera de ellas nos muestra los objetivos y las motivaciones que se persiguen con la realización de este proyecto. En la segunda, se abordan y desarrollan todos los diferentes procesos teóricos y técnicos, asà como matemáticos, que forman un sistema ANPR común, con el fin de implementar una aplicación práctica que pueda demostrar la utilidad de estos en cualquier situación. En la tercera, se desarrolla esa parte práctica en la que se apoya la base teórica del trabajo. En ésta se describen y desarrollan los diversos algoritmos, creados con el fin de estudiar y comprobar todo lo planteado hasta ahora, asà como observar su comportamiento. Se implementan varios procesos caracterÃsticos del reconocimiento de caracteres y patrones, como la detección de áreas o patrones, rotado y transformación de imágenes, procesos de detección de bordes, segmentación de caracteres y patrones, umbralización y normalización, extracción de caracterÃsticas y patrones, redes neuronales, y finalmente el reconocimiento óptico de caracteres o comúnmente conocido como OCR. La última parte refleja los resultados obtenidos a partir del sistema de reconocimiento de caracteres implementado para el trabajo y se exponen las conclusiones extraÃdas a partir de éste. Finalmente se plantean las lÃneas futuras de mejora, desarrollo e investigación, para poder realizar un sistema más eficiente y global. This Thesis deals about license plate characters recognition and identification. These kinds of systems are also known worldwide as ANPR systems ("Automatic Number Plate Recognition") or LPR ("License Plate Recognition"). The great number of vehicles and logistics moving every second all over the world, requires a registration for treatment and control. Thereby, it’s therefore necessary to implement a system that can identify correctly these resources, for further processing, thus building a useful, flexible and dynamic tool. This work has been structured into several parts. The first one shows the objectives and motivations attained by the completion of this project. In the second part, it’s developed all the different theoretical and technical processes, forming a common ANPR system in order to implement a practical application that can demonstrate the usefulness of these ones on any situation. In the third, the practical part is developed, which is based on the theoretical work. In this one are described and developed various algorithms, created to study and verify all the questions until now suggested, and complain the behavior of these systems. Several recognition of characters and patterns characteristic processes are implemented, such as areas or patterns detection, image rotation and transformation, edge detection processes, patterns and character segmentation, thresholding and normalization, features and patterns extraction, neural networks, and finally the optical character recognition or commonly known like OCR. The last part shows the results obtained from the character recognition system implemented for this thesis and the outlines conclusions drawn from it. Finally, future lines of improvement, research and development are proposed, in order to make a more efficient and comprehensive system.