979 resultados para Fusion process


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The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.

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Fusion energy is a clean and safe solution for the intricate question of how to produce non-polluting and sustainable energy for the constantly growing population. The fusion process does not result in any harmful waste or green-house gases, since small amounts of helium is the only bi-product that is produced when using the hydrogen isotopes deuterium and tritium as fuel. Moreover, deuterium is abundant in seawater and tritium can be bred from lithium, a common metal in the Earth's crust, rendering the fuel reservoirs practically bottomless. Due to its enormous mass, the Sun has been able to utilize fusion as its main energy source ever since it was born. But here on Earth, we must find other means to achieve the same. Inertial fusion involving powerful lasers and thermonuclear fusion employing extreme temperatures are examples of successful methods. However, these have yet to produce more energy than they consume. In thermonuclear fusion, the fuel is held inside a tokamak, which is a doughnut-shaped chamber with strong magnets wrapped around it. Once the fuel is heated up, it is controlled with the help of these magnets, since the required temperatures (over 100 million degrees C) will separate the electrons from the nuclei, forming a plasma. Once the fusion reactions occur, excess binding energy is released as energetic neutrons, which are absorbed in water in order to produce steam that runs turbines. Keeping the power losses from the plasma low, thus allowing for a high number of reactions, is a challenge. Another challenge is related to the reactor materials, since the confinement of the plasma particles is not perfect, resulting in particle bombardment of the reactor walls and structures. Material erosion and activation as well as plasma contamination are expected. Adding to this, the high energy neutrons will cause radiation damage in the materials, causing, for instance, swelling and embrittlement. In this thesis, the behaviour of a material situated in a fusion reactor was studied using molecular dynamics simulations. Simulations of processes in the next generation fusion reactor ITER include the reactor materials beryllium, carbon and tungsten as well as the plasma hydrogen isotopes. This means that interaction models, {\it i.e. interatomic potentials}, for this complicated quaternary system are needed. The task of finding such potentials is nonetheless nearly at its end, since models for the beryllium-carbon-hydrogen interactions were constructed in this thesis and as a continuation of that work, a beryllium-tungsten model is under development. These potentials are combinable with the earlier tungsten-carbon-hydrogen ones. The potentials were used to explain the chemical sputtering of beryllium due to deuterium plasma exposure. During experiments, a large fraction of the sputtered beryllium atoms were observed to be released as BeD molecules, and the simulations identified the swift chemical sputtering mechanism, previously not believed to be important in metals, as the underlying mechanism. Radiation damage in the reactor structural materials vanadium, iron and iron chromium, as well as in the wall material tungsten and the mixed alloy tungsten carbide, was also studied in this thesis. Interatomic potentials for vanadium, tungsten and iron were modified to be better suited for simulating collision cascades that are formed during particle irradiation, and the potential features affecting the resulting primary damage were identified. Including the often neglected electronic effects in the simulations was also shown to have an impact on the damage. With proper tuning of the electron-phonon interaction strength, experimentally measured quantities related to ion-beam mixing in iron could be reproduced. The damage in tungsten carbide alloys showed elemental asymmetry, as the major part of the damage consisted of carbon defects. On the other hand, modelling the damage in the iron chromium alloy, essentially representing steel, showed that small additions of chromium do not noticeably affect the primary damage in iron. Since a complete assessment of the response of a material in a future full-scale fusion reactor is not achievable using only experimental techniques, molecular dynamics simulations are of vital help. This thesis has not only provided insight into complicated reactor processes and improved current methods, but also offered tools for further simulations. It is therefore an important step towards making fusion energy more than a future goal.

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Recently, it has been shown that fusion of the estimates of a set of sparse recovery algorithms result in an estimate better than the best estimate in the set, especially when the number of measurements is very limited. Though these schemes provide better sparse signal recovery performance, the higher computational requirement makes it less attractive for low latency applications. To alleviate this drawback, in this paper, we develop a progressive fusion based scheme for low latency applications in compressed sensing. In progressive fusion, the estimates of the participating algorithms are fused progressively according to the availability of estimates. The availability of estimates depends on computational complexity of the participating algorithms, in turn on their latency requirement. Unlike the other fusion algorithms, the proposed progressive fusion algorithm provides quick interim results and successive refinements during the fusion process, which is highly desirable in low latency applications. We analyse the developed scheme by providing sufficient conditions for improvement of CS reconstruction quality and show the practical efficacy by numerical experiments using synthetic and real-world data. (C) 2013 Elsevier B.V. All rights reserved.

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The restriction of the one dimensional (1D) master equation (ME) with the mass number of the projectile-like fragment as a variable is studied, and a two-dimensional (2D) master equation with the neutron and proton numbers as independent variables is set up, and solved numerically. Our study showed that the 2D ME can describe the fusion process well in all projectile-target combinations. Therefore the possible channels to synthesize super-heavy nuclei can be studied correctly in wider possibilities. The available condition for employing 1D ME is pointed out.

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We propose and advocate basic principles for the fusion of incomplete or uncertain information items, that should apply regardless of the formalism adopted for representing pieces of information coming from several sources. This formalism can be based on sets, logic, partial orders, possibility theory, belief functions or imprecise probabilities. We propose a general notion of information item representing incomplete or uncertain information about the values of an entity of interest. It is supposed to rank such values in terms of relative plausibility, and explicitly point out impossible values. Basic issues affecting the results of the fusion process, such as relative information content and consistency of information items, as well as their mutual consistency, are discussed. For each representation setting, we present fusion rules that obey our principles, and compare them to postulates specific to the representation proposed in the past. In the crudest (Boolean) representation setting (using a set of possible values), we show that the understanding of the set in terms of most plausible values, or in terms of non-impossible ones matters for choosing a relevant fusion rule. Especially, in the latter case our principles justify the method of maximal consistent subsets, while the former is related to the fusion of logical bases. Then we consider several formal settings for incomplete or uncertain information items, where our postulates are instantiated: plausibility orderings, qualitative and quantitative possibility distributions, belief functions and convex sets of probabilities. The aim of this paper is to provide a unified picture of fusion rules across various uncertainty representation settings.

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The results from applying a sensor fusion process to an adaptive controller used to balance all inverted pendulum axe presented. The goal of the sensor fusion process was to replace some of the four mechanical measurements, which are known to be sufficient inputs for a linear state feedback controller to balance the system, with optic flow variables. Results from research into the psychology of the sense of balance in humans were the motivation for the investigation of this new type of controller input. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described. The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training till-le for the adaptive controller and reduced performance (measured as the time the pendulum remains upright)

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Infrared polarization and intensity imagery provide complementary and discriminative information in image understanding and interpretation. In this paper, a novel fusion method is proposed by effectively merging the information with various combination rules. It makes use of both low-frequency and highfrequency images components from support value transform (SVT), and applies fuzzy logic in the combination process. Images (both infrared polarization and intensity images) to be fused are firstly decomposed into low-frequency component images and support value image sequences by the SVT. Then the low-frequency component images are combined using a fuzzy combination rule blending three sub-combination methods of (1) region feature maximum, (2) region feature weighting average, and (3) pixel value maximum; and the support value image sequences are merged using a fuzzy combination rule fusing two sub-combination methods of (1) pixel energy maximum and (2) region feature weighting. With the variables of two newly defined features, i.e. the low-frequency difference feature for low-frequency component images and the support-value difference feature for support value image sequences, trapezoidal membership functions are proposed and developed in tuning the fuzzy fusion process. Finally the fused image is obtained by inverse SVT operations. Experimental results of visual inspection and quantitative evaluation both indicate the superiority of the proposed method to its counterparts in image fusion of infrared polarization and intensity images.

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Anti-spoofing is attracting growing interest in biometrics, considering the variety of fake materials and new means to attack biometric recognition systems. New unseen materials continuously challenge state-of-the-art spoofing detectors, suggesting for additional systematic approaches to target anti-spoofing. By incorporating liveness scores into the biometric fusion process, recognition accuracy can be enhanced, but traditional sum-rule based fusion algorithms are known to be highly sensitive to single spoofed instances. This paper investigates 1-median filtering as a spoofing-resistant generalised alternative to the sum-rule targeting the problem of partial multibiometric spoofing where m out of n biometric sources to be combined are attacked. Augmenting previous work, this paper investigates the dynamic detection and rejection of livenessrecognition pair outliers for spoofed samples in true multi-modal configuration with its inherent challenge of normalisation. As a further contribution, bootstrap aggregating (bagging) classifiers for fingerprint spoof-detection algorithm is presented. Experiments on the latest face video databases (Idiap Replay- Attack Database and CASIA Face Anti-Spoofing Database), and fingerprint spoofing database (Fingerprint Liveness Detection Competition 2013) illustrate the efficiency of proposed techniques.

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Samples with a composition of 40InF 3-20ZnF 2-5MCl- xBaF 2-ySrF 2, where M=Na, Li and x+y=35 mol%, were prepared. The thermal properties related to the Ba/Sr ratio and to the remaining chlorine content in the glasses were studied. Thermal stability is improved with the addition of chlorine. However, chlorine concentration is regulated by the sublimation of indium fluorides which takes place at about 600°C. Indium fluorides arc formed during glass fusion. The mechanisms of chlorine sublimation were studied. © 2005 Akadémiai Kiadó, Budapest.

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Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth?s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.

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We recently established an in vitro assay that monitors the fusion between latex-bead phagosomes and endocytic organelles in the presence of J774 macrophage cytosol (Jahraus et al., 1998). Here, we show that different reagents affecting the actin cytoskeleton can either inhibit or stimulate this fusion process. Because the membranes of purified phagosomes can assemble F-actin de novo from pure actin with ATP (Defacque et al., 2000a), we focused here on the ability of membranes to nucleate actin in the presence of J774 cytosolic extracts. For this, we used F-actin sedimentation, pyrene actin assays, and torsional rheometry, a biophysical approach that could provide kinetic information on actin polymerization and gel formation. We make two major conclusions. First, under our standard in vitro conditions (4 mg/ml cytosol and 1 mM ATP), the presence of membranes actively catalyzed the assembly of cytosolic F-actin, which assembled into highly viscoelastic gels. A model is discussed that links these results to how the actin may facilitate fusion. Second, cytosolic actin paradoxically polymerized more under ATP depletion than under high-ATP conditions, even in the absence of membranes; we discuss these data in the context of the well described, large increases in F-actin seen in many cells during ischemia.

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Structural studies of viral membrane fusion proteins suggest that a “trimer-of-hairpins” motif plays a critical role in the membrane fusion process of many enveloped viruses. In this motif, a coiled coil (formed by homotrimeric association of the N-terminal regions of the protein) is surrounded by three C-terminal regions that pack against the coiled coil in an oblique antiparallel manner. The resulting trimer-of-hairpins structure serves to bring the viral and cellular membranes together for fusion. learncoil-vmf, a computational program developed to recognize coiled coil-like regions that form the trimer-of-hairpins motif, predicts these regions in the membrane fusion protein of the Visna virus. Peptides corresponding to the computationally identified sequences were synthesized, and the soluble core of the Visna membrane fusion protein was reconstituted in solution. Its crystal structure at 1.5-Å resolution demonstrates that a trimer-of-hairpins structure is formed. Remarkably, despite less than 23% sequence identity, the ectodomains in Visna and HIV-1 envelope glycoproteins show detailed structural conservation, especially within the area of a hydrophobic pocket in the central coiled coil currently being targeted for the development of new anti-HIV drugs.

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We propose a knowledge fusion architecture KnoFuss based on the application of problem-solving methods technology, which allows methods for subtasks of the fusion process to be combined and the best methods to be selected, depending on the domain and task at hand.

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Au cours des dernières décennies, l’effort sur les applications de capteurs infrarouges a largement progressé dans le monde. Mais, une certaine difficulté demeure, en ce qui concerne le fait que les objets ne sont pas assez clairs ou ne peuvent pas toujours être distingués facilement dans l’image obtenue pour la scène observée. L’amélioration de l’image infrarouge a joué un rôle important dans le développement de technologies de la vision infrarouge de l’ordinateur, le traitement de l’image et les essais non destructifs, etc. Cette thèse traite de la question des techniques d’amélioration de l’image infrarouge en deux aspects, y compris le traitement d’une seule image infrarouge dans le domaine hybride espacefréquence, et la fusion d’images infrarouges et visibles employant la technique du nonsubsampled Contourlet transformer (NSCT). La fusion d’images peut être considérée comme étant la poursuite de l’exploration du modèle d’amélioration de l’image unique infrarouge, alors qu’il combine les images infrarouges et visibles en une seule image pour représenter et améliorer toutes les informations utiles et les caractéristiques des images sources, car une seule image ne pouvait contenir tous les renseignements pertinents ou disponibles en raison de restrictions découlant de tout capteur unique de l’imagerie. Nous examinons et faisons une enquête concernant le développement de techniques d’amélioration d’images infrarouges, et ensuite nous nous consacrons à l’amélioration de l’image unique infrarouge, et nous proposons un schéma d’amélioration de domaine hybride avec une méthode d’évaluation floue de seuil amélioré, qui permet d’obtenir une qualité d’image supérieure et améliore la perception visuelle humaine. Les techniques de fusion d’images infrarouges et visibles sont établies à l’aide de la mise en oeuvre d’une mise en registre précise des images sources acquises par différents capteurs. L’algorithme SURF-RANSAC est appliqué pour la mise en registre tout au long des travaux de recherche, ce qui conduit à des images mises en registre de façon très précise et des bénéfices accrus pour le traitement de fusion. Pour les questions de fusion d’images infrarouges et visibles, une série d’approches avancées et efficaces sont proposés. Une méthode standard de fusion à base de NSCT multi-canal est présente comme référence pour les approches de fusion proposées suivantes. Une approche conjointe de fusion, impliquant l’Adaptive-Gaussian NSCT et la transformée en ondelettes (Wavelet Transform, WT) est propose, ce qui conduit à des résultats de fusion qui sont meilleurs que ceux obtenus avec les méthodes non-adaptatives générales. Une approche de fusion basée sur le NSCT employant la détection comprime (CS, compressed sensing) et de la variation totale (TV) à des coefficients d’échantillons clairsemés et effectuant la reconstruction de coefficients fusionnés de façon précise est proposée, qui obtient de bien meilleurs résultats de fusion par le biais d’une pré-amélioration de l’image infrarouge et en diminuant les informations redondantes des coefficients de fusion. Une procédure de fusion basée sur le NSCT utilisant une technique de détection rapide de rétrécissement itératif comprimé (fast iterative-shrinking compressed sensing, FISCS) est proposée pour compresser les coefficients décomposés et reconstruire les coefficients fusionnés dans le processus de fusion, qui conduit à de meilleurs résultats plus rapidement et d’une manière efficace.