954 resultados para decentralised data fusion


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George V Land (Antarctica) includes the boundary between Late Archean-Paleoproterozoic metamorphic terrains of the East Antarctic craton and the intrusive and metasedimentary rocks of the Early Paleozoic Ross-Delamerian Orogen. This therefore represents a key region for understanding the tectono-metamorphic evolution of the East Antarctic Craton and the Ross Orogen and for defining their structural relationship in East Antarctica, with potential implications for Gondwana reconstructions. In the East Antarctic Craton the outcrops closest to the Ross orogenic belt form the Mertz Shear Zone, a prominent ductile shear zone up to 5 km wide. Its deformation fabric includes a series of progressive, overprinting shear structures developed under different metamorphic conditions: from an early medium-P granulite-facies metamorphism, through amphibolite-facies to late greenschist-facies conditions. 40Ar-39Ar laserprobe data on biotite in mylonitic rocks from the Mertz Shear Zone indicate that the minimum age for ductile deformation under greenschist-facies conditions is 1502 ± 9 Ma and reveal no evidence of reactivation processes linked to the Ross Orogeny. 40Ar-39Ar laserprobe data on amphibole, although plagued by excess argon, suggest the presence of a ~1.7 Ga old phase of regional-scale retrogression under amphibolite-facies conditions. Results support the correlation between the East Antarctic Craton in the Mertz Glacier area and the Sleaford Complex of the Gawler Craton in southern Australia, and suggest that the Mertz Shear Zone may be considered a correlative of the Kalinjala Shear Zone. An erratic immature metasandstone collected east of Ninnis Glacier (~180 km east of the Mertz Glacier) and petrographically similar to metasedimentary rocks enclosed as xenoliths in Cambro-Ordovician granites cropping out along the western side of Ninnis Glacier, yielded detrital white-mica 40Ar-39Ar ages from ~530 to 640 Ma and a minimum age of 518 ± 5 Ma. This pattern compares remarkably well with those previously obtained for the Kanmantoo Group from the Adelaide Rift Complex of southern Australia, thereby suggesting that the segment of the Ross Orogen exposed east of the Mertz Glacier may represent a continuation of the eastern part of the Delamerian Orogen.

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This work is aimed to present the main differences of nuclear data uncertainties among three different nuclear data libraries: EAF-2007, EAF-2010 and SCALE-6.0, under different neutron spectra: LWR, ADS and DEMO (fusion)

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We present a novel approach using both sustained vowels and connected speech, to detect obstructive sleep apnea (OSA) cases within a homogeneous group of speakers. The proposed scheme is based on state-of-the-art GMM-based classifiers, and acknowledges specifically the way in which acoustic models are trained on standard databases, as well as the complexity of the resulting models and their adaptation to specific data. Our experimental database contains a suitable number of utterances and sustained speech from healthy (i.e control) and OSA Spanish speakers. Finally, a 25.1% relative reduction in classification error is achieved when fusing continuous and sustained speech classifiers. Index Terms: obstructive sleep apnea (OSA), gaussian mixture models (GMMs), background model (BM), classifier fusion.

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EURATOM/CIEMAT and Technical University of Madrid (UPM) have been involved in the development of a FPSC [1] (Fast Plant System Control) prototype for ITER, based on PXIe (PCI eXtensions for Instrumentation). One of the main focuses of this project has been data acquisition and all the related issues, including scientific data archiving. Additionally, a new data archiving solution has been developed to demonstrate the obtainable performances and possible bottlenecks of scientific data archiving in Fast Plant System Control. The presented system implements a fault tolerant architecture over a GEthernet network where FPSC data are reliably archived on remote, while remaining accessible to be redistributed, within the duration of a pulse. The storing service is supported by a clustering solution to guaranty scalability, so that FPSC management and configuration may be simplified, and a unique view of all archived data provided. All the involved components have been integrated under EPICS [2] (Experimental Physics and Industrial Control System), implementing in each case the necessary extensions, state machines and configuration process variables. The prototyped solution is based on the NetCDF-4 [3] and [4] (Network Common Data Format) file format in order to incorporate important features, such as scientific data models support, huge size files management, platform independent codification, or single-writer/multiple-readers concurrency. In this contribution, a complete description of the above mentioned solution is presented, together with the most relevant results of the tests performed, while focusing in the benefits and limitations of the applied technologies.

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Los sensores inerciales (acelerómetros y giróscopos) se han ido introduciendo poco a poco en dispositivos que usamos en nuestra vida diaria gracias a su minituarización. Hoy en día todos los smartphones contienen como mínimo un acelerómetro y un magnetómetro, siendo complementados en losmás modernos por giróscopos y barómetros. Esto, unido a la proliferación de los smartphones ha hecho viable el diseño de sistemas basados en las medidas de sensores que el usuario lleva colocados en alguna parte del cuerpo (que en un futuro estarán contenidos en tejidos inteligentes) o los integrados en su móvil. El papel de estos sensores se ha convertido en fundamental para el desarrollo de aplicaciones contextuales y de inteligencia ambiental. Algunos ejemplos son el control de los ejercicios de rehabilitación o la oferta de información referente al sitio turístico que se está visitando. El trabajo de esta tesis contribuye a explorar las posibilidades que ofrecen los sensores inerciales para el apoyo a la detección de actividad y la mejora de la precisión de servicios de localización para peatones. En lo referente al reconocimiento de la actividad que desarrolla un usuario, se ha explorado el uso de los sensores integrados en los dispositivos móviles de última generación (luz y proximidad, acelerómetro, giróscopo y magnetómetro). Las actividades objetivo son conocidas como ‘atómicas’ (andar a distintas velocidades, estar de pie, correr, estar sentado), esto es, actividades que constituyen unidades de actividades más complejas como pueden ser lavar los platos o ir al trabajo. De este modo, se usan algoritmos de clasificación sencillos que puedan ser integrados en un móvil como el Naïve Bayes, Tablas y Árboles de Decisión. Además, se pretende igualmente detectar la posición en la que el usuario lleva el móvil, no sólo con el objetivo de utilizar esa información para elegir un clasificador entrenado sólo con datos recogidos en la posición correspondiente (estrategia que mejora los resultados de estimación de la actividad), sino también para la generación de un evento que puede producir la ejecución de una acción. Finalmente, el trabajo incluye un análisis de las prestaciones de la clasificación variando el tipo de parámetros y el número de sensores usados y teniendo en cuenta no sólo la precisión de la clasificación sino también la carga computacional. Por otra parte, se ha propuesto un algoritmo basado en la cuenta de pasos utilizando informaiii ción proveniente de un acelerómetro colocado en el pie del usuario. El objetivo final es detectar la actividad que el usuario está haciendo junto con la estimación aproximada de la distancia recorrida. El algoritmo de cuenta pasos se basa en la detección de máximos y mínimos usando ventanas temporales y umbrales sin requerir información específica del usuario. El ámbito de seguimiento de peatones en interiores es interesante por la falta de un estándar de localización en este tipo de entornos. Se ha diseñado un filtro extendido de Kalman centralizado y ligeramente acoplado para fusionar la información medida por un acelerómetro colocado en el pie del usuario con medidas de posición. Se han aplicado también diferentes técnicas de corrección de errores como las de velocidad cero que se basan en la detección de los instantes en los que el pie está apoyado en el suelo. Los resultados han sido obtenidos en entornos interiores usando las posiciones estimadas por un sistema de triangulación basado en la medida de la potencia recibida (RSS) y GPS en exteriores. Finalmente, se han implementado algunas aplicaciones que prueban la utilidad del trabajo desarrollado. En primer lugar se ha considerado una aplicación de monitorización de actividad que proporciona al usuario información sobre el nivel de actividad que realiza durante un período de tiempo. El objetivo final es favorecer el cambio de comportamientos sedentarios, consiguiendo hábitos saludables. Se han desarrollado dos versiones de esta aplicación. En el primer caso se ha integrado el algoritmo de cuenta pasos en una plataforma OSGi móvil adquiriendo los datos de un acelerómetro Bluetooth colocado en el pie. En el segundo caso se ha creado la misma aplicación utilizando las implementaciones de los clasificadores en un dispositivo Android. Por otro lado, se ha planteado el diseño de una aplicación para la creación automática de un diario de viaje a partir de la detección de eventos importantes. Esta aplicación toma como entrada la información procedente de la estimación de actividad y de localización además de información almacenada en bases de datos abiertas (fotos, información sobre sitios) e información sobre sensores reales y virtuales (agenda, cámara, etc.) del móvil. Abstract Inertial sensors (accelerometers and gyroscopes) have been gradually embedded in the devices that people use in their daily lives thanks to their miniaturization. Nowadays all smartphones have at least one embedded magnetometer and accelerometer, containing the most upto- date ones gyroscopes and barometers. This issue, together with the fact that the penetration of smartphones is growing steadily, has made possible the design of systems that rely on the information gathered by wearable sensors (in the future contained in smart textiles) or inertial sensors embedded in a smartphone. The role of these sensors has become key to the development of context-aware and ambient intelligent applications. Some examples are the performance of rehabilitation exercises, the provision of information related to the place that the user is visiting or the interaction with objects by gesture recognition. The work of this thesis contributes to explore to which extent this kind of sensors can be useful to support activity recognition and pedestrian tracking, which have been proven to be essential for these applications. Regarding the recognition of the activity that a user performs, the use of sensors embedded in a smartphone (proximity and light sensors, gyroscopes, magnetometers and accelerometers) has been explored. The activities that are detected belong to the group of the ones known as ‘atomic’ activities (e.g. walking at different paces, running, standing), that is, activities or movements that are part of more complex activities such as doing the dishes or commuting. Simple, wellknown classifiers that can run embedded in a smartphone have been tested, such as Naïve Bayes, Decision Tables and Trees. In addition to this, another aim is to estimate the on-body position in which the user is carrying the mobile phone. The objective is not only to choose a classifier that has been trained with the corresponding data in order to enhance the classification but also to start actions. Finally, the performance of the different classifiers is analysed, taking into consideration different features and number of sensors. The computational and memory load of the classifiers is also measured. On the other hand, an algorithm based on step counting has been proposed. The acceleration information is provided by an accelerometer placed on the foot. The aim is to detect the activity that the user is performing together with the estimation of the distance covered. The step counting strategy is based on detecting minima and its corresponding maxima. Although the counting strategy is not innovative (it includes time windows and amplitude thresholds to prevent under or overestimation) no user-specific information is required. The field of pedestrian tracking is crucial due to the lack of a localization standard for this kind of environments. A loosely-coupled centralized Extended Kalman Filter has been proposed to perform the fusion of inertial and position measurements. Zero velocity updates have been applied whenever the foot is detected to be placed on the ground. The results have been obtained in indoor environments using a triangulation algorithm based on RSS measurements and GPS outdoors. Finally, some applications have been designed to test the usefulness of the work. The first one is called the ‘Activity Monitor’ whose aim is to prevent sedentary behaviours and to modify habits to achieve desired objectives of activity level. Two different versions of the application have been implemented. The first one uses the activity estimation based on the step counting algorithm, which has been integrated in an OSGi mobile framework acquiring the data from a Bluetooth accelerometer placed on the foot of the individual. The second one uses activity classifiers embedded in an Android smartphone. On the other hand, the design of a ‘Travel Logbook’ has been planned. The input of this application is the information provided by the activity and localization modules, external databases (e.g. pictures, points of interest, weather) and mobile embedded and virtual sensors (agenda, camera, etc.). The aim is to detect important events in the journey and gather the information necessary to store it as a journal page.

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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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This work is aimed to present the main differences of nuclear data uncertainties among three different nuclear data libraries: EAF-2007, EAF-2010 and SCALE-6.0, under different neutron spectra: LWR, ADS and DEMO (fusion). To take into account the neutron spectrum, the uncertainty data are collapsed to onegroup. That is a simple way to see the differences among libraries for one application. Also, the neutron spectrum effect on different applications can be observed. These comparisons are presented only for (n,fission), (n,gamma) and (n,p) reactions, for the main transuranic isotopes (234,235,236,238U, 237Np, 238,239,240,241Pu, 241,242m,243Am, 242,243,244,245,246,247,248Cm, 249Bk, 249,250,251,252Cf). But also general comparisons among libraries are presented taking into account all included isotopes. In other works, target accuracies are presented for nuclear data uncertainties; here, these targets are compared with uncertainties on the above libraries. The main results of these comparisons are that EAF-2010 has reduced their uncertainties for many isotopes from EAF-2007 for (n,gamma) and (n,fission) but not for (n,p); SCALE-6.0 gives lower uncertainties for (n,fission) reactions for ADS and PWR applications, but gives higher uncertainties for (n,p) reactions in all applications. For the (n,gamma) reaction, the amount of isotopes which have higher uncertainties is quite similar to the amount of isotopes which have lower uncertainties when SCALE-6.0 and EAF-2010 are compared. When the effect of neutron spectra is analysed, the ADS neutron spectrum obtained the highest uncertainties for (n,gamma) and (n,fission) reactions of all libraries.

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The elemental distribution for as-received (AR), H implanted (AI) and post-implanted annealed (A) Eurofer and ODS-Eurofer steels has been characterized by means of micro Particle Induced X-ray Emission (μ-PIXE), micro Elastic Recoil Detection (μ-ERD) and Secondary Ion Mass Spectrometry (SIMS). The temperature and time-induced H diffusion has been analyzed by Resonance Nuclear Reaction Analysis (RNRA), Thermal Desorption Spectroscopy (TDS), ERDA and SIMS techniques. μ-PIXE measurements point out the presence of inhomogeneities in the Y distribution for ODS-Eurofer samples. RNRA and SIMS experiments evidence that hydrogen easily outdiffuses in these steels even at room temperature. ERD data show that annealing at temperatures as low as 300 °C strongly accelerates the hydrogen diffusion process, driving out up to the 90% of the initial hydrogen.

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This paper addresses the question of maximizing classifier accuracy for classifying task-related mental activity from Magnetoencelophalography (MEG) data. We propose the use of different sources of information and introduce an automatic channel selection procedure. To determine an informative set of channels, our approach combines a variety of machine learning algorithms: feature subset selection methods, classifiers based on regularized logistic regression, information fusion, and multiobjective optimization based on probabilistic modeling of the search space. The experimental results show that our proposal is able to improve classification accuracy compared to approaches whose classifiers use only one type of MEG information or for which the set of channels is fixed a priori.

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One of the key scrutiny issues of new coming energy era would be the environmental impact of fusion facilities managing one kg of tritium. The potential change of committed dose regulatory limits together with the implementation of nuclear design principles (As Low as Reasonably achievable - ALARA -, Defense in Depth -D-i-D-) for fusion facilities could strongly impact on the cost of deployment of coming fusion technology. Accurate modeling of environmental tritium transport forms (HT, HTO) for the assessment of fusion facility dosimetric impact in Accidental case appears as of major interest. This paper considers different short-term releases of tritium forms (HT and HTO) to the atmosphere from a potential fusion reactor located in the Mediterranean Basin. This work models in detail the dispersion of tritium forms and dosimetric impact of selected environmental patterns both inland and in-sea using real topography and forecast meteorological data-fields (ECMWF/FLEXPART). We explore specific values of this ratio in different levels and we examine the influence of meteorological conditions in the HTO behavior for 24 hours. For this purpose we have used a tool which consists on a coupled Lagrangian ECMWF/FLEXPART model useful to follow real time releases of tritium at 10, 30 and 60 meters together with hourly observations of wind (and in some cases precipitations) to provide a short-range approximation of tritium cloud behavior. We have assessed inhalation doses. And also HTO/HT ratios in a representative set of cases during winter 2010 and spring 2011 for the 3 air levels.