997 resultados para estimation des provisions


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The Mid Miocene marine formations of Salles area (former "Sallomacian" stage) have been studied again from numerous outcrops and cores. The deep structural framework influences notably of the characteristics and distribution of the deposits, which are neritic. The stratigraphy is stated precisely thanks to the planktonic fauna and floradetailed examination (probably Serravallian zones NN6 - N12). Several paleobiofacies are reconstituted from the rich invertebrate faunas, which give also paleoclimatic data.

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Trabalho de Projecto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Teatro e Comunidade.

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Similarly to other organisms, Vertebrates changed during the Cenozoic Era. Mammals are the only ones to change quickly; their well mineralised bones and teeth are often fossilised. They are highly diverse and even isolated teeth can be identified. They are thus a good tool for establishing a biochronological framewoork. Among Mammals, Rodents with a short lifetime evolve more quickly than the large Mammals. In Europe, the first elaborated zonation was investigated by the Regional Committee on Neogene Stratigraphy and issued as the MN Zonation (Mammals Neogene) by Mein, 1976. During the following years, progress in knowledge lead to new charts. The latest one resulted from collective work (de Bruijn et al., 1992). Bîochronology gives relative data; if we desire to have numerical age estimates, we must correlate these results with radiometrie data, marine biostratigraphîcal units or the Geomagnetic Polarity Time Scale. For Europe, these results are summarised by Steininger et al. (1989-1996) and Steininger (1999). After some recents developments on MN Zonation, here is discussed the succession of Neogene small mammals Portuguese localities. Fortunately these localities are in majority inbedded in marine context. Their assigment to MN Zones is proposed and correlations with the spanish Aragonian Scale (Daams el al., 1999) are also suggested. In fact, some differences appear between Portugal and Aragonian assemblages, probably for ecological reasons. Therefore, the MN zonation is always useful for short and long distance biochronological correlations.

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The Domerian sections from the Lusitanian Basin of São Pedro de Muel, Rabaçal and Tomar have provided us with more than 1100 Ostracods belonging from 18 genus and about 48 species. The faunal diversity and density of the associations decrease in space (from Tomar to Rabaçal and São Pedro de Muel) and time, with favourable environments for the proliferation of Ostracods at the lower part of the sections (Stokesi subzone) and more hostile at the upper part (Ragazzonii subzone). The Monestieri and Nitescens horizons and the Subnodosus subzone are characterized by a typical assemblage of Ostracods. The palaeoecological Ostracod indexes reveal the fluctuations of the oxygenation, temperature, depth and hydrodynamism of the water, on the different sections and on the whole platform. They display a diachronous cooling in the Lower Domerian series. In the upper part of the Middle and in the Upper Domerian, the deeper, less oxygenated and cooler waters prevent the development of the Ostracod faunas.

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Les années quatre-vingt signalent un point de bascule dans et une mutation majeure dans les caractéristiques narratives de la littérature française. D’une certaine façon, elles entament la contemporanéité littéraire telle que nous la connaissons du point de vue critique. Nous insisterons sur le rôle des revues et des éditoriaux dans ce processus. Ils manifestent quelques hésitations de la critique par rapport à la littérature naissante.

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This fascicle, dedicated to the Domerian (Late Pliensbachian) ammonites faunas, is the third part of the “Atlas des fossiles caractéristiques du Lias portugais“. It follows two previous publications about the Hettangian-Sinemurian and the Carixian (Lower fifty species are concisely described and illustrated. The other groups (nautilids, belemnites, brachiopods, bivalvia...) will be published afterwards. The principal objective of the “Atlas des fossiles caractéristiques du Lias portugais“ is to make the main liassic lusitanian fossils known to a wide public. It also aims to support field studies by giving a rich iconography dedicated to the lusitanian invertebrate macrofaunas. In the case of the ammonites, all the species are described and the “Atlas” can be used as an exhaustive database for biostratigraphic and paleobiogeographic studies.

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In this work, we present results from teleseismic P-wave receiver functions (PRFs) obtained in Portugal, Western Iberia. A dense seismic station deployment conducted between 2010 and 2012, in the scope of the WILAS project and covering the entire country, allowed the most spatially extensive probing on the bulk crustal seismic properties of Portugal up to date. The application of the H-κ stacking algorithm to the PRFs enabled us to estimate the crustal thickness (H) and the average crustal ratio of the P- and S-waves velocities V p/V s (κ) for the region. Observations of Moho conversions indicate that this interface is relatively smooth with the crustal thickness ranging between 24 and 34 km, with an average of 30 km. The highest V p/V s values are found on the Mesozoic-Cenozoic crust beneath the western and southern coastal domain of Portugal, whereas the lowest values correspond to Palaeozoic crust underlying the remaining part of the subject area. An average V p/V s is found to be 1.72, ranging 1.63-1.86 across the study area, indicating a predominantly felsic composition. Overall, we systematically observe a decrease of V p/V s with increasing crustal thickness. Taken as a whole, our results indicate a clear distinction between the geological zones of the Variscan Iberian Massif in Portugal, the overall shape of the anomalies conditioned by the shape of the Ibero-Armorican Arc, and associated Late Paleozoic suture zones, and the Meso-Cenozoic basin associated with Atlantic rifting stages. Thickened crust (30-34 km) across the studied region may be inherited from continental collision during the Paleozoic Variscan orogeny. An anomalous crustal thinning to around 28 km is observed beneath the central part of the Central Iberian Zone and the eastern part of South Portuguese Zone.

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A new algorithm for the velocity vector estimation of moving ships using Single Look Complex (SLC) SAR data in strip map acquisition mode is proposed. The algorithm exploits both amplitude and phase information of the Doppler decompressed data spectrum, with the aim to estimate both the azimuth antenna pattern and the backscattering coefficient as function of the look angle. The antenna pattern estimation provides information about the target velocity; the backscattering coefficient can be used for vessel classification. The range velocity is retrieved in the slow time frequency domain by estimating the antenna pattern effects induced by the target motion, while the azimuth velocity is calculated by the estimated range velocity and the ship orientation. Finally, the algorithm is tested on simulated SAR SLC data.

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This paper extents the by now classic sensor fusion complementary filter (CF) design, involving two sensors, to the case where three sensors that provide measurements in different bands are available. This paper shows that the use of classical CF techniques to tackle a generic three sensors fusion problem, based solely on their frequency domain characteristics, leads to a minimal realization, stable, sub-optimal solution, denoted as Complementary Filters3 (CF3). Then, a new approach for the estimation problem at hand is used, based on optimal linear Kalman filtering techniques. Moreover, the solution is shown to preserve the complementary property, i.e. the sum of the three transfer functions of the respective sensors add up to one, both in continuous and discrete time domains. This new class of filters are denoted as Complementary Kalman Filters3 (CKF3). The attitude estimation of a mobile robot is addressed, based on data from a rate gyroscope, a digital compass, and odometry. The experimental results obtained are reported.

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This paper presents an ankle mounted Inertial Navigation System (INS) used to estimate the distance traveled by a pedestrian. This distance is estimated by the number of steps given by the user. The proposed method is based on force sensors to enhance the results obtained from an INS. Experimental results have shown that, depending on the step frequency, the traveled distance error varies between 2.7% and 5.6%.

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This paper addresses the estimation of surfaces from a set of 3D points using the unified framework described in [1]. This framework proposes the use of competitive learning for curve estimation, i.e., a set of points is defined on a deformable curve and they all compete to represent the available data. This paper extends the use of the unified framework to surface estimation. It o shown that competitive learning performes better than snakes, improving the model performance in the presence of concavities and allowing to desciminate close surfaces. The proposed model is evaluated in this paper using syntheticdata and medical images (MRI and ultrasound images).

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Dimensionality reduction plays a crucial role in many hyperspectral data processing and analysis algorithms. This paper proposes a new mean squared error based approach to determine the signal subspace in hyperspectral imagery. The method first estimates the signal and noise correlations matrices, then it selects the subset of eigenvalues that best represents the signal subspace in the least square sense. The effectiveness of the proposed method is illustrated using simulated and real hyperspectral images.

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As it is widely known, in structural dynamic applications, ranging from structural coupling to model updating, the incompatibility between measured and simulated data is inevitable, due to the problem of coordinate incompleteness. Usually, the experimental data from conventional vibration testing is collected at a few translational degrees of freedom (DOF) due to applied forces, using hammer or shaker exciters, over a limited frequency range. Hence, one can only measure a portion of the receptance matrix, few columns, related to the forced DOFs, and rows, related to the measured DOFs. In contrast, by finite element modeling, one can obtain a full data set, both in terms of DOFs and identified modes. Over the years, several model reduction techniques have been proposed, as well as data expansion ones. However, the latter are significantly fewer and the demand for efficient techniques is still an issue. In this work, one proposes a technique for expanding measured frequency response functions (FRF) over the entire set of DOFs. This technique is based upon a modified Kidder's method and the principle of reciprocity, and it avoids the need for modal identification, as it uses the measured FRFs directly. In order to illustrate the performance of the proposed technique, a set of simulated experimental translational FRFs is taken as reference to estimate rotational FRFs, including those that are due to applied moments.

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Given an hyperspectral image, the determination of the number of endmembers and the subspace where they live without any prior knowledge is crucial to the success of hyperspectral image analysis. This paper introduces a new minimum mean squared error based approach to infer the signal subspace in hyperspectral imagery. The method, termed hyperspectral signal identification by minimum error (HySime), is eigendecomposition based and it does not depend on any tuning parameters. It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.

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In hyperspectral imagery a pixel typically consists mixture of spectral signatures of reference substances, also called endmembers. Linear spectral mixture analysis, or linear unmixing, aims at estimating the number of endmembers, their spectral signatures, and their abundance fractions. This paper proposes a framework for hyperpsectral unmixing. A blind method (SISAL) is used for the estimation of the unknown endmember signature and their abundance fractions. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The proposed framework simultaneously estimates the number of endmembers present in the hyperspectral image by an algorithm based on the minimum description length (MDL) principle. Experimental results on both synthetic and real hyperspectral data demonstrate the effectiveness of the proposed algorithm.