983 resultados para large reservoirs
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A list of considerations on the problems with large groups. This material was sent to Debra Morris in 2007, by David Jaques, an educationist with many years' experience of working with groups.
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How the mathematical concept of Coarse Geometries is useful to analysing the Web
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This is one of a series of short case studies describing how academic tutors at the University of Southampton have made use of learning technologies to support their students.
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This is one of a series of short case studies describing how academic tutors at the University of Southampton have made use of learning technologies to support their students.
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El art??culo es un resumen de la propia autora sobre la conferencia realizada en la sede del CDL. Contiene una presentaci??n en catal??n, realizada por Aina Carreras
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This a short presentation which introduces how models and modelling help us to solve large scale problems in the real world. It introduces the idea that dynamic behaviour is caused by interacting components in the system. Feedback in the system makes behaviour prediction difficult unless we use modelling to support understanding
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The purpose of this expository arti le is to present a self- ontained overview of some results on the hara terization of the optimal value fun tion of a sto hasti target problem as (dis ontinuous) vis osity solution of a ertain dynami programming PDE and its appli ation to the problem of hedging ontingent laims in the presen e of portfolio onstraints and large investors
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Este es un manual diseñado para profesores de clases de niveles múltiples de gran tamaño. Contiene una serie de actividades especialmente creadas para hacer frente a todas las dificultades que surgen en este contexto. Muchas actividades pueden ser utilizadas con éxito también en clases más pequeñas y más homogéneas. Las actividades están seleccionadas según un criterio diferente: cómo despertar el interés de los estudiantes; cómo personalizar e individualizar su trabajo; cómo promover la colaboración; cómo hacer que los estudiantes tomen conciencia de su aprendizaje; cómo lograr una gestión positiva de clase. El autor señala cómo la variedad también puede conducir al desorden y lo importante que es crear y respetar las normas y rutinas, cruciales para la buena gestión de la clase. No se olvida de crear un sentido de pertenencia a un grupo, que es extremadamente importante en las clases grandes, donde los estudiantes tímidos o más débiles podrían sentirse excluidos. El trabajo en grupo se mezcla con el trabajo individual y una vez más el autor demuestra ser comprensivo hacia los sentimientos de los estudiantes, fomenta la individualización y la personalización, junto con actividades de grupo. Las actividades siempre están diseñadas para mantener un equilibrio entre individuo y grupo. El profesor dirige el grupo, mantiene todo bajo control y es el punto de referencia para todos los estudiantes, y al mismo tiempo interactúa con el grupo. De hecho los estudiantes de nivel superior pueden llegar a ser de gran ayuda para los más débiles, creando así una especie de cadena de aprendizaje. Muchas actividades están destinadas a que los estudiantes tomen conciencia de sus estilos de aprendizaje y sean responsables de su propio aprendizaje, y para evaluar su propio progreso.
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A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,...,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0={T0egy, T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates KS with attributes above T1≤T0. An eigenproblem of dimension d0+d1 for S0+S 1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j≥2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson's eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0, 1, 2,...,R} regulate accuracy; for large-dimensional S, high accuracy requires S 0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24 × 106, involving 1.2 × 1012 nonzero matrix elements, and 8.4×109 Slater determinants
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A general reduced dimensionality finite field nuclear relaxation method for calculating vibrational nonlinear optical properties of molecules with large contributions due to anharmonic motions is introduced. In an initial application to the umbrella (inversion) motion of NH3 it is found that difficulties associated with a conventional single well treatment are overcome and that the particular definition of the inversion coordinate is not important. Future applications are described
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Large scale image mosaicing methods are in great demand among scientists who study different aspects of the seabed, and have been fostered by impressive advances in the capabilities of underwater robots in gathering optical data from the seafloor. Cost and weight constraints mean that lowcost Remotely operated vehicles (ROVs) usually have a very limited number of sensors. When a low-cost robot carries out a seafloor survey using a down-looking camera, it usually follows a predetermined trajectory that provides several non time-consecutive overlapping image pairs. Finding these pairs (a process known as topology estimation) is indispensable to obtaining globally consistent mosaics and accurate trajectory estimates, which are necessary for a global view of the surveyed area, especially when optical sensors are the only data source. This thesis presents a set of consistent methods aimed at creating large area image mosaics from optical data obtained during surveys with low-cost underwater vehicles. First, a global alignment method developed within a Feature-based image mosaicing (FIM) framework, where nonlinear minimisation is substituted by two linear steps, is discussed. Then, a simple four-point mosaic rectifying method is proposed to reduce distortions that might occur due to lens distortions, error accumulation and the difficulties of optical imaging in an underwater medium. The topology estimation problem is addressed by means of an augmented state and extended Kalman filter combined framework, aimed at minimising the total number of matching attempts and simultaneously obtaining the best possible trajectory. Potential image pairs are predicted by taking into account the uncertainty in the trajectory. The contribution of matching an image pair is investigated using information theory principles. Lastly, a different solution to the topology estimation problem is proposed in a bundle adjustment framework. Innovative aspects include the use of fast image similarity criterion combined with a Minimum spanning tree (MST) solution, to obtain a tentative topology. This topology is improved by attempting image matching with the pairs for which there is the most overlap evidence. Unlike previous approaches for large-area mosaicing, our framework is able to deal naturally with cases where time-consecutive images cannot be matched successfully, such as completely unordered sets. Finally, the efficiency of the proposed methods is discussed and a comparison made with other state-of-the-art approaches, using a series of challenging datasets in underwater scenarios
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The first part of this work presents an accurate analysis of the most relevant 3D registration techniques, including initial pose estimation, pairwise registration and multiview registration strategies. A new classification has been proposed, based on both the applications and the approach of the methods that have been discussed. The main contribution of this thesis is the proposal of a new 3D multiview registration strategy. The proposed approach detects revisited regions obtaining cycles of views that are used to reduce the inaccuracies that may exist in the final model due to error propagation. The method takes advantage of both global and local information of the registration process, using graph theory techniques in order correlate multiple views and minimize the propagated error by registering the views in an optimal way. The proposed method has been tested using both synthetic and real data, in order to show and study its behavior and demonstrate its reliability.
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This thesis studies robustness against large-scale failures in communications networks. If failures are isolated, they usually go unnoticed by users thanks to recovery mechanisms. However, such mechanisms are not effective against large-scale multiple failures. Large-scale failures may cause huge economic loss. A key requirement towards devising mechanisms to lessen their impact is the ability to evaluate network robustness. This thesis focuses on multilayer networks featuring separated control and data planes. The majority of the existing measures of robustness are unable to capture the true service degradation in such a setting, because they rely on purely topological features. One of the major contributions of this thesis is a new measure of functional robustness. The failure dynamics is modeled from the perspective of epidemic spreading, for which a new epidemic model is proposed. Another contribution is a taxonomy of multiple, large-scale failures, adapted to the needs and usage of the field of networking.
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The high level of realism and interaction in many computer graphic applications requires techniques for processing complex geometric models. First, we present a method that provides an accurate low-resolution approximation from a multi-chart textured model that guarantees geometric fidelity and correct preservation of the appearance attributes. Then, we introduce a mesh structure called Compact Model that approximates dense triangular meshes while preserving sharp features, allowing adaptive reconstructions and supporting textured models. Next, we design a new space deformation technique called *Cages based on a multi-level system of cages that preserves the smoothness of the mesh between neighbouring cages and is extremely versatile, allowing the use of heterogeneous sets of coordinates and different levels of deformation. Finally, we propose a hybrid method that allows to apply any deformation technique on large models obtaining high quality results with a reduced memory footprint and a high performance.
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Els sistemes aquàtics continental representen un dels ecosistemes més amenaçats a nivell mundial, com a conseqüència de l'ús intensiu quel'home en fa. La conca del Guadiana no està lliure d'aquestes pressions antròpiques. Les grans infraestructures hidràuliques i l'escorrentia provinent de l'agricultura són només exemples dels greus problemes que pateix la conca. Aquests problemes es fan especialment palesos en la zona alta de la conca, on l'escassetat d'aigua no fa més que agreujar el problema.Tot això ha generat la necessitat urgent d'avaluar l'estat de conservació d'aquests ecosistemes aquàtics continentals, poder determinar la mesura i la magnitud de les pertorbacions que els estan afectant i així proposar mesures de gestió destinades a restaurar-ne la integritat ecològica. El principal objectiu que presenta aquest és determinar els patrons de distribució de les comunitats de algals (amb una menció especial en el grup de les diatomees) i de les seves causes en la conca del Guadiana i associades, amb la finalitat d'establir i proposar eines que permetin avaluar l'estat de conservació de les masses d'aigua d'aquestes conques.