Online Discussions for Large Cohorts - Ian Harwood

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.

Large heterogeneous classes. 'Clases heterog??neas'

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

Modelling for Problem Solving in the Large

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

Dynamic programming for stochastic target problems, Viscosity solutions and hedging in markets with Portfolio constraints and large investors

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

Teaching large multilevel classes.

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.

Select-divide-and-conquer method for large-scale configuration interaction

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

Treatment of nonlinear optical properties due to large amplitude anharmonic vibrational motions: umbrella motion in NH3

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

Anàlisi geomètrica del Diaclasat de les Guilleries en el sector de la Vall del Ter entre els embassaments del Pasteral i Susqueda (Girona)

The Guilleries are a small and mountainous area located in the north-westem part of the Catalonian Coastal Ranges where metamorphic and igneous Paleozoic rocks are exposed. After the main hercynian folding this area was affected by a brittle deformation that is mainly manifested by the intrusion of a very large number of dykes of granodiorite and the development of a complex joint system. Trends of dykes indicate that their intrusion was related to a SE-NW extension, whose estimated value is 40% on an average. This extension seems to stand, although without any associated igneous event, with the development of NE-SW directed joints which make the main set. Five families more were developed later, one gently-dipping and fou upright; the latter trending roughly SE-NW, ENE-WSW, ESE-WNW and N-S. AU the joint sets appear in the metasedimentary Paleozoic rocks and in the hercynian intrusive bodies. Concerning the ages, joints that belong to the NE-SW and SE-NW directed sets and also those slightly dipping have been attributed to the late-hercynian times and all the other are considered to be later

Efficient topology estimation for large scale optical mapping

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

Large-Scale Surface registration

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.

Robustness against large-scale failures in communications networks

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.

Image classification for a large number of object categories

L'increment de bases de dades que cada vegada contenen imatges més difícils i amb un nombre més elevat de categories, està forçant el desenvolupament de tècniques de representació d'imatges que siguin discriminatives quan es vol treballar amb múltiples classes i d'algorismes que siguin eficients en l'aprenentatge i classificació. Aquesta tesi explora el problema de classificar les imatges segons l'objecte que contenen quan es disposa d'un gran nombre de categories. Primerament s'investiga com un sistema híbrid format per un model generatiu i un model discriminatiu pot beneficiar la tasca de classificació d'imatges on el nivell d'anotació humà sigui mínim. Per aquesta tasca introduïm un nou vocabulari utilitzant una representació densa de descriptors color-SIFT, i desprès s'investiga com els diferents paràmetres afecten la classificació final. Tot seguit es proposa un mètode par tal d'incorporar informació espacial amb el sistema híbrid, mostrant que la informació de context es de gran ajuda per la classificació d'imatges. Desprès introduïm un nou descriptor de forma que representa la imatge segons la seva forma local i la seva forma espacial, tot junt amb un kernel que incorpora aquesta informació espacial en forma piramidal. La forma es representada per un vector compacte obtenint un descriptor molt adequat per ésser utilitzat amb algorismes d'aprenentatge amb kernels. Els experiments realitzats postren que aquesta informació de forma te uns resultats semblants (i a vegades millors) als descriptors basats en aparença. També s'investiga com diferents característiques es poden combinar per ésser utilitzades en la classificació d'imatges i es mostra com el descriptor de forma proposat juntament amb un descriptor d'aparença millora substancialment la classificació. Finalment es descriu un algoritme que detecta les regions d'interès automàticament durant l'entrenament i la classificació. Això proporciona un mètode per inhibir el fons de la imatge i afegeix invariança a la posició dels objectes dins les imatges. S'ensenya que la forma i l'aparença sobre aquesta regió d'interès i utilitzant els classificadors random forests millora la classificació i el temps computacional. Es comparen els postres resultats amb resultats de la literatura utilitzant les mateixes bases de dades que els autors Aixa com els mateixos protocols d'aprenentatge i classificació. Es veu com totes les innovacions introduïdes incrementen la classificació final de les imatges.

Hand-held 3D-scanner for large surface registration

L'objectiu d'aquesta tesi és l'estudi de les diferents tècniques per alinear vistes tridimensionals. Aquest estudi ens ha permès detectar els principals problemes de les tècniques existents, aprotant una solució novedosa i contribuint resolent algunes de les mancances detectades especialment en l'alineament de vistes a temps real. Per tal d'adquirir les esmentades vistes, s'ha dissenyat un sensor 3D manual que ens permet fer adquisicions tridimensionals amb total llibertat de moviments. Així mateix, s'han estudiat les tècniques de minimització global per tal de reduir els efectes de la propagació de l'error.

William Beaumont Large

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