7,604 research outputs found
Learning through work experience
How students learn and develop through work experience is here analysed. We draw upon contemporary learning theory, recent developments in the adult education and curriculum theory in developing a critique of current thinking and explore how far this provides the basis for a new pedagogic model for supporting learning through work experience. We discuss the concept of 'context' and the learning which occurs within and between the different contexts of education and work and argue that most models of work experience have either ignored the influence of context upon learning or have approached this issue mechanistically. New curriculum frameworks are needed to and to allow work in all of its forms to be used as a basis for the development of knowledge, skills and identity. We present a typology of work experience which identifies models of work experience, including a model which embodies the concept of 'connectivity'. We suggest that this may provide the basis for a productive and useful relationship between formal and informal learning
Weighted Point Cloud Augmentation for Neural Network Training Data Class-Imbalance
Recent developments in the field of deep learning for 3D data have
demonstrated promising potential for end-to-end learning directly from point
clouds. However, many real-world point clouds contain a large class im-balance
due to the natural class im-balance observed in nature. For example, a 3D scan
of an urban environment will consist mostly of road and facade, whereas other
objects such as poles will be under-represented. In this paper we address this
issue by employing a weighted augmentation to increase classes that contain
fewer points. By mitigating the class im-balance present in the data we
demonstrate that a standard PointNet++ deep neural network can achieve higher
performance at inference on validation data. This was observed as an increase
of F1 score of 19% and 25% on two test benchmark datasets; ScanNet and
Semantic3D respectively where no class im-balance pre-processing had been
performed. Our networks performed better on both highly-represented and
under-represented classes, which indicates that the network is learning more
robust and meaningful features when the loss function is not overly exposed to
only a few classes.Comment: 7 pages, 6 figures, submitted for ISPRS Geospatial Week conference
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Dynamic phenomena arising from an extended Core Group model
In order to obtain a reasonably accurate model for the spread of a particular infectious disease through a population, it may be necessary for this model to possess some degree of structural complexity. Many such models have, in recent years, been found to exhibit a phenomenon known as backward bifurcation, which generally implies the existence of two subcritical endemic equilibria. It is often possible to refine these models yet further, and we investigate here the influence such a refinement may have on the dynamic behaviour of a system in the region of the parameter space near R0 = 1. We consider a natural extension to a so-called core group model for the spread of a sexually transmitted disease, arguing that this may in fact give rise to a more realistic model. From the deterministic viewpoint we study the possible shapes of the resulting bifurcation diagrams and the associated stability patterns. Stochastic versions of both the original and the extended models are also developed so that the probability of extinction and time to extinction may be examined, allowing us to gain further insights into the complex system dynamics near R0 = 1. A number of interesting phenomena are observed, for which heuristic explanations are provided
Laser cleaning of the output window in a laser ignition system for gas turbines
Laser ignition (LI) of both liquid fuels and gaseous combustible mixtures in gas turbines offers the potential for reduced emissions and increased reliability. During the combustion process, carbon and other by-products accumulate on the walls of the combustion chamber. For laser based ignition systems, this could potentially reduce the transmissive properties of the output window required for transmission of the laser radiation into the combustion chamber. Presented in this paper is an empirical study into the laser cleaning of an output window for the removal of accumulated carbon prior to laser ignition, with the mechanism of removal discussed
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