831 research outputs found
The challenge of real-time automatic mapping for environmental monitoring network management
The automatic interpolation of environmental monitoring network data such as air quality or radiation levels in real-time setting poses a number of practical and theoretical questions. Among the problems found are (i) dealing and communicating uncertainty of predictions, (ii) automatic (hyper)parameter estimation, (iii) monitoring network heterogeneity, (iv) dealing with outlying extremes, and (v) quality control. In this paper we discuss these issues, in light of the spatial interpolation comparison exercise held in 2004
Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements
A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities
Modelling frontal discontinuities in wind fields
A Bayesian procedure for the retrieval of wind vectors over the ocean using satellite borne scatterometers requires realistic prior near-surface wind field models over the oceans. We have implemented carefully chosen vector Gaussian Process models; however in some cases these models are too smooth to reproduce real atmospheric features, such as fronts. At the scale of the scatterometer observations, fronts appear as discontinuities in wind direction. Due to the nature of the retrieval problem a simple discontinuity model is not feasible, and hence we have developed a constrained discontinuity vector Gaussian Process model which ensures realistic fronts. We describe the generative model and show how to compute the data likelihood given the model. We show the results of inference using the model with Markov Chain Monte Carlo methods on both synthetic and real data
MillennialâScale Vulnerability of the Antarctic Ice Sheet to Regional Ice Shelf Collapse
The response of the Antarctic Ice Sheet to ice shelf collapse is explored with a high resolution ice sheet model. Rapid melting is applied to each of its major present day drainage basins in turn , to determine which parts of the ice sheet are most vulnerable to change in oceanic forcing, over the next 1000 years. We findthat West Antarctica can be largely deglaciated over a millenium, leading to more than two metres of sea level rise, if any of its major ice shelved disintegrated. The response of East Antarctica is more muted, but not negligible
Fusing Quantitative Requirements Analysis with Model-based Systems Engineering
A vision is presented for fusing quantitative
requirements analysis with model-based systems
engineering. This vision draws upon and combines
emergent themes in the engineering milieu.
âRequirements engineeringâ provides means to
explicitly represent requirements (both functional and
non-functional) as constraints and preferences on
acceptable solutions, and emphasizes early-lifecycle
review, analysis and verification of design and
development plans. âDesign by shoppingâ emphasizes
revealing the space of options available from which to
choose (without presuming that all selection criteria
have previously been elicited), and provides means to
make understandable the range of choices and their
ramifications. âModel-based engineeringâ emphasizes
the goal of utilizing a formal representation of all
aspects of system design, from development through
operations, and provides powerful tool suites that
support the practical application of these principles.
A first step prototype towards this vision is
described, embodying the key capabilities.
Illustrations, implications, further challenges and
opportunities are outlined
Learning to live with Dale's principle: ANNs with separate excitatory and inhibitory units
The units in artificial neural networks (ANNs) can be thought of as abstractions of biological neurons, and ANNs are increasingly used in neuroscience research. However, there are many important differences between ANN units and real neurons. One of the most notable is the absence of Dale's principle, which ensures that biological neurons are either exclusively excitatory or inhibitory. Dale's principle is typically left out of ANNs because its inclusion impairs learning. This is problematic, because one of the great advantages of ANNs for neuroscience research is their ability to learn complicated, realistic tasks. Here, by taking inspiration from feedforward inhibitory interneurons in the brain we show that we can develop ANNs with separate populations of excitatory and inhibitory units that learn just as well as standard ANNs. We call these networks Dale's ANNs (DANNs). We present two insights that enable DANNs to learn well: (1) DANNs are related to normalization schemes, and can be initialized such that the inhibition centres and standardizes the excitatory activity, (2) updates to inhibitory neuron parameters should be scaled using corrections based on the Fisher Information matrix. These results demonstrate how ANNs that respect Dale's principle can be built without sacrificing learning performance, which is important for future work using ANNs as models of the brain. The results may also have interesting implications for how inhibitory plasticity in the real brain operates
ERP Systems and the University as an 'Unique' Organisation
Enterprise Resource Planning (ERP) systems are widely used by large corporations around the
world. Recently universities have turned to ERP as a means of replacing existing management
and administration computer systems. In this article we provide analysis of the rollout of an ERP
system in one particular institution in the UK, the particular focus being on how the
development, implementation and use of both generic and university specific functionality is
mediated and shaped by a fundamental and long standing tension within universities: this is the
extent to which higher education institutions are organisations much like any other and the
extent to which they are âuniqueâ. The aim of this article is not to attempt to settle this issue of
similarity/difference in one way or another. Rather, it seeks to illustrate the value of taking
discussions of similarity relationships surrounding the university and other organisations as the
topic of analysis. One way of working with these kinds of issues without resolving them is to
consider their âdistributionâ and where ERP shifts the responsibility for their final resolution.
This is a novel and insightful way of understanding how ERP systems are refashioning the
identity of universities. We suggest, moreover, that ERP software is âaccompaniedâ by such
tensions in which ever site it is implemented. The research presented here is based on a
participant observation study carried over the period of three years
Dynamic control of visible radiation by a liquid crystal filled Fabry-PĂ©rot etalon
Copyright © 2007 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Journal of Applied Physics 102 (2007) and may be found at http://link.aip.org/link/?JAPIAU/102/093108/1A liquid crystal filled Fabry-Pérot etalon has been constructed to control the resonant transmission of electromagnetic radiation over the visible range of the spectrum. This has been achieved through the use of a 1.5 ”m thick homogeneously aligned liquid crystal layer in the core of a silver-clad etalon structure. Applying an electric field across the core reorientates the liquid crystal director and changes the refractive index for incident light polarized parallel to the rubbing direction. By measuring the transmitted intensity as a function of wavelength for a variety of applied voltages shifts in the positions of the resonant transmission modes of up to 80 nm have been observed. In addition, these results have been compared to model data generated using a multilayer optics model to obtain the dispersion of the liquid crystal over the visible range of the electromagnetic spectrum
Time-resolved sign-dependent switching in a hybrid aligned nematic liquid crystal cell
Copyright © 2008 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. This is the published version of an article published in New Journal of Physics Vol. 10, article 083045. DOI: 10.1088/1367-2630/10/8/083045An optical waveguide technique is used to determine the director tilt profile across a hybrid aligned nematic (HAN) liquid crystal cell, in which the optical response is dependent on the sign of the applied voltage. Two physical models are shown that fit the equilibrium experimental data, but with alternative explanations for this sign dependence. Models with either a flexoelectric coefficient of 2.25Ă10â11 C mâ1 or a bound surface charge of 12.2 ÎŒC mâ2 are shown that fit this equilibrium data. In an attempt to resolve this degeneracy sign-dependent switching data are analysed. However, neither model can explain these switching data, which are affected by slow transients of ~100 ms which are believed to be due to the motion of free ions in the liquid crystal. From the form of these slow transients, it is suggested that the equilibrium position of the ions is next to a cell substrate
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