Information Rich 3D Computer Modeling of Urban Environments

We are living in an increasingly information rich society. Geographical Information Systems now allow us to precisely tag information to specific features, objects and locations. The Internet is enabling much of this information to be accessed by a whole spectrum of users. At CASA we are attempting to push this technology towards a three-dimensional GIS, that works across the Internet and can represent significant chunks of a large city. We believe that the range of possible uses for such technology is diverse, although we feel that urban planning is an area that can benefit greatly. An opportunity to push this “planning technology” arose when CASA won a tender from Hackney Council to develop a dynamic website for community participation in the process of regenerating the Woodberry Down Estate. This is a run down part of northeast London that is undergoing a major redevelopment. CASA has developed a system that not only informs the local residents about the redevelopment process but it also enables them to use dynamic visualisations of the “before and after effects” of different plans, and then to discuss and vote on the variety of options

Temperature perturbation model of the opto-galvanic effect in CO2-laser discharges

A detailed discharge model of the opto-galvanic effect in molecular laser gas mixtures is developed based on the temperature perturbation or discharge cooling mechanism of Smith and Brooks (1979). Excellent agreement between the model and experimental results in CO2 laser gas mixtures is obtained. The model should be applicable to other molecular systems where the OGE is being used for laser stabilisation and as a spectroscopic tool

Efficacy of laser preionization with a semiconductor source and propene addition

It is established that propene is an effective additive instabilising uv preionised CO2 TEA laser discharges: its effect being particularly pronounced with semiconductor-edge preionised lasers where the preionisation levels are shown to be low

Generalized enthalpy model of a high pressure shift freezing process

High-pressure freezing processes are a novel emerging technology in food processing, offering significant improvements to the quality of frozen foods. To be able to simulate plateau times and thermal history under different conditions, in this work we present a generalized enthalpy model of the high-pressure shift freezing process. The model includes the effects of pressure on conservation of enthalpy and incorporates the freezing point depression of non-dilute food samples. In addition the significant heat transfer effects of convection in the pressurizing medium are accounted for by solving the two-dimensional Navier-Stokes equations. We run the model for several numerical tests where the food sample is agar gel, and find good agreement with experimental data from the literature

Evolution PDEs and augmented eigenfunctions. I finite interval

The so-called unified method expresses the solution of an initial-boundary value problem for an evolution PDE in the finite interval in terms of an integral in the complex Fourier (spectral) plane. Simple initial-boundary value problems, which will be referred to as problems of type~I, can be solved via a classical transform pair. For example, the Dirichlet problem of the heat equation can be solved in terms of the transform pair associated with the Fourier sine series. Such transform pairs can be constructed via the spectral analysis of the associated spatial operator. For more complicated initial-boundary value problems, which will be referred to as problems of type~II, there does \emph{not} exist a classical transform pair and the solution \emph{cannot} be expressed in terms of an infinite series. Here we pose and answer two related questions: first, does there exist a (non-classical) transform pair capable of solving a type~II problem, and second, can this transform pair be constructed via spectral analysis? The answer to both of these questions is positive and this motivates the introduction of a novel class of spectral entities. We call these spectral entities augmented eigenfunctions, to distinguish them from the generalised eigenfunctions introduced in the sixties by Gel'fand and his co-authors

Viterbi Training for PCFGs: Hardness Results and Competitiveness of Uniform Initialization

We consider the search for a maximum likelihood assignment of hidden derivations and grammar weights for a probabilistic context-free grammar, the problem approximately solved by “Viterbi training.” We show that solving and even approximating Viterbi training for PCFGs is NP-hard. We motivate the use of uniformat-random initialization for Viterbi EM as an optimal initializer in absence of further information about the correct model parameters, providing an approximate bound on the log-likelihood.

Empirical Risk Minimization for Probabilistic Grammars: Sample Complexity and Hardness of Learning

Probabilistic grammars are generative statistical models that are useful for compositional and sequential structures. They are used ubiquitously in computational linguistics. We present a framework, reminiscent of structural risk minimization, for empirical risk minimization of probabilistic grammars using the log-loss. We derive sample complexity bounds in this framework that apply both to the supervised setting and the unsupervised setting. By making assumptions about the underlying distribution that are appropriate for natural language scenarios, we are able to derive distribution-dependent sample complexity bounds for probabilistic grammars. We also give simple algorithms for carrying out empirical risk minimization using this framework in both the supervised and unsupervised settings. In the unsupervised case, we show that the problem of minimizing empirical risk is NP-hard. We therefore suggest an approximate algorithm, similar to expectation-maximization, to minimize the empirical risk. Learning from data is central to contemporary computational linguistics. It is in common in such learning to estimate a model in a parametric family using the maximum likelihood principle. This principle applies in the supervised case (i.e., using annotate

Evidence of a saturated gravity-wave spectrum throughout the atmosphere

The view adapted here is that the dominant mesoscale motions are due to internal gravity waves and show that previous and new vertical wave number spectra of horizontal winds are consistent with the notion of a saturation limit on wave amplitudes. It is also proposed that, at any height, only those vertical wave numbers m less than m sub asterisk are at saturation amplitudes, where m sub asterisk is the vertical wave number of the dominant energy-containing scale. Wave numbers m less than m sub asterisk are unsaturated, but experience growth with height due to the decrease of atmospheric density. The result is a saturated spectrum of gravity waves with both m sub asterisk decreasing and wave energy increasing with height. This saturation theory is consistent with a variety of atmospheric spectral observations and provides a basis for the notion of a universal spectrum of atmospheric gravity waves