Authority in the classroom: dictionaries and corpora, COBUILD and the Bank of English

Language learners ask a variety of questions about words and their meanings and uses: “What does X mean? What is the word for X in English? Can you say X? When do you use X and when do you use Y (e.g. synonyms, grammatical structures, prepositional choices, variant phrases, etc)?”

De l'espace au temps: des verbes de mouvements aller et venir à leur grammaticalisation en auxiliaires temporels dans quelques langues romanes (français, catalan, espagnol, italien, portugais) et en anglais

De nombreuses langues du monde grammaticalisent les formes lexicales itive (aller) et ventive (venir) en auxiliaires temporels. Si ce fait a été abondamment décrit dans des langues particulières, on ne dispose pas d’une étude contrastive des deux tours, ce que nous proposons d’entreprendre dans la présente communication, sur quelques langues, A partir des premiers constats suivants : - la forme itive est plus fréquemment grammaticalisée que la forme ventive : en anglais p. ex. seul go est grammaticalisé ; - si le plus souvent l’itif s’est grammaticalisé dans l’expression de l’imminence-ultériorité (le train va partir) et le ventif dans celle de la récence (le train vient de partir), ce n’est pas toujours le cas : en catalan, anar + inf. est un prétérit (el tren va marchar : ‘le train est parti’), et actualise donc le procès non comme ultérieur mais comme antérieur ; - certaines langues, comme le français, ont développé sur ces auxiliaires, outre les effets de sens temporel d’imminence-ultériorité pour l’itif et de récence pour le ventif, un effet de sens d’extraordinaire, qui peut être signifié aussi bien par l’un que par l’autre tour (il va pas / vient pas me dire) - l’imminence-ultériorité sur l’itif et la récence sur le ventif souffrent des restrictions temporelles, plus accusées pour le premier : en francais p. ex., aller, dans cet effet de sens, se conjugue aux seuls présent et imparfait (le train va / allait / * irait / *est allé partir) ; venir admet en plus le futur et le conditionnel (le train vient/ venait/viendra/ viendrait/ *est venu de partir). On se propose (i) d’expliciter les différents éléments de l’asymétrie dans la grammaticalisation des deux formes itive et ventive dans les langues retenues (anglais, catalan, espagnol, français, italien, portugais), et (ii) de formuler une hypothèse explicative de ces faits hétérogènes.

From cardinal spline wavelet bases to highly coherent dictionaries

Wavelet families arise by scaling and translations of a prototype function, called the mother wavelet. The construction of wavelet bases for cardinal spline spaces is generally carried out within the multi-resolution analysis scheme. Thus, the usual way of increasing the dimension of the multi-resolution subspaces is by augmenting the scaling factor. We show here that, when working on a compact interval, the identical effect can be achieved without changing the wavelet scale but reducing the translation parameter. By such a procedure we generate a redundant frame, called a dictionary, spanning the same spaces as a wavelet basis but with wavelets of broader support. We characterize the correlation of the dictionary elements by measuring their 'coherence' and produce examples illustrating the relevance of highly coherent dictionaries to problems of sparse signal representation.

Knowledge, capabilities and manufacturing innovation: a US-Europe comparison

In this paper we report a comparative analysis of the factors which contribute to the innovation performance of manufacturing firms in the US state of Georgia, and three European regions, the UK regions of Wales and the West Midlands, and the Spanish region of Catalonia. We consider the factors which shape firms’ ability to generate new products and processes and undertake various forms of organisational and structural change. We are particularly concerned with how firms collect the knowledge on which they base their innovation and their effectiveness in translating that knowledge into new innovations. Three main empirical conclusions result. First, US firms have more widespread links to external knowledge sources than those in Europe and notably the universities make a greater contribution to innovation in the US than in Europe. Second, UK firms prove more effective at capturing synergies between their innovation activities than US and Catalan firms. Third, firms’ operating environment proves more conducive to innovation in the US than in either the UK regions or Catalonia. Our results suggest the potential for mutual learning. For the UK there are lessons in terms of the way in which the universities in Georgia are supporting innovation. For firms in Georgia and in Catalonia the potential lessons are more strategic or organisational and relate to how they can better capture potential synergies between their innovation activities.

Sparse signal representation by adaptive non-uniform B-spline dictionaries on a compact interval

Non-uniform B-spline dictionaries on a compact interval are discussed in the context of sparse signal representation. For each given partition, dictionaries of B-spline functions for the corresponding spline space are built up by dividing the partition into subpartitions and joining together the bases for the concomitant subspaces. The resulting slightly redundant dictionaries are composed of B-spline functions of broader support than those corresponding to the B-spline basis for the identical space. Such dictionaries are meant to assist in the construction of adaptive sparse signal representation through a combination of stepwise optimal greedy techniques.

Sparsity and "something else": an approach to encrypted image folding

A property of sparse representations in relation to their capacity for information storage is discussed. It is shown that this feature can be used for an application that we term Encrypted Image Folding. The proposed procedure is realizable through any suitable transformation. In particular, in this paper we illustrate the approach by recourse to the Discrete Cosine Transform and a combination of redundant Cosine and Dirac dictionaries. The main advantage of the proposed technique is that both storage and encryption can be achieved simultaneously using simple processing steps.

Describing and communicating uncertainty within the semantic web

The Semantic Web relies on carefully structured, well defined, data to allow machines to communicate and understand one another. In many domains (e.g. geospatial) the data being described contains some uncertainty, often due to incomplete knowledge; meaningful processing of this data requires these uncertainties to be carefully analysed and integrated into the process chain. Currently, within the SemanticWeb there is no standard mechanism for interoperable description and exchange of uncertain information, which renders the automated processing of such information implausible, particularly where error must be considered and captured as it propagates through a processing sequence. In particular we adopt a Bayesian perspective and focus on the case where the inputs / outputs are naturally treated as random variables. This paper discusses a solution to the problem in the form of the Uncertainty Markup Language (UncertML). UncertML is a conceptual model, realised as an XML schema, that allows uncertainty to be quantified in a variety of ways i.e. realisations, statistics and probability distributions. UncertML is based upon a soft-typed XML schema design that provides a generic framework from which any statistic or distribution may be created. Making extensive use of Geography Markup Language (GML) dictionaries, UncertML provides a collection of definitions for common uncertainty types. Containing both written descriptions and mathematical functions, encoded as MathML, the definitions within these dictionaries provide a robust mechanism for defining any statistic or distribution and can be easily extended. Universal Resource Identifiers (URIs) are used to introduce semantics to the soft-typed elements by linking to these dictionary definitions. The INTAMAP (INTeroperability and Automated MAPping) project provides a use case for UncertML. This paper demonstrates how observation errors can be quantified using UncertML and wrapped within an Observations & Measurements (O&M) Observation. The interpolation service uses the information within these observations to influence the prediction outcome. The output uncertainties may be encoded in a variety of UncertML types, e.g. a series of marginal Gaussian distributions, a set of statistics, such as the first three marginal moments, or a set of realisations from a Monte Carlo treatment. Quantifying and propagating uncertainty in this way allows such interpolation results to be consumed by other services. This could form part of a risk management chain or a decision support system, and ultimately paves the way for complex data processing chains in the Semantic Web.