Fionn Murtagh

We assess both marginal density clustering, and spatial clustering using a Markov random field, on multiband Earth observation data. We use a Bayes factor assessment procedure in all cases. We find that the spatial model leads to better results, although the non-spatial clustering achieves a better false alarm rate.© (2003) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

It is useful to have available a general technique for checking on examination results. In this regard, Correspondence Analysis offers a number of advantages over other exploratory data analytic techniques. We illustrate some aspects of its use here, using the results obtained by 34 students in the B. Sc. degree examination in the author's department.

... I. Bondar Wide Field Plate Archive of the Crimean astrophysical observatory: status and perspective Ana Borisova Photometric ... Eruptive Prominence Images Harry Enke Gridbased detection of Galaxy Clusters using Virtual Observatory methods Mohsen Farid Characterization ...

The implementation of a European Concerted Research Action designated as COST Action 283 "Computational and Information Infrastructure in the Astronomical DataGrid" is described. The main objective of the Action is to develop innovative and well focused approaches to data and information handling, in the context of astronomy and astrophysics. This includes processing and interpretation of data and, more generally, information, at the time of data capture or later "archival research", "data mining" and "virtual observatories" and so forth), and including aspects of the collaborative work and man-machine environments needed for this.

We present a method that automatically builds a domain concept hierarchy from a textual corpus. This concept hierarchy aims at helping ontology building and for semantic indexing of document collections. The approach we implemented aims at being automatic, as independent as possible of the language and can be applied to any field. We evaluate the different steps of the method using a Wikipedia sub-collection. We clearly show that our method can be of great help when building domain ontologies. The results also show the benefits of using C-value to select candidate terms.

This article tackles the classic super-resolution (SR) problem Elad99 of obtaining a high-resolution (HR) still image from a sequence of low-resolution (LR) images that have been warped and sub-sampled. The goal here is to recover frequencies higher than the Nyquist frequency by merging the LR information. We focus on the critical step of the SR process before any fusion technique can be applied which consists of the registration of LR images with an arbitrary reference image at sub-pixel accuracy. We propose a registration algorithm for color images, derived from the one described by Djamdji and Bijaoui in Ref. 2. This algorithm achieves automatic feature-based registration at sub-pixel accuracy. It seeks to take advantage of the multi-band (RGB) information in a color image to improve the robustness and accuracy compared to more usual greyscale registration. The fusion of the data from LR images into a higher resolution image is then carried out through thin plate spline interpola...

ABSTRACT The Ward error sum of squares hierarchical clustering method has been very widely used since its first description by Ward in a 1963 publication. It has also been generalized in various ways. Two algorithms are found in the literature and software, both announcing that they implement the Ward clustering method. When applied to the same distance matrix, they produce different results. One algorithm preserves Ward’s criterion, the other does not. Our survey work and case studies will be useful for all those involved in developing software for data analysis using Ward’s hierarchical clustering method.

Abstract This paper describes different approaches suitable for the implementation of the 3D Haar wavelet transform (HWT). These transforms are important in 3D image compression and video processing applications. The algorithms for the standard (SHWT), nonstandard (NSHWT), tensor product (TPHWT) and transpose based decompositions (TSHWT and TNSHWT) are described together with their implementation in MATLAB®. The influence of both the hard and soft threshold applied to these decompositions is also examined. ...

ABSTRACT Our primary objective is evaluation of quality of process. This is addressed through semantic mapping of process. We note how this is complementary to the primacy of output results or products. We use goal-oriented discourse as a case study. We draw benefit from how social and political theorist, Ju¨rgen Habermas, uses what was termed ‘‘communicative action’’. An orientation in Habermas’s work, that we use, is analysis of communication or discourse. For this, we take Twitter social media. In our case study, we map the discourse semantically, using the correspondence analysis platform for such latent semantic analysis. This permits qualitative and quantitative analytics. Our case study is a set of eight carefully planned Twitter campaigns relating to environmental issues. The aim of these campaigns was to increase environmental awareness and behaviour. Each campaign was launched by an initiating tweet. Using the data gathered in these Twitter campaigns, we sought to map them, and hence to track the flow of the Twitter discourse. This mapping was achieved through semantic embedding. The semantic distance between an initiating act and the aggregate semantic outcome is used as a measure of process effectiveness.

We address the problems of (1) segmenting coarse from fine granularity materials, and (2) discriminating between materials of different granularities. For the former we use wavelet features, and an enhanced version of the widely used EM algorithm. A weighted Gaussian mixture model is used, with a second order spatial neighborhood. For granularity discrimination we investigate the use of multiresolution entropy.

Our work has focused on support for film or television scriptwriting. Since this involves potentially varied story-lines, we note the implicit or latent support for interactivity. Furthermore the film, television, games, publishing and other sectors are converging, so that cross-over and re-use of one form of product in another of these sectors is ever more common. Technically our work has been largely based on all pairwise interrelationships that are used to reveal the semantics of the data, and the dynamics of the narrative revealed ...

ABSTRACT Geometric data analysis, which is multivariate data analysis, is an approach for what has been referred to as the visualisation and verbalisation of data. The general objectives are data mining and knowledge discovery. In the first case study, we use the narrative surrounding very highly profiled tweets, and thus a Twitter event of significance and importance. In the second case study, we use eight carefully planned Twitter campaigns relating to environmental issues. The aim of these campaigns was to increase environmental awareness and behaviour. Each campaign was launched by an initiating tweet. In our previous work we noted the following, which we address in an innovative way in this new work: "top-down communication campaigns [in social media] both predominate and are advised by those involved in `social marketing' ... . However, this rarely manifests itself through measurable behaviour change ..." We visualise and we show how we can quantify change in Twitter narrative. Potentially too, we show how we can assess statistical significance of these social media events.

Abstract The authors describe initial experiments in detecting cosmic ray hits on single Hubble Space Telescope Wide Field/Planetary Camera CCD-frames. Classifiers are trained on images with (what are considered to be) the cosmic ray hits marked. A range of classifiers are assessed. The IRAF cosmicrays task is found to be conservative, having a low detection rate combined with a low false alarm rate. The classical k-nearest neighbours method offers a versatile and broad-ranging alternative. With the rather homogeneous input data used, ...