Multi-level visualisation using Gaussian process latent variable models

Projection of a high-dimensional dataset onto a two-dimensional space is a useful tool to visualise structures and relationships in the dataset. However, a single two-dimensional visualisation may not display all the intrinsic structure. Therefore, hierarchical/multi-level visualisation methods have been used to extract more detailed understanding of the data. Here we propose a multi-level Gaussian process latent variable model (MLGPLVM). MLGPLVM works by segmenting data (with e.g. K-means, Gaussian mixture model or interactive clustering) in the visualisation space and then fitting a visualisation model to each subset. To measure the quality of multi-level visualisation (with respect to parent and child models), metrics such as trustworthiness, continuity, mean relative rank errors, visualisation distance distortion and the negative log-likelihood per point are used. We evaluate the MLGPLVM approach on the ‘Oil Flow’ dataset and a dataset of protein electrostatic potentials for the ‘Major Histocompatibility Complex (MHC) class I’ of humans. In both cases, visual observation and the quantitative quality measures have shown better visualisation at lower levels.

Coupling 3D visualisation to qualitative assessment of built environment designs

Geographical information systems (GIS) coupled to 3D visualisation technology is an emerging tool for urban planning and landscape design applications. The utility of 3D GIS for realistically visualising the built environment and proposed development scenarios is much advocated in the literature. Planners assess the merits of proposed changes using visual impact assessment (VIA). We have used Arcview GIS and visualisation software: called PolyTRIM from the University of Toronto, Centre for Landscape Research (CLR) to create a 3D scene for the entrance to a University campus. The paper investigates the thesis that to facilitate VIA in planning and design requires not only visualisation, but also a structured evaluation technique (Delphi) to arbitrate the decision-making process. (C) 2001 Elsevier Science B.V. All rights reserved.

A collaborative approach for incorporating forensic case data into crime investigation using criminal intelligence analysis and visualisation

There is an increasing awareness that the articulation of forensic science and criminal investigation is critical to the resolution of crimes. However, models and methods to support an effective collaboration between these partners are still poorly expressed or even lacking. Three propositions are borrowed from crime intelligence methods in order to bridge this gap: (a) the general intelligence process, (b) the analyses of investigative problems along principal perspectives: entities and their relationships, time and space, quantitative aspects and (c) visualisation methods as a mode of expression of a problem in these dimensions. Indeed, in a collaborative framework, different kinds of visualisations integrating forensic case data can play a central role for supporting decisions. Among them, link-charts are scrutinised for their abilities to structure and ease the analysis of a case by describing how relevant entities are connected. However, designing an informative chart that does not bias the reasoning process is not straightforward. Using visualisation as a catalyser for a collaborative approach integrating forensic data thus calls for better specifications.

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

Valoriser le géopatrimoine par la médiation indirecte et la visualisation des objets géomorphologiques

Résumé: Valoriser le géopatrimoine par la médiation indirecte et la visualisation des objets géomorphologiques Le géopatrimoine regroupe des objets géologiques lato sensu auxquels certaines valeurs sont attribuées, en fonction de leur intérêt pour la science, de leur rareté, de leurs particularités culturelles ou écologiques, etc. Valoriser le géopatrimoine signifie avant tout faire partager cette approche aux non-spécialistes, en expliquant ce qui fait la valeur de ces objets. Cette valorisation peut s'effectuer, entre autres, sous la forme d'une activité touristique et contribuer ainsi au développement régional. Faire comprendre l'origine, la singularité et la valeur des formes du relief implique le recours à une communication éducative, désignée par le terme de médiation. Les implications de la dimension éducative du processus, comme la prise en compte des connaissances et attentes du public, la création d'un environnement favorable à l'apprentissage ou l'attractivité du contenu, sont souvent négligées. Du point de vue conceptuel, un modèle de la médiation indirecte (c'est-à-dire au moyen de supports médiatiques) a été proposé et appliqué au développement empirique de produits de médiation et à leur évaluation. Ce modèle ne garantit pas la réussite de la communication éducative, mais contribue à créer un cadre favorable au processus. De plus, plusieurs lignes directrices pour le choix du type de média et sa mise en forme ont été définies sur la base d'une compilation de résultats de la psychologie cognitive sur l'usage des médias pour l'apprentissage. Des méthodes qualitatives et quantitatives variées ont été mobilisées : enquêtes par questionnaire ex situ et in situ, auprès des visiteurs de géomorphosites de montagne, réalisation de médias interactifs testés ensuite auprès de divers publics (parcours enregistré, pré- et post-questionnaires) et entretiens collectifs. Les résultats obtenus éclairent divers aspects de la problématique. L'étude du public a montré, par exemple, que le géotourisme possède un réel public parmi les visiteurs des sites de montagnes : trois-quarts d'entre eux expriment de l'intérêt pour des explications sur la géologie et l'évolution du paysage. Cette thèse a exploré ces aspects liés au processus d'apprentissage en se focalisant sur les médias visuels, surtout interactifs. La plupart des médias visuels couramment utilisés en géomorphologie ont été considérés. Le développement de versions interactives de ces médias sous forme d'applications web a fourni un aperçu concret des possibilités des nouvelles technologies. Les utilisateurs apprécient en particulier a richesse du contenu, le haut degré d'interactivité et la variété de ces applications. De tels médias incitent à visiter le site naturel et semblent aussi répondre aux intérêts de publics variés. Abstract: Geoheritage promotion through non-personal interpretation and visualisation of geomorphological features Geoheritage concerns all geological features lato sensu to which some values are attributed, according to their scientific interest, their rarity, their cultural or ecological dimensions, etc. Geoheritage promotion implies sharing this point of view with non-specialists, explaining what gives value to those objects. Geotourism is one of the many ways to achieve geoheritage promotion, while contributing also to regional development. In order to make non-specialists understand the origin, the specificity and the value of landforms, educational communication is needed, that is called interpretation (French: médiation). This education dimension has several, and often neglected, implications, like taking into account public's knowledge and expectations, creating a favourable learning environment, attractive design, etc. From the conceptual point of view, a model for non-personal interpretation has been proposed and applied for the empirical development and for the assessment of interpretive products. This model does not guarantee success of educational communication, but help creating a favourable environment for this process. Moreover, some guidelines were defined from a compilation of several results of cognitive psychology on media use for learning. They guide the choice of the kind of media and its design. Several qualitative and quantitative methods were applied: survey questionnaires ex situ and in situ by mountain geomorphosites visitors, interactive medias developed and then tested by different kinds of users (with usertracking, pre- and post-survey questionnaires), group interviews. The results answered different aspects of the research questions. Visitor surveys revealed for example that geotourism could attract many visitors of mountain areas: three quarters of them say they are interested in getting explanations about geology and landscape (in particular its dynamic dimensions). This thesis examined those aspects with a focus on visual medias, both statics and interactive. Most of currently used medias in geomorphology were considered. Interactive versions of those medias were developed in web applications; they gave a concrete overview on the opportunities that new technologies offer. The content richness, the high interaction level and the diversity of the applications are the most liked aspects by the users. Such medias drive to visit the natural site and seem to correspond to the interests of various kinds of publics. Zusammenfassung: Aufwertung des erdwissenschaftlichen Erbes durch mediale Vermittlung und Visualisierung von geomorphologischen Objekten Das erdwissenschaftliche Erbe besteht aus geologischen Gegebenheiten lato sensu, denen entsprechend ihrer Bedeutung für die Wissenschaft, ihrer Seltenheit, ihrer kulturellen oder ökologischen Besonderheiten usw. bestimmte Werte zugeordnet werden. Das erdwissenschaftliche Erbe aufzuwerten bedeutet in erster Linie, diesen Ansatz Nichtspezialisten näher zu bringen, indem ihnen erklärt wird, was den Wert dieser Gegebenheiten ausmacht. Dies kann etwa im Rahmen eines touristischen Angebots geschehen und so die regionale Entwicklung unterstützen. Um Entstehung, Besonderheit und Wert von Geländeformen verständlich zu machen, wird eine pädagogische Kommunikationsform verwendet, die als mediale Vermittlung (franz. médiation) bezeichnet wird. Die Bedeutung der pädagogischen Dimension des Vermittlungsprozesses wie etwa der Einbezug des Wissens und der Erwartungen des Publikums, die Gestaltung eines positiven Lernklimas oder die Attraktivität des Inhalts wird oft vernachlässigt. Auf konzeptueller Ebene wurde ein Modell der indirekten Interpretation erarbeitet (d. h. anhand von Medien), das bei der empirischen Entwicklung der Interpretationsprodukte und ihrer Evaluation Anwendung fand. Dieses Modell garantiert zwar nicht den Erfolg der pädagogischen Kommunikation. Es trägt aber dazu bei, einen für den Prozess günstigen Kontext zu schaffen. Des Weiteren wurden mehrere Richtlinien für die Wahl des Medientyps und dessen Ausgestaltung anhand einer Zusammenstellung von Resultaten der kognitiven Psychologie über den Gebrauch von Medien in Lernprozessen definiert. Es wurden verschiedene qualitative und quantitative Methoden eingesetzt: Befragung mittels Fragebogen der Besucher von geomorphologischen Geotopen im Gebirge - ex situ und in situ -, Erarbeitung von interaktiven Medien, die anschliessend anhand verschiedener Zielgruppen gestestet wurden (Aufnahme des Besuchparcours, Vor- und Nachfragebögen) sowie kollektive Interviews. Die Ergebnisse geben Aufschluss zu verschiedenen Aspekten der Fragestellung. Die Befragung des Publikums hat zum Beispiel deutlich gemacht, dass der Geotourismus unter den Besuchern von Berggebieten tatsächlich auf eine Nachfrage stösst: drei Viertel von ihnen zeigen ein Interesse für Erläuterungen zur Geologie und der Landschaftsentwicklung. Die vorliegende Doktorarbeit hat die genannten Aspekte der Lernprozesse untersucht, wobei der Fokus auf visuellen, insbesondere interaktiven Medien lag. Die meisten gängigen visuellen Medien der Geomorphologie wurden berücksichtigt. Die Entwicklung von interaktiven Versionen dieser Medien in Form von Web-Anwendungen hat die Möglichkeiten der neuen Technologien veranschaulicht. Die Benutzer schätzten insbesondere die Vielfalt des Inhalts, die hohe Interaktivität und die Diversität dieser Anwendungen. Solche Medien laden dazu ein, ein Naturgebiet zu besuchen und scheinen den Interessen der verschiedenen Publikumsgruppen entgegenzukommen.

Performance analysis of software run-time behaviour using 3D-visualisation

Monimutkaisen tietokonejärjestelmän suorituskykyoptimointi edellyttää järjestelmän ajonaikaisen käyttäytymisen ymmärtämistä. Ohjelmiston koon ja monimutkaisuuden kasvun myötä suorituskykyoptimointi tulee yhä tärkeämmäksi osaksi tuotekehitysprosessia. Tehokkaampien prosessorien käytön myötä myös energiankulutus ja lämmöntuotto ovat nousseet yhä suuremmiksi ongelmiksi, erityisesti pienissä, kannettavissa laitteissa. Lämpö- ja energiaongelmien rajoittamiseksi on kehitetty suorituskyvyn skaalausmenetelmiä, jotka edelleen lisäävät järjestelmän kompleksisuutta ja suorituskykyoptimoinnin tarvetta. Tässä työssä kehitettiin visualisointi- ja analysointityökalu ajonaikaisen käyttäytymisen ymmärtämisen helpottamiseksi. Lisäksi kehitettiin suorituskyvyn mitta, joka mahdollistaa erilaisten skaalausmenetelmien vertailun ja arvioimisen suoritusympäristöstä riippumatta, perustuen joko suoritustallenteen tai teoreettiseen analyysiin. Työkalu esittää ajonaikaisesti kerätyn tallenteen helposti ymmärrettävällä tavalla. Se näyttää mm. prosessit, prosessorikuorman, skaalausmenetelmien toiminnan sekä energiankulutuksen kolmiulotteista grafiikkaa käyttäen. Työkalu tuottaa myös käyttäjän valitsemasta osasta suorituskuvaa numeerista tietoa, joka sisältää useita oleellisia suorituskykyarvoja ja tilastotietoa. Työkalun sovellettavuutta tarkasteltiin todellisesta laitteesta saatua suoritustallennetta sekä suorituskyvyn skaalauksen simulointia analysoimalla. Skaalausmekanismin parametrien vaikutus simuloidun laitteen suorituskykyyn analysoitiin.

Génération automatique de configurations et de scénarios d'utilisation d'outils de visualisation à partir de spécifications de tâches d'analyse de logiciels

Nous proposons une approche qui génère des scénarios de visualisation à partir des descriptions de tâches d'analyse de code. La dérivation de scénario est considérée comme un processus d'optimisation. Dans ce contexte, nous évaluons différentes possibilités d'utilisation d'un outil de visualisation donnée pour effectuer la tâche d'analyse, et sélectionnons le scénario qui nécessite le moins d'effort d'analyste. Notre approche a été appliquée avec succès à diverses tâches d'analyse telles que la détection des défauts de conception.

Predicting the thermal inactivation of bacteria in a solid matrix: simulation studies on the relative effects of microbial thermal resistance parameters and process conditions

A combined mathematical model for predicting heat penetration and microbial inactivation in a solid body heated by conduction was tested experimentally by inoculating agar cylinders with Salmonella typhimurium or Enterococcus faecium and heating in a water bath. Regions of growth where bacteria had survived after heating were measured by image analysis and compared with model predictions. Visualisation of the regions of growth was improved by incorporating chromogenic metabolic indicators into the agar. Preliminary tests established that the model performed satisfactorily with both test organisms and with cylinders of different diameter. The model was then used in simulation studies in which the parameters D, z, inoculum size, cylinder diameter and heating temperature were systematically varied. These simulations showed that the biological variables D, z and inoculum size had a relatively small effect on the time needed to eliminate bacteria at the cylinder axis in comparison with the physical variables heating temperature and cylinder diameter, which had a much greater relative effect. (c) 2005 Elsevier B.V All rights reserved.

Generic unified modelling process for developing semantically rich, dynamic and temporal models

Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a model’s quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models.

Visualisation of macropinosome maturation by the recruitment of sorting nexins

We report that phosphoinositol-binding sorting nexin 5 ( SNX5) associates with newly formed macropinosomes induced by EGF stimulation. We used the recruitment of GFP-SNX5 to macropinosomes to track their maturation. Initially, GFP-SNX5 is sequestered to discrete subdomains of the macropinosome; these subdomains are subsequently incorporated into highly dynamic, often branched, tubular structures. Time-lapse videomicroscopy revealed the highly dynamic extension of SNX5-labelled tubules and their departure from the macropinosome body to follow predefined paths towards the perinuclear region of the cell, before fusing with early endosomal acceptor membranes. The extension and departure of these tubular structures occurs rapidly over 5-10 minutes and is dependent upon intact microtubules. As the tubular structures depart from the macropinosome there is a reduction in the surface area and an increase in tension of the limiting membrane of the macropinosome. In addition to the recruitment of SNX5 to the macropinosome, Rab5, SNX1 and EEA1 are also recruited by newly formed macropinosomes, followed by the accumulation of Rab7. SNX5 forms heterodimers with SNX1 and this interaction is required for endosome association of SNX5. We propose that the departure of SNX5-positive tubules represents a rapid mechanism of recycling components from macropinosomes thereby promoting their maturation into Rab7-positive structures. Collectively these findings provide a detailed real-time characterisation of the maturation process of the macropinocytic endosome.

3D information visualisation: An historical perspective

The use of 3D visualisation of digital information is a recent phenomenon. It relies on users understanding 3D perspectival spaces. Questions about the universal access of such spaces has been debated since its inception in the European Renaissance. Perspective has since become a strong cultural influence in Western visual communication. Perspective imaging assists the process of experimenting by the sketching or modelling of ideas. In particular, the recent 3D modelling of an essentially non-dimensional Cyber-space raises questions of how we think about information in general. While alternate methods clearly exist they are rarely explored within the 3D paradigm (such as Chinese isometry). This paper seeks to generate further discussion on the historical background of perspective and its role in underpinning this emergent field. © 2005 IEEE.

GIS linked environmental process models

In recent years there has been a great effort to combine the technologies and techniques of GIS and process models. This project examines the issues of linking a standard current generation 2½d GIS with several existing model codes. The focus for the project has been the Shropshire Groundwater Scheme, which is being developed to augment flow in the River Severn during drought periods by pumping water from the Shropshire Aquifer. Previous authors have demonstrated that under certain circumstances pumping could reduce the soil moisture available for crops. This project follows earlier work at Aston in which the effects of drawdown were delineated and quantified through the development of a software package that implemented a technique which brought together the significant spatially varying parameters. This technique is repeated here, but using a standard GIS called GRASS. The GIS proved adequate for the task and the added functionality provided by the general purpose GIS - the data capture, manipulation and visualisation facilities - were of great benefit. The bulk of the project is concerned with examining the issues of the linkage of GIS and environmental process models. To this end a groundwater model (Modflow) and a soil moisture model (SWMS2D) were linked to the GIS and a crop model was implemented within the GIS. A loose-linked approach was adopted and secondary and surrogate data were used wherever possible. The implications of which relate to; justification of a loose-linked versus a closely integrated approach; how, technically, to achieve the linkage; how to reconcile the different data models used by the GIS and the process models; control of the movement of data between models of environmental subsystems, to model the total system; the advantages and disadvantages of using a current generation GIS as a medium for linking environmental process models; generation of input data, including the use of geostatistic, stochastic simulation, remote sensing, regression equations and mapped data; issues of accuracy, uncertainty and simply providing adequate data for the complex models; how such a modelling system fits into an organisational framework.

Visualisation of bioinformatics datasets

Analysing the molecular polymorphism and interactions of DNA, RNA and proteins is of fundamental importance in biology. Predicting functions of polymorphic molecules is important in order to design more effective medicines. Analysing major histocompatibility complex (MHC) polymorphism is important for mate choice, epitope-based vaccine design and transplantation rejection etc. Most of the existing exploratory approaches cannot analyse these datasets because of the large number of molecules with a high number of descriptors per molecule. This thesis develops novel methods for data projection in order to explore high dimensional biological dataset by visualising them in a low-dimensional space. With increasing dimensionality, some existing data visualisation methods such as generative topographic mapping (GTM) become computationally intractable. We propose variants of these methods, where we use log-transformations at certain steps of expectation maximisation (EM) based parameter learning process, to make them tractable for high-dimensional datasets. We demonstrate these proposed variants both for synthetic and electrostatic potential dataset of MHC class-I. We also propose to extend a latent trait model (LTM), suitable for visualising high dimensional discrete data, to simultaneously estimate feature saliency as an integrated part of the parameter learning process of a visualisation model. This LTM variant not only gives better visualisation by modifying the project map based on feature relevance, but also helps users to assess the significance of each feature. Another problem which is not addressed much in the literature is the visualisation of mixed-type data. We propose to combine GTM and LTM in a principled way where appropriate noise models are used for each type of data in order to visualise mixed-type data in a single plot. We call this model a generalised GTM (GGTM). We also propose to extend GGTM model to estimate feature saliencies while training a visualisation model and this is called GGTM with feature saliency (GGTM-FS). We demonstrate effectiveness of these proposed models both for synthetic and real datasets. We evaluate visualisation quality using quality metrics such as distance distortion measure and rank based measures: trustworthiness, continuity, mean relative rank errors with respect to data space and latent space. In cases where the labels are known we also use quality metrics of KL divergence and nearest neighbour classifications error in order to determine the separation between classes. We demonstrate the efficacy of these proposed models both for synthetic and real biological datasets with a main focus on the MHC class-I dataset.

Visualisation of heterogeneous data with simultaneous feature saliency using Generalised Generative Topographic Mapping

Most machine-learning algorithms are designed for datasets with features of a single type whereas very little attention has been given to datasets with mixed-type features. We recently proposed a model to handle mixed types with a probabilistic latent variable formalism. This proposed model describes the data by type-specific distributions that are conditionally independent given the latent space and is called generalised generative topographic mapping (GGTM). It has often been observed that visualisations of high-dimensional datasets can be poor in the presence of noisy features. In this paper we therefore propose to extend the GGTM to estimate feature saliency values (GGTMFS) as an integrated part of the parameter learning process with an expectation-maximisation (EM) algorithm. The efficacy of the proposed GGTMFS model is demonstrated both for synthetic and real datasets.

Probabilistic topographic information visualisation

The focus of this thesis is the extension of topographic visualisation mappings to allow for the incorporation of uncertainty. Few visualisation algorithms in the literature are capable of mapping uncertain data with fewer able to represent observation uncertainties in visualisations. As such, modifications are made to NeuroScale, Locally Linear Embedding, Isomap and Laplacian Eigenmaps to incorporate uncertainty in the observation and visualisation spaces. The proposed mappings are then called Normally-distributed NeuroScale (N-NS), T-distributed NeuroScale (T-NS), Probabilistic LLE (PLLE), Probabilistic Isomap (PIso) and Probabilistic Weighted Neighbourhood Mapping (PWNM). These algorithms generate a probabilistic visualisation space with each latent visualised point transformed to a multivariate Gaussian or T-distribution, using a feed-forward RBF network. Two types of uncertainty are then characterised dependent on the data and mapping procedure. Data dependent uncertainty is the inherent observation uncertainty. Whereas, mapping uncertainty is defined by the Fisher Information of a visualised distribution. This indicates how well the data has been interpolated, offering a level of ‘surprise’ for each observation. These new probabilistic mappings are tested on three datasets of vectorial observations and three datasets of real world time series observations for anomaly detection. In order to visualise the time series data, a method for analysing observed signals and noise distributions, Residual Modelling, is introduced. The performance of the new algorithms on the tested datasets is compared qualitatively with the latent space generated by the Gaussian Process Latent Variable Model (GPLVM). A quantitative comparison using existing evaluation measures from the literature allows performance of each mapping function to be compared. Finally, the mapping uncertainty measure is combined with NeuroScale to build a deep learning classifier, the Cascading RBF. This new structure is tested on the MNist dataset achieving world record performance whilst avoiding the flaws seen in other Deep Learning Machines.