Semantic Similarity of Spatial Scenes

The formalization of similarity in spatial information systems can unleash their functionality and contribute technology not only useful, but also desirable by broad groups of users. As a paradigm for information retrieval, similarity supersedes tedious querying techniques and unveils novel ways for user-system interaction by naturally supporting modalities such as speech and sketching. As a tool within the scope of a broader objective, it can facilitate such diverse tasks as data integration, landmark determination, and prediction making. This potential motivated the development of several similarity models within the geospatial and computer science communities. Despite the merit of these studies, their cognitive plausibility can be limited due to neglect of well-established psychological principles about properties and behaviors of similarity. Moreover, such approaches are typically guided by experience, intuition, and observation, thereby often relying on more narrow perspectives or restrictive assumptions that produce inflexible and incompatible measures. This thesis consolidates such fragmentary efforts and integrates them along with novel formalisms into a scalable, comprehensive, and cognitively-sensitive framework for similarity queries in spatial information systems. Three conceptually different similarity queries at the levels of attributes, objects, and scenes are distinguished. An analysis of the relationship between similarity and change provides a unifying basis for the approach and a theoretical foundation for measures satisfying important similarity properties such as asymmetry and context dependence. The classification of attributes into categories with common structural and cognitive characteristics drives the implementation of a small core of generic functions, able to perform any type of attribute value assessment. Appropriate techniques combine such atomic assessments to compute similarities at the object level and to handle more complex inquiries with multiple constraints. These techniques, along with a solid graph-theoretical methodology adapted to the particularities of the geospatial domain, provide the foundation for reasoning about scene similarity queries. Provisions are made so that all methods comply with major psychological findings about people’s perceptions of similarity. An experimental evaluation supplies the main result of this thesis, which separates psychological findings with a major impact on the results from those that can be safely incorporated into the framework through computationally simpler alternatives

A Process for Producing Ice Coverage Marine Information Objects (MIOs) in IHO S-57 format

While global warming may be opening up more Arctic waters in the summer, ice still infests key shipping lanes in the northern hemisphere during the winter months. To safely navigate these areas, mariners rely on daily ice coverage charts produced by national governmental agencies. Ice charts are primarily issued in paper format or as a fax. However, there is increased interest to ice coverage information on vessel navigation systems such as an Electronic Chart and Display Information Systems (ECDIS). However, to do so, the ice information must be provided as a separate layer of information to the Electronic Navigational Chart (ENC).Mientras que un calentamiento global puede aumentar la extension de las aguas ârticas en verano, el hieio sigue infestando las dénotas maritimas en el hemisferio septentrional durante los meses de invierno. Para navegar en estas zonas de forma segura, los navegantes conffan en las cartas de cobertura diaria del hielo producidas por agendas gubernamentales nacionales. Las cartas del hielo son editadas principaimente en formato impreso o como fax. Sin embargo, hay un interés creciente por la informaciôn de cobertura del hielo en los sistemas de navegaciôn de los buques, como por ejemplo en los Sistemas de Presentaciôn de las Cartas Electrônicas y de Informaciôn (ECDIS). Sin embargo, para producirlas, tiene que proporcionarse la informaciôn sobre el hielo como una serie de informaciôn separada para la Carta Electrônica de Navegaciôn (ENC).Bien que le réchauffement global puisse faire enfler les eaux arctiques en été, les glaces envahissent toujours les principaux couloirs de navigation dans l'hémisphère, pendant la saison hivernale. Afin de naviguer en toute sécurité dans ces zones, les navigateurs se fient aux cartes des glaces produites quotidiennement par les agences gouvernementales nationales. Les cartes des glaces sont essentiellement communiquées sous forme imprimée ou de télécopie. On note cependant un regain d’intérêt pour les informations sur la couverture des glaces, dans des systèmes de navigation maritime tel que l ’ECDIS (système de visualisation des cartes électroniques et d'information). Toutefois, pour ce faire, les renseignements sur les glaces doivent être transmis, en tant que « niveau » d’information distinct, aux Cartes électroniques de navigation (ENC)

UK utility data integration: overcoming schematic heterogeneity

In this paper we discuss syntactic, semantic and schematic issues which inhibit the integration of utility data in the UK. We then focus on the techniques employed within the VISTA project to overcome schematic heterogeneity. A Global Schema based architecture is employed. Although automated approaches to Global Schema definition were attempted the heterogeneities of the sector were too great. A manual approach to Global Schema definition was employed. The techniques used to define and subsequently map source utility data models to this schema are discussed in detail. In order to ensure a coherent integrated model, sub and cross domain validation issues are then highlighted. Finally the proposed framework and data flow for schematic integration is introduced

Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians

This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of finite mixture models, conjugate families and factorization. Both the joint probability density of the variables and the likelihood function of the (objective or subjective) observation are approximated by a special mixture model, in such a way that any desired conditional distribution can be directly obtained without numerical integration. We have developed an extended version of the expectation maximization (EM) algorithm to estimate the parameters of mixture models from uncertain training examples (indirect observations). As a consequence, any piece of exact or uncertain information about both input and output values is consistently handled in the inference and learning stages. This ability, extremely useful in certain situations, is not found in most alternative methods. The proposed framework is formally justified from standard probabilistic principles and illustrative examples are provided in the fields of nonparametric pattern classification, nonlinear regression and pattern completion. Finally, experiments on a real application and comparative results over standard databases provide empirical evidence of the utility of the method in a wide range of applications

A new criterion for soft set based decision making problems under incomplete information

[EN]We put forward a completely redesigned approach to soft set based decision making problems under incomplete information. An algorithmic solution is proposed and compared with previous approaches in the literature. The computational performance of our algorithm is critically analyzed by an experimental study