281 research outputs found
Uncertainty representation in software models: a survey
This paper provides a comprehensive overview and analysis of research work on how uncertainty is currently represented in software models. The survey presents the definitions and current research status of different proposals for addressing uncertainty modeling and introduces a classification framework that allows to compare and classify existing proposals, analyze their current status and identify new trends. In addition, we discuss possible future research directions, opportunities and challenges.This work is partially supported by the European Commission (FEDER) and the Spanish Government under projects APOLO (US1264651), HORATIO (RTI2018-101204-B-C21), EKIPMENT-PLUS (P18-FR-2895) and COSCA (PGC2018-094905-B-I00)
Towards development of fuzzy spatial datacubes : fundamental concepts with example for multidimensional coastal erosion risk assessment and representation
Les systĂšmes actuels de base de donnĂ©es gĂ©odĂ©cisionnels (GeoBI) ne tiennent gĂ©nĂ©ralement pas compte de l'incertitude liĂ©e Ă l'imprĂ©cision et le flou des objets; ils supposent que les objets ont une sĂ©mantique, une gĂ©omĂ©trie et une temporalitĂ© bien dĂ©finies et prĂ©cises. Un exemple de cela est la reprĂ©sentation des zones Ă risque par des polygones avec des limites bien dĂ©finies. Ces polygones sont crĂ©Ă©s en utilisant des agrĂ©gations d'un ensemble d'unitĂ©s spatiales dĂ©finies sur soit des intĂ©rĂȘts des organismes responsables ou les divisions de recensement national. MalgrĂ© la variation spatio-temporelle des multiples critĂšres impliquĂ©s dans lâanalyse du risque, chaque polygone a une valeur unique de risque attribuĂ© de façon homogĂšne sur l'Ă©tendue du territoire. En rĂ©alitĂ©, la valeur du risque change progressivement d'un polygone Ă l'autre. Le passage d'une zone Ă l'autre n'est donc pas bien reprĂ©sentĂ© avec les modĂšles dâobjets bien dĂ©finis (crisp). Cette thĂšse propose des concepts fondamentaux pour le dĂ©veloppement d'une approche combinant le paradigme GeoBI et le concept flou de considĂ©rer la prĂ©sence de lâincertitude spatiale dans la reprĂ©sentation des zones Ă risque. En fin de compte, nous supposons cela devrait amĂ©liorer lâanalyse du risque. Pour ce faire, un cadre conceptuel est dĂ©veloppĂ© pour crĂ©er un model conceptuel dâune base de donnĂ©e multidimensionnelle avec une application pour lâanalyse du risque dâĂ©rosion cĂŽtier. Ensuite, une approche de la reprĂ©sentation des risques fondĂ©e sur la logique floue est dĂ©veloppĂ©e pour traiter l'incertitude spatiale inhĂ©rente liĂ©e Ă l'imprĂ©cision et le flou des objets. Pour cela, les fonctions d'appartenance floues sont dĂ©finies en basant sur lâindice de vulnĂ©rabilitĂ© qui est un composant important du risque. Au lieu de dĂ©terminer les limites bien dĂ©finies entre les zones Ă risque, l'approche proposĂ©e permet une transition en douceur d'une zone Ă une autre. Les valeurs d'appartenance de plusieurs indicateurs sont ensuite agrĂ©gĂ©es basĂ©es sur la formule des risques et les rĂšgles SI-ALORS de la logique floue pour reprĂ©senter les zones Ă risque. Ensuite, les Ă©lĂ©ments clĂ©s d'un cube de donnĂ©es spatiales floues sont formalisĂ©s en combinant la thĂ©orie des ensembles flous et le paradigme de GeoBI. En plus, certains opĂ©rateurs d'agrĂ©gation spatiale floue sont prĂ©sentĂ©s. En rĂ©sumĂ©, la principale contribution de cette thĂšse se rĂ©fĂšre de la combinaison de la thĂ©orie des ensembles flous et le paradigme de GeoBI. Cela permet lâextraction de connaissances plus comprĂ©hensibles et appropriĂ©es avec le raisonnement humain Ă partir de donnĂ©es spatiales et non-spatiales. Pour ce faire, un cadre conceptuel a Ă©tĂ© proposĂ© sur la base de paradigme GĂ©oBI afin de dĂ©velopper un cube de donnĂ©es spatiale floue dans le system de Spatial Online Analytical Processing (SOLAP) pour Ă©valuer le risque de l'Ă©rosion cĂŽtiĂšre. Cela nĂ©cessite d'abord d'Ă©laborer un cadre pour concevoir le modĂšle conceptuel basĂ© sur les paramĂštres de risque, d'autre part, de mettre en Ćuvre lâobjet spatial flou dans une base de donnĂ©es spatiales multidimensionnelle, puis l'agrĂ©gation des objets spatiaux flous pour envisager Ă la reprĂ©sentation multi-Ă©chelle des zones Ă risque. Pour valider l'approche proposĂ©e, elle est appliquĂ©e Ă la rĂ©gion Perce (Est du QuĂ©bec, Canada) comme une Ă©tude de cas.Current Geospatial Business Intelligence (GeoBI) systems typically do not take into account the uncertainty related to vagueness and fuzziness of objects; they assume that the objects have well-defined and exact semantics, geometry, and temporality. Representation of fuzzy zones by polygons with well-defined boundaries is an example of such approximation. This thesis uses an application in Coastal Erosion Risk Analysis (CERA) to illustrate the problems. CERA polygons are created using aggregations of a set of spatial units defined by either the stakeholdersâ interests or national census divisions. Despite spatiotemporal variation of the multiple criteria involved in estimating the extent of coastal erosion risk, each polygon typically has a unique value of risk attributed homogeneously across its spatial extent. In reality, risk value changes gradually within polygons and when going from one polygon to another. Therefore, the transition from one zone to another is not properly represented with crisp object models. The main objective of the present thesis is to develop a new approach combining GeoBI paradigm and fuzzy concept to consider the presence of the spatial uncertainty in the representation of risk zones. Ultimately, we assume this should improve coastal erosion risk assessment. To do so, a comprehensive GeoBI-based conceptual framework is developed with an application for Coastal Erosion Risk Assessment (CERA). Then, a fuzzy-based risk representation approach is developed to handle the inherent spatial uncertainty related to vagueness and fuzziness of objects. Fuzzy membership functions are defined by an expert-based vulnerability index. Instead of determining well-defined boundaries between risk zones, the proposed approach permits a smooth transition from one zone to another. The membership values of multiple indicators (e.g. slop and elevation of region under study, infrastructures, houses, hydrology network and so on) are then aggregated based on risk formula and Fuzzy IF-THEN rules to represent risk zones. Also, the key elements of a fuzzy spatial datacube are formally defined by combining fuzzy set theory and GeoBI paradigm. In this regard, some operators of fuzzy spatial aggregation are also formally defined. The main contribution of this study is combining fuzzy set theory and GeoBI. This makes spatial knowledge discovery more understandable with human reasoning and perception. Hence, an analytical conceptual framework was proposed based on GeoBI paradigm to develop a fuzzy spatial datacube within Spatial Online Analytical Processing (SOLAP) to assess coastal erosion risk. This necessitates developing a framework to design a conceptual model based on risk parameters, implementing fuzzy spatial objects in a spatial multi-dimensional database, and aggregating fuzzy spatial objects to deal with multi-scale representation of risk zones. To validate the proposed approach, it is applied to Perce region (Eastern Quebec, Canada) as a case study
An adverbial approach for the formal specification of topological constraints involving regions with broad boundaries
Topological integrity constraints control the topological properties of spatial objects and the validity of their topological relationships in spatial databases. These constraints can be specified by using formal languages such as the spatial extension of the Object Constraint Language (OCL). Spatial OCL allows the expression of topological constraints involving crisp spatial objects. However, topological constraints involving spatial objects with vague shapes (e.g., regions with broad boundaries) are not supported by this language. Shape vagueness requires using appropriate topological operators (e.g., strongly Disjoint, fairly Meet) to specify valid relations between these objects; otherwise, the constraints cannot be respected. This paper addresses the problem of the lack of terminology to express topological constraints involving regions with broad boundaries. We propose an extension of Spatial OCL based on a geometric model for objects with vague shapes and an adverbial approach for topological relations between regions with broad boundaries. This extension of Spatial OCL is then tested on an agricultural database
A contour tree based spatio-temporal data model for oceanographic applications
To present the spatio/temporal data from oceanographic modeling in GIS has been a challenging task due to the highly dynamic characteristic and complex pattern of variables, in relation to time and space. This dissertation focuses the research on spatio-temporal GIS data model applied to oceanographic model data, especially to homogeneous iso-surface data. The available spatio-temporal data models are carefully reviewed and characteristics in spatial and temporal issues from oceanographic model data are discussed in detail. As an important tool for data modeling, ontology is introduced to categorize oceanographic model data and further set up fundamental software components in the new data model. The proposed data model is based on the concept of contour tree. By adding temporal information to each node and arc of the contour tree, and using multiple contour trees to represent different time steps in the temporal domain, the changes can be stored and tracked by the data model. In order to reduce the data volume and increase the data quality, the new data model integrates spatial and temporal interpolation methods within it. The spatial interpolation calculates the data that fall between neighboring contours at a single time step. The Inverse Distance Weighting (IDW) is applied as the main algorithm and the Minimum Bounding Rectangle (MBR) is used to enhance the spatial interpolation performance. The temporal interpolation calculates the data that are not recorded, which fall between neighboring contour trees for adjacent time steps. The âlinear interpolationâ algorithm is preferred to the ânearest neighborâs valueâ and âsplineâ interpolation methods, for its modest accuracy and the simple implementation scheme. In order to evaluate the support functions of the new data model, a case study is presented with the motivation to show how this data model supports complicated spatio-temporal queries in forecasting applications. This dissertation also showcases some work in contour tree simplification. A new simplification algorithm is introduced to reduce the data complexity. This algorithm is based on the branch decomposition method and supports temporal information integrated into contour trees. Three types of criteria parameters are introduced to run different simplification methods for various applications
Users Integrity Constraints in SOLAP Systems. Application in Agroforestry
SpatialData Warehouse and Spatial On-Line Analytical Processing are decision support technologies which offer the spatial and multidimensional analysis of data stored in multidimensional structure. They are aimed also at supporting geographic knowledge discovery to help decision-maker in his job related to make the appropriate decision . However, if we donât consider data quality in the spatial hypercubes and how it is explored, it may provide unreliable results. In this paper, we propose a system for the implementation of user integrity constraints in SOLAP namely âUIC-SOLAPâ. It corresponds to a methodology for guaranteeing results quality in an analytical process effectuated by different users exploiting several facts tables within the same hypercube. We integrate users Integrity Constraints (IC) by specifying visualization ICs according to their preferences and we define inter-facts ICs in this case. In order to validate our proposition, we propose the multidimensional modeling by UML profile to support constellation schema of a hypercube with several fact tables related to subjects of analysis in forestry management. Then, we propose implementation of some ICs related to users of such a system
Architectural decisions in AI-based systems: an ontological view
Architecting AI-based systems entails making some decisions that are particular to this type of systems. Therefore, it becomes necessary to gather all necessary knowledge to inform such decisions, and to articulate this knowledge in a form that facilitates knowledge transfer among different AI projects. In this exploratory paper, we first present the main results of a literature survey in the area, and then we propose a preliminary ontology for architectural decision making, which we exemplify using a subset of the papers selected in the literature review. In the discussion, we remark on the variety of decision types and system contexts, highlighting the need to further investigate the current state of research and practice in this area. Besides, we summarize our plans to move along this research area by widening the literature review and incorporating more AI-related concepts to this first version of the ontology.This paper has been funded by the Spanish Ministerio de Ciencia e InnovaciĂłn under project / funding scheme PID2020-117191RB-I00 / AEI/10.13039/501100011033.Peer ReviewedPostprint (author's final draft
Recommended from our members
MC2: MPEG-7 content modelling communities
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe use of multimedia content on the web has grown significantly in recent years. Websites such as Facebook, YouTube and Flickr cater for enormous amounts of multimedia content uploaded by users. This vast amount of multimedia content requires comprehensive content modelling otherwise
retrieving relevant content will be challenging. Modelling multimedia content can be an extremely time consuming task that may seem impossible particularly when undertaken by individual users. However, the advent of Web 2.0 and associated communities, such as YouTube and Flickr, has
shown that users appear to be more willing to collaborate in order to take on enormous tasks such as multimedia content modelling. Harnessing the power of communities to achieve comprehensive content modelling is the primary focus of this research.
The aim of this thesis is to explore collaborative multimedia content modelling and in particular the effectiveness of existing multimedia content modelling tools, taking into account the key development challenges of existing collaborative content modelling research and the associated
modelling tools. Four research objectives are pursued in order to achieve this; first, design a user experiment to study usersâ tagging behaviour with existing multimedia tagging tools and identify any relationships between such user behaviour; second, design and develop a framework for MPEG-7 content modelling communities based on the results of the experiment; third, implement an online
service as a proof of concept of the framework; fourth, validate the framework through the online service during a repeat of the initial user experiment.
This research contributes first, a conceptual model of user behaviour visualised as a fuzzy cognitive
map and, second, an MPEG-7 framework for multimedia content modelling communities (MC2) and its proof of concept as an online service. The fuzzy cognitive model embodies relationships between user tagging behaviour and context and provides an understanding of user priorities in the description of content features and the relationships that exist between them. The MC2 framework,
developed based on the fuzzy cognitive model, is deep-rooted in user content modelling behaviour and content preferences. A proof of concept of the MC2 framework is implemented as an online service in which all metadata is modelled using MPEG-7. The online service is validated, first, empirically with the same group of users and through the same experiment that led to the development of the fuzzy cognitive model and, second, functionally against the folksonomy and MPEG-7 content modelling tools used in the initial experiment. The validation demonstrates that MC2 has the advantages without the shortcomings of existing multimedia tagging tools by harnessing the ease of use of folksonomy tools while producing comprehensive structured metadata.Supported by UK Engineering and Physical Sciences Research Council (EPSRC
Developing a model and a language to identify and specify the integrity constraints in spatial datacubes
La qualité des données dans les cubes de données spatiales est importante étant donné que ces données sont utilisées comme base pour la prise de décision dans les grandes organisations. En effet, une mauvaise qualité de données dans ces cubes pourrait nous conduire à une mauvaise prise de décision. Les contraintes d'intégrité jouent un rÎle clé pour améliorer la cohérence logique de toute base de données, l'un des principaux éléments de la qualité des données. Différents modÚles de cubes de données spatiales ont été proposés ces derniÚres années mais aucun n'inclut explicitement les contraintes d'intégrité. En conséquence, les contraintes d'intégrité de cubes de données spatiales sont traitées de façon non-systématique, pragmatique, ce qui rend inefficace le processus de vérification de la cohérence des données dans les cubes de données spatiales. Cette thÚse fournit un cadre théorique pour identifier les contraintes d'intégrité dans les cubes de données spatiales ainsi qu'un langage formel pour les spécifier. Pour ce faire, nous avons d'abord proposé un modÚle formel pour les cubes de données spatiales qui en décrit les différentes composantes. En nous basant sur ce modÚle, nous avons ensuite identifié et catégorisé les différents types de contraintes d'intégrité dans les cubes de données spatiales. En outre, puisque les cubes de données spatiales contiennent typiquement à la fois des données spatiales et temporelles, nous avons proposé une classification des contraintes d'intégrité des bases de données traitant de l'espace et du temps. Ensuite, nous avons présenté un langage formel pour spécifier les contraintes d'intégrité des cubes de données spatiales. Ce langage est basé sur un langage naturel contrÎlé et hybride avec des pictogrammes. Plusieurs exemples de contraintes d'intégrité des cubes de données spatiales sont définis en utilisant ce langage. Les designers de cubes de données spatiales (analystes) peuvent utiliser le cadre proposé pour identifier les contraintes d'intégrité et les spécifier au stade de la conception des cubes de données spatiales. D'autre part, le langage formel proposé pour spécifier des contraintes d'intégrité est proche de la façon dont les utilisateurs finaux expriment leurs contraintes d'intégrité. Par conséquent, en utilisant ce langage, les utilisateurs finaux peuvent vérifier et valider les contraintes d'intégrité définies par l'analyste au stade de la conception
- âŠ