34,633 research outputs found
Modeling Spatial Data in the MADS Conceptual Model
Despite the well-established benefits of conceptual modeling for application design, current spatio-temporal conceptual models do not cope satisfactorily with designers' requirements. In this paper we first identify the goals of a spatio-temporal conceptual model and then we describe the MADS model along its structural and spatial dimensions. As the modeling concepts are orthogonal, the proposed model achieves both simplicity (as concepts are independent from each other) and expressive power (as concepts may be freely associated). The model, which includes the features of the ODMG standard model for object-oriented systems, has been implemented by translating it into operational models of existing products. Experience gained by modeling a number of applications enabled us to assess the advantages of MADS with respect to traditional entity-relationship modeling. A visual schema editor and a visual query editor are being develope
Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems
The modelling, analysis, and visualisation of dynamic geospatial phenomena
has been identified as a key developmental challenge for next-generation
Geographic Information Systems (GIS). In this context, the envisaged
paradigmatic extensions to contemporary foundational GIS technology raises
fundamental questions concerning the ontological, formal representational, and
(analytical) computational methods that would underlie their spatial
information theoretic underpinnings.
We present the conceptual overview and architecture for the development of
high-level semantic and qualitative analytical capabilities for dynamic
geospatial domains. Building on formal methods in the areas of commonsense
reasoning, qualitative reasoning, spatial and temporal representation and
reasoning, reasoning about actions and change, and computational models of
narrative, we identify concrete theoretical and practical challenges that
accrue in the context of formal reasoning about `space, events, actions, and
change'. With this as a basis, and within the backdrop of an illustrated
scenario involving the spatio-temporal dynamics of urban narratives, we address
specific problems and solutions techniques chiefly involving `qualitative
abstraction', `data integration and spatial consistency', and `practical
geospatial abduction'. From a broad topical viewpoint, we propose that
next-generation dynamic GIS technology demands a transdisciplinary scientific
perspective that brings together Geography, Artificial Intelligence, and
Cognitive Science.
Keywords: artificial intelligence; cognitive systems; human-computer
interaction; geographic information systems; spatio-temporal dynamics;
computational models of narrative; geospatial analysis; geospatial modelling;
ontology; qualitative spatial modelling and reasoning; spatial assistance
systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964);
Special Issue on: Geospatial Monitoring and Modelling of Environmental
Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press
Variable density flow in porous media
We review the state of the art in modeling of variable-density flow and transport in porous media, including conceptual models for convection systems, governing balance equations, phenomenological laws, constitutive relations for fluid density and viscosity, and numerical methods for solving the resulting nonlinear multifield problems. The discussion of numerical methods addresses strategies for solving the coupled spatio-temporal convection process, consistent velocity approximation, and error-based mesh adaptation techniques. As numerical models for those nonlinear systems must be carefully verified in appropriate tests, we discuss weaknesses and inconsistencies of current model-verification methods as well as benchmark solutions. We give examples of field-related applications to illustrate specific challenges of further research, where heterogeneities and large scales are important
Moving Object Trajectories Meta-Model And Spatio-Temporal Queries
In this paper, a general moving object trajectories framework is put forward
to allow independent applications processing trajectories data benefit from a
high level of interoperability, information sharing as well as an efficient
answer for a wide range of complex trajectory queries. Our proposed meta-model
is based on ontology and event approach, incorporates existing presentations of
trajectory and integrates new patterns like space-time path to describe
activities in geographical space-time. We introduce recursive Region of
Interest concepts and deal mobile objects trajectories with diverse
spatio-temporal sampling protocols and different sensors available that
traditional data model alone are incapable for this purpose.Comment: International Journal of Database Management Systems (IJDMS) Vol.4,
No.2, April 201
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Conceptual modelling and the quality of ontologies: A comparison between object-role modelling and the object paradigm
Ontologies are key enablers for sharing precise and machine-understandable semantics among different applications and parties. Yet, for ontologies to meet these expectations, their quality must be of a good standard. The quality of an ontology is strongly based on the design method employed. This paper addresses the design problems related to the modelling of ontologies, with specific concentration on the issues related to the quality of the conceptualisations produced. The paper aims
to demonstrate the impact of the modelling paradigm adopted on the quality of ontological models and, consequently, the potential impact that such a decision can have in relation to the development of
software applications. To this aim, an ontology that is conceptualised based on the Object Role Modelling (ORM) approach is re-engineered into a one modelled on the basis of the Object Paradigm (OP). Next, the two ontologies are analytically compared using the specified criteria. The conducted
comparison highlights that using the OP for ontology conceptualisation can provide more expressive, reusable, objective and temporal ontologies than those conceptualised on the basis of the ORM approach
Conceptual Modelling and The Quality of Ontologies: Endurantism Vs. Perdurantism
Ontologies are key enablers for sharing precise and machine-understandable
semantics among different applications and parties. Yet, for ontologies to meet
these expectations, their quality must be of a good standard. The quality of an
ontology is strongly based on the design method employed. This paper addresses
the design problems related to the modelling of ontologies, with specific
concentration on the issues related to the quality of the conceptualisations
produced. The paper aims to demonstrate the impact of the modelling paradigm
adopted on the quality of ontological models and, consequently, the potential
impact that such a decision can have in relation to the development of software
applications. To this aim, an ontology that is conceptualised based on the
Object-Role Modelling (ORM) approach (a representative of endurantism) is
re-engineered into a one modelled on the basis of the Object Paradigm (OP) (a
representative of perdurantism). Next, the two ontologies are analytically
compared using the specified criteria. The conducted comparison highlights that
using the OP for ontology conceptualisation can provide more expressive,
reusable, objective and temporal ontologies than those conceptualised on the
basis of the ORM approach
Dynamic texture recognition using time-causal and time-recursive spatio-temporal receptive fields
This work presents a first evaluation of using spatio-temporal receptive
fields from a recently proposed time-causal spatio-temporal scale-space
framework as primitives for video analysis. We propose a new family of video
descriptors based on regional statistics of spatio-temporal receptive field
responses and evaluate this approach on the problem of dynamic texture
recognition. Our approach generalises a previously used method, based on joint
histograms of receptive field responses, from the spatial to the
spatio-temporal domain and from object recognition to dynamic texture
recognition. The time-recursive formulation enables computationally efficient
time-causal recognition. The experimental evaluation demonstrates competitive
performance compared to state-of-the-art. Especially, it is shown that binary
versions of our dynamic texture descriptors achieve improved performance
compared to a large range of similar methods using different primitives either
handcrafted or learned from data. Further, our qualitative and quantitative
investigation into parameter choices and the use of different sets of receptive
fields highlights the robustness and flexibility of our approach. Together,
these results support the descriptive power of this family of time-causal
spatio-temporal receptive fields, validate our approach for dynamic texture
recognition and point towards the possibility of designing a range of video
analysis methods based on these new time-causal spatio-temporal primitives.Comment: 29 pages, 16 figure
Log-Euclidean Bag of Words for Human Action Recognition
Representing videos by densely extracted local space-time features has
recently become a popular approach for analysing actions. In this paper, we
tackle the problem of categorising human actions by devising Bag of Words (BoW)
models based on covariance matrices of spatio-temporal features, with the
features formed from histograms of optical flow. Since covariance matrices form
a special type of Riemannian manifold, the space of Symmetric Positive Definite
(SPD) matrices, non-Euclidean geometry should be taken into account while
discriminating between covariance matrices. To this end, we propose to embed
SPD manifolds to Euclidean spaces via a diffeomorphism and extend the BoW
approach to its Riemannian version. The proposed BoW approach takes into
account the manifold geometry of SPD matrices during the generation of the
codebook and histograms. Experiments on challenging human action datasets show
that the proposed method obtains notable improvements in discrimination
accuracy, in comparison to several state-of-the-art methods
Between Sense and Sensibility: Declarative narrativisation of mental models as a basis and benchmark for visuo-spatial cognition and computation focussed collaborative cognitive systems
What lies between `\emph{sensing}' and `\emph{sensibility}'? In other words,
what kind of cognitive processes mediate sensing capability, and the formation
of sensible impressions ---e.g., abstractions, analogies, hypotheses and theory
formation, beliefs and their revision, argument formation--- in domain-specific
problem solving, or in regular activities of everyday living, working and
simply going around in the environment? How can knowledge and reasoning about
such capabilities, as exhibited by humans in particular problem contexts, be
used as a model and benchmark for the development of collaborative cognitive
(interaction) systems concerned with human assistance, assurance, and
empowerment?
We pose these questions in the context of a range of assistive technologies
concerned with \emph{visuo-spatial perception and cognition} tasks encompassing
aspects such as commonsense, creativity, and the application of specialist
domain knowledge and problem-solving thought processes. Assistive technologies
being considered include: (a) human activity interpretation; (b) high-level
cognitive rovotics; (c) people-centred creative design in domains such as
architecture & digital media creation, and (d) qualitative analyses geographic
information systems. Computational narratives not only provide a rich cognitive
basis, but they also serve as a benchmark of functional performance in our
development of computational cognitive assistance systems. We posit that
computational narrativisation pertaining to space, actions, and change provides
a useful model of \emph{visual} and \emph{spatio-temporal thinking} within a
wide-range of problem-solving tasks and application areas where collaborative
cognitive systems could serve an assistive and empowering function.Comment: 5 pages, research statement summarising recent publication
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