Extending a geo-catalogue with matching capabilities

To achieve semantic interoperability, geo-spatial applications need to be equipped with tools able to understand user terminology that is typically different from the one enforced by standards. In this paper we summarize our experience in providing a semantic extension to the geo-catalogue of the Autonomous Province of Trento (PAT) in Italy. The semantic extension is based on the adoption of the S-Match semantic matching tool and on the use of a specifically designed faceted ontology codifying domain specific knowledge. We also briefly report our experience in the integration of the ontology with the geo-spatial ontology GeoWordNet

Trivial movements and redistribution of polyphagous insect herbivores in heterogeneous vegetation

The aim of this thesis was to study the interplay between movement patterns of polyphagous insect herbivores and vegetation heterogeneity within agricultural fields. I examined if and how 1) host plant species, 2) host plant quality, 3) vegetation architecture, and 4) trap crop physical design influence movement patterns of individuals and spatial distribution of populations. Foragers may aggregate in profitable areas by tactic movement, or by area-restricted search, i.e. by moving randomly but slowing down movement and increasing rate of turning after encountering a profitable patch. Movement patterns of polyphagous herbivores have a high potential for influencing their distribution among hosts differing in quality. However, information on the role random vs. non-random components in their movement behavior is scarce. The results of this thesis show that both host plant species and within species differences in host plant quality affect movement behavior of a polyphagous herbivore, the European tarnished plant bug nymphs. The host plant induced movement patterns also explained the distribution of nymphs in heterogeneous vegetation. Because redistribution was very fast, it appears that no tactic behavior is needed for the nymphs to locate preferred hosts in heterogeneous vegetation composed of small patches. Instead the nymphs may successfully locate superior hosts merely by random movement coupled with sensitivity to local host quality. The physical structure of environment influences redistribution of populations at several spatial scales. At small scale the architecture of vegetation may influence redistribution of insects that move on the plant surface. At large scale e.g. trap crop physical design may affect redistribution of pests. In this thesis I derive a model for predicting the impact of vegetation architecture on the rate of displacement by insects moving on the plant surface. I also present and explore models of the interplay between pest movement and trap crop physical design. The trap crop models suggest that considerable reduction in pest density may be achieved using small trap crop cover with trap crops that the pest distinctly prefers over the crop. It supports also the idea that trap crop placement may have a dramatic impact on the efficiency of the trap crops

Answer Set Programming Modulo `Space-Time'

We present ASP Modulo `Space-Time', a declarative representational and computational framework to perform commonsense reasoning about regions with both spatial and temporal components. Supported are capabilities for mixed qualitative-quantitative reasoning, consistency checking, and inferring compositions of space-time relations; these capabilities combine and synergise for applications in a range of AI application areas where the processing and interpretation of spatio-temporal data is crucial. The framework and resulting system is the only general KR-based method for declaratively reasoning about the dynamics of `space-time' regions as first-class objects. We present an empirical evaluation (with scalability and robustness results), and include diverse application examples involving interpretation and control tasks

Unstable manifolds and Schroedinger dynamics of Ginzburg-Landau vortices

The time evolution of several interacting Ginzburg-Landau vortices according to an equation of Schroedinger type is approximated by motion on a finite-dimensional manifold. That manifold is defined as an unstable manifold of an auxiliary dynamical system, namely the gradient flow of the Ginzburg-Landau energy functional. For two vortices the relevant unstable manifold is constructed numerically and the induced dynamics is computed. The resulting model provides a complete picture of the vortex motion for arbitrary vortex separation, including well-separated and nearly coincident vortices.Comment: 23 pages amslatex, 5 eps figures, minor typos correcte

Turning the shelves: empirical findings and space syntax analyses of two virtual supermarket variations

The spatial structure of a virtual supermarket was systematically varied to investigate human behavior and cognitive processes in unusual building configurations. The study builds upon experiments in a regular supermarket, which serve as a baseline case. In a between-participant design a total of 41 participants completed a search task in two different virtual supermarket environments. For 21 participants the supermarket shelves were turned towards them at a 45° angle when entering the store, giving high visual access to product categories and products. For 20 participants the shelves were placed in exactly the opposite direction obstructing a quick development of shopping goods dependencies. The obtained differences in search performance between the two conditions are analyzed using space syntax analyses and comparisons made of environmental features and participants’ actual search path trajectories

Grounding Dynamic Spatial Relations for Embodied (Robot) Interaction

This paper presents a computational model of the processing of dynamic spatial relations occurring in an embodied robotic interaction setup. A complete system is introduced that allows autonomous robots to produce and interpret dynamic spatial phrases (in English) given an environment of moving objects. The model unites two separate research strands: computational cognitive semantics and on commonsense spatial representation and reasoning. The model for the first time demonstrates an integration of these different strands.Comment: in: Pham, D.-N. and Park, S.-B., editors, PRICAI 2014: Trends in Artificial Intelligence, volume 8862 of Lecture Notes in Computer Science, pages 958-971. Springe

EAGLE—A Scalable Query Processing Engine for Linked Sensor Data

Recently, many approaches have been proposed to manage sensor data using semantic web technologies for effective heterogeneous data integration. However, our empirical observations revealed that these solutions primarily focused on semantic relationships and unfortunately paid less attention to spatio–temporal correlations. Most semantic approaches do not have spatio–temporal support. Some of them have attempted to provide full spatio–temporal support, but have poor performance for complex spatio–temporal aggregate queries. In addition, while the volume of sensor data is rapidly growing, the challenge of querying and managing the massive volumes of data generated by sensing devices still remains unsolved. In this article, we introduce EAGLE, a spatio–temporal query engine for querying sensor data based on the linked data model. The ultimate goal of EAGLE is to provide an elastic and scalable system which allows fast searching and analysis with respect to the relationships of space, time and semantics in sensor data. We also extend SPARQL with a set of new query operators in order to support spatio–temporal computing in the linked sensor data context.EC/H2020/732679/EU/ACTivating InnoVative IoT smart living environments for AGEing well/ACTIVAGEEC/H2020/661180/EU/A Scalable and Elastic Platform for Near-Realtime Analytics for The Graph of Everything/SMARTE

Articulated Pose Estimation Using Hierarchical Exemplar-Based Models

Exemplar-based models have achieved great success on localizing the parts of semi-rigid objects. However, their efficacy on highly articulated objects such as humans is yet to be explored. Inspired by hierarchical object representation and recent application of Deep Convolutional Neural Networks (DCNNs) on human pose estimation, we propose a novel formulation that incorporates both hierarchical exemplar-based models and DCNNs in the spatial terms. Specifically, we obtain more expressive spatial models by assuming independence between exemplars at different levels in the hierarchy; we also obtain stronger spatial constraints by inferring the spatial relations between parts at the same level. As our method strikes a good balance between expressiveness and strength of spatial models, it is both effective and generalizable, achieving state-of-the-art results on different benchmarks: Leeds Sports Dataset and CUB-200-2011.Comment: 8 pages, 6 figure