Efficiently reasoning about qualitative constraints through variable elimination

© 2016 ACM. We introduce, study, and evaluate a novel algorithm in the context of qualitative constraint-based spatial and temporal reasoning, that is based on the idea of variable elimination, a simple and general exact inference approach in probabilistic graphical models. Given a qualitative constraint network M, our algorithm enforces a particular directional local consistency on M, which we denote by ←-consistency. Our discussion is restricted to distributive subclasses of relations, i.e., sets of relations closed under converse, intersection, and weak composition and for which weak composition distributes over non-empty intersections for all of their relations. We demonstrate that enforcing ←-consistency on a given qualitative constraint network defined over a distributive subclass of relations allows us to decide its satisfiability. The experimentation that we have conducted with random and real-world qualitative constraint networks defined over a distributive subclass of relations of the Region Connection Calculus, shows that our approach exhibits unparalleled performance against competing state-of-the-art approaches for checking the satisfiability of such constraint networks

Efficiently characterizing non-redundant constraints in large real world qualitative spatial networks

RCC8 is a constraint language that serves for qualitative spatial representation and reasoning by encoding the topological relations between spatial entities. We focus on efficiently characterizing non-redundant constraints in large real world RCC8 networks and obtaining their prime networks. For a RCC8 network N a constraint is redundant, if removing that constraint from N does not change the solution set of N. A prime network of N is a network which contains no redundant constraints, but has the same solution set as N. We make use of a particular partial consistency, namely, G⋄-consistency, and obtain new complexity results for various cases of RCC8 networks, while we also show that given a maximal distributive subclass for RCC8 and a network N defined on that subclass, the prunning capacity of G⋄-consistency and ⋄-consistency is identical on the common edges of G and the complete graph of N, when G is a triangulation of the constraint graph of N. Finally, we devise an algorithm based on G⋄-consistency to compute the unique prime network of a RCC8 network, and show that it significantly progresses the state-of-the-art for practical reasoning with real RCC8 networks scaling up to millions of nodes

On redundancy in linked geospatial data

RCC8 is a constraint language that serves for qualitative spatial representation and reasoning by encoding the topological relations between spatial entities. As such, RCC8 has been recently adopted by GeoSPARQL in an effort to enrich the Semantic Web with qualitative spatial relations. We focus on the redundancy that these data might harbor, which can throttle graph related applications, such as storing, representing, querying, and reasoning. For a RCC8 network N a constraint is redundant, if removing that constraint from N does not change the solution set of N. A prime network of N is a network which contains no redundant constraints, but has the same solution set as N. In this paper, we present a practical approach for obtaining the prime networks of RCC8 networks that originate from the Semantic Web, by exploiting the sparse and loosely connected structure of their constraint graphs, and, consequently, contribute towards offering Linked Geospatial Data of high quality. Experimental evaluation exhibits a vast decrease in the total number of non-redundant constraints that we can obtain from an initial network, while it also suggests that our approach significantly boosts the state-of-the-art approach

Efficient path consistency algorithm for large qualitative constraint networks

We propose a new algorithm called DPC+ to enforce partial path consistency (PPC) on qualitative constraint networks. PPC restricts path consistency (PC) to a triangulation of the underlying constraint graph of a network. As PPC retains the sparseness of a constraint graph, it can make reasoning tasks such as consistency checking and minimal labelling of large qualitative constraint networks much easier to tackle than PC. For qualitative constraint networks defined over any distributive subalgebra of well-known spatio-temporal calculi, such as the Region Connection Calculus and the Interval Algebra, we show that DPC+ can achieve PPC very fast. Indeed, the algorithm enforces PPC on a qualitative constraint network by processing each triangle in a triangulation of its underlying constraint graph at most three times. Our experiments demonstrate significant improvements of DPC+ over the state-of-the-art PPC enforcing algorithm

On redundancy in simple temporal networks

© 2016 The Authors and IOS Press. The Simple Temporal Problem (STP) has been widely used in various applications to schedule tasks. For dynamical systems, scheduling needs to be efficient and flexible to handle uncertainty and perturbation. To this end, modern approaches usually encode the temporal information as an STP instance. This representation contains redundant information, which can not only take a significant amount of storage space, but also make scheduling inefficient due to the non-concise representation. In this paper, we investigate the problem of simplifying an STP instance by removing redundant information. We show that such a simplification can result in a unique minimal representation without loss of temporal information, and present an efficient algorithm to achieve this task. Evaluation on a large benchmark dataset of STP exhibits a significant reduction in redundant information for the involved instances

Tractable Fragments of Temporal Sequences of Topological Information

In this paper, we focus on qualitative temporal sequences of topological information. We firstly consider the context of topological temporal sequences of length greater than 3 describing the evolution of regions at consecutive time points. We show that there is no Cartesian subclass containing all the basic relations and the universal relation for which the algebraic closure decides satisfiability. However, we identify some tractable subclasses, by giving up the relations containing the non-tangential proper part relation and not containing the tangential proper part relation. We then formalize an alternative semantics for temporal sequences. We place ourselves in the context of the topological temporal sequences describing the evolution of regions on a partition of time (i.e. an alternation of instants and intervals). In this context, we identify large tractable fragments

Wildfire monitoring via the integration of remote sensing with innovative information technologies

In the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA) volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applications during and after wildfire crisis, from fire detection and fire-front propagation monitoring, to damage assessment in the inflicted areas. The processed satellite imagery is combined with auxiliary geo-information layers, including land use/land cover, administrative boundaries, road and rail network, points of interest, and meteorological data to generate and validate added-value fire-related products. The service portfolio has become available to institutional End Users with a mandate to act on natural disasters and that have activated Emergency Support Services at a European level in the framework of the operational GMES projects SAFER and LinkER. Towards the goal of delivering integrated services for fire monitoring and management, ISARS/NOA employs observational capacities which include the operation of MSG/SEVIRI and NOAA/AVHRR receiving stations, NOA's in-situ monitoring networks for capturing meteorological parameters to generate weather forecasts, and datasets originating from the European Space Agency and third party satellite operators. The qualified operational activity of ISARS/NOA in the domain of wildfires management is highly enhanced by the integration of state-of-the-art Information Technologies that have become available in the framework of the TELEIOS (EC/ICT) project. TELEIOS aims at the development of fully automatic processing chains reliant on a) the effective storing and management of the large amount of EO and GIS data, b) the post-processing refinement of the fire products using semantics, and c) the creation of thematic maps and added-value services. The first objective is achieved with the use of advanced Array Database technologies, such as MonetDB, to enable efficiency in accessing large archives of image data and metadata in a fully transparent way, without worrying for their format, size, and location, as well as efficiency in processing such data using state-of-the-art implementations of image processing algorithms expressed in a high-level Scientific Query Language (SciQL). The product refinement is realized through the application of update operations that incorporate human evidence and human logic, with semantic content extracted from thematic information coming from auxiliary geo-information layers and sources, for reducing considerably the number of false alarms in fire detection, and improving the credibility of the burnt area assessment. The third objective is approached via the combination of the derived fire-products with Linked Geospatial Data, structured accordingly and freely available in the web, using Semantic Web technologies. These technologies are built on top of a robust and modular computational environment, to facilitate several wildfire applications to run efficiently, such as real-time fire detection, fire-front propagation monitoring, rapid burnt area mapping, after crisis detailed burnt scar mapping, and time series analysis of burnt areas. The approach adopted allows ISARS/NOA to routinely serve requests from the end-user community, irrespective of the area of interest and its extent, the observation time period, or the data volume involved, granting the opportunity to combine innovative IT solutions with remote sensing techniques and

Operational Wildfire Monitoring and Disaster Management Support Using State-of-the-art EO and Information Technologies

Fires have been one of the main driving forces in the evolution of plants and ecosystems, determining the current structure and composition of the Landscapes. However, significant alterations in the fire regime have occurred in the recent decades, primarily as a result of socioeconomic changes, increasing dramatically the catastrophic impacts of wildfires as it is reflected in the increase during the 20th century of both, number of fires and the annual area burnt. Therefore, the establishment of a permanent robust fire monitoring system is of paramount importance to implement an effective environmental management policy. Such an integrated system has been developed in the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA). Volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applications during and after wildfire crisis, from fire detection and fire-front propagation monitoring, to damage assessment in the inflicted areas. The processed satellite imagery is combined with auxiliary geo-information layers and meteorological data to generate and validate added-value fire-related products. The service portfolio has become available to institutional End Users with a mandate to act on natural disasters in the framework of the operational GMES projects SAFER and LinkER addressing fire emergency response and emergency support needs for the entire European Union. Towards the goal of delivering integrated services for fire monitoring and management, ISARS/NOA employs observational capacities which include the operation of MSG/SEVIRI and NOAA/AVHRR receiving stations, NOA’s in-situ monitoring networks for capturing meteorological parameters to generate weather forecasts, and datasets originating from the European Space Agency and third party satellite operators. The qualified operational activity of ISARS/NOA in the domain of wildfires management is highly enhanced by the integra

A one-stop perineal clinic: our eleven-year experience.

INTRODUCTION AND HYPOTHESIS: The perineal clinic is a dedicated setting offering assessment for various childbirth-related presentations including obstetric anal sphincter injuries (OASIs), perineal wound complications, pelvic floor dysfunction and other conditions such as female genital mutilation(FGM). We describe the clinical presentation and outcomes of women from a tertiary perineal clinic based on data collected over an 11-year period. METHODS: This is a retrospective observational study. A one-stop outpatient service was offered to all women who sustained OASIs (postnatally and antenatally in a subsequent pregnancy), perineal complications (within 16 weeks postpartum), FGM and/or peripartum symptoms of urinary/anal incontinence or prolapse. Assessment included history with validated questionnaires, examination and anal manometry and endoanal ultrasound when appropriate. Outcomes were compared among different grades of OASIs. Management of each type of presentation was reported with outcomes. RESULTS: There were 3254 first attendance episodes between 2006 and 2016. The majority (58.1%) were for OASIs, followed by perineal wound complications. Compared to the lower grades, the higher grades of OASI were associated with poorer outcomes in terms of symptoms, investigations and complications. Women with OASIs had unrelated symptoms such as urinary incontinence, perineal pain and wound infections that needed further intervention. A high proportion(42%) of wound complications required further specialist management. CONCLUSION: We describe a dedicated, one-stop perineal clinic model for antenatal and postnatal women for management of perineal and pelvic floor disorders. This comprehensive and novel data will enable clinicians to better counsel women regarding of outcomes after OASI and focus training to minimize risks of morbidities

Building Virtual Earth Observatories using Ontologies and Linked Geospatial Data

TELEIOS is a European project that addresses the need for scalable access to petabytes of Earth Observation data and the discovery of knowledge that can be used in applications. To achieve this, TELEIOS builds on scientific database technologies (array databases, SciQL, data vaults), Semantic Web technologies (stRDF and stSPARQL) and linked geospatial data. In this technical communication we outline the TELEIOS advancements to the state of the art and give an overview of its technical contributions up to today