Ontology-based Activity Recognition Framework and Services

This paper introduces an ontology-based integrated framework for activity modeling, activity recognition and activity model evolution. Central to the framework is ontological activity modeling and semantic-based activity recognition, which is supported by an iterative process that incrementally improves the completeness and accuracy of activity models. In addition, the paper presents a service-oriented architecture for the realization of the proposed framework which can provide activity context-aware services in a scalable distributed manner. The paper further describes and discusses the implementation and testing experience of the framework and services in the context of smart home based assistive living

Forward Modeling of Double Neutron Stars: Insights from Highly-Offset Short Gamma-Ray Bursts

We present a detailed analysis of two well-localized, highly offset short gamma-ray bursts---GRB~070809 and GRB~090515---investigating the kinematic evolution of their progenitors from compact object formation until merger. Calibrating to observations of their most probable host galaxies, we construct semi-analytic galactic models that account for star formation history and galaxy growth over time. We pair detailed kinematic evolution with compact binary population modeling to infer viable post-supernova velocities and inspiral times. By populating binary tracers according to the star formation history of the host and kinematically evolving their post-supernova trajectories through the time-dependent galactic potential, we find that systems matching the observed offsets of the bursts require post-supernova systemic velocities of hundreds of kilometers per second. Marginalizing over uncertainties in the stellar mass--halo mass relation, we find that the second-born neutron star in the GRB~070809 and GRB~090515 progenitor systems received a natal kick of $\gtrsim 200~\mathrm{km\,s}^{-1}$ at the 78\% and 91\% credible levels, respectively. Applying our analysis to the full catalog of localized short gamma-ray bursts will provide unique constraints on their progenitors and help unravel the selection effects inherent to observing transients that are highly offset with respect to their hosts.Comment: 18 pages, 7 figures, 1 table. ApJ, in pres

Semantic Smart Homes: Towards Knowledge Rich Assisted Living Environments

International audienceThe complexity of the Emergency Supply Chains makes its management very difficult. Hence, we present in this article a comprehensive view of the French emergency supply chain (ESC), we propose an ad hoc relationship model between actors, and a GRAI grid-based model to initiate a new approach for controlling the ESC deficiencies, especially related to decision making. Throughout the article, we discuss the interest of the use of enterprise modelling to model the ESC. We discuss too, the characterization of the different issues related to the steering of the ESC. A literature review based on the GRAI grid model is proposed and discussed too. The GRAI method is used here because it presents the advantage of using the theory of complex systems, and it provides a dynamic model of an organization by focusing on decision-making and decisions communication

A Logical Framework for Behaviour Reasoning and Assistance in a Smart Home

Abstract- Smart Homes (SH) have emerged as a realistic intelligent assistive environment capable of providing assistive living for the elderly and the disabled. Nevertheless, it still remains a challenge to assist the inhabitants of a SH in performing the “right” action(s) at the “right ” time in the “right ” place. To address this challenge, this paper introduces a novel logical framework for cognitive behavioural modelling, reasoning and assistance based on a highly developed logical theory of actions- the Event Calculus. Cognitive models go beyond data-centric behavioural models in that they govern an inhabitant’s behaviour by reasoning about its knowledge, actions and environmental events. In our work we outline the theoretical foundation of such an approach and describe cognitive modelling of SH. We discuss the reasoning capabilities and algorithms of the cognitive SH model and present the details of the various tasks it can support. A system architecture is proposed to illustrate the use of the framework in facilitating assistive living. We demonstrate the perceived effectiveness of the approach through presentation of its operation in the context of a real world daily activity scenario. Index Terms – Event calculus, cognitive modelling

muSR and Magnetometry Study of the Type-I Superconductor BeAu

We present muon spin rotation and relaxation (muSR) measurements as well as demagnetising field corrected magnetisation measurements on polycrystalline samples of the noncentrosymmetric superconductor BeAu. From muSR measurements in a transverse field, we determine that BeAu is a type-I superconductor with Hc = 256 Oe, amending the previous understanding of the compound as a type-II superconductor. To account for demagnetising effects in magnetisation measurements, we produce an ellipsoidal sample, for which a demagnetisation factor can be calculated. After correcting for demagnetising effects, our magnetisation results are in agreement with our muSR measurements. Using both types of measurements we construct a phase diagram from T = 30 mK to Tc = 3.25 K. We then study the effect of hydrostatic pressure and find that 450 MPa decreases Tc by 34 mK, comparable to the change seen in type-I elemental superconductors Sn, In and Ta, suggesting BeAu is far from a quantum critical point accessible by the application of pressure.Comment: 10 pages, 8 figure

Learning Behaviour for Service Personalisation and Adaptation

Context-aware applications within pervasive environments are increasingly being developed as services and deployed in the cloud. As such these services are increasingly required to be adaptive to individual users to meet their specific needs or to reflect the changes of their behavior. To address this emerging challenge this paper introduces a service-oriented personalisation framework for service personalisation with special emphasis being placed on behavior learning for user model and service function adaptation. The paper describes the system architecture and the underlying methods and technologies including modelling and reasoning, behavior analysis and a personalisation mechanism. The approach has been implemented in a service-oriented prototype system, and evaluated in a typical scenario of providing personalised travel assistance for the elderly using the help-on-demand services deployed on smartphone