D. J. Fontaine

Scenario recognition for temporal reasoning in medical domains

The recognition of high level clinical scenes is fundamental in patient monitoring. In this paper, we propose a technique for recognizing a session, i.e. the clinical process evolution, by comparison against a predetermined set of scenarios, i.e. the possible behaviors for this process. We use temporal constraint networks to represent both scenario and session. Specific operations on networks are then applied to perform the recognition task. An index of temporal proximity is introduced to quantify the degree of matching between two temporal networks in order to select the best scenario fitting a session. We explore the application of our technique, implemented in the Déjà Vu system, to the recognition of typical medical scenarios with both precise and imprecise temporal information.

Improving the Spatial-Temporal Clue Based Segmentation by the Use of Rhythm

Video is a major media in the society of information under way. Unfortunately, the full use of this media is limited by the opaque character of the video which prevents content-based access. In this paper we improve our previous spatial temporal clues-based semantic video segmentation technique, and propose the use of the rhythm within a video to more precisely capture temporal relations within a scene and between scenes in a video. Preliminary evidence based on a 7 minutes video shows that our spatial temporal clues-based segmentation technique coupled with the rhythm consideration fully detect the narrative structure of a video.

Temporal Scenario Recognition for Intelligent Patient Monitoring

The recognition of high level clinical scenes as they are developing is fundamental in patient monitoring. In this paper, we propose a technique to recognize on the fly a session, i.e. the clinical processs evolution, by comparison to a predetermined set of scenarios, i.e. the possible behaviours for this process. We use temporal constraint networks to represent both scenario and session. Specific operations on networks are then applied to perform the recognition task. An index of proximity is introduced to quantify the degree of matching between two temporal networks and used to select the best scenario fitting a session. We explore the application of our technique to the recognition of typical scenarios for mechanical ventilation management.

Structure and dynamics of the Earth's polar ionosphere: recent results inferred from incoherent scatter sounders

For 20 years, a large part of ionospheric research has been devoted to high latitudes and in particular to the range 60–70° where an oval of auroras permanently encircles each pole. The auroral light emissions are accompanied by the production of ionization, electric currents and fields. Indeed, the auroral latitudes play a dominant role in the ionospheric electrodynamics because electric fields and currents reach thus at their largest intensities. Observations from low-altitude satellites and from ground-based facilities have contributed to the analysis and modelling of the structure and dynamics of the auroral ionosphere. The results illustrated here are inferred from observations of the European Japanese incoherent scatter radars (EISCAT) based in North Scandinavia. Recently, the field of view of the EISCAT facilities has been extended toward the pole with two radars built in 1996 and 2000 at Spitzbergen (78°N): the EISCAT Svalbard radars. Other ground-based instruments (magnetometers, photometers, etc) have also been deployed at the same location. At first sight, the ionization production in the polar ionosphere is expected to be weak because of the reduced solar illumination. The first observations reveal, in contrast, the presence of intense and variable structures, which are still under investigation. To develop our understanding of these events, we discuss the theoretical results given by the particle penetration from solar origin, and of its effects into the dayside polar ionosphere.

An approach by graphs for the recognition of temporal scenarios

This paper presents an approach by graphs for the recognition of temporal scenarios, that represent models of the dynamical behavior of a system. The aim of the presented work is to analyze the relative situation of a scenario and an effective behavior of the system, called a session. Different symbolic levels of recognition are proposed to qualify this status. All these levels, as well as most of the properties, are formulated in terms of graphs of temporal constraints. Different contexts are analyzed, where the session is either statically built, when considered as a history, or dynamically built, when information is treated in an incremental manner or on-line. In a second phase, each status is refined using a numeric estimation of the proximity between a scenario and a session. This estimation is performed by calculating an overlapping index or a temporal difference index between the volumes of the domains corresponding to the temporal graphs of the scenario and the session.

Recognising a scenario by calculating a temporal proximity index between constraint graphs

The recognition of temporal scenarios is expressed by means of the proximity between a scenario (which represents a systems possible behavior) and a session (which describes the observed behaviour). This recognition is qualified with a proximity index, which allows one to classify, either online or offline, the scenario candidates for an explanation of the evolution. This approach, when used in a dynamic systems supervisory or diagnostic tasks, opens up possibilities for using or learning scenarios, or even for structuring the scenarios.

Structuring of the Magnetospheric Plasma by the Solar Terrestrial Interactions

The existence of a magnetospheric cavity around a planet depends on the interactions of the planet including its atmospheric and magnetic environment with the interplanetary medium. A magnetized planet like the Earth sets a magnetic obstacle against the supersonic super-Alfvenic solar wind flow. The solar wind pressure shapes the magnetosphere, compressing it on the dayside to a few Earth’s radii while the nightside tail extends to hundreds of Earth’s radii. Away from a homogeneous and constant distribution, very different plasma regions have been identified inside the magnetosphere. Mass and energy transfers with the solar wind are considered as responsible for the magnetospheric plasma structure and dynamics at large-scale as well as for impulsive or transient events. However, these transfer processes remain poorly understood, and reconnection and other working assumptions are presently put forward and developed. Detailed descriptions of the magnetosphere at various complexity levels can be found in textbooks on space plasma physics. This simplified introduction only aims at proposing keys to get an insight into the structure of the magnetospheric plasma, into a few basic concepts and specific processes at the root of the present understanding and also into questions and issues to be addressed in the future.