Diane Lingrand

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Workflows offer a powerful way to describe and deploy applications on grid infrastructures. Many workflow management systems have been proposed but there is still a lack of a system that would allow both a simple description of the dataflow of the application and an efficient execution on a grid platform. In this paper, we study the requirements of such a(More)
The medical community is producing and manipulating a tremendous volume of digital data for which computerized archiving, processing and analysis is needed. Grid infrastructures are promising for dealing with challenges arising in computerized medicine but the manipulation of medical data on such infrastructures faces both the problem of interconnecting(More)
Workflows offer a powerful way to describe and deploy applications on grid infrastructures. Many workflow management systems have been proposed but there is still a lack of a system that would allow both a simple description of the dataflow of the application and an efficient execution on a grid platform. In this paper, we study the requirements of such a(More)
In the present paper, we review and complete the equations and the formalism which allow to achieve a minimal parameterization of the retinal displacement for a monocular visual system without calibration. Considering the emergence of active visual systems for which we can not consider that the calibration parameters are either known or xed, we develop an(More)
In this paper, we study grid jobs submission latency. The latency highly impacts performances on production grids, due to its high values and variations. It is particularly prejudicial for determining the status and expected duration of jobs and it makes outliers detection difficult. In previous work, a probabilistic model of the latency has been presented.(More)
Grids reliability remains an order of magnitude below clusters on production infrastructures. This work is aimsed at improving grid application performances by improving the job submission system. A stochastic model, capturing the behavior of a complex grid workload management system is proposed. To instantiate the model, detailed statistics are extracted(More)
The NeuroLOG project designs an ambitious neurosciences middleware, gaining from many existing components and learning from past project experiences. It is targeting a focused application area and adopting a user-centric perspective to meet the neuroscientists expectations. It aims at fostering the adoption of HealthGrids in a pre-clinical community. This(More)
Grid technologies are appealing to deal with the challenges raised by computational neurosciences and support multi-centric brain studies. However, core grids middleware hardly cope with the complex neuroimaging data representation and multi-layer data federation needs. Moreover, legacy neuroscience environments need to be preserved and cannot be simply(More)
We revisit the problem of parameter estimation in computer vision, reconsidering and implementing what may be called the Kanatani's estimation method, presented here as a simple optimisation problem, so (a) without any direct reference to a probabilistic framework but (b) considering (i) non-linear implicit measurement equations and parameter constraints,(More)