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DTSTART:20190331T010000
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DTSTART:20191027T010000
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DTSTART:20200329T010000
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DTSTART;TZID=Europe/Paris:20200312T130000
DTEND;TZID=Europe/Paris:20200312T140000
DTSTAMP:20260430T021010
CREATED:20200316T165354Z
LAST-MODIFIED:20200316T165501Z
UID:784-1584018000-1584021600@www.naxys.be
SUMMARY:Jérôme Daquin (UNamur)
DESCRIPTION:Title: Aspects of the secular dynamics of terrestrial orbits \nAbstract: The threat raised by space debris has vivified long-term studies of terrestrial orbits. To apprehend the motion on long time scales\, the Astrodynamics community has translated\, deployed and adapted many tools coming from Dynamical System theory and Celestial Mechanics: from the construction of effective averaged models more amenable to analytical and/or numerical investigations to the construction of resonant normal forms\, including modern dynamical chaos indicator to visualise the template of the phase-space.  Those efforts contributed to foster the `passive debris removal ideology’\, where natural perturbations are ‘surfed’ rather than `counteracted’. In this talk\, I will review and discuss some aspects of the long-term dynamics of terrestrial orbits\, especially in the range of medium altitude. I will then present recent results obtained by the author and collaborators on the 2g+h lunisolar resonance where a (normally hyperbolic) manifold structure has been identified.
URL:https://www.naxys.be/event/jerome-daquin-unamur/
LOCATION:E22
CATEGORIES:NAXYS Seminar
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DTSTART;TZID=Europe/Paris:20200326T130000
DTEND;TZID=Europe/Paris:20200326T140000
DTSTAMP:20260430T021010
CREATED:20200316T165112Z
LAST-MODIFIED:20200316T165248Z
UID:779-1585227600-1585231200@www.naxys.be
SUMMARY:Justin Buhendwa Nyenyezi (ISP-Bukavu\, DRC) - POSTPONED
DESCRIPTION:Title: A Low-rank tensor based preconditioner for accelerating deformable 3D medical image registration \nAbstract: Modeled as a variational problem\, the deformable 3D image registration problem needs to solve a sequence of linear systems during the optimization process. Although these linear systems are sparse and structured\, they are very large and ill conditioned. This leads to low convergence rate of the algorithms used to solve the problem or to inaccurate solutions. \nSince it is observed that much of the time is spent in the solution of these linear systems\, there is a need to provide efficient system solvers. Let N be the number of voxels in the image. Algorithms with linear complexity O(N ) based on fast Discrete Cosine Transforms or additive spliting operator are yet available. However\, this linear complexity may be far too large for large 3D medical images. In our current study\, we examine the contribution of a specific Low-rank preconditioner in a tensor-train format. We argue that\, this preconditioner offers the most compromise between complexity and precision\, since it allows to replace this linear\ncomplexity by a logarithmic complexity O(log N ). \nFor this purpose\, we first propose to use a compressed representation of data with a given accuracy ε using tensor train format. Then\, within this tensor train format\, we propose this low-rank preconditioner build with spectral information to speedup and stabilize the system solver. A benchmark of some registration algorithms on a large set of 3D medical images and different from their linear system solvers is provided. The benchmark relies on the perfomance profile based on the earlier decrease of the function value.
URL:https://www.naxys.be/event/justin-buhendwa-nyenyezi-isp-bukavu-drc-postponed/
LOCATION:E25
CATEGORIES:NAXYS Seminar
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