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Dans le district de l’Ouest Lausannois s’annonce un vaste chantier, celui de la ville durable. La question commerciale semble étonnamment peu traitée, voire absente des documents de planification de ce morceau de ville en devenir. Pourtant, la transition n ...
We tackle the problem of trajectory planning in an environment comprised of a set of obstacles with uncertain time-varying locations. The uncertainties are modeled using widely accepted Gaussian distributions, resulting in a chance-constrained program. Con ...
In modular robotics, there is classically a compromise between coupling complexity and functionality. The mechanical and electrical designs are linked, such that adding electrical features often requires redesigning the mechanical components. However, incr ...
The effects of operational and geometrical uncertainties on Tip Leakage Vortex (TLV) characteristics are investigated in the current research. Geometrical uncertainties are comprised of manufacturing tolerances or gradual geometry degradation over the time ...
To assess the number of life-bearing worlds in astrophysical environments, it is necessary to take the intertwined processes of abiogenesis (birth), extinction (death), and transfer of life (migration) into account. We construct a mathematical model that i ...
The early time high altitude electromagnetic pulse conducted environment calculation is revisited by using the transmission line (TL) theory and including high-frequency corrections that were not present in the earlier studies. Waveform salient parameters, ...
In robotics, ergodic control extends the tracking principle by specifying a probability distribution over an area to cover instead of a trajectory to track. The original problem is formulated as a spectral multiscale coverage problem, typically requiring t ...
We introduce a protocol addressing the conformance test problem, which consists in determining whether a process under test conforms to a reference one. We consider a process to be characterized by the set of end products it produces, which is generated ac ...
We study a stochastic program where the probability distribution of the uncertain problem parameters is unknown and only indirectly observed via finitely many correlated samples generated by an unknown Markov chain with d states. We propose a data-driven d ...
Spatial count data models are used to explain and predict the frequency of phenomena such as traffic accidents in geographically distinct entities such as census tracts or road segments. These models are typically estimated using Bayesian Markov chain Mont ...
