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Publications associées (27)

High Resolution Air Pollution Maps in Urban Environments Using Mobile Sensor Networks

Alcherio Martinoli, Ali Marjovi, Adrian Arfire

We propose three modeling methods using a mobile sensor network to generate high spatio-temporal resolution air pollution maps for urban environments. In our deployment in Lausanne (Switzerland), dedicated sensing nodes are anchored to the public buses and ...

IEEE2015

Stochastic Modeling of Lane Distribution and Dynamic Control of Managed Lanes for Highways

Sofia Samoili

Recurrent congestion during increasingly extended daily peak periods is an escalating phenomenon with multidimensional impact.Congestion mitigation in highways is polarized between invasive infrastructure interventions and Intelligent Transportation System ...

EPFL2015

Reducing Randomness in Matrix Models for Wireless Communication

Marc Desgroseilliers

Pushed by the proliferation of antennas and of multiuser scenarios, matrices with random entries are appearing more and more frequently in information theory. This leads to the study of matrix channels, where the capacity depends on the distribution of the ...

EPFL2015

Modeling work zone crash frequency by quantifying measurement errors in work zone length

Mehmet Yildirimoglu

Work zones are temporary traffic control zones that can potentially cause safety problems. Maintaining safety, while implementing necessary changes on roadways, is an important challenge traffic engineers and researchers have to confront. In this study, th ...

Pergamon-Elsevier Science Ltd2013

Statistical modelling of the snow depth distribution in open alpine terrain

Michael Lehning

The spatial distribution of alpine snow covers is characterised by large variability. Taking this variability into account is important for many tasks including hydrology, glaciology, ecology or natural hazards. Statistical modelling is frequently applied ...

European Geosciences Union2013

Hyperspectral Image Compressed Sensing Via Low-Rank And Joint-Sparse Matrix Recovery

Pierre Vandergheynst, Mohammad Golbabaee

We propose a novel approach to reconstruct Hyperspectral images from very few number of noisy compressive measure- ments. Our reconstruction approach is based on a convex minimiza- tion which penalizes both the nuclear norm and the l2,1 mixed-norm of the d ...

Ieee2012

A Quasi-Likelihood Approach to Zero-Inflated Spatial Count Data

Anthea Monod

The increased accessibility of data that are geographically referenced and correlated increases the demand for techniques of spatial data analysis. The subset of such data comprised of discrete counts exhibit particular difficulties and the challenges furt ...

EPFL2012

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