Publications related to Systematic sampling

Sense in Motion with Belief Clustering: Efficient Gas Source Localization with Mobile Robots

Given the patchy nature of gas plumes and the slow response of conventional gas sensors, the use of mobile robots for Gas Source Localization (GSL) tasks presents significant challenges. These aspects increase the difficulties in obtaining gas measurements ...

2024

Sparse autoregressive neural networks for classical spin systems

Giuseppe Carleo, Dian Wu, Indaco Biazzo

Efficient sampling and approximation of Boltzmann distributions involving large sets of binary variables, or spins, are pivotal in diverse scientific fields even beyond physics. Recent advances in generative neural networks have significantly impacted this ...

Iop Publishing Ltd2024

Automated all-functionals infrared and Raman spectra

Nicola Marzari, Lorenzo Bastonero

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these measurements freq ...

Nature Portfolio2024

Comparison of two methods for bioaerosol sampling and characterization in a low-biomass chamber environment

Dusan Licina, Shen Yang, Marouane Merizak, Akila Muthalagu

Bioaerosols are emitted from various sources into the indoor environment and can positively and negatively impact human health. Humans are the major source of bioaerosol emissions indoors, specifically for bacteria. However, efficient sampling to guarantee ...

PERGAMON-ELSEVIER SCIENCE LTD2023

First detection of the BAO signal from early DESI data

Andrei Variu, Cheng Zhao, Anand Stéphane Raichoor, David Schlegel

We present the first detection of the baryon acoustic oscillations (BAOs) signal obtained using unblinded data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). From a selected sam ...

Oxford Univ Press2023

Virtual metrology applied to milling process

Paul Arthur Adrien Pierre Dreyfus

Production quality and process efficiency are the two main drivers that lead any industrial strategy. To ensure product quality, a duality historically existed between two approaches, namely batch sampling and systematic sampling. In batch sampling, the ba ...

EPFL2022

Mechanical intelligence for learning embodied sensor-object relationships

Ahalya Prabhakar

Intelligence involves processing sensory experiences into representations useful for prediction. Understanding sensory experiences and building these contextual representations without prior knowledge of sensor models and environment is a challenging unsup ...

Nature Portfolio2022

Customized Neural Network training to predict the highly imbalanced data of domestic hot water usage

Dolaana Khovalyg, Amirreza Heidari

Despite space heating and cooling, the energy use for hot water production has not changed significantly over time and accounts for a big share in modern, well-insulated buildings. The main challenge of hot water generation lies in the highly stochastic na ...

CLIMA 2022 conference2022

Influence of depositional fabric on mechanical properties of naturally deposited sands

Gioacchino Viggiani, Edward Carlo Giorgio Andò

Fabric characteristics and shear deformation behaviour were analysed in four intact small-scale samples, including two disturbed and two undisturbed samples of naturally deposited sand from a shoal in the San Francisco Bay. Triaxial compression tests were ...

ICE PUBLISHING2022

Human mortality at extreme age

Anthony Christopher Davison, Léo Raymond-Belzile

We use a combination of extreme value statistics, survival analysis and computer-intensive methods to analyse the mortality of Italian and French semi-supercentenarians. After accounting for the effects of the sampling frame, extreme-value modelling leads ...

ROYAL SOC2021

Unbiased Monte Carlo cluster updates with autoregressive neural networks

Giuseppe Carleo, Riccardo Rossi, Dian Wu

Efficient sampling of complex high-dimensional probability distributions is a central task in computational science. Machine learning methods like autoregressive neural networks, used with Markov chain Monte Carlo sampling, provide good approximations to s ...

AMER PHYSICAL SOC2021

Test rooms to study human comfort in buildings: A review of controlled experiments and facilities

Dusan Licina, Mengdi Kong

Occupants' comfort perception affects building energy consumptions. To improve the understanding of human comfort, which is crucial to reduce energy demand, laboratory experiments with humans in controlled environments (test rooms) are fundamental, but the ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Spatial and temporal heterogeneity of methane ebullition in lowland headwater streams and the impact on sampling design

Andrew Lean Robison

Headwater streams are known sources of methane (CH4) to the atmosphere, but their contribution to global scale budgets remains poorly constrained. While efforts have been made to better understand diffusive fluxes of CH4 in streams, much less attention has ...

American Society of Limnology and Oceanography2021

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

François Maréchal, Ivan Daniel Kantor, Julia Granacher

Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of reliable design solutions difficult. We propose an algorithm fo ...

2021

Automatic Content Curation of Visual Heritage

Mathieu Salzmann, Frédéric Kaplan, Delphine Ribes Lemay, Nicolas Henchoz, Valentine Bernasconi

Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum fü ...

2021

Uncertain Sampling with Certain Priors

Golnooshsadat Elhami

Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...

EPFL2021

The role of demand in fostering product vs process innovation: a model and an empirical test

Gabriele Pellegrino

While the extant innovation literature has provided extensive evidence of the so-called "demand-pull" effect, the possible diverse impact of demand evolution on product vs process innovation activities has not been yet investigated. This paper develops a f ...

SPRINGER2021

Imaging plasma formation in isolated nanoparticles with ultrafast resonant scattering

Christoph Bostedt, Daniela Rupp, Alessandro Colombo

We have recorded the diffraction patterns from individual xenon clusters irradiated with intense extreme ultraviolet pulses to investigate the influence of light-induced electronic changes on the scattering response. The clusters were irradiated with short ...

2020

Structural Screening and Design of Platinum Nanosamples for Oxygen Reduction

Kevin Rossi

Nanocatalyst-by-design promises to empower the next generation of electrodes for energy devices. However, current numerical methods consider individual and often geometrical closed-shell nanoparticles, neglecting how the coexistence of several and structur ...

AMER CHEMICAL SOC2020

Testing of asymptomatic individuals for fast feedback-control of COVID-19 pandemic

Gabriel Aeppli

We argue that frequent sampling of the fraction ofa priorinon-symptomatic but infectious humans (either by random or cohort testing) significantly improves the management of the COVID-19 pandemic, when compared to intervention strategies relying on data fr ...

2020