Publications related to Nonprobability sampling

Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Stewart Cole, Jean-Paul Richard Kneib, Andrei Variu, Xin Chen, Daniel Felipe Forero Sanchez, Eduardo Sanchez, Zheng Zheng, Hua Zhang, Sun Hee Kim, Cheng Zhao

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg(2) over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI ...

Iop Publishing Ltd2024

Into the ice: Exploration and data capturing in glacial moulins by a tethered robot

Josephine Anna Eleanor Hughes, Max Mirko Polzin

Glacial moulins (cylindrical meltwater drainage shafts) provide valuable insights into glacier dynamics, but are inaccessible and hazardous environments for humans to study. Exploring them using passive sensor probes has revealed their complex geometry, wh ...

Wiley2024

Identification of typical district configurations: A two-step global sensitivity analysis framework

François Maréchal, Jonas Schnidrig, Cédric Terrier

The recent geopolitical conflicts in Europe highlighted the sensibility of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy system configurations to ensure energy supply stability, it is necess ...

2023

Pre-annealing for improved LPCVD deposited boron-doped poly-Si hole-selective contacts

Franz-Josef Haug, Luca Massimiliano Antognini, Josua Andreas Stückelberger, Xinyu Zhang, Zhao Wang, Jie Yang

We demonstrate the beneficial effect of a pre-annealing step prior to the boron diffusion on passivation and contact resistivity of industrially LPCVD deposited poly-Si/SiOX hole-selective contacts. We investigate the influence of the pre-annealing tempera ...

ELSEVIER2023

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Cristina Ramona Cudalbu

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impa ...

FRONTIERS MEDIA SA2023

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

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

Stephen William Wasilewski

To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into di ...

EPFL2023

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

Detection of Settlements in Tanzania and Mozambique by Many Regional Few-Shot Models

Devis Tuia, Marc Conrad Russwurm, Lloyd Haydn Hughes

In this work, we propose an approach to aid in mapping small settlements, which are often misclassified by models trained on a large-scale context (global or regional). We leverage pre-trained land cover models and few-shot learning to enhance the detectio ...

2023

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023