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Concept

Statistical model validation

Related publications (31)

Scenario optimization for the tokamak ramp-down phase in RAPTOR: A. Analysis and model validation on ASDEX Upgrade

Olivier Sauter, Federico Alberto Alfredo Felici, Anna Teplukhina, Simon Van Mulders, Cassandre Ekta Contré

We discuss how the combination of experimental observations and rapid modeling has enabled to improve understanding of the tokamak ramp-down phase in ASDEX Upgrade. A series of dedicated experiments has been performed, to disentangle the effect of individu ...

Iop Publishing Ltd2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection

Lijing Xin

Metabolic changes precede malignant histology. However, it remains unclear whether detectable characteristic metabolome exists in esophageal squamous cell carcinoma (ESCC) tissues and biofluids for early diagnosis. Here, we conduct NMR- and MS-based metabo ...

Nature Portfolio2024

Can lateral tenodesis improve the rotational stability of the ACL reconstruction? A finite element analysis

Dimitar Yuriev Stanev

One of the most common knee injuries is the Anterior Cruciate Ligament (ACL) rupture with severe implications on knee stability. The usual treatment is the ACL Reconstruction (ACLR) surgery where the surgeon replaces the torn ligament with a graft in an ef ...

Public Library Science2024

A modelling framework for modern heritage buildings energy simulation

Franz Graf, Giulia Marino, Giuseppe Galbiati

The latest European polices highlight the urgent need to rehabilitate the existing building stock, responsible for 40 % of the EU's total energy consumption. In this process, a key role is played by thermal simulations, assessing the effective energy perfo ...

Elsevier2023

Bed Topography Inference from Velocity Field Using Deep Learning

Christophe Ancey, Mehrdad Kiani Oshtorjani

Measuring bathymetry has always been a major scientific and technological challenge. In this work, we used a deep learning technique for inferring bathymetry from the depth-averaged velocity field. The training of the neural network is based on 5742 labora ...

2023

Characterization of wind turbine flow through nacelle-mounted lidars: a review

Fernando Porté Agel, Peter Andreas Brugger

This article provides a comprehensive review of the most recent advances in the planning, execution, and analysis of inflow and wake measurements from nacelle-mounted wind Doppler lidars. Lidars installed on top of wind turbines provide a holistic view of ...

2023

An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0

Adrien Michel

Many methods exist to model snow densification in order to calculate the depth of a single snow layer or the depth of the total snow cover from its mass. Most of these densification models need to be tightly integrated with an accumulation and melt model a ...

COPERNICUS GESELLSCHAFT MBH2023

Spatiotemporal wildfire modeling through point processes with moderate and extreme marks

Jonathan Koh Boon Han

Accurate spatiotemporal modeling of conditions leading to moderate and large wildfires provides better understanding of mechanisms driving fire-prone ecosystems and improves risk management. Here, we develop a joint model for the occurrence intensity and t ...

2023

Do we really measure what we think we are measuring?

Michael Herzog, Janir Nuno Ramos Antunes Da Cruz, Simona Adele Garobbio, Dario Alejandro Gordillo Lopez

Tests used in the empirical sciences are often (implicitly) assumed to be representative of a given research question in the sense that similar tests should lead to similar results. Here, we show that this assumption is not always valid. We illustrate our ...

Cell Press2023

Laterally unconfined neutral or negative buoyancy inflow into a quiescent ambient over sloping bottom

Haoran Shi

This work studies the nearshore hydrodynamics of a shallow turbulent flow entering a laterally unconfined quiescent ambient with a sloping bottom boundary. Examples of such flow are neutrally buoyant ebb tidal jets and hyperpycnal river plumes entering ope ...

EPFL2023

Biomass to energy: a machine learning model for optimum gasification pathways

Berend Smit, Kevin Maik Jablonka

Biomass is a highly versatile renewable resource for decarbonizing energy systems. Gasification is a promising conversion technology that can transform biomass into multiple energy carriers to produce heat, electricity, biofuels, or chemicals. At present, ...

Royal Soc Chemistry2023

Deep Learning Generalization with Limited and Noisy Labels

Mahsa Forouzesh

Deep neural networks have become ubiquitous in today's technological landscape, finding their way in a vast array of applications. Deep supervised learning, which relies on large labeled datasets, has been particularly successful in areas such as image cla ...

EPFL2023

Coupling remote sensing and particle tracking to estimate trajectories in large water bodies

Tamar Kohn, Alfred Johny Wüest, Damien Bouffard, Chaojie Li

Propelled by the rapid development of equipment, technology and computational power, the monitoring and simulation of the hydrodynamics in lakes have steadily advanced. In contrast, water quality simulations are more difficult to implement, due to the diff ...

Elsevier2022

SporTran: A code to estimate transport coefficients from the cepstral analysis of (multivariate) current time series

Loris Ercole

SporTran is a Python utility designed to estimate generic transport coefficients in extended systems, based on the Green-Kubo theory of linear response and the recently introduced cepstral analysis of the current time series generated by molecular dynamics ...

ELSEVIER2022

Improving the efficiency of identifying malignant pulmonary nodules before surgery via a combination of artificial intelligence CT image recognition and serum autoantibodies

Jiancheng Yang

ObjectiveTo construct a new pulmonary nodule diagnostic model with high diagnostic efficiency, non-invasive and simple to measure. MethodsThis study included 424 patients with radioactive pulmonary nodules who underwent preoperative 7-autoantibody (7-AAB) ...

SPRINGER2022

Fading of brain network fingerprint in Parkinson's disease predicts motor clinical impairment

Enrico Amico

The clinical connectome fingerprint (CCF) was recently introduced as a way to assess brain dynamics. It is an approach able to recognize individuals, based on the brain network. It showed its applicability providing network features used to predict the cog ...

Wiley2023

Frequency-domain data-driven position-dependent controller synthesis for Cartesian Robots

Alireza Karimi, Philippe Louis Schuchert

Cartesian robots have position-dependent dynamics that should be accounted for in high performance applications. Traditional methods design Linear Time Invariant (LTI) controllers which are robustly stable with respect to position variations, but require a ...

2023

New particle formation event detection with Mask R-CNN

Lubna Dada

Atmospheric new particle formation (NPF) is an important source of climate-relevant aerosol particles which has been observed at many locations globally. To study this phenomenon, the first step is to identify whether an NPF event occurs or not on a given ...

Copernicus Publications2022

Perturbation theory models for LSST-era galaxy clustering: Tests with subpercent mock catalog measurements in Fourier and configuration space

Jonathan Andrew Blazek

We analyze the clustering of galaxies using the z = 1.006 snapshot of the CosmoDC2 simulation, a high-fidelity synthetic galaxy catalog designed to validate analysis methods for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We prese ...

American Physical Society2022