Publications related to Further development of the RDRA method for the optimal acquisition of data in process integration retrofit projects

Related publications (11)

Machine Learning Techniques for Uncertainty Estimation in Dynamic Aperture Prediction

The dynamic aperture is an essential concept in circular particle accelerators, providing the extent of the phase space region where particle motion remains stable over multiple turns. The accurate prediction of the dynamic aperture is key to optimising pe ...

2025

Unraveling the architectural design process: A comprehensive study of challenges in designing with reused components

Corentin Jean Dominique Fivet

With increasing environmental problems such as resource scarcity, high CO₂ emissions, growing construction waste and biodiversity loss, the design strategy with reused components offers a much-needed sustainable solution. However, a radical shift in the co ...

CRC Press2025

Paediatric Personalized Research Network Switzerland (SwissPedHealth): a joint paediatric national data stream

Jacques Fellay, Dylan Lawless, Mariam Ait Oumelloul, Simon Christian J Boutry

Introduction Children represent a large and vulnerable patient group. However, the evidence base for most paediatric diagnostic and therapeutic procedures remains limited or is often inferred from adults. There is an urgency to improve paediatric healthcar ...

2024

An explorative method to support design decisions based on carbon constraints and daylight sufficiency needs

Nazanin Rezaei Oghazi

The global construction industry contributes to 37% of carbon emissions associated to both building operations and construction. To help achieve the net-zero targets set by 2050, it is mandated to achieve a 50% reduction in carbon emissions by 2030. As we ...

EPFL2024

Uncertainty quantification for Fisher-Kolmogorov equation on graphs with application to patient-specific Alzheimer's disease

Alfio Quarteroni

The Fisher-Kolmogorov equation is a diffusion-reaction PDE that models the accumulation of prionic proteins, which are responsible for many different neurological disorders. The most important and studied misfolded protein in literature is the Amyloid-beta ...

EDP SCIENCES S A2024

Energy, SBS symptoms, and productivity in Swiss open-space offices: Economic evaluation of standard, actual, and optimum scenarios

Dolaana Khovalyg, Dusan Licina, Verena Marie Barthelmes, Arnab Chatterjee, Cecile Anne Berquand

The fundamental aspiration of new-generation high-performing buildings is to reduce energy use while securing indoor environmental quality conducive to human health and productivity. However, existing frameworks for identifying Key Performance Indicators ( ...

PERGAMON-ELSEVIER SCIENCE LTD2023

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Michaël Unser, Pakshal Narendra Bohra, Pol del Aguila Pla

We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

2023

Human personal air pollution clouds in a naturally ventilated office during the COVID-19 pandemic

Dusan Licina, Shen Yang, Maria Viviana Gonzalez Serrano

Personal cloud, termed as the difference in air pollutant concentrations between breathing zone and room sites, represents the bias in approximating personal inhalation exposure that is linked to accuracy of health risk assessment. This study performed a t ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Influence of the molecular weight and physical properties of a thermoplastic polymer on its dynamic wetting behavior

Valentin Rougier

The wetting dynamics of molten thermoplastic polymers, which are known to influence the force balance of the triple line, are not understood properly despite their importance in many industrial processes. In particular, the influence of the molecular weigh ...

Elsevier2023

Robust Collaborative Learning with Linear Gradient Overhead

Rachid Guerraoui, Nirupam Gupta, Rafaël Benjamin Pinot, Le Nguyen Hoang, Sadegh Farhadkhani, John Stephan

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

PLMR2023

Leveraging industrial biorefineries for the energy transition

François Maréchal, Julia Granacher

Biorefineries hold the potential to provide products and energy carriers at reduced environmental impact compared to their fossil-based counterparts. Thus, they can contribute to the decarbonization of sectors in which electrification of demands is challen ...

Elsevier Sci Ltd2023