Processus

Applied sciences
Business
Administration des affaires
Business Process Management

Publications associées (22)

À propos
Confidentialité
Mentions légales

Graph Chatbot

Safety risk management in University laboratories

Anastasia Jung

Risk management has become an essential element in the functioning of modern society. Correct risk identification and assessment are undoubtedly crucial to improving overall safety; nevertheless, often, it is accompanied by the wrong selection of correctiv ...

EPFL2023

Comparative techno-economic and energy analyses of integrated biorefinery processes of furfural and 5-hydroxymethylfurfural from biomass residue

François Maréchal

For efficient feedstock and energy utilization, integrated biorefinery processes are applied to furfural production from bagasse to convert furfural residue into 5-hydroxymethylfurfural (HMF)-an important intermediate building block for the production of v ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Functional data analysis with rough sample paths?

Victor Panaretos, Neda Mohammadi Jouzdani

Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

TAYLOR & FRANCIS LTD2024

Process-informed adsorbent design guidelines for direct air capture

Berend Smit, Susana Garcia Lopez, Fergus Robert Lloyd Mcilwaine

Direct air capture using solid adsorbents is a proven technology critical to reducing our net greenhouse gas emissions to zero and beyond. Currently, academic research into the technology mainly focuses on the devel-opment of new adsorbents. However, there ...

ELSEVIER SCIENCE SA2022

Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells

Idan Segev, Werner Alfons Hilda Van Geit, Oren Amsalem

Many scientific systems are studied using computer codes that simulate the phenomena of interest. Computer simulation enables scientists to study a broad range of possible conditions, generating large quantities of data at a faster rate than the laboratory ...

FRONTIERS MEDIA SA2022

A semantic-driven tradespace framework to accelerate aircraft manufacturing system design

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

During the design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated according to key performance indicators to achieve the optimal system performance. It is a highly complex process involving multidisciplinary s ...

SPRINGER2022

Toward Code Review Notebooks

Denis Gillet, Maria Jesus Rodriguez Triana, Juan Carlos Farah, Sandy Ingram

Peer code review has proven to be a valuable tool in software engineering. However, integrating code reviews into educational contexts is particularly challenging due to the complexity of both the process and popular code review tools. We propose to addres ...

IEEE2022

Creating and controlling exceptional points of non-Hermitian Hamiltonians via homodyne Lindbladian invariance

Fabrizio Minganti

The exceptional points (EPs) of non-Hermitian Hamiltonians (NHHs) are spectral degeneracies associated with coalescing eigenvalues and eigenvectors, which are associated with remarkable dynamical properties. These EPs can be generated experimentally in ope ...

AMER PHYSICAL SOC2022

Dielectric properties of 3-3 flexible composites by infiltration of elastomers into porous ceramic structures using cellulose scaffold

Frank Nüesch, Thomas Geiger

Elastomer composites are prepared by infiltrating polydimethylsiloxane (PDMS) into a porous ceramic structure of nanoparticles. This method differs from the conventional approach, where particles are dispersed into the polymer matrix, since here, the polym ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs

Nicolas Henri Bernard Flammarion, Etienne Patrice Boursier, Loucas Pillaud-Vivien

The training of neural networks by gradient descent methods is a cornerstone of the deep learning revolution. Yet, despite some recent progress, a complete theory explaining its success is still missing. This article presents, for orthogonal input vectors, ...

NeurIPS2022

Page 2 sur 3