Publications related to Data scraping

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Properties of plasma turbulence in the boundary region of magnetically confined plasmas are investigated in three-dimensional full torus numerical simulations of TCV experiments with a lower single null divertor configuration. Simulations are performed using the full-

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, isothermal, electromagnetic, gyro-fluid model FELTOR and compare favourable and unfavourable magnetic field directions by inverting the total magnetic field. An analysis of particle transport and intermittent fluctuations, utilizing synthe

The migration of Infoscience, EPFL’s institutional repository, to DSpace-CRIS required a custom Python-based pipeline to automate the ingestion of research outputs and datasets. Limitations in default DSpace-CRIS import tools, such as insufficient query controls, incomplete metadata mappings, and a lack of deduplication mechanisms, necessitated a tailored approach.  The pipeline leverages the DSpace REST API to enable precise queries, metadata reconciliation, and robust deduplication. It incorporates fallb

This presentation explores the potential of artificial intelligence tools to automate certain recurring tasks in the archival field. It is based on concrete examples involving data processing in Excel or CSV files, directory organization, and metadata extraction. By formulating needs in natural language, it becomes possible to automatically generate appropriate formulas or scripts—for instance, to normalize dates, rename files, create folders, or extract relevant values from structured rows. The approach re

Nuclear fusion offers a promising route toward a clean and abundant energy source, though harnessing its potential remains an important scientific and engineering challenge. This thesis delves into one of the main challenges of fusion, namely managing the high heat fluxes exhausted from the plasma core. The understanding of scrape-off layer and divertor physics, which define how this heat load will be transported towards the reactor walls, is of crucial importance for the achievement of future reliable ther

The preparation of parallel corpora is a challenging task, particularly for languages that suffer from under-representation in the digital world. In a multi-lingual country like India, the need for such parallel corpora is stringent for several low-resourc ...

Machine Learning (ML) approaches are increasingly being investigated as an alternative to Random Utility Models (RUMs) for modelling passenger mode choice. These approaches have the potential to provide valuable insights into choice modelling research questions. However, the research and the methodologies used are fragmented. Whilst systematic reviews on RUMs for mode choice prediction have long existed and the methods have been well scrutinised for mode choice prediction, the same is not true for ML models

Integrating the plasma core performance with an edge and scrape-off layer (SOL) that leads to tolerable heat and particle loads on the wall is a major challenge. The new European medium size tokamak task force (EU-MST) coordinates research on ASDEX Upgrade ...

Four numerical codes are employed to investigate the dynamics of scrape-off layer filaments in tokamak relevant conditions. Experimental measurements were taken in the MAST device using visual camera imaging, which allows the evaluation of the perpendicula ...

The Web became the central medium for valuable sources of information extraction applications. However, such user-generated resources are often plagued by inaccuracies and misinformation due to the inherent openness and uncertainty of the Web. In this work we study the problem of extracting structured information out of Web data with a credibility guarantee. The ultimate goal is that not only the structured information should be extracted as much as possible but also its credibility is high. To achieve this

This paper presents two discretisation schemes for the parallel gradient operator used in scrape-off layer plasma turbulence simulations. First, a simple model describing the propagation of electrostatic shear-Alfven waves, and retaining the key elements o ...

Data scraping

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Fluctuation-driven cross-field plasma transport in FELTOR turbulence simulations of the TCV-X23 scenario

Automating Data Imports in a DSpace-CRIS’s Institutional Repository

Performance assessment of a reactor-scale tightly baffled divertor using the SOLPS-ITER software

OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation

A systematic review of machine learning methodologies for modelling passenger mode choice

Overview of progress in European medium sized tokamaks towards an integrated plasma-edge/wall solution

Multi-code analysis of scrape-off layer filament dynamics in MAST

Information Extraction on the Web with Credibility Guarantee

Numerical approach to the parallel gradient operator in tokamak scrape-off layer turbulence simulations and application to the GBS code