Lukas Calefice
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View article: Search for the decay B0 → ϕϕ
Search for the decay B0 → ϕϕ Open
A bstract A search for the decay B 0 → ϕϕ is made using pp collision data collected with the LHCb detector at centre-of-mass energies of 7, 8 and 13 TeV, corresponding to an integrated luminosity of 9 fb − 1 . No significant signal is obse…
View article: Measurement of ψ(2S) to J/ψ cross-section ratio as function of multiplicity in pPb collisions at $$ \sqrt{s_{\textrm{NN}}}=8.16 $$ TeV
Measurement of ψ(2S) to J/ψ cross-section ratio as function of multiplicity in pPb collisions at $$ \sqrt{s_{\textrm{NN}}}=8.16 $$ TeV Open
A bstract The production ratio of ψ (2 S ) to J/ψ charmonium states is presented as a function of multiplicity in proton-lead collisions at a centre-of-mass energy of $$ \sqrt{s_{\textrm{NN}}}=8.16 $$ TeV, for both prompt and nonpro…
View article: Coherent photoproduction of ρ0, ω and excited vector mesons in ultraperipheral PbPb collisions
Coherent photoproduction of ρ0, ω and excited vector mesons in ultraperipheral PbPb collisions Open
A bstract The invariant-mass distribution for the coherent photoproduction of dipions in ultraperipheral PbPb collisions is measured using data, corresponding to an integrated luminosity of 224.6 ± 9.6μb − 1 , collected by the LHCb experim…
View article: Summary of the trigger systems of the Large Hadron Collider experiments ALICE, ATLAS, CMS and LHCb
Summary of the trigger systems of the Large Hadron Collider experiments ALICE, ATLAS, CMS and LHCb Open
In modern high energy physics (HEP) experiments, triggers perform the important task of selecting, in real time, the data to be recorded and saved for physics analyses. As a result, trigger strategies play a key role in extracting relevant…
View article: A Novel Spanish Dataset for Financial Education Text Simplification Targeting Visually Impaired Individuals
A Novel Spanish Dataset for Financial Education Text Simplification Targeting Visually Impaired Individuals Open
Automatic Text Simplification (ATS) is a crucial task in natural language processing, aimed at making texts more comprehensible, particularly for specific groups such as individuals with visual impairments. One of the primary challenges in…
View article: Experience and results from running the LHCb trigger system at 30MHz
Experience and results from running the LHCb trigger system at 30MHz Open
The LHCb experiment underwent a major upgrade of its detector for the ongoing third run of data taking at the LHC. A key feature of this upgrade is the complete redesign of the data acquisition chain that allows to run a fully software-bas…
View article: Out-of-Distribution Detection with Memory-Augmented Variational Autoencoder
Out-of-Distribution Detection with Memory-Augmented Variational Autoencoder Open
This paper proposes a novel method capable of both detecting OOD data and generating in-distribution data samples. To achieve this, a VAE model is adopted and augmented with a memory module, providing capacities for identifying OOD data an…
View article: Exploration and selection of LLM models for financial text simplification
Exploration and selection of LLM models for financial text simplification Open
This research is dedicated to the simplification of Spanish-language financial texts to enhance accessibility for screen readers. We present a qualitative and quantitative analysis of the text simplification process, employing a set of Spa…
View article: Summary of the trigger systems of the Large Hadron Collider experiments ALICE, ATLAS, CMS and LHCb
Summary of the trigger systems of the Large Hadron Collider experiments ALICE, ATLAS, CMS and LHCb Open
In modern High Energy Physics (HEP) experiments, triggers perform the important task of selecting, in real time, the data to be recorded and saved for physics analyses. As a result, trigger strategies play a key role in extracting relevant…
View article: Lexical Complexity Prediction and Lexical Simplification for Catalan and Spanish: Resource Creation, Quality Assessment, and Ethical Considerations
Lexical Complexity Prediction and Lexical Simplification for Catalan and Spanish: Resource Creation, Quality Assessment, and Ethical Considerations Open
Automatic lexical simplification is a task to substitute lexical items that may be unfamiliar and difficult to understand with easier and more common words. This paper presents the description and analysis of two novel datasets for lexical…
View article: A Novel Dataset for Financial Education Text Simplification in Spanish
A Novel Dataset for Financial Education Text Simplification in Spanish Open
Text simplification, crucial in natural language processing, aims to make texts more comprehensible, particularly for specific groups like visually impaired Spanish speakers, a less-represented language in this field. In Spanish, there are…
View article: An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection
An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection Open
In the area of medical imaging, one of the factors that can negatively influence the performance of prediction algorithms is the limited number of observations for each class within a labeled dataset. Usually, in order to increase the samp…
View article: CTD2022: Standalone track reconstruction and matching algorithms for GPU-based High level trigger at LHCb
CTD2022: Standalone track reconstruction and matching algorithms for GPU-based High level trigger at LHCb Open
The LHCb Upgrade in Run 3 has changed its trigger scheme for a full software selection in two steps. The first step, HLT1, will be entirely implemented on GPUs and run a fast selection aiming at reducing the visible collision rate from 30 …
View article: Effect of the high-level trigger for detecting long-lived particles at LHCb
Effect of the high-level trigger for detecting long-lived particles at LHCb Open
Long-lived particles (LLPs) show up in many extensions of the Standard Model, but they are challenging to search for with current detectors, due to their very displaced vertices. This study evaluated the ability of the trigger algorithms u…
View article: Improving Semi-supervised Deep Learning by using Automatic Thresholding to Deal with Out of Distribution Data for COVID-19 Detection using Chest X-ray Images
Improving Semi-supervised Deep Learning by using Automatic Thresholding to Deal with Out of Distribution Data for COVID-19 Detection using Chest X-ray Images Open
Semi-supervised learning (SSL) leverages both labeled and unlabeled data for training models when the labeled data is limited and the unlabeled data is vast. Frequently, the unlabeled data is more widely available than the labeled data, he…
View article: Semisupervised Deep Learning for Image Classification With Distribution Mismatch: A Survey
Semisupervised Deep Learning for Image Classification With Distribution Mismatch: A Survey Open
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
View article: Dealing with distribution mismatch in semi-supervised deep learning for COVID-19 detection using chest X-ray images: A novel approach using feature densities
Dealing with distribution mismatch in semi-supervised deep learning for COVID-19 detection using chest X-ray images: A novel approach using feature densities Open
In the context of the global coronavirus pandemic, different deep learning solutions for infected subject detection using chest X-ray images have been proposed. However, deep learning models usually need large labelled datasets to be effec…
View article: Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets
Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets Open
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
View article: Semi-supervised Deep Learning for Image Classification with Distribution Mismatch: A Survey
Semi-supervised Deep Learning for Image Classification with Distribution Mismatch: A Survey Open
Deep learning methodologies have been employed in several different fields, with an outstanding success in image recognition applications, such as material quality control, medical imaging, autonomous driving, etc. Deep learning models rel…
View article: A Comparison of CPU and GPU Implementations for the LHCb Experiment Run 3 Trigger
A Comparison of CPU and GPU Implementations for the LHCb Experiment Run 3 Trigger Open
The Large Hadron Collider beauty (LHCb) experiment at CERN is undergoing an upgrade in preparation for the Run 3 data collection period at the Large Hadron Collider (LHC). As part of this upgrade, the trigger is moving to a full software i…
View article: Review of opportunities for new long-lived particle triggers in Run 3 of the Large Hadron Collider
Review of opportunities for new long-lived particle triggers in Run 3 of the Large Hadron Collider Open
Long-lived particles (LLPs) are highly motivated signals of physics Beyond the Standard Model (BSM) with great discovery potential and unique experimental challenges. The LLP search programme made great advances during Run 2 of the Large H…
View article: arXiv : Review of opportunities for new long-lived particle triggers in Run 3 of the Large Hadron Collider
arXiv : Review of opportunities for new long-lived particle triggers in Run 3 of the Large Hadron Collider Open
Long-lived particles (LLPs) are highly motivated signals of physics Beyond the Standard Model (BSM) with great discovery potential and unique experimental challenges. The LLP search programme made great advances during Run 2 of the Large H…
View article: Dealing with Distribution Mismatch in Semi-supervised Deep Learning for Covid-19 Detection Using Chest X-ray Images: A Novel Approach Using Feature Densities
Dealing with Distribution Mismatch in Semi-supervised Deep Learning for Covid-19 Detection Using Chest X-ray Images: A Novel Approach Using Feature Densities Open
In the context of the global coronavirus pandemic, different deep learning solutions for infected subject detection using chest X-ray images have been proposed. However, deep learning models usually need large labelled datasets to be effec…
View article: A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica
A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica Open
The implementation of deep learning based computer aided diagnosis systems for the classification of mammogram images can help in improving the accuracy, reliability, and cost of diagnosing patients. However, training a deep learning model…
View article: Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning
Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning Open
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.