arXiv subjects

P. H. O. Silva

Publications and source records attributed to P. H. O. Silva.

5 recordsLinked to original sources

arXiv2026

Holographic information measures for spin-$3/2$ $Δ$ baryons in AdS/QCD

Spin-$3/2$ $Δ$ baryon resonances are investigated within AdS/QCD, using Rarita-Schwinger fields. The differential configurational entropy (DCE) and differential configurational complexity (DCC) associated with their bulk energy densities are computed. It yields Regge-like trajectories relating configurational information measures to the radial excitation number and the experimental mass spectrum of the $Δ$ baryons. We then extrapolate the spectrum of heavier $Δ$ baryon resonances beyond the currently established states in the PDG, also comparing them with states in the PDG that are omitted from the summary table. Our results support a relevant interplay among holographic QCD dynamics, configurational information entropy, and baryon spectroscopy in strongly coupled QCD.

hep-th↗

arXiv2025

Higher-spin light-flavor baryonic spectroscopy in AdS/QCD at finite temperature

Light-flavor baryon resonances in the $J^P=3/2^+$, $J^P=5/2^+$, and $J^P=5/2^-$ families are investigated in a soft-wall AdS/QCD model at finite temperature, including the zero temperature limit. Regge-like trajectories relating the configurational entropy underlying these resonances to both the radial quantum number and the baryon mass spectra are constructed, allowing for the extrapolation of the higher-spin light-flavor baryonic mass spectra to higher values of the radial quantum number. The configurational entropy is shown to increase drastically with temperature, in the range beyond T ~ 38 MeV. The mass spectra of baryon families are analyzed, supporting a phase transition nearly above the Hagedorn

hep-ph↗

arXiv2024

Insightful Railway Track Evaluation: Leveraging NARX Feature Interpretation

The classification of time series is essential for extracting meaningful insights and aiding decision-making in engineering domains. Parametric modeling techniques like NARX are invaluable for comprehending intricate processes, such as environmental time series, owing to their easily interpretable and transparent structures. This article introduces a classification algorithm, Logistic-NARX Multinomial, which merges the NARX methodology with logistic regression. This approach not only produces interpretable models but also effectively tackles challenges associated with multiclass classification. Furthermore, this study introduces an innovative methodology tailored for the railway sector, offering a tool by employing NARX models to interpret the multitude of features derived from onboard sensors. This solution provides profound insights through feature importance analysis, enabling informed decision-making regarding safety and maintenance.

eess.SP↗

arXiv2021

Hybrid Method Based on NARX models and Machine Learning for Pattern Recognition

This work presents a novel technique that integrates the methodologies of machine learning and system identification to solve multiclass problems. Such an approach allows to extract and select sets of representative features with reduced dimensionality, as well as predicts categorical outputs. The efficiency of the method was tested by running case studies investigated in machine learning, obtaining better absolute results when compared with classical classification algorithms.

cs.LG↗

arXiv2019

Detection of Muscle Fatigue Using Variable Bit Flow Modulation and Cross Correlation of Electromyographic Signals

The surface electromyography (sEMG) analysis can provide information on muscle fatigue status by estimation of muscle fibre conduction velocity (MFCV), a measure of the travelling speed of motor unit action potentials in muscle tissue. This paper proposes a technique for MFCV estimation using cross-correlation methods and variable bitstream modulation. The technique displays an estimate based on a set of data generated by the gain variation modulation, providing an average estimate of the MFCV. The observed trend of MFCV decrease correlates with the fatigue state of the observed muscle. Finally, the values found were compared with information from the literature, validating the method and showing the advantages of using variable modulation.

eess.SP↗