Ruxandra Stoean

Processed dataset from: Cold call: the acoustic repertoire of Ross Sea killer whales (Orcinus orca, Type C) in McMurdo Sound, Antarctica [R.Wellard et. al, 2020]

Dragomir Andrei, Ruxandra Stoean

For our study, we used a procedure similar to Sandholm [2023] in order to splitthe raw sound data into more manageable sound segments. This was required dueto the highly volatile length of the recordings presented in the original Wellard et al.[2020a] paper.We …

Processed dataset from: Cold call: the acoustic repertoire of Ross Sea killer whales (Orcinus orca, Type C) in McMurdo Sound, Antarctica [R.Wellard et. al, 2020]

Dragomir Andrei, Ruxandra Stoean

For our study, we used a procedure similar to Sandholm [2023] in order to splitthe raw sound data into more manageable sound segments. This was required dueto the highly volatile length of the recordings presented in the original Wellard et al.[2020a] paper.We …

Garbage vs Non-garbage

Ruxandra Stoean, Cătălin Stoean

The images are gathered by students from several upper primary and lower secondary schools in Europe with the aim of training an AI model for distinguishing between pictures of garbage and non-garbage. The cooperation was based on a KA220 Erasmus+ project.The images …

Garbage vs Non-garbage

Ruxandra Stoean, Cătălin Stoean

The images are gathered by students from several schools in Europe with the aim o training an AI model for distinguishing in an image between garbage and non-garbage. The cooperation was based on a KA220 Erasmus+ project.The images were uploaded by the …

Evaluation Performance of Metaheuristics-Tuned Convolutional Neural Networks for Direct Current Motor Using Mel Spectrograms

Aleksandar Petrović, Cătălin Stoean, Ruxandra Stoean, Luka Jovanović et autres

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Understanding of Latent Spaces in a Battery Aging Prediction Model Through eXplainable AI

Carlos Cano-Domingo, Manuel Soler‐Ortiz, David Modesto, Anas Belfadil et autres

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Improving PV Power Prediction Based on GRU and Meteorological Factors

Myriam Cumbajín, Ruxandra Stoean, José A. Aguado, Gonzalo Joya

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Symmetrical Current Flow Reconstruction for Sector-Shaped Multi-wire Cables Using Machine Learning

Ariana-Andra Şerpar, Ruxandra Stoean, Carlos Cano-Domingo, Ann-Sophie Bülter et autres

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Battery State-of-Health Prediction Using XGBoost Tuned by Modified Metaheuristics

Dejan Bulaja, Nebojša Bačanin, Ruxandra Stoean, Branislav Radomirović et autres

Reliable state-of-health (SOH) prediction is critical for ensuring the safety and dependability of batteries. Traditional data-driven techniques primarily rely on historical battery data to forecast future performance. However, since the degradation of the battery SOH is significantly influenced by upcoming operational loads, …

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Deep learning event detector from long-term signal variation for seismic activity warning out of Schumann resonance

Carlos Cano-Domingo, Ruxandra Stoean, Manuel Soler‐Ortiz, Nuria Novas et autres

Deep Learning (DL) has shown capability in many areas of impact on everyday life. The paper proposes a DL architecture tailored for event detection from examining the time evolution of a signal. With temporal characteristics extracted by a Convolutional Neural Network (CNN) …

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A hybrid deep learning approach for enhancing the Lorentzian curve fit algorithm for Schumann resonance

Carlos Cano-Domingo, Ruxandra Stoean, Gonzalo Joya, Nuria Novas et autres

Schumann Resonance (SR) represents a set of very weak signals formed by the electromagnetic wave propagation along the Earth-ionosphere cavity. Traditionally, SR studies have focused on extracting only their first mode using the average frequency spectrum over long segments. However, advances in …

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A Machine Learning Hourly Analysis on the Relation the Lonosphere and Schumann Resonance Frequency

Carlos Cano-Domingo, Ruxandra Stoean, Gonzalo Joya, Nuria Novas et autres

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