Fault Diagnosis of Induction Motors Using Recurrence Quantification Analysis and LSTM with Weighted BN by Dengyu Xiao, Yixiang Huang, Chengjin Qin, Haotian Shi, Yanming Li

“…To cover those shortcomings, in this paper, two manual feature learning approaches are embedded into a deep learning algorithm, and thus, a novel fault diagnosis framework is proposed for three-phase induction motors with a hybrid feature learning method, which combines empirical statistical parameters, recurrence quantification analysis (RQA) and long short-term memory (LSTM) neural network. …”
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Categorical Cross-Recurrence Quantification Analysis Applied to Communicative Interaction during Ainsworth’s Strange Situation by Danitza Lira-Palma, Karolyn González-Rosales, Ramón D. Castillo, Rosario Spencer, Andrés Fresno

“…The metrics were estimated through a Categorical Cross-Recurrence Quantification Analysis applied to the behaviours of individuals and dyads. …”
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A Differential Biomarker Based on Recurrence Quantification Analysis of EEG Signal and Genetic Algorithm for Epilepsy Diagnosis by Vanithamani Palanisamy, A Ranichitra, Radhamani Ellapparaj

“…Among 12 calculated RQA features from EEGs, the features of longest diagonal line, transitivity and the recurrence rate with 6, 4 and 3 numbers of 100% accuracy in separating normal and epileptic EEGs yielded better results than other recurrence features. …”
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Sliding Recurrence Analysis and its Application of Gear Vibration Signal by Xiao Han, Lv Yong

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Study on incentive mechanism of reward and punishment on work efficiency of PCB welder based on recurrence quantification analysis and electroencephalogram signals by Zhang Qian, Mingyue Guo, Fuwang Wang

“…To address this issue, this study innovatively combines recurrence quantification analysis (RQA) with electroencephalogram (EEG) signals, proposing a dynamic incentive evaluation model based on the analysis of brain chaos characteristics. …”
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Application of Recurrent Neural Networks in Uncertainty Analysis of Sheet Metal Forming by Cruz Daniel, Parreira Tomás, Marques Armando, Prates Pedro, Oliveira Marta, Neto Diogo, Santos Abel, Amaral Rui, Barbosa Manuel, Pereira André

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Decoding Pain Dynamics: EEG Insights into Neural Responses and Classification via RQA Analysis by Mahsa Tavasoli, Zahra Einalou, Reza Akhondzadeh

“…For this purpose, at the first step phasic pain is produced using coldness, then dynamical features via EEG are analyzed via Recurrence Quantification Analysis (RQA) method and finally Rough neural network classifier has been used for achieving accuracy to detect and categorize pain and non-pain states. …”
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Robust confinement state classification with uncertainty quantification through ensembled data-driven methods by Yoeri Poels, Cristina Venturini, Alessandro Pau, Olivier Sauter, Vlado Menkovski, the TCV Team, the WPTE Team

“…We propose ensembling data-driven methods on two axes: model formulations and feature sets. The former considers a dynamic formulation based on a recurrent Fourier neural operator-architecture and a static formulation based on gradient-boosted decision trees. …”
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Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement by Kaustab C. Sahu, Slawomir Koziel, Anna Pietrenko-Dabrowska

“…Its main ingredient is a recurrent neural network (RNN) with the main architectural components being bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) layers. …”
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Application of Artificial Intelligence Models to Predict the Onset or Recurrence of Neovascular Age-Related Macular Degeneration by Francesco Saverio Sorrentino, Marco Zeppieri, Carola Culiersi, Antonio Florido, Katia De Nadai, Ginevra Giovanna Adamo, Marco Pellegrini, Francesco Nasini, Chiara Vivarelli, Marco Mura, Francesco Parmeggiani

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Recurrence-Based Techniques for Data-Driven Fault Diagnosis and Monitoring in Neutral-Point-Clamped Inverters by Lincoln Moura De Oliveira, Menaouar Berrehil El Kattel, Esio Eloi Dos Santos Filho, Juan C. Vasquez, Josep M. Guerrero, Fernando Luiz Marcelo Antunes

“…This paper introduces a novel data-driven condition monitoring (CM) approach for Neutral-Point-Clamped (NPC) inverters based on Recurrence Plot Analysis (RPA) and Recurrence Quantification Analysis (RQA). …”
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Graph-informed convolutional autoencoder to classify brain responses during sleep by Sahar Zakeri, Somayeh Makouei, Sebelan Danishvar

“…Then, functional connectivity features and recurrence quantification analysis were extracted from sub-bands. …”
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Child-therapist acoustic synchrony and response trajectories in autism intervention: an AI-based automated analysis using dynamic systems theory and affective computing by Giulio Bertamini, Silvia Perzolli, Arianna Bentenuto, Cesare Furlanello, Mohamed Chetouani, David Cohen, Paola Venuti

“…After AI-based automatic speech segmentation, acoustic synchrony was assessed using Cross-Recurrence Quantification Analysis to derive interaction metrics over the entire therapy sessions employing affective prosodic features. …”
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Cutting guides in mandibular tumor ablation: Are we as accurate as we think? by Omar Suhaym, Loren Moles, Nicholas Callahan

“…Purpose: Tumor margin status is critical in local tumor recurrence and is a significant prognostic factor in head and neck cancer survival. …”
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Multi-task Bayesian model combining FDG-PET/CT imaging and clinical data for interpretable high-grade prostate cancer prognosis by Maxence Larose, Louis Archambault, Nawar Touma, Raphaël Brodeur, Félix Desroches, Nicolas Raymond, Daphnée Bédard-Tremblay, Danahé LeBlanc, Fatemeh Rasekh, Hélène Hovington, Bertrand Neveu, Martin Vallières, Frédéric Pouliot

“…BSN also provides automated prostate segmentation, uncertainty quantification, personalized feature-based explanations, and introduces dynamic predictions, a novel approach that relies on short-term outcomes to refine long-term prognosis. …”
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VDMS: An Improved Vision Transformer-Based Model for PM_2.5 Concentration Prediction by Tong Zhao, Meixia Qu

“…China’s accelerating industrialization has led to worsening air pollution, characterized by recurrent haze episodes. The accurate quantification of PM_2.5 distribution is crucial for air quality assessment and public health management. …”
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A Data-Driven Approach for Predicting Remaining Useful Life of Semiconductor Devices Based on Machine Learning and Synthetic Data Generation: A Review and Case Study on SiC MOSFETs by Yarens J. Yarenscruz, Fernando Castano, Alberto Villalonga, Madhav Mishra, Rodolfo E. Haber

“…However, several challenges remain, including the availability and quality of data, as well as the uncertainty quantification of the results. To tackle these obstacles, this work explores the use of synthetic data for augmenting datasets, as well as feature selection and the assessment of different neural network architectures, including models with recurrent layers and probabilistic output. …”
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Bayesian-Optimized Multi-Task Gaussian Process Regression With Composite Kernels for Soybean Oil Futures Forecasting by Hui-Dong Yin, Yi-Yang Li

“…Traditional econometric models and machine learning approaches often struggle with non-stationary data and uncertainty quantification, while existing Gaussian process applications in agricultural markets remain underexplored. …”
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