Control of an autonomous wind energy conversion system based on doubly fed induction generator supplying a non-linear load by M. L’Hadj Said, M. Ali Moussa, T. Bessaad

“…A permanent magnet synchronous machine (PMSM) connected to a wind turbine supplies this converter, that is sized proportionately to the variation range of the necessary rotational speed. …”
Get full text

Joint image reconstruction and segmentation of real-time cardiovascular magnetic resonance imaging in free-breathing using a model based on disentangled representation learning by Tobias Wech, Oliver Schad, Simon Sauer, Jonas Kleineisel, Nils Petri, Peter Nordbeck, Thorsten A. Bley, Bettina Baeßler, Bernhard Petritsch, Julius F. Heidenreich

Get full text

The autonomic response following taVNS predicts changes in level of consciousness in DoC patients by Yan Li, Francesco Riganello, Jing Yu, Martina Vatrano, Mingquan Shen, Lijuan Cheng, Xiaohua Hu, Chengcheng Ni, Feiyang Wang, Bo Zheng, ChengCheng Zhang, Chaoyi Xie, Meiqi Li, Wangshan Huang, Fangfang Shou, Nantu Hu, Steven Laureys, Haibo Di

“…Significant modulations in HRV parameters (HF, VLF, SampEn) were observed, indicating variations in autonomic response between the control group and DoC patients. …”
Get full text

Dynamic Surrogate Optimization of Vertically Stacked Nanosheet FET Based on Gaussian Process Regression by Christofer N. Yalung, Doldet Tantraviwat

Get full text

Road Crash Analysis and Modeling: A Systematic Review of Methods, Data, and Emerging Technologies by Lars Skaug, Mehrdad Nojoumian, Nolan Dang, Amy Yap

“…Key findings demonstrate the superiority of random-parameter models over fixed-parameter approaches in handling unobserved heterogeneity, the effectiveness of Bayesian hierarchical models for spatial–temporal analysis, and promising results from machine learning approaches for real-time crash prediction. …”
Get full text

Integrating infiltration processes in hybrid downscaling methods to estimate sub-surface soil moisture by Mo Zhang, Yong Ge, Jianghao Wang

Get full text

B5G Applications and Emerging Services in Smart IoT Environments by Hani Attar, Mohammed Alghanim, Jafar Ababneh, Khosro Rezaee, Ayat Alrosan, Mohanad A. Deif

“…On the other hand, the term Beyond the Fifth Generation (B5G) symbolizes certain specifications required to succeed the future-proof of the Fifth Generation (5G), i.e., the predicted high-level parameters, such as ultra-reliable low-latency communications, massive machine-type communications, and improved mobile broadband, which are essential for the expected high-level future applications; consequently, 5G wireless (cellular) networks must be reconsidered precisely and in-depth to cope with the applications’ required high-level standard parameters in B5G. …”
Get full text

Existing Line Correction Based on Cuckoo Algorithm by Wenkun WANG

Get full text

An Improved SOGI-Higher-Order Sliding Mode Observer-Based Induction Motor Speed Estimation by Enyam Kobena Badu, Effah Francis Boafo, Hammond Desmond

Get full text

Supervised autoencoder MLP for financial time series forecasting by Bartosz Bieganowski, Robert Ślepaczuk

Get full text

Deep Learning of Temperature – Dependent Stress – Strain Hardening Curves by Nikolić, Filip, Čanađija, Marko

“…The microstructure arrangement and the temperature – dependent mechanical properties of each phase were known parameters, while the output parameter was the stress – strain response of the two – phase RVE. …”
Get full text

A novel region based neighbors searching classification algorithm for big data by Rajib Kumar Halder, Mohammed Nasir Uddin, Md Ashraf Uddin

“…The K-Nearest Neighbors (KNN) algorithm remains a cornerstone of machine learning due to its intuitive design and effectiveness in classification tasks. …”
Get full text

State of the Art in Automated Operational Modal Identification: Algorithms, Applications, and Future Perspectives by Hasan Mostafaei, Mahdi Ghamami

“…Additionally, the review covers frequency-domain methods like Frequency Domain Decomposition (FDD) and Enhanced Frequency Domain Decomposition (EFDD), highlighting their application in spectral analysis and modal parameter extraction. Techniques based on machine learning (ML), deep learning (DL), and artificial intelligence (AI) are explored for their ability to automate feature extraction, classification, and decision making in large-scale SHM systems. …”
Get full text

Prediction of Blast Vibration Velocity of Buried Steel Pipe Based on PSO-LSSVM Model by Hongyu Zhang, Shengwu Tu, Senlin Nie, Weihua Ming

“…A least squares support vector machine (LS-SVM) model was established to predict the peak vibration velocity of the pipeline and determine the best parameter combination in the LS-SVM model through a local particle swarm optimization (PSO), and the results of the PSO-LSSVM model were predicted. …”
Get full text

Learning to Optimize Joint Chance-Constrained Power Dispatch Problems by Meiyi Li, Javad Mohammadi

“…Our theoretical analysis, supported by empirical evidence, reveals strong flexibility in parameter tuning, adaptability to diverse datasets, and significantly improved computational speed.…”
Get full text

Enhancing Binary Classification Performance in Biomedical Datasets: Regularized ELM with SMOTE and Quantile Transforms Focused on Breast Cancer Analysis by Brilliant Friezka Aina, Meta Kallista, Ig. Prasetya Dwi Wibawa, Ginaldi Ari Nugroho, Ivana Meiska, Syifa Melinda Naf’an

“…The final selection of the regularization parameter (C) in R-ELM influences the model's performance and calculation time. …”
Get full text

An intelligent algorithm for identifying dropped blocks in wellbores by Qian Wang, Zixuan Yang, Chenxi Ye, Wenbao Zhai, Xiao Feng

“…Feature extraction algorithms, including the principal component analysis bounding box method, triangular meshing method, triaxial projection method, local curvature method, and model segmentation projection method, were employed, which resulted in the extraction of 32 feature parameters from the point cloud data. An optimal machine learning algorithm was developed by training it with 10 machine learning algorithms and the block data collected in the field. …”
Get full text

UWB and GNSS Sensor Fusion Using ML-Based Positioning Uncertainty Estimation by Mihkel Tommingas, Taavi Laadung, Sander Varbla, Ivo Muursepp, Muhammad Mahtab Alam

“…This article presents a novel machine learning (ML) augmented sensor fusion scheme for seamless indoor-outdoor positioning using ultra-wideband (UWB) and global navigation satellite system (GNSS) sensors. …”
Get full text

Data-Driven Digital Twin Framework for Predictive Maintenance of Smart Manufacturing Systems by Tarana Khan, Urfi Khan, Adnan Khan, Calahan Mollan, Inga Morkvenaite-Vilkonciene, Vijitashwa Pandey

“…Three process parameters, namely cutting velocity, feed rate, and depth of cut, and two dependent parameters, surface roughness and power consumption, were selected for model development. …”
Get full text

Wearable IoT (w-IoT) artificial intelligence (AI) solution for sustainable smart-healthcare by Gurdeep Singh

“…These solutions exhibit real-time responses with underlying machine-learning (ML) methodologies alongside ubiquitous, context-aware, pervasive and advance software features. …”
Get full text