The robustness of popular multiclass machine learning models against poisoning attacks: Lessons and insights by Majdi Maabreh, Arwa Maabreh, Basheer Qolomany, Ala Al-Fuqaha

“…Here, instead of flipping the labels randomly, we use the clustering approach to choose the training samples for label changes to influence the classifiers’ performance and the distance-based anomaly detection capacity in quarantining the poisoned samples. …”
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Real-time bearing fault classification of induction motor using enhanced inception ResNet-V2 by Karan Kumar K, Srihari Mandava

“…The rolling bearing is a vital part used in different rotating electrical devices. Detecting defects in bearings is crucial for the safe operation of these machines. …”
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HyenaCircle: a HyenaDNA-based pretrained large language model for long eccDNA prediction by Fuyu Li, Wenxiang Lu, Yunfei Bai

“…Long eccDNAs (typically 1–5 kb) pose detection challenges due to their large size, hindering functional studies. …”
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Temperature Prediction and Fault Warning of High-Speed Shaft of Wind Turbine Gearbox Based on Hybrid Deep Learning Model by Min Zhang, Jijie Wei, Zhenli Sui, Kun Xu, Wenyong Yuan

“…This study proposes a Spatio-Temporal Attentive (STA) synergistic architecture for GHSS fault detection and early warning by utilizing the in situ monitoring data from a wind farm. …”
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Adaptive online modeling of ship maneuvering motion based on error monitoring by Yaohui YU, Suyang LIU, Zihao WANG, Wenbo XIE, Yan PENG

“…ResultsThe simulation results show that the error detection mechanism can effectively reduce the frequency of online model updating and save computational resources. …”
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Aboveground biomass estimation using multimodal remote sensing observations and machine learning in mixed temperate forest by Shashika Himandi Gardeye Lamahewage, Chandi Witharana, Rachel Riemann, Robert Fahey, Thomas Worthley

“…Utilizing remote sensing (RS) data, such as Airborne Light Detection and Ranging (LiDAR), aerial imagery, and satellite images can significantly enhance the efficiency of forest carbon monitoring efforts. …”
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Optimization of machine learning methods for de-anonymization in social networks by Nurzhigit Smailov, Fatima Uralova, Rashida Kadyrova, Raiymbek Magazov, Akezhan Sabibolda

“…By proposing a scalable and effective framework for analyzing anonymized data in social networks, this research contributes to improved fraud detection and strengthened Internet security. …”
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HSDT-TabNet: A Dual-Path Deep Learning Model for Severity Grading of Soybean Frogeye Leaf Spot by Xiaoming Li, Yang Zhou, Yongguang Li, Shiqi Wang, Wenxue Bian, Hongmin Sun

“…Furthermore, the overall generalization ability of the model is improved through hyperparameter optimization based on the tree-structured Parzen estimator (TPE). …”
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Advancing brain tumor diagnosis: Deep siamese convolutional neural network as a superior model for MRI classification by Gowtham Murugesan, Pavithra Nagendran, Jeyakumar Natarajan

“…Abstract The timely detection and precise classification of brain tumors using techniques such as magnetic resonance imaging (MRI) are imperative for optimizing treatment strategies and improving patient outcomes. …”
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Implementation of MF block in CNN for advanced REB fault diagnosis by M. Pandiyan, Narendiranath Babu T.

“…This study presents an automated detection approach for diagnosing faults in REBs using a Customized Convolutional Neural Network (C-CNN). …”
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Predicting biochar yield from biomass pyrolysis: A comprehensive data-driven approach using machine learning and SHAP analysis by Walid Abdelfattah, Munthar Kadhim Abosaoda, Krunal Vaghela, Gowrishankar J, Prabhat Kumar Sahu, Kamred Udham Singh, R. Sivaranjani, Rohit Chauhan, Siya Singla, Samim Sherzod

“…The dataset, comprising 14 chemical, physical, and reaction parameters collected from reputable studies, was processed using outlier detection via the Monte Carlo Outlier Detection (MCOD) algorithm and hyperparameter tuning to optimize model performance. …”
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Optimizing Stroke Recognition With MediaPipe and Machine Learning: An Explainable AI Approach for Facial Landmark Analysis by Reshad Ul Karim, Sammam Mahdi, Abrar Samin, Aniqua Nusrat Zereen, M. Abdullah-Al-Wadud, Jia Uddin

“…Early detection of stroke is critical for improving survival rates and recovery. …”
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Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…The framework has several key modules: data preprocessing, feature selection, outlier detection, model training, hyperparameter optimization, and model interpretation. …”
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Metaparameter optimized hybrid deep learning model for next generation cybersecurity in software defined networking environment by C. Labesh Kumar, Suresh Betam, Denis Pustokhin, E. Laxmi Lydia, Kanchan Bala, Rajanikanth Aluvalu, Bhawani Sankar Panigrahi

“…To ensure optimal performance of the CNN-BiGRU-AM model, hyperparameter tuning is performed by utilizing the seagull optimization algorithm (SOA) model to enhance the efficiency and robustness of the detection system. …”
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Robust self-supervised denoising of voltage imaging data using CellMincer by Brice Wang, Tianle Ma, Theresa Chen, Trinh Nguyen, Ethan Crouse, Stephen J. Fleming, Alison S. Walker, Vera Valakh, Ralda Nehme, Evan W. Miller, Samouil L. Farhi, Mehrtash Babadi

“…Incorporating CellMincer into standard workflows significantly improves neuronal segmentation, peak detection, and functional phenotype identification, consistently surpassing current methods in both SNR gain and consistency.…”
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Machine Learning-Based Prediction of No-Show Telemedicine Encounters by C. Mahony Reategui-Rivera, Wanting Cui, Stefan Escobar-Agreda, Leonardo Rojas-Mezarina, Joseph Finkelstein

“…A 70% training, 10% validation, and 20% testing split were used over 10 iterations, with hyperparameter tuning performed on the validation set to identify optimal model parameters. …”
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Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images by Fadwa Alrowais, Mohammed Alqahtani, Jahangir Khan, Achraf Ben Miled, Da’ad Albalawneh, Abdulwhab Alkharashi, Samah Al Zanin, Radwa Marzouk

“…The proposed ENDDFTL-ABSPFI method aims to enhance brain stroke detection and classification models using facial imaging. …”
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CAEB7-UNet: An Attention-Based Deep Learning Framework for Automated Segmentation of C-Spine Vertebrae in CT Images by Abhishek Kumar Pandey, Kedarnath Senapati, G. P. Pateel

“…Further, the model is optimized by incorporating hyperparameter optimization, specifically, hybrid learning rate scheduler strategies, along with the AdamW optimizer and custom data augmentation. …”
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A predictive analytics approach with Bayesian-optimized gentle boosting ensemble models for diabetes diagnosis by Behnaz Motamedi, Balázs Villányi

“…The GentleBoost classifier is optimized using Bayesian hyperparameter tuning, focusing on learning rate and the number of weak learners, and is validated using 10-fold cross-validation. …”
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BCSM-YOLO: An Improved Product Package Recognition Algorithm for Automated Retail Stores Based on YOLOv11 by Pingqing Hou, Shaoze Huang

“…Robustness tests confirm its strong anti-interference ability, demonstrating its effectiveness for detection and identification of supermarket goods.…”
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