Intelligent Fault Detection and Self-Healing Mechanisms in Wireless Sensor Networks Using Machine Learning and Flying Fox Optimization by Almamoon Alauthman, Abeer Al-Hyari

“…This paper presents an intelligent framework based on Light Gradient Boosting Machine integration for fault detection and a Flying Fox Optimization Algorithm in dynamic self-healing. …”
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Comparison of mask R-CNN and YOLOv8-seg for improved monitoring of the PCB surface during laser cleaning by Lu Qiao, Markus Veltrup, Bernd Mayer

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Construction of a risk prediction model for pulmonary infection in patients with spontaneous intracerebral hemorrhage during the recovery phase based on machine learning by Jixiang Xu, Yuan Li, Fumin Zhu, Fumin Zhu, Xiaoxiao Han, Liang Chen, Yinliang Qi, Yinliang Qi, Xiaomei Zhou, Xiaomei Zhou

“…Seven ML algorithms were employed to build predictive models, with performance evaluated based on the area under the receiver operating characteristic (AUC) curve, sensitivity, specificity, and accuracy. …”
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Context-Aware Adaptive Encryption: Integrating Sensitive Data Detection and Network intrusion detection for Dynamic Data Security and Encryption by Leonardo C. Lawrence, Ramin Giovanni, Cynthia Calongne, Abdullah Alshboul

“…The proposed system employs deep learning models to identify sensitive information and machine learning algorithms to monitor network activity for potential intrusions. …”
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You Only Look Once Version 5 and Deep Simple Online and Real-Time Tracking Algorithms for Real-Time Customer Behavior Tracking and Retail Optimization by Mohamed Shili, Osama Sohaib, Salah Hammedi

“…By leveraging these algorithms, stores can track customer behavior, identify popular products, and monitor high-traffic areas, enabling businesses to adapt quickly to customer preferences and optimize store layout and inventory management. …”
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Identification of Mattic Epipedon Degradation on the Northeastern Qinghai–Tibetan Plateau Using Hyperspectral Data by Junjun Zhi, Hong Zhu, Jingwen Yang, Qiuchen Yan, Dandan Zhi, Zhongbao Sun, Liangwei Ge, Chengwen Lv

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A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor Measurements by Masrur Ahmed, Jing Kong, Ningbo Jiang, Hiep Nguyen Duc, Praveen Puppala, Merched Azzi, Matthew Riley, Xavier Barthelemy

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Robust Predictive Maintenance for Robotics via Unsupervised Transfer Learning by Arash Golibagh Mahyari, Thomas locher

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Sustainable phytoprotection: a smart monitoring and recommendation framework using Puma Optimization for potato pathogen detection by Amal H. Alharbi, Faris H. Rizk, Khaled Sh. Gaber, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Pushan Kumar Dutta, Doaa Sami Khafaga

“…This study proposes a novel hybrid framework for potato disease classification that integrates copula-based dependency modeling with a Restricted Boltzmann Machine (RBM), further enhanced through hyperparameter tuning using the biologically inspired Puma Optimization (PO) algorithm. …”
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Advanced removal of butylparaben from aqueous solutions using magnetic molybdenum disulfide nanocomposite modified with chitosan/beta-cyclodextrin and parametric evaluation through... by Saeed Hosseinpour, Alieh Rezagholizade-shirvan, Mohammad Golaki, Amir Mohammadi, Amir Sheikhmohammadi, Zahra Atafar

“…This research fully evaluates machine learning approaches that optimize complicated environmental remediation operations while advanced nanomaterials used with data-driven optimization provide a strong adaptable method to remove organic water pollutants thus supporting sustainable treatment development. …”
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Evaluation and optimization of adaptive cruise control in autonomous vehicles using the car learning to act simulator: A performance evaluation under various weather conditions by Roza Al-Hindawi, Taqwa Alhadidi

“…Therefore, this study used the Hill Climb (HC) and Tabu Machine Learning (ML) algorithms to optimize the speed of the ego vehicle to maintain a safe spacing distance between it and the leading vehicle by training and developing CARLA using a Bayesian Network (BN).…”
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Optimizing Solar Radiation Prediction Based on The Internet of Things Platform in Photovoltaic Power Plant by Neda Ashrafi Khozani, Maryam Mahmoudi, Shabnam Nasr Esfahani

“…Meta-heuristic algorithms are utilized for optimizing tree-based methods, as well as for feature and instance selection. …”
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Prescribed‐time resilient current‐sensorless DC power converter control by Maryam Homayounzadeh, Mohamadreza Homayounzade, Mohammad‐Hassan Khooban

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A Method for Identifying Landslide-Prone Areas Using Multiple Factors and Adaptive Probability Thresholds: A Case Study in Northern Tongren, Longwu River Basin, Qinghai Province by Jiawen Bao, Xiaojun Luo, Yueling Shi, Mingyue Hou, Jichao Lv, Guoxiang Liu

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Classification Importance of Seed Morphology and Insights on Large-Scale Climate-Driven Strophiole Size Changes in the Iberian Endemic Chasmophytic Genus <i>Petrocoptis</i> (Caryop... by Jorge Calvo-Yuste, Ángela Lis Ruiz-Rodríguez, Brais Hermosilla, Agustí Agut, María Montserrat Martínez-Ortega, Pablo Tejero

“…Employing cluster and machine learning algorithms, we delineated well-defined morphogroups based on seed traits and evaluated their recognizability. …”
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Multimodal data-based human motion intention prediction using adaptive hybrid deep learning network for movement challenged person by Mustufa Haider Abidi

“…Therefore, in this paper, an Adaptive Hybrid Network (AHN) is implemented for effective human motion intention prediction. …”
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Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine) by Chuin-Hen Liew, Song-Quan Ong, David Chun-Ern Ng

“…Grid Search was used to optimize the hyperparameters of each algorithm. The study analyzed 1988 children and 30 study variables after data were processed. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…[Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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Application of Fuzzy System on Settlement of Shallow Footing on Granular Soil by Soroush Lesani

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Leveraging IGOOSE-XGBoost for the Early Detection of Subclinical Mastitis in Dairy Cows by Rui Guo, Yongqiang Dai

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