Multi-Objective Optimization of Milling Ti-6Al-4V Alloy for Improved Surface Integrity and Sustainability Performance by Djordje Cica, Sasa Tesic, Milisav Markovic, Branislav Sredanovic, Stevo Borojevic, Milan Zeljkovic, Davorin Kramar, Franci Pušavec

“…Moreover, a multi-objective parameter optimization model integrating the machining responses (surface roughness, microhardness, energy consumption, and productivity) and sustainability metrics (environmental impact, operator’s health and safety, and waste management) was introduced. …”
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Optimizing Class Imbalance in Facial Expression Recognition Using Dynamic Intra-Class Clustering by Qingdu Li, Keting Fu, Jian Liu, Yishan Li, Qinze Ren, Kang Xu, Junxiu Fu, Na Liu, Ye Yuan

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Permanent Magnet Assisted Synchronous Reluctance Motor for Subway Trains by Vladimir Dmitrievskii, Vadim Kazakbaev, Vladimir Prakht, Alecksey Anuchin

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Enhancing the specific modulus of Al–Li alloys: A machine learning approach to micro-alloying element identification by Lyu Jing, Li Yanan, Li Xiwu, Zheng Lei, Xiao Wei, Liu Qilong, Liu Rui, Li Zhihui, Xiong Baiqing

“…To enhance the specific modulus of aerospace structural materials, this study employs machine learning methods to optimize the micro-alloying composition of Al–Li alloys. …”
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Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm by Jianjiao Deng, Yunuo Qin, Xi Chen, Yanyong He, Yu Song, Xinpeng Zhang, Wenting Ma, Shoukui Li, Yudong Wu

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A Novel Method for Mechanical Fault Diagnosis Based on Variational Mode Decomposition and Multikernel Support Vector Machine by Zhongliang Lv, Baoping Tang, Yi Zhou, Chuande Zhou

“…A novel fault diagnosis method based on variational mode decomposition (VMD) and multikernel support vector machine (MKSVM) optimized by Immune Genetic Algorithm (IGA) is proposed to accurately and adaptively diagnose mechanical faults. …”
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Advancing in creep index of soil prediction: A groundbreaking machine learning approach with Multivariate Adaptive Regression Splines by Mohammed E. Seno, Husein Ali Zeini, Hamza Imran, Mohammed Noori, Sadiq N. Henedy, Nouby M. Ghazaly

“…Grid search hyperparameter tuning was applied to optimize the MARS model, as well as a black-box model (Support Vector Machine, SVM) and a white-box model (Lasso), with five-fold cross-validation used to assess their performance. …”
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A Review of OBD-II-Based Machine Learning Applications for Sustainable, Efficient, Secure, and Safe Vehicle Driving by Emmanouel T. Michailidis, Antigoni Panagiotopoulou, Andreas Papadakis

“…To this end, a diverse set of ML approaches is examined, encompassing supervised, unsupervised, reinforcement learning (RL), deep learning (DL), and hybrid models intended to support advanced driving analytics tasks such as fuel optimization, emission control, driver behavior analysis, anomaly detection, cybersecurity, road perception, and driving support. …”
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Prediction of clinical stages of cervical cancer via machine learning integrated with clinical features and ultrasound-based radiomics by Maochun Zhang, Qing Zhang, Xueying Wang, Xiaoli Peng, Jiao Chen, Hanfeng Yang

“…The model developed by support vector machine (SVM) emerged as the superior model. …”
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An Innovation Machine Learning Approach for Ship Fuel-Consumption Prediction Under Climate-Change Scenarios and IMO Standards by Bassam M. Aljahdali, Yazeed Alsubhi, Ayman F. Alghanmi, Hussain T. Sulaimani, Ahmad E. Samman

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Prediction of mortality risk in patients with severe community-acquired pneumonia in the intensive care unit using machine learning by Jingjing Pan, Tao Guo, Haobo Kong, Wei Bu, Min Shao, Zhi Geng

“…Abstract The aim of this study was to develop and validate a machine learning-based mortality risk prediction model for patients with severe community-acquired pneumonia (SCAP) in the intensive care unit (ICU). …”
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A Machine-Learning-Based Approach for the Detection and Mitigation of Distributed Denial-of-Service Attacks in Internet of Things Environments by Sebastián Berríos, Sebastián Garcia, Pamela Hermosilla, Héctor Allende-Cid

“…This study proposes a machine-learning-based framework to enhance DDoS attack detection and mitigation, employing Random Forest, XGBoost, and Long Short-Term Memory (LSTM) models. …”
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Machine-Learning-Powered Information Systems: A Systematic Literature Review for Developing Multi-Objective Healthcare Management by Maryam Bagheri, Mohsen Bagheritabar, Sohila Alizadeh, Mohammad (Sam) Salemizadeh Parizi, Parisa Matoufinia, Yang Luo

“…The incorporation of machine learning (ML) into healthcare information systems (IS) has transformed multi-objective healthcare management by improving patient monitoring, diagnostic accuracy, and treatment optimization. …”
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A comparative analysis of machine learning-based methods for impervious surface mapping using SAR and optical data by Siqi He, Lihong Zhu, Yiman Li, Qing Xia, Qiong Zheng, Zheng Wang, Xinyu Zou

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Machine learning approaches for predicting frailty base on multimorbidities in US adults using NHANES data (1999–2018) by Teng Li, Xueke Li, Haoran XU, Yanyan Wang, Jingyu Ren, Shixiang Jing, Zichen Jin, Gang chen, Youyou Zhai, Zeyu Wu, Ge Zhang, Yuying Wang

“…And in machine learning process, feature selection for the frailty prediction model involved three algorithms. …”
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Automation of Predictive Maintenance: An Experimental Framework for Aircraft Landing Gear by Izaak Stanton, Kamran Munir, Ahsan Ikram, Murad El‐Bakry

“…This research presents an experimental analysis comparing industry‐selected machine learning models and a hand‐picked selection of automated machine‐learning tools. …”
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Fostering non-intrusive load monitoring for smart energy management in industrial applications: an active machine learning approach by Lukas Fabri, Daniel Leuthe, Lars-Manuel Schneider, Simon Wenninger

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Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy by Tobias Schraut, Anne Schützenberger, Tomás Arias-Vergara, Melda Kunduk, Matthias Echternach, Stephan Dürr, Julia Werz, Michael Döllinger

“…Subjects were classified into two hoarseness groups based on auditory-perceptual ratings, with predicted scores serving as continuous hoarseness severity ratings. A videoendoscopic model was developed by selecting a suitable classification algorithm and a minimal-optimal subset of glottal parameters. …”
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A retrospective cohort study using machine learning to predict coronary artery lesions in children with Kawasaki disease by Yanan Duan, Aiping Chen, Xuedi Cheng

“…Subsequently, through machine learning, a predictive column chart model was constructed using clinical features and routine laboratory blood indicators, and the model was evaluated using ROC curves, calibration curves, and DCA curves. …”
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Countermeasuring Anti-Ship Missiles for Surface Naval Platforms: A Machine Learning Approach With Explainable Artificial Intelligence by Murat Ertop, Ali Oter, Ali Kara

“…Using a commercial simulator containing countermeasure algorithms, datasets representing large-scale scenarios have been created, and the collected data have been trained with the proposed Multilayer Perceptron model. This model has been used to predict target parameters. …”
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