Mechanical performance dataset for alloy with applications at low temperatures by Haoxuan Tang, Zhiyuan Chen, Xin Yao, Zhiping Xu

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Towards generalizable machine learning prediction of downskin surface roughness in laser powder bed fusion by Jigar Patel, Mihaela Vlasea, Sagar Patel

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Combine soybean harvesting performance with grain loss distribution by Sagar Regmi, William Rexroad, Timothy Lecher, Cody M. Allen

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Embedding Tangent Space Extreme Learning Machine for EEG Decoding in Brain Computer Interface Systems by Mingwei Zhang, Yao Hou, Rongnian Tang, Youjun Li

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Large Language Model and Traditional Machine Learning Scoring of Evolutionary Explanations: Benefits and Drawbacks by Yunlong Pan, Ross H. Nehm

“…Results showed that with very basic prompt engineering, ChatGPT-4o achieved the highest performance across LLMs. …”
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Modeling of Exhaust Gas Temperature at the Turbine Outlet Using Neural Networks and a Physical Expansion Model by Alessandro Brusa, Alice Grossi, Mirco Lenzi, Fenil Panalal Shethia, Nicolò Cavina, Ioannis Kitsopanidis

“…The accurate estimation of exhaust gas temperature across the turbine is always more important for the optimization of engine performance, ensuring durability of the turbine impeller and catalyst, and reducing and calculating emissions concentration. …”
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Assessment for shallow and large tunnel construction in weak ground conditions: Application of tunnel boring machines by Servet Karahan, Candan Gokceoglu

“…Abstract With recent technological advancements, tunnel boring machines (TBM) have developed and exhibited high performance in large diameters and weak ground conditions. …”
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Aircraft Skin Machine Learning-Based Defect Detection and Size Estimation in Visual Inspections by Angelos Plastropoulos, Kostas Bardis, George Yazigi, Nicolas P. Avdelidis, Mark Droznika

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Synergistic use of satellite, legacy, and in situ data to predict spatio-temporal patterns of the invasive Lantana camara in a savannah ecosystem by Lilly Theresa Schell, Emma Evers, Sarah Schönbrodt-Stitt, Konstantin Müller, Maximilian Merzdorf, Drew Arthur Bantlin, Insa Otte

“…The model's predictive performance was robust, with AUCROC values ranging from 0.93 to 0.98 and AUCPR values ranging from 0.79 to 0.94. …”
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Condition Monitoring and Fault Prediction in PMSM Drives Using Machine Learning for Elevator Applications by Vasileios I. Vlachou, Theoklitos S. Karakatsanis, Dimitrios E. Efstathiou, Eftychios I. Vlachou, Stavros D. Vologiannidis, Vasiliki E. Balaska, Antonios C. Gasteratos

“…Ongoing challenges such as managing machine thermal load and developing more durable materials for PMSMs require the development of suitable models that are adapted to existing drive systems. …”
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Optimized design and performance testing of hydraulic electrostatic actuator by Yuze Ye, Qingsong He, Changli Yang, Xiaodong Xu, Lin Xie, Diyi Liu, Bo Zeng, Zhijian Leng

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Predicting the glass transition temperature of polymer based on generative adversarial networks and automated machine learning by Zhanjie Liu, Yixuan Huo, Qionghai Chen, Siqi Zhan, Qian Li, Qingsong Zhao, Lihong Cui, Jun Liu

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Evolving Machine Learning Methods for Density Estimation of Liquid Alkali Metals over the Wide Ranges by Tao Lin, Amir Seraj

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Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm by Rafiqul Islam, Md. Arif Hossain

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Electric Discharge Machining of AZ91 Magnesium Hybrid Composites under Different Dielectric Mediums by T. Prakash, R. Ranjith, S. Krishna Mohan, S. Venkatesan

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Static Topology Optimization and Dynamic Characteristics Analysis of 6000T Compression-Shear Test Machine Frame by Genshang Wu, Beibei Cui, Yanmin Li, Jinggan Shao, Zhanshu He, Shusen Zhao, Chao Li, Jinlong Yu

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Indoor Air Quality Prediction in Sick Building Using Machine and Deep Learning: Comparative Analysis by Hayder Qasim Flayyih, Jumana Waleed, Amer M. Ibrahim

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Interpretable Machine Learning Models and Symbolic Regressions Reveal Transfer of Per- and Polyfluoroalkyl Substances (PFASs) in Plants: A New Small-Data Machine Learning Method to... by Yuan Zhang, Yanting Li, Yang Li, Lin Zhao, Yongkui Yang

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QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals by Veysel Yusuf Cambay, Irem Tasci, Gulay Tasci, Rena Hajiyeva, Sengul Dogan, Turker Tuncer

“…Therefore, EEG signal processing is crucial for neuroscience and machine learning (ML). Therefore, a new EEG stress dataset has been collected, and an explainable feature engineering (XFE) model has been proposed using the Directed Lobish (DLob) symbolic language. …”
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Low-cycle fatigue life prediction method for stud connectors based on interpretable machine learning by Jianan Pan, Xiaoling Liu, Bing Wang, Ying Liu

“…Secondly, the predictive performance of nine machine learning models was compared by combining cross-validation and hyperparameter optimization. …”
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