Building a composition-microstructure-performance model for C–V–Cr–Mo wear-resistant steel via the thermodynamic calculations and machine learning synergy by Shuaiwu Tong, Shuaijun Zhang, Chong Chen, Tao Jiang, Peng Li, Shizhong Wei

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Predictive modeling for mechanical characteristics of ultra high-performance concrete blended with eggshell powder and nano silica utilizing traditional technique and machine learn... by Yi Zhang, Qizhi Zhang, Ali H. AlAteah, Ahmed Essam, Sahar A. Mostafa

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Performance prediction and optimization of a high-efficiency tessellated diamond fractal MIMO antenna for terahertz 6G communication using machine learning approaches by Kamal Hossain Nahin, Jamal Hossain Nirob, Akil Ahmad Taki, Md Ashraful Haque, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Reem Ibrahim Alkanhel, Hanaa A. Abdallah, Abdelhamied A. Ateya, Ahmed A. Abd El-Latif

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Comparative Analysis of Dry, Minimum Quantity Lubrication, and Nano-Reinforced Minimum Quantity Lubrication Environments on the Machining Performance of AZ91D Magnesium Alloy by Berat Baris Buldum, Kamil Leksycki, Suleyman Cinar Cagan

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Comparative performance of twelve machine learning models in predicting COVID-19 mortality risk in children: a population-based retrospective cohort study in Brazil by Adriano Lages dos Santos, Maria Christina L. Oliveira, Enrico A. Colosimo, Robert H. Mak, Clara C. Pinhati, Stella C. Gallante, Hercílio Martelli-Júnior, Ana Cristina Simões e Silva, Eduardo A. Oliveira

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Performance improvement of extreme multi-label classification using K-way tree construction with parallel clustering algorithm by Purvi Prajapati, Amit Thakkar

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Comparing Cross-Subject Performance on Human Activities Recognition Using Learning Models by Zhe Yang, Mengjie Qu, Yun Pan, Ruohong Huan

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Performance evaluation of geopolymer masonry units: A hybrid approach combining laboratory testing and AI modeling by Md. Zia Ul Haq, Sandeep Singh, Tarak Vora, A.K. Dasarathy, Kaushik Bharti, Vanitha S, Priyadarshi Das, Laura Ricciotti

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Prediction of uniaxial compressive strength of limestone from ball mill grinding characteristics using supervised machine learning techniques by Sahas V. Swamy, Bijay Mihir Kunar, Karra Ram Chandar, Mamdooh Alwetaishi, Shashikumar Krishnan, Sudhakar Reddy

“…The findings demonstrate that combining grinding characteristics with machine learning offers an accurate, cost-effective alternative to conventional UCS testing, with significant practical applications in rock engineering.…”
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Machine Learning Models for Predicting Seismic Response of a Novel Two-Stage Friction Pendulum Isolated Bridge Structure by Hanzlah Akhlaq, Tianbo Peng, Kawsu Jitteh, Muhammad Salman Khan

“…A graphical user interface (GUI) was developed using the best-performing model (i.e., XGB), offering engineers an accessible tool for seismic response prediction. …”
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Performance of an End-to-End Inventory Demand Forecasting Pipeline Using a Federated Data Ecosystem by Henrique Duarte Moura, Els de Vleeschauwer, Gerald Haesendonck, Ben De Meester, Lynn D’eer, Tom De Schepper, Siegfried Mercelis, Erik Mannens

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Augmenting insights into heat transfer performance of direct-contact evaporator: An interpretable data-driven hybrid strategy by Yinzhen Tan, Bo Yu, Jianxin Pan, Wuliang Yin, Min Wang, Hua Wang, Kai Yang, Qingtai Xiao

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Evidence on the performance of nature-based solutions interventions for coastal protection in biogenic, shallow ecosystems: a systematic map by Avery B. Paxton, Trevor N. Riley, Camille L. Steenrod, Brandon J. Puckett, Jahson B. Alemu I., Savannah T. Paliotti, Alyssa M. Adler, Laura Exar, Josette E. T. McLean, James Kelley, Y. Stacy Zhang, Carter S. Smith, Rachel K. Gittman, Brian R. Silliman

“…Methods We identified potentially relevant articles on the performance of NBS for coastal protection using predefined and tested search strategies across two indexing platforms, one bibliographic database, two open discovery citation indexes, one web-based search engine, and a novel literature discovery tool. …”
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Secure Beamforming via Amplify-and-Forward Relays in Machine-to-Machine Communications by Zhongjian Liu, Xiaoning Zhang, Lin Bai, Chen Chen, Haige Xiang

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Optimization of a Redundant Freedom Machining Toolpath for Scroll Profile Machining by Song Gao, Zifang Hu, Huicheng Zhou, Jiejun Xie, Chenglei Zhang, Xiaohan Zhang

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On the Achievable User Number of the Downlinks in Cellular-Based Machine-to-Machine Communications by Yingbo Li, Chen Chen, Lin Bai, Ye Jin

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Machine learning based prediction of geotechnical parameters affecting slope stability in open-pit iron ore mines in high precipitation zone by John Gladious, Partha Sarathi Paul, Manas Mukhopadhyay

“…This project underscores the significant potential of integrating advanced machine learning techniques with traditional geotechnical practices, particularly in regions experiencing heavy rainfall, to foster safer and more efficient engineering solutions.…”
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Analyzing the performance of biomedical time-series segmentation with electrophysiology data by Richard Redina, Jakub Hejc, Marina Filipenska, Zdenek Starek

“…Traditional rule-based and feature engineering approaches often struggle with complex clinical patterns and noise. …”
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Interactions Between Leaf Area Dynamics and Vineyard Performance, Environment, and Viticultural Practices by Yishai Netzer, Noa Ohana-Levi

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Performance of Raman Spectroscopy in biopsy tissue for rapid diagnosis of Tracheobronchial Tuberculosis: A prospective study by Qin Zhang, Mingming Deng, Qian Gao, Xiaoming Zhou, Yu Guo, Yuexiang Wang, Yinghui Fu, Jasmine Lin Zhang, Shuo Chen, Gang Hou

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