Analyzing the compressive performance of lightweight foamcrete and parameter interdependencies using machine intelligence strategies by Wang Guoyuan, Fan Wenbo, Shi Qingbin, Luo Yingqi

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A synthetic data-driven machine learning approach for athlete performance attenuation prediction by Mauricio C. Cordeiro, Ciaran O. Cathain, Ciaran O. Cathain, Lorcan Daly, Lorcan Daly, David T. Kelly, David T. Kelly, Thiago B. Rodrigues

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Comparative Performance of Textured Yarn Drawn through Apron and Godet in Draw Texturing Machine by Subhankar Maity, Bibekananda Basu, Abhishek Mishra

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Evaluating soiling effects to optimize solar photovoltaic performance using machine learning algorithms by Muhammad Faizan Tahir, Anthony Tzes, Tarek H.M. El-Fouly, Mohamed Shawky El Moursi, Nauman Ali Larik

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Comparison of machine learning model performance for predicting the climate variables in Johor Bahru, Malaysia by Farid Zamani Che Rose, Nur Aqilah Khadijah Rosili, Muhammad Fadhil Marsani

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Monte Carlo Thompson sampling-guided design for antibody engineering by Taro Kakuzaki, Hikaru Koga, Shuuki Takizawa, Shoichi Metsugi, Hirotake Shiraiwa, Zenjiro Sampei, Kenji Yoshida, Hiroyuki Tsunoda, Reiji Teramoto

“…It was recently reported that a machine-learning guided protein engineering approach such as Thompson sampling (TS) has been used to efficiently explore sequence space in the framework of Bayesian optimization. …”
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Machine learning predictive performance in road accident severity: A case study from Thailand by Ittirit Mohamad, Sajjakaj JomnonKwao, Vatanavongs Ratanavaraha

“…This study evaluates the predictive performance of multiple supervised machine learning algorithms in classifying accident severity, addressing the gap in prior research that lacks a comparative analysis of multiple models trained on large-scale crash data. …”
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Machine Learning-Based Methods for the Seismic Damage Classification of RC Buildings by Sung Hei Luk

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Optimized machine learning algorithms with SHAP analysis for predicting compressive strength in high-performance concrete by Samuel Olaoluwa Abioye, Yusuf Olawale Babatunde, Oluwafikejimi Abigail Abikoye, Aisha Nene Shaibu, Bailey Jonathan Bankole

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Prediction of Promotors in Agrobacterium and Klebsiella Using Novel Feature Engineering and Ensemble Learning Approach by Nagwan Abdel Samee, Rawan Talaat, Ali Raza, Hadil Shaiba, Souham Meshoul

“…Our method achieved remarkable accuracy, precision, and recall rates of 99%, 98%, and 99%, respectively, which not only demonstrate the effectiveness of our model but also exceed the current performance of the state of the art in this area. By leveraging advanced classification techniques, we provide a robust framework for promoter prediction that can significantly enhance genetic engineering and biotechnological applications involving these organisms.…”
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What Gets Measured Gets Improved: Monitoring Machine Learning Applications in Their Production Environments by Dominik Protschky, Luis Lammermann, Peter Hofmann, Nils Urbach

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Cloud-Based Intrusion Detection Approach Using Machine Learning Techniques by Hanaa Attou, Azidine Guezzaz, Said Benkirane, Mourade Azrour, Yousef Farhaoui

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Machine Learning Tool for Analyzing Finite Buffer Queueing Systems by Attahiru Sule Alfa, Haitham Abu Ghazaleh

“…Queueing delays are one very important performance measure for most engineering network systems. …”
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Anomaly Detection of Marine Diesel Engines: A Novel Approach using Transformer Neural Networks for Reconstruction and Residual Analysis by Qin Liang, Erik Vanem, Knut Erik Knutsen, Vilmar Æsøy, Houxiang Zhang

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Iris: A Next Generation Digital Pathology Rendering Engine by Ryan Erik Landvater, Ulysses Balis

“…Herein, we introduce Iris, a new high-performance digital pathology rendering system. Specifically, we outline and detail the performance metrics of Iris Core, the core rendering engine technology. …”
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Squirrel search algorithm-support vector machine: Assessing civil engineering budgeting course using an SSA-optimized SVM model by He Yanqing, Shi Ling, Yao Xiaoqin, Zhang Haojie, Al-Barakati Abdullah A.

“…Nevertheless, in practical application, the machine learning-based evaluation model for civil engineering budget courses faces the predicament of inadequate evaluation accuracy. …”
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Data on battery health and performance: Analysing Samsung INR21700-50E cells with advanced feature engineering by Sahar Qaadan, Aiman Alshare, Alexander Popp, Myrel Tiemann, Utz Spaeth, Benedikt Schmuelling

“…It uniquely combines raw data and engineered features derived from charge-discharge cycles and Hybrid Pulse Power Characterization tests. …”
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Divalent cation engineering of PEO/LDH coatings for corrosion protection of AZ31 magnesium alloy supported by machine learning analysis by Mosab Kaseem, Talitha Tara Thanaa, Krishna Kumar Yadav, Hagar H. Hassan, Arash Fattah-alhosseini

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Machine learning and experimental emission assessment in high temperature air premixed charged compression ignition engines using the Pugh matrix by Mohammed Al Awadh, Kah Ong Michael Goh

“…Abstract This research explores the performance, exhaust emissions, and combustion properties of a Premixed Charged Compression Ignition (PCCI) engine using combinations of Andropogon narudus (AN) and Sapota Oil Methyl Ester (SOME) blended as substitute fuels. …”
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Industrial multi-machine data aggregation, AI-ready data preparation, and machine learning for virtual metrology in semiconductor wafer and slider production by Feiyang Ou, Julius Suherman, Chao Zhang, Henrik Wang, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…Because of machine commonalities, data can be selected to draw out operational value across machines. …”
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