Composite Bayesian Optimization in function spaces using NEON—Neural Epistemic Operator Networks by Leonardo Ferreira Guilhoto, Paris Perdikaris

“…Abstract Operator learning is a rising field of scientific computing where inputs or outputs of a machine learning model are functions defined in infinite-dimensional spaces. …”
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Enhanced U-Net with Multi-Module Integration for High-Exposure-Difference Image Restoration by Bo-Lin Jian, Hong-Li Chang, Chieh-Li Chen

“…Machine vision systems have become key unmanned vehicle (UAV) sensing systems. …”
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Enhancing Emotion Recognition in Speech Based on Self-Supervised Learning: Cross-Attention Fusion of Acoustic and Semantic Features by Bashar M. Deeb, Andrey V. Savchenko, Ilya Makarov

“…However, state-of-the-art models for speech emotion recognition use many parameters, which leads to computational complexity. …”
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Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…Compared with traditional methods—such as deep neural networks, support vector machines, and linear regression—the proposed model effectively integrates static and dynamic agricultural data. …”
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Simplified Grinding Temperature Model Study by Lishchenko N. V., Larshin V. P., Krachunov H.

“…The scope of the studied model corresponds to the modern technological operations of grinding on CNC machines for conditions where the numerical value of the Peclet number is more than 4. …”
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The calculation algorithm of oil and gas production enterprise energy efficiency indicators by A. Yu. Arestova, V. N. Ulyanov, M. Yu. Frolov

“…The assessment of energy efficiency indicators will require adaptation of the parameter’s identification method for rotating electrical machines in operating modes. …”
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A study on predicting the risk of coronary artery disease in OSAHS patients based on a four-variable screening tool potential predictive model and its correlation with the severity... by Yanli Yao, Yu Li, Yulan Chen, Xuan Qiu, Gulimire Aimaiti, Ayiguzaili Maimaitimin

“…A random forest machine learning algorithm was used to evaluate the importance of each risk factor. …”
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Positron emission tomography imaging biomarker and artificial intelligence for the characterization of solitary pulmonary nodule by Ashish Kumar Jha, Ashish Kumar Jha, Umeshkumar Baburao Sherkhane, Umeshkumar Baburao Sherkhane, Nilendu C. Purandare, Nilendu C. Purandare, Leonard Wee, Andre Dekker, Venkatesh Rangarajan, Venkatesh Rangarajan

“…Radiomics and machine learning are other promising technologies which can be utilised to characterise the SPN.PurposeThis study explores the potential of PET radiomics signatures and machine learning algorithms to characterise the SPN.MethodsThis retrospective study aimed to characterize solitary pulmonary nodules (SPNs) using PET radiomics. …”
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A Novel Method to Forecast Nitrate Concentration Levels in Irrigation Areas for Sustainable Agriculture by Halil Karahan, Müge Erkan Can

“…In addition to nitrate concentrations, other parameters, such as flow rate, EC, pH, and precipitation, were also measured simultaneously. …”
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Structural Strength of Corrugated Cardboard Products by Ivan A. Kosarev, Aleksandr V. Guriev

“…Laboratory samples have been produced, differing in the number of elements (from 1 to 6) and the angle of flute peak adhesion line orientation (from 0° to 90° in 15° increments) relative to the machine direction. A method has been developed to evaluate the structural strength and stability of samples with various parameters under edgewise compression conditions. …”
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A Neutron Source Based on Spherical Tokamak by Francesco P. Orsitto, Nunzio Burgio, Marco Ciotti, Guglielmo Lomonaco, Fabio Panza, Alfonso Santagata

“…Starting from a new scaling law of energy confinement tested, approximately, on ST40 spherical tokamak, the parameters of a 15 MW ST DT fusion reactor (ST180) are derived, and a preliminary radial build of the machine is established.…”
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An Advanced Deep Learning Model for Identifying Blue Horizontal-branch Stars from LAMOST DR10 by Yuhang Zhang, Yude Bu, Jiangchuan Zhang, Ke Wang, Huili Wu, Mengmeng Zhang, Shanshan Li, Jingzhen Sun, Xiaoming Kong, Zhenping Yi, Meng Liu

“…Our study emphasizes the potential and effectiveness of using machine learning methods in identifying and analyzing BHB stars.…”
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Research on application of diamond FAT for black lithium tantalate wafer processing based on nanoindentation and scratch techniques by Linlin Cao, Zhijie Huang, Zhanshuo Zhang, Wei Wei, Tingting Cai, Xiaolong Zhou, Chengyu Sun, Julong Yuan, Wei Hang, Huiying Ni, Yingjie Wang

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Correlation method of processing the image of the surface microrelief to determine its roughness by Alexey D. Abramov, Dmitry S. Klyuev

“…A new optoelectronic method for measuring the roughness parameters of microreliefs of machined surfaces is proposed, which is based on digital processing of their halftone images. …”
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Optimization and microstructural study of friction riveted carbon-Kevlar and aluminum joints for aerospace applications by Nagarajan Jawahar Vignesh, Rajesh Jesudoss Hynes Navasingh, Shenbaga Velu Pitchumani, Angela Jennifa Sujana Jesudoss, Piotr Nieslony, Venkatachalam Gopalan, Krzysztof Stebel, Radosław Jasiński, Maciej Zdanowski, Jana Petru, Robert Čep

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A numerical conductive network model for investigating the strain-sensing response of graphene nanoplatelets-filled elastomeric strain sensors by Alireza Alidoust, Mojtaba Haghgoo, Reza Ansari, Jamaloddin Jamali, Mohammad Kazem Hassanzadeh-Aghdam

“…Strain sensors have attracted great attentions for practical applications such as human-machine interface. It is challenging to model the electrical behavior of elastomeric strain sensors modified with nanomaterials. …”
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Intelligent Analysis Method of Gear Faults Based on FRWT and SVM by Hongfang Chen, Yanqiang Sun, Zhaoyao Shi, Jiachun Lin

“…Then, a particle optimization method is used to optimize SVM parameters, and the feature vectors as training samples are input into SVM for training while the test samples are input for fault recognition. …”
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Influences of Temperature Variations Around Subway Ventilations on Fractures of Continuous Welded Rail Fractures by Jung-Youl Choi, Sang-Yeol Park, Sun-Hee Kim, Jee-Seung Chung

“…This study examines factors affecting the thermal expansion behavior of continuous welded rails (CWRs) in urban rail systems and investigates conditions that lead to rail weld fractures. Parameters affecting CWR fractures near ventilation shafts in urban rail systems are identified through field investigations and machine learning analysis. …”
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A Comprehensive Review of Thermal Management Challenges and Safety Considerations in Lithium-Ion Batteries for Electric Vehicles by Ali Alawi, Ahmed Saeed, Mostafa H. Sharqawy, Mohammad Al Janaideh

“…Additionally, the study explores the impact of integrating artificial intelligence (AI) and machine learning (ML) into BTMS on thermal performance prediction and energy-efficient cooling, focusing on optimizing the operating parameters of cooling systems. …”
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Intelligent hydraulic fracturing under industry 4.0—a survey and future directions by Jing Jia, Qinghu Fan, Jianglu Jing, Kehui Lei, Lichang Wang

“…The study addresses major advancements such as real-time optimization of fracturing parameters, intelligent allocation of fracturing fluids and materials, risk early warning systems, and fracture monitoring. …”
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