Cross-validation for training and testing co-occurrence network inference algorithms by Daniel Agyapong, Jeffrey Ryan Propster, Jane Marks, Toby Dylan Hocking

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Classification and Recognition Method for Bearing Fault based on IFOA-SVM by Wei Zhang, Zhihua Ma

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A Reinforcement-Learning Based Approach for Designing High-Voltage SiC MOSFET Guard Rings by Tejender Singh Rawat, Chia-Lung Hung, Yi-Kai Hsiao, Wei-Chen Yu, Surya Elangovan, Wei-Ting Lin, Yi-Rong Lin, Kai-Lin Yang, Nien-Yi Jan, Yung-Hui Li, Hao-Chung Kuo

“…For high-power silicon carbide (SiC) devices, breakdown voltage analysis is an important parameter, especially for guard ring design. This work explores the implementation of machine learning on SiC guard ring parameters such as ion implanted dose and energy. …”
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Precise prediction of choke oil rate in critical flow condition via surface data by Qing Wang, Muntadher Abed Hussein, Bhavesh Kanabar, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Mohammad Mahtab Alam, Hojjat Abbasi

“…The novelty of this study lies in the comprehensive comparison of machine learning methods applied to real-world oil production data, with a particular focus on the impact of key well parameters on production efficiency. …”
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Data-driven framework for prediction of mechanical properties of waste glass aggregates concrete by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Hamza Imran, Miguel Angel Duque Vaca, Greys Carolina Herrera Morales, Nestor Ulloa, Krishna Prakash Arunachalam

“…The practical implications of this research extend to sustainable machine learning-based concrete design, where AI-driven optimization can help reduce the reliance on conventional trial-and-error methods. …”
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Deep learning based stacking ensembles for tropical sorghum classification by Muhammad Aqil, Muhammad Azrai, Roy Efendi, Nining Nurini Andayani, Suwardi, Bunyamin Zainuddin, Suarni, Herawati, Andi Irma Damayanti, Muhammad Jihad, Syafruddin, Ramlah Arief, Paesal, Yustisia, Rahman

“…Grid and Bayesian search optimizations were applied for parameter tuning, and model performance was assessed using an 80/20 train-validation split and tenfold cross-validation. …”
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EFFICIENCY UPGRADING OF VIBRATION TREATMENT THROUGH COMPUTER MODELLING by Evgenia M. Tamarkina

“…The results of the theoretical and field research and of the computer simulation of the vibration treatment are described. The metal removal parameters are defined. They make the quantitative prognosis of the treatment intensity in the vibro-finishing machines with different designs of work chambers possible. …”
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Identification of Torsional Fatigue Properties of Titanium Alloy Turned Surfaces and Their Distribution Characteristics by Bin Jiang, Dengyun Wang, Peiyi Zhao, Hongchao Sang

“…The torsional strength and fatigue life calculation method is developed based on initial performance parameters derived from the finite element model. This method enables the correlation identification between surface morphology characteristics, surface and subsurface performance parameters, and fatigue properties. …”
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Mill+, an intuitive tool for simulating the milling process: Vibrations, cutting forces and surface quality control by Gorka Urbikain-Pelayo, Daniel Olvera-Trejo, Luis Norberto López de Lacalle, Alex Elías-Zuñiga, Itziar Cabanes

“…Machining is a highly technological manufacturing process for producing high-added value components across various engineering applications ranging from automotive to aerospace and medical devices. …”
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SIMULATION AND FINITE ELEMENT ANALYSIS OF SPUR GEARS WITH HIGH PRECISION GEAR INSERTION by WANG ZhongHou, HE ZhongYuan, WANG ZhenFei, YANG YongMing, LI Yan

“…The actual tooth surface is hardly obtained utilizing the existing simulation machining method. Therefore,a highprecision simulation machining method for gear shaping is proposed. …”
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SIMULATION AND ACCURACY VERIFICATION OF HIGH PRECISION GEAR HOBBING BASED ON CATIA by HE ZhongYuan, WANG ZhongHou, LIU Lei, WU ShiQing

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A patterning algorithm for the dynamic bin packing problem with placement groups by Evgeniy A. Brazhnikov, Artem A. Panin, Alexey V. Ratushnyi

“…We consider an NP-hard problem of dynamically distributing virtual machines to servers with placement groups. For each virtual machine, parameters such as required number of resources and creation and deletion timestamps are known. …”
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A holistic research based on RSM and ANN for improving drilling outcomes in Al–Si–Cu–Mg (C355) alloy by Şenol Bayraktar, Cem Alparslan, Nurten Salihoğlu, Murat Sarıkaya

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On the Use of Compressed Air and Synthetic Biodegradable Cutting Fluid to Enhance the Surface Quality of WAAM–CMT Manufactured Low-Alloy Steel Parts During Post-Processing Milling... by Déborah de Oliveira, Marcos Vinícius Gonçalves, Guilherme Menezes Ribeiro, André Luis Silva da Costa, Luis Regueiras, Tiago Silva, Abílio de Jesus, Lucival Malcher, Maksym Ziberov

“…However, parts produced by WAAM may need post-processing by machining to achieve functional surface requirements. …”
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Design and damping characterization of sandwich composite made of particle-filled hollow spheres and steel sheets by Xin Zhou, Lars Penter, Ulrike Jehring, Hartmut Göhler, Thomas Weißgärber, Steffen Ihlenfeldt

“…To address manufacturing tolerances, a finite element (FE) model-based optimization was developed to accurately determine PHSS material parameters. These parameters were used in an FE model of the PHSS-steel composite, with identified contact parameters minimizing measurement and simulation differences. …”
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Large language models generating synthetic clinical datasets: a feasibility and comparative analysis with real-world perioperative data by Austin A. Barr, Joshua Quan, Eddie Guo, Emre Sezgin, Emre Sezgin

“…BackgroundClinical data is instrumental to medical research, machine learning (ML) model development, and advancing surgical care, but access is often constrained by privacy regulations and missing data. …”
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Assessing Drone-Based Remote Sensing for Monitoring Water Temperature, Suspended Solids and CDOM in Inland Waters: A Global Systematic Review of Challenges and Opportunities by Shannyn Jade Pillay, Tsitsi Bangira, Mbulisi Sibanda, Seifu Kebede Gurmessa, Alistair Clulow, Tafadzwanashe Mabhaudhi

“…In particular, the review comprehensively analyses the potential advancements in utilising drone technology along with machine learning algorithms, platform type, sensor characteristics, statistical metrics, and validation techniques for monitoring these water quality parameters. …”
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Monitoring modeling and analysis of the electromagnetic environment of HVDC transmission lines based on ion flow and wind coupling field by Ziyi Qin, Jiong Chen, Maoxin Ren, Fan Yin

“…The nonlinear mapping relationship between the model design parameters and the feature parameters is approximated by an extreme learning machine, and the actual measurement results are used to invert the model design parameters to modify the finite element model and realize the precise monitoring of the ρj and E in different wind speed and direction situations. …”
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Toward Efficient Hierarchical Federated Learning Design Over Multi-Hop Wireless Communications Networks by Tu Viet Nguyen, Nhan Duc Ho, Hieu Thien Hoang, Cuong Danh Do, Kok-Seng Wong

“…Federated learning (FL) has recently received considerable attention and is becoming a popular machine learning (ML) framework that allows clients to train machine learning models in a decentralized fashion without sharing any private dataset. …”
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Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma by Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry

“…Data from 526 advanced HNSCC patients treated with chemotherapy and cetuximab in the TPExtreme trial were analyzed using a double‐exponential model. TK parameters from the first line and maintenance (TKL1) or after four cycles (TK4) were used to predict PPS and post‐cycle 4 OS (OS4), combined with 12 baseline parameters. …”
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