Machining Scheme Selection of Features Based on Process Knowledge Graph and Improved Cosine Similarity Matching by Lin Wang, Hao Cheng, Rui Wang, Xunzhuo Huang

“…Then, considering the influence coefficient of the process parameter and the usage coefficient of the machining scheme, an improved cosine similarity formula is designed for MSS. …”
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Machine learning with knowledge constraints for design optimization of microring resonators as a quantum light source by Parisa Sadeghli Dizaji, Hamidreza Habibiyan

“…However, the current design flow is hindered by computational challenges and a complex, high-dimensional parameter space with interdependent variables. In this work, we present a knowledge-integrated machine learning framework based on Bayesian Optimization for designing squeezed light sources using microring resonators. …”
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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…This study explores the application of advanced machine learning (ML) models to predict CO₂ solubility in NaCl brine, a critical parameter for effective carbon capture, utilization, and storage (CCUS). …”
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Sex classification accuracy through machine learning algorithms - morphometric variables of human ear and nose by Tej Kaur, Kewal Krishan, Akanksha Sharma, Ankita Guleria, Vishal Sharma

“…The study aims at predicting sex accuracy from different parameters of ear and nose by using a novel approach of Machine Learning Library, ‘PyCaret’. …”
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Evaluation of mesoporous silica synthesized for green adsorption by modeling via machine learning and mass transfer by Minge Yang, Qiqing Yue, Junyi He

“…The case study was analysis of mesoporous material for adsorption separation of target solute from aqueous solution. Mass transfer and machine learning evaluations were carried out to obtain separation efficiency. …”
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Information-extreme machine learning of wrist prosthesis control system based on the sparse training matrix by Suprunenko M. K., Zborshchyk O. P., Sokolov O.

“…The article considers the problem of machine learning of a wrist prosthesis control system with a non-invasive biosignal reading system. …”
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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…However, its application in virtual screening across diverse molecular structures presents challenges, particularly in optimizing search parameters. To address these limitations, we developed a machine learning (ML) framework that automates the selection of optimal docking parameters. …”
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Heat treatment control technology of high-strength steel gears based on support vector machine by Yanzhong Wang, Libin Zhang, Yulu Su, Hai Liu, HaiLong Yang, Yanyan Chen

“…In this study, with the help of machine learning, a support vector machine prediction model of gear tissue distribution is constructed based on heat treatment parameters, and the radial basis functions kernel function is selected as the kernel function of the support vector machine to improve the accuracy of model prediction by optimizing the kernel parameters. …”
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Extraction of kaolin and tribo informative analysis of the Al-kaolin composite through machine learning approaches by V. S. S. Venkatesh, Guttikonda Manohar, Pandu Ranga Vundavilli, M. M. Mahapatra, Ashish Goyal, Abhijit Bhowmik

“…A feature importance analysis revealed that the standard of distance (Sod) was the most influential parameter affecting these outputs.…”
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The interpretable machine learning model for depression associated with heavy metals via EMR mining method by Site Xu, Mu Sun

“…This study aims to develop an interpretable and efficient machine learning (ML) model with robust performance to identify depression linked to heavy metal exposure. …”
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Metro Shield Machine Attitude Prediction Method Integrating Excavation Index and Support Vector Regression by ZHANG Zhen, LIANG Jie, ZHANG Yulong, CHEN Tie, LIU Gang

“…By introducing characteristic parameters with physical significance, the support vector regression model can more accurately predict the shield machine attitude and provide effective support for real-time shield machine attitude adjustments during the construction process.…”
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Application and feasibility analysis of knowledge-based machine learning in predicting fatigue performance of stainless steel by Jia Wang, Dongkui Fan, C.S. Cai

“…Eight machine learning models were deployed and analyzed using the dataset, and their predictive performances were evaluated using assessment metrics. …”
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Machinability and Geometric Evaluation of FFF-Printed PLA-Carbon Fiber Composites in CNC Turning Operations by Sergio Martín-Béjar, Fermín Bañón-García, Carolina Bermudo Gamboa, Lorenzo Sevilla Hurtado

“…These findings support the use of machining operations as a viable and efficient post-processing method for improving the functionality of polymer-based components produced by additive manufacturing.…”
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ACCOUNTING OF INSTRUMENTAL ERRORS IN THE CONTROL OF WINDINGS OF ELECTRICAL MACHINES WITH THE USE OF QUASI-PERIODIC TEST SIGNALS by A. A. Sheinikov, Yu. V. Suchodolov, V. V. Zelenko

“…The solution of problems of diagnostics of windings of electric machines is associated with the necessity of selection of quasi-periodic test signals against the background noise. …”
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Topological data analysis and machine learning for COVID-19 detection in CT scan lung images by Rabih Assaf, Abbas Rammal, Alban Goupil, Mohammad Kacim, Valeriu Vrabie

“…In response to this pressing need for accurate and parameter-free methods for COVID-19 identification, particularly within lung images, we introduce a novel approach that combines the principles of topological data analysis with the capabilities of machine learning. …”
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A MACHINE LEARNING FRAMEWORK FOR SUICIDAL THOUGHTS PREDICTION USING LOGISTIC REGRESSION AND SMOTE ALGORITHM by Sarni Maniar Berliana, Omas Bulan Samosir, Rafidah Abd Karim, Victoria Pena Valenzuela, Krismanti Tri Wahyuni, Andi Alfian

“…This study focused on predicting suicidal thoughts using machine learning, leveraging the 2021 National Women's Life Experience Survey (SPHPN) involving women aged 15 to 64. …”
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Dimensional Accuracy Evaluation of Single-Layer Prints in Direct Ink Writing Based on Machine Vision by Yongqiang Tu, Haoran Zhang, Hu Chen, Baohua Bao, Canmi Fang, Hao Wu, Xinkai Chen, Alaa Hassan, Hakim Boudaoud

“…Addressing the critical need for precision non-contact assessment in DIW fabrication, this study develops a novel machine vision-based framework for dimensional accuracy evaluation. …”
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Machine learning algorithms for manufacturing quality assurance: A systematic review of performance metrics and applications by Ashfakul Karim Kausik, Adib Bin Rashid, Ramisha Fariha Baki, Md Mifthahul Jannat Maktum

“…Adopting Machine Learning (ML) in manufacturing quality assurance (QA) has accelerated with Industry 4.0, enabling automated defect detection, predictive maintenance, and real-time process optimization. …”
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Digital Twin Control Method of Machine Tool Feed Rate Based on Fuzzy Neural Network by YIN Jia, BAI Lele, TIAN Hui, WU Shijie, Hou Guijin, TANG Yuyang, LIU Hongguang, ZHANG Jun

“…In the current milling process of aviation parts, considering many factors such as deformation, roughness, and tool wear, process engineers always set conservative parameters based on experience, resulting in low machining efficiency, and an inability to adaptively adjust the cutting parameters according to the cutting trajectory and machine load. …”
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Bio-coolants for sustainable friction drilling process: A machine learning approach to temperature reduction by R. Sankaranarayanan, Rajesh Jesudoss Hynes Navasingh, Angela Jennifa Sujana J․, Robert Čep

“…Decision-tree based analyses not only show optimal results, but also the different parameter combinations as options for the chosen process. …”
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