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Machines | An Open Access Journal from MDPI Machines is an international, peer-reviewed, open access journal on machinery and engineering published monthly online by MDPI The IFToMM is affiliated with Machines and its members receive a discount on the article processing charges
Machines | Editorial Board - MDPI Interests: design of high precision machines; air-bearings design; micro cutting; ultraprecision machining; smart tooling * Section: Advanced Manufacturing Special Issues, Collections and Topics in MDPI journals
Machines | Instructions for Authors - MDPI Manuscripts for Machines should be submitted online at susy mdpi com The submitting author, who is generally the corresponding author, is responsible for the manuscript during the submission and peer review process
Machines | Aims Scope - MDPI About Machines Aims Machines (ISSN 2075-1702) is an international, peer-reviewed journal on machinery and engineering It publishes research articles, reviews and communications
Machines | Special Issues - MDPI Machines publishes Special Issues to create collections of papers on specific topics, with the aim of building a community of authors and readers to discuss the latest research and develop new ideas and research directions
Design and Application of Electrical Machines | MDPI Books Electrical machines are one of the most important components of the industrial world They are at the heart of the new industrial revolution, brought forth by the development of electromobility and renewable energy systems
Bioinspired Soft Machines: Engineering Nature’s Grace into Future . . . This article explores the transformative advances in soft machines, where biology, materials science, and engineering have converged We discuss the remarkable adaptability and versatility of soft machines, whose designs draw inspiration from nature’s elegant solutions
Comparative Analysis of Machine Learning Models for Predicting . . . - MDPI Methods included random forests, gradient boosting frameworks, support vector machines, neural networks, and logistic regression, each with hyperparameters optimized through Bayesian search routines and evaluated using corrected cross-validation techniques
Machines | Special Issue : Advanced Condition Monitoring and . . . - MDPI Machines is an international peer-reviewed open access monthly journal published by MDPI Please visit the Instructions for Authors page before submitting a manuscript The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs)
Multimodal Large Language Model-Based Fault Detection and . . . - MDPI In nuclear power plants and photovoltaic systems, ML-based fault diagnosis techniques, such as KNNs, support vector machines (SVMs), bagged trees, and ensemble methods, detect faults in pressurized water reactors