Mathematical Models for the Design of Electrical Machines

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Renaissance Fun The machines behind the scenes by Steadman, Philip

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Advances in the Field of Electrical Machines and Drives

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Co-Corporeality of Humans, Machines, & Microbes

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Co-Corporeality of Humans, Machines, & Microbes

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Magnetic Material Modelling of Electrical Machines

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Advanced Permanent Magnet Machines and Drives

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Modelling and Control of Switched Reluctance Machines

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Renaissance Fun The machines behind the scenes by Steadman, Philip

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From Curlers to Chainsaws Women and Their Machines

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The Voice of the Machines An Introduction to the Twentieth Century by Lee, Gerald Stanley, 1862-1944

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Die Casting: Dies—Machines—Methods by Lucas, Chester L.

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Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2018 /

Table of Contents: “…Machine Learning for Enhanced Waste Quantity Reduction: Insights from the MONSOON Industry 4.0 Project -- Deduction of time-dependent machine tool characteristics by fuzzy-clustering -- Unsupervised Anomaly Detection in Production Lines -- A Random Forest Based Classifer for Error Prediction of Highly Individualized Products -- Web-based Machine Learning Platform for Condition-Monitoring -- Selection and Application of Machine Learning-Algorithms in Production Quality -- Which deep artifificial neural network architecture to use for anomaly detection in Mobile Robots kinematic data -- GPU GEMM-Kernel Autotuning for scalable machine learners -- Process Control in a Press Hardening Production Line with Numerous Process Variables and Quality Criteria -- A Process Model for Enhancing Digital Assistance in Knowledge-Based Maintenance -- Detection of Directed Connectivities in Dynamic Systems for Different Excitation Signals using Spectral Granger Causality -- Enabling Self-Diagnosis of AutomationDevices through Industrial Analytics -- Making Industrial Analytics work for Factory Automation Applications -- Application of Reinforcement Learning in Production Planning and Control of Cyber Physical Production Systems -- LoRaWan for Smarter Management of Water Network: From metering to data analysis.…”
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Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2020 /

Table of Contents: “…Preface -- Energy Profile Prediction of Milling Processes Using Machine Learning Techniques -- Improvement of the prediction quality of electrical load profiles with artficial neural networks -- Detection and localization of an underwater docking station -- Deployment architecture for the local delivery of ML-Models to the industrial shop floor -- Deep Learning in Resource and Data Constrained Edge Computing Systems -- Prediction of Batch Processes Runtime Applying Dynamic Time Warping and Survival Analysis -- Proposal for requirements on industrial AI solutions -- Information modeling and knowledge extraction for machine learning applications in industrial production systems -- Explanation Framework for Intrusion Detection -- Automatic Generation of Improvement Suggestions for Legacy, PLC Controlled Manufacturing Equipment Utilizing Machine Learning -- Hardening Deep Neural Networks in Condition Monitoring Systems against Adversarial ExampleAttacks -- First Approaches to Automatically Diagnose and Reconfigure Hybrid Cyber-Physical Systems -- Machine learning for reconstruction of highly porous structures from FIB-SEM nano-tomographic data.…”
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Machinability and Tribological Performance of Advanced Alloys

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Electric Machines for Smart Grids Applications Design, Simulation and Control

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Advances in Human and Machine Navigation Systems

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X-Machines for Agent-Based Modeling FLAME Perspectives by Kiran, Mariam

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Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2018

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Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2020

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