Humanizing Technology for Society via Man-Machine Systems
Papers relating to the general title of Man-Machine Systems are solicited especially including those in the areas of human system reliability, mechatronics, bio-mechatronics and man machine interactions. Other topics of interest for submission include, but are not limited to:
Brain Machine Interfacing, Man-Machine Interfacing, Human Information Processing, Human-Computer Interaction, Embodiment of Communication and Action in Robots, Human-Robot Interfacing, Mobile Robotic, Neuroscience-Inspired Robots and Communication, Swarm Robotics, Hybrid Drone, Ontological Approach.
Deep Learning, Ensemble Method, Machine Learning, Expert Systems, Image Processing, Gaze Emotion Detection, Pattern Recognition, Swarm Intelligence, Hybrid Intelligent Systems, Systems Intelligence, Fuzzy Modelling, Computational and Optimization Techniques, Natural Language Processing (NLP), Speech Recognition.
Vehicle-to-Vehicle (V2V) Communication, Point Cloud Data Processing, Internet of Things (IoT), IoT Architectures, Smart Things, Smart Sensors, Smart Cities, Smart Community, IoT applications, Intelligent Connected Vehicles, Autonomous Sensor.
Tomography Imaging, Digital Signal Processing, Control of Intelligent Systems, System Integration, Machine Vision, Embedded System, Instrumentation, Networked Control Systems, Information management, Communication systems, Soft Computing and Control methods, Acoustic, Biomedical Signal Applications.
Machine Design, Computer Aided Engineering Design, Control and Automation, Rehabilitation Robot Design, Automation Technology, Process Control, Reverse Engineering, Intelligent Process Systems, Mechatronics and Bio-Mechatronics
|Submission of Full Paper||15 August 2023|
|Notification of Acceptance||15 July 2023 (onward)|
|Submission of Camera Ready||20 August 2023|
|Registration||20 August 2023|
Cologne University of Applied Sciences, Germany
Neuroscience Inspired Empathic Sensor System for Individual Comfort Climate Control
Victoria University of Wellington, New Zealand
Introduction to Time Series Analysis with Ordinal Patterns