The IEEE International Conference on Computational Intelligence and Virtual Environments
for Measurement Systems and Applications (CIVEMSA 2018) is dedicated to all aspects
of computational intelligence, virtual environments and human-computer interaction
technologies for measurement systems and related applications.

TOPICS OF INTEREST
Papers are solicited on all aspects of computational intelligence, human-computer
interaction technologies, and virtual environments for measurement systems and the
related applications, from the points of view of both theory and practice. This includes, but
is not limited to, the following topics with specific emphasis on the measurement aspects:
• Intelligent Measurement Systems
• Human-computer Interaction
• Augmented & Virtual Reality
• Accuracy & Precision of Neural & Fuzzy
Components
• Accuracy & Precision of Virtual
Environments
• Perception, Neurodynamics,
Neurophysiology, Psychophysics
• Multimodal Sensing
• Multimodal (Visual, Haptic, Audio, etc.)
Virtual Environments
• Sensors & Displays
• Calibration and System Calibration
• Multi-Sensor Data Fusion & Intelligent
Sensor Fusion
• Intelligent Monitoring & Control Systems
• Neural & Fuzzy Technologies For
Identification, Prediction, & Control of
Complex Dynamic Systems
• Evolutionary monitoring & control
• Evolutionary Techniques For
Optimization & Logistics
• Neural & Fuzzy Signal/Image Processing
For Industrial, Environmental & Domotic
Applications
• Neural & Fuzzy Signal/Image Processing
For Entertainment & Educational
Applications
• Image Understanding & Recognition
• Machine & Deep Learning for Intelligent
Systems
• Object Modeling
• Object & System Model Validation
• Virtual Reality languages
• Computational Intelligence
Technologies For Robotics & Vision
• Computational Intelligence
Technologies For Medical &
Bioengineering Applications
• Computational Intelligence For
Entertainment & Educational
Applications
• Distributed Collaborative Virtual
Environments
• Model-Based Telecommunications &
Telecontrol
• Hybrid Systems
• Fuzzy & Neural Components For
Embedded Systems
• Hardware Implementation of Neural &
Fuzzy Systems For Measurements
• Neural, Fuzzy & Genetic/Evolutionary
Algorithms For System Optimization &
Calibration
• Neural & Fuzzy Techniques For System
Diagnosis
• Reliability of Fuzzy & Neural Components
• Fault Tolerance & Testing In Fuzzy &
Neural Components
• Neural & Fuzzy Techniques For Quality
Measurement
• Standards
• Human Machine Interaction