CALL FOR PAPERS
Topic 1: Location Based Mobile Marketing Innovations
Indoor positioning system of smart phones
Mobile geographic information systems
Location based marketing for smartphone users
Location-based marketing strategies
Mobile marketing applications
Geo-fencing for business
Geocaching
Business and consumers location information
Transportation system connected to location-based services (LBS)
LBS-based reservation technology and mobile applications
LBS-based tour guide technology and applications
Location-based big-data analysis and applications
AI technology for LBS
Mobile engagement strategies and developing LBS technologies
Contextual services and location data for improved services and increase business traction and engagement
Topic2: Higher Level Artificial Neural Network Based Intelligent Systems
Adaptive Architectures and Mechanisms
Stability and Instability in Artificial Neural Networks
Complex Artificial Neural Network Based Systems and Dynamics
Learning Paradigms and Algorithms
Self-Organization and Emergence
Support Vector Machines and Kernel Methods
RBF Structures
Neurodynamic Approaches and Solutions
Reinforcement Learning
Stochastic Learning and Statistical Algorithms
Cognitive frame work using ANN Clustering process using the artificial neural networks
Fast stable learning in the hybrid neural network Neural
Network based power management systems Information storage and quality prediction using ANN
FPGA implementation process in ANN
Distance recognition in wireless sensor network using ANN
Analyzing different hybrid activation function using the supervised learning algorithm
Self learning, adaptability, deployment process in the neural networks and machine learning methods
Hybridization of intelligent sytems, Tentative Schedule
Topic3: Current Applications and Innovations of Artificial Intelligence and Machine Learning in Aerospace
Predictive Maintenance
Generative design
Efficient supply chain management
Improved quality control
Smart Concessions Management
Smart Repairs Management
Automatic Part Geo Location
Identification in a DMU or Assembly Line
NC Documentation Device
Knowledge-Based Engineering
Reverse Engineering
Flight Safety
Threat detection
Horizon Detection
Autonomous Drones
Autonomous Helicopters
Autonomous Aerospace Vehicles
Topic4: Research Trends on Autonomous Vehicles
Semi-automated vehicles
Autonomous/intelligent robotic vehicles
Vehicle environment perception
Cooperative driving and cooperative vehicle-infrastructure systems
Vehicle-to-infrastructure and vehicle-to-vehicle (V2I/V2V) communication
Wireless in-car networks
Vehicle system architecture and design
Vehicular Internet of Things (IoT) infrastructure
Intelligent vehicle software and computing infrastructure
Edge data analytics for vehicular systems
Cloud computing applications for vehicular systems
Intelligent control of network and processing resources in V2X architectures
Dynamic congestion control in V2X communication
Cognition in autonomous driving
Distributed intelligence, machine learning, decision making for autonomous driving • Learning algorithms for autonomous driving
Geographic information systems (GIS) or intelligent transportation systems (ITS) • Applications for intelligent vehicles
Security and privacy issues and protection mechanisms
Cyber-physical system modeling
Early experience and field trials of connected and autonomous vehicles
Topic5: Data analytics for Public Health Care
Application of data analytics in public health care informatics
Challenges using data analytics in public health care
Future strategies in health informatics
Advantages of data analytics in health care
Significant impact of data analytics in public health care
Powerful data analytics tools in healthcare
Methods, techniques in data collecting for health care public health care
Trends in data analytics in health care
Using data analytics in public health care for safety purposes
Importance of data analytics in public health care
Effectiveness of data analytics in public health care
What are the current use-cases data analytics in healthcare informatics?
What is involved in the process of data analytics integration for these applications?
Assessment and evaluation of data analytics in public health care
Different modes of data analytics in public health care and their interactions