Track A. Intelligent Systems and Applications

• Intelligent optimization techniques
• ACO algorithms, evolution strategies and applications
• Genetic algorithms, evolution strategies, genetic programming and evolutionary programming
• Hybrid evolutionary algorithms
• Evolutionary algorithms and applications
• Fuzzy Systems, fuzzy logic and possibility theory
• Fuzzy expert systems
• Fuzzy system design using evolutionary algorithms
• Fuzzy system modeling and simulation
• Fuzzy systems and applications
• Artificial Neural Networks
• Machine Learning and applications
• Architectures and algorithms
• Knowledge based networks
• Implementation issues of neural networks
• Support Vector Machines
• Neural network applications
• Fusion of neural network- fuzzy systems
• Fusion of fuzzy systems- evolutionary algorithms
• Fusion of neural network - evolutionary algorithms
• Fusion of neural network- fuzzy systems- evolutionary algorithms
• Bayesian networks and probabilistic reasoning
• Fusion of statistical methods and soft computing techniques
• Intelligent techniques in Bioinformatics
• Soft computing/computational intelligence in control systems
• Adaptive control systems
• Control applications in robotics, manufacturing, process control, industrial systems, automotive, vehicular systems, spacecraft and so on
• Embedded and real-time operating systems
• Parallel and distributed algorithms and architectures
• Language Processors
• Web Intelligence techniques

Track B. Intelligent Image Processing

• Design and implementation of intelligent signal processing systems signal processing
• Speech processing
• Features and classification
• Texture analysis
• Stereoscopic vision
• Shape processing
• Object recognition
• Image and video retrieval
• Image and video compression

Track C. Intelligent Data mining and Security

• Discovering patterns in continuous data
• Uncertainty management for data mining
• Clustering algorithms and applications
• Classification trees
• Mining time series
• Mining in a Mobile Environment
• Statistical Considerations in Learning
• XML Mining
• Text Mining
• Distributed Data Mining
• Database querying
• Database querying and static routing algorithms
• Cryptography
• Security and reliabilities issues
• Network protocols