Handbook of Research on Applied Cybernetics and Systems Science

• #1. A Survey of Parallel Community Detection Algorithms
• #2. Towards Automation of IoT Analytics: An Ontology-Driven Approach
• #3. Image Processing for Surveillance and Security
• #4. Application of Corona Product of Graphs in Computing Topological Indices of Some Special Chemical Graphs
• #5. Statistical Analysis of Functional Magnetic Resonance Imaging Data
• #6. Modeling Associations: Sensor Fusion and Signaling Bar Codes
• #7. Graph-Based Semi-Supervised Learning With Big Data
• #8. Machine Learning Methods as a Test Bed for EEG Analysis in BCI Paradigms
• #9. Machine Learning Approaches for Supernovae Classification
• #10. Supervised Learning in Absence of Accurate Class Labels: A Multi-Instance Learning Approach
• #11. Patient Data De-Identification: A Conditional Random-Field-Based Supervised Approach
• #12. Support Vector Machines and Applications
• #13. Design and Analysis of Computer Experiments
• #14. Effective Statistical Methods for Big Data Analytics
• #15. Measuring Complexity of Chaotic Systems With Cybernetics Applications
• #16. Cyber-Physical Systems: An Overview of Design Process, Applications, and Security
• #17. Scientometrics: A Study of Scientific Parameters and Metrics
• #18. Design of Assistive Speller Machine Based on Brain Computer Interfacing

Snehanshu Saha received MS degree in Mathematics from the Clemson University, USA, in 2003. He obtained his PhD in Mathematics from University of Texas at Arlington in 2008. He is currently working as Professor in the Department of Computer Science and Engineering and & Head- Center for Applied Mathematical Modeling & Simulation, PESIT South-Bangalore. His research interests include Brain-Computer interface/Big Data analytics/ Mathematical Modeling/ Theory of Differential Equations/Astro-informatics. He has served as an invited speaker for many international conferences in Indian and abroad. He serves as the reviewer for many journals like Computational Cognitive Science, Springer, International Journal of Innovative Information and Electrical Engineering (IJIIEE), etc. He is a senior member of the IEEE.

Abhyuday Mandalis anAssociate Professor at University of Georgia, USA. He received his bachelor’s and master’s degrees from Indian Statistical Institute, Kolkata, another master’s degree from University of Michigan and Ph.D. in 2005 from Georgia Institute of Technology. His research interests include design of experiments, optimization and genetic algorithms, drug discovery and fMRI data analysis. Currently he is an Associate Editor of Statistics and Probability Letters and Sankhya - Series B.