Handbook of Research on Computational Intelligence for Engineering, Science, and Business

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Bhattacharyya, Siddhartha
IGI Global, Nov 30, 2012 - Computers - 746 pages

Using the same strategy for the needs of image processing and pattern recognition, scientists and researchers have turned to computational intelligence for better research throughputs and end results applied towards engineering, science, business and financial applications.

Handbook of Research on Computational Intelligence for Engineering, Science, and Business discusses the computation intelligence approaches, initiatives and applications in the engineering, science and business fields. This reference aims to highlight computational intelligence as no longer limited to computing-related disciplines and can be applied to any effort which handles complex and meaningful information.


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Computational Intelligence Using Type2 Fuzzy Logic Framework
Soft Computing Based Statistical Time Series Analysis Characterization of Chaos Theory and Theory of Fractals
Machine Intelligence Using Hierarchical Memory Networks
Image Processing and Segmentation
Image Analysis and Understanding Based on Information Theoretical Region Merging Approaches for Segmentation and Cooperative Fusion
Multilevel Image Segmentation by a Multiobjective Genetic Algorithm Based OptiMUSIG Activation Function
A Novel Fuzzy Rule Guided Intelligent Technique for Gray Image Extraction and Segmentation
Graph Based Segmentation of Digital Images
Adaptive Median Filtering Based on Unsupervised Classification of Pixels
Database Oriented Techniques
Data Clustering Algorithms Using Rough Sets
Evolution of Genetic Algorithms in Classification Rule Mining
Database Anonymization Techniques with Focus on Uncertainty and MultiSensitive Attributes
Using Data Masking for Balancing Security and Performance in Data Warehousing
Compilation of References

Development of a StopLine Violation Detection System for Indian Vehicles
A Comparative Study of Unsupervised Video Shot Boundary Detection Techniques Using Probabilistic Fuzzy Entropy Measures
A Hierarchical Multilevel Image Thresholding Method Based on the Maximum Fuzzy Entropy Principle
About the Contributors

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About the author (2012)

Dr. Siddhartha Bhattacharyya did his Bachelors in Physics, Bachelors in Optics and Optoelectronics and Masters in Optics and Optoelectronics from University of Calcutta, India in 1995, 1998 and 2000 respectively. He completed PhD in Computer Science and Engineering from Jadavpur University, India in 2008. He is currently an Associate Professor in Information Technology of RCC Institute of Information Technology, Kolkata, India. Prior to this, he was an Assistant Professor in Computer Science and Information Technology of University Institute of Technology, The University of Burdwan, India from 2005-2011. He was a Lecturer in Information Technology of Kalyani Government Engineering College, India during 2001-2005. He is a co-author of a book and more than about 75 research publications. He was the member of the Young Researchers' Committee of the WSC 2008 Online World Conference on Soft Computing in Industrial Applications. He was the convener of the AICTE-IEEE National Conference on Computing and Communication Systems (CoCoSys-09) in 2009. He has been the member of the organizing and technical program committees of several national and international conferences. He is the Assistant Editor of International Journal of Pattern Recognition Research since 2010. He is the member of the editorial board of International Journal of Engineering, Science and Technology and the member of the editorial advisory board of HETC Journal of Computer Engineering and Applications. His research interests include soft computing, pattern recognition and quantum computing. Dr. Bhattacharyya is a member of IEEE, IRSS and IAENG. He is a life member of OSI and ISTE, India.

Dr. Paramartha Dutta did his Bachelors and Masters in Statistics from the Indian Statistical Institute, Calcutta in the years 1988 and 1990 respectively. He afterwards completed his Master of Technology in Computer science from the same Institute in the year 1993 and Doctor of Philosophy in Engineering from the Bengal Engineering and Science University, Shibpur in 2005 respectively. He has served in the capacity of research personnel in various projects funded by Govt. of India, which include DRDO, CSIR, Indian Statistical Institute, Calcutta etc. Dr. Dutta is now a Professor in the Department of Computer and system Sciences of the Visva Bharati University, West Bengal, India. Prior to this, he served Kalyani Government Engineering College and College of Engineering in West Bengal as full time faculty members. He has coauthored four books and has also one edited book to his credit. He has published about hundred twenty papers in various journals and conference proceedings, both international and national. Presently, he is supervising four students for their Ph. D program registered with Visva Bharati University and West Bengal University of Technology. Dr. Dutta is a Life Fellow of the Optical Society of India (OSI), Computer Society of India (CSI), Indian Science Congress Association (ISCA), Indian Society for Technical Education (ISTE), Indian Unit of Pattern Recognition and Artificial Intelligence (IUPRAI) - the Indian affiliate of the International Association for Pattern Recognition (IAPR), Senior Member of Associated Computing Machinery (ACM), IEEE Computer Society, USA and IACSIT. [Editor]

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