Case studies in intelligent computing : achievements and trends /
edited by Biju Issac and Nauman Israr.
- 1 online resource
An Auerbach book.
1. Survey of intelligent computing / Kuruvilla Mathew and Biju Issac -- 2. Intelligent machine vision technique for disease detection through eye scanning / Amit Laddi and Amod Kumar -- 3. Laser promotes Profiliferation of stem cells : a comprehensive case study consolidated by intelligent agent-based model predictions / Aya Sedky Adly, Mohamed Hassan Haggag, and Mostafa-Sami M. Mostafa -- 4. Semantic orientation-based approaches for sentiment analysis / Basant Agarwal, Namita Mittal, and Vijay Kumar Sharma -- 5. Rough set on two universal sets and knowledge representation / Debi P. Acharjya -- 6. Automating network protocol identification / Ryan G. Goss and Geoff S. Nitschke -- 7. Intelligent and non-intelligent approaches in image denoising : a comparative study / Mantosh Biswas and Hari Om -- 8. Fuzzy relevance vector machines with application to surface electromyographic signal classification / Hong-Bo Xie, Hu Huang, and Socrates Dokos -- 9. Intelligent remote operating system detection / Joao P. Souza Medeiros, Joao B. Borges Neto, Gutto S. Dantas Queiroz, and Paulo S. Motta Pires -- 10. An automated surveillance system for public places / Kumar S. Ray, Debayan Ganguly, and Kingshuk Chatterjee -- 11. Nature-inspired intelligence : a modern tool for warfare strategic decision making / Lavika Goel -- 12. High-utility patterns discovery in data mining : a case study / Chiranjeevi Manike and Hari Om -- 13. Bag of Riemannian words for virus classification / Masoud Faraki and Mehrtash Harandi -- 14. Normalized ordinal distance : a performance metric for ordinal, probabilistic-ordinal, or partial-ordinal classification problems / Mohammad Hasan Bahari and Hugo van Hamme -- 15. Predictive data mining for oral cancer treatment / Neha Sharma and Hari Om -- 16. Human identification using individual dental radiograph records / Omaima Nomir and Mohamed Abdel-Mottaleb -- 17. A novel hybrid Bayesian-based reasoning : multinomial logistic regression classification and regression tree for medical knowledge-based systems and knowledge-based systems / Patcharaporn Paokanta -- 18. Application of backpropagation neural networks in calculation of robot kinematics / R.R. Srikant and Ch. Srinivasa Rao -- 19. Conceptual modeling of networked organizations : the case of Aum Shinrikyo / Saad Alqithami, Jennifer Haegele, and Henry Hexmoor -- 20. Energy-efficient wireless sensor networks using learning techniques / Sumit Tokle, Shamantha Rai Bellipady, Rajeev Ranjan, and Shirshu Varma -- 21. Knowledge on routing nodes in MANET : a soft computing approach / Senthilkumar K. and Arunkumar Thangavelu -- 22. Implication of feature extraction methods to improve performance of hybrid wavelet-ANN rainfall-runoff model / Vahid Nourani, Tohid Rezapour Khanghah, and Aida Hosseini Baghanam -- 23. Artificial intelligence : a tool for better understanding complex problems in long-term care / Vijay K. Mago, Ryan Woolrych, Vahid Dabbaghian, and Andrew Sixsmith -- 24. Combining feature selection and data classification using ensemble approaches : application to cancer diagnosis and credit scoring / Afef Ben Brahim, Waad Bouaguel, and Mohamed Limam -- 25. Intelligent grade estimation technique for Indian black tea / Amit Laddi and Neelam Rup Prakash.
The book is a modern introduction to the whole field of intelligent systems, also known as artificial intelligence. Artificial intelligence has grown significantly in recent years and many texts and resources have failed to keep up with this important technology. The book takes a modern, 21st century approach to the concepts of artificial intelligence and includes the latest developments, developmental tools, programming, and approaches related to AI-- Intelligent software can come to decisions on its own, based on the training on a data set - which makes Artificial Intelligence (AI) a primary area of research these days. AI is the study and design of a system that comprehends its environment and makes decisions that maximize its chances of success. In most cases it is an application intelligence that evolves over time and gets better with fewer errors. In others it can be an intelligence derived out of a set of options or constraints--