214 black & white illustrations, 118 black & white tables
Biju Issac, Nauman Israr
Unsewn / adhesive bound
Table Of Contents
Survey of Intelligent Computing; Kuruvilla Mathew and Biju Issac Intelligent Machine Vision Technique for Disease Detection through Eye Scanning; Amit Laddi and Amod Kumar Laser Promotes Proliferation of Stem Cells: A Comprehensive Case Study Consolidated by Intelligent Agent-Based Model Predictions; Aya Sedky Adly, Mohamed H. Haggag, and Mostafa-Sami M. Mostafa Semantic Orientation-Based Approaches for Sentiment Analysis; Basant Agarwal, Namita Mittal, and Vijay Kumar Sharma Rough Set on Two Universal Sets and Knowledge Representation; Debi P. Acharjya Automating Network Protocol Identification; Ryan G. Goss and Geoff S. Nitschke Intelligent and Non-Intelligent Approaches in Image Denoising: A Comparative Study; Mantosh Biswas and Hari Om Fuzzy Relevance Vector Machines with Application to Surface Electromyographic Signal Classification; Hong-Bo Xie, Hu Huang, and Socrates Dokos Intelligent Remote Operating System Detection; Joao P. Souza Medeiros, Joao B. Borges Neto, Gutto S. Dantas Queiroz, and Paulo S. Motta Pires An Automated Surveillance System for Public Places; Kumar S. Ray, Debayan Ganguly, and Kingshuk Chatterjee Nature-Inspired Intelligence: A Modern Tool for Warfare Strategic Decision Making; Lavika Goel High-Utility Patterns Discovery in Data Mining: A Case Study; Chiranjeevi Manike and Hari Om Bag of Riemannian Words for Virus Classification; Masoud Faraki and Mehrtash Harandi Normalized Ordinal Distance: A Performance Metric for Ordinal, Probabilistic-Ordinal, or Partial-Ordinal Classification Problems; Mohammad Hasan Bahari and Hugo Van Hamme Predictive Data Mining for Oral Cancer Treatment; Neha Sharma and Hari Om Human Identification Using Individual Dental Radiograph Records; Omaima Nomir and Mohamed Abdel-Mottaleb A Novel Hybrid Bayesian-Based Reasoning: Multinomial Logistic Regression Classification and Regression Tree for Medical Knowledge-Based Systems and Knowledge-Based Systems; Patcharaporn Paokanta Application of Backpropagation Neural Networks in Calculation of Robot Kinematics; R. R. Srikant and Ch. Srinivasa Rao Conceptual Modeling of Networked Organizations: The Case of Aum Shinrikyo; Saad Alqi thami , Jennifer Haegele, and Henry Hexmoor Energy-Efficient Wireless Sensor Networks Using Learning Techniques; Sumit Tokle, Shamantha Rai Bellip ady, Rajee v Ranjan, and Shirshu Varma Knowledge on Routing Nodes in MAN ET: A Soft Computing Approach; Senthilkumar K and Arunkumar Thangavelu Implication of Feature Extraction Methods to Improve Performance of Hybrid Wavelet-ANN Rainfall-Runoff Model; Vahid Nourani, Tohid Rezapour Khanghah, and Aida Hosseini Baghanam Artificial Intelligence: A Tool for Better Understanding Complex Problems in Long-Term Care; Vijay K. Mago, Ryan Woolrych, Vahid Dabbaghian, and Andrew Sixsmith Combining Feature Selection and Data Classification Using Ensemble Approaches: Application to Cancer Diagnosis and Credit Scoring; Afef Ben Brahim, Waad Bouaguel, and Mohamed Limam Intelligent Grade Estimation Technique for Indian Black Tea; Amit Laddi and Neelam R. Prakash
Dr. Biju Issac is a senior lecturer at the School of Computing, Teesside University, United Kingdom, and has more than 15 years of academic experience with higher education in India, Malaysia, and the United Kingdom. He earned a PhD in networking and mobile communications, along with MCA (master of computer applications) and BE (electronics and communications engineering). He is a senior Institute of Electrical and Electronics Engineers (IEEE) member, a fellow of the Higher Education Academy, an Institution of Engineering and Technology (IET) member, and a chartered engineer (CEng). He is a CISCO-Certified Network Associate (CCNA) instructor, a Sun-Certified Java instructor, and a Lotus Notes professional. His broad research interests are in computer networks, wireless networks, computer or network security, mobility management in 802.11 networks, intelligent computing, data mining, spam detection, secure online voting, e-learning, and so forth. Dr. Issac has authored more than 60 peer-reviewed research publications, including conference papers, book chapters, and journal papers. He has supervised postgraduate research students to completion. He is in the technical program committee of many international conferences and on the editorial board of some journals and has reviewed many research papers. Dr. Nauman Israr has been a senior lecturer at the School of Computing, Teesside University, United Kingdom, for many years. He earned his PhD in wireless sensor networks at the University of Bradford, United Kingdom. He teaches computer networks-related subjects at the university. His areas of research expertise are wireless sensor networks, wireless networked control systems, fly-by-wireless systems, active aircraft, and wireless embedded systems. Dr. Israr was a research fellow at Queen's University Belfast (Active Aircraft Project). The aim of that project was to design and develop a wireless nervous system for the next-generation Airbus aircrafts, where the wireless system will be used to reduce the turbulence on the aircraft, thus reducing the fuel burned. He has published a number of conference papers, book chapters, and journal papers.