Case Studies in Intelligent Computing

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advanced intelligent computing case studies
ANFIS
ANFIS Algorithm
ANFIS Model
artificial
artificial intelligence applications
Automating Network Protocol Identification
Category=UYQ
Data Set
Decomposition Level
Denoising Methods
Dental Radiographs
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
extraction
feature
fuzzy logic systems
Fuzzy Rough Set
Fuzzy Set
HSI Value
Intelligent Grade Estimation Technique for Indian Black Tea
Intelligent Machine Vision Technique for Disease Detection through Eye Scanning
Intuitionistic Fuzzy Set
Inverse Kinematics
Kalman Lter
Log Sigmoid Activation Function
Low Intensity Laser Irradiation
machine learning techniques
Machine Vision
machines
Medical Knowledge-Based Systems and Knowledge-Based Systems
Membership Function Parameters
Membership Functions
multilayer
N0 N1 N2 N3 N4
networks
neural
neural network modeling
Pe Rc
perceptron
remote sensing analysis
RGB
Sclera Region
Sensor Node
sentiment analysis methods
Sugeno Type FIS
support
Survey of Intelligent Computing
Tea Samples
vector

Product details

  • ISBN 9781482207033
  • Weight: 1218g
  • Dimensions: 178 x 254mm
  • Publication Date: 29 Aug 2014
  • Publisher: Apple Academic Press Inc.
  • Publication City/Country: CA
  • Product Form: Hardback
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Although the field of intelligent systems has grown rapidly in recent years, there has been a need for a book that supplies a timely and accessible understanding of this important technology. Filling this need, Case Studies in Intelligent Computing: Achievements and Trends provides an up-to-date introduction to intelligent systems.

This edited book captures the state of the art in intelligent computing research through case studies that examine recent developments, developmental tools, programming, and approaches related to artificial intelligence (AI). The case studies illustrate successful machine learning and AI-based applications across various industries, including:

  • A non-invasive and instant disease detection technique based upon machine vision through the image scanning of the eyes of subjects with conjunctivitis and jaundice
  • Semantic orientation-based approaches for sentiment analysis
  • An efficient and autonomous method for distinguishing application protocols through the use of a dynamic protocol classification system
  • Nonwavelet and wavelet image denoising methods using fuzzy logic
  • Using remote sensing inputs based on swarm intelligence for strategic decision making in modern warfare
  • Rainfall–runoff modeling using a wavelet-based artificial neural network (WANN) model

Illustrating the challenges currently facing practitioners, the book presents powerful solutions recently proposed by leading researchers. The examination of the various case studies will help you develop the practical understanding required to participate in the advancement of intelligent computing applications.

The book will help budding researchers understand how and where intelligent computing can be applied. It will also help more established researchers update their skills and fine-tune their approach to intelligent computing.

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.