Cognitive Informatics, Computer Modelling, and Cognitive Science
Volume 1: Theory, Case Studies, and Applications

Examines the history, theory and development of Cognitive Science applied to solve key issues in cognitive informatics and computing

G. R. Sinha (Edited by), Jasjit Suri (Edited by)

9780128194430, Elsevier Science

Paperback, published 8 April 2020

410 pages
23.4 x 19 x 2.6 cm, 0.84 kg

Cognitive Informatics, Computer Modelling, and Cognitive Science: Theory, Case Studies, and Applications presents the theoretical background and history of cognitive science to help readers understand its foundations, philosophical and psychological aspects, and applications in a wide range of engineering and computer science case studies. Cognitive science, a cognitive model of the brain, knowledge representation, and information processing in the human brain are discussed, as is the theory of consciousness, neuroscience, intelligence, decision-making, mind and behavior analysis, and the various ways cognitive computing is used for information manipulation, processing and decision-making.

1. Introduction to cognitive science, informatics, and modeling2. Machine consciousness: mind, machine, and society contributors3. Brain-computer interface and neurocomputing4. The impact on cognitive development of a self-contained exploratory and technology-rich course on the physics of light and sound5. Identification of normal and abnormal brain hemorrhage on magnetic resonance images6. Cognitive informatics, computer modeling and cognitive science assessment of knee osteoarthritis in radiographic images: a machine learning approach7. Adaptive circadian rhythm a cognitive approach through dynamic light management8. Cognitive and brain function analysis of sleeping stage electroencephalogram wave using parallelization9. The future networks - a cognitive approach10. Identification of face along with configuration beneath unobstructed ambiance via reflective deep cascaded neural networks11. Setting up a neural machine translation system for English to Indian languages12. An extreme learning-based adaptive control design for an autonomous underwater vehicle13. Geometric total plaque area is an equally powerful phenotype compared to carotid intima-mediathickness for stroke risk assessment14. Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms15. Identification of road signs using a novel convolutional neural network16. Machine learning behind classification tasks in various engineering and science domains

Subject Areas: Biochemical engineering [TC]