Cognition and Cognitive Process Modelling
Cognitive Science is the study of the mind and human intelligence,
including computational models of human thought.
It is the interdisciplinary study of how information, e.g., concerning
perception, language, reasoning, and emotion, is represented and
transformed in the mind.
It consists of multiple research disciplines, including psychology
, artificial intelligence , philosophy , neuroscience , learning
sciences , linguistics , anthropology , sociology , and education
Nature of Mind and Mind Body problem.
Mechanisms of Mind.
Multiplicity of Mind.
Evolution Natural and Artificial.
The First AI Debate.
The Second AI Debate.
Representation and Third AI Debate.
Cognitive Models (SOAR/ACT-R/CLARION)
Principles of Interaction Design
Design methodology for complex products, services and events:
Design of integrated systems, products for future use, products
to be used in groups, devices used in public places, design of multi-modal
interfaces, expressive interfaces, products that enrich user experience.
The course takes an inter-disciplinary approach drawing upon
product design, visual communication, information architecture,
cognitive psychology and computer science. The course involves exploration
of alternatives, pushing the envelope of what is known.
The focus is on working collaboratively in groups to solve design
problems. The course will involve doing projects. Students need
to build soft prototypes of proposed systems at the end of the course.
Introduction to early VR technologies.
Input Devices: Trackers, Navigatioin & Gesture Interface.
Output Devices: Graphics, 3D, Sound & Haptic Displays.
Computing architecture for VR.
Human Factors in VR.
Traditional & Emerging applications of VR.
Image and Vision Processing
Digital Image Representation.
Intensity Transformations and Spatial Filtering.
Frequency Domain Processing.
Color Image Processing.
Morphological Image Processing.
Development and Evaluation of Artificial Neural Network Model
for Real life Applications.
Fuzzy Logic and its use in control engineering.
Problem solving using fuzzy techniques.
Genetic Programming: Issues and Applications.
Hidden Markov Models.
Hybrid Systems of ANN, GA and Fuzzy systems.
Advanced Graphics and Animation
Simple Raster Graphics.
Viewing in 3D.
Object Heirarchy and simple PHIGS.
Representing curves and surfaces.
Achromatic and colored lights.
Visible surface determination.
Illumination and shading.
Animation Production and Techniques.
Interpolation and bsic techniques.
Natural Language Processing
Introduction to course.
Language Models and Word prediction.
Part of Speech Tagging.
Named Entity Recognition.
Word Sense Disambiguation.
Natural Language Generation.
Artificial Neural Networks.
Supervised Learning Neural Networks.
Unsupervised Learning Neural Networks.
Radial Basis Functions.
Fuzzy sets, logic, reasoning, controllers.
The term vocabulary & postings lists.
Dictionaries and tolerant retrieval.
Scoring, term weighting & the vector space model.
Computing scores in a complete search system.
Evaluation in information retrieval.
Relevance feedback & query expansion.
Probabilistic information retrieval.
Language models for information retrieval.
Text classification & Naive Bayes.
Vector space classification.
Support vector machines & machine learning on documents.
Matrix decompositions & latent semantic indexing.
Web search basics.
Web crawling and indexes.
Wireless Sensor Network
Overview Of Wireless.
Sensor Network Platforms And Tools.