09ZS18
MOBILE COMPUTING
3 0 0 3
INTRODUCTION: History – Added dimensions of mobile computing
– Condition of the mobile user. (3)
DEVELOPMENT FRAMEWORKS AND TOOLS: N-tier client server
– Java Wireless Toolkit: CLDC and MIDP – Hello MIDP – Publishing frameworks:
Cocoon – Architecture – Generators, Transformers, Serializers – Sitemap – XSP –
Hello Cocoon. (6)
XML FOR MOBILE
COMPUTING:
XML Schema – RDF – RDF Schema – UML and RDF – XML and UML. (3)
MOBILE GRAPHICAL UI: Model View Controller – Presentation
Abstraction Control – Transform based techniques – PAC TG – Single Channel
Specialization – Specialization on Server – Java Wireless Toolkit GUI – Example
– Modeling with UML – UML extensions – Optimizing GUI. (8)
SYNCHRONIZATION AND REPLICATION: Taxonomy – For mobile
applications – SyncML – WebDAV – Using UML.
(4)
LOCATION BASED SERVICES: Data acquisition of
location information – Geographical Positioning System based solution – Non GPS
solution – Geographical Information System – Location information modeling: GML
– Location based Java Wireless Toolkit application. (7)
MOBILE SECURITY: Taxonomy of problems – Security in wireless
networks – Distinguishing privacy and security – Modeling security with UML. (3)
MOBILE DEVELOPMENT PROCESS: UML based development
– Use cases – Testing: Mobile infrastructure –
Validating use cases – Effect of dimensions of mobility on testing – Case
study: Electrical field service company – Requirements – Detailed design –
Implementation. (8)
Total 42
REFERENCES:
1.
Reza
B Far, “Mobile Computing Principles: Designing
and Developing Mobile Applications with UML and XML”, Cambridge
University Press, United Kingdom,
2005.
2.
Golden
G Richard III, Loren Schwiebert, Frank Adelstein and Sandeep K S Gupta,
“Fundamentals of Mobile and Pervasive Computing”, McGraw-Hill Inc., USA, 2005.
3.
Michael
Juntao Yuan, “Enterprise J2ME: Developing Mobile Java Applications”,
Pearson Education, USA, 2004.
4.
Mohammad
Ilyas and Imad Mahgoub, “Mobile Computing Handbook”, Aurebach Publishers, 2005.
09ZS20 EVOLUTIONARY
COMPUTING TECHNIQUES
INTRODUCTION: Historical
development of Evolutionary Computation (EC) – Features of EC – Classification
of EC – Advantages – Applications.
(4)
SIMULATED
ANNEALING: Introduction – Annealing schedule – Pseudo
code – Parameter selection – Applications.
(3)
HILL
CLIMBING:
Introduction – Mathematical description – Local and Global maxima – Ridges –
Plateau – Pseudo code – Applications.
(3)
GENETIC
ALGORITHMS:
Introduction – Biological Background – Operators in GA-GA Algorithm –
Classification of GA – Applications.
(12)
ANT
COLONY OPTIMIZATION:
Introduction – From real to artificial ants- Theoretical considerations –
Convergence proofs – ACO Algorithm – ACO and model based search – Application
principles of ACO. (10)
PARTICLE
SWARM OPTIMIZATION:
Introduction – Principles of bird flocking and fish schooling – Evolution of
PSO – Operating principles – PSO Algorithm – Neighborhood Topologies –
Convergence criteria – Applications of PSO. (10)
Total 42
REFERENCES:
1.
S
N Sivanandam and S N Deepa, “Introduction to Genetic Algorithm”, Springer
Verlag publication, New Delhi,
2008.
2.
Kenneth
A DeJong, “Evolutionary Computation A Unified Approach”, Prentice Hall of India,
New Delhi,
2006.
3.
Marco
Dorigo and Thomas Stutzle, “Ant Colony optimization”, Prentice Hall of India,
New Delhi 2005.
4.
Kennedy
J and Russel C Eberhart, “Swarm Intelligence”, Morgan Kaufmann Publishers, USA,
2001.
09ZS41
USER INTERFACE DESIGN
3 0 2 4
HUMAN FACTORS: The importance of User Interface – UI and
Software Designer – Goals of UI design – Motivations for human factors in
Design – Understanding user needs and requirements. (5)
INTERACTION DEVICES: Pointing devices – Speech recognition,
digitization and generation - Image and video displays.
(4)
MODELS: Theories – Different models - Object -
Action Interface Model - Principles for Design - Data display and entry
guidelines.
(5)
DESIGN PROCESS:
User Interface Design Process – Classes of UI
design – Principles of good design – Evaluating design using the principles –
Choice of color – Task oriented approach for UI - Case study.
(4)
GUI design process -
Design of icons – Use of metaphors – GUI style guides and toolkits – Portability
– GUI design and object oriented approach – Case study.
(4)
CSCW
user interfaces
- CSCW characteristics – Examples – CSCW UI – Method of specifying and designing
UI for CSCW systems – Case study. (3)
USABILITY: The viewpoint of user, customer and designer
–Usability specification – Description of stages in usability specification and
evaluation. (6)
INFORMATION RELATED: Information Search and Visualization –
Hypermedia and WWW. (7)
HCI STANDARDS: ECMA – ISO – BSI guide.
(4)
Total 42
Lab components:
1.
Introductory lab, getting acquainted with software (like Visual
C++ / Delphi / Builder)
2.
Simple component-oriented programming example, Windows API
demonstration
3.
Window features, window redrawing, validity of window content,
message and user message handling
4.
Application with dialog box, basic building blocks, blocks
properties, mutual communication
5.
Keyboard and mouse in Windows, cursor changes, clipboard
6.
Multithreaded application, development of user interface
components
7.
Development of a Web UI and its evaluation
REFERENCES:
1.
Linda Mcaulay, “HCI for Software Designers”,International Thompson
Computer Press, USA,1998.
2.
Ben Schneiderman, "Designing the User Interface", Pearson
Education, New Delhi,2005.
3.
Alan Cooper, "The Essentials of User Interface Design",
IDG Books, New Delhi,1995.
4.
Jacob Nielsen, "Usability Engineering", Academic Press,
1993.
5. Alan Dix et al, "Human - Computer Interaction",
Prentice Hall, USA,1993.
09ZC14 DATA
WAREHOUSING AND MINING
3 0 0 3
DATA WAREHOUSING: Introduction- Definition and description, need for data
ware housing, need for strategic information, failures of past decision support
systems, OLTP vs DWH-DWH requirements-trends in DWH-Application of DWH. (8)
DATA WAREHOUSING ARCHITECTURE: Reference
architecture- Components of reference architecture - Data warehouse building
blocks, implementation, physical design process and DWH deployment process. A
Multidimensional Data, Model Data Warehouse Architecture. (9)
DATA MINING: Data mining tasks-Data
mining vs KDD- Issues in data mining, Data Mining metrics, Data mining
architecture - Data cleaning- Data transformation- Data reduction - Data mining
primitives. (6)
Association Rule
Mining: Introduction - Mining
single dimensional Boolean association rules from transactional databases -
Mining multi dimensional association rules.
(5)
Classification and Prediction: Classification
Techniques - Issues regarding classification and prediction - decision tree -
Bayesian classification –Classifier accuracy – Clustering – Clustering Methods
- Outlier analysis. (9)
APPLICATIONS
AND OTHER DATA MINING METHODS:
Distributed and parallel Data Mining Algorithms, Text mining- Web mining. (5)
Total 42
REFERENCES:
1.
Jiawei
Han and Micheline Kamber, ” Data Mining Concepts and Techniques”, Morgan
Kaufmann Publishers, USA,
2006.
2.
Berson,
”DataWarehousing, Data Mining and OLAP”,
Tata McGraw Hill Ltd, New Delhi,
2004.
3.
Arun
K Pujari,”Data mining techniques”, Oxford University Press, London, 2003.
4.
Dunham
M H, ”Data mining: Introductory and Advanced Topics”. Pearson Education, New
Delhi, 2003.
5. Mehmed
Kantardzic,” Data Mining Concepts, Methods and Algorithms”, John Wiley and
Sons, USA, 2003
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