3 sem subjects and syllabus

PERIODS
OUTCOMES:
 Implement machine learning through neural networks.
 Write Genetic Algorithm to solve the optimization problem
 Develop a Fuzzy expert system.
 Model Neuro Fuzzy system for clustering and classification.
REFERENCES: 1. Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani, “Neuro-Fuzzy and Soft
Computing”, Prentice-Hall of India, 2003
2. Kwang H.Lee, “First course on Fuzzy Theory and Applications”, Springer–Verlag Berlin
Heidelberg, 2005.
3. George J. Klir and Bo Yuan, “Fuzzy Sets and Fuzzy Logic-Theory and Applications”,
Prentice Hall, 1995.
4. James A. Freeman and David M. Skapura, “Neural Networks Algorithms, Applications,
and Programming Techniques”, Pearson Edn., 2003.
5. David E. Goldberg, “Genetic Algorithms in Search, Optimization and Machine Learning”,
Addison Wesley, 2007.
6. Mitsuo Gen and Runwei Cheng,”Genetic Algorithms and Engineering Optimization”,
Wiley Publishers 2000.
7. Mitchell Melanie, “An Introduction to Genetic Algorithm”, Prentice Hall, 1998.
8. S.N.Sivanandam, S.N.Deepa, “Introduction to Genetic Algorithms”, Springer, 2007.
9. A.E. Eiben and J.E. Smith “Introduction to Evolutionary Computing” Springer, 2003
10. E. Sanchez, T. Shibata, and L. A. Zadeh, Eds., "Genetic Algorithms and Fuzzy Logic
Systems: Soft Computing Perspectives, Advances in Fuzzy Systems - Applications and
Theory", Vol. 7, River Edge, World Scientific, 1997.
11. ROSS TIMOTHY J, Fuzzy Logic with Engineering Applications, Wiley India Pvt Ltd, New
Delhi, 2010


IF7007 SOFTWARE QUALITY AND TESTING L T P C
3 0 0 3
OBJECTIVES:
 To explore the basics and goals of software testing.
 To discuss various types of software testing and its techniques
 To list out various tools which can be used for automating the testing process
 To introduce various software quality standards for establishing quality environment
 To discuss various methods and evaluation procedures for improving the quality
models
UNIT I INTRODUCTION 9
Basics of Software Testing – Testing Principles – Goals – Testing Life Cycle– Phases of
Testing–Test Plan(IEEE format) – Importance of Testing in Software Production Cycle.
UNIT II SOFTWARE TESTING METHODOLOGY 9
Software Test Plan – Components of Plan - Types of Technical Reviews - Static and
Dynamic Testing- – Software Testing in Spiral Manner - Information Gathering - Test
Planning - Test Case Design - Test Development - Test Coverage - Test Evaluation -
Prepare for Next Spiral - Conduct System Test - Acceptance Test - Summarize Testing
Results.
UNIT III EMERGING SPECIALIZED AREAS IN TESTING 9
Test Process Assessment – Test Automation Assessment - Test Automation Framework –
Nonfunctional Testing – SOA Testing – Agile Testing – Testing Center of Excellence –
Onsite/Offshore Model - Taxonomy of Testing tools, Methodology to evaluate automated
testing tools, Rational Testing Tools, Java Testing Tools, JMetra, JUNIT and Cactus.
UNIT IV SOFTWARE QUALITY MODELS 9
Software quality –Verification versus Validation– Components of Quality Assurance – SQA
Plan – Quality Standards – CMM – PCMM – CMMI – Malcolm Baldrige National Quality
Award.
UNIT V QUALITY THROUGH CONTINUOUS IMPROVEMENT PROCESS 9
Role of Statistical Methods in Software Quality – Transforming Requirements into Test
Cases – Deming’s Quality Principles – Continuous Improvement through Plan Do Check
Act (PDCA).
TOTAL: 45 PERIODS
OUTCOMES:
Upon Completion of the course, the students should be able to
 Compare and pick out the right type of software testing process for any given real world
problem
 Carry out the software testing process in efficient way
 Automate the testing process by using several testing tools
 Establish a quality environment as specified in standards for developing quality software
 Analyze and improve the quality procedures based on the past experience
37
REFERENCES:
1. William E.Lewis, “Software Testing and Continuous Quality Improvement”, Third edition,
Auerbach Publications, 2011.
2. Kshirasagar Naik, Priyadarshi Tripathy, “Software Testing and Quality Assurance -
Theory and Practice”, John Wiley & Sons publication, 2011.
3. Ron Patton, “Software testing”, Second edition, Pearson Education, 2007
4. Elfriede Dustin, Jeff Rashka, John Paul, “Automated Software Testing: Introduction,
Management and Performance”, Addison-Wesley, 1999.
5. Effective Methods for Software Testing, 2nd Edition, William E. Perry , Second Edition,
Wiley India, 2006.
6. Software Testing Tools, K.V.K.K. Prasad, Dream tech press, 2008
7. Testing and Quality Assurance for Component-based Software, by Gao, Tsao and Wu,
Artech House Publishers
8. Software Testing, Srinivasan Desikan & Gopalaswamy Ramesh, Pearson Education,
2006.
9. Software Testing Techniques, Scott Loveland & Geoffrey Miller, Shroff Publishers, 2005.
10. Software Testing Techniques, by Bories Beizer, Second Edition, Dreamtech Press
Managing the Testing Process, by Rex Black, Wiley



IF7014 4G TECHNOLOGIES L T P C
3 0 0 3
OBJECTIVES: • To learn various generations of wireless and cellular networks
• To study about fundamentals of 3G Services, its protocols and applications
• To study about evolution of 4G Networks, its architecture and applications
• To study about WiMAX networks, protocol stack and standards
• To Study about Spectrum characteristics & Performance evaluation
UNIT I INTRODUCTION 9
Introduction: History of mobile cellular systems, First Generation, Second Generation,
Generation 2.5, Overview of 3G & 4G, 3GPP and 3GPP2 standards
UNIT II 3G NETWORKS 9
3G Networks: Evolution from GSM, 3G Services & Applications, UMTS network structure,
Core network, UMTS Radio access, HSPA – HSUPA, HSDPA, CDMA 1X , EVDO Rev -0,
Rev-A, Rev-B, Rev-C Architecture, protocol stack.
49
UNIT III 4G LTE NETWORKS 9
4G Vision, 4G features and challenges, Applications of 4G, 4G Technologies – Multi carrier
modulation, Smart Antenna Techniques, OFDM-MIMO Systems, Adaptive Modulation and
Coding with Time-Slot Scheduler, Bell Labs Layered Space Time (BLAST) System,
Software-Defined Radio, Cognitive Radio.
UNIT IV WiMAX NETWORKS 9
WiMax: Introduction – IEEE 802.16, OFDM, MIMO, IEEE 802.20
UNIT V SPECTRUM & PERFORMANCE 9
Spectrum for LTE-Flexibility-Carrier Aggregation-Multi standard Radio base stations-RF
requirements for LTE-Power level requirements-Emission requirements-Sensitivity and
Dynamic range-Receiver susceptibility. Performance Assessment-Performance Evaluation
TOTAL:45 PERIODS
OUTCOMES:
Upon completion of the course, the students should be able to:
 Acquaint with the latest 3G/4G and WiMAX networks and its architecture.
 Interpret the various protocols and standards in various layers in Wireless networks.
 Design and implement wireless network environment for any application using latest
wireless protocols and standards
 Analyze the performance of networks
 Explore the benefits of WiMax networks
 Exploit various diversity schemes in LTE
REFERENCES:
Introduction to 3G Mobile Communication, Juha Korhonen, Artech House,
(www.artechhouse.com), Jan 2003, ISBN-10: 1580535070
1. 4G LTE/LTE – Advanced for Mobile Broadband, Erik Dahlman, Stefan Parkvall,
Johan Skold, Academic Press 2011.
2. 3G Evolution HSPA and LTE for Mobile Broadband, Erik Dahlman, Stefan Parkvall,
Johan Skold and Per Beming, Academic Press, Oct 2008, ISBN-10: 0123745381
3. UMTS Mobile Communication for the Future, Flavio Muratore, John Wiley & Sons
Ltd, Jan 2001, ISBN-10: 0471498297
4. HSDPA/HSUPA for UMTS, Harri Holma and Antti Toskala, Johan Wiley & Sons Ltd,
May 2006, ISBN-10: 0470018844
5. Savo G.Glisic, “Advanced Wireless Networks- 4GTechnologies”, Wiley, 2006
6. Magnus Olsson, Catherine Mulligan, “EPC and 4G packet network”, Elsevier 2012
7. Vijay Garg, “Wireless Communications and Networking”, Elsevier, Morgan kufmann
publisher 2007.

MA7155 Applied Probability and Statistics E-books Notes Model question paper

MA7155 Applied Probability and Statistics E-books Notes Model question paper 

UNIT-V Multivariate Analysis
Download- NOTES\


References E-books Download below:

1.Jay L. Devore, “Probability and Statistics For Engineering and the Sciences”,Thomson
and Duxbury, 2002. E-book- Download
To purchase a hard copy- Click Here

2.Richard Johnson. ”Miller & Freund’s Probability and Statistics for Engineer”, Prentice –
Hall , Seventh Edition, 2007.E-book- download
To purchase a hard copy- Click Here

3.Richard A. Johnson and Dean W. Wichern, “Applied Multivariate Statistical Analysis”,
Pearson Education, Asia, Fifth Edition, 2002. E-book- download
To purchase a hard copy- Click Here

4.Gupta S.C. and Kapoor V.K.”Fundamentals of Mathematical Statistics”, Sultan an Sons,
E-book- download
To purchase a hard copy- Click Here


5.Dallas E Johnson , “Applied Multivariate Methods for Data Analysis”, Thomson an Duxbury
press,1998. E-book- download
To purchase a hard copy- Click Here

NE7202 Network And Information Security Important Questions April May 2014

NE7202 Network And Information Security Important Questions April May 2014 

 

NE7202 Important Questions to download – Click Here

Also check :

NE7202 Notes – Click Here

 

CP7202 Advanced Databases Notes, E-books

1. R.Elmasri, S.B.Navathe, “Fundamental of database Systems”E-book Download- Click Here

2. Thomas cannolly and Carolyn begg, “Databases systems, A practical Approach to Design, Implementation and Management” E-book Download- Click Here

3. Henery F Korth, Abraham Silberschatz, S.Sudharshan, “Database System Concepts”E-book Download -Click Here

4.C.J.Date, A.kannan and S.Swaynthan, “A Introduction to Database Systems”E-book Download- click here

5. Ragu Ramakrishnan, Johannes Gehrke, “Database Management Systems” E-book Download- Click Here

NOTE’S For All Subjects PPT – ME Tech it 

Nis   https://drive.google.com/folderview?id=0B5Py0CpqNGQ0cF8yb2VnUUNjNW8&usp=sharing

 

CC   https://drive.google.com/folderview?id=0B5Py0CpqNGQ0NnlUX3FRdnE0SFE&usp=sharing

 

ADB  https://drive.google.com/folderview?id=0B5Py0CpqNGQ0OGdKSndVanVVT1E&usp=sharing

IF7202 CLOUD COMPUTING e_books

1. Kai Hwang, Geoffrey C Fox, Jack G Dongarra, “Distributed and Cloud Computing, From Parallel Processing to the Internet of Things”, Morgan Kaufmann Publishers, 2012.  Click Here

2. John W.Rittinghouse and James F.Ransome, “Cloud Computing: Implementation, Management, and Security”, CRC Press, 2010.  Click Here

3. Toby Velte, Anthony Velte, Robert Elsenpeter, “Cloud Computing, A Practical Approach”, TMH, 2009.  Click Here

4. Kumar Saurabh, “ Cloud Computing – insights into New-Era Infrastructure”, Wiley India,2011.
5. George Reese, “Cloud Application Architectures: Building Applications and Infrastructure in the Cloud” O’Reilly  Click Here

6. James E. Smith, Ravi Nair, “Virtual Machines: Versatile Platforms for Systems and Processes”, Elsevier/Morgan Kaufmann, 2005. Click Here 

7. Katarina Stanoevska-Slabeva, Thomas Wozniak, Santi Ristol, “Grid and Cloud Computing – A Business Perspective on Technology and Applications”, Springer.  Click Here 

8. Ronald L. Krutz, Russell Dean Vines, “Cloud Security – A comprehensive Guide to Secure Cloud Computing”, Wiley – India, 2010   Click Here

9. Rajkumar Buyya, Christian Vecchiola, S.Tamarai Selvi, ‘Mastering Cloud Computing”, TMGH,2013. Click Here

10. Gautam Shroff, Enterprise Cloud Computing, Cambridge University Press, 2011   Click Here

11. Michael Miller, Cloud Computing, Que Publishing,2008  Click Here

12. Nick Antonopoulos, Cloud computing, Springer Publications, 2010  Click Here

NE7202 NETWORK AND INFORMATION SECURITY

1. William Stallings, “Cryptography and Network Security: Principles and Practices”, Third Edition, Pearson Education, 2006.       Click Here  
2. Matt Bishop ,“Computer Security art and science ”, Second Edition, Pearson Education, 2002  Click Here
3. Wade Trappe and Lawrence C. Washington, “Introduction to Cryptography with Coding Theory” Second Edition, Pearson Education, 2007  Click Here
4. Jonathan Katz, and Yehuda Lindell, Introduction to Modern Cryptography, CRC Press, 2007    Click Here
5. Douglas R. Stinson, “Cryptography Theory and Practice”, Third Edition, Chapman & Hall/CRC, 2006  Click Here
6. Wenbo Mao, “Modern Cryptography – Theory and Practice”, Pearson Education, First Edition, 2006.  Click Here
7. Network Security and Cryptography, Menezes Bernard, Cengage Learning, New Delhi, 2011 
8. Man Young Rhee, Internet Security, Wiley, 2003   Click Here
9. OWASP top ten security vulnerabilities: http://xml.coverpages.org/OWASPTopTen. Pdf   Click Here

IF7203-DATA WAREHOUSING AND DATA MINING QUESTION BANK WITH ANSWERS UNIT I-DATA WAREHOUSE

Part A

Two marks

1.  Define Data warehouse (or) what is Data Warehouse?

A data warehouse is a repository of multiple heterogeneous data sources organized under a unified schema at a single site to facilitate management decision making.                          (Or)

A data warehouse is a subject-oriented, time-variant and non-volatile collection of data in support of management’s decision-making process.

2.  What are operational databases?

Organizations maintain large database that are updated by daily transactions are called operational databases.

3.  Define OLTP?

If an on-line operational database systems is used for efficient retrieval, efficient storage and management of large amounts of data, then the system is said to be on-line transaction processing.

4.  Define OLAP?

Data warehouse systems serves users (or) knowledge workers in the role of data analysis and decision-making. Such systems can organize and present data in various formats. These systems are known as on-line analytical processing systems.

5.  Write short notes on multidimensional data model?

Data warehouses and OLTP tools are based on a multidimensional data model. This model is used for the design of corporate data warehouses and department data marts. This model contains a Star schema, Snowflake schema and Fact constellation schemas. The core of the multidimensional model is the data cube.

6.  Define data cube?

It consists of a large set of facts (or) measures and a number of dimensions.

7.  What are facts?

Facts are numerical measures. Facts can also be considered as quantities by which we can analyze the relationship between dimensions.

8.  What are dimensions?

Dimensions are the entities (or) perspectives with respect to an organization for keeping records and are hierarchical in nature.

9.  Define dimension table?

A dimension table is used for describing the dimension. (e.g.) A dimension table for item may contain the attributes item_ name, brand and type.

10.       Define fact table?

Fact table contains the name of facts (or) measures as well as keys to each of the related dimensional tables.

11.       What are lattice of cuboids?

In data warehousing research literature, a cube can also be called as cuboids. For different (or) set of dimensions, we can construct a lattice of cuboids, each showing the data at different level. The lattice of cuboids is also referred to as data cube.

12.       What are apex cuboids?

The 0-D cuboids which holds the highest level of summarization is called the apex cuboids. The apex cuboids are typically denoted by all.

13.       List out the components of star schema?

A large central table (fact table) containing the bulk of data with no redundancy. A set of smaller attendant tables (dimension tables), one for each dimension.

14.       What is snowflake schema?

The snowflake schema is a variant of the star schema model, where some dimension tables are normalized thereby further splitting the tables in to additional tables.

15.       List out the components of fact constellation schema?

This requires multiple fact tables to share dimension tables. This kind of schema can be viewed as a collection of stars and hence it is known as galaxy schema (or) fact constellation schema.

16.       Point out the major difference between the star schema and the snowflake schema?

The dimension table of the snowflake schema model may be kept in normalized form to reduce redundancies. Such a table is easy to maintain and saves storage space.

17.       Which is popular in the data warehouse design, star schema model (or) snowflake schema model?

Star schema model, because the snowflake structure can reduce the effectiveness and more joins will be needed to execute a query.

18.       Define concept hierarchy?

A concept hierarchy defines a sequence of mappings from a set of low-level concepts to higher-level concepts.

19.       Define total order?

If the attributes of a dimension which forms a concept hierarchy such as “street<city< province_or_state <country”, then it is said to be total order. Country Province or state City Street Fig: Partial order for location

20.       Define partial order?

If the attributes of a dimension which forms a lattice such as “day<{month<quarter; week}<year, then it is said to be partial order.

21.       Define schema hierarchy?

A concept hierarchy that is a total (or) partial order among attributes in a database schema is called a schema hierarchy.

22.       List out the OLAP operations in multidimensional data model?

Roll-up _ Drill-down _ Slice and dice _ Pivot (or) rotate

23.       What is roll-up operation?

The roll-up operation is also called drill-up operation which performs aggregation on a data cube either by climbing up a concept hierarchy for a dimension (or) by dimension reduction.

24.       What is drill-down operation?

Drill-down is the reverse of roll-up operation. It navigates from less detailed data to more detailed data. Drill-down operation can be taken place by stepping down a concept hierarchy for a dimension.

25.       What is slice operation?

The slice operation performs a selection on one dimension of the cube resulting in a sub cube.

26.       What is dice operation?

The dice operation defines a sub cube by performing a selection on two (or) more dimensions.

27.       What is pivot operation?

This is a visualization operation that rotates the data axes in an alternative presentation of the data.

28.       List out the views in the design of a data warehouse?

Top-down view _ Data source view _ Data warehouse view _ Business query view.

29.       What are the methods for developing large software systems?

Waterfall method _ Spiral method

30.       How the operation is performed in waterfall method?

The waterfall method performs a structured and systematic analysis at each step before proceeding to the next, which is like a waterfall falling from one step to the next.

31.       How the operation is performed in spiral method?

The spiral method involves the rapid generation of increasingly functional systems, with short intervals between successive releases. This is considered as a good choice for the data warehouse development especially for data marts, because the turnaround time is short, modifications can be done quickly and new designs and technologies can be adapted in a timely manner.

32.       List out the steps of the data warehouse design process?

Choose a business process to model.

 Choose the grain of the business process

 Choose the dimensions that will apply to each fact table record.

 Choose the measures that will populate each fact table record.

33.       What is enterprise warehouse?

An enterprise warehouse collects all the information’s about subjects spanning the entire organization. It provides corporate-wide data integration, usually from one (or) more operational systems (or) external information providers. It contains detailed data as well as summarized data and can range in size from a few giga bytes to hundreds of giga bytes, tera bytes (or) beyond.

34.       What is data mart?

Data mart is a database that contains a subset of data present in a data warehouse. Data marts are created to structure the data in a data warehouse according to issues such as hardware platforms and access control strategies. We can divide a data warehouse into data marts after the data warehouse has been created. Data marts are usually implemented on low-cost departmental servers that are UNIX (or) windows/NT based.

35.       What are dependent and independent data marts?

Dependent data marts are sourced directly from enterprise data warehouses. Independent data marts are data captured from one (or) more operational systems (or) external information providers (or) data generated locally with in particular department (or) geographic area.

 36.       What is virtual warehouse?

 A virtual warehouse is a set of views over operational databases. For efficient query processing, only some of the possible summary views may be materialized. A virtual warehouse is easy to build but requires excess capability on operational database servers.

37.       Define indexing?

 Indexing is a technique, which is used for efficient data retrieval (or) accessing data in a faster manner. When a table grows in volume, the indexes also increase in size requiring more storage.

38.       What are the types of indexing?

B-Tree indexing _ Bit map indexing _ Join indexing

39.       Define metadata?

Metadata is used in data warehouse is used for describing data about data. (i.e.) Meta data are the data that define warehouse objects. Metadata are created for the data names and definitions of the given warehouse.

40.       Define VLDB?

Very Large Data Base. If a database whose size is greater than 100GB, then the database is said to be very large database.

PART B

16 (OR) 8 MARKS

1.      Discuss the components of data warehouse.    (8)

_Subject-oriented

_Integrated

_Time-Variant

_Non-volatile

2.      List out the differences between OLTP and OLAP.      (8)

_ Users and system orientation

_ Data contents

_ Database design

_ View

_ Access patterns

3.       Discuss the various schematic representations in multidimensional model.

_ Star schema

_ Snow flake schema

_ Fact constellation schema

4.       Explain the OLAP operations I multidimensional model.

_ Roll-up

_ Drill-down

_ Slice and dice

_ Pivot or rotate

5.      Explain the design and construction of a data warehouse.

_ Design of a data warehouse

• Top-down view

• Data source view

• Data warehouse view

• Business query view

_ Process of data warehouse design

6.      Explain the three-tier data warehouse architecture.

_ Warehouse database server (Bottom tier)

_ OLAP server (middle tier)

_ Client (top tier)

7.      Explain indexing.

_ Definition

_ B-Tree indexing

_ Bit-map indexing

_ Join indexing

8.       Write notes on metadata repository.

_ Definition

_ Structure of the data warehouse

_ Operational metadata

_ Algorithms used for summarization

_ Mapping from operational environment to data warehouse

_ Data related to system performance

_ Business metadata