msc tcs syllabi 2009
TRANSCRIPT
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PSG COLLEGE OF TECHNOLOGY: COIMBATORE - 641 004
(Autonomous college affiliated to Anna University, Coimbatore)
2009 REGULATIONS OF FIVE YEAR INTEGRATED MSc THEORETICAL COMPUTER SCIENCE DEGREE PROGRAMME (For the batches of students admitted in 2009 - 2010 and subsequently)
NOTE: The regulations hereunder are subject to amendments as may be made by the Academic Council of the College from time to time. Any or all such amendments will be effective from such date and to such batches of students (including those already undergoing the programme) as may be decided by the Academic Council. 1. CONDITIONS FOR ADMISSION
Candidates for admission to the first semester of the five year Integrated M.Sc. Theoretical Computer Science Degree programme will be required to satisfy the conditions of admission thereto prescribed by the Anna University, Coimbatore.
2. DURATION OF THE PROGRAMME i) Minimum Duration: The programme leading to the Degree of Master of
Science (MSc) in Theoretical Computer Science will extend over a period of 5 years / 10 semesters with 2 semesters per academic year. Each semester shall normally consist of 90 working days.
ii) Maximum Duration: The student shall complete all the passing
requirements of the MSc degree programme within a maximum period of 7 years / 14 semesters, reckoned from the commencement of the semester to which the student was first admitted.
3. STRUCTURE OF THE PROGRAMMES i) Curriculum: The curriculum for each programme includes courses of study
and detailed syllabi. The courses of study include theory courses ( electives), Practicals, Project Work I, Project Work II etc. as given in section 12.
ii) Electives: Every student shall opt electives from the list of electives relating to
his/her degree programme in consultation with the tutor and the HOD. iii) One Credit Courses: Students can also opt for one credit industry /
research oriented courses of 14 hours duration which will be offered by experts from industry / other institution / our faculty on specialized topics apart from the prescribed courses of study of the programme. Students can complete such one credit courses during the semesters 1 to 6,
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8 to 9 as and when these courses are offered by different departments. A
student will also be permitted to register for the one credit courses of other departments provided the student has fulfilled the necessary pre-requisites of the course being offered subject to approval by both the Heads of Departments.
iv) Project Work I & II: Every student shall undertake the Project Work I during the
seventh semester and the Project Work II during the tenth semester. The Project Work I & II shall be undertaken in industrial / research organizations or in the college in consultation with the faculty guide and the HOD. In case of the Project Work at industrial / research organization, the same shall be jointly supervised by a faculty guide and an expert from the organization.
v) Credit assignment:
The exact number of credits assigned to the different courses are shown in section 12. vi) Minimum credits: The minimum number of credits to be earned through
successful completion of the courses of study in the respective branch listed in section 12 infra, by a student to qualify for the award of degree is 233.
vii) Medium of instruction: The medium of instruction, examinations, project
report etc. shall be English.
4. REQUIREMENTS OF ATTENDANCE AND PROGRESS
i) A student will be deemed to have completed the course of any semester only if a) he / she has satisfied the attendance requirements as per the norms given
below:
Minimum attendance for eligibility to appear for semester examinations - 80%.
An exemption up to 10% can be awarded based on recommendation of HOD for participation in official co & extra curricular activities, Sports & games, paper or project presentation etc.
An exemption up to 10% can be awarded in exceptional cases on medical grounds on recommendation of the HOD.
b) his / her progress has been satisfactory and
c) his / her conduct has been satisfactory.
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ii) Students who do not qualify to appear for final examinations of any
semester for want of attendance and/or progress and/or conduct have to register for and redo that semester programme at the next immediate available opportunity subject to the approval of Anna University, Coimbatore.
5. PROCEDURE FOR COMPLETING THE PROGRAMME i) The course work of the odd semesters will normally be conducted only in odd
semesters and that of the even semesters only in even semesters. ii) A student will be permitted to proceed to the courses of study of any semester
only if he/she has satisfied the requirements of attendance, progress and conduct in respect of the preceding semester and had paid fees for that semester.
6. PROCEDURE FOR REJOINING THE PROGRAMME
A student who is required to repeat the study of any semester for want of attendance/ progress/conduct or who desires to rejoin the course after a period of discontinuance or who upon his/her own request is permitted by the authorities to repeat the study of any semester, may join the semester which he/she is eligible or permitted to join, only at the time of its normal commencement for a regular batch of students and after obtaining the approval from Anna University, Coimbatore. No student will however be enrolled in more than one semester at any time. In the case of repeaters, the marks secured earlier in the repeated courses will be disregarded.
7. ASSESSMENT AND PASSING REQUIREMENTS
i) Assessment: The assessment will comprise continuous assessment
and final examination, carrying marks as specified in the scheme in section 12. Continuous assessment will be made as per the guidelines framed by the College from time to time. All assessments will be done on absolute marks basis. However, for the purpose of reporting the performance of a student, letter grades and grade points will be awarded as per section 7 (iv).
ii) Final Examinations: Final examinations will normally be conducted during
November / December and during April / May of each year. Supplementary examinations may be conducted at such times as may be decided by the College.
A student will be permitted to appear at the final examination of a
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semester only if he/she has completed the study of that semester satisfying the
requirements given in section 4 and registers simultaneously for the examinations of the highest semester eligible and all the courses which he/she be in arrears of. A student who is not permitted to appear at the final examination of a semester, is not permitted to proceed to the following semester.
A student who is not permitted to appear at the final examination of any semester has to register for and redo the courses of that semester at the next available opportunity.
(iii) Project Work I & II: Every student shall submit reports on Project Work I and
Project Work II on dates announced by the college / department through the faculty guide to the HoD. If a student fails to submit the report on Project Work I or Project Work II on or before the specified date, he/she is deemed to have failed in it.
The student shall present seminars about the progress of the Project Work I
and the Project Work II during the seventh semester and tenth semester respectively. The seminars shall be presented before a review committee constituted by the HoD.
The Project Work I and the Project Work II will be evaluated based on the
seminars, reports and viva-voce examinations. The viva-voce examination will be carried out by a team consisting of an internal examiner, usually the supervisor, and an external examiner, appointed by the Principal. Due weightage will be given to the publications arising out of the Project Work during the evaluation of the Project Work I & II.
A student who fails in a Project Work shall register for redoing the same at the
beginning of a subsequent semester. A student is permitted to register for the Project Work II only after passing the Project Work I.
iv. Letter Grade and Grade Point: Each student, based on his / her
performance, will be awarded a final letter grade and grade point as given in the table infra for each course at the end of each semester by following (a) Relative Grading System for theory courses having Continuous
Assessment and Final Examination components and
(b) Absolute Grading System for all other courses including Laboratory courses, Project and
Courses carrying only Continuous Assessment marks.
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a. Relative Grading System
In relative grading system, the grades are awarded to the students based on their performance relative to the other as detailed below. For each course, the total mark, M [M is equal to Continuous Assessment marks secured (CA) + Final Examination marks secured (FE)] is computed for each student. For each course the statistical parameters mean( ), and
standard deviation( ) of the distribution of marks are arrived as given below,
where n is the total number of students appeared in a course.
n
Mi
n
Mi
n
in
i
2
1
1
The letter grade and the grade point to each student studying a course are awarded based on the statistical parameters, mean, )( and standard
deviation, )( of the distribution of marks as detailed below :
Range of total marks (M) secured (M=CA+ FE)
Grade Grade Point, g
2M S 10
22.1 M A 9
2.14.0 M B 8
4.04.0 M C 7
4.02.1 M D 6
2.1M50,2Min E 5
]50,2[minM or FE less than 50%
of maximum of final examination marks. RA 0
Withdrawal from examination W 0
The examiner and HOD may recommend change of range for any course after due justification.
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b. Absolute Grading System
In absolute grading system, the letter grade and grade points are awarded to each student based on the percentage of marks secured by him/her in Lab courses, Project and courses carrying only continuous assessment marks, as detailed below.
Range of percentage of total marks
Letter Grade
Grade Point g
90 to 100 S 10
80 to 89 A 9
70 to 79 B 8
60 to 69 C 7
55 to 59 D 6
50 to 54 E 5
0 to 49
or less than 50% in final examination
RA 0
Withdrawal W 0
“RA” denotes reappearance/absent “W” denotes withdrawal from the final examination.
(v) Cumulative Grade Point Average: After the completion of the programme,
the Cumulative Grade Point Average (CGPA) from the first semester to final semester is calculated using the formula.
CGPA = i
ii
C
Cg
where gi is Grade point secured corresponding to the course Ci is Credit rating of the course
vi) Passing a course: A student, who is absent for the final examination or
withdraws from final examination or secures a letter grade RA (Grade point 0) in any course carrying continuous assessment and final examination marks, will retain the already earned continuous assessment marks for two subsequent appearances in the examination of that course and
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thereafter he/she will be solely assessed by the final examination carrying the
entire marks of that course.
A student, who scores a letter grade RA (Grade point 0) in any course carrying only continuous assessment marks, will be solely examined by a final examination carrying the entire marks of that course, the continuous assessment marks obtained earlier being disregarded. If a student who has registered for a one credit course does not clear the same successfully, it will be treated as „withdrawal‟ from that course. The one credit courses will be evaluated by the course instructor / department faculty concerned and will carry a total of 100 marks for continuous assessment; out of which 50 marks will be for final test to be scheduled by the course instructor / department faculty concerned.
If a student fails to submit the report on project work on or before the date specified by the college / department, he/she is deemed to have failed in the project work and awarded grade RA. If a student fails to appear for the viva-voce examination after submitting the report on project work on the date specified by the college / department, he/she will be marked as absent for the project work. Such candidates will be allowed to appear for the viva-voce examination at the next earliest opportunity, the project being evaluated at that time.
A student who is absent in the final semester examination of a course after registering for the same will be considered to have appeared and failed in that examination and awarded grade RA.
vii) Supplementary Examinations
For courses under Relative Grading System:
a. Examination in a course conducted exclusively as a supplementary examination
If a student appears in the above supplementary examination, then his / her grade in that course will be on par with the grade allotted for the same score in that course in the immediate preceding regular examination.
b. Examination in a course conducted as a regular examination for a batch of regular students and as a supplementary examination for a batch of other students.
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If a student appears in a supplementary examination, the examination being conducted along with a batch of regular students, then his / her grade in that course will be based on the grade allotted to the same score in that course applicable to the above batch of regular students.
For courses under Absolute Grading System ::
If a student appears in a supplementary examination for the above courses, the grade and grade point will be awarded according to absolute grading system based on the percentage of marks secured in that course.
8. QUALIFYING FOR THE AWARD OF DEGREE
A student will be declared to have qualified for the award of the five year integrated MSc Degree programme provided
i) he/she has successfully completed the course requirements and has passed all the prescribed courses of study of the respective programme listed in section 12 within the duration specified in section 2 and
ii) No disciplinary action is pending against the student.
9. CLASSIFICATION OF DEGREE
i) First Class with Distinction: A student who qualifies for the award of
degree vide section 8 having passed all the courses of all the ten semesters at the first opportunity within ten consecutive semesters after the commencement of his /her study and securing a CGPA of 8.50 and above shall be declared to have passed in First Class with Distinction. For this purpose the withdrawal from examination (vide section 10) will not be construed as an opportunity for appearance in the examination. Further, the authorized break of study (vide section 11) will not be counted for the purpose of classification.
ii) First Class: A student who qualifies for the award of degree vide section 8
having passed all the courses of all the ten semesters within a maximum period of ten consecutive semesters after commencement of his /her study and securing a CGPA of 6.50 and above shall be declared to have passed in First Class. For this purpose, the authorized break of study (vide section
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11) will not be counted for the purpose of classification.
iii) Second Class: All other students who qualify for the award of degree vide
section 8 shall be declared to have passed in Second Class.
10. WITHDRAWAL FROM EXAMINATION
i) A student may, for valid reasons, be granted permission to withdraw from appearing for the examination in any course or courses of one semester examination. Also, only one application for withdrawal is permitted for that semester examination in which withdrawal is sought.
ii) Withdrawal application shall be valid only if the student is otherwise eligible
to write the examination and if it is made prior to the commencement of the semester examination or on the day of the examination of a course / set of courses and also recommended by the HoD and the Principal.
11. TEMPORARY BREAK OF STUDY FROM THE PROGRAMME
i) A student is not normally permitted to temporarily break the study. However, if a student intends to temporarily discontinue the programme in the middle for valid reasons (such as accident or hospitalization due to prolonged ill health) and to rejoin the programme in a later respective semester he/she shall apply to the Principal in advance, in any case, not later than the last working day of the semester in question stating the reasons thereof, through the HoD. A student will be permitted to temporarily break the study only once during the entire duration of the programme. Withdrawal shall not be construed as an opportunity for appearance in the examination for the eligibility of a student for First Class with Distinction.
ii) A student permitted for break of study shall rejoin the programme at the
respective semester as and when it is offered after the break and shall be governed by the rules and regulations in force at the time of rejoining.
iii) The duration specified for passing all the courses for the purpose of
classification of Degree (vide section 9 ) shall be increased by the period of such break of study permitted.
iv) The total period for completion of the programme reckoned from the
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commencement of the semester to which the student was first
admitted shall not exceed the maximum period specified in section 2 irrespective of the period of break of study in order that he/she may be qualified for the award of the degree.
v) If any student is detained for non-completion of study of a semester vide
section 5, the period of such detention shall not be considered as permitted break of study and section 11 (iii) is not applicable for such case.
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12. COURSES OF STUDY AND SCHEME OF ASSESSMENT
M.Sc .Theoretical Computer Science (Total Credits to be earned: 233)
Course
Code
Course Title Hours/Week Credit
Maximum marks
Lecture
Tutorial
Practical
CA
FE Total
SEMESTER 1
THEORY
09XT11
ENGLISH FOR PROFESSIONAL SKILLS
3 0 0 3 50 50 100
09XT12
MATHEMATICAL METHODS – I
3 1 0 4 50 50 100
09XT13
APPLIED PHYSICS 4 0 0 4 50 50 100
09XT14
ANALOG AND DIGITAL ELECTRONICS
4 0 0 4 50 50 100
09XT15
PROBLEM SOLVING AND C PROGRAMMING
3 0 3 5 50 50 100
PRACTICAL
09XT16
APPLIED PHYSICS LAB 0 0 3 2 100
- 100
09XT17
DIGITAL ELECTRONICS LAB
0 0 3 2 100
- 100
09XT18
ENGINEERING DRAWING 2 0 3 4 100
- 100
19 1 12 28 SEMESTER 2
THEORY
09XT21
DISCRETE STRUCTURES 3 2 0 4 50 50 100
12
09XT22
MATHEMATICAL METHODS – II
3 1 0 4 50 50 100
09XT23
ABSTRACT ALGEBRA 3 1 0 4 50 50 100
09XT24
OBJECT ORIENTED PROGRAMMING
4 0 0 4 50 50 100
09XT25
DATA STRUCTURES AND ALGORITHMS
4 0 0 4 50 50 100
PRACTICAL
09XT26
MATHEMATICAL COMPUTING LAB
0 0 3 2 100
- 100
09XT27
OBJECT ORIENTED PROGRAMMING LAB (C++ AND JAVA)
0 0 3 2 100
- 100
09XT28
DATA STRUCTURES LAB 0 0 3 2 100
- 100
17 4 9 26
Course
Code
Course Title Hours/Week Credit
Maximum marks
Lecture
Tutorial
Practical
CA
FE Total
SEMESTER 3
THEORY
09XT31
LINEAR ALGEBRA AND ITS APPLICATIONS
3 1 0 4 50 50 100
09XT32
GRAPH THEORY 3 1 0 4 50 50 100
09XT33
PROBABILITY AND STATISTICS
3 2 0 4 50 50 100
09XT34
ADVANCED DATA STRUCTURES
4 0 0 4 50 50 100
09XT35
COMPUTER ORGANIZATION AND ASSEMBLY LANGUAGE PROGRAMMING
4 0 0 4 50 50 100
PRACTICAL
09XT36
STATISTICAL PACKAGES LAB
0 0 3 2 100
- 100
13
09XT37
ADVANCED DATA STRUCTURES LAB
0 0 3 2 100
- 100
09XT38
ASSEMBLY LANGUAGE PROGRAMMING LAB
1 0 3 3 100
- 100
18 4 9 27
SEMESTER 4
THEORY
09XT41
DATA BASE DESIGN 4 0 0 4 50 50 100
09XT42
DESIGN AND ANALYSIS OF ALGORITHMS
3 0 2 4 50 50 100
09XT43
OPERATING SYSTEMS 4 0 0 4 50 50 100
09XT44
COMPUTER NETWORKS AND TCP/IP
4 0 0 4 50 50 100
09XT45
STOCHASTIC PROCESSES
3 2 0 4 50 50 100
PRACTICAL
09XT46
RDBMS LAB 0 0 3 2 100
- 100
09XT47
OPERATING SYSTEMS LAB
0 0 3 2 100
- 100
09XT48
COMPUTER NETWORKS AND TCP/IP LAB
0 0 3 2 100
- 100
19 2 9 26
CA – Continuous Assessment FE - Final Examination
(Total Credits to be earned: 233)
Course
Code
Course Title Hours/Week Credit
Maximum marks
Lecture
Tutorial
Practical
CA
FE Total
SEMESTER 5
THEORY
14
09XT51
COMPUTATIONAL NUMBER THEORY AND CRYPTOGRAPHY
3 1 0 4 50 50 100
09XT52
COMPUTER GRAPHICS AND ANIMATION
4 0 0 4 50 50 100
09XT53
THEORY OF COMPUTING 4 0 0 4 50 50 100
09XT54
OPTIMIZATION TECHNIQUES
3 1 0 4 50 50 100
09XT55
SOFTWARE ENGINEERING 4 0 0 4 50 50 100
PRACTICAL
09XT56
COMPUTER GRAPHICS AND ANIMATION LAB
0 0 3 2 100
- 100
09XT57
OPTIMIZATION TECHNIQUES LAB
0 0 3 2 100
- 100
09XT58
SOFTWARE ENGINEERING LAB
0 0 3 2 100
- 100
18 2 9 26
SEMESTER 6
THEORY
09XT61
SECURITY IN COMPUTING 4 0 0 4 50 50 100
09XT62
PRINCIPLES OF COMPILER DESIGN
4 0 0 4 50 50 100
09XT63
PRINCIPLES OF PROGRAMMING LANGUAGES
4 0 0 4 50 50 100
09XT64
SOFT COMPUTING 4 0 0 4 50 50 100
09XT65
ELECTIVE – I 3 0 2 4 50 50 100
PRACTICAL
09XT66
SECURITY IN COMPUTING LAB
0 0 3 2 100
- 100
09XT67
PRINCIPLES OF COMPILER DESIGN LAB
0 0 3 2 100
- 100
15
09XT68
SOFT COMPUTING LAB 0 0 3 2 100
- 100
19 0 11 26
Course
Code
Course Title Hours/Week Credit
Maximum marks
Lecture
Tutorial
Practical
CA
FE Total
SEMESTER 7
09XT01
PROJECT WORK I – INDUSTRY / RESEARCH PROJECT
0 0 - 12 50 50 100
SEMESTER 8
THEORY
09XT81
PARALLEL AND DISTRIBUTED COMPUTING
4 0 0 4 50 50 100
09XT82
MATHEMATICAL MODELLING
3 1 0 4 50 50 100
09XT83
DATA MINING 3 0 0 3 50 50 100
09XT84
ELECTIVE – II 3 0 2 4 50 50 100
09XT85
ELECTIVE – III (SELF STUDY)
0 2 2 4 50 50 100
PRACTICAL
09XT86
PARALLEL AND DISTRIBUTED COMPUTING LAB
0 0 3 2 100
- 100
09XT87
MATHEMATICAL MODELLING LAB
0 0 3 2 100
- 100
09XT88
DATA MINING LAB 0 0 3 2 100
- 100
13 3 13 25
SEMESTER 9
THEORY
09XT91
MACHINE LEARNING 3 0 0 3 50 50 100
09XT92
INTELLIGENT INFORMATION RETRIEVAL
3 0 0 3 50 50 100
09XT93
GAME THEORY 3 1 0 4 50 50 100
16
09XT94
ELECTIVE – IV 3 0 2 4 50 50 100
09XT95
ELECTIVE – V (SELF STUDY)
0 2 2 4 50 50 100
PRACTICAL
09XT96
INTELLIGENT INFORMATION RETRIEVAL LAB
0 0 3 2 100
- 100
09XT97
MACHINE LEARNING LAB 0 0 3 2 100
- 100
09XT98
RESEARCH SPECIALIZATION LAB
1 0 3 3 100
- 100
13 3 13 25
SEMESTER 10
09XT02
PROJECT WORK II – RESEARCH AND DEVELOPMENT PROJECT
0 0 - 12 50 50 100
CA – Continuous Assessment FE - Final Examination ELECTIVES 09XTE1 DIGITAL IMAGE PROCSESSING 09XTE2 DATA COMPRESSION 09XTE3 COMPUTATIONAL GEOMENTROY 09XTE4 QUANTUM COMPUTING 09XTE5 WAVELET TRANSFORMS AND APPLICATIONS 09XTE6 ALGORITHMIC BIOINFORMATICS 09XTE7 RANDOMIZED ALGORITHMS 09XTE8 ADVANCED COMPUTER GRAPHICS 09XTE9 MULTI PARADIGM PROGRAMMING LANGUAGES 09XTEA WIRELESS NETWORKS 09XTEB PROGRAM SEMANTIC ANALYSIS 09XTEC NETWORK MANAGEMENT 09XTED SEMANTIC WEB 09XTEE PERVASIVE COMPUTING 09XTEF NETWORK ALGORITHMICS 09XTEG SOFTWARE PATTERNS 09XTEH GRID COMPUTING 09XTEI CLOUD COMPUTING
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SEMESTER - I
18
09XT11 ENGLISH FOR PROFESSIONAL SKILLS 3 0 0 3
READING Reading for deep comprehension – reading for local and global, inferential and critical - Critical reading of literary texts (7) WRITING
Fundamental principles of clear writing – style in formal writing (8) Technical writing – writing reports and technical papers Drafting official letters, email and memos GRAMMAR – Functional Grammar (3) LISTENING
Listening for specific information (6) (Short speeches and News bulletins) SPEAKING
Short presentations and Group discussions (8) SOFT SKILLS Intra and Interpersonal Communication (10) Telephone Etiquette Body Language Interview Techniques
Total 42
Note : Teaching Material prepared by the Faculty, Department of English. REFERENCES 1. Bert Decker, “The Art of Communicating”, Decker Communication Inc., 2004. 2. Meenakshi Raman and Sangeeta Sharma, “Technical Communication: Principles and Practice”, Oxford University press, 2004. 3. Albert Joseph, “Writing Process 2000”, Prentice Hall, 1996. 4. Dale A Level Jr. and William P Galle Jr, “Managerial Communication”, Business Publications Inc., 1988.
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09XT12 MATHEMATICAL METHODS - I 3 1 0 4
BASIC CONCEPTS: Functions – Limit, continuity, piecewise continuity, periodic, differentiable, integrable, absolutely integrable. Fundamental theorem of calculus (statement only). Sequences – increasing, decreasing, bounded, function limit properties (No Proof) - Series – convergence and divergence – alternating series test, absolute convergence – ratio test, power series. (10) FOURIER SERIES: Dirichlet‟s conditions, statement of Fourier theorem, Fourier
coefficients, change of scale, Half-range sine and cosine series, RMS value, Parseval‟s theorem, Applications (9) FUNCTIONS OF TWO VARIABLES: Models, partial derivative and its geometrical
interpretation. Stationary points – maxima, minima and saddles. Taylor series about a point. Constrained maxima and minima – Lagrange multiplier method. (6) MULTIPLE INTEGRALS: Evaluation of multiple integrals - Change of order of
integration - Applications of multiple integrals to find area and volume of solid. (6) BETA AND GAMMA INTEGRALS: Definition - Relation connecting Beta and
Gamma integral - Properties - Evaluation of definite integrals in terms of Beta and Gamma functions. (3) ORDINARY DIFFERENTIAL EQUATIONS: Linear Differential Equations of higher
order with constant coefficients -Euler's equation with variable coefficients - Simultaneous equations - Method of variation of parameters - Linear Equations of the 2nd order : Complete solution given one solution of homogeneous equation - complete solution by removal of first derivative. (8)
Total 42 REFERENCES 1. Erwin Kreyszig, “Advanced Engineering Mathematics”, John Wiley and Sons, 2001. 2. Thomas G B Jr.and Finney R L, “Calculus and Analytic Geometry”, Addison-Wesley, 2000. 3. Lian and Hungerfors, “Mathematics with Applications”, Addison Wesley, 2002. 4. Riley K F, Hobson M P and Bence S J, "Mathematical Methods for Physics and Engineering", Cambridge University Press, 2004. 5. Ray Wyile C and Louis C Barrett “ Advanced Engineering Mathematics”, McGraw Hill, 2001.
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6. Roland E Thomas, Albert J Rosa, “The Analysis and Design of Linear
Circuits”, John Wiley and Sons, 2004 7. Michael D Greenberg, “Advanced Engineering Mathematics”, Pearson Education, 2006. 8. Thomas L Harman, James B Dabney, Norman John Richert, “Advanced Engineering Mathematics with MATLAB”, Brooks/Cole, Thomson Learning, 2000.
09XT13 APPLIED PHYSICS 4 0 0 4
CRYSTALS AND CRYSTALLIRE SOLIDS: Introduction – Close packed structure –
Non - close – packed structure – The crystal lattice – Labelling crystal planes – X-ray diffraction – Electron microscopes – Allotropic phase transition – Changing the crystal. (9) ELECTRICAL PROPERTIES OF METALS: Introduction – Drude‟s classical theory of
Electrical Conduction – failures of the classical model – Block‟s quantum theory of electrical conduction – Band theory of solids – Distribution of the electrons between the eneryx states – The Fermi – Dirac distribution – The density of states – The free electron model – The density of occupied states – Band theory of electrical conduction – Super conductions : Type I and Type II (10) SEMICONDUCTORS: Introduction – Band theory and semiconductors - Holes
optical properties of semiconductors. The effective mass n-type semiconductors, P-type semiconductors – Majority and minority carriers – The Hall effect. The P-n junction with an applied voltage – Transistors – Hetero Junctions – Optoelectronic devices. (10) MAGNETIC PROPERTIES: Introduction – Macroscopic magnetic quantities – Atomic magnets – Magnetic moments of material – Curie Para magnetism. Ordered magnetic materials – Temperature dependence of permanent magnets – Ferromagnetic domains – Soft and hard magnets – Applications of magnetic materials for information storage. Super conducting magnet – SQUID magnetometers. (10) DIELECTRICS : Introduction – Induced polarization – Polarization mechanisms – The frequency dependence of the dielectric constant – Resonant absorption and dipole relaxation – impurities in dielectrics – Pieyo electricity – Ferroelectrics – Dielectric breakdown. (9) FIBER OPTICS: Optical fibers – GRIN and STEP index fibers – Attenuation – Fiber optic communication – Principles of optical recording. (8)
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Total 56
REFERENCES
1. Richard Turton , "The Physics of Solids", Oxford University Press, 2007. 2. William D Callistor ,"Material Science and Engineering", John Wiley and Sons, New York, 2007. 3. Srivastava J P, "Elements of Solid State Physics ", Prentice Hall of India, 2004 4. Robert Resnick and David Halliday, "Fundamentals of Physics", John Wiley and Sons Inc, 2006. 5. Allen Shotwell R , "An Introduction to Fiber Optics", Prentice Hall of India, 2004.
09XT14 ANALOG AND DIGITAL ELECTRONICS 4 0 0 4
SEMICONDUCTOR DEVICES AND CIRCUITS: (Qualitative treatment only)
Fundamental aspects of semiconductors - PN junction diode -Zener diode - Rectifiers - Zener voltage regulators - Filters - Switch-mode power supplies- principle of operation, advantages and disadvantages - Bipolar Junction Transistors - Transistor Amplifiers and inverters - Field Effect Transistor. (7) NUMBER SYSTEM AND CODES: Binary - Octal - Hexadecimal - BCD - excess three - Gray codes - Error correcting and detecting codes. (7) DIGITAL CIRCUITS AND GATES: AND, OR, NOT, NAND and NOR gates - exclusive OR gates. Positive and negative logic systems - Digital integrated circuits-Characteristics - TTL and MOS logic circuits –Comparison. (6) BOOLEAN ALGEBRA AND KARNAUGH MAPS: Boolean relations - Laws and
theorems - Simplifications - Karnaugh maps and simplifications - Don't care conditions - NAND-NAND realizations. (7) COMBINATIONAL LOGIC: Design and Implementation of Half and Full adders -
Subtractors - Parallel adders - Carry look ahead addition - Subtractors - Encoders and decoders - Multiplexers and De-multiplexers. (7) SEQUENTIAL LOGIC: R-S, J-K, D and T type Flip-Flops - Binary counters: Ripple
and synchronous types - UP/DOWN counters - Decade counters - Shift registers - Ring counters. (6) OPERATIONAL AMPLIFIERS: Definition of terms - Inverting and non-inverting
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amplifiers, inverting summing amplifier, integrators and differentiators. (8)
A/D AND D/A CONVERTORS: DACs: weighted and binary ladder types - ADCs: counter, dual slope, successive approximation types. (8)
Total 56
REFERENCES 1. Leach D P “Digital Principles & Applications” 6e, Tata Mcgraw Hill, 2008. 2. Gothamann H, "Digital Electronics: An Introduction to Theory and Practice", Prentice Hall, 2001. 3. Mottershed A, "Electronic devices and circuits", Prentice Hall of India 2008 4. Paul Horowitz and Winfield Hill,The Art of Electronics Second edition, Cambridge University Press, 1989 5. Hamachar V C, Vranesic Z G and Zaky S G, "Computer Organization", McGraw Hill, 2002.
09XT15 PROBLEM SOLVING AND C PROGRAMMING 3 0 3 5
PROBLEM SOLVING: Introduction to Problem Solving- Program development- Analyzing and Defining the Problem- Modular Design – Algorithm - Flow Chart - Programming Language-Types of programming language- Program Development Environment. (3) C LANGUAGE: Introduction to C Language - C character set - Identifiers and
Keywords - Data Types - Constants - Variables - Arrays - Declarations - Expressions - Statements - Symbolic constants - Operators and Expressions - Library Functions - Data Input and Output Functions. (6) CONTROL STATEMENTS: While Statement - Do While Statement – For Loop –
Nested Loop - If Else - Switch - Break - Continue - Comma Operator – Goto Statement - (4) FUNCTIONS: Defining Function - Accessing a Function - Passing Arguments to
Functions - Specifying Arguments Data Types - Function Prototypes - Storage Classes - Auto - Static - Extern and Register Variables. (6) ARRAYS: Defining Array – Processing array - Passing array to a function - Multi dimensional array - Array and strings. (4) POINTERS: Declarations - Pointers to a function - Pointers and one dimensional arrays - Operating a pointer - Pointer and multi dimensional arrays -
23
arrays of pointers - Functions Pointers.
(8) STRUCTURES AND UNIONS: Definition of Structure and Union - Processing a
structure - User defined data types - Structures and pointers - Passing structure to functions - Self referential structures. (5) FILES: File concepts – Operations on Files – Types of Files, Various Read and Write
Functions on Files. (4) Enumerated Data Type – Typedef - Preprocessor Directives - Command Line Arguments. (2)
Total 42 REFERENCES
1. Deitel H M and Deitel P J, “C How to Program”, Prentice Hall, 2006 2. Kernighan B W and Ritchie D M, “C Programming Language (ANSI C)”, Pearson Education, 2004. 3. Gottfried B,” Programming With C”, Mc Graw Hill, 2004 4. Herbert Schildt, “C The Complete Reference", Mc Graw Hill, 2001 5. Michael Schneider G, Steven W, Weingart and David M Perlman, “An Introduction to Programming and Problem Solving with Pascal “, John Wiley and Sons, 1998.
09XT16 APPLIED PHYSICS LAB 0 0 3 2
APPLIED PHYSICS LABORATORY 1. Magnetic Hysteresis 2. Resistivity of an Alloy – Carey Foster‟s Bridge 3. Band Gap of Thermistor – Post Office Box 4. Thermal Conductivity of Metallic Wire – Wiedmann Franz law 5. Temperature co-efficient of Resistance – Post Office Box 6. Efficiency of Solar Cell 7. Band Gap Determination – Reverse Saturation Current 8. Photodiode Characteristics 9. Refractive Index of Glass – Laser 10. Thickness of fibre – Air Wedge
09XT17 DIGITAL ELECTRONICS LAB 0 0 3 2
24
1 Study of basic logic gates and realization of logic gates using universal gates. 2. Multiplexer 3. Demultiplexer 4 Half and full adder / subtractor 5. Encoder and decoder 6. Binary decade counter 7. BCD to seven segment decoder 8. Study of D/A converter 9. Crystal Oscillator using logic gates 10 Four bit shift register
09XT18 ENGINEERING DRAWING 2 0 3 4
INTRODUCTION: Importance of Engineering Drawing – Drawing Instruments and
uses. BIS specifications – Layout of drawing sheets – Lines – Lettering and dimensioning. (7) TYPES OF PROJECTION: Orthographic and Isometric Projections of solids and
their conversion – Perspective Projection – Visual ray and Vanishing point methods. (6) ORTHOGRAPHIC PROJECTION: Principles of Projection and First Angle Projection
– Projection of Points, Straight lines, Planes and solids. (3) SECTION OF SOLIDS: Projection of sectional views with section planes parallel,
perpendicular and inclined to reference planes – True shape of sections. (3) DEVELOPMENT OF SURFACES: Development of Prisms, Pyramids and Solids of
revolution - Development of lateral surface of truncated solids. (3) COMPUTER GRAPHICS: Basic Principles – Computer hardware and graphics
software – Basic principles of interactive computer graphics – Point plotting technique, Line drawing display – Modeling of three dimensional objects – Display of solid objects. (6)
Total 28 REFERENCES
1. Venugopal N., “Engineering Drawing and Graphics”, New Age International, 2002. 2. Gopalakrishnan K. R., “Engineering Drawing”, Vol I and II, Subhas stores, Bangalore 1992.
25
3. Parkinson and Sinha, “First year Engineering Drawing”, Wheeler 1992.
SEMESTER – 2
09XT21 DISCRETE STRUCTURES 3 2 0 4
MATHEMATICAL LOGIC: Proposition - Logical operators - Truth tables – Laws of
Logic – equivalences – Rules of inference - Validity of arguments – consistency of specifications – Propositional Calculus – Quantifiers and universe of discourse. (9) PROOF TECHNIQUES: Introduction – Methods of proving theorems – Direct proofs, Proof by contraposition, vacuous and trivial proofs, proofs by contradiction – Mistakes in proofs – Mathematical induction – strong mathematical induction and well ordering - Program correctness. (7) RELATIONS AND FUNCTIONS: Definition and properties of Binary Relations – Representing Relations – Closures of Relations – Composition of Relations – Equivalence Relations – Partitions and Covering of Sets – Partial Orderings – n – Ary Relations and their Applications. Functions-Injective, Surjective, Bijective functions, Composition, identity and inverse. (7) COMBINATORICS: Basics of counting – The Pigeonhole principle - Permutations and Combinations with and without repetition, Permutations with indistinguishable elements, distribution of objects - Generating permutations and combinations in Lexographic order. (8) RECURRENCE RELATIONS: Some Recurrence Relation Models, Solutions of recurrence relations by substitution and generating functions, the method of characteristic roots, solution of non homogeneous finite order linear recurrence relations- Divide and conquer recurrence relations, Masters theorem. (7) LATTICES: Lattices as partially ordered set – Properties of Lattices – Lattices as algebraic system – Sublattices – Direct product and Homomorphism
26
– Some special lattices. (4)
Total 42 REFERENCES
1. Kenneth H Rosen, “Discrete Mathematics and its Application”, Tata Mc Graw Hill, 2007.
2. Judith L. Gersting, “Mathematical Structures for Computer Science”, W.H. Freeman and Company, 2006.
3. Tremblay J P and Manohar R, “Discrete Mathematical structures with application to Computer Science”, Tata Mc Graw Hill, 2002.
4. Doerr Alan and Levasseur Kenneth, "Applied Discrete Structures for Computer Science", Galgotia Publications, 2001.
5. Benard Kolman, Robert C Busby and Sharan Ross, "Discrete Mathematical Structures", Pearson Education, 2008.
6. Ralph P Grimaldi, “ Discrete and Combinatorial Mathematics – An Applied Introduction”, Addison Wesley, 2003
09XT22 MATHEMATICAL METHODS – II
3 1 0 4 TRANSFORM METHODS : Concept of Transformation - Examples for Transformations. (2) LAPLACE TRANSFORM : Definition - Transforms of Standard Functions -
Transform of unit step function - Dirac delta function. – Transforms of derivatives and integrals -Transforms of Periodic functions - Inverse Laplace transform- Convolution Theorem . Method of solving ordinary linear differential equations with constant coefficient by Laplace transform technique. Some applications to engineering problems. (8) FOURIER TRANSFORMS : Fourier integrals - Fourier transform- Finite and infinite
Fourier sine and cosine transform - Transforms of standard functions - Properties, Convolution theorem ( Statement only) – Discrete Fourier and Fast Fourier Transforms – Discrete Convolution – Periodic sequence and circular convolution – Discrete Fourier Transform – decimation–in-time algorithm – Decimation-in-frequency algorithm – Computation of inverse DFT (8) COMPLEX VARIABLES : Analytic functions - Cauchy - Riemann equations in Cartesian and Polar- Coordinates - Statement of sufficient conditions- Properties of Analytic Functions - Finding analytic function whose real/ imaginary part is given- conformal mapping, Bilinear map - Complex integration - Cauchy 's fundamental theorem and formula - Taylor's series-Laurent's series (Statement only) - Singularities - Residue theorem- Cauchy's lemma and Jordan's lemma (Statement only)- Evaluation of real integrals using contour integration along semi circle and unit circle. (14)
27
BOUNDARY VALUE PROBLEMS : Solution of Partial differential equation by the
method of separation of variable. One dimensional wave equation, one dimensional heat equation, two dimensional heat equation, Laplace equation of two dimensions (Cartesian). Solution of above boundary value problems by Fourier series technique ( Governing equations may be assumed.) (10)
Total 42
REFERENCES
1. Riley K F, Hobson M P and Bence S J, " Mathematical Methods for Physics and
Engineering," Cambridge University, 2004. 2. Ray Wyile C and Louis C Barrett, " Advanced Engineering Mathematics", Mc
Graw Hill, 2001. 3. Erwin Kreyszig, " Advanced Engineering Mathematics '', John Wiley and Sons,
2001 4. Eginhard J Muth , " Transform Methods with Applications to Engineering",
Prentice Hall 1977.
09XT23 ABSTRACT ALGEBRA 3 1 0
4 ALGEBRAIC STRUCTURE: Groups - Definition and Example, Properties of Groups, Permutation Groups, Symmetric Groups, Cyclic Groups. (5)
SUBGROUPS AND NORMAL SUBGROUPS: Subgroups – Definition, Cosets and Lagrange‟s theorem, Homomorphism – Isomorphism – Cayley‟s theorem – Normal subgroups – Factor group – Fundamental theorem of group homomorphism. Direct Products - Definition and Examples, Properties, Group of units modulo n as an external direct product – Applications. (10) GROUPS AND CODING: Coding of Binary information and Error detection – Group codes – Decoding and Error correction.
(4)
RINGS: Definition and Properties – Integral domain - Homomorphism – Ideals and
Factor Rings – Polynomials Rings – Factorisation of Polynomials – Reducibility tests, irreducibility tests, Unique factorization in Z [x]. Divisibility in Integral domain –irreducible primes. Euclidean domain – Division Algorithm – Unique factorization domain. (12)
FIELDS: Definition – Extension fields, Algebraic extension – splitting field.
28
Finite fields – Classification of Finite fields , Structure of Finite fields, Subfields of
a finite field. Geometric constructions – Constructible numbers, angle – trisectors and circle and squares. (11)
Total 42
REFERENCES
1. Joseph A Gallian, “ Contemporary Abstract Algebra”, Houghton Mifflin, 2002. 2. Herstein I N, “Topics in Algebra”, John Wiley and Sons, 2001. 3. Benard Kolman, Robert C Busy and Sharan Ross, “Discrete Mathematical Structures”, Pearson Education, 2001.
4. Trembley J P and Manohar R, “Discrete Mathematical Structures with Application to Computer Science,” Tata McGraw Hill, 1997.
09XT24 OBJECT ORIENTED PROGRAMMING
4 0 0 4
PRINCIPLES OF OBJECT ORIENTED PROGRAMMING: Software crisis Software
Evolution - Procedure Oriented Programming - Object Oriented Programming paradigm - Basic concepts and benefits of OOP - Object Oriented Language - Application of OOP - Structure of C++ - Applications of C++ - Tokens, Expressions and Control Structures - Operators in C++ - Manipulators. (10) FUNCTIONS IN C++ Function Prototyping - Call by Reference - Return by reference - Inline functions - Default, Const Arguments - Function - Overloading - Friend and Virtual Functions - Classes and Objects - Member functions - Nesting of Member functions - Private member functions - Memory allocation for Objects - Static data members - Static Member Functions - Arrays of Objects - Objects as Function - Arguments - Friendly Functions - Returning Objects - Const Member functions - Pointers to Members. (10) CONSTRUCTORS: Parameterized Constructors - Multiple Constructors in a Class
- Constructors with Default Arguments - Dynamic Initialization of Objects - Copy and Dynamic Constructors – Destructors overloading - Overloading Unary and Binary Operators - Overloading Binary Operators using Friend functions. (10) INHERITANCE: Defining Derived Classes - Single Inheritance - Making a Private
Member Inheritable - Multiple Inheritance - Hierarchical Inheritance - Hybrid Inheritance - Virtual Base Classes - Abstract Classes - Constructors in Derived Classes – Dynamic Polymorphism - Member Classes - Nesting of Classes. (10)
29
STREAMS: String I/O -Character I/O - Object I/O - I/O with multiple Objects - File
pointers - Disk I/O with member functions - Exception handling - Templates – Software Object Templates . (8) COMPARISON OF JAVA WITH C++ : Structure of programs – Data Types –
Access specifies – Arrays – Polymorphism – Inheritance - Windows programming – Multithread programming. (8)
Total 56
REFERENCES 1. Bjarne Stroustrup, “The C++ Programming Language”, Addison Wesley, 2004. 2. Stanley B Lippman and Josee Lajoie, “The C++ Primer”, Addison Wesley, 2005. 3. Harvey M. Deitel,and Paul J. Deitel, “C++ How to Program”, Prentice Hall, 2007. 4. Patrick Naughton and Herbert Schilbert, “Java 2 Complete Reference“, Tata Mc Graw Hill, 2003.
09XT25 DATA STRUCTURES AND ALGORITHMS
4 0 0 4 INTRODUCTION: Software Development process – Abstraction - Data structures - Abstract Data Types - Primitive data structures - Analysis of algorithms - Best, worst and average case time complexities - notations. (6) ARRAYS: Operations - Implementation of one, two, three and multi dimensioned arrays – Sparse and dense matrices - Applications. (4) STRINGS: Implementation - operations - String applications. SETS: Operations on sets - implementation of sets. (5) STRUCTURES AND UNIONS: Implementation – operations – Applications (3) STACKS: Primitive operations - Sequential implementation - Applications:
Subroutine handling - Recursion – Expression Processing. (5) QUEUES: Primitive operations - sequential implementation - Priority Queues -
Dequeues - Applications: Image component labeling; Machine shop simulation. (6) LISTS: Primitive Operations - Singly linked lists, Doubly linked lists, Circular lists, Multiply linked lists - Applications: Addition of Polynomials; Sparse
30
Matrix representation and Operations. – Linked Stacks - Linked queues -
Linked Priority queues - Dynamic Storage Management. (12) TREES: Terminologies - Implementation - BINARY TREE: Properties - Sequential and linked representation - Common binary tree operations - Traversals - Expression trees - Infix, Postfix and Prefix expressions - Threaded trees - Tournament trees - Heaps, Max heap, Min heap - Applications: Huffman codes; Placement of signal boosters. (8) TABLE: Introduction – Operations – Implementation. (3) HASHING: Hash function – Separate chaining – Open addressing – Linear probing –
Quadratic probing – Double hashing - rehashing. (4)
Total 56 REFERENCES 1. Mark Allen Weiss , “ Data Structures and Algorithm Analysis in C++”, Addison-Wesley, 2006. 2. Nell Dale, “C++ Plus Data Structures”, Jones and Bartlett , 2006. 3. Aaron M Tanenbaum, Moshe J Augenstein and Yedidyah Langsam, "Data structures using C and C++", Prentice Hall of India , 2005. 4. Sahni Sartaj, "Data Structures, Algorithms and Applications in C++", University Press, 2005. 5. Robert L Kruse and Clovis L Tondo, “ Data Structures and Program design in C”, Pearson Education, 2005. 6. Angela B Shiflet, “Elementary Data Structures with Pascal”, West Publishing company, 1990.
09XT26 MATHEMATICAL COMPUTING LAB
0 0 3 2 1. Programs on differentiation and integration.
2. Finding Fourier series
3. Solving ordinary differential equations using Laplace transform techniques.
4. Solving boundary value problems using Fourier series techniques.
5. Conformal mappings of standard functions.
31
09XT27 OBJECT ORIENTED PROGRAMMING LAB (C++ AND JAVA) 0 0 3 2
1. Arithmetic operations using array of objects and dynamic data members. 2. Creation of a class having read-only member function and processing the objects
of that class. 3. Creation of a class which keeps track of the member of its instances. Usage of
static data member, constructor and destructor to maintain updated information about active objects.
4. Illustration of a data structure using dynamic objects. 5. Usage of static member to count the number of instances of a class. 6. Illustration for the need of default arguments. 7. Usage of a function to perform the same operation on more than one data type. 8. Creation of a class with generic data member. 9. Overloading the operators to do arithmetic operations on objects. 10. Acquisition of the features of an existing class and creation of a new class with
added features in it. 11. Implementation of run time polymorphism. 12. Overloading stream operators and creation of user manipulators. 13. Designing a function to alarm, when an error occurs. 14. Implementation of derived class which has direct access to both its own members
and the public members of the base class. 15. Implementation of Streams to store and maintain Library system, with the features
of Book Issue and Book Return. 16. Implementation of console application for getting inputs from keyboard. 17. Conversion checking from one data type to another data type. 18. Implementation of Notepad with all basic features of Text Editor. 19. Implementation of delayed threads. 20. Checking the different alignments of various Layouts.
09XT28 DATA STRUCTURES LAB
0 0 3 2 Implementation of the following problems: 1. Sparse and dense Matrix operations using arrays 2. Library of string operations - representing strings using arrays 3. Set operations 4. Stacks using array representation 5. Queues using array representation 6. Linked Lists: Singly linked, Doubly linked and Circular lists 7. Linked Stacks and Queues 8. Conversion and Manipulation of Expressions 9. Binary trees and Threaded trees (with graphical representation) 10. Conversion of infix expression to postfix expression and evaluation 11. Implementation and analysis of Table 12. Hash Table linear probing and chaining
SEMESTER – 3
32
09XT31 LINEAR ALGEBRA AND ITS APPLICATIONS 3 1 0 4 SYSTEM OF LINEAR EQUATIONS: System of linear equations – Row reduction
and Echelon forms – Vector equation – Matrix equation Ax=b. (4) VECTOR SPACES: Vector spaces and subspaces – Linear combination, Span,
Linear independence and dependence - Null space, Column space, and Row space – Basis and dimension of a vector space – Rank and nullity. (10)
LINEAR TRANSFORMATION: Introduction to linear transformations – Linear
Transformations from Rn to Rm – General Linear Transformations – Kernel and range – Inverse Linear Transformations – Matrices of General Linear Transformations – Change of basis – Similarity – Isomorphism. (6)
INNER PRODUCT SAPCES: Inner product, Length, and orthogonality – Orthogonal
sets – Orthogonal projections – Inner product spaces – Orthonormal bases:Gram-Schmidt process – Best Approximation, Least-squares. (8) EIGEN VALUES, EIGEN VECTORS AND SINGULAR VALUE DECOMPOSITION:
Eigen values and eigen vectors– Eigen vectors and linear transformations – Complex eigen values – Diagonalization – Diagonalization of symmetric matrices – Singular value decomposition. (6) APPLICATIONS OF LINEAR ALGEBRA: Linear models in business, science and
engineering – Markov chains – Graph theory – Computer Graphics – Fractals – Chaos – Cryptography – Warps and Morphs – Image processing. (8)
Total 42
REFERENCES
1. Howard Anton, “Elementary Linear Algebra”, John Wiley, 2005. 2. David C Lay, “ Linear Algebra And Its Applications”, Addison Wesley, 2006. 3. Gilbert Strang, “Linear Algebra And Its Applications”, Brooks/Cole, 2005. 4. Kenneth Hardy, “Linear Algebra For Engineers And Scientists Using Matlab”,
Prentice Hall, 2005. 5. Otto Bretscher, „Linear Algebra with Applications”, Pearson Education, 2005. 6. George Nakos and David Joyner, “Linear Algebra With Applications”,
Brooks/Cole, 1998.
33
09XT32 GRAPH THEORY 3 1 0 4
BASIC CONCEPTS: Graphs - directed and undirected, subgraphs, graph models, degree of a vertex, degree sequence, Havel-Hakimi theorem, Hand-shaking lemma. Connectivity, walk, path, distance, diameter. Isomorphic graphs. Common classes of graphs – regular, complete, petersen, cycle, path, tree, k-partite, planar, hypercube, mesh. Spanning trees – Vertex and edge cuts, Matrix tree theorem, Kruskal‟s – Visibility graphs. (4) CONNECTIVITY: Vertex and edge connectivity, relationship between vertex and
edge connectivity, bounds for connectivity. Harary‟s construction of k-connected graphs. (8) EULERIAN AND HAMILTONIAN GRAPHS: Eulerian graphs, chinese postman
problem, Hamiltonian graphs, Dirac‟s and Ore‟s theorems, Gray codes. (6) MATCHING, VERTEX-COLORING AND DOMINATION: Matching, Perfect
matching, Bipartite matching, Hall‟s theorem. Vertex-coloring – upper chromatic number, bounds using clique number, (G), Welsh – Powell theorem. Dominating set, domination number, bounds, Applications of the above concepts. (12) RANDOM GRAPHS: Random graph – Definitions of G(n, p) and G(n, M) models.
Ramsey number – definition, Erdos theorem. n-existentially closed graphs, asymptotically almost surely graphs and their existence theorem. Expectation and the first moment method, variance and second moment method, threshold function. Web graph models. (12) Total
42 REFERENCES
1. Anthony Bonato, “A Course on Web Graphs”, American Mathematical Society, 2008. 2. Douglas B West, “Graph Theory”, Prentice Hall, 1999. 3. Haynes T W, Hedetniemi and Slater P J, “Fundamentals of Domination in Graphs”, Marcel Dekker, 1998. 4. Jonathan Gross and Jay Yellen, “Graph Theory and its Applications”, CRC Press, 1998. 5. Bela Bollobas, “Random Graphs“, Cambridge University Press, 2001.
09XT33 PROBABILITY AND STATISTICS
3 2 0 4
PROBABILITY AND CONCEPT OF RANDOM VARIABLE : Axiomatic
34
approach to probability, addition and multiplication laws of probability,
Conditional probability, Baye‟s theorem. Discrete and continuous random variables - Probability distributions, joint probability distributions, marginal and conditional density functions, statistical independence, mathematical expectation. (10)
PROBABILITY DISTRIBUTIONS AND APPLICATIONS: Discrete distributions – Binomial, Poisson and Geometric distribution. Continuous distributions – Uniform, Normal, Exponential and Weibull distributions, moment generating functions, mean and variance. Limit Theorems: Markov‟s Inequality, Chebyshev‟s Inequality, Strong Law of Large Numbers, Central Limit Theorem. ` (7) CORRELATION AND REGRESSION: Simple linear correlation and regression, multiple regression analysis, multiple and partial Correlation Coefficients. (5) THEORY OF ESTIMATION: Point estimation – Properties of estimation. Interval estimation – Estimates of mean, standard deviation and properties. (6) TESTS OF HYPOTHESES : Level of significance, type I and type II errors. Large sample tests - Tests for mean, standard deviation, proportions. Small sample tests - Tests based on t, F and Chi-square distributions. (6)
ANALYSIS OF VARIANCE : Introduction to design of experiments, Analysis of variance - CRD and RBD models. (4) STATISTICAL QUALITY CONTROL: Statistical basis for control charts, control
limits. Control charts for variables - ,X R charts. Charts for defectives – p and np
charts. Charts for defects – C chart. (4)
Total 42
REFERENCES 1. Trivedi K S, “Probability and Statistics with Reliability, Queuing and Computer Science Applications”, John Wiley, 2003. 2. Richard Johnson, Irwin Miller and John Fruend, “Miller and Freund‟s Probability and Statistics for Engineers”, Prentice Hall, 2004. 3. Medhi J, " Stochastic Processes", New Age International Publishers , 2004. 4. Douglas C Montgomery and George C Runger, “ Applied Statistics and Probability for Engineers”, John Wiley and Sons, 2002 . 5. Roy D.Yates, David J.Goodman, “Probability and Stochastic Processes – a friendly Introduction for Electrical and Computer Engineers”, John Wiley and Sons, Inc.2004.
35
6. Jay L Devore, “Probability and Statistics for Engineering and the Sciences”,
Thomson Asia, 2002. 7. Sheldon M Ross, “Introduction to Probability Models”, Academic Press, 2003. 8. Kai Lai Chung, Farid AitSahlia, “Elementary Probability Theory”, Springer Verlag, 2004.
09XT34 ADVANCED DATA STRUCTURES
4 0 0 4
INTRODUCTION: Algorithms – analysis of algorithms – best case and worst case
complexities, analysis of some algorithms using simple data structures, Amortized time complexity. ̀ (6) SORTING: Insertion sort, selection sort, shell sort, bubble sort, heap sort, recursive
quick sort and merge sort, radix sort – Algorithms and their time complexity. (6) SEARCHING: Linear Search, Binary search.
(2)
BINARY SEARCH TREES : Searching – Insertion and deletion of elements – Analysis. (3)
AVL TREES : Definition – Height – Searching – insertion and deletion of elements, AVL rotations – Analysis. (5) RED BLACK TREES : Definition – Searching – insertion and deletion of elements –
algorithms and their time complexities. (5) AUGMENTING DATA STRUCTURE: Dynamic order statistics, how to augment a data structure, interval trees (4) SPLAY TREES : Definition – Steps in Splaying and Amortized analysis.
(3) k-d TREES: Definition – Searching – Insertion – Deletion and analysis (4) MULTIWAY SEARCH TREES: Indexed Sequential Access – m-way search trees –
B-Tree – Searching, insertion and deletion - B+ trees - Tries. (5) BINOMIAL HEAP AND FIBONACCI HEAP: Binomial trees and binomial heaps –
Operations on binomial heap – Structure of Fibonacci heaps – merge heap operations, decreasing a key and deleting a node – Bounding the maximum degree. (5) DATA STRUCTURES FOR DISJOINT SETS: Disjoint set
36
operations, linked list representation of disjoint set, disjoint set forests, union,
find, analysis. (4) GRAPHS: Definition – Representations (Adjacency matrix, packed adjacency list
and linked adjacency list) – Network representation – Graph search methods (Breadth first and depth first traversals). (4)
Total 56
REFERENCES
1. Thomas H Cormen, Charles E Leiserson and Ronald L Rivest “Introduction to Algorithms” , Prentice Hall, 2005.
2. Mark Allen Weiss , “ Data Structures and Algorithm Analysis in C++”, Addison-Wesley, 2006.
3. Sahni Sartaj, "Data Structures, Algorithms and Applications in C++", Universities Press, 2005.
4. Robert L Kruse and Clovis L Tondo, “ Data Structures and Program design in C”, Pearson Education, 2005. 5. Adam Drozdek, “ Data Structures and Algorithms in C++”, Vikas Publishing House, 2002.
09XT35 COMPUTER ORGANIZATION AND ASSEMBLY LANGUAGE
PROGRAMMING 4 0 0 4
DATA REPRESENTATION : Data types - Fixed point and floating point number
representation (IEEE format) - Representation of signed numbers – arithmetic operation on signed numbers - Alphanumeric data representation. (6) REGISTER TRANSFER AND MICRO OPERATIONS: Register transfer language - Inter register transfer - Arithmetic micro operations - Logic micro operations - Shift micro operations - Control functions. (3) BASIC COMPUTER ORGANIZATION AND DESIGN: Instruction codes- Computer
registers - Computer Instructions - Timing and Control - Instruction Cycle - Memory Reference Instructions - Input - Output and Interrupts – Complete Computer Description - Design of Basic Computer - Design of Accumulator Logic. (8)
37
CENTRAL PROCESSING UNIT: Processor Bus organization - Stack
organization - Instruction formats - Data transfer and manipulation - RISC and CISC machine characteristics – Introduction to Hardwired and micro programmed control – Processor Performance Measurement - Multiprocessor Organisation – RISC and CISC characteristics. (6) MEMORY AND INPUT-OUTPUT UNITS: Memory hierarchy - Main memory: RAM
and ROM address spaces - Associative memory - Cache memory – Cache Hit rate and Miss Penalty – Memory Interleaving. (6) PERIPHERAL DEVICES: I/O interface - I/O bus versus memory bus - Isolated
versus memory - Mapped I/O - Example of I/O interface – DMA - Input-Output processor. (5) INTRODUCTION TO MICROPROCESSORS: Evolution of Micro processors - Micro
processor based systems– Instruction Level Parallelism. (5) INTEL 8086/88 PROCESSOR: Functional units of 8086 – Pipelining in 8086 -
Addressing modes – Instruction format - Instructions - assembler directives – Construction of Machine code –Data Transfer and Data Manipulation Instructions. (8) ASSEMBLY LANGUAGE PROGRAMMING: Programs for multi precision addition, subtraction - Block moves - Array processing - String processing - Procedures and macros - ISR. (9)
Total 56 REFERENCES 1. Morris Mano, "Computer Systems Architecture", Pearson Education, 2002. 2. Hamachar V C, Vranesic Z G and Zaky S G, "Computer Organization", McGraw Hill, 2002. 3. John P Hayes, “ Computer Architecture and Organization”, Tata McGraw Hill, 1998 4. Douglus V Hall, "Microprocessors and Interfacing", McGraw Hill, 2002. 5. Barry B Brey, "The Intel Microprocessors - 8086/88, and 80186,80286,80386, and 80486", Pearson Education, 2006. 6. James L Antonakos, “An Introduction to the Intel family of Microprocessors”, Pearson Education, 1999.
09XT36 STATISTICAL PACKAGES LAB 0 0 3
2
1. Implementation of classification and tabulation of data. 2. Graphical and diagrammatic presentation of data.
38
3. Perform calculations that measure the central tendency and dispersion of
data. 4. Implementation of measures of Skewness, moments and kurtosis. 5. Determination of point and interval estimates. 6. Solving linear regression, polynomial regression and non-linear regression
based problems. 7. Solving multiple regression and correlation analysis based problems. 8. Solving the problems based on Time series analysis and forecasting. 9. Implementing statistical quality control charts. 10. Evaluation of polynomial coefficients for interpolation. 11. Perform an interpolation with newton‟s polynomial and lagrange polynomial. 12. Solving unconstrained and constrained optimization problems.
Implement using mathematical packages like SPSS, MATLAB, MATHEMATICA or MAPLE.
09XT37 ADVANCED DATA STRUCTURES LAB 0 0 3 2
Implementation of the following problems: 1. Sorting algorithms 2. Searching 3. Binary search tree and its operations (with Graphical display) 4. AVL tree including all rotations 5. Implementation of k-d trees 6. B-tree and its operations 7. Disjoint set operations 8. Problem using binomial heap and fibonacci heap 9. Graphs and graph traversals
09XT38 ASSEMBLY LANGUAGE PROGRAMMING LAB
1 0 3 3 1. Implement the functionality of AND, OR and Not gates. 2. Convert the given number with one parameter moils number to any other radices form 3. Implement addition and subtraction of binary numbers using both one‟s complement and two‟s complement arithmetic. 4. Implement parity bit generation for a n-bit binary data. 5. Implement Multiplication and division of binary number using repeated addition and division respectively. 6. Sort the Nibbles of the given integer.
39
7. Conversion of BCD numbers into ASCII characters and vice versa.
8. Multiprecision addition and subtraction. 9. Packing and unpacking of BCD digits. 10. Multiplication of signed operands using BOOTH Algorithm. 11. Arrangement of numbers in ascending and descending order. 12. Study of INT 21H functions for input and output. 13. Delay loop implementation. 14. Checking whether a given character string is a PALINDROME 15. Implementation of LEFT (), RIGHT (), SUBSTR () functions 16. Usage of MACROS - 17. BCD to Binary conversion and vice versa. 18. To check whether a given string is a substring of another. 19. To display the contents of the given memory locations. 20. Encryption and decryption of a message.
SEMESTER – 4
09XT41 DATABASE DESIGN
4 0 0 4 BASIC CONCEPTS : Introduction to databases – Conventional file Processing – Data Modeling for a database – Three level architecture – Data Independence – Components of a Database Management System (DBMS) – Advantages and disadvantages of a DBMS – System Environment – users of DBMS. (8) DATA MODELS : Introduction – Data Associations – entities, attributes, relationships – Entity relationship data models (ERD) – Generalization – Aggregation – Conversion of ERD into tables – applications – Introduction to Network data model and Hierarchical data model. (9) FILE ORGANIZATION : Storage device Characteristics – constituents of a file – Operations on file - Serial files – Sequential files – Index Sequential files – Direct files – Binary and Secondary key retrieval – Indexing using Tree structures. (9) RELATIONAL MODEL : Introduction – Relational databases – Relational Algebra –
Relational algebra queries – Relational calculus : Tuple Relational calculus, Domain relational calculus – Queries in Relational calculus. (9) RELATIONAL DATABASE MANIPULATION: Structured Query Language (SQL) - Basic data retrieval – Condition specification - SQL Join – views and update. (6) DATA BASE DESIGN THEORY: Functional dependencies – axioms – Normal forms based on primary keys – Second Normal form Third Normal form,
40
Boyce – Codd Normal form – examples.
Multivalued dependencies – Fourth Normal form – Data base design process – Database Tuning. (10) DATABASE SECURITY , INTEGRITY AND CONTROL: Security and Integrity threats – Defense mechanisms-Transaction and concurrency control mechanisms. (5)
Total 56
REFERENCES 1. Bipin C.Desai, “An Introduction to Database System „‟, Galgotia Publisher, 2004. 2. Silberschatz A., Korth H and Sudarshan S., “Database System Concepts”, McGraw Hill Inc., 2002. 3. Elmasri R and Navathe S.B, “Fundamentals of Database Systems”, Pearson Education, 2002. 4. Raghu Ramakrishnan and Johannes Gehrke, “Database Management System”, McGraw Hill Inc., 2003.
09XT42 DESIGN AND ANALYSIS OF ALGORITHMS 3 0 2 4
INTRODUCTION: Fundamentals of algorithmic problem solving, deciding an
appropriate data structure and algorithm design technique – Methods of specifying an algorithm – providing correctness of an algorithm – analyzing an algorithm. (3) DIVIDE AND CONQUER: Integer multiplication – Strassen‟s matrix multiplication –
closest pair – convex hull. (4) GREEDY METHOD: Optimization problems – minimum cost spanning tree. (Kruskal and Prim‟s algorithms) – topological sorting – knapsack problem – Huffman trees (6) DYNAMIC PROGRAMMING: Method – Floyd‟s algorithm for all pair shortest path problem – 0/1 knapsack problem – optimal binary search trees. (5) BACKTRACKING: Method – solution space and tree organization – 8 queen‟s problem – Hamiltonian circuit graph coloring. (6) BRANCH AND BOUND: Method – Assignment problem – Traveling salesman
problem. (5)
41
FLOW NETWORK: Flow networks and Flows – Example – Network with
multiple sources and working with flows – The Ford – Fulkerson method – Augumenting paths – Max – Flow min – cut theorem – The Edmonds – Karp algorithm. (5) NP HARD AND NP COMPLETE CLASSES: Basic concepts – Satisfiability problem
– NP hard and NP complete problems – Cooks theorem (informal proof) (4) APPROXIMATION ALGORITHM: Introduction – 0/1 knapsack – traveling salesman
problem. (4)
Total 42
REFERENCES
1. Jon Kleinberg and Eve Tardos “ Algorithm Design”, Pearson Education, 2005. 2. Thomas H Cormen, Charles E Leiserson, and Ronald L Rivest “Introduction to Algorithms” , Prentice Hall, 2005. 3. Anany Levitin, “ Introduction to design and analysis of algorithm”, Addison -Wesley, 2006 4. Sara Baase and Allen Van Gelder “ Computer Algorithms -- Introduction to Design and Analysis”,. Addison-Wesley, 2000. 5. Michael T Goodrich, Roberto Tamassia, “ Algorithm Design”, John Wiley and sons, 2002. 6. Ellis Horowitz, Sartaj Sahni and Sanguthevar Rajasekaran, “ Fundamentals of Computer Algorithms” University press 2008.
09XT43 OPERATING SYSTEMS
4 0 0 4 INTRODUCTION: Operating Systems Objectives and Functions – Evolution of
Operating Systems – Structure of Operating System – Components of Computers. (5) MEMORY MANAGEMENT: Memory hierarchy – Linking and Loading the process – Memory Management requirement. (3) MEMORY ORGANIZATION: Fixed partitioning - Dynamic partitioning – Buddy
Systems – Simple paging – Multilevel paging – Inverted paging – Simple Segmentation – Segmentation and paging. (5) VIRTUAL MEMORY MANAGEMENT: Need for Virtual Memory management –
Demand Paging - Page Fault Routine – Demand Segmentation – Combined demand
42
segmentation and paging - Operating systems policies.
(6) PROCESS DESCRIPTION AND CONTROL: Process Creation - Process states –
Process Description – Process Control. (5) PROCESS AND THREADS: Relationship between process and threads – Thread State – Thread Synchronization – Types of Thread. (2) PROCESS SYNCHRONIZATION: Concurrent Process – Principles of Concurrency – Mutual Exclusion – Software support – Hardware Support – Operating System Support - Deadlock - Deadlock Prevention, Avoidance and Detection and recovery. (5) PROCESS SCHEDULING: Types of Scheduling – Scheduling Criteria – Scheduling Algorithms. (4) I/O MANAGEMENT AND DISK SCHEDULING: Organization of I/O function –
Evolution of I/O function – Types of I/O devices – Logical Structure of I/O functions – I/O Buffering – Disk I/O – Disk Scheduling algorithms – Disk Cache. (6) FILE MANAGEMENT: Files – File management Systems – File System Architecture – Functions of File Management – File Directories – Secondary Storage Management – File Allocation. (7) UNIX: Basic Unix Commands – File and Directory commands – Filters – IO Redirections - Introduction to shell scripts – Variables – Command Line arguments – Decision and Repetitive commands. (8)
Total 56 REFERENCES
1. William Stallings, “Operating Systems”, Prentice-Hall, 2004. 2. Silberschatz. A, Galvin. P and Gagne.G, “Operating System Concepts” John Wiley and Sons, 2002. 3. Charles Crowely, “Operating System a Design Oriented Approach”, Tata McGraw Hill, 2000. 4. D. M. Dhamdhere, “Operating Systems- A Concept based Approach”, Tata McGraw Hill, 2003. 5. Sumithabha Das, “Unix System V.4 – Concepts and Applications”, Tata McGraw Hill, 2004
43
09XT44 COMPUTER NETWORKS AND TCP/IP
4 0 0 4
INTRODUCTION: Network goals - Applications of Networks - Design issues for the
layers - OSI Reference Model - Types of Network - Network Topologies (4) DATA ENCODING: Digital-to-Digital Encoding, Analog-to-Digital Encoding - Digital-
to-Analog Encoding, ASK, FSK, PSK, QAM - Bit Rate, Baud Rate.- Sampling Rate (6) TRANSMISSION OF DIGITAL DATA: Transmission Impairments - Single and
Multiple bit error correction-Error Detection and Correction - Cyclic Redundancy Check Code -.Hamming Code (4) DATA COMMUNICATION: Multiplexing - Synchronous and Asynchronous TDM – FDM –CDM - Switching, Circuit Switching, Packet Switching (4) DATA LINK CONTROL AND PROTOCOLS: Line Discipline - Flow Control - Sliding Window Protocol - Error Control - Automatic Repeat Request – Stop – and - wait ARQ. Go – back – by - n ARQ, Selective Reject ARQ,- Bit-oriented Protocols – HDLC,PPP.. (6) LOCAL AREA NETWORKS: Random Access protocols- Ethernet – Fast Ethernet – Gigabit Ethernet – Wireless LANs- Blue tooth. (6) TCP/IP: TCP/IP Protocol Structure - Internet Protocol - UDP – TCP. (6) ROUTING : Distance vector routing _ Link state Routing – RIP – OSPF- BGP
(6) APPLICATIONS: FTP, TELNET, SMTP - MIME Format, DNS, HTTP. (5) INTERNETWORKING: LAN -LAN Connections – Repeaters- Hubs - Bridge –
Switches - Routers – Virtual LANs. (5) ADVANCED NETWORK ARCHITECTURE : Introduction to ATM – ISDN - MPLS (4)
Total 56
REFERENCES
44
1. Behrouz A Forouzan , "Data Communication and Networking", Mc Graw Hill, 2007.
2. Comer E, "Internetworking with TCP/IP, Principles Protocols and Architecture", Prentice Hall, 2001.
3. Tanenbaum A. S, "Computer Networks", Prentice Hall, 2003. 4. William Stallings, “Data and Computer Communication”, Prentice Hall, 2005 5. Behrouz A Forouzan, Sophia Chung Fegan, “TCP/ IP Protocol Suite”, Tata
McGraw Hill, 2004 6. Hardy J K, "Inside Networks", Prentice Hall , 1999.
09XT45 STOCHASTIC PROCESSES 3 2 0 4
CONDITIONAL PROBABILITY AND CONDITIONAL EXPECTATION: Introduction
– Discrete case – Continuous case – Computing Expectations by Conditioning – Computing Probabilities by Conditioning - Applications (7)
STOCHASTIC PROCESSES: Introduction – Classification of Stochastic Processes
– Markov Chain: Introduction -Transition Probability Matrices – Chapman Kolmogorov Equations - Classification of States – Limit Theorems – Applications. (7) CONTINUOUS TIME MARKOV CHAINS: Introduction – Poisson Process - Birth and Death Processes – Kolmogorov Differential Equations – Pure Birth Process - Pure Death Process - Applications. (6) RENEWAL THEORY: Introduction – Distribution - Renewal Theorems - Residual and Excess Life Times - Alternating Renewal Process - Renewal Reward Processes – Regenerative Processes. (7) GENERAL QUEUEING MODELS: Single and Multiserver Poisson Queues - Single Server Queue with Poisson input and general service M / G/1 – General input and exponential service – G/M/1 Queueing model – G/M/C Queueing model. (8)
Total 42
REFERENCES
1. Saeed Ghahramani, “Fundamentals of Probability with Stochastic Processes”, Prentice Hall, 2005. 2. Sheldon M Ross, “Introduction to Probability Models”, Academic Press, 2003. 3. Sheldon M Ross, “Stochastic Processes”, John Wiley and Sons, 2004. 4. Medhi J, “ Stochastic Processes”, New Age International Publishers , 2002.
45
5. Samuel Karlin Howard E.Taylor, “A First course in Stochastic Processes”,
Academic Press, 2002 6. Paul Minh D L, “Applied Probability Models”, Duxbury Thomson Learning, 2002 7. Gross.D and Harris C.M, “ Fundamentals of Queueing theory” John Wiley & sons, 1998.
09XT46 RDBMS LAB 0 0 3 2
SQL – ORACLE, SQL SERVER List of experiments are to be given time to time and Packages need to be developed.
09XT47 OPERATING SYSTEMS LAB 0 0 3 2
Implementation of the following algorithms 1. Memory management 2. Page replacement algorithm 3. Process scheduling algorithm 4. Process Synchronization 5. Thread Implementation 6. I/O Scheduling Unix: 7. Familiarize basic unix commands 8. shell program to do basic operations 9. shell program for menu driven programs 10. shell program for creating directories
09XT48 COMPUTER NETWORKS AND TCP/IP LAB
0 0 3 2
1. Read a Binary string, and hence display the wave forms corresponding to a. NRZ-L and NRZ-I encoding b. Manchester and differential Manchester encoding 2. Read a Binary string, and hence display the waveforms corresponding to a. PSK with 4 different phases b. PSK with 8 different phases c. QAM with 4 phases and 2 Amplitudes 3. Read a 4 bit binary number and hence find the 7 bit Hamming code to facilitate a single bit error correction. 4. Read a Binary string corresponding to the Message to be transmitted, and another binary string, corresponding to generator Polynomial and hence generate the CRC check sum. 5. Implement Sliding Window Protocol.
46
6. Read a binary string corresponding to an HDLC frame, and bit-stuff, if needed,
and identify the frame to be transmitted. 7. Read an IP Address in dotted notation, and hence , find out its network IP Address, with the help of a suitable mask. 8. Create a TCP socket between a server and a client and authenticate the user. 9. Implement a chat session using Socket Programming. 10. Configuring a Router 11. Configuring VLANS on a Router 12. Creation of VTP 13. Creation of Spanning Tree on a VLAN 14. Building Static Routing Tables on a Router 15. Implement Vector Distance Routing Algorithm. 16. Design a DNS server, and resolve a Domain Name from a Client‟s request.
SEMESTER – 5
09XT51 COMPUTATIONAL NUMBER THEORY AND CRYPTOGRAPHY 3 1 0 4
THEORY OF DIVISIBILITY: Introduction – Divisibility – Greatest common divisor – Prime numbers – Fundamental theorem of arithmetic – Mersenne primes – Fermat numbers – Euclidean algorithm – Euler totient function )(n (4)
CONGRUENCES: Definition – Basic properties of Congruences – Residue classes –
Chinese reminder theorem – Primitive roots – Legendre and Jacobi symbols. (6) PSEUDO – RANDOMNESS: Number generators – Pseudo random bit generators –
RSA, BBS. (4) CRYPTOGRAPHY INTRODUCTION: Encryption and secrecy – Objective of
cryptography – Attacks – Cryptographic protocols – Provable security. (3) SYMMETRIC KEY CRYPTOGRAPHY: Stream cipher – Block ciphers – DES –
Modes of operation – AES. (5) PUBLIC KEY CRYPTOGRAPHY: Concept of public key cryptography – RSA – Merkle – Hellman Cryptosystem – Elgamal Cryptosystems, Elliptic curve cryptosystem - Digital Signature – Hash function – RSA Signatures – Elgamal Signatures – Fail stop Signatures – Time stamping. (14) SECRET SHARING SCHEMES: Threshold secret sharing – Shamir Threshold Scheme – Blakey scheme – Modular scheme – Group oriented cryptography –
47
Threshold Decryption – Elgamal – RSA- Threshold Signatures RSA – Elgamal –
Threshold DSS Signatures. (6)
Total 42 REFERENCES 1. Ivan Niven, Herbert S Zuckerman and Hugh L Montgomery, “ Introduction to the theory of Numbers”, John Wiley and Sons 2004. 2. Tom M Apostol, “ Introduction to Analytic Number theory”, Springer-Verlag , 1992. 3. Neal Koblitz “ A course in Number Theory and Cryptography”, Springer Verlag, 2002 4. Kenneth H Rosen, “Elementary Number theory and its Applications”, Addison Wesley, 2005. 5. Josef Pieprzyk, Thomas Harjono and Jenifer Seberry, “ Fundamentals of Computer Security”, Springer-Verlag, 2008. 6. Bruce Schneier, “ Applied Cryptography”, John Wiley and Sons, 2001. 7. Alfred J, Menezes, Paul C, Van Oorschot and Scott A Vanstone, “ Hand Book of Applied Cryptography”, CRC Press, 2001. 8. William Stallings, “Cryptography and Network Security”, Prentice Hall, 2006. 9. Douglas R Stinson, “Cryptography Theory and Practice”, CRC Press , 1995.
09XT52 COMPUTER GRAPHICS AND ANIMATION 4 0 0 4
GRAPHICS INPUT - OUTPUT DEVICES: Raster scan Displays - Random scan
displays - Direct view storage tubes - Flat panel displays - Mouse - Track Ball - Joy Stick - Digitizers - Touch panels - LCD. (4) GRAPHICAL USER INTERFACE AND INTERACTIVE INPUT METHODS: The user
dialog - Input of graphical data - Input function - Interactive picture construction techniques - Virtual reality environments. (4) TWO DIMENSIONAL GRAPHICS: Basic transformations - Matrix representation and homogeneous coordinates - Composite transformations - Line drawing algorithms: DDA and Bresenham's algorithms - Circle generation algorithms: Mid point circle algorithm - Point clipping - Line clipping: Cohen Sutherland algorithm - Polygon clipping: Sutherland Hodgeman algorithm - Line covering. (10) RASTER GRAPHICS: Fundamentals: generating a raster
48
image, representing a raster image, scan converting a line drawing, displaying
characters, speed of scan conversion, natural images - Solid area scan conversion: Scan conversion of polygons, Y-X algorithm, properties of scan conversion algorithms - Interactive raster graphics: painting model, moving parts of an image, feed back images. (10) CURVES AND SURFACES: Parametric representation of curves - Bezier curves –
B-Spline curves - Parametric representation of surfaces - Bezier surfaces - Curved surfaces - Ruled surfaces - Quadric surfaces – Concatenation of two curve segments – Order of Continuity. . (6) THREE DIMENSIONAL GRAPHICS: 3D transformations - Viewing 3D graphical data
- Orthographic, oblique, perspective projections - Hidden lines and hidden surface removal. (6) MAYA SOFTWARE AND ANIMATION:: Modeling - Dynamics and Simulation - Mel
(Maya Embedded language)scripting –Animation - Animation function - Raster animation - Key frame systems - motion specification - Morphing - Tweening. Tiling the plane - Recursively defined curves - Koch curves - C curves - Dragons - Space filling curves - Fractals - Grammar based models - Graftals - Turtle graphics - Ray tracing. (16)
Total 56
REFERENCES 1. Donald Hearn and Pauline Baker M, " Computer Graphics", Pearson Education, 2002. 2. Rankin John R, "Computer Graphics Software Construction", Prentice Hall., 1989. 3. Foley James D, Vandam Andries and Hughes John F, "Computer Graphics : Principles and Practice", Pearson Education, 2002. 4. Danny Riddel, Morgan Robinson and Nathaniel Stein,"Maya 7 for Windows and Macintosh",Peachpit Press, 2006. 5. Mark R. Wilkins and Chris Kazmier,"Mel Scripting for Maya Animators",Morgan Kaufmann Publishers, 2005. 6. Sergey Tsiptsin,"Understanding Maya", ArtHouse Media, 2007.
09XT53 THEORY OF COMPUTING 4 0 0 4
FORMAL LANGUAGES: Four classes of grammar – Regular set – Context free
language – Generation trees – Ambiguity – Normal forms(Chomsky and Grievas) – Pumping Lemma‟s (8)
49
FINITE AUTOMATA: Finite State Automata – NDFA – Conversion of NDFA to DFA –
regular expressions - Equivalence of regular grammar and finite automata, State minimization. (8) PUSH DOWN AUTOMATA: Definition – Acceptance by final state and empty stack –
Equivalence of acceptance by final state and empty stack – Equivalence of PDA‟s and CFL‟s – Definition of DPDA (12) TURING MACHINE: Definition – Models – Construction of simple turing machine-
Programming techniques for turing machine – Extension to the basic turing machine – Restricted turing machine – Turing machine and computers – Halting problem. (14) UNSOLVABLE PROBLEM AND COMPUTATIONAL FUNCTIONS: Unsolvable problems – Primitive recursive function – recursively enumerable language – Universal Turing machine – Tractable and untractable problems - P and NP problems. (14)
Total 56 REFERENCES
1. John E Hopcroft, Jeffrey D Ullman and Rajeev Motwani, "Introduction to Automata Theory, Languages and Computation," Pearson Education, Edition 3, 2007.
2. Martin, “ Introduction to Languages and the Theory of Computation”, Tata McGraw Hill, 2005
3. Harry R Lewis and Christes H Papadimitriou,“ Elements of the Theory of Computation”, Pearson Education, 2005
4. Peter linz, “An Introduction to Formal Language and Automata”, Jones and Bartlett Publisher, 2006
09XT54 OPTIMIZATION TECHNIQUES 3 1 0 4
LINEAR PROGRAMMING : Graphical method for two dimensional problems – Central problems of Linear Programming – Definitions – Simplex Algorithm – Phase I and Phase II of Simplex Method. (10) SIMPLEX MULTIPLIERS: Dual and Primal – Dual Simplex Method – Revised Simplex Method - Sensitivity Analysis – Transportation problem and its
50
solution – Assignment problem and its solution by Hungarian method –
Karmakar‟s method – Statement, Conversion of the Linear Programming problem into the required form, Algorithm. (10)
INTEGER PROGRAMMING: Gomory cutting plane methods for all integer and mixed integer programming problems - Branch and Bound method (Land – Dolg and Dakin algorithms). (6) DYNAMIC PROGRAMMING: Principle of Optimality – Backward and forward induction methods - Calculus method of solution- Tabular method of solution – Shortest path network problems – Applications in production. (6) PERT: Arrow networks - Time estimates - Earliest expected time, latest allowable
occurrence time and slack of events - Critical path - Probability of meeting scheduled date of completion of project. (5) CPM: Calculations on CPM networks - Various floats for activities - Critical path - Updating a project - Operation time cost trade off curve - Project time cost trade off curve - Selection of schedule based on cost analysis. (5)
Total 42
REFERENCES
1. Hillier F and Liberman G J, “Introduction to Operations Research”, McGraw Hill
, 2005. 2. Hamdy A Taha, “Operations Research – An Introduction”, Prentice Hall, 2001. 3. Kambo N S “ Mathematical Programming Techniques”, Affiliated East-West press, 1991. 4. Singiresu S Rao, “Engineering optimization theory and Practice”, New Age International, 1996.
09XT55 SOFTWARE ENGINEERING 4 0 0 4
INTRODUCTION : System - System Development - Types of systems – People involved in the systems development - The project life cycle models - Need for Software Engineering - Objectives and Benefits of Software Engineering - Factors that influence Quality & Productivity – Quality attributes of a software product. (9) SOFTWARE PLANNING : Software Project Estimation - Different techniques of Project cost estimation Decomposition techniques - COCOMO & PUTNAM models (5)
51
SOFTWARE ANALYSIS : Functional and non-functional requirements-
Requirements engineering process – Elicitation – validation and management – software prototyping - Principles of Analysis - Analysis tools - Analysis Models. (12) DESIGN CONCEPTS AND PRINCIPLES : Design process and concepts – Levels of
Design - Coupling - Cohesion -Design Tools - Software Design Methods – Design Techniques - Design of Input and control - Design of Output (12) OBJECT ORIENTED SYSTEMS DEVELOPMENT : Object Oriented Systems
Development life Cycle - Object oriented methodologies - Rational Unified Process – Unified Modeling Language –Process workflows – Importance of Modeling – Types of Modeling (16) Case Study (2)
Total 56
REFERENCES 1. Pressman R S, “Software Engineering – A Practitioner‟s Approach”, Tata McGraw Hill , 2005. 2. Shari Lawrence Pfleeger, “Software Engineering Theory and Practice”, Pearson Education , 2005 3. Ian Sommerville, “Software Engineering”, Addison Wesley, 2006. 4. Philippe Krucheten, The Rational Unified Process – An Introduction , Addison – Wesley 2003. 5. Grady Booch , James Rumbaugh and Ivar Jacobson , The Unified Modeling Language User Guide, Pearson Education, 1999. 6. Martin Fowler and Kendall Scott, UML Distilled , Pearson Education, 2002. 7. John Hunt, The Unified Process for Practitioners , Springer, 2000. 8. Hans-Erik Eriksson, Magnus Penker, Brain Lyons, David Fado, “UML Toolkit”, OMG Press Wiley Publishing Inc., 2004.
09XT56 COMPUTER GRAPHICS AND ANIMATION LAB 0 0 3 2
1. Drawing a line, circle using algorithms 2. Implementation of 2D Transformations (translation, scaling, rotation) 3. Window – viewport simulation with various aspect ratios 4. Polygon clipping and line clipping using algorithms. 5. Drawing a 2D curve using Bezier generation
52
6. Drawing a 2D curve using B-Spline generation
7. Model a primitive (car / Aircraft) with Maya Software 8. Simulate the primitive 9. Animate the primitive
09XT57 OPTIMIZATION TECHNIQUES LAB 0 0 3 2
1. Solving inequalities using Simplex, Two-phase, Dual simplex methods, Revised simplex method 2. Finding initial basic feasible solution using (i) North-West corner rule (ii) Matrix minimum and (iii) Vogel‟s approximation method and also perform optimality test using MODI method. 3. Solving Assignment problem using Hungarian method 4. Gomory;s cutting plane methods for all IPP and mixed IPP 5. Solving Dynamic Programming problems 6. To find the critical path for the given PERT and CPM networks
09XT58 SOFTWARE ENGINEERING LAB 0 0 3 2
1. Implementation of requirement analysis process using the appropriate tool 2. Implement of Design using the rational tools 3. Generate use case diagram and related object oriented analysis representation using rational tools 4. Generation of code using appropriate tool 5. Implementation of debugging process using the appropriate tool 6. Testing the applications for unit testing 7. Testing the application for integrated testing 8. Testing application for load or volume testing 9. Using an appropriate tool for generate test cases/ test plan/ test documents 10. Using MS-Project for generating CP/M and PERT charts and finally preparation of project plan
SEMESTER – 6
09XT61 SECURITY IN COMPUTING 4 0 0 4
INTRODUCTION: Security goals, Attacks, Services and Mechanisms -Techniques –
Understanding threats. (5) PROGRAM SECURITY: Secure programs, non Malicious program errors – Buffer overflows – Malware Taxonomy – viruses and other Malicious code – Targeted Malicious code – Defense mechanisms. (8)
53
SECURITY AT APPLICATION LAYER: Email – Email security – PGP – Key rings – PGP certificates – S/MIME – Applications of S/MIME – Web Security – Attacks and defenses. (8) SECURITY AT TRANSPORT LAYER: SSL Architecture – Four protocols – SSL message formats – Transport layer security. (7) SECURITY AT NETWORK LAYER: Threats in networks, network security controls – firewalls – Intrusion detection system – IPSEC – modes – security protocols – security association – Internet key exchange - VPN. (8) OS SECURITY: Memory and Address protection – Access control – file protection mechanisms – User authentication – Models o f security – Trusted OS design. (7) DATABASE SECURITY: Security Requirements – Reliability and Integrity – Sensitive data – Multilevel Databases. (7) LEGAL ISSUES IN COMPUTER SECURITY: Protecting programs and data – Rights of Employees and Employers – Computer crime, Digital Rights Management( (DRM) (6)
Total 56
REFERENCES 1. Roberta Bragg, Mark Rhodes, Keith Strass Berg J, “Network Security - The complete reference”, Tata McGraw Hill 2006. 2. Behrouz, A.Forouzan, “Cryptography and Network Security”, Tata McGraw Hill, 2007. 3. Charles P Pfleeger, Shari Lawrence P Fleeger, “Security in Computing”, Pearson Education, 2004. 4. William Stallings, “Cryptography and Network Security”, Prentice Hall, 2006.
09XT62 PRINCIPLES OF COMPILER DESIGN 4 0 0 4
SYSTEMS PROGRAMMING : Language Processors – Data Structures for Language Processing – Introduction to Assemblers, Macro processors, Interpreters. Linkers and Loaders - its need and working. (8)
54
LEXICAL ANALYSIS: Role of a Lexical Analyzer – Finite Automata – Regular
Expressions to Finite Automata – Minimizing the number of states of a Deterministic Finite Automata – Implementation of a lexical analyzer. (6) PARSING TECHNIQUES: Context free grammars – Derivations and parse trees – Ambiguity – Capabilities of context free grammars. Top down and bottom up parsing – Handles – Shift reduce parsing – Operator precedence parsing – Recursive descent parsing - Predictive parsing. (12) AUTOMATIC PARSING TECHNIQUES: LR parsers – Canonical collection of LR(0) items – Construction of SLR parsing tables – LR(1) sets of items construction – Construction of canonical LR parsing tables. (10) SYNTAX DIRECTED TRANSLATION: Semantic actions – Implementations of
syntax directed translators – Immediate code: postfix notation; quadruples; triples; indirect triples – Methods of translation of assignment statements, Boolean expression and control statements. (10) INTERMEDIATE CODE GENERATION: Postfix notation, Quadruples, triples ,
indirect triples – Representing information in a symbol table. (3) CODE OPTIMIZATION : introduction to code optimization – basic blocks – DAG
representation – error detection and recovery - code generation. (7)
Total 56
REFERENCES 1. John J. Donovan, “ Systems Programming”, McGraw Hill , 1999. 2. Dhamdhere D.M., “Systems Programming”, Tata McGraw Hill, 2001. 3. Aho A.V, R.Sethi and Ullman J.D., “Compilers : Principles, Techniques and Tools”, Addison Wesley, Longman,2007 4. Dhamdhere D.M., “Compiler Construction Principles and Practice”, Macmillan Company, 1997. 5. Holub Allen I. “Compiler Design in C”, Prentice Hall , 2001.
09XT63 PRINCIPLES OF PROGRAMMING LANGUAGES 4 0 0
4
55
INTRODUCTION : The Role of Programming Languages: Toward Higher-level
Languages, Problems of Scale, Programming Paradigms, Language Implementation Bridging the Gap - Language Description:- Syntactic Structure: Expression Notations, Abstract Syntax Trees, Lexical Syntax, Context -Free Grammars, Grammars for Expressions, Variants of Grammars. (8)
IMPERATIVE PROGRAMMING: Statements: Structured Programming:- The Need
for Structured Programming, Syntax-Directed Control Flow, Design Considerations: Syntax, Handling Special Cases in Loops, Programming with invariants, Proof Rules for Partial Correctness, Control flow in C - Types: Data Representation:- The Role of Types, Basic Types, Arrays Sequences of Elements, Records: Named Fields, Unions and variant Records, Sets, Pointers: Efficiency and Dynamic Allocation, Two String Tables, Types and Error Checking - Procedure Activations:- Introduction to Procedures, Parameter-passing Methods, Scope Rules for Names, Nested Scopes in the Source Text, Activation Records, Lexical Scope: Procedures as in C, Lexical Scope: Nested Procedures and Pascal. (12)
OBJECT ORIENTED PROGRAMMING : Groupings of Data and Operations:-
Constructs fro Program Structuring, Information Hiding, Program Design with Modules, Modules and Defined Types, Class Declarations in C++, Dynamic Allocation I C++, Templates: Parameterized Types, Implementation of Objects in C++. - Object-Oriented Programming:- What is an Object?, Object-Oriented Thinking - Objects in Smalltalk. (8)
FUNCTIONAL PROGRAMMING: Elements of Functional Programming:- A little
Language of expressions, Types : Values and Operations, Function declarations, Approaches to Expression Evaluation, Lexical Scope, Type Checking - Functional Programming in a Typed Languages:- Exploring a List, Function Declaration by Cases, Functions as First-Class Values, ML: Implicit Types, Data Types, Exception Handling in M, Little quit in Standard ML - Functional Programming with Lists:- Scheme, a Dialect of Lisp, The Structure of Lists, List Manipulation, A Motivating Example: Differentiation, Simplification of Expressions, Storage Allocation for Lists. (16)
OTHER PARADIGMS: Logic Programming:- Computing with Relations, Introduction to Prolog, Data Structures in Prolog, Programming techniques, Control in Prolog, Cuts - An Introduction to Concurrent Programming:- Parallelism in Hardware, Streams: Implicit Synchronization, Concurrency as interleaving, Liveness Properties, Safe Access to Shared Data, Concurrency in Ada, Synchronized Access to Shared variables. (12)
Total 56
REFERENCES
56
1. Terrence W. Pratt, Marvin V.Selkowitz and T.V.Gopal “Programming Languages Design and Implementation”, Pearson Education, 2006. 2. Ravi Sethi, “Programming Languages Concepts and Constructs “, Pearson Education, 2006. 3. Robert W. Sebesta, “Concepts of Programming Languages”, Addison Wesley, 2005. 4. Robert Harber, “ Programming in standard ML”, Carnegie Mellon University, 2005. 5. Larry C. Paulson, “ ML for working Programmer”, Cambridge University Press, 1997. 6. Al Kelley and Ira Pohl, “ A Book on C “ Pearson Education, 2005.
09XT64 SOFT COMPUTING
4 0 0 4
ARTIFICIAL INTELLIGENCE(AI): Characteristics of AI problem - State space representation - AI search strategies: Brute force, depth first, breadth first, best first, hill climbing and A* algorithms (10) KNOWLEDGE REPRESENTATION: Logic- Propositional calculus - Predicate calculus - Rules of inference - Resolution - unification algorithm - Semantic networks - Frames – Scripts (9) SOFT COMPUTING AND CONVENTIONAL AI: Constituents - Characteristics - Hybrid models (2) FUZZY SET THEORY: Fuzzy sets - Basic definitions - Membership functions -
Fuzzy rules and reasoning - Fuzzy relations - fuzzy if-then rules - Fuzzy reasoning (13) GENETIC ALGORITHMS: Survival of the fittest - Fitness computations - Cross over
- Mutation - Reproduction - Rank method - Rank space method. (4) NEURAL NETWORKS: Basic concepts - Network properties - Learning in simple
neurons - Single layer perceptrons - Multilayer perceptrons - Supervised and unsupervised learning – Backpropagation network, Kohonen's self organizing network, Hopfield network. (18)
Total 56
REFERENCES
1. Patrick Henry Winston, "Artificial Intelligence", Pearson Education, 2004. 2. Peter Norvig and Stuart J. Russel, “”Artificial Intelligence: A Modern Approach”, Prentice Hall , 2005.
57
3. Elaine Rich and Kevin Knight, "Artificial Intelligence", Tata McGraw Hill,
2002. 4. Ross Timothy J, " Fuzzy Logic with Engineering Applications", John Wiley and Sons Ltd, 2005. 5. Rajasekaran S and Vijayalakshmi Pai G A, “ Neural Networks, Fuzzy Logic and Genetic Algorithms”, Prentice Hall, 2003. 6. Laurene Fausett, "Fundamentals of Neural Networks", Prentice Hall, 1994. 7. Patterson Dan W, "Artificial Neural Networks", Prentice Hall, 1996. 8. Jang J S R, Sun C T and Mizutani E, "Neuro- Fuzzy and Soft Computing", Prentice Hall, 1997.
09XT65 ELECTIVE - I 3 0 2 4
09XT66 SECURITY IN COMPUTING LAB 0 0 3 2
1. Implementation of substitution cipher. 2. Implementation of transposition cipher. 3. Generation of keys using pseudorandom generators 4. Implementation of RSA cryptosystem 5. Implementation of Shamir threshold scheme for secret sharing. 6. Digital signature, generation and verification. 7. Implementation of firewall 8. Packages using the concepts of IPSec, SSL and PGP.
09XT67 PRINCIPLES OF COMPILER DESIGN LAB 0 0 3 2
1. Implementation of Transition diagram to strip off comment statements from a given source file 2. Design and Implementation of a Symbol Table Manager. 3. Implementation of following parsing algorithms a. Recursive descent Parser b. Shift reduce parser. c. Operator Precedence Parser 4. Implementation of the Syntax directed translation Engine to a. Simulate Desk Calculator b. Generation of Postfix code. c. Post and Pre Code Optimizer. 5. Using LEX and YACC under UNIX environment for compiler design related problems.
09XT68 SOFT COMPUTING LAB
0 0 3 2
58
1. Implementation of logic problems using PROLOG. (Problem sheet will be
provided) 2. Develop any two of the following applications : a) Define an application and implement using Fuzzy Logic. b) Define an application and implement using any type of Neural Network. c) Define an application and implement using Genetic Algorithm. Note: The applications should be based on Research Publications.
SEMESTER – 7
09XT01 INDUSTRY PROJECT WORK AND VIVA VOCE 0 0 – 12
SEMESTER – 8
09XT81 PARALLEL AND DISTRIBUTED COMPUTING
4 0 0 4
INTRODUCTION: Concepts and Terminology - Flynn's Classical Taxonomy – Terminology (4)
PARALLEL COMPUTER MEMORY ARCHITECTURES: Shared Memory - Distributed Memory -Hybrid Distributed-Shared Memory Multiprocessors: Communication and Memory issues - Message Passing Architectures - Vector Processing and SIMD Architectures (8)
THE CM-2, MASPAR, AND CM-5 ARCHITECTURES - Latency Hiding Architectures -Multithreading Architectures -Dataflow Architectures -Bulk synchronous parallel model - Asynchronous Parallel Programming Model - Overview of basic CPU and memory design issues (8)
PARALLEL PROGRAMMING MODELS: Overview -Shared Memory Model - Threads Model - Message Passing Model - Data Parallel Model - Other Models (6)
DESIGNING PARALLEL PROGRAMS: Automatic vs. Manual Parallelization - Understand the Problem and the Program - Partitioning -Communications - Synchronization -Data Dependencies - Load Balancing -Granularity -I/O -Limits and Costs of Parallel Programming - Performance Analysis and Tuning - Parallel Examples -Array Processing (8)
DISTRIBUTED COMPUTING: Introduction -- Definitions, motivation -
Communication Mechanisms - Communication protocols,-RPC- RMI- stream oriented communication - Distributed Algorithms – snapshots - leader election - etc: [Optional or can be as case study - Naming:- generic schemes – DNS - naming and localization.] Synchronization -Traditional synchronization - lock free - clocks. Replication and Coherence - Consistency models and protocols - Fault Tolerance --
59
group communication - Two- and three - Phase commit - Check pointing -
Security - Threats - Control mechanisms - Systems - Distributed File Systems:- NFS – Coda – etc - Middleware - outline of CORBA – Jini - Mobile systems. (6)
PRAM ALGORITHMS: PRAM model of computation- Work-Time formalism and Brent‟s Theorem; algorithm design techniques-parallel prefix, pointer jumping, Euler tours, divide and conquer, symmetry breaking; survey of data-parallel algorithms; relative power of PRAM models. (8)
DENSE LINEAR ALGEBRA - Matrix transposition - Matrix product - Gaussian
elimination - Data distribution - Parallel linear algebra libraries. (8)
Total 56
REFERENCES 1. Selim G Akl, "Parallel Computation: Models and Methods", Prentice Hall, 1997. 2. Gibbons A and Rytter W, "Parallel Algorithms", Cambridge University, 1988. 3. JaJa J, "Introduction to Parallel Algorithms", Addison Wesley, 1992. 4. Leighton F T, "Introduction to Parallel Algorithms and Architectures: Arrays, Trees
and Hyper cubes", Morgan Kaufmann, 1991. 5. Lynch N A, "Distributed Algorithms", Morgan Kaufmann, 1996. 6 Tel G, "Introduction to Distributed Algorithms", Cambridge University, 2000. 7. Andrew S. Tannenbaum and Maarten van Steen, “ Distributed Systems,
Principles and Paradigm” Prentice Hall, 2002. 8. Vijay K Garg, “Elements of Distributed Computing”, Wiley 2002.
09XT82 MATHEMATICAL MODELLING
3 1 0 4
INTRODUCTION TO MODELING: Modeling process, Overview of different kinds of models (3) EMPIRICAL MODELING WITH DATA FITTING: Error function, least squares
method; fitting data with polynomials and splines. (4) QUALITATIVE MODELING WITH FUNCTIONS: Modeling species propagation, supply and demand, market equilibrium, market adjustment. Inventory models – Various types of inventory models with shortage and without shortage, Probabilistic models, Modeling with proportion and scale. (10) CAUSAL MODELING AND FORECASTING: Introduction, Modeling the causal time
60
series, forecasting by regression analysis, predictions by regression. Planning,
development and maintenance of linear models, trend analysis, modeling seasonality and trend, trend removal and cyclical analysis, decomposition analysis. Modeling financial time series. Econometrics and time series models. (12) MODELING WITH BIOINFORMATICS: Introduction, Biological data- types, mode of collection, documentation and submission. Sequence alignment- Definition, significance, dot matrix method, dynamic programming- Global and local alignment tools, scoring matrices and gap penalties. Multiple sequence alignment: Iterative methods. Genetic algorithm, Hidden Markovian models, statistical methods, position specific scoring matrices. (13)
Total 42
REFERENCES 1. Edward A.Bender, “An Introduction to Mathematical Modeling”, Dover, 2000. 2. Giordano F R, Weir M D, and Fox W P, “A First Course in Mathematical Modeling”. Brooks/Cole, 1997. 3. Hamdy A Taha, “Operation Research- An Introduction”, Pearson Education, .2002. 4. Borovkov K, “Elements of Stochastic Modeling”, World Scientific, 2003. 5. Christoffersen P, “ Elements of Financial Risk Management”, Academic Press, 2003. 6. Mount. D W, “Bioinformatics Sequence and genome analysis ”, Cold Spring Harbor Laboratory, 2001 7. Salzberg Searls and Kasif, “ Computational Methods in Molecular Biology”, Elsevier, 1998
09XT83 DATA MINING 3 0 0 3
INTRODUCTION: Motivation for Data Miniing – Importance – Definition – Kinds of
data for Data Mining – Data Mining functionalities – Patterns – Classification of Data Mining Systems – Major issues in Data Mining. (4) DATA PREPROCESSING: Types of data, Data cleaning, Aggregation, Sampling –
Data Reduction – Feature subset selection - 2x and Information Gain.
(5) MINING FREQUENT PATTERNS, ASSOCIATIONS AND CORRELATIONS: Basic
concepts – Efficient and Scalable Frequent Itemset Mining methods – Apriori, FP Tree – Association Mining to Correlation Analysis – Constraint based Association Mining. (8)
61
CLASSIFICATION AND PREDICTION: Classification – Prediction – Classification by
Decision Tree Induction – Bayesian Classification – Classification based on concepts from Association Rule Mining – Prediction – Classifier accuracy –Evaluating the accuracy of a classifier. (7) CLUSTER ANALYSIS: Cluster Analysis – Types of data in Cluster Analysis – A
categorization of major clustering methods – partitioning methods – hierarchical methods – density based methods – grid based methods – Model based clustering – Outlier analysis. (7) MINING COMPLEX TYPES OF DATA: Multidimensional analysis and descriptive
mining of complex data objects – Mining Spatial Databases – Mining Multimedia Databases – Mining time- Series databases and sequence data – Mining Text Databases – Mining the World Wide Web. (7) APPLICATIONS AND TRENDS IN DATA MINING: Data Mining Applications – Data
Mining system products and Research prototypes – Trends in Data Mining. (4) Total 42 REFERENCES 1. Jiwai Han and Micheline Kamber , “ Data Mining – Concepts and Techniques”,
Morgan Kaufmann Publishers, 2006. 2. Tan, Skinbach, Kumar, “Introduction to Data Mining”, Pearson Education, 2007 3. Arun K Pujari, “Data Mining Techniques”, Orient Blackswan, 2001 4. Bhavani Thuraisingham, “ Data Mining – Technologies, Techniques, Tools and
Trends”, CRC Press, 1999. 5. Sean Kelly, "Data Warehousing in Action", John Wiley & Sons Inc., 1997. 6. Robert Groth, "Data Mining", Prentice Hall, 1998. 7. Ian Witten, "Data Mining: Practical Machine Learning Tools”, 2nd Edition, Elsevier,
2006.
09XT84 ELECTIVE - II 3 0 2 4
09XT85 ELECTIVE – III (SELF STUDY)
0 2 2 4 09XT86 PARALLEL AND DISTRIBUTED COMPUTING LAB
0 0 3 2
62
1. Basic Master – Worker program and send messages:
2. Write a program to find the summation of largest number in a very larger array of integers. ( The contents of the array should be equally distributed to all processes ).
3. Write a parallel program in SPMD to calculate the PI value using integral approximation method. 4. Simple Matrix multiplication, Transpose, using parallel algorithm. 5. Select your own choice of very dense computational problem having divide and conquer method and implement it in parallel algorithm. And produce the performance chart with 2, 4, 6 and 8 nodes.
09XT87 MATHEMATICAL MODELLING LAB
0 0 3 2 Softwares: MATLAB programming, Mathlab, Mathematica, Maple. Topics: Some of the major topics to be covered include (not necessarily in the order given):
Types of Mathematical Models: Numerical, Analytical, and Graphical. Algebraic Models: Linear, Quadratic, and Exponential. Models of Ratio & Proportion: Graphs, Critical Path, Weighted Averages. Models of Weighted Averages. Practical Applications of Models. Regression - Finding Curves of Best Fit.
Students have to develop a mini package for this course at the end of this semester. Some of the titles are given below. But it is not limited. Mini Package Titles:
1. Implementation of fitting data with polynomials and splines. 2. Various types of inventory models with shortage and without shortage. 3. Usage of mathematical modeling in marketing. 4. Casual modeling and Forecasting. 5. Implementation of Genetic Algorithm in modeling. 6. Implementation of Hidden Markovian models.
09XT88 DATA MINING LAB 0 0 3 2
Implementation of 1. Data mining query language using Oracle 2. Classification by Decision Tree 3. Clustering by any one method 4. Text mining using any one technique
SEMESTER – 9
63
09XT91 MACHINE LEARNING 3 0 0 3
INTRODUCTION: Learning associations, classification, regression, unsupervised and supervised learning – Learning classes from examples – Learning multiple classes- Model selection and generalization. (6) DECISION UNDER UNCERTAINTY: Bayesian decision theory- Classification-
losses and risks – Discriminant functions-Bayesian networks – Association rules. (4) PARAMETRIC METHODS: Maximum likelihood estimation - Evaluating an estimator – Bayes estimator- Multivariate methods – Estimation of missing values - Multivariate classification and regression. (6) DIMENSIONALITY REDUCTION: Subset selection - Principal component analysis - Factor analysis - Linear discriminant analysis. (6) CLUSTERING: K means clustering - Hierarchical clustering – Choosing the number
of clusters. (6) DECISION TREES: Univariate trees – Rule extraction from trees - Multivariate trees. (5) NEURAL NETWORKS: Multilayer Perceptrons - Learning vector quantization – Support vector machines. (4) HIDDEN MARKOV MODELS: Discrete Markov process – Finding the state sequence
– Model selection. (5)
Total 42 REFERENCES
1. Alpaydin Ethem, “ Introduction to Machine Learning ”, Prentice Hall, 2004. 2. Richard O Duda, Peter E Hart and David G Stork, “Pattern Classification”, Wiley
and Sons, 2001. 3. Tom Mitchell, “Machine Learning”, McGraw Hill, 1997. 4. Christopher M Bishop, “Pattern Recognition and Machine Learning ”, Springer,
2007. 5. Trevor Hastie, Robert Tibshirani and Jerome Friedman, “The Elements of
Statistics Learning”, Springer, 2001 6. David Barber, “ Machine Learning: A Probabilistic Approach”,
http://www.idiap.ch/~barber, 2006.
09XT92 INTELLIGENT INFORMATION RETRIEVAL 3 0 0 3
INTRODUCTION: Overview of IR Systems - Historical Perspectives -
64
Goals of IR - The impact of the web on IR - The role of artificial intelligence (AI)
in IR – Experimental Evaluation of IR: Performance metrics: recall, precision, and F-measure; Evaluations on benchmark text collections - Document Representation: Statistical Characteristics of Text - Basic Query Processing : Query Operations
and Languages - Relevance feedback; Query expansion; Query languages - Data Structure and File Organization for IR - Automatic Indexing and Indexing Models. (12) RETRIEVAL MODELS: Similarity Measures and Ranking - Boolean Matching - Vector Space Models - Probabilistic Models - ranked retrieval; text-similarity metrics - TF-IDF (term frequency/inverse document frequency) weighting - cosine similarity – Basic Tokenizing, Indexing, and Implementation of Vector-Space Retrieval:
Simple tokenizing, stop-word removal, and stemming; inverted indices; efficient processing with sparse vectors; Java implementation. (8) TEXT REPRESENTATION: Word statistics; Zipf's law; Porter stemmer; morphology; index term selection; using thesauri. Metadata and markup languages (SGML, HTML, XML). (3) SEARCH AND FILTERING TECHNIQUES: Relevance Feedback - User Profiles - Collaborative Filtering - Document and Term Clustering, Document Categorization - Web Search : IR Systems and the WWW - Search engines; spidering; metacrawlers; directed spidering; link analysis (e.g. hubs and authorities, Google PageRank); shopping agents - Heterogeneous Information Sources - Intelligent Web Agents. (7)
TEXT CATEGORIZATION AND CLUSTERING: Categorization algorithms: Rocchio; naive Bayes; decision trees; and nearest neighbor. Clustering algorithms: agglomerative clustering; k-means; expectation maximization (EM). Applications to information filtering; organization; and relevance feedback. (4)
RECOMMENDER SYSTEMS: Collaborative filtering and content-based recommendation of documents and products. INFORMATION EXTRACTION AND INTEGRATION: Extracting data from text; XML; semantic web; collecting and integrating specialized information on the web. (6)
Web Mining and Its Applications (2)
Total 42
REFERENCES
65
1. Ricardo Baeza-Yates and Berthier Ribeiro-Neto,” Modern Information
Retrieval”, Addison Wesley, 1999. 2. William B. Frakes and Ricardo Baeza-Yates, “Information Retrieval Data
Structures and Algorithms”, Prentice Hall, 1992. 3. G. Salton and M. J. McGill, “Introduction to Modern Information Retrieval”,
McGraw-Hill, 1983. 4. C.J. Van Rijsbergen, ” Information Retrieval”, Butterworths, 1979. 5. C. J. Van Rijsbergen, ”The Geometry of Information Retrieval”, Cambridge
University Press, 2004.
09XT93 GAME THEORY 3 1 0 4
INTRODUCTION: Game theory the theory of rational choice – coming attractions: Interacting decision – makers. (3)
GAME WITH PERFECT INFORMATION: Nash equilibrium – Strategic games –
Example: the prisoner‟s dilemma, Matching Pennis – Best response functions – Dominated actions – Illustration – Cournot‟s model of oligopoly - electrol competition. (8) MIXED STRATEGY EQUILIBRIUM: Strategic games in which players may randomize – Dominated actions – expert diagnosis – reporting a crime – The formation of player‟s belief. (6) EXTENSIVE GAMES WITH PERFECT INFORMATION: Strategies and outcomes –
Nash equilibrium – Stackelberg‟s model of duopoly, buying votes – Allowing for simultaneous moves – Entry into a monopolized industry – Electrol competition with strategic voters – committee decision making. (8) GAMES WITH IMPERFECT INFORMATION: Bayesian games – Examples –
Strategic information – Transmission – Agenda Control with imperfect Information – Education as a signal of ability. (8) REPEATED GAMES: The prisoner‟s dilemma – Finitely repeated and infinitely repeated – Strategies – Nash equilibrium – Subgame – Perfect equilibria and the one – deviation – Property – General results – Finitely replaced games – Variation on a theme: Imperfect observability. REFERENCES 1. Martin J Osborne, “ An Introduction to game theory”, Oxford University Press, 2004. 2. Eric Rasmusen, “ Games and Information - An Introduction to
66
Game Theory”, Blackwell Publishers, 2006.
09XT94 ELECTIVE - IV 3 0 2 4
09XT95 ELECTIVE – V (SELF STUDY) 0 2 2 4
09XT96 INTELLIGENT INFORMATION RETRIEVAL LAB 0 0 3 2
Programming related to:
1. Document indexing 2. Vector Space Model 3. Make a precision plot for each search engine as above for the first 10 returned
links as a function of the number of documents returned. 4. Synonym expansion using a thesaurus, and automatic query expansion by
common terms/phrases in top-ranked documents 5. Calculating probabilities based on the corpus as a whole 6. Implementing k-means algorithm 7. Expressing Knowledgebase in RDF / OWL. 8. Querying RDF/XML
09XT97 MACHINE LEARNING LAB 0 0 3 2
A Problem Sheet will be provided for classification, regression and decision tree rules. Implement any three packages : 1. Implement Classification using Bayesian Estimator. 2. Reduce dimensions using PCA / LDA. 3. Implement K-means Clustering. 4. Implement Classification using Support Vector Machines. 5. Find the state sequence using a HMM.
09XT98 RESEARCH SPECIALIZATION LAB 1 0 3 3
SEMESTER – 10
09XT02 RESEARCH AND DEVELOPMENT PROJECT AND VIVA VOCE
0 0 - 12
ELECTIVES
09XTE1 DIGITAL IMAGE PROCESSING 3 0 2 4
DIGITAL IMAGE FUNDAMENTALS : Elements of a Digital image
67
Processing system – Structure of the Human eye – Image formation and
contrast sensitivity – Sampling and Quantization – Neighbours of a pixel – Distance measures – Photographic film structure and exposure – Film characteristics – Linear scanner – Video camara – Image processing applications. (4) IMAGE TRANSFORMS : Introduction to Fourier transform – DFT – Properties of two
dimensional FT – Seprability, Translation, Periodicity, Rotation, Avarage value – FFT algorithm – Walsh transform – Hadamard transform – Discrete Cosine transform. (4) IMAGE ENHANCEMENT : Definition – Spatial domain methods – Frequency domain
methods – Histogram modification technique – Neighbourhood averaging – Media filtering – Lowpass filtering – Averageing of multiple images – Image sharpening by differentiation and high pass filtering. (8) IMAGE RESTORATION : Definition – Degradation model – Discrete formulation –
Circulant matrices – Block circulant matrices – Effect of diagnolization of circulant and block circulant matrices – Unconstrained and constrained restorations – Inverse filtering – Wiener filter – Restoration in apatial domain. (8) IMAGE ENCODING : Objective and fidelity criteria – Basic encoding process – The
mapping – The quantizer – The coder- Differential encoding – Contour encoding – Runlength encoding – Image encoding relative to fidelity criterion – Differential pluse code modulation. (8) IMAGE ANALYSIS AND COMPUTER VISION : Typical computer vision system –
Image analysis techniques – Spatial feature extraction – Amplitude and Histogram features - Transform features – Edge detection – Gradient operators – Boundary extraction – Edge linking – Boundary representation – Boundary matching – Shape representation. (10)
Total 42
REFERENCES
1. Rafael C Gonzalez., and Richard Eugene Woods, “Digital Image Processing” , Prentice Hall 2007. 2. Anil K Jain., “Fundamentals of Digital Image Processing” Prentice Hall, 2005. 3. Kenneth R Castleman, “Digital Image Processing”, Tsinghua University Press, 2003. LAB :
Using MATLAB 1. Obtain the histogram of a given image.
68
2. Add different types of noise to a given image and select an efficient filter to
get a clear image. 3. Image Segmentation using Boundary detection technique. 4. Image Segmentation using Edge linking technique. 5. Compress an image using a compression algorithm.
09XTE2 DATA COMPRESSION 3 0 2 4
DATA COMPRESSION LEXICON: Introduction to Data Compression - Dawn Age -
Coding - Modeling - Ziv and Lampel- Lossy Compression (4) MINIMUM REDUNDANCY CODING (THE DAWN AGE): The Shannon - Fano
Algorithm, The Huffman Algorithm - Into the Huffman Code : Counting the Symbols, Building the tree - Compression Code. (4) ADAPTIVE HUFFMAN CODING: Adaptive Coding - Updating the Huffman Tree -
The Code. (4) ARITHMETIC HUFFMAN CODING: Arithmetic Coding - The Code. (6) STATISTICAL MODELING: Higher-order Modeling - Finite Context Modeling -
Adaptive Modeling – Highest - Order Modeling. (4) DICTIONARY-BASED COMPRESSION: Static Vs Adaptive - Israeli roots – ARC. (4) SLIDING WINDOW COMPRESSION: The Algorithm - LZSS Compression - The Code - Compression Code. (4) LZ78 COMPRESSION: Compression – Decompression.
(4) SPEECH COMPRESSION: Digital Audio Concepts - Lossless Compression of Sound. (4) VIDEO COMPRESSION: JPEG Compression - Implementing DCT - Complete Code
Listing. (4) Total 42
REFERENCES
69
1. Mark Nelson, "The Data Compression Book", BPB Publications, 2003
2. Khalid Sayood, “Introduction to Data Compression”, Morgan Kaufmann, 2003 3. Yun Q Shi, Huifang Sun, “ Image and Video Compression for Multimedia Engineering”, CRC Press, 2008. 4. David S Tanbman and Michael W Marcellin, “ JPEG – 2000 Image Compression Fundamentals, Standards and Practice” Kluwer Academic, 2002. LAB 1. Implement Shannon Fano algorithm and Huffman algorithm. 2. Design compression and decompression program using adaptive Huffman
coding. 3. Implement arithmetic coding algorithm. 4. Design compression program using statistical modeling upto 3 order. 5. Design compression and decompression program using L277 algorithm
09XTE3 COMPUTATIONAL GEOMETRY 3 0 2 4
PRELIMINARIES: Mathematical and geometric review. Review of algorithm analysis
techniques - Mathematical models of computation - Randomized algorithms and probabilistic analysis techniques - Representation of basic geometric objects, convexity, polytopes. (3) GEOMETRIC SEARCHING: Point location, interval and segment trees, data
structures for nearest neighbors, range searching, multi-dimensional search trees. (6) CONVEX HULLS: Problem Statement and Lower Bounds - Convex Hull Algorithms
in the Plane - Graham's Scan - Jarvis's March -QUICKHULL techniques -Dynamic Convex Hull - Convex Hull in 3D. (8) PROXIMITY PROBLEMS: Closest pair, Voronoi diagrams and Delaunay
triangulations, relationship to convex hulls, and applications. (8) INTERSECTION PROBLEMS: Planar Applications - Intersection of Convex
Polygons, Star-shaped Polygons; Intersection of Line Segments, 3D Applications - Intersection of 3D Convex Polyhedra; Intersection of Half-spaces (5) VISIBILITY AND SHORTEST PATH PROBLEMS: Visibility graphs and their uses - Euclidean minimum spanning trees - Shortest path problems. (4)
70
ARRANGEMENTS: Line, hyperplane, and line segment arrangements -
Incremental construction techniques - Complexity of lower envelopes - Duality. (4) APPLICATIONS: Computer Graphics – Geographic Information System – Robot Motion Planning – Scientific Computing.
(4)
Total 42 REFERENCES 1. Berg M de , Van Kreveld M, Overmars M, and Schwarzkopf O, “ Computational Geometry: Algorithms and Applications”, Springer Verlag, 2000. 2. Preparata F P, Shamos M I, “ Computational Geometry: An Introduction ”, Springer Verlag, 1993. 3. Joseph O'Rourke, “Computational Geometry in C”, Cambridge University, 1998. 4. Goodman J E and O'Rourke J “ Handbook of Discrete and Computational Geometry”, CRC Press , 2004. LAB:
1. Randomized algorithms and probabilistic analysis techniques. 2. Convex Hull Algorithms in the Plane. 3. Line, hyperplane, and line segment arrangements.
4. Geographic Information System. 5. Robot Motion Planning.
09XTE4 QUANTUM COMPUTING 3 0 2 4
MATHEMATICAL BACKGROUND: Complex numbers, Boolean algebra, Logic gates, Hilbert spaces, Matrices, Unitary maps. (3) BASIC PROBABILITY THEORY: Probability space - Events - Random Variables-
Distributions - Conditional probability - Conditional expectation and variance – Markov / Chebychev / Chernoff-inequalities. (4) ELEMENTARY QUANTUM PHYSICS: Qubits - Entanglement - Evolution of quantum
systems - Measurement, Quantum gates and networks. (7) APPLICATIONS: Bell States - Superdense Coding - No-Cloning Theorem - Quantum
Teleportation. (4)
71
ALGORITHMS: Resources for classical and quantum computing - Deutsch-
Jozsa algorithm - Phase Estimation - Quantum Fourier transform – Eigen-Value Estimation - Shor‟s factoring algorithm; Amplitude amplification - Grover‟s searching algorithm; Proving complexity lower bounds for quantum computers. (14) CRYPTOGRAPHY: Classical one-time pad - Quantum one-time pad, Quantum key distribution. (6) ERROR CORRECTION: Classical repetition codes - Three-qubit code, Nine-qubit
code. (4)
Total 42 REFERENCES 1. Michael A Nielsen and Isaac L Chuang, “ Quantum Computation and Quantum Information”, Cambridge University,2000. 2. Giuliano Benenti, Giulio Casati and Giuliano Strini, “ Principles of Quantum Computation and Information”, World Scientific, 2004. 3. Loan Burda, „Introduction to Quantum Computation”, Universal Publishers, 2005 4. Michel Le Bellac, “ A Short Introduction to Quantum Information and Quantum Computation”, Cambridge University, 2006. LAB
1. Eigen value estimation - Power method to find dominant eigen value 2. Generation of Quantum key 3. Implement three qubit code, nine qubit code
09XTE5 WAVELET TRANSFORMS AND APPLICATIONS
3 0 2 4
CONTINUOUS WAVELET TRANSFORM: Introduction – Continuous Time –
Frequency representation of signals – Uncertainty principle and Time - frequency tiling. (8) DISCRETE WAVELET TRANSFORM: Introduction – Haar scaling functions and
Function spaces – Haar wavelet function - Orthogonality – Normalization of Haar Bases at different scales – Relation to filter banks: – MRA – signal decomposition (analysis) - Signal reconstruction (synthesis) (12) BIORTHOGONAL WAVELETS: Introduction – Biorthogonality in vector space –
Biorthogonal wavelet systems – Biorthogonal analysis – Biorthogonal synthesis –
72
Construction of Biorthogonal wavelet systems (8)
LIFTING SCHEME: Introduction – Geometrical foundations of lifting scheme – Linear
wavelet transform using lifting. (6) APPLICATIONS: Image Compression – Denoising – Computer graphics.
(8)
Total 42
REFERENCES
1. Sidney Burrus C, Ramesh A Gopinath and Haitao Guo, “Introduction to Wavelets and Wavelet transforms - A primer”, Prentice Hall, 1998.
2. Raghuveer M Rao and Ajit S Bopardikar, “Wavelet transforms – Introduction to theory and applications”, Addison Wesley, 2000.
3. Soman K P and Ramachandran K I, “Insight into wavelets from theory to practice”, Prentice Hall, 2004.
4. Mallat S, “A wavelet tour of signal processing”, Academic, 1998. 5. Agostino Abbate and Casimer M Decusatis, “Wavelets and subbands:
Fundamentals and applications”, Birkhauser, 2002. 6. Jensen A, Cour-Harbo and Anders la, “Ripples in Mathematics – The Discrete
Wavelet Transform”, Springer, 2001. LAB Implementation of various wavelet applications
1. Implement soft and hard thresholdings.
2. Estimate noise of 1-D wavelet coefficients.
3. Single level and Multi level 2-D wavelet decompositions and reconstructions.
4. Implementation of filter bank trees.
5. Using wavelets to remove noise from signals.
6. Using wavelets to remove noise from images.
7. Using wavelets to compress images.
8. Implement wavelet packet analysis.
9. Compression and denoising a signal using wavelet packets.
10. Compressing an image using wavelet packets.
09XTE6 ALGORITHMIC BIOINFORMATICS
3 0 2 4
INTRODUCTION: Biological data, DNA,RNA, Amino acids, Protein, Structural
73
databases, genomes, Central dogma- Molecular Biology, Prediction of
molecular function and structure. (6)
SEQUENCE COMPARISON ALGORITHMS: Dynamic Programming Algorithms, Edit Distance and Alignments, Alignment with Gap Penalties, Spliced Alignment, Similarity-Based Approaches to Gene Prediction, Multiple Alignment, HMM, Profile HMM Alignment, Viterbi Algorithm, Randomized Algorithms-Gibbs sampling, Genetic, Expectation Maximization Algorithm. (10)
EXHAUSTIVE SEARCH ALGORITHMS: Repeat finding Hash tables, Exact, approximate, combinatorial pattern matching, profile search, Motifs, Motif finding using Greedy algorithm, Dynamic Programming Algorithms, Divide-and-Conquer Algorithms, Keyword Trees, Suffix Trees, Heuristic Similarity Search Algorithms, BLAST: Sequence against a Database . (10)
GRAPH BASED ALGORITHMS: Shortest superstring problem – sequencing by
hybridization – SBH as a Hamiltonian path problem – SBH as an Eulerian Path problem – Fragment assembly in DNA sequencing – Protein sequencing and Identification. (6)
CLUSTERING ALGORITHMS: Support Vector Machine, Ant Colony Algorithm,
Clustering and Trees, Hierarchical Clustering, k- Means Clustering, Evolutionary Trees, Distance-Based, Additive Matrices, parsimony Tree Reconstruction. (10)
Total 42
REFERENCES
1. Neil Jones & Pavel Pevzner, “An Introduction to Bioinformatics Algorithms”, MIT Press, 2004. 2. Jonathan Pevsner, "Bioinformatics and Functional Genomics", John Wiley & Sons, 2003. 3. Mount, “ Bioinformatics: Sequence and Genome Analysis”, Cold Spring Harbor Laboratory Press, 2004. LAB
1. Motif Finding. 2. Sequence Comparison. 3. Searching biological databases. 4. Applications of HMM. 5. Finding SBH using Hamilton cycle / Eulerian Path.
74
6. Implementation of some clustering algorithms.
09XTE7 RANDOMIZED ALGORITHMS 3 0 2 4
INTRODUCTION: Examples of randomized algorithm, models of computational, Las Vegas and Monte Carlo algorithms, Complexity classes, min-max principle. (6) MOMENT AND DEVIATION: Linearity of expectation, Markov and Chebyshev inequalities, occupancy problem, randomized selection, coupon collector‟s problem (4) TAIL INEQUALITIES: The Chernoff bound, routing and wiring problem (2) PROBABILISTIC METHODS: Deletion methods, random graphs, expanders,
Lovasz, local lemma. (4) MARKOV CHAINS AND RANDOM WALKS: Markov chains, random walks, electric
networks, rapidly mixing markov chains, random walks on expanders (6) DATA STRUCTURES: Randomized search trees, hashing, skip lists.
(4) GRAPH ALGORITHMS: Shortest paths, minimum spanning trees, min cut, independent sets, dynamic graph algorithms (4) GEOMETRIC ALGORITHMS: Random sampling, randomized incremental
algorithms, linear programming (4) APPROXIMATE COUNTING: Monte carlo methods, approximating the permanent, volume estimation. (2) ONLINE ALGORITHMS: Paging problem, k-server problem, adversary models.
(2) NUMBER THEORETIC ALGORITHMS: Groups and fields, quadratic residues, RSA cryptosystem, polynomial roots and factoring, primality testing (2) DERANDOMIZATION: K-wise independence, probabilistic methods, discrepancy, derandomization in parallel (2)
Total 42
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REFERENCES 1. Motwani R and Raghavan P: “ Randomized Algorithms”, Cambridge University Press, 1995. 2. Grimmett G and Stirzaker D, “ Probability and Random Processes” Oxford University Press, 2006 3. Noga Alon and Spencer J,”The Probabilistic Method‟”, Wiley, 2000 4. Mulmuley K,” Computational Geometry: An Introduction Through Randomized Algorithms”, Prentice Hall, 1994 5. Michael Mitzenmacher and Eli lipfal “Probability & Computing: Randomized
Algorithms and Probabilistic Analysis” Cambridge University Press, 2005 LAB
1. Implement algorithms to generate Pseudo random numbers and Quasi random numbers. Integrate the latter with Moute Carlo methods.
2. Experiment on the solution of a mathematical problem using Markov Chains. 3. Implement the shortest path and minimum spanning trees algorithms with a
graphical interface and output. 4. Demonstrate the application of an RSA Crypto system. 5. Implement the K-server on-line algorithms. 6. Implement the insertions and deletions in randomized search trees.
09XTE8 ADVANCED COMPUTER GRAPHICS
3 0 2 4
GEOMETRICAL TRANSFORMATIONS: 2D Transformations- Homogeneous Coordination and metric representation – Composition of 2D transformations – Window to view port transport, Efficiency- Matrix representation of 3D transformations – Composition of 3D transformation – Transformation as a change in coordinate system. (3) VIEWING IN 3D : Projections – specifying arbitrary 3D viewing – The Mathematics
of planar geometric projections – implementing planar geometric projections, Coordinate systems. (3) OBJECT HIERARCHY : Geometric modeling- Characteristics of retained – mode
graphics packages – Defining and displaying structure – Modeling transformations, Hierarchical structure networks. (3) INPUT DEVICES – INTERACTION TECHNIQUES AND INTERACTION TASKS:
Interaction hardware – Basic interaction tasks – Composite interaction tasks. (3)
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DIALOGUE DESIGN : The form and content of user-computer dialogues – User
interface styles – Important design considerations – Modes and syntax – Visual design – The design methodology (3) USER INTERFACE SOFTWARE : Basic interaction – handling models - window
management systems – output handling in window systems – Input handling in windows systems – Interaction –technique toolkits – User-interface management systems. (3) REPRESENTING CURVES AND SURFACES : Polygon meshing – parametric cubic curves, Parametric bicubic surfaces, Quadric surfaces (3) SOLID MODELLING: Representing solids – Regularized Boolean set operations – Primitive instancing – Sweep representations – Boundary representations – Spatial – Partitioning representations – Constructive solid geometry – Comparison of representation – User interfaces for solid modeling. (3) ACHROMATIC AND COLORED LIGHT : Achromatic light – Chromatic color – Color Models for Raster Graphics – Reproducing Color – Using Color in Computer Graphics . (3) REALISM : Why realism? Fundamental difficulties – Rendering techniques for line drawing – Rendering techniques for shaded images – Improved object models – Dynamics – steropsis – Improved displays – Interacting with our other senses – Aliasing and antialiasing. (3) VISIBLE SURFACE DETERMINATION : Function of two variables – Techniques for efficient visible surface algorithms – Algorithms for visible line determination – The z-buffer algorithm – List – priority Algorithm – Area subdivision algorithms – Algorithms for octrees – Algorithms for curved surfaces – Visible ray tracing. (3) ILLUMINATIONS AND SHADING : Illumination models – Shading models for polygons – Surface detail – Shadows – Transparency – Inter object reflections – Physically based illumination models – Extended light sources – Spectral sampling – Improved camera model – Global Illumination algorithms – Recursive ray tracing – Radiosity methods – The rendering pipeline. (3) IMAGE MANIPULATION AND SHADING : What is an image ? Filtering – Image
Processing – Geometric transformations of Images – Multipass transformation – Image Composition – Mechanism for Image Storage – Special Effects with images (3)
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ANIMATION : Conventional and Computer assisted Animation – Animation
languages – Methods of controlling animation - Basic rules of animation – Problems peculiar to animation. (3)
Total 42 REFERENCES 1. Foley James D, Vandam Andries and Hughes John F, "Computer Graphics : Principles and Practice", Pearson Education, 2002. 2. Donald Hearn and Pauline Baker M, “ Computer Graphics” , Pearson Education, 2002. 3. Rankin John R, "Computer Graphics Software Construction", Prentice Hall, 1989. LAB
Implement the following using the OpenGL in VC++
1. Using glReeti function, draw
a) A flurry b) A checkerboard 2. Write the window to view port mapping functions, and use it to draw the since
curve in real world 3. coordinates. 4. Using user defined line To and move To functions, plot the Fibonacci series. 5. Write the Canvas class and it‟s supporting classes. Use the Canvas class to draw
a simple meander. 6. Write functions to change the background and foreground colors. 7. Write a function to draw an n-sided polygon (using the basic Canvas class and
line To and move To functions) 8. Write a program to draw the Sierpinski gasket. 9. Write a program to draw the graph of a given mathematical function f(x). 10. Write a program to read a data file that contains a collection of Polylines in the
appropriate format and draw each polyline. 11. Write a parameterized function to display a house and call it a number of times by
passing different values to form a village. 12. Write a program that displays a colored triangle and rectangle and rotates them at
different angles along two axis.
09XTE9 MULTI PARADIGM PROGRAMMING LANGUAGES 3 0 2 4
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INTRODUCTION: The need for multiple paradigms – Terms and concepts
Design, Analysis, Domains and Families – Commonality and variability analysis - Multi-paradigm design and programming languages. (4) COMMONALITIES ANALYSIS: The essences of Abstraction - Priming Analysis – Dimensions of Commonality and Commonality Categories - Commonality and Evolution –Examples (8) VARIABILITY ANALYSIS: The Spice of life – The commonality base – Positive and negative variability – The domain and range of variability – Binding time – Variability tables , traps, review and dependency. (8) APPLICATION AND SOLUTION DOMAIN ANALYSIS: The big picture analysis,
Domain analysis and beyond – Sub domains in domain analysis. C++ Solution domain overview. (8) MIXING AND WEAVING PARADIGMS: An overview of multi-paradigm design and
activities. Method and design paradigm weavings - Dimensions of Variability and commonality analysis – Codependent design – Design and Structures. Management issues - Augmenting solution design with patterns. (10) Multi-paradigm programming languages and Programming in C++ and Oz and case – Studies Text editor and language translator. (4)
Total 42 REFERENCES
1. James O Coplien, “Multi-Paradigm Design for C++”, Addison Wesley, 1998. 2. Peter Van Roy and Seif Hasidi, “ Concepts Techniques and Models of Computer Programming”, The MIT Press, 2004 3. Czarnecki and Eisenecker, “ Generative Programming”, Addision Wesley, 2001. LAB
Implementation of Multi paradigm programming concepts using Standard C++
1. Implementation of Abstraction using classes and templates.
2. Implementation of Generic programming : Containers.
- Reading and sorting integers and floating point numbers
- Function objects
3. Implementation of class hierarchies and interfaces. 4. Implementation of Multiprogramming paradigm. - handling polymorphic objects.
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09XTEA WIRELESS NETWORKS 3 0 2 4
WIRELESS FUNDAMENTALS: Spectrum Allocations – Propagation Modeling –
Modern Communications Systems – Multiple Access – Cellular and Ad-hoc-Concepts. (5) WLAN TECHNOLOGIES: System Architecture – 802.11 PHYs – 802.11 MAC –
WPA and 802.11i: Security – 802.11e: MAC Enhancements for Quality of Service – Related Wireless Standards (Hyperlan, HomeRF, Bluetooth, Zigbee, Wireless USB). (12) NETWORK HARDWARE AND SOFTWARE; Switches (Ethernet, ATM/MPLS, IP) –
Routers (IP, layer 7, etc.) – Network software basics (OS, drivers, protocols, management) – Socket programming introduction. (10) WLAN DEPLOYMENT ISSUES: Interference – Resource Allocation – Network
Planning, Deployment and Analysis – Performance Tuning – Network Monitoring. (8) FUTURE TRENDS: Emerging WLAN Related Technologies – 802.11 Trends –
Cellular – 802.16 – 802.20 – 802.22 – UWB, Cognitive Radios, Sensor Networks, RFID – 4G and Data Communications Convergence. (7) Total 42 REFERENCES
1. Steve Rackley, “ Wireless Networking Technology” , Newnes, 2007. 2. Papadimitriou G I, Pomportsis A S, Nicopolitidis P, and Obaidat M S, “Wireless Networks”, John Wiley and Sons, 2003. 3. Matthew Gast, “802.11 @ Wireless Networks: The Definitve Guide”, O‟ Reilly, 2002. LAB 1. Study of NS-2 simulator. 2. Simulation of a IEEE 802.11 LAN under various conditions using NS-2 simulator (varied number of nodes, traffic rates, and contention window size). 3. Simulation of a priority MAC protocol using NS-2 simulator. 4. Simulation of TCP over error-prone wireless network using NS-2 simulator. 5. Development of Mobile application using blue tooth.
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09XTEB PROGRAM SEMANTIC ANALYSIS
3 0 2 4
INTRODUCTION: A Simple Imperative Programming Language - Notion of state of a
program in execution (process) using Finite State Transition diagrams - using first-order logic formulae – Operational semantics and denotational semantics. (4) ANALYZING ASSIGNMENT STATEMENTS: Deriving strongest postcondition from a
given pre-condition - and deriving weakest pre-condition from a given post-condition. Dealing with loops: loop invariants - Appropriateness of loop-invariants for proving desired - Post-conditions of programs – Abstract syntax and semantics of loop in ML – Parsing loop. (8) FORMAL INTRODUCTION TO HOARE LOGIC: syntax and semantics - Notions of partial and total correctness - Axioms and basic inference rules for partial correctness proofs in Hoare logic. (6)
FIXPOINT THEORY: Undefined operations and infinite loops – Recursively defined mappings – Continuous functions and strict extensions of functions. (4)
STRENGTHENING AND WEAKENING OF CONSTRAINTS: Weakest pre-conditions and strongest post-conditions - using Hoare logic proofs - Incompatibility of the strongest loop invariant in sequential programs- reduction from halting problem of Turing machines - Translating programs (with recursive function calls) manipulating variables of finite-domain types to push-down automata. (6)
ANALYSIS OF PROGRAMS WITH VARIABLES OF FINITE-DOMAIN TYPES:
Reducing proof obligations in Hoare logic to state Reachability in an appropriate push-down automaton (PDA) - Deciding state Reachability in PDA by checking non-emptiness of an appropriate context-free language - PDA and CFG based techniques for proving properties of programs. (4) Operational semantics – Proof-theoretical semantics – Declarations of data structures – Procedures and functions – Objects and classes – Continuations and jumps. (6) TRANSLATING PROGRAMS: The Formal language to corresponding Boolean
programs - Semantics preserving syntactic transformations. Translating assignment statements in original program to parallel assignments to predicate-tracking Boolean variables in a Boolean program- Translating procedure call-free programs in a C-like language to Boolean programs. Discovering traces of a Boolean program from corresponding push-down automaton or context-free grammar. (4)
Total 42 REFERENCES 1. Michael Huth and Mark Ryan,”Logic in Computer Science:
81
Modeling and Reasoning about Systems” , Cambridge University
Press, 2004 2. Bjorn Kirkerud, “Programming language semantics: Imperative and object oriented languages”, Thomson computer press, 1997. 3. Glynn Winskel, “ Formal Semantics of Programming Languages”, MIT Press, 1993. LAB
1. Study on using a static checkup for the verification of code written in a high level Programming Languages.
2. Implementation of Algebraic semantics. 3. Implementation of fixed point identity in recursion in the Lambda calculus. 4. Implementation of action semantics of a calculator. 5. Formal verification using Hoare Logic with updates for a simple while – language. 6. Proving Program correctness with Hoare‟s Logic for programs with procedures.
09XTEC NETWORK MANAGEMENT 3 0 2 4
NETWORK MANAGEMENT ARCHITECTURES & APPLICATIONS: Management
Standards and Models - Network Management Functions -Configuration Management & Auto-discovery - Configuration Database & Reports - Abstract Syntax Notation One (ASN.1) (5) SNMP : SNMP v1 - Structure of Management Information -Std. Management
Information Base (MIBs) -SNMPv1 Protocol -Network Management Functions (5) FAULT MANAGEMENT: Fault Identification and Isolation - Event Correlation
Techniques - SNMP v2 - Version 2 Protocol Specification -Version 2 MIB Enhancements -MIB-II - SNMP v3 - Version 3 Protocol & MIB - Network Management Functions. (7) SECURITY MANAGEMENT: Functions - Protecting Sensitive Information - Host and
User Authentication - Key Management - User Based Security Model - View Based Access Model. (5) ACCOUNTING MANAGEMENT: Performance Management - Network Usage,
Metrics and Quotas. (2)
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REMOTE NETWORK MONITORING: RMON 1 - Statistics Collection - Alarms
and Filters - Remote Network Monitoring RMON 2 - Monitoring Network Protocol Traffic. (6) MANAGEMENT TOOLS: Application-Layer Visibility - Management Tools, Systems and Applications -Test and Monitoring Tools - Integrating Tools - Development Tools - Web-based Enterprise Management - XML based network management – Distributed Network Management – NMS software features and Design. (7) DHCP: DHCP configuration - Implementing DHCP -Managing and Monitoring DHCP - Implementing Name Resolution Using DNS - Managing and Monitoring DNS - Implementing and Managing Software Update Services. (5)
Total 42 REFERENCES 1. William Stallings, “SNMP, SNMPv2, SNMPv3 and RMON 1 and 2”, Addison
Wesley, 1999. 2. D.E. Comer, “Internetworking with TCP/IP Vol- III”, (BSD Sockets Version),
Prentice Hall of India, 2003. 3. David Zelsterman, A practical guide to SNMPv3 Network Management”, Prentice
Hall , 1999. LAB 1. Study of security features and Networking commands in Windows Environment 2. Configuration of a server in a LAN Environment. 3. Packet Sniffing. 4. Study of MIB tools. 5. SNMP dataframe detection by clients – study of a SNMP tools (Oputils). 6. Tool Based Testing of Network Management Software.
09XTED SEMANTIC WEB
3 0 2 4
INTRODUCTION TO SEMANTIC WEB: Today‟s Web - From Today‟s Web to the
Semantic Web - Examples - Semantic Web Technologies - A Layered Approach. (4) DESCRIBING STRUCTURED WEB DOCUMENTS USING XML: Introduction to
Markup Languages - The XML Language - Structuring - Namespaces - Addressing and Querying XML Documents - Processing. (8) DESCRIBING WEB RESOURCES IN RDF: Introduction to RDF - Basic Ideas - RDF: XML-Based Syntax - RDF Schema: Basic Ideas - RDF
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Schema - An Axiomatic Semantics for RDF and RDF Schema - A Direct
Inference System for RDF and RDFS - Querying in RQL. (9) WEB ONTOLOGY LANGUAGE: OWL Introduction - The OWL Language -
Examples - OWL in OWL - Future Extensions. (8) LOGIC AND INFERENCE: Introduction - Example of Monotonic Rules: Family Relationships - Monotonic Rules: Syntax - Monotonic Rules: Semantics - Nonmonotonic Rules: Motivation and Syntax - Example of Nonmonotonic Rules - Rule Markup in XML for Monotonic Rules - Rule Markup in XML for Nonmonotonic Rules. (8) APPLICATIONS: Horizontal Information Products - Data Integration - e-Learning - Web Services - Other Scenarios. (3) ONTOLOGY ENGINEERING: Constructing Ontologies Manually - Reusing Existing
Ontologies - Using Semiautomatic Methods - On-To-Knowledge Semantic Web Architecture. (2)
Total 42 REFERENCES 1. Breitman K K, Casanova M A and Truszkowski W, “Semantic Web: Concepts,
Technologies and Applications”, Springer, 2007. 2. Grigoris Antoniou and Frank van Harmelen, “A Semantic Web Primer”, The MIT Press Cambridge, Massachusetts London, England, 2004. 3. John Davies, Dieter Fensel & Frank van Harmelen, “Towards the Semantic Web”, Wiley , 2002.
LAB :
1. Generate XML data directly from the SQL server & display it on the web page neatly formatted.
2. Creating XML DTD and XSD for the given XML document. 3. Design a XSLT to display the XML document (given as input) based on the
constraints given. 4. Generate an RDF graph. 5. Convert a relational Database into RDF:
a. According to the value-based mapping. b. According to the URI-based mapping.
c. According to the object-based mapping.
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6. Create an RDFS ontology (in triple or graph notation)
7. Write an RDF/XML encoding for the given situation. 8. A Package to implement the techniques learnt.
09XTEE PERVASIVE COMPUTING 3 0 2 4
INTRODUCTION: Pervasive Computing – Principles – Pervasive Computing Applications – Pervasive Information Technology – Pervasive Information Access Devices – Smart Identification, Smart card, labels, tokens – Embedded Controls, Smart Sensors, Actuators, Appliances, Home Networking, Entertainment – Pervasive Application Development Software – Operating System, Windows CE, Palm OS, Symbian OS, Java Card – Middleware – Security – Connecting the World, WWAN, SRWC, DECT, Bluetooth, IrDA – Mobile Internet – Internet Protocols. ( 6 ) PERVASIVE APPLICATION DEVELOPMENT: Approaches for Developing
Pervasive Applications – Developing Mobile Applications – Presentation Transcoding – Device Independent View Component – Heterogeneity of Device Platforms – Dynamics of Application Environment – ISAM Application Model – ISAM Architecture – Context Awareness and Mobility to Building Pervasive Applications. ( 8 ) LOCATION MANAGEMENT: Introduction to Location Management – DNS Server, Server Process, Client Process – Location Update – Location Inquiry – Location Management Cost – Network Topology – Mobility Pattern, Memory Less Movement Model, Markovian Model, Shortest Distance Model, Gauss-Markov Model, Activity Based Model, Mobility Trace, Fluid-Flow Model, Gravity Model. ( 8 ) LOCATION UPDATES AND LOCATING MOVING OBJECTS: Location Update
Strategies, Always update, Never-Update, Time Based, Movement Based, Distance Based Update Strategies – Architecture of Location Directories, Two-Tier Scheme, Hierarchical Scheme – Optimization of the Architecture – Taxonomy and Location Management Techniques – Case Studies. ( 10 ) LOCATION BASED SERVICES: Introduction – Research on Location Based
Services – Location Relatedness and the Query Model - Location Dependent Data – Location Aware Queries – Location Dependent Queries – Moving Object Database Queries – Query Classification – Query Translation Steps in LDQ Processing – Case Studies. ( 10 )
Total 42
REFERENCES
1. Mohammad Ilyas, Imad Mahgoub, “Mobile Computing Handbook”, Auerbach Publications, 2005.
2. Horst Henn, Jochen Burkhardt, and Thomas Schack, “Pervasive Computing”, Pearson Education, 2007.
85
3. Uwe Hansmann, Martin S. Nicklous, and Thomas Stoper, “Pervasive
Computing Handbook”, Springer-Verlag, 2001. 4. Uwe Hansmann, Martin S. Nicklous, and Thomas Stoper, “Principles of Mobile
Computing”, Springer-Verlag, 2001. LAB
1. Implement the algorithms to model and develop the location dependent services. 2. Implement storage and retrieval in mobile and spatial databases. 3. Design and implement the location relatedness and the query model, Location
Dependent query Model, Location Aware queries and moving object database queries.
4. Design and Implement the query classification and query transition in LDQ processing.
5. Develop a package
09XTEF NETWORK ALGORITHMICS 3 0 2
4 INTRODUCTION: Algorithms Vs Algorithmics – What network algorithmics is about
– Network bottlenecks – Endnode bottlenecks – Router bottlenecks – characteristics of network algorithmics . (4) NETWORK IMPLEMENTATION MODELS: Protocols - Hardware - Network device
architectures – Operating System Implementation Principles – System Principles – Principles for modularity and efficiency – Principles for speeding up routines – Principles in action. (8) ENDNODE ALGORITHMICS: Copying data – Transferring Control – Maintaining
timers – Protocol Processing. (7) ROUTER ALGORITHMICS: Exact match lookup – Prefix match look ups – Packet
Classification – Switching – Scheduling packets – Computing traffic matrices. (15) NETWORK SECURITY: Searching for multiple strings in packet payloads – IP trace
back via probabilistic marking and logging – Detecting worms. (8) Total 42 REFERENCES 1. George Varghese, “Network Algorithmics, An Interdisciplinary
86
Approach to Designing Fast Networked Devices”, Morgan Kaufmann, 2006.
2. Michal Pioro and Deepankar Medhi, “ Routing Flow and Capacity Design in Communication and Computer Networks”, Morgan Kaufmann, 2007. 3. James D McCabe, “Network Analysis, Architecture and Design”, Morgan Kaufmann, 2007. 4. Panos C Lekkas, “Network Processors, Architectures, Protocols and Platforms”, Telecom Engineering, 2008. LAB
1. Implementation of CRC using a fast implementation technique. 2. Implementation of IP prefix lookup using lulea tries. 3. Implementation of binary search on prefixes 4. Implementation of packet classification using linear search 5. Implementation of packet classification using set pruning trees 6. Implementation of decision trees approach for packet classification. 7. Implementation of packet scheduling algorithms. 8. Implementation of Aho Corasick algorithm.
09XTEG SOFTWARE PATTERNS
3 0 2 4
INTRODUCTION : Reusable Software – Reusable object oriented software –
Patterns – Definition – Overview & motivation – categories – relationship between patterns – pattern description - Architecture Patterns : From Mud to Structure - Layers - Pipes and Filters - Blackboard - Distributed systems - Broker - Interactive Systems : Model View Controller (MVC) – Presentation Abstraction Control - Adaptable Systems : Reflection – Microkernel (13) DESIGN PATTERNS : Creational pattern : Abstract factory – Builder – Factory
method – Prototype – Singleton - Structural patterns Adapter – Bridge – Composite – Decorator – Façade – Flyweight – Proxy – Behavioral patterns – Command – Interpreter – Iterator – Mediator – Memento – Observer – State – strategy – Template method – Visitor. (13) STRUCTURAL DECOMPOSITION : Whole-part – Organization of work : Master
slave – Management : Command processor – Communication : Forwarder Receiver – Dispatcher Server – Publisher subscriber - IDIOMS
(8) Antipatterns in Software development, software architecture, software project management – Pattern mining. (2) CASE STUDY : Document Editor – Web browser – Binary Tree – Parsing – Arrays &
Stacks – Thread specific storage manager – sort utility (6)
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Total 42
REFERENCES
1. Frank Buschman, Regine Meunier, Hans Rohnert, Petersommerlad and Michael Stal, “Pattern-Oriented Software Architecture: A System of Patterns”, John Wiley and Sons, 2006 2. Erich Gamma, Richard Helm, Ralph Johnsons and John Vlissides, “Design Patterns: Elements of Reusable Object- Oriented Software”, Addison Wesley, 2006. 3. Steven John Metsker and William C Wake, “Design Patterns in Java”, Addison Wesley, 2006 4. James William Cooper and James Cooper, “Java Design Patterns : a Tutorial”, Addison Wesley, 2005 5. Mary Shaw and David Garlan, “Software Architecture”, Prentice Hall Edition, 2001 6. William J Brown, Hays W McCormick III and Scott W Thomas, “Antipatterns in Project Management”, John Wiley and Sons, 2003 7. Alan Shalloway and James Trott, “Design Patterns Explained: A New Perspective on Object-Oriented Design”, Addison Wesley, 2004. LAB
Study of Software patterns by developing applications using advanced Patterns 1. Arrays and stacks 2. Thread specific 3. Storage manager 4. Sort Utility 5. Parsing 6. Binary Tree 7. Document Editor. 8. Digital Clock and Analog clock 9. Representation of data in various formats (Bar chart, Pie chart and Table)
09XWAN GRID COMPUTING 3 0 2 4
INTRODUCTION: High performance computing, cluster computing, meta computing, peer to peer computing, Internet computing, Grid computing – Types
88
of grids – The grid: past, present, future - Grid applications.
(5) GRID COMPUTING TECHNOLOGY: Evolution of the grid – Desktop Grids – Cluster
grids – HPC grids – Computational and Data Grids. (5) THE ANATOMY OF THE GRID: Virtual organizations – Grid architecture and its
relationship to other distributed technology – autonomic computing – Service virtualization – infrastructure and its applications. (7) THE OPEN GRID SERVICES ARCHITECTURE AND INFRASTRUCTURE:
Evolution to OGSA, Physiology of the Grid : OGSA Infrastructure – OGSA Basic services, Creating and Managing grid services, Managing grid environments – grid –enabling software applications, Grid Enabling network services, Grid security, grid resource management and scheduling – High level introduction to OGSI, Technical details of OGSI specification. (10) GRID COMPUTING IN BUSINESS: Grid taxonomy – Departmental Grids –
Enterprise Grids – Open Grids and the Grid – Joining the Grid – Strategies for participation – Building an Enterprise Grid – Example – Software Release Engineering on the Grid – Grid enabling a solution – Grid Infrastructure provider – Service Provider on the Grid – example – Grid for Equipment Health Monitoring. (8) CASE STUDY: Globus toolkit – Architecture, programming model, sample
implementation, High level services. (7)
Total 42 REFERENCES: 1. Ahmar Abbas, “Grid Computing Practical Guide to Technology and Applications”,
Firewall Media, New Delhi, 2008.
2. Jan Foster and Coul Kesselman, ”The Grid: Blueprint for a New Computing
Infrastructure”, Morgan Kaufman, New Delhi 2006.
3. Fran Berman, Geoffrey fox and Anthony Hey J.G, „Grid Computing Making the
Global Infrastructure a Reality, Wiley USA, 2003.
4. Plaszczak P and R Wellner, “Grid Computing: The Savvy Manager‟s Guide”,
Elsevier, 2006.
5. Joshy Joseph and Craig Fellenstein, “ Grid Computing”, Pearson Education,
2007.
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LAB : 1. Set-up a mini-CA, issue a cert to X and Y and try to set-up an authentication
connection between the two. 2. Build a simple CA service to obtain certificates 3. Build a more scalable system, incorporating Registration Authorities and online
checking of the status of the certificates using an independent client program 4. Integrate on-line checks in a piece of middleware.
09XWA0 CLOUD COMPUTING
3 0 2 4
INTRODUCTION TO PARALLEL AND DISTRIBUTED COMPUTING: Distributed
computing models and technologies SOA, Web Services , Software as a Service (SaaS)- Virtualization-Parallelization (6) ADVANCED WEB TECHNOLOGIES: AJAX and Mashup. (4) INTRODUCTION TO CLOUD COMPUTING : Definition, History, Comparison of
Cloud Computing with Grid, Cluster and Utility Computing, Pros and Cons of Cloud Computing (4) VIRUTUALIZATION : Types of Virtualization, Tools for Virtualization, Architecture of VMM, Virtualization for Cloud. (4) MAP REDUCE PARADIGMS: Introduction, GFS Architecture, HDFS Architecture,
Hbase, Google big Table, Amazon‟s (key value) pair storage and Microsoft‟s Azure infrastructure, Map reduce programming examples. (10) CLOUD COMPUTING FRAMEWORK: Amazon EC3, S3 storage revises, Aneka
frame work, IBM blue Cloud. (7) APPLICATIONS: Distributed search engine and distributed data mining in the cloud. (7)
Total : 42
REFERENCES:
1. Liu M L, “Distributed Computing Principles and Applications”,
90
Pearson Education, New Delhi, 2005
2. Ron Schmelzer et al, ”XML and Web Services”, Pearson Education, New Delhi, 2002.
3. Chang et al, “Bigtable “A Distributed Storage System for Structured Data”, OSDI, 2006.
4. Dean J and Ghemawat S, “ MapReduce: Simplified Data Processing on Large Clusters” OSDI, 2004.
5. DeCandia et al G,” Dynamo Amazon‟s Highly Available Key-Value Store”, SOSP, 2007.
6. Ghemawat S, Gobioff H and Leung S T, ”The Google File System”, Proc. SOSP, 2003.
7. Kossmann D, ”The State of the Art in Distributed Query Processing”, ACM Computing Surveys”, 2000.
8. Weil S A, Brandt S A, Miller E L, Long D D E and Maltzahn C, ”Ceph: A Scalable, High-Performance Distributed File
9. System”, Proc. OSDI, 2006. 10. Fox A, Gribble S D, Chawathe Y, Brewer E A and Gauthier P, ”Cluster-based
Scalable Network Services”, Proceedings of the Sixteenth ACM Symposium on Operating Systems Principles, SOSP, 1997.
11. Gupta I, Chandra T D. and Goldszmidt G S, “On Scalable and Efficient Distributed Failure Detectors”, Proceedings of the Twentieth Annual ACM Symposium on Principles of Distributed Computing, PODC01, ACM Press, New York, 2001.
12. KubiatowiczJ, Bindel D, Chen Y, Czerwinski S, Eaton P, Geels D, Gummadi R, Rhea S, Weatherspoon H, WellsC, and Zhao, “ OceanStore: An Architecture for Global-Scale Persistent Storage”, SIGARCH Comput. Archit. News 28, 5, 2000.10.
13. Barroso et al, L Barroso, J Dean and Hoelzle U, "Web Search for a Planet: The Google Cluster Architecture," IEEE Micro, 2003.
14. Ghemawat et al, S Ghemawat, Gobioff H and Leung S T, "The Google File System," SIGOPS Oper. Syst. Rev, 2003.
15. Dean and Ghemawat, Dean J and Ghemawat S, "MapReduce: Simplified Data Processing on Large Clusters," presented at OSDI'04: Sixth Symposium on Operating System Design and Implementation, San Francisco, CA, 2004.
16. Bryant R E, "Data-Intensive Supercomputing: The Case for DISC," Technical report CMU-CS-07-128.
LAB :
1. Implement a distributed search engine. 2. Implement distributive data mining for an application.
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