B. TECH. FOUR YEAR DEGREE COURSE R18 - SVECW

B. TECH. FOUR YEAR DEGREE COURSE

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING

R18 – REGULATIONS, COURSE STRUCTURE & SYLLABUS

(Applicable for the batches admitted from 2018-19)

SHRI VISHNU ENGINEERING COLLEGE FOR WOMEN :: BHIMAVARAM

(Autonomous)

Approved by AICTE & Affiliated to JNTU-K, Kakinada

Accredited with ‘A’ grade by NAAC & NBA

Vishnupur, Bhimavaram -534202

West Godavari Dist., Andhra Pradesh, India

Email: [email protected], website: www.svecw.edu.in

SHRI VISHNU ENGINEERING COLLEGE FOR WOMEN:: BHIMAVARAM

(AUTONOMOUS)

VISION

Transform the society through excellence in Education, Community empowerment

and sustained Environmental protection.

MISSION

To achieve Academic excellence through innovative learning practices

To instill self confidence among rural students by supplementing with co-

curricular and extra-curricular activities

To inculcate discipline and values among students

To establish centers for Institute Industry partnership

To extend financial assistance for the economically weaker sections

To create self-employment opportunities and skill up gradation

To support environment friendly Green Practices

Creating innovation hubs


(AUTONOMOUS)

Department of Computer Science & Engineering

Vision To become a leader in providing academic excellence with career development skills

and research abilities in the area of Computer Science & Engineering.

Mission

To achieve Academic excellence through innovative learning practices

To prepare students to adapt to the challenges of an ever-changing market needs

To build necessary skills required for employability through career development

training

To create interest among students to pursue higher studies

To enrich students with good character, and high integrity to serve the society

To promote research and development in the frontier areas of Computer Science &

Engineering

To inculcate the spirit of moral values and discipline among students

ACADEMIC REGULATIONS

B.Tech. FOUR YEAR DEGREE COURSE

R18 Regulations

(Applicable for the batches admitted from 2018-2019)

SHRI VISHNU ENGINEERING COLLEGE FOR WOMEN : BHIMAVARAM (Autonomous)

Approved by AICTE & Affiliated to JNTUK, Kakinada

Accredited with ‘A’ Grade by NAAC & NBA

Vishnupur, Bhimavaram, West Godavari Dist., Andhra Pradesh, India. PIN - 534202

Email: [email protected], Website: www.svecw.edu.in

®

mailto:[email protected]

REGULATIONS THE DEGREE OF BACHELOR OF TECHNOLOGY - REGULAR

(With effect from 2018-19)

RB 0.0

TITLE AND DURATION OF THE COURSE

The course shall be called the degree course in Bachelor of Technology, abbreviated as B.Tech. The course shall be of four academic years duration divided into eight semesters, each semester having duration of minimum 16 weeks. The calendar of events in respect of the course shall be fixed by the Institute from time to time. The external examination in all the subjects shall be conducted at the end of each semester for all the eight semesters. Students joining the B.Tech . programme shall have to complete the programme in a stipulated time frame of 8 years from the date of joining a n d students joining the B.Tech. Programme in the third semester directly through Lateral Entry Scheme (LES) shall have to complete the programme in a stipulated time frame of 6 years from the date of joining otherwise; they shall forfeit their seat in B.Tech. Programme and their admission shall stand cancelled. The students who availed GAP years facility can complete the programme in 10 years.

When a student is detained for lack of credits / shortage of attendance, she may be re-admitted into the same semester / year in which she has been detained. However, the academic regulations under which she was first admitted shall continue to be applicable to her.

RB 1.0 ELIGIBILITY FOR ADMISSION

RB 1.1 Admissions are done as per the norms prescribed by Government. The Government orders issued from time to time in this regard shall prevail.

RB 1.2 The Candidate shall be an Indian National.

RB 1.3 The Candidate should have passed the qualifying examination, Intermediate or equivalent on the date of admission.

RB 1.4 Seats in each programme in the college are classified into CATEGORY-A (70% of intake) and CATEGORY – B (30% of intake) besides lateral entry.

RB 1.5

Category ‘A’ Seats shall be filled by the Convener, EAMCET Admissions. Category ‘B’ Seats shall be filled by the College as per the guidelines of Andhra Pradesh State Council of Higher Education. ‘Lateral Entry’ candidates (20% of the intake) shall be admitted into the Third semester directly based on the rank secured by the candidate in Engineering Common Entrance Test (ECET) in accordance with the instructions received from the Convener, ECET and Government of Andhra Pradesh.

RB 2.0 AWARD OF B.TECH. DEGREE

RB 2.1

A Student shall be declared eligible for the award of the B.Tech. Degree, if she pursues a course of study in not less than four and not more than eight academic years (plus maximum of 2 years of GAP years). A Student admitted into III semester shall be declared eligible for the award of the B.Tech. Degree, if she pursues a course of study in not less than three and not more than six academic years (plus maximum of 2 years of GAP years).

RB 2.2

Each discipline of the B.Tech. programme is designed to have a total of 160 credits and the student shall have to complete the courses and earn all credits as per the requirements for award of the degree. Students joining the B.Tech. programme in the third semester directly through Lateral Entry Scheme (LES) shall have to complete the courses, excluding first year courses and earn 124 credits as per the requirements for award of the degree.

RB 2.3

The B.Tech. Degree shall be conferred on a candidate who has satisfied the following requirements. A Regular student (four year programme) should register herself for 160 credits. In order to become eligible for the award of B.Tech. Degree, the student must obtain 160 credits. A Lateral Entry student should register herself for 124 credits and should obtain all the credits. However, it is mandatory for the students to complete the noncredit courses

RB 3.0 MINIMUM INSTRUCTION DAYS

RB 3.1 The minimum instruction days for each semester shall be 90 working days.

RB 4.0 COURSES OF STUDY

Branch Code- Branch Abbreviation 01-CE ( Civil Engineering ) 02-EEE ( Electrical and Electronics Engineering ) 03-ME (Mechanical Engineering ) 04-ECE ( Electronics and Communication Engineering ) 05-CSE ( Computer Science & Engineering ) 12-IT ( Information Technology )

RB 4.1

Groups of Courses: The Courses in the B.Tech. Programme is of five kinds: Core, Professional Elective, Open Elective, Free Elective and Mandatory Audit Course. Core Course: These are courses which are to be compulsorily studied by a student and it is the core requirement to complete the programme in a said branch. Professional Elective Course: A student can choose a course (subject) from a pool of courses of branch concerned, which add proficiency to the students. Open Elective Course: These are the courses offered by other branches. These courses are designed to lead to knowledge enhancement in multi disciplinary domains. Free Elective Course: A student can choose a course (subject) from a pool of courses of branch concerned, which add proficiency to the students. Mandatory Audit Course: These courses allow a student to attend classes without the benefit of a grade for a course. An undergraduate student who audits a course does so, for the purpose of self-enrichment and academic exploration.

RB 5.0 DISTRIBUTION AND WEIGHTAGE OF MARKS

RB 5.1

The performance of a student in each semester shall be evaluated subject wise with a maximum of 100 marks for theory and 75 marks for practical subject. The main project work shall be evaluated for 200 marks, Mini Project 1 and Mini Project 2 are evaluated each for 50 marks and seminar is evaluated for 50 marks.

RB 5.2

For theory subjects, the distribution shall be 40 marks for Internal Evaluation and 60 marks for the End Examinations.

RB 5.3

Internal evaluation 40 marks shall be awarded as follows: 20 marks for Descriptive, 10 marks for Quiz and 10 marks for Assignment. The descriptive examination is for 90 minutes duration conducted for 30 marks. Each descriptive examination question paper consists of three questions (either - or type) from three units. Three questions to be answered, one from each unit. The descriptive examination conducted for 30 Marks is to be brought down to total marks of 20. The quiz examination is for 20 minutes duration (Conducted with 20 multiple choice questions with a weightage of ½ Mark each). Thought provoking questions shall be covered in Quiz examination.

After every two Units, one Assignment/Tutorial shall be conducted. Two questions from each Unit and maximum of 4 questions must be set in Assignment. Assignment/Tutorial consists of Theory, Design, Analysis, Simulation, Algorithms, Drawing, etc. as the case may be. Out of the 3 Assignments / tutorials, average of best of the 2 Assignments shall be considered for awarding of marks.

For theory subjects, during the semester there shall be 2 MID tests. As the syllabus is framed for 6 units, the First MID examination (both descriptive and quiz) is conducted from first three units and Second MID examination (both descriptive and quiz) is considered from last three units of each subject. Average of two Mid tests (both descriptive and quiz) shall be considered as final marks of the MID. Eg: A student got 18 marks out of 20 marks in Descriptive-1, 8 marks out of 10 marks in Quiz-1 and 8 marks out of 20 marks in Descriptive-2 and 2 marks out of 10 marks in Quiz-2. Assignment-1 = 9 out of 10, Assignment-2 = 4 out of 10 and Assignment-3 = 10 out of 10. The student Internal marks are = ((26+10)/2 + ((9+10)/2) = 27.5 is rounded to 28 marks out of 40 marks. If a student is absent for any one MID examination, she can appear for a Grand Test after MID-2. The Grand Test will be conducted with questions covering the entire syllabus. The marks in the grand test is reduced to 30 marks and to be considered for respective mid. ** All the fractional marks are rounded to the next higher whole digit.

RB 5.4

The end semester examination is conducted for 60 marks by covering the topics of all units. The end examination paper contains 12 questions (two from each unit with either - or choice) of 10 marks each. 1 question has to be answered from each unit. (6 x 10 = 60 marks)

RB 5.5

For practical subjects, there shall be continuous evaluation during the semester for 25 internal marks. Out of the 25 marks for internal, day-to-day work 10 marks, Record 5 marks and 10 marks to be awarded by conducting an internal laboratory test. The end examination shall be conducted for 50 marks by the internal examiner and external examiner.

RB 5.6

For the subject having design and/or drawing (such as Engineering Graphics, Engineering Drawing, Machine Drawing) and estimation, the distribution shall be 40 marks for internal evaluation (20 marks for day–to–day work, and 20 marks for MID tests) and 60 marks for end examination. The average of 2 MIDs shall be considered as final marks of the MID.

RB 5.7

For the seminar, the student shall collect the information on a specialized topic and prepare a technical report showing her understanding over the topic, and submit to the department, which shall be evaluated by the Departmental Committee consisting of Head of the Department, seminar supervisor and senior faculty member. The seminar report shall be evaluated for 50 marks. There shall be no external examination for seminar.

RB 5.8

Out of a total of 200 marks for the main project work, 100 marks shall be for Internal Evaluation and 100 marks for the End Semester Examination. The End Semester Examination (Viva – Voce) shall be conducted by the Committee. The Committee consists of an external examiner, Head of the Department and Supervisor of the Project. The evaluation of project work shall be conducted at the end of the Eighth semester. The Internal Evaluation marks shall be on the basis of Two seminars given by each student on the topic of her project and evaluated by an Internal Committee, consisting of Head of the department, supervisor of the project and a senior faculty member.

RB 5.9

For the mini project works, 50 marks shall be for Internal Evaluation. Viva- Voce shall be conducted by the Committee. The Committee consists of Head of the Department and Supervisor of the Project. The Viva–Voce may be conducted along with respective semester lab external examinations. There shall be no external examination for mini projects.

RB 5.10

Laboratory marks and the internal marks awarded by the department are not final. The marks are subjected to be scrutinized and scaled by the Institute wherever it felt desirable. The internal and laboratory marks awarded by the department shall be referred to a Committee if required. The Committee shall arrive at a scaling factor and the marks shall be scaled as per the scaling factor. The recommendations of the Committee are final and binding. The laboratory records and internal test papers shall be preserved for two years after the final examinations of that semester in the respective departments as per the norms of the Institute and shall be produced to the Committees as and when they ask for.

RB 6.0

PROGRAMME STRUCTURE

Basic Science Courses 10-12%

Engineering Science Courses 9-10%

Humanities and Social Science Courses 6-8%

Professional Core Courses 55-65%

Professional Elective Courses 10-12%

Project

5-7%

Open Elective Courses 5-7%

Internships / Certification Courses/ Seminar 3-4%

Mandatory Audit Courses – 6 courses without credits - RB 7.0 SCHEME OF INSTRUCTION FOR I, II, III AND IV YEARS

RB 7.1 The Schemes of Instruction and syllabi of all B.Tech. programmes are given separately, which are approved by the BOS concerned and the Academic Council.

RB 8.0 CONTACT HOURS AND CREDITS

RB 8.1 One hour of lecture/Tutorial is equivalent to one credit and one hour of practical work/field work is equivalent to 0.5 credit.

RB 8.2

THEORY / TUTORIAL CLASSES Each course is prescribed with fixed number of lecture periods per week. During lecture periods, the course instructor shall deal with the concepts of the course. For certain courses, tutorial periods are prescribed in order to give exercises to the students and to closely monitor their learning abilities and achievements.

RB 8.3

LABORATORY / DRAWING COURSES A minimum prescribed number of experiments/drawings/jobs/programmes have to be performed by students, who shall complete these in all aspects and get each experiment evaluated by teacher concerned and certified by the Head of the Department concerned at the end of the semester.

RB 9.0 MEDIUM OF INSTRUCTION

The Medium of Instruction and examination is in English.

RB 10 ATTENDANCE REQUIREMENTS

RB 10.1

In each semester the candidate has to put in a minimum attendance of 75% with a provision of condonation of 10% of the attendance by the Principal on the specific recommendation of the HOD, showing some reasonable cause such as medical grounds, participation in University level sports, cultural activities, seminars, workshops, paper presentation etc.

RB 10.2 Shortage of attendance below 65% in aggregate shall not be condoned.

RB 10.3 Students, having shortage of attendance and got condonation for attendance, shall have to pay requisite fee towards condonation.

RB 10.4 Students whose shortage of attendance is not condoned will be detained and the student has to re-register for that semester when it is offered by the department.

RB 10.5

Rules for calculation of attendance for the re-admitted candidates who were detained for want of attendance or who had break – in study for various reasons: a) No. of classes conducted shall be counted from the day one of the semester concerned, irrespective of the date of payment of tuition fee. b) They should submit a written request to the Principal, along with a challan paid towards tuition and other fee, for re-admission before the commencement of class-work. c) Student should come to know about the date of commencement of class-work of the semester into which she wishes to get re-admission. The information regarding date of commencement of class-work for each semester is available in the college notice boards/ website. RB 11.0 CONDITIONS FOR PASS AND AWARD OF CREDITS FOR A COURSE

RB 11.1

A candidate shall be declared to have passed in individual theory/drawing course if she secures a minimum of 40% aggregate marks (40 marks out of 100, Internal and semester end examination marks put together), subject to a minimum of 35% marks (21 marks out of 60) in semester end examination. For successful completion of mandatory audit course the student must get a satisfactory grade from the department offering the course. If fails, she has to reappear whenever the course is offered.

RB 11.2

A candidate shall be declared to have passed in individual lab/project course if she secures a minimum of 40% aggregate marks (Internal and semester end examination marks put together), subject to minimum of 35% marks in semester end examination.

RB 11.3 The student has to pass the failed course by appearing the supplementary examination as per the requirement for the award of degree.

RB 11.4 On passing a course of a programme, the student shall earn assigned credits in that course. RB 12.0 TRANSITORY REGULATIONS

RB 12.1

A candidate, who is detained or discontinued in the semester, on readmission shall be required to pass all the courses in the curriculum prescribed for such batch of students in which she joins subsequently. However, exemption shall be given to those candidates who have already passed in such courses in the earlier semester(s) and substitute subject may be offered as approved by College Academic Committee and ratified by Academic Council.

RB 12.2 A student shall be eligible for promotion to next semester of B.Tech. programme, if she satisfies the conditions as stipulated in Regulation RB10.

RB 12.3

Further, a student shall be eligible for promotion to V / VII Semesters of B.Tech. programme, if she acquires the minimum number of credits as given below: A student shall be promoted from Semester - IV to Semester - V or from Semester - VI to Semester - VII only if she fulfills the academic requirements of 50% of the credits from the exams for which results are declared. For Lateral Entry Candidates

A student shall be promoted from Semester - VI to Semester - VII only if she fulfills the academic requirements of 50% credits from the exams for which results are declared.

UG IT 1 T 01 18

RB 13.0

COURSE CODE AND COURSE NUMBERING SCHEME: The subject codes shall be given by the Department teaching the subject. Each subject code contains 10 characters. The 10 Characters for each subject shall be coded as per the following guidelines.

While giving the subject codes the Departments can follow the following steps. i. Collect the requirements from various Departments.(subjects which they have to teach for other Departments) ii. Prepare a list of all the subjects the Departments have to teach in that semester (for their Department as well as other Departments based on the requirements they have collected in point i.) iii. Give subject codes to all these subjects following the guidelines given. iv. Communicate these subject codes(identified in point i) to various Departments. v. Use the subject codes identified in point iii to the subjects in their course structure.

RB 14.0 CONSOLIDATED GRADE CARD

A consolidated grade card containing credits and grades obtained by the candidate shall be issued after completion of the four years B.Tech. Programme.

UG for B.Tech.

subjects

PG for M.Tech/MBA

subjects

Code of the Dept

teaching the subject

IT – IT

CS – CSE

EC – ECE

EE – EEE

ME – Mech

CE – Civil

MB – MBA

BS – Basic Sc.

Semester

Number

1/2/3/…/8

Type of subject

T – Theory-Core/Elective P – Practical S – Seminar J – Project A – Mandatory Audit course M – MOOC I – Internship/certification course/Yoga/Foreign languages/EPICS

Serial Number of the

course taught by the

department in the

semester

01/02/03/….

Regulation

Year

RB 15.0 METHOD OF AWARDING LETTER GRADES AND GRADE POINTS FOR A COURSE

RB 15.1

A letter grade and grade point shall be awarded to the student in each course based on her performance as per the grading system given below

Marks Range Theory (Max – 100)

Marks Range Lab (Max – 75)

Letter Grade Level Grade Point

≥ 90 ≥ 67 O Outstanding 10

≥ 80 < 90 ≥ 60 < 67 S Excellent 9

≥ 70 < 80 ≥ 52 < 60 A Very Good 8

≥ 60 < 70 ≥ 45 < 52 B Good 7

≥ 50 < 60 ≥ 37 < 45 C Fair 6

≥ 40 < 50 ≥ 30 < 37 D Satisfactory 5

< 40 < 30 F Fail 0

Absent 0

RB 15.2

Calculation of Semester Grade Points Average(SGPA)* for semester: The Performance of each student at the end of each semester is indicated in terms of SGPA. The SGPA is calculated as below:

SGPA (Si) = ∑(Ci x Gi) / ∑Ci (for all courses passed in that semester)

Where Ci is the number of credits of the ith course and Gi is the grade point scored by the student in the ith course.

* SGPA is calculated for the candidates who passed all the courses in that semester

RB 15.3

Calculation of Cumulative Grade Points Average (CGPA) The CGPA is calculated as below:

CGPA =∑(Ci x Si) / ∑Ci (for entire programme)

Where Si is the SGPA of the ith semester and Ci is the total number of credits in that semester. The SGPA and CGPA shall be rounded off to 2 decimal points and reported in the transcripts

RB 15.4 Equivalent Percentage for CGPA is = (CGPA-0.75) x 10

RB 16.0

REVALUATION As per the notification issued by the Controller of Examination, the student can submit the application for revaluation, along with the fee receipt for revaluation of her answer script(s) of theory course(s), if she is not satisfied with the Grade obtained. The Controller of Examination shall arrange for revaluation of those answer script(s).

RB 16.1

For Revaluation a new external examiner, other than the first examiner, shall re-evaluate the answer

script(s). If there is any change in marks (below 15% of the maximum External marks) the highest of

the two marks will be considered and if there is any change in marks (Equal or above 15% of the

maximum External marks), the script will be evaluated by the third valuator. The marks of all the

three valuators are compared and the average of two nearer marks will be awarded to the student.

RB 17.0

SUPPLEMENTARY EXAMINATIONS.

Supplementary examinations shall be conducted twice in an academic year, along with regular semester end examinations.

RB 18.0

READMISSION CRITERIA.

A candidate, who is detained in a semester due to lack of attendance/ credits, has to obtain written permission from the Principal for readmission in the same semester after duly fulfilling all the required norms stipulated by the college in addition to paying an administrative fee of Rs.1,000/-

RB 19.0

BREAK IN STUDY.

Student, who discontinues her studies for whatsoever may be the reason, can get readmission into appropriate semester of B.Tech. programme after break-in study only with the prior permission of the Principal of the College provided, such candidate shall follow the transitory regulations applicable to such batch in which she joins. An administrative fee of Rs.1000/- per year of break in study in addition to the prescribed tuition fee and special fee has to be paid by the candidate to condone her break in study if this break in study is not covered under GAP year facility.

RB 20.0

AWARD OF DIVISION.

The award of division for the candidates who admitted into respective B.Tech. programmes in the year 2018-2019 and onwards, is as shown in the following table.

CGPA secured from 160 credits DIVISION

≥ 7.75 without any supplementary passing First Class with Distinction

≥ 6.75 with supplementary exams passing First Class

≥ 5.75 to < 6.75 Second Class

≥ 4.75 to < 5.75 Pass Class

For the purpose of awarding First Class with Distinction, the student must get CGPA within 4 years in case of candidates admitted through EAMCET & Management Quota or within 3 years in case of Lateral Entry candidates admitted through ECET, 6 or 5 years for the students who availed the facility of GAP year, without appearing for any supplementary examinations. Detained candidates are not eligible for the award of First Class with Distinction. For the purpose of awarding First, Second and Pass Class, CGPA obtained in the examinations appeared within the maximum period allowed for the completion of course shall be considered.

RB 21.0 BETTERMENT /IMPROVEMENT OF CUMULATIVE GRADE POINT AVERAGE

RB 21.1

A candidate, after becoming eligible for the award of the Degree, may reappear for the external Examination in any of the theory courses as and when conducted, for the purpose of improving the CGPA. But this reappearance shall be within a period of two academic years after becoming eligible for the award of the Degree, subject to fulfillment of Regulation RB 2.0.

RB 21.2

However, this facility shall not be availed by a candidate to reappear either for Internal Examination or for Semester End Examinations in Practical courses (including Project Viva- voce) and also for Semester End Examinations evaluated internally for the purpose of improvement.

RB 21.3 Modified Grade Card and New Consolidated Grade Card shall be issued after incorporating new Grades and Credits.

RB 22.0 ADVANCED SUPPLEMENTARY EXAMINATIONS

RB 22.1

Candidate(s), who fails in Theory or Lab courses of 4th year second semester, can appear for advanced supplementary examinations conducted within one month after declaration of the revaluation results. However, those candidates who fail in this advanced supplementary examinations of IV year second semester shall appear for subsequent examination along with regular candidates in the examinations conducted at the end of the respective academic year.

RB 23.0

MALPRACTICES The Principal/chief superintendent shall refer the cases of malpractices in internal assessment tests and Semester End Examinations to a Malpractice Enquiry Committee, constituted by him/her for the purpose. The Principal shall take necessary action, against the erring students based on the recommendations of the Committee as per JNTUK Malpractice regulations.

RB 24.0

The physically challenged candidates who have availed additional examination time and a scribe during their Intermediate/EAMCET examinations shall be given similar concessions on production of relevant proof/documents.

RB 25.0

The students who are suffering from contagious diseases are not allowed to appear either internal or Semester end examinations with other students. A separate room will be allotted for such type of students.

RB 26.0

The students who participate in coaching/tournaments held at State/National/International levels through University / Indian Olympic Association during Semester end external examination period shall be promoted to subsequent semesters till the entire course is completed as per the guidelines of University Grants Commission Letter No. F. 1-5/88 (SPE/PES), dated 18-08-1994.

RB 27.0

The Principal shall deal with any academic problem, which is not covered under these rules and regulations, in consultation with the Heads of the Departments in an appropriate manner, and subsequently such actions shall be placed before the Academic Council for ratification. Any emergency modification of Regulation, approved in the Heads of the Departments meetings, shall be reported to the Academic Council for ratification.

RB 28.0 The Academic Council, from time to time, may revise or amend or change the Regulations, schemes of examination and/or syllabi.

RB 29.0

GAP YEAR: Shri Vishnu Engineering College for Women encourages admitted students to defer enrollment for one year to travel, pursue a special project or activity, work or spend time in another meaningful way provided they do not enroll in a degree-granting programme at another college. Deferral for two-year obligatory military service is also granted. The student who wants to avail GAP year must take prior approval from the Principal. The Principal shall grant this facility to students on case -to -case basis, by considering the genuinely of the case.

RB 29.1 The GAP years can be availed only between II Year and III year.

RB 29.2 The students who have backlogs are not eligible for availing GAP year facility.

RB 30.0

FREE ELECTIVES In IV year II semester, Free Electives are offered to students which shall enable interested students to pass these free electives during III year and IV year I semester, and make themselves free in IV year for six months and can attend 6 months Internship/Project Work in Industry /Institute and after proper evaluation and recommendations of the Department, the work done can be submitted as Project work. Prior permission and registration of Free Electives is compulsory. The students who register for free elective should not have any standing backlogs. The students shall not be allowed to register in 3/2 or 4/1 without registering in 3/1. If any student would like to discontinue for the free elective in 3/2 or 4/1 after registering in 3/1, she can be permitted to do so.

RB 30.1

Minimum 20% of intake of students is compulsory for offering regular electives, whereas for Free Electives, the minimum students to register is 10% of total intake of students in that branch

RB 30.2 After announcement of the revaluation results, the students can also register for Free Elective in respect of R-18 regulations.

RB 31.0 As per the demand of the industry, a specific elective can be offered in the department with the permission of the Principal and that can be ratified in the college academic committee.

RB 32.0 For internship, minimum period shall be one month. However it can be completed in 3 to 4 slots /intervals which shall be a minimum of five days slot.

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MALPRACTICES GUIDELINES

Disciplinary Action for / Improper Conduct in Examinations

Nature of Malpractices/Improper conduct Punishment

If the candidate:

1.(a)

Possesses or keeps accessible in examination hall,

any paper, note book, programmable calculators, Cell phones, palm computers or any other form of

material concerned with or related to the subject of the examination (theory or practical) in which

he is appearing but has not made use of.

(material shall include any marks on the body of the candidate which can be used as an aid in the

subject of the examination)

Expulsion from the examination hall and

cancellation of the performance in that subject only.

(b)

Gives assistance or guidance or receives it from any other candidate orally or by any other body

language methods or communicates through cell phones with any candidate or persons in or

outside the examination hall in respect of any matter.

Expulsion of all the candidates involved from the examination hall and cancellation of

the performance in that subject only. In case of an outsider, he will be handed over to the

police and a case will be registered against him

2.

Has copied in the examination hall from any

paper, book, programmable calculators, palm computers or any other form of material relevant

to the subject of the examination (theory or

practical) in which the candidate is appearing.


cancellation of the performance in that subject and all other subjects the candidate

has already appeared including practical

examinations and project work and shall not be permitted to appear for the remaining

examinations of the subjects of that Semester/year.

The Hall Ticket of the candidate will be

seized and cancelled.

3.

Impersonates any other candidate in connection

with the examination.

The candidate/Person who has impersonated

shall be expelled from examination hall. The candidate will also be debarred and forfeits

the course. The performance of the original

candidate, who has been impersonated, shall be cancelled in all the subjects of the

examination (including practicals and project work) already appeared and shall not be

allowed to appear for examinations of the

remaining subjects of that semester/year. The candidate is also debarred for two consecutive

semesters from class work and all semester end examinations. The continuation of the

course of such candidate is subject to the academic regulations in connection with

forfeiture of seat. If the imposter is an

outsider, he will be handed over to the police and a case is registered against him.

4. Smuggles in the Answer book or additional sheet

or takes out or arranges to send out the question


cancellation of performance in that subject

paper during the examination or answer book or

additional sheet, during or after the examination.

and all the other subjects the candidate has

already appeared including practical examinations and project work and shall not

be permitted for the remaining examinations

of the subjects of that semester/year. The candidate is also debarred for two consecutive

semesters from class work and all semester end examinations. The continuation of the

course by the candidate is subject to the academic regulations in connection with

forfeiture

of seat.

5.

Uses objectionable, abusive or offensive language

in the answer paper or in letters to the examiners

or writes to the examiner requesting him to award pass marks.

Cancellation of the performance in that

subject.

6.

Refuses to obey the orders of the Chief Superintendent / Asst. Superintendent / any

officer on duty or misbehaves or creates

disturbance of any kind in and around the examination hall or organizes a walk out or

instigates others to walk out, or threatens the officer-in charge or any person on duty in or

outside the examination hall of any injury to his

person or to any of his relations whether by words, either spoken or written or by signs or by

visible representation, assaults the officer-in-charge, or any person on duty in or outside the

examination hall or any of his relations, or indulges in any other act of misconduct or

mischief which results in damage to or destruction

of property in the examination hall or any part of the College campus or engages in any other act

which in the opinion of the officer on duty amounts to use of unfair means or misconduct or

has the tendency to disrupt the orderly conduct of

the examination.

In Case of students, they shall be expelled from examination halls and cancellation of

their performance in that subject and all other

subjects the candidate(s) has (have) already appeared and shall not be permitted to

appear for the remaining examinations of the subjects of that semester / year. The

candidates also are debarred and forfeit their

seats. In case of outsiders, they will be handed over to the police and a police case is

registered against them.

7.

Leaves the examination hall taking away answer

script or intentionally tears of the script or any

part thereof inside or outside the examination hall.


cancellation of performance in that subject

and all the other subjects the candidate has already appeared including practical

examinations and project work and shall not be permitted for the remaining examinations

of the subjects of that semester/year. The candidate will also be debarred for two

consecutive semesters from class work and all

semester end examinations. The continuation of the course by the candidate is subject to

the academic regulations in connection with forfeiture of seat.

8.

Possess any lethal weapon or firearm in the

examination hall.


cancellation of the performance in that subject and all other subjects the candidate

has already appeared including practical


of the subjects of that semester/year. The

candidate will also forfeit his/her course.

9.

If the student of the college, who is not a

candidate for the particular examination or any person not connected with the college indulges in

any malpractice or improper conduct mentioned in

clause 6 to 8.

Student of the college expulsion from the

examination hall and cancellation of the performance in that subject and all other

subjects the candidate has already appeared

including practical examinations and project work and shall not be permitted for the

remaining examinations of the subjects of that semester/year. The candidate will also

forfeit the course.

Person(s) who do not belong to the College will be handed over to police and a police

case will be registered against them.

10.

Comes in a drunken/intoxicated condition to the

examination hall.


cancellation of the performance in that

subject and all other subjects the candidate has already appeared including practical


of the subjects of that semester/year.

11.

Copying detected on the basis of internal evidence, such as, during valuation or during

special scrutiny.

Cancellation of the performance in that subject and all other subjects the candidate

has appeared including practical examinations and project work of that

semester/year examinations.

12. If any malpractice is detected which is not

covered in the above clauses1 to 11

Reported to the Principal for further action to

award suitable punishment.

Malpractices identified by squad or special invigilators

Punishments to the candidates as per the guidelines.

* * * * *


(AUTONOMOUS)


UG : Computer Science & Engineering – CSE

Program Educational Objectives – PEOs:

PEO 1. Graduates will have the expertise in analyzing real time problems and

providing appropriate solutions related to Computer Science & Engineering.

PEO 2. Graduates will have the knowledge of fundamental principles and innovative

technologies to succeed in higher studies and research.

PEO 3. Graduates will continue to learn and to adapt technology developments

combined with deep awareness of ethical responsibilities in profession.

Program Specific Outcomes – PSOs:

PSO1. Apply various programming skills to deliver innovative quality software

products for the changing business needs.

PSO2. Utilize the skills of Data Analytics, Cloud Computing and Machine Learning

to address technological challenges in multidisciplinary areas of engineering.

Program Outcomes –POs:

PO 1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

PO 2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PO 3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

PO 4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

PO 5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.

PO 6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.

PO 7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.

PO 8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO 9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO 10. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

PO 11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

PO 12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

SHRI VISHNU ENGINEERING COLLEGE

FOR WOMEN

Department of COMPUTER SCIENCE & ENGINEERING

Chemistry

English

OOP

Physics

Mathematics C Programming

Data Structures

Probability & Statistics

Discrete Mathematics

Digital Electronics

FLAT

Compiler Design

Computer Graphics

Artificial Intelligence

DAA

DBMS

COA

SE

ADB

STM

CN

OS

MPMC

Image Processing

NLP

DWDMW

BDT

SPM

WT

CC

IS

ETC

Pattern Recognition

ML

SC

BCT

DS

DP Cyber

Security Management

Science

Virtual Reality

Deep

Learning

IRS

SNSW

HCI

E-COM Web

Services

IOT

HPC

EH

CF

SHRI VISHNU ENGINEERING COLLEGE FOR WOMEN (AUTONOMOUS) BHIMAVARAM - 534202


Course Structure – R18 (With effect from 2018-2019)

I Year - I Semester

I Year - II Semester

S.No Course Code Course Title L T P C IM EM TM

1 UGBS1T0118 English-I 3 - - 3 40 60 100

2 UGBS1T0218 Mathematics–I 2 1 - 3 40 60 100

3 UGBS1T0318 Semiconductor Physics 3 - - 3 40 60 100

4 UGME1T0118 Engineering Drawing 2 - 2 3 40 60 100

5 UGBS1P0618 English Communication Skills Lab - - 3 1.5 25 50 75

6 UGBS1P0718 Semiconductor Physics Lab - - 3 1.5 25 50 75

7 UGME1P0218 Workshop Practice and Innovation Lab - - 3 1.5 25 50 75

8 UGBS1A1018 Environmental Science 2 - - - - - -

Total 12 1 11 16.5 235 390 625


1 UGBS2T0118 English-II 3 - - 3 40 60 100

2 UGBS2T0218 Mathematics–II 2 1 - 3 40 60 100

3 UGBS2T0418 Applied Chemistry 3 - - 3 40 60 100

4 UGCS2T0118 Programming for Problem Solving 3 - - 3 40 60 100

5 UGEE2T0218 Basic Electrical & Electronics

Engineering 3 - - 3 40 60 100

6 UGBS2P0618 Business Communication Lab - - 3 1.5 25 50 75

7 UGBS2P0818 Applied Chemistry Lab - - 3 1.5 25 50 75

8 UGCS2P0218 Programming for Problem Solving Lab - - 3 1.5 25 50 75

9 UGBS2A1118 Indian Constitution 2 - - - - - -

Total 16 1 9 19.5 275 450 725



Course Structure – R18

(With effect from 2018-2019) II Year - I Semester

II Year - II Semester


1 UGBS3T0318 Probability and Statistics 3 - - 3 40 60 100

2 UGCS3T0118 Data Structures 3 - - 3 40 60 100

3 UGCS3T0218 Digital Electronics 3 - - 3 40 60 100

4 UGCS3T0318 Discrete Mathematics 3 - - 3 40 60 100

5 UGCS3T0418 Object Oriented Programming 3 - - 3 40 60 100

6 Open Elective-I 3 - - 3 40 60 100

7 UGCS3P0518 Data Structures Lab - - 3 1.5 25 50 75

8 UGCS3P0618 Object Oriented Programming Lab - - 3 1.5 25 50 75

9 UGBS3A0718 Essence of Indian Traditional Knowledge 2 - - - - - -

Total 20 0 6 21 290 460 750


1 UGCS4T0118 Computer Organization and Architecture 3 - - 3 40 60 100

2 UGCS4T0218 Database Management Systems 3 - - 3 40 60 100

3 UGCS4T0318 Design and Analysis of Algorithms 3 - - 3 40 60 100

4 UGCS4T0418 Formal Languages and Automata Theory

3 - - 3 40 60 100

5 UGCS4T0518 Software Engineering 3 - - 3 40 60 100

6 Open Elective-II 3 - - 3 40 60 100

7 UGCS4P0618 Database Management Systems Lab - - 3 1.5 25 50 75

8 UGCS4P0718 Object Oriented Analysis and Design Lab

2 - 3 3.5 25 50 75

9 UGCS4J0818 Mini Project-1 - 1 2 2 50 - 50

10 UGBS4A0318 Effective Technical Communication 2 - - - - - -

Total 22 1 8 25 340 460 800



Course Structure – R18

(With effect from 2018-2019)

III Year - I Semester

III Year - II Semester


1 UGCS5T0118 Compiler Design 3 - - 3 40 60 100

2 UGCS5T0218 Computer Networks 3 - - 3 40 60 100

3 UGCS5T0318 Microprocessors and Microcontrollers 3 - - 3 40 60 100

4 UGCS5T0418 Operating Systems 3 - - 3 40 60 100

5 Professional Elective-I 3 - - 3 40 60 100

6 UGCS5P1018 Compiler Design Lab - - 3 1.5 25 50 75

7 UGCS5P1118 Computer Networks & Operating

Systems Lab - - 3 1.5 25 50 75

8 UGCS5P1218 Microprocessors and Microcontrollers Lab

- - 3 1.5 25 50 75

9 UGBS5A0218 Logical Reasoning 2 - - - - - -

Total 17 0 9 19.5 275 450 725


1 UGCS6T0118 Data Warehousing and Data Mining 3 - - 3 40 60 100

2 UGCS6T0218 Information Security 3 - - 3 40 60 100

3 UGCS6T0318 Web Technologies 3 - - 3 40 60 100

4 Professional Elective-II 3 - - 3 40 60 100

5 Open Elective-III 3 - - 3 40 60 100

6 UGCS6P1018 Data Warehousing and Data Mining

Lab - - 3 1.5 25 50 75

7 UGCS6P1118 Information Security Lab - - 3 1.5 25 50 75

8 UGCS6P1218 Web Technologies Lab - - 3 1.5 25 50 75

9 UGCS6J1318 Mini Project-2 - 1 2 2 50 - 50

10 UGBS6A0118 Quantitative Ability 2 - - - - - -

Total 17 1 11 21.5 325 450 775




IV Year - I Semester

IV Year - II Semester


1 UGMB7T0118 Management Science 3 - - 3 40 60 100

2 UGCS7T0118 Data Science 3 - - 3 40 60 100

3 UGCS7T0218 Machine Learning 3 - - 3 40 60 100

4 Professional Elective-III 3 - - 3 40 60 100

5 Open Elective-IV 3 - - 3 40 60 100

6 UGCS7P0918 Data Science with R Lab - - 3 1.5 25 50 75

7 UGCS7P1018 Machine Learning Lab - - 3 1.5 25 50 75

Total 15 0 6 18 250 400 650


1 Free Elective-I 3 - - 3 40 60 100

2 Free Elective-II 3 - - 3 40 60 100

3 Free Elective-III 3 - - 3 40 60 100

4 UGCS8J1818 Major Project - - 10 5 100 100 200

5 UGCS8S1918 Seminar - 2 - 2 50 - 50

6 UGCS8I2018 Internship/Certification Course/EPICS /Foreign Languages/Yoga

- - - 3 - - -

Total 9 2 10 19 270 280 550

L – Lectures, T – Tutorials, P – Practicals, C – Credits, IM – Internal Marks, EM – External Marks, TM – Total Marks




S.No. Course Code Professional Elective-I

(III B.Tech I-Sem)

1 UGCS5T0518 Advanced Databases

2 UGCS5T0618 Computer Graphics

3 UGCS5T0718 Artificial Intelligence

4 UGCS5T0818 Linux Programming

5 UGCS5T0918 Software Testing Methodologies

S.No. Course Code Professional Elective-II

(III B.Tech II-Sem)

1 UGCS6T0418 Big Data Technologies

2 UGCS6T0518 Image Processing

3 UGCS6T0618 Natural Language Processing

4 UGCS6T0718 Cloud Computing

5 UGCS6T0818 Software Project Management

6 UGCS6T0918 Introduction to Analytics (Associate Analytics-1)

S.No. Course Code Professional Elective-III

(IV B.Tech I-Sem)

1 UGCS7T0318 Blockchain Technologies

2 UGCS7T0418 Pattern Recognition

3 UGCS7T0518 Soft Computing

4 UGCS7T0618 Cyber Security

5 UGCS7T0718 Design Patterns

6 UGCS7T0818 Data Analytics (Associate Analytics-2)




S.No. Course Code Free Elective-I

(IV B.Tech II-Sem)

1 UGCS8T0118 Internet of Things

2 UGCS8T0218 Human Computer Interaction

3 UGCS8T0318 High Performance Computing

4 UGCS8T0418 Computer Forensics

5 UGCS8T0518 Deep Learning

S.No. Course Code Free Elective-II

(IV B.Tech II-Sem)

1 UGCS8T0618 Social Networks and Semantic Web

2 UGCS8T0718 E-Commerce

3 UGCS8T0818 Mobile Application Development

4 UGCS8T0918 Scripting Languages

5 UGCS8T1018 Innovation and New Product Development

6 UGCS8T1118 Information Security Management

(Security Analyst-1)

S.No. Course Code Free Elective-III

(IV B.Tech II-Sem)

1 UGCS8T1218 Web Services

2 UGCS8T1318 Virtual Reality

3 UGCS8T1418 Mobile Adhoc and Sensor Networks

4 UGCS8T1518 Ethical Hacking

5 UGCS8T1618 Information Retrieval Systems

6 UGCS8T1718 Information Security Incident Response and

Management (Security Analyst -2)




The following courses are offered to the students of other departments.

S.No. Course Code Open Electives

1 UGCS0T0118 Computer Networks

2 UGCS0T0218 Computer Organization and Architecture

3 UGCS0T0318 Database Management Systems

4 UGCS0T0418 Data Science

5 UGCS0T0518 Design and Analysis of Algorithms

6 UGCS0T0618 Internet of Things

7 UGCS0T0718 Linux Programming

8 UGCS0T0818 Object Oriented Programming through C++

9 UGCS0T0918 Object Oriented Programming through Java

10 UGCS0T1018 Operating Systems

11 UGCS0T1118 Python Programming

Note: Each department will notify the list of Open Electives to be offered at the time of course registration.


(AUTONOMOUS)

OPEN ELECTIVES OFFERED BY DEPARTMENT OF CIVIL ENGINEERING

S.

No.

Subject

Code Subject Name L T P C I E TM

1 UGCE0T0118 RS & GIS and its Applications 3 - - 3 40 60 100

2 UGCE0T0218 Elements of Transportation

Engineering 3 - - 3 40 60 100

3 UGCE0T0318 Water Supply Engineering. 3 - - 3 40 60 100

4 UGCE0T0418 Sanitary Engineering 3 - - 3 40 60 100

5 UGCE0T0518 Environment Pollution. 3 - - 3 40 60 100

6 UGCE0T0618 Elements of Dam & Irrigation

Engineering. 3 - - 3 40 60 100

7 UGCE0T0718 Disaster Management 3 - - 3 40 60 100

8 UGCE0T0818 Basic Elements of Earthquake

Engineering 3 - - 3 40 60 100


(AUTONOMOUS)

OPEN ELECTIVES OFFERED BY DEPARTMENT OF ELECTRICAL & ELECTRONICS ENGINEERING

S.

No.

Subject

Code Subject Title L T P C I E TM

1 UGEE0T0118 Energy Studies 3 - - 3 40 60 100

2 UGEE0T0218 Energy Audit and

Conservation 3 - - 3 40 60 100

3 UGEE0T0318 Sensors & Applications 3 - - 3 40 60 100

4 UGEE0T0418 Industrial Electronics 3 - - 3 40 60 100

5 UGEE0T0518 Electrical Machines for EV’s 3 - - 3 40 60 100

6 UGEE0T0618 PLC & Applications 3 - - 3 40 60 100

7 UGEE0T0718 Solar Energy Appliances 3 - - 3 40 60 100

8 UGEE0T0818 Energy Storage

Technologies 3 - - 3 40 60 100

9 UGEE0T0918 MATLAB 3 - - 3 40 60 100

10 UGEE0T1018 AI Techniques 3 - - 3 40 60 100


(AUTONOMOUS)

OPEN ELECTIVES OFFERED BY DEPARTMENT OF MECHANICAL ENGINEERING

S.

No. Subject Code Subject Title L T P C I E TM

1 UGME0T0118 Metallurgy and Material

Science 3 - - 3 40 60 100

2 UGME0T0218 Basics of Mechanical

Engineering 3 - - 3 40 60 100

3 UGME0T0318 Engineering Mechanics 3 - - 3 40 60 100

4 UGME0T0418 Strength of Materials

3 - - 3 40 60 100

5 UGME0T0518 Fluid Machinery 3 - - 3 40 60 100

6 UGME0T0618 Nanotechnology 3 - - 3 40 60 100

7 UGME0T0718 Thermodynamics 3 - - 3 40 60 100

8 UGME0T0818 Thermal and Fluid

Engineering 3 3 40 60 100

9 UGME0T0918 Automobile Engineering 3 - - 3 40 60 100

10 UGME0T1018 Computer Aided

Engineering Drawing 2 - 2 3 40 60 100

11 UGME0T1118 Industrial Engineering

and Management 3 - - 3 40 60 100

12 UGME0T1218 Quality and Reliability

Engineering 3 - - 3 40 60 100


(AUTONOMOUS)

OPEN ELECTIVES OFFERED BY DEPARTMENT OF ELECTRONICS & COMMUNICATION ENGINEERING

S.

No. Subject Code Name of the Course L T P C I E T

1 UGEC0T0118 Basic Electronics Engineering 3 0 0 3 40 60 100

2 UGEC0T0218 Applications of Electronic Devices 3 0 0 3 40 60 100

3 UGEC0T0318 Analog & Digital Communication 3 0 0 4 40 60 100

4 UGEC0T0418 Data Communication 3 0 0 3 40 60 100

5 UGEC0T0518 Microprocessors and Multicore

Systems 3 0 0 3 40 60 100

6 UGEC0T0618 VLSI Design 3 0 0 3 40 60 100

7 UGEC0T0718 Image Processing 3 0 0 3 40 60 100

8 UGEC0T0818 Wavelet Transforms 3 0 0 3 40 60 100

9 UGEC0T0918 Embedded systems 3 0 0 3 40 60 100

10 UGEC0T1018 MEMS 3 0 0 3 40 60 100

11 UGEC0T1118 Electronic Instrumentation 3 0 0 3 40 60 100


(AUTONOMOUS)

OPEN ELECTIVES OFFERED BY DEPARTMENT OF INFORMATION TECHNOLOGY

S. No. Subject Code List of Open Electives L T P C IM EM TM

1 UGIT0T0118 Data Structures 3 - - 3 40 60 100

2 UGIT0T0218 Software Engineering 3 - - 3 40 60 100

3 UGIT0T0318 Web Technologies 3 - - 3 40 60 100

4 UGIT0T0418 Unix Programming 3 - - 3 40 60 100

5 UGIT0T0518 E-Commerce 3 - - 3 40 60 100

6 UGIT0T0618 Artificial Intelligence 3 - - 3 40 60 100

7 UGIT0T0718 Computer Graphics 3 - - 3 40 60 100

8 UGIT0T0818 Cloud computing 3 - - 3 40 60 100

9 UGIT0T0918 Machine Learning 3 - - 3 40 60 100

10 UGIT0T1018 Advanced Data Structures 3 - - 3 40 60 100

11 UGIT0T1118 Design and Analysis of

Algorithms 3 - - 3 40 60 100

12 UGIT0T1218 Parallel Computing 3 - - 3 40 60 100

13 UGIT0T1318 Bioinformatics 3 - - 3 40 60 100

14 UGIT0T1418 Advanced Java 3 - - 3 40 60 100


(AUTONOMOUS)

OPEN ELECTIVES OFFERED BY DEPARTMENT OF BASIC SCIENCE

S. No. Subject

Code List of Open Electives L T P C IM EM TM

1 UGBS0T0118 Probability and Statistics 3 - - 3 40 60 100

2 UGBS0T0218 Operations Research 3 - - 3 40 60 100

3 UGBS0T0318 Numerical Methods & Complex

Variables 3 - - 3 40 60 100

4 UGBS0T0418 Optimization Techniques (Open

Elective—I) 3 - - 3 40 60 100

5 UGBS0T0518 Optimization Techniques (Open

Elective—II) 3 - - 3 40 60 100

I YEAR

I SEMESTER

ENGLISH – I

(Common to All Branches)

Subject Code: UGBS1T0118 L T P C

I Year / I Semester 3 0 0 3

COURSE OBJECTIVES:

1. To train students in all LSRW skills in order to make them independent, lifelong

learners by availing of these four skills.

2. To prepare the students to face the emerging challenges of the world.

3. To inculcate the habit of reading beyond academics among students and to

enable them to be competent communicators on various platforms.

4. To expose students to different cultural contexts.

SYLLABUS:

UNIT-I 9hrs

Short Story:STEVE JOB’S SPEECH AT STANFORD GRADUATION CEREMONY

Grammar : Concord forms : Subject-verb agreement

Kinds of Verbs and Tenses

Speaking :Describing oneself and others, objects, places, processes and narrating

events and stories.

Listening :Listening to narratives, talks and conversations and answering

questions on them.

UNIT-II: THE MEANING OF LIFE By VIKTOR E.FRANKL 11 hrs

(from the book ‘Man’s Search for Meaning’)

Grammar : Articles and prepositions

Speaking : Framing appropriate questions and giving answers: exercises

Assignment-I:Each Student is required to present a report on a problem faced by

individuals or the society with an analysis and possible solutions. She

has to make an oral presentation of it in the class after the completion

of Unit-II Examination. It is mandatory for all the students. It is for

Internal Assessment.

UNIT-III: THE DAILY FIVE BY ROBIN SHARMA 10hrs

(from the book ‘THE LEADER WHO HAD NO TITLE’)

Vocabulary:Selected Etymological roots and word formation; prefixes and suffixes

derived from foreign languages to form derivatives in English.

Speaking :Speaking spontaneously on ideas using idiomatic expressions.

UNIT-IV :THE FESTIVAL OF THE SACRED TOOTH RELIC IN SRI LANKA

based on the travelogues of Fa Hien 12 hrs

Vocabulary: Synonyms and antonyms

Grammar : Transformation of sentences: Direct and Indirect Speech;

Active Voice and Passive Voice

Assignment-II: Each Student is required to present a report on a problem faced

by individuals or the society with an analysis and possible solutions.

She has to make an oral presentation of it in the class after the

completion of Unit-IV Examination. It is mandatory for all the

students. It is for Internal Assessment.

UNIT-V : SATYA NADELLA’S LETTER TO HIS EMPLOYEES IN JUNE 2015

Grammar : Simple, Compound and Complex Sentences 09hrs

Uses of Phrases and Clauses in Sentences

UNIT-VI: A REVIEW ON THE MOVIE ‘ THE MAN FROM THE EARTH’

(2007 release) 11hrs

Composition: Paragraph writing, e-mail writing

Listening : Listening comprehension

Assignment-III : Each Student is required to submit a critical review of the

prescribed movie in the syllabus.

COURSE OUTCOMES:

Upon the completion of the course, the student will be able to:

CO 1. Develop a meaningful general essay or an essay from the prescribed text.

CO 2. Illustrate, the kind and functions of verbs and their tenses, concord forms and appropriate articles and prepositions

CO 3. Build corpus of vocabulary through affixation and idioms.

CO 4. Utilize varying sentence structures with appropriate phrases and clauses,

identify the use of specific words and phrases in the test and convenience of transformation of sentences.

CO 5. Choose and maintain formal style and tone with varied syntax to create

clean and cognate paragraphs and emails.

Mapping of COs to POs:

POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 - - - - - - - - - 3 - 3

CO2 - - - - - - - - - 3 - 3

CO3 - - - - - - - - - 3 - 3

CO4 - - - - - - - - - 3 - 3

CO5 - - - - - - - - - 3 - 3

SOURCE BOOKS FOR ENGLISH- I

1. Man’s Search for Meaning by Viktor E.Frankl

2. The Leader who had no Title by Robin Sharma

3. Life, Language and Culture – Explorations –I .

Internet sources for:

Steve Job’s speech at Stanford Graduation Ceremony

Satya Nadella’s letter to his employees in June 2015

The Movie ‘ The Man from the Earth’ (2007 release )

BOOKS FOR FURTHER REFERENCE

1. The Oxford guide to Writing & Speaking – John Seely

2. A Practical English Grammar Exercises 2 (Thrid Edition) – A.J. Thomson and A.V.

Martinet, Oxford University Press, New Delhi, 2007.

3. The Students’ Companion – Wilfred D. Best (New Edition) – Harper, Collins

Publishers, 2012.

4. Col-Locate Your World, A store house of words & word-relations, their similarities

& dissimilarities – Ajay Singh, Arihant Publications (I) Pvt. Ltd., Meerut.

4. English Conversation Practice – Grant Taylor, Tata Mc Graw-Hill Publishing

Company Limited, New Delhi, 2007.

5. Verbal Workout – Intensive practice to boost your English Vocabulary,

Educational Software Technologies

6. The Official Cambridge Guide to IELTS, For Academic & General Training, (With

DVD-ROM), Student Book with Answers, 2015.

7. Immortal Speeches, Complied by Harshvardhan Dutta, Unicorn Books Pvt. Ltd.,

Distributors – Pustak Mahal, Delhi.

MATHEMATICS - I




COURSE OBJECTIVES:

To prepare students to learn the concepts of Rank of a matrix, Eigen values,

Eigen vectors.

To Familiarize students with analytical methods to solve Ordinary differential

equations.

SYLLABUS:

UNIT-I: MATRICES 13hrs

Types of Matrices: Symmetric, skew-symmetric, orthogonal, Hermitian, Skew-

Hermitian, Unitary. Rank of a matrix by Echelon form and Normal form, Inverse of

Non-singular matrices by Gauss-Jordan method, System of linear equations - solving

system of Homogeneous and Non-Homogeneous equations by Gauss elimination

method.

UNIT-II: EIGEN VALUES AND EIGEN VECTORS 11hrs

Linear Transformation and Orthogonal Transformations, Eigen values and Eigen

vectors and their properties, Diagonalization of matrices; Cayley-Hamilton Theorem

(without proof).

UNIT -III: ORDINARY DIFFERENTIAL EQUATIONS OF FIRST ORDER AND

FIRST DEGREE 11hrs

Exact, Reducible to exact equations, Linear and Bernoulli’s equations.

UNIT –IV: ORDINARY DIFFERENTIAL EQUATIONS OF HIGHER ORDER 13hrs

Second and Higher order linear differential equations with constant coefficients, Non-

Homogeneous terms of the type , polynomials in , and

, Equations reducible to linear ODE with constant Coefficients, Legendre’s

equation and Cauchy-Euler equation.

UNIT-V: MEAN VALUE THEOREMS 11hrs

Rolle’s theorem, Mean value theorems, Taylor’s and Maclaurin theorems with

remainders

UNIT-VI: APPLICATIONS 9hrs

Finding the current in an Electrical Circuit by Gauss elimination method, Finding

inverse and powers of a matrix by Cayley-Hamilton Theorem, Orthogonal Trajectories,

Newton’s Law of Cooling, Law of Natural Growth and Decay, LCR Circuits.

Course Outcomes:

CO1: List various types of matrices and their properties.

CO2: Determine the rank, inverse and powers of a matrix.

CO3: Apply matrix techniques to model and solve system of linear equations.

CO4: Illustrate Eigen values, Eigen vectors, properties and diagonalization of a

given matrix.

CO5: Apply appropriate analytical technique to model and solve a given differential

equation.

CO6: Examine Mean value theorems for a given function.

CO7: Construct the Taylor’s and Maclaurin’s series from generalized mean value theorem.


POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 3 3 3 2 - - - - - - - 3

CO2 3 3 3 2 - - - - - - - 3

CO3 3 3 3 2 - - - - - - - 3

CO4 3 3 3 2 - - - - - - - 3

CO5 3 3 3 2 - - - - - - - 3

CO6 3 3 3 2 - - - - - - - 3

CO7 3 3 3 2 - - - - - - - 3

TEXT BOOKS:

1. B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers, 43rd

Edition.

2. Ramana B.V., Higher Engineering Mathematics, Tata McGraw Hill New Delhi,

11th

Reprint, 2010.

3. N.P. Bali and Manish Goyal, A text book of Engineering Mathematics, Laxmi

Publications, Reprint, 2008.

REFERENCE BOOKS:

1. W. E. Boyce and R. C. DiPrima, Elementary Differential Equations and Boundary Value Problems, 9th Edn., Wiley India, 2009.

2. D. Poole, Linear Algebra: A Modern Introduction, 2nd Edition, Brooks/Cole,

2005. 3. Veerarajan T., Engineering Mathematics for first year, Tata McGraw-Hill, New

Delhi,2008. 4. G.B. Thomas and R.L. Finney, Calculus and Analytic geometry, 9th Edition,

Pearson, Reprint, 2002.

5. Erwin kreyszig, Advanced Engineering Mathematics, 9th Edition, John Wiley & Sons,2006.

SEMICONDUCTOR PHYSICS



COURSE OBJECTIVES:

To highlight the hidden importance of physics concepts in Engineering &

Technology.

To facilitate the students with the aid of advanced insight in the applied

science.

To focus on the real time applications of physics in engineering fields.

To prepare the students to face the challenges in core fields with the support

of physics principles.

To motivate the students to understand the Engineering Principles through

basic ideas in Physics.

SYLLABUS:

UNIT-I: ELECTRONIC MATERIALS 11hrs

Free electron theory, Sommerfield theory. Band theory of solids. Energy bands in

solids, E-K diagram, Direct and indirect band gaps, Types of electronic materials:

metals, semiconductors, and insulators, Fermi-Dirac distribution.

UNIT-II:SEMICONDUCTORS 12hrs

Intrinsic and extrinsic semiconductors, Dependence of Fermi level on carrier-

concentration and temperature (equilibrium carrier statistics), Carrier generation

and recombination, Carrier Transport: diffusion and drift, P-N junction I-V

characteristics.

UNIT-III: LIGHT-SEMICONDUCTOR INTERACTION 8hrs

Optical transitions in bulk semiconductors: absorption, spontaneous emission, and

stimulated

emission; Transition rates (Fermi's Golden Rule), Optical loss and gain;

Photovoltaic effect, Exciton.

UNIT-IV : PHOTONIC DEVICES 8hrs

Light Emitting Diode, Semiconductor Laser, Photo Diode, Avalanche Photodiode,

PN junction solar cells.

UNIT-V:ENGINEERED SEMICONDUCTOR MATERIALS 8hrs

Homo and Hetero junctions and associated band-diagrams, special semiconducting

devices such as quantum wells, wires, and dots.

UNIT- VI : MEASUREMENTS 8hrs

Four-point probe and van der Pauw measurements for carrier density, resistivity,

and hall mobility; Hot-point probe measurement, capacitance-voltage

measurements, parameter Extraction from diode I-V characteristics.

COURSE OUTCOMES:

CO1: Distinguish the concepts of free electron motion in metals by classical and quantum theory. CO2: Classify solids on the basis of band theory.

CO3: Compare the Fermi energy levels of intrinsic and extrinsic semiconductors.

CO4: Apply the knowledge of carrier transport mechanisms to understand the characteristics of a P-N junction diode.

CO5: Explain the optical transitions in bulk semiconductors to understand optical loss and gain based on transition rates.

CO6: Apply the light -semiconductor interaction techniques to study the functioning of various photonic devices. CO7: Analyze the characterization techniques of low-dimensional special semiconducting devices. CO8: Make use of highly sophisticated methods including four-point probe, hot-point probe, and Van der Pauw method to measure the various electronic parameters.


POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 3 3 - - - - - - - - - -

CO2 3 3 - - - - - - - - - -

CO3 3 3 - - - - - - - - - -

CO4 3 2 - - - - - - - - - -

CO5 3 2 - - - - - - - - - -

CO6 3 3 - - - - - - - - - -

CO7 3 3 - 3 - - - - - - - -

CO8 3 3 - 3 - - - - - - - -

TEXT BOOKS:

1. P. Bhattacharya, Semiconductor Optoelectronic Devices, Prentice Hall of India

(1997).

2. J. Singh, Semiconductor Optoelectronics: Physics and Technology, McGraw-Hill

Inc. (1995)

REFERENCE BOOKS

1. B. E. A. Saleh and M. C. Teich, Fundamentals of Photonics, John Wiley & Sons,

Inc., (2007).

2. S. M. Sze, Semiconductor Devices: Physics and Technology, Wiley (2008).

3. A. Yariv and P. Yeh, Photonics: Optical Electronics in Modern Communications,

Oxford University Press, New York (2007).

4. Physics Volume II by Resnick, Halliday & Walker ( John Wiley & sons)

5. Engineering Physics by P. K. Palanisamy, SciTech Publishers

6. Engineering Physics by D. K. Bhattacharya, Oxford Publishers

7. Engineering Physics by M. N. Avadhanulu & Kshirsagar, S. Chand Publishers

8. Electrical Characterization of Semiconductor Materials and Devices, Jamal Deen

and Fabian Pascal

ENGINEERING DRAWING

Subject Code: UGME1T0118 L T P C


COURSE OBJECTIVES:

1. To acquire basic skills in technical graphic communication and also get thorough

knowledge of various geometrical elements used in Engineering practice.

2. Impart and inculcate proper understanding of the theory of projection and

projection of one dimensional objects on 2D planes.

3. To impart knowledge on projecting two dimensional figures and to visualize the

different positions of planes.

4. To visualize and represent the 3D objects in 2D planes with proper dimensioning,

scaling.

5. To visualize and represent the pictorial views of two & three dimensional objects

with proper dimensioning and scaling.

6. Interpret and represent both two & three dimensional of objects

SYLLABUS:

UNIT-I: 36 hrs

Objective: Acquire basic skills in technical graphic communication and also get

thorough knowledge of various geometrical elements used in Engineering practice

INTRODUCTION TO THE ENGINEERING DRAWING, Polygons, Conic

sections: construction of ellipse, parabola and hyperbola by general method,

Introduction to scales.

INTRODUCTION TO ORTHOGRAPHIC PROJECTIONS: projections of points

UNIT-II: 9hrs

Objective: Impart and inculcate proper understanding of the theory of projection

and projection of one dimensional objects on 2D planes.

PROJECTIONS OF STRAIGHT LINES perpendicular to one and parallel to other,

parallel to both the planes, parallel to one plane and inclined to the other plane,

inclined to both the planes, determination of true lengths, angle of inclinations

and traces.

COURSE OUTCOMES:

CO 1: Familiarize how industry communicates, practices for accuracy in presenting

the technical information through drawing.

CO 2: Develop the engineering perspective essential for representing orthographic projections.

CO 3: Develop the engineering perspective essential for representing isometric projections.

CO 4: Improve their visualization skills to develop new designs.


COs POs PSOs

1 2 3 4 5 6 7 8 9 10 11 12 1 2

CO1 3 2 2 - - - - - - 3 - 2 - -

CO2 3 2 2 - - - - - - 3 - 2 - -

CO3 3 2 2 - - - - - - 3 - 2 - -

CO4 3 3 3 - - - - - - 3 - 3 - -

UNIT-III: 12hrs

Objective: To impart knowledge on projecting two dimensional figures and to

visualize the different positions of planes.

PROJECTIONS OF PLANES: regular planes perpendicular/parallel to one plane

and inclined to the other reference plane; inclined to both the reference planes

UNIT-IV: 15hrs

Objective: To visualize and represent the 3D objects in 2D planes with proper

dimensioning, scaling.

PROJECTIONS OF SOLIDS – Prisms, Pyramids, Cones and Cylinders with the

axis inclined to one of the reference plane.

UNIT-V: 12hrs

Objective: To visualize and represent the pictorial views of two & three

dimensional objects with proper dimensioning and scaling.

ISOMETRIC PROJECTIONS

UNIT-VI 12 hrs

Objective: Interpret and represent both two & three dimensional of objects.

Conversion of isometric views to orthographic views

Conversion of orthographic views to isometric views

TEXT BOOKS:

1. Engineering Drawing by N.D. Butt, Chariot Publications

2. Engineering Drawing by K.L.Narayana & P. Kannaiah, Scitech Publishers.

3. Engineering Graphics by PI Varghese, McGrawHill Publishers

4. Engineering Drawing + AutoCad – K Venugopal, V. Prabhu Raja, New Age

REFERENCES:

1. Engineering Graphics for Degree by K.C. John, PHI Publishers

2. Engineering Drawing by Agarwal & Agarwal, Tata McGraw Hill Publishers

3. Engineering Drawing by M.B.Shah&B.C.Rana,Pearson Publications

ENGLISH COMMUNICATION SKILLS LAB


Subject Code: UGBS1P0618 L T P C

I Year / I Semester 0 0 3 1.5

Laboratory objectives:

1. To expose students to different expressions and usage of English

2. To inculcate the basic skills of communication in English Language

3. To enable students to acquire right pronunciation of English words

4. To prepare students to acquire employability skills

English Lab Activities:

UNIT-I: Introduction to sounds of English – Phonetic Transcription (2 sessions)

UNIT-II: Introduction to Stress and Intonation

UNIT-III: English for Social Purposes- Role play/ Situational Dialogues & Just a

minute ( 4 sessions)

UNIT-IV: Body Language (2 sessions)

UNIT-V : PPT Presentation ( General topics) (3 sessions)

Practice Work

UNIT-VI: Debate ( 2 sessions)

Laboratory Outcomes:

Upon the completion of the course, the students will be able to:

C01: Make use of correct sounds of English through phonetic transcription,

appropriate stress, intonation in speech.

CO2: Construct role plays, situational dialogues and just a minute talk for effective

oral communication.

CO3: Demonstrate appropriate body language for effective oral communication.

CO4: Construct suitable PPTs and organize them for better oral presentation.

CO5: Take part in debates to develop argumentative skills in discussions.


POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 - - - - - - - - 3 3 - 3

CO2 - - - - - - - - 3 3 - 3

CO3 - - - - - - - - 3 3 - 3

CO4 - - - - - - - - 3 3 - 3

CO5 - - - - - - - - 3 3 - 3

SOURCE BOOKS:

1. Cambridge English for Job Hunting – Colin Downes, CUP, 2009

2. English for Presentations, Oxford University Press

3. Body Language – Allan & Barbara Pease

4. Strengthen Your Communication Skills – Maruthi Publications

SEMICONDUCTOR PHYSICS LAB



LABORATORY OBJECTIVES:

1. To familiarize with the principles of semiconducting materials.

2. To strengthen students to understand physical concepts of semiconductors in a

better way.

3. To enhance analytical thinking and to improve to problem solving techniques

EXPERIMENTS: (Any Eight of the following to be done)

EXP1: Determination of single slit diffraction using Lasers.

EXP2: Study of I/V characteristics of PN junction diode

EXP3: Study of I/V characteristics of ZENER DIODE.

EXP4: L C R Series Resonance Circuit

EXP5: Energy Band gap of a Semiconductor p-n junction diode.

EXP6: Determine the Planck’s constant using photo-cell

EXP7: Characteristics of Thermistor

EXP8: Time constant of RC circuit.

EXP9: Bending losses of optical fibre

EXP10: STEWART AND GEE‟S APPARATUS

Magnetic field along the axis of a current carrying coil.

LABORATORY OUTCOMES:

CO-1: Apply the scientific knowledge to understand optical concepts

CO-2: Outline the characteristics of fundamental electronic devices to understand

their functioning

CO-3: Make of use of analytical knowledge and problem solving techniques to measure electronic parameters

CO-4: Compare the equivalence between theoretical and experimental values for electronic circuits


POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 3 2 - - - - - - - - - -

CO2 3 3 - - - - - - - - - -

CO3 3 3 - - - - - - - - - -

CO4 3 2 - 2 - - - - - - - -

WORKSHOP PRACTICE AND INNOVATION LAB

Subject Code: UGME1P0218 L T P C



1. To develop and enhance relevant technical hand skills required by the technician

working in the various engineering industries and workshops.

2. To impart basic know-how of various hand tools and their use in different

sections of manufacturing.

3. To build the understanding of the complexity of the industrial job in

manufacturing processes and production technology.

4. To Emphasis on various practices involved in technology of workshop practices.

LIST OF EXPERIMENTS: Part A

Workshop Practice

S.NO TITLE

CARPENTRY

1 T-Lap Joint

2 Cross Lap Joint

FITTING

3 V—Fit

4 Square Fit

TIN SMITHY

5 Taper Tray

6 Rectangular Box without lid

HOUSE WIRING

7 a) Parallel / Series Connection of three bulbs

b) Staircase Wiring/ Two Lamps controlled by two SPST Switches

8 Florescent Lamp

Welding

9 To make Lap Joint by Gas Welding

10 To make Butt Joint by Arc Welding

Part B

Innovation Lab

During the due course, the students have to design/develop/manufacture any

product and/or improve the process capabilities for better quality.

COURSE OUTCOMES:

At the end of course the student will be able to:

CO1: Use various tools to prepare basic carpentry, fitting and welded joints.

CO2: Fabricate various objects using sheet metal.

CO3: Make basic house wiring connections.

CO4: Design/Develop a prototype/product.


COs POs PSOs

1 2 3 4 5 6 7 8 9 10 11 12 1 2

CO1 3 - - 3 - - - - - - - 2 - -

CO2 3 - - 3 - - - - - - - 2 - -

CO3 3 - - 3 - - - - - - - 2 - -

CO4 3 3 3 3 - - - - - - - 2 - -

ENVIRONMENTAL SCIENCE

Subject Code: UGBS1A1018 L T P C


COURSE OBJECTIVES:

1. To educate students about environment, and its degradation.

2. To acquire awareness, sensitivity about biodiversity and understanding associate

problems.

3. To provide knowledge to solve environmental problems.

SYLLABUS:

12 hrs

UNIT-I: MULTIDISCIPLINARY NATURE OF ENVIRONMENTAL

STUDIES: Definition, Scope, Importance and sustainability - People,

institutions in the environment.

ECOSYSTEMS & BIODIVERSITY

Introduction to Ecosystem, types of Ecosystems ,Bio diversity its conservation:

Conservation of biodiversity: Insitu conservation, Exsitu conservation.

UNIT-II: ENERGY &WATER RESOURCES 6hrs

INTRODUCTION: Non-conventional energy resources (solar/wind/tidal) &

controlling in use of electricity and conventional energy sources( fossil fuels &

coal)Water management (rain water harvesting watershed management and

water conservation) Urban problems related to energy.

UNIT-III: ENVIRONMENTAL POLLUTION: 11hrs

Definition, Cause, effects and control measures of Air pollution, Water

pollution, Soil pollution, Noise pollution, nuclear hazards. Role of an individual

in prevention of pollution. – Pollution case studies. Global Environmental

Challenges: Stockholm and Rio Summit: Global warming and climate change,

acid rains, ozone layer depletion

SOLID WASTE MANAGEMENT: Sources, classification, effects and control

measures of urban and industrial solid wastes. Consumerism and waste

products.

UNIT-IV: SOCIAL ISSUES AND THE ENVIRONMENT: 6hrs

Resettlement and rehabilitation of people, its problems and concerns.

Environmental ethics: Environmental Protection Act –Air (Prevention and

Control of Pollution) Act. –Water Prevention and control of Pollution) Act –

Wildlife Protection Act –Forest Conservation Act-Issues involved in

enforcement of environmental legislation. –Public awareness

4hrs

UNIT-V: ENVIRONMENTAL MANAGEMENT: Impact Assessment and its

significance various stages of EIA, preparation of EMP and EIS, Environmental

audit. Ecotourism.

GREEN CHEMISTRY: Introduction & Principles. The student should submit a

report individually on any issues of Environmental Studies course and make a

power point presentation.

UNIT-VI 12hrs

I. Studying the nearest lake water/farm land/forest ecosystems and preparing

document and creating awareness programs among public in mitigating

pollution.

II.Conducting Mass level cycling for making aware of public in minimizing

use of fossil fuels.(ECO CLUB ACTIVITY)

III.Mass level plantation programs and involving students in government

Programs NEERU-CHETTU

IV.Poster presentation, involving the students in making aware of public

Avoiding the use of Non-biodegradable polythene covers, glasses,

bottles.

V. Involving the students in making aware of farmers use/preparing of natural

manure and avoiding use of Insecticides/pesticides and chemical fertilizers.

COURSE OUTCOMES:

CO 1: Create awareness towards environmental problems.

CO 2: Sensitize the students towards eco-friendly practices for the sustainable

development.

CO 3: Encourage the students to participate in environmental protection

activities.


POs PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12

CO1 3 - - 3 - - 3 - - - - -

CO2 3 - - - - - 3 - - - - -

CO3 3 - - - - - 3 - - - - 3

TEXT BOOKS:

1. Environmental Studies by R. Rajagopalan, 2nd Edition, 2011, Oxford

University Press.

2. A Textbook of Environmental Studies by Shashi Chawla, TMH, New Delhi.

3. Environmental Studies by P.N. Palaniswamy, P. Manikandan, A.

GeethEnviroa, and K. Manjula Rani; Pearson Education, Chennai.

REFERENCE BOOKS:

1. Text Book of Environmental Studies by Deeshita Dave & P. Udaya

Bhaskar, Cengage Learning.

2. Environmental Studies by K.V.S.G. Murali Krishna, VGS

Publishers,Vijayawada.

3. Environmental Studies by Benny Joseph, Tata McGraw Hill Co, New Delhi.

4. Environmental Studies by Piyush Malaviya, Pratibha Singh, Anoop singh:

Acme Learning, New Delhi.

I YEAR

II SEMESTER

ENGLISH – II



I Year / II Semester 3 0 0 3

COURSE OBJECTIVES:

1. To train student in all LSRW skills in order to make them independent lifelong

learners by availing of these four skills.

2. To prepare students to face the emerging challenges of the world.

3. To inculcate the habit of reading beyond academics among students and to

enable them to

be competent communicators on various platforms.

4. To expose students to different cultural and social contexts.

SYLLABUS:

UNIT-I:The Rule of Law by Stephen Hawking (from Stephen Hawking’s ‘The

Grand Design’) 8hrs.

Letter writing: Official and Business letters

Phrasal verbs and idiomatic expressions

UNIT-II:Malala Yousafzai’s Speech at the U N General Assembly 14hrs.

One word substitutes, Précis writing

Extempore speaking

Assignment-I : Each Student is required to present a report on a problem faced by

individuals or the society with an analysis and possible solutions. She

has to make an oral presentation of it in the class after the completion

of UNIT-II Examination. It is mandatory for all the students. It is for

Internal Assessment.

UNIT-III:Next Sunday by R.K.Narayana from his book ‘NEXT SUNDAY’

Essay writing – Descriptive, Expository, analytical and Narrative

Providing examples or evidence in writing 8hrs.

UNIT-IV:‘Give Us A Role Model’ from ‘Ignited Minds’ by A P J Adbul Kalam

Preparing a Resume/ C.V.

Redundancies and clichés in writing 13hrs.

Assignment-II : Each Student is required to present a report on a problem faced

by individuals or the society with an analysis and possible solutions.

She has to make an oral presentation of it in the class after the

completion of Unit-IV Examination. It is mandatory for all the students.

It is for Internal Assessment.

UNIT-V:Sudha Murthy’s Letter to JRD TATA

Common errors in English 7hrs.

UNIT-VI:A Review on the Movie ‘ Cast Away’ 14 hrs.

Report Writing

Information Transfer

Assignment-III : Each Student is required to submit a critical review of the

prescribed movie in the syllabus

COURSE OUTCOMES:


CO1: Develop a meaningful general essay or an essay from the prescribed

text.

CO2: Construct official and business letters.

CO3: Choose phrasal verbs and idioms effectively in oral and written

communication.

CO4: Make use of one word substitutes in précis, construct resumes and different

types essays with examples or evidence in writing.

CO5: Identify redundancies or clichés in writing and common errors in English.

CO6: Develop reports and transform information into paragraph(s).


POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 - - - - - - - - - 3 - 3

CO2 - - - - - - - - 3 3 - 3

CO3 - - - - - - - - - 3 - 3

CO4 - - - - - - - - - 3 - 3

CO5 - - - - - - - - - 3 - 3

CO6 - - - - - - - - - 3 - 3

SOURCE BOOKS FOR ENGLISH-II

1. The Grand Design- Stephen Hawking

2. Next Sunday – R K Narayan

3. Ignited Minds – A P J Abdul Kalam

Internet sources for:

Malala Yousafzai’s speech at the UN General Assembly

Sudha Murthy’s letter to JRD TATA

The Movie ‘Cast Away”

BOOKS FOR FURTHER REFERENCE

1. The Oxford guide to Writing & Speaking – John Seely

2. A Practical English Grammar Exercises 2 (Thrid Edition) – A.J. Thomson and A.V.

Martinet, Oxford University Press, New Delhi, 2007.

3. The Students’ Companion – Wilfred D. Best (New Edition) – Harper, Collins

Publishers, 2012.

4. Col-Locate Your World, A store house of words & word-relations, their similarities

& dissimilarities – Ajay Singh, Arihant Publications (I) Pvt. Ltd., Meerut.

4. English Conversation Practice – Grant Taylor, Tata Mc Graw-Hill Publishing

Company Limited, New Delhi, 2007.

5. Verbal Workout – Intensive practice to boost your English Vocabulary,

Educational Software Technologies

6. The Official Cambridge Guide to IELTS, For Academic & General Training, (With

DVD-ROM), Student Book with Answers, 2015.

7. Immortal Speeches, Complied by Harshvardhan Dutta, Unicorn Books Pvt. Ltd.,

Distributors – Pustak Mahal, Delhi.

MATHEMATICS-II




Course Objectives:

To assist the students in learning and applying the concepts of partial

differentiation to solve real world problems.

To train the students to deal with improper integrals and multiple integrals.

To prepare the students to learn the concepts of Vector calculus.

SYLLABUS:

Unit -I: Partial Differentiation 11hrs.

Partial Differentiation, Total derivative; Jacobian, Functional dependence, Maxima,

minima of functions of two and three variables, Lagrange method of undetermined

multipliers.

Unit -II: Special Functions 8hrs.

Definition of Improper integrals, Beta and Gamma functions and their properties.

Unit-III: Multiple Integrals 12hrs.

Evaluation of Double Integrals (Cartesian and polar coordinates), change of order of

integration (only Cartesian form). Evaluation of Triple Integrals: Change of variables

(Cartesian to polar) for double and triple integrals.

Unit-IV: Vector Differentiation 12hrs.

Vector point functions and scalar point functions. Gradient, Divergence and Curl,

Solenoidal and Irrotational Vectors. Directional derivative, Vector Identities.

Unit-V: Vector Integration 13 hrs.

Line, Surface and Volume Integrals. Green’s, Gauss and Stoke’s Theorems (without

proofs) and their applications involving cubes, sphere and rectangular

parallelepipeds.

Unit-VI: Applications 10hrs.

Areas (by double integrals) and volumes by (by double integrals, by triple integrals),

Centre of mass and Gravity (constant and variable densities) by double and triple

integrals, Scalar potential function.Work done by force as a line integral.

COURSE OUTCOMES:

Upon completion of the course the students will be able to

CO1: Apply the concepts of Partial differentiation to Jacobians and Extrema of several variable functions. CO2: Evaluate various kinds of improper integrals using Beta and Gamma functions. CO3: Evaluate double and triple integrals in Cartesian and Polar coordinates over

given regions.

CO4: Apply multiple integrals to find area, volume center of mass, center of gravity

of given region/object.

CO5: Determine the Gradient, Divergence of a vector field using vector

differentiation and prove identities relating to them.

CO6: Evaluate vector integrals (Line, surface, volume) and justify the relation

between them by integral theorems.


POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 3 3 3 2 - - - - - - - 3

CO2 3 3 3 2 - - - - - - - 3

CO3 3 3 3 2 - - - - - - - 3

CO4 3 3 3 2 - - - - - - - 3

CO5 3 3 3 2 - - - - - - - 3

CO6 3 3 3 2 - - - - - - - 3

TEXT BOOKS:

1. B.S. Grewal, Higher Engineering Mathematics, Khanna Publishers

2. Ramana B.V., Higher Engineering Mathematics, Tata McGraw Hill New Delhi, 11th

Reprint, 2010.

3. N.P. Bali and Manish Goyal, A text book of Engineering Mathematics, Laxmi

Publications, Reprint, 2008.

REFERENCE BOOKS:

1. W. E. Boyce and R. C. DiPrima, Elementary Differential Equations and Boundary

Value Problems, 9th Edn., Wiley India, 2009.

2. D. Poole, Linear Algebra: A Modern Introduction, 2nd Edition, Brooks/Cole,

2005.

3. Veerarajan T., Engineering Mathematics for first year, Tata McGraw-Hill, New

Delhi,2008.

4. G.B. Thomas and R.L. Finney, Calculus and Analytic geometry, 9th Edition,

Pearson,Reprint, 2002.

5. Erwin kreyszig, Advanced Engineering Mathematics, 9th Edition, John Wiley &

Sons, 2006.

APPLIED CHEMISTRY

(Common to CSE & IT)



COURSE OBJECTIVES:

1. To provide basic building blocks of Engineering by coverage of Fundamental Chemistry Topics.

2. To Provide Information on exciting new materials now available in Engineering. 3. Technical growth that could motivate a new generation of Engineers.

SYLLABUS :

UNIT-I: ATOMIC AND MOLECULAR STRUCTURE 11hrs.

Molecular orbitals of diatomic molecules and plots of the multicenter orbitals. Energy

level diagrams of diatomic molecules (O2, Cl2, H2 and N2). Pi-molecular orbitals of

butadiene. Crystal field theory and the energy level diagrams for transition metal

ions (Octahedral-Mo(CO)6, [Co(NH3)6 ]+3) and their magnetic properties.

UNIT-II:ELECTRO CHEMISTRY AND CORROSION 10hrs.

EMF, Cell reactions, cell representation, cell potentials, Nernst equation and

applications. Conductance- specific, equivalent and molar conductance. Reference

electrode-SHE, calomel and glass electrode. Batteries-Primary cell, secondary cell (Li

ion and Pb-acid battery. Fuel cells- H2-O2, methanol-oxygen cell

Dry and wet corrosion and their mechanisms. Pilling - Bedworth Rule. Types of

Corrosion – galvanic corrosion, concentration cell corrosion, pitting corrosion and

stress corrosion. Factors influencing corrosion. Corrosion Prevention methods –

Cathodic protection – Sacrificial anodic method and Impressed current method.

Metallic coatings –galvanization, tinning and electroplating.

UNIT-III:ENGINEERING MATERIALS 8hrs.

Polymers-Definition and types–mechanism of free radical addition polymerization,

condensation polymerization-Terylene, conducting polymers classification with poly

acetylene, bio degradable polymers (Poly lactic acid, poly vinyl alcohol). Preparation

properties and applications of Bakelite, nylon-6,6 and Teflon. Rubbers and

elastomers-natural rubber, Thiokol. Nano Composites – Classification, Matrix face

and dispersed phase and applications

UNIT-IV : ORGANIC REACTIONS AND SPECTROSCOPY 5hrs.

Introduction to addition reactions, substitution reactions (SN1, SN2) and elimination

reactions (E1,E2) aliphatic only, Oxidation-Reduction reactions(K2Cr2O7, KMnO4,

hydrogenation, NaBH4 and LiAlH4).Principles of UV, IR, NMR, Mass – selection rules

and applications.Preparation of Drugs-Definition, Classification, Structure and uses

of Asprin and Ibuprofen.

UNIT-V:WATER TECHNOLOGY 8hrs.

Hardness of water – Types, Units and Numerical problems on hardness- EDTA

method, potable water treatment, steps involved in treatment. RO method, Ion-

exchange method. Boiler troubles-Sludge, scale, Priming, foaming, caustic

embrittlement and boiler corrosion their prevention.

UNIT-VI :STEREOCHEMISTRY 12hrs.

Representations of three dimensional structures-Newmann-Sawhorse

Representations, Structural Isomers-Chain-position-functional, Stereo Isomers-

Conformational isomerism (Ethane)-Configurations (Geometrical and Optical),

Elements of Symmetry-Plane of symmetry and centre of symmetry and Chirality,

Enantiomers, Diastereomers and Optical Activity of lactic acid.

COURSE OUTCOMES:

CO 1. Analyze microscopic chemistry in terms of atomic and molecular orbitals

and intermolecular forces.

CO 2. Summarize the basic concepts of electrochemistry and distinguish the

working principles of batteries and fuel cells.

CO 3. Distinguish the types of corrosion, and apply corrosion preventive methods

in the field of Engineering.

CO 4. Illustrate the types and properties of Polymers and their applications in

various industries.

CO 5. Distinguish the ranges of the electromagnetic spectrum used for exciting

different molecular energy levels in various spectroscopic techniques.

CO 6. Illustrate major chemical reactions that are used in the synthesis of

molecules.

CO 7. Summarize the boiler troubles due to hard water in boilers.

CO 8. Choose suitable method involved in water treatment depending on the

contaminants.

CO 9. Outline the spatial arrangement of atoms in the molecules.



CO1 3 - - - - - - - - - - -

CO2 3 2 - - - - 3 - - - - -

CO3 3 2 - - - - 3 - - - - -

CO4 3 - - - - - 3 - - - - -

CO5 3 2 - - - - - - - - - -

CO6 3 - - - - - - - - - - -

CO7 3 - - - - - 3 - - - - -

CO8 3 - - - - - - - - - - -

CO9 - 2 - - - - - - - - - -

TEXT BOOKS

1. Text book of Engineering Chemistry by Jain & Jain. Dhanpat Rai Publishing Company, 16th Edn., 2015.

2. A Text book of Engineering Chemistry by Shashi Chawla. Dhanpat Rai Publications, 3rd Edn., 2013.

3. A text book of Organic Reactions Stereochemistry and Mechanism by P.S. Kalsi, 9th Edition, 2016.

4. A text book of Organic chemistry by Bahl and bahl, S. Chand Publications, 21st Edition, 2017.

5. A text book of Inorganic chemistry by J.D.Lee, Wiley india edition. REFERENCE BOOKS

1. A Text book of Engineering Chemistry by S.S.Dara. S.Chand & Company Ltd., 12th Edn.,2010.

2. A Text book of Engineering Chemistry Shika Agarwal, Cambridge, 2015 Edition 3. A text book of Engineering Chemistry by Rath, Rama Devi, Reddy, Cengage

Learning Indian pvt Ltd., 2016 4. A Text book of Chemistry, principles and applications by M.J.sienko and

R.A.Plane. 5. Fundamentals of molecular spectroscopy by C.N.Banwell 6. A Text book of Physical chemistry by P.W. Atkins 7. A Text book of Organic chemistry: structure and function by K.P.C.Volhardt and

N.E. Schore,5th edition 8. A text book of Inorganic chemistry by Dr.Wahid U.Malik, S.Chand publication, revised edition.

PROGRAMMING FOR PROBLEM SOLVING


Subject Code: UGCS2T0118 L T P C I Year / II Semester 3 0 0 3

Prerequisites: Basic knowledge in Mathematics and Logical Skills.

Course Objectives:

The students will learn about Computer components and program development

steps. They will understand the concepts of algorithms, flowcharts and basic

concepts in C Programming language like operators, control statements and loops.

They can develop modular and readable C programs using the concepts like

pointers, functions, structures and files.

Syllabus:

UNIT I: 7 hrs

Problem Solving: Basic Computer Organization, Algorithm, Pseudo code,

Flowchart, Program development steps, Computer Languages: Machine, Symbolic

and High-level languages.

UNIT II: 8 hrs

Basics of C: History of C, Structure of a C program, C tokens, Identifiers, Data

types, Constants, Variables, Input/Output Statements, Creating and running

programs, Operators, Precedence and order of evaluation, Type conversion.

Selection Statements: Simple If, If-else, Nested if-else, Else-if, Switch statement

and Examples.

UNIT III: 8 hrs

Loop Statements: While, Do-while, For, Continue, Break and Goto statements.

Arrays: Arrays declaration, Definition, Accessing elements, Storing elements, 1-D

arrays, 2-D arrays and Multidimensional Arrays. Searching and Sorting: Linear

and Binary Search, Bubble sort, Selection sort.

UNIT IV: 8 hrs

Functions: Basics, Categories of functions, Parameter passing mechanism, Passing

an Array to a Function, Scope rules, Storage Classes, C Pre-processor directives.

Recursion: Recursion versus Iterations, Recursive solutions for factorial, Fibonacci

series and GCD.

UNIT V: 8 hrs

Pointers: Introduction, Pointer Arithmetic, Array of Pointers, Pointers to Pointers,

Pointers to Functions, Dynamic memory allocation functions, Command-line

arguments.

Strings: Concepts, String Input/Output functions, Arrays of Strings, String

manipulation functions.

UNIT VI: 10 hrs

Structures: Declaration, definition and initialization of Structures, Accessing

Structures, Nested Structures, Arrays of Structures, Structures and Functions,

Pointers to Structures, Bit fields, Unions, Type definition (typedef), Enumerated

types.

Files: Introduction to Files, Types of Files, Modes of Files, Accessing Files, File

Input/Output functions, File handling functions, Applications of Files.

Course Outcomes:


CO1: Design algorithms for arithmetic and logical problems.

CO2: Apply basic programming skills for translating algorithms into programs.

CO3: Analyze complex problems and develop solutions by modularization.

CO4: Develop programs using pointers, strings, structures and files.

Mapping of COs to POs :

POs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

CO1 3 3 3 3 - - - - - - - -

CO2 3 3 3 3 3 - - - - - - -

CO3 3 3 3 3 3 - - - - - - -

CO4 3 3 3 3 3 - - - - - - -

TEXT BOOKS :

1. Reema Thareja, Programming in C, OXFORD. 2. Dennis Ritchie and Brian Kernighan, The C programming Language, Prentice Hall.

REFERENCE BOOKS:

1. Herbert Schildt, C: The Complete Reference,4th Edition, Osborne Mc Graw Hill. 2. B. A. Forouzan and R. F. Gilberg, Computer Science: A Structured Programming Approach using C, 3rd Edition, Thomson Publications. 3. Yashawanth Kanethkar, Let us C, 8th Edition, Jones & Bartlett Publishers. 4. Stephen G. Kochan, Programming in C, 3rd Edition, Pearson Education Private Limited. 5. E. Balagurusamy, C Programming and Data Structures, TMH.

BASIC ELECTRICAL & ELECTRONICS ENGINEERING

Subject Code: UGEE2T0218 L T P C


Prerequisites: Engineering Physics

Course Objective: The basic input to all engineering is the electric energy. A basic

course on Electrical Engineering is almost essential for all engineering students. This

course will offervarious features of Electrical & Electronics Engineering starting from

simple DC circuits, Transformers, various DC & AC machines, and Electronic devices.

SYLLABUS:

UNIT I: DC Circuits 10 hrs

Electrical circuit parameters (R, L and C), ohms law, Kirchhoff current and voltage

laws, voltage and current sources, series and parallel circuits, voltage and current

division rule, analysis of simple circuits with dc excitation (independent sources

only), Star to delta transformation

UNIT II: DC Machines 11 hrs

Construction, working of DC Generator, EMF Equation, types and characteristics of

DC generators, Principle of DC motor Torque Equation of Motor, types of DC Motors,

Torque-speed characteristic and speed control of DC motor.

UNIT III: Transformers 9 hrs

Construction, Principle of operation, types, EMF Equation of a Transformer, OC and

SC tests, efficiency and regulation, simple problems

UNIT IV: AC Machines 9 hrs

Construction and working of three-phase Induction motor, types, slip-torque

characteristics. Construction and working of Alternators, types, EMF equation,

regulation by synchronous impedance method

UNIT V: Electronic Devices 10 hrs

PN junction diodes, types, V-I characteristics. Transistors, types, characteristics.

Principle of operation of Half wave, Full wave rectifiers and bridge rectifiers,

Introduction to OP-AMPs

UNIT VI: Amplifiers and Oscillators 9 hrs

Biasing Methods, Classification of Amplifiers, Feedback Amplifiers, Transistor as an

Amplifier, frequency response of CE Amplifier, Principles of Oscillators – RC Phase

Shift, Wien Bridge.

COURSE OUTCOMES:

CO1: To Interpret and analyze basic electric circuits with DC excitation.

CO2: To demonstrate the working principles of DC machines.

CO3: To analyze the constructional features of Transformers and to study of its

working principle.

CO4: To explain the constructional features and study of AC machines.

CO5: To summarize the working principles of Diodes, Transistors and analyze their

characteristics.

CO6: To classify the working principles of the different types of Amplifiers &

Oscillators.


POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 3 3 - - - - - - - - - -

CO2 3 3 - - - - - - - - - -

CO3 3 3 - - - - - - - - - -

CO4 3 3 - - - - - - - - - -

CO5 3 3 - - - - - - - - - -

CO6 3 3 - - - - - - - - - -

TEXT BOOKS:

1. “Basic Electrical Engineering” by Nagsarkar,,Sukhija, 2nd edition, Oxford

University Press, 2005

2. “Basic Electrical Engineering” by M. S. Naidu & S. Kamaksiah, TMH publications

3. “Basic Electrical Engineering” by S. N. SINGH, PHI learning, 2011.

REFERENCE BOOKS:

1. “Basic Electrical Engineering” by C. L. Wadhwa, 4th edition, New Age Publishers,

2007.

2. “Basic Electrical Engineering”, by D. C. Kulshreshtha, 2nd edition, McGraw Hill,

2009.

3. “Basic Electrical Engineering”, D. P. Kothari and I. J. Nagrath, 3rd edition, Tata

McGraw Hill, 2010.

BUSINESS COMMUNICATION LAB



I Year / II Semester 0 0 3 1.5


1. To expose student to different situations for better communication

2. To inculcate the habit of learning vocabulary for effective communication

3. To enable students to acquire Business English communication

ENGLISH LAB ACTIVITIES:

UNIT – I: (2 sessions)

Listening: Listening to short conversations or monologues

Speaking: Giving information about oneself and their opinions and Giving a

short talk on business related topics

Reading: Reading short and simple texts to understand the central idea/theme.

Writing: Writing a piece of internal business communication of 30-40 words

(Email)

UNIT – II: (2 sessions)

Listening : Listening to a conversation/ monologue and taking notes

Speaking : Giving short talk on business related topics.

Reading: Matching descriptions of people to short texts. Matching statements to

Information given in a graph or graphs.

Writing : Writing a piece of internal business communication of 30-40 words

(Message)

UNIT – III (2 sessions)

Listening: Listening to longer conversations/interviews.

Speaking: Extempore

Reading : Reading a longer text and deciding whether the statements

about the text are right or wrong or if the information is not given.

Writing : Write a business letter or e-mail of 60-80 words, based on

an input text and some notes.

UNIT – IV (2 sessions)

Listening: Listening to TV news channels and taking notes.

Listening to songs and writing down the lyrics.

Speaking: Interview sessions

Reading: Read a longer text and answering questions. .

Writing: Writing a Business Report

UNIT – V: (2 sessions)

Listening: Watching short documentaries and making notes.

Speaking: Short plays, Presentations.

Reading : Read short texts and fill in a form using information from the texts.

Writing : Write a skit and enact.

UNIT – VI: (2 sessions)

Listening: Watching documentaries and making notes.

Speaking: Nail your point.

Reading : Critical Reading to know author’s perspective.

Writing : Write a skit and enact.

COURSE OUTCOMES:


CO1: Develop listening skills through short or long conversations, monologues,

interviews, TV news channels as well as watch documentaries and take

notes.

CO2: Demonstrate speaking skills through talking about oneself, opinions, about

business related topics and speak one’s opinion.

CO3: Examine speaking skills through giving extempore, participating in skits, short

plays, presentations and mock interviews.

CO4: Build reading skills through general or critical reading of simple or longer

texts to understand theme, to match statements correctly, to answer

questions and to know author’s perspective.

CO5: Apply writing skills with the practice of taking or making notes, emails or

messages with a maximum of 40 or 80 words.

CO6: Test for writing skills through reports or skits.

CO7: Develop Listening, Speaking, Reading and Speaking skills for effective

communicator in writing as well as speaking for business purposes.


POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 - - - - - - - - 3 3 - 3

CO2 - - - - - - - - 3 3 - 3

CO3 - - - - - - - - 3 3 - 3

CO4 - - - - - - - - 3 3 - 3

CO5 - - - - - - - - 3 3 - 3

CO6 - - - - - - - - 3 3 - 3

CO7 - - - - - - - - 3 3 - 3

REFERENCE BOOKS:

1. Cambridge English – Business English Certificate Preliminary

2. Suresh Kumar. E. & Sreehari P.A (2007), Handbook for English Language

Laboratories,

3. Cambridge University Press India Pvt. Ltd, New Delhi.

4. Mandal S. K (2006),Effective Communication & Public Speaking , Jaico

Publishing House, New Delhi.

5. Grant Taylor (2004), English Conversation Practice, Tata McGraw Hill, New Delhi.

6. Balasubramanian .T (2000), A text book of English Phonetics for Indian

Student, MacMillan Publishers, India.

7. Kamalesh Sadanand, Susheela Punitha (2008), Spoken English: A foundation

Course: Parts 1& 2, New Delhi, Orient Longman Pvt. Ltd

WEB REFERENCES: 1. www.cambridgeenglish.org. 2. www.esl-lab.com

http://www.cambridgeenglish.org/

http://www.esl-lab.com/

APPLIED CHEMISTRY LAB

(Common to CSE & IT )


I Year / II Semester 0 0 3 1.5


1. To learn various analytical techniques for analyzing and solving engineering

problems.

2. To understand the principles associated with basics of engineering chemistry

and applications of these principles in avoiding common difficulties.

EXPERIMENTS:

Exp1: Introduction to chemistry laboratory – Quantitative analysis, Qualitative

analysis Molarity, Normality, Primary, Secondary standard solutions,

Volumetric titrations

Exp2: Determination of ferrous ion by dichromometry.

Exp3: Determination of total hardness of given water sample by EDTA method

Exp4: Conductometric Titrations between strong acid and strong base

Exp5: Potentiometric Titrations between strong acid and strong base

Exp6: Determination of surface tension of polymer/organic liquid

Exp7: Determination of Rate Constant of a reaction

Exp8: Adsorption of Acetic acid by Charcoal

Exp9: Thin Layer Chromatography

Exp10: Synthesis of Aspirin

Exp11: Synthesis of Urea-Formaldehyde

LABORATORY OUTCOMES :

CO 1: Apply the basic knowledge on volumetric and quantitative analysis.

CO 2: Analyse the parameters to measure the quality of water samples.

CO 3: Measure Physical and chemical properties of organic solvent sand solutions

used in Engineering.

CO 4: Apply the knowledge to synthesize a drug or a polymer.



CO1 3 - - - - - - - - - - -

CO2 3 2 - - - - 3 - - - - -

CO3 3 2 - - - - - - - - - -

CO4 3 - - - - - - - - - - -

PROGRAMMING FOR PROBLEM SOLVING LAB

(Common to All Branches) Subject Code: UGCS2P0218 L T P C I Year / II Semester 0 0 3 1.5

Prerequisites: Basic knowledge in Mathematics and Logical Skills.

Course Objectives:

The students will learn to develop the programs for solving the basic problems using

Operators, Control statements and Loops. They will able to write programs using

concepts like Arrays, Strings, Pointers, Functions and Files.

List of Experiments:

EXP 1: a. Write a C program that will output your name and address using a separate

printf() statement for each line of output. b. Modify your solution for the previous program so that it produces all the

output using only one printf() statement.

c. Write a C program to output the following text exactly as it appears here: " C is just like sea……" she said. d. Write a C program that prompts the user to enter a distance in inches and

then outputs that distance in yards and feet.

e. Write a C program to convert the temperature from degree Centigrade to

Fahrenheit and vice versa.

EXP 2: a. Write a C program to find the largest of three numbers using nested if-else.

b. Write a C Program to swap two numbers without using a temporary variable.

c. Write a C simple program based on operators (pre, post increment, bitwise and, or, etc.).

d. Write a C simple program based on type conversions (from int to float and float to int).

EXP 3:

a. Write a C program that displays all the numbers from X to Y, that are divisible by a and b. (X,Y,a and b should be read from the key board)

b. Write a C program that reads an unspecified number of integers, determines

how many positive and negative values have been read, and computes the

total and average of the input values, not counting zeros. Your program ends

with the input 0. Display the average as a floating-point number. (For

example, if you entered 1, 2, and 0, the average should be 1.5.)

c. Write a C program for finding student Grade by reading marks as input.

EXP 4: a. The total distance travelled by vehicle in ‘t’ seconds is given by distance s =

ut+1/2at2 where ‘u’ and ‘a’ are the initial velocity (m/sec.) and acceleration (m/sec2). Write a C program to find the distance travelled at regular intervals of time given the values of ‘u’ and ‘a’. The program should provide the flexibility to the user to select his own time intervals and repeat the calculations for different values of ‘u’ and ‘a’.

b. Write a C program, which takes two integer operands and one operator from the user, performs the operation and then prints the result. (Consider the operators +,-,*, /, % and use Switch Statement)

c. Write a C Program to enter a decimal number, calculate and display the binary equivalent of that number.

EXP 5: a. Write a C program to find the sum of individual digits of a positive integer and

find the reverse of the given number. b. A Fibonacci sequence is defined as follows: the first and second terms in the

sequence are 0 and 1, Subsequent terms are found by adding the preceding two terms in the sequence. Write a C program to generate the first n terms of the sequence.

c. Write a C program to generate all the prime numbers between 1 and n, where n is a value supplied by the user.

EXP 6: a. Write a C program to check whether the given number is Armstrong number or not.

b. Write C programs for the following series:

c. Write a C program to find the roots of a Quadratic equation.

EXP 7:

a. Write C programs that use both recursive and non-recursive functions i. To find the factorial of a given integer. ii. To find the GCD (greatest common divisor) of two given integers.

b. Write C programs for implementing Storage classes: (Auto, register, static, extern)

EXP 8:

a. Write a C program to find the minimum and maximum integer of an Array. b. Write a C program that uses functions to perform the following:

i. Addition of Two Matrices ii. Multiplication of Two Matrices

EXP 9:

a. Write a C program to construct the following pyramid of numbers.

1 1 2 1 2 3

*

* *

* * *

1

2 3

4 5 6

A B B C C C D D D D E E E E E

EXP 10:

a. Write a C program to swap two numbers using call by reference method. b. Write a C program that uses a pointer to read and display Array elements. c. Write a C program to create an array with calloc(), store the values into it and

find their sum. EXP 11:

a. Write a C program to find length of the given string without using strlen(). b. Write a C program that uses functions to perform the following operations:

i. To insert a sub-string in to a given main string from a given position. ii. To delete n Characters from a given position in a given string.

c. Write a C program to determine if the given string is a palindrome or not. EXP 12:

a. Write a C program to implement Linear search. b. Write a C program to implement sorting of an array using Bubble sort.

EXP 13:

a. Examples which explores the use of structures, union and other derived data types.

EXP 14:

a. Write a C program which copies the contents of one file to another. b. Write a C program to count the number of characters and number of lines in

a file. c. Write a C Program to merge two files into a third file. The names of the files

must be entered using command line arguments. d. Write a C program that copies the characters from position X to position Y

from one file to another file.

Course Outcomes:

Upon completion of course, the students will be able to:

CO 1. Test and execute the programs and correct syntax and logical errors. CO 2. Develop programs for the basic mathematical and general problems. CO 3. Analyze complex problems and break them into logical modules and

interpret the results.


POs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

CO1 3 3 3 3 3 - - 3 3 3 - -

CO2 3 3 3 3 3 - - 3 3 3 - -

CO3 3 3 3 3 3 - - 3 3 3 - -

TEXT BOOKS:

1. Byron Gottfried, Jitender Chhabra, Programming with C (Schaum's Outlines

Series), Mc Graw Hill Publishers.

2. Yashwanth Kanetkar, Let us C, 8th Edition, Jones & Bartlett Publishers.

REFERENCE BOOKS:

1. Herbert Schildt, C: The Complete Reference, 4th Edition, Mc Graw Hill.

2. B. A. Forouzan and R. F. Gilberg, Computer Science: A Structured

Programming Approach using C, 3rd Edition, Thomson Publications.

INDIAN CONSTITUTION



COURSE OBJECTIVES:

1. To train students in understanding the basic structure of Indian Constitution

2. To prepare students to live better and happily with other fellow beings through

the application of Fundamental Rights in their lives.

SYLLABUS:

UNIT-I: Introduction to Indian Constitution

Meaning of the term Indian Constitution –Preamble- Constituent Assembly- Salient

Features of Indian Constitution

UNIT-II: Fundamental Rights

Fundamental Rights -Fundamental Duties -The Directive Principles of State Policy

UNIT-III: Union Government

Union Government -Union Legislature (Parliament) -Lok Sabha and Rajya Sabha (with Powers and Functions) -Union Excecutive -President of India (with Powers and Functions) -Prime Minister of India (with Powers and Functions) -Union Judiciary (Supreme Court) -Jurisdiction of the Supreme Court

UNIT-IV State Government

State Government -State Legislature (Legislative Assembly / Vidhan Sabha,

Legislative Council / Vidhan Parishad) -Powers and Functions of the State

Legislature -State Executive-Governor of the State (with Powers and Functions) -The

Chief Minister of the State (with Powers and Functions) -State Judiciary (High

Courts)

UNIT-V: Local Self Governance

Powers and functions of Municipalities, Panchyats, ZP’s and Co – Operative Societies

UNIT-VI: Sovereign Bodies

Election Commission of India (with Powers and Functions) -The Union Public Service

Commission (with Powers and Functions)

http://indianconstitution4ba.blogspot.in/2012/10/what-is-constitution.html

http://indianconstitution4ba.blogspot.in/2012/08/preamble.html

http://indianconstitution4ba.blogspot.in/2012/08/preamble.html

http://indianconstitution4ba.blogspot.in/2012/08/salient-features-of-indian-constitution.html

http://indianconstitution4ba.blogspot.in/2012/08/salient-features-of-indian-constitution.html

http://indianconstitution4ba.blogspot.in/2012/10/union-government-of-india.html

http://indianconstitution4ba.blogspot.in/2012/10/state-government.html

http://indianconstitution4ba.blogspot.in/2012/10/vidhan-sabha.html

http://indianconstitution4ba.blogspot.in/2012/10/vidhan-sabha.html

http://indianconstitution4ba.blogspot.in/2012/10/powers-and-functions-of-state.html

http://indianconstitution4ba.blogspot.in/2012/10/powers-and-functions-of-state.html

http://indianconstitution4ba.blogspot.in/2012/10/state-executive.html

http://indianconstitution4ba.blogspot.in/2012/10/state-executive.html

http://indianconstitution4ba.blogspot.in/2012/10/state-judiciary.html

http://indianconstitution4ba.blogspot.in/2012/10/state-judiciary.html

COURSE OUTCOMES:

Upon the completion of the course, the student will be able to:

CO1: Examine salient features of Indian Constitution and live accordingly in society.

CO2: Interpret the meaning of Fundamental Rights and Directive Principles of State

Policy and, develop an attitude which paves the way for better living

conditions.

CO3: Discover various aspects of Union Government legislation and live up to the

expectations of the rules.

CO4: Critically examine State Government legislation and improve your living

standards by following the rules strictly.

CO5: Examine powers and functions of local bodies such as Muncipalities and

Panchayats and,take advantage of available resources for better living.

CO6: Analyze the powers and functions of Election Commission and The Union

Public Service Commission and decide upon it for safe and secured life.


POs 1 2 3 4 5 6 7 8 9 10 11 12

CO1 3 - - - - - - - - - - -

CO2 - 3 - - - - - - - - - -

CO3 - - 3 - - - - - - - - -

CO4 - - - 3 - - - - - - - -

CO5 - - - - 3 - - - - - - -

CO6 - - - - - 3 - - - - - -

BOOKS: 1. Introduction to constitution of India, Durga Das Basu, Lexis Nexis Publications

2. Constitution of India by PRFESSIONAL BOOK PUBLISHERS

3. The Constitution of India by Arun K Tiru vengadam, Blooms bury publishers.

4. The constitution of India by PM Bakshi, Universal law publishing co

5. The Constitution of India by S.R. Bhansali, Universal law publishing co

II Year

I Semester

PROBABILITY AND STATISTICS


II Year / I Semester 3 0 0 3

Prerequisites: Basic knowledge in Mathematics.

Course Objectives:

To expose students to present the theory and methods of ‘probability and statistics’ needed to support Engineering decision making.

To prepare students to create an understanding on various types of sampling distribution and their applications in Engineering.

To train students the basic principles of Statistical Inference.

Syllabus: UNIT I: (9 lectures)

Basic Statistics

Measures of Central Tendency: Mean, Median, Mode Measures of Dispersion: Variance, Standard deviation, Skewness and Kurtosis.

UNIT II: (8 lectures)

Basic Probability

Introduction to Probability, Conditional Probability, Baye’s Theorem on Probability;

Random Variables: Discrete and continuous - Probability function – density and

distribution function, Expectation of a Random Variable, Moments, Chebychev's

Inequality (Without proof).

UNIT III: (7 lectures)

Probability Distributions

Probability distributions: Binomial, Poisson and Normal - Evaluation of statistical

parameters: Mean, Variance and their properties, Introduction to Exponential,

Gamma and Weibull distributions.

UNIT IV: (7 lectures)

Bivariate Distributions

Curve fitting by the method of Least squares- Fitting of straight line, parabola and exponential curves, Simple Correlation and Regression – Rank correlation.

UNIT V: (7 lectures)

Sampling Distribution And Estimation

Introduction – Sampling distribution of means with known and unknown standard

deviation.

Estimation: Criteria of a good estimator, point and interval estimators for means and

proportions.

UNIT VI: (10 lectures)

Tests Of Hypothesis

Introduction-Type-I, Type-II Errors, Maximum Error, one –tail, two-tail tests,Test of significance: Large sample test for single proportion, difference of proportions, single mean, difference of means. Test of significance: Small sample test for single mean, difference of means and test of ratio of variances (F-Test) - Chi-square test for goodness of fit and independence of attributes.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Evaluate various measures of central tendency and dispersion of real data CO 2. Apply basic theorems of probability and Baye’s theorem to solve real time

Problems. CO 3. Classify the Random variable and Probability distribution involved in a given

problem and examine the relevant probabilities and parameters. CO 4. Construct a suitable curve to the given data using least squares method CO 5. Determine the Correlation and Regression of two variable quantities CO 6. Demonstrate the concepts of statistical estimation CO 7. Apply the principles of Hypothesis testing to draw conclusions about real time

data.

Mapping of COs to POs: POs/

COs PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12

CO1 3 3 2 3 - - - - - - - 3

CO2 3 3 2 3 - - - - - - - 3

CO3 3 3 2 3 - - - - - - - 3

CO4 3 3 2 3 - - - - - - - 3

CO5 3 3 2 3 - - - - - - - 3

CO6 3 3 2 3 - - - - - - - 3

CO7 3 3 2 3 - - - - - - - 3

TEXT BOOKS: 1. Dr.T.S.R.Murthy, Probability and Statistics for Engineers, BS Publications. 2. Ronald E. Walpole, Sharon L. Mayers and Keying Ye, Probability and Statistics for Engineers and Scientists, Pearson Education. 3. Miller, John E. Freund, Probability and Statistics for Engineers, PHI.

REFERENCE BOOKS:

1. Dr.T.S.R.Murthy, Probability and Statistics, I.K. International Publishing. 2. S.C.Gupta &V.K.Kapoor, Fundamentals of Mathematical Statistics, Sultan Chand. 3. Murugesan, Probability, Statistics and Random Processes, Anuradha Publishers. 4. S.C.Guptha, Fundamentals of Statistics, Himalaya Publishing.

DATA STRUCTURES

Subject Code: UGCS3T0118 L T P C


Prerequisites: The students must have thorough knowledge on the concepts of arrays, pointers, structures and functions along with basic constructs of C language to implement the data structure algorithms. Course Objectives: The course is intended to provide the foundations of the Data Structures and to emphasize the importance of Data Structures for efficient algorithms. The objective is to ensure that the student able study design and implement major linear and non-linear data structures along with performance analysis.

Syllabus: UNIT I: (9 Lectures)

Recursion and Linear Search: Preliminaries of algorithm, Algorithm analysis and

complexity. Recursion: Definition, Design Methodology and Implementation of recursive

algorithms, Linear and binary recursion, recursive algorithms for factorial function, GCD

computation, Fibonacci sequence, Towers of Hanoi, Tail recursion, List Searches using

Linear Search, Binary Search.

UNIT II: (8 Lectures)

Sorting Techniques: Basic concepts, Bubble Sort, Insertion sort, selection sort, quick

sort, radix sort , and merge sort Algorithms.

UNIT III: (8 Lectures)

Stacks: Basic Stack Operations, Representation of a Stack using Arrays, Stack

Applications: Infix- to postfix Transformation, Evaluating Arithmetic Expressions.

Queues: Basic Queues Operations, Representation of a Queue using array,

Implementation of Queue Operations, Applications of Queues-Round robin Algorithm,

Circular Queues.

UNIT IV: (8 Lectures)

Linked Lists: Introduction, single linked list, representation of a linked list in memory,

Operations on a single linked list, Reversing a single linked list, applications of single

linked list: Representing polynomial expressions, Linked List representation of Stack and

Queue, Circular linked list, Double linked list.

UNIT V: (8 Lectures)

Trees: Basic tree concepts, Binary Trees: Properties, Representation of Binary Trees

using arrays and linked lists, Binary Search Trees, operations on a Binary Search trees,

Binary Tree Traversals in recursive fashion, Creation of binary tree from in-order and

pre/post order traversals, Binary Heaps and heap sort, Balanced trees: Definition and

need.

UNIT VI: (7 Lectures)

Graphs: Definitions, Properties, Applications, Representation of Unweighted Graphs,

Weighted Graphs, Graph Search Methods: BFS, DFS Implementation.

Course Outcomes: Upon completion of this course, the students will be able to:

CO 1. Understand the principles, working methodologies and operations of both linear and nonlinear data structures.

CO 2. Demonstrate the design methodology and implementation of recursive and iterative algorithms to solve complex problems.

CO 3. Apply the techniques of data structures for formulating solutions to real world problems.

CO 4. Analyze time and space complexities to design searching and sorting algorithms for building optimal solutions.

CO 5. Compare performance analysis and choose suitable data structure for developing efficient applications.


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 3 - - - - - - - - - - 3 -

CO2 3 3 3 3 - - - - - - - - 3 -

CO3 3 3 3 3 - 3 - - - - - 3 3 -

CO4 3 3 3 3 - - - - - - - - 3 -

CO5 3 3 3 3 - 3 - - - - - 3 3 -

TEXT BOOKS: 1.Richard F, Gilberg, Forouzan, Data Structures, 2nd edition, Cengage.

2. Aaron M. Tenenbaum, YedidyahLangsam, Moshe J Augenstein, Data Structures

usingC, Pearson.

3. Mark Allen Weiss, Data structures and Algorithm Analysis in C, 2nd edition, Pearson

Education. Ltd.

REFERENCE BOOKS: 1.Jean-Paul Tremblay Paul G. Sorenson, An Introduction to Data Structures with

Applications, 2nd edition, Mc Graw Hill Higher Education.

2.Seymour Lipschutz, Data Structure with C, TMH.

3.Reema Thareja, Data Structures using C, 2nd edition, Oxford.

DIGITAL ELECTRONICS



Prerequisites: Basic knowledge in Boolean Algebra.

Course Objectives: This course helps students to acquire basic knowledge on number systems, logic gates, gate level minimization, combinational and sequential logic circuits, registers and counters and PLA’s.


Number Systems: Digital Systems, Binary, Decimal, Octal and Hexadecimal

Numbers, Conversion of Numbers from One Radix to another Radix, r’s Complement

and (r-1)’s Complements of Numbers, Signed Binary Numbers, Binary Codes.


Logic Gates and Boolean algebra: Basic Gates NOT, AND, OR, Boolean

Theorems, Complement And Dual of Logical Expressions, Universal Gates, XOR and

XNor Gates, SOP,POS, Minimizations of Logic Functions Using Boolean Theorems,

Two level Realization of Logic Functions Using Universal Gates.

Gate- Level Minimization: Karnaugh Map Method (K-Map): Minimization of

Boolean Functions maximum up to Four Variables, POS And SOP, Simplifications

With Don’t Care Conditions Using K-Map.


Combinational Logic Circuits: Design of Half Adder, Full Adder, Half Subtractor,

Full Subtractor, Ripple Adders and Subtractors, Ripple Adder/Subtractor Using Ones

and Twos Complement Method. Design of Decoders, Encoders, Multiplexers, De-

multiplexers, Higher Order De-multiplexers and Multiplexers, Priority Encoder, Code

Converters, Magnitude Comparator.


Introduction to Sequential Logic Circuits: Classification of Sequential Circuits,

Basic Sequential Logic Circuits: Latch and Flip-Flop, RS- Latch Using NAND and NOR

Gates, Truth Tables. RS, JK, T and D Flip Flops, Truth and Excitation Tables,

Conversion of Flip Flops. Flip Flops With Asynchronous Inputs (Preset and Clear).


Registers and Counters:Design of Registers, Buffer Register, Control Buffer

Registers, Bidirectional Shift Registers, Universal Shift Register, Design of Ripple

Counters, Synchronous Counters and Variable Modulus Counters, Ring Counter,

Johnson Counter.


Introduction to RAM and Programmable Logic Devices (PLDs): Introduction

to RAM: Read and Write operations, PLA, PAL, PROM, Realization of Switching

Functions using PROM, PAL and PLA. Comparison of PLA, PAL and PROM.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1 Summarize various number systems for computer arithmetic.

CO 2 Apply Boolean algebra principles to simplify the Boolean expressions.

CO 3 Interpret and design the combinational and sequential circuits.

CO 4 Distinguish various types of PLDs and recognize its relationship with switching

functions.


COs PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9

PO1

0

PO1

1

PO1

2

PSO

1

PSO

2

CO1 3 3 - - - - - - - - - - - -

CO2 3 3 - - - - - - - - - - - -

CO3 3 3 3 - - - - - - - - - - -

CO4 3 3 3 - - - - - - - - - - -

TEXT BOOKS:

1. M. Morris Mano, Michael D Ciletti, Digital Design , 5/e, Pearson. 2. Roth, Fundamentals of Logic Design, 5/e, Cengage.

REFERENCE BOOKS: 1. Kohavi, Jha, Switching and Finite Automata Theory, 3/e, Cambridge. 2. Leach, Malvino, Saha, Digital Logic Design, TMH. 3. R.P.Jain,Modern Digital Electronics, TMH.

DISCRETE MATHEMATICS



Prerequisites: Basic knowledge in Mathematics.

Course Objectives: This course will introduce various methods of representation and

manipulations of data. These methods in subsequent courses will be used in design and

analysis of algorithms, computability theory, digital logic gates, and software engineering

and computer systems.

Syllabus:

UNIT I: (10 Lectures)

Objectives: Acquiring the relevance of statements, inferences and predicates

in computer science

Mathematical Logic:

Propositional Calculus: Statements and Notations, Connectives, Truth Tables,

Tautologies, Equivalence of Formulas, Duality law, Tautological Implications, Normal

Forms, Theory of Inference for Statement Calculus, Consistency of Premises, Indirect

Method of Proof.

Predicate calculus: Predicative Logic, Statement Functions, Variables and Quantifiers,

Free & Bound Variables, Inference theory for predicate calculus.


Objectives: Overview of number theory, basic algorithms in number theory

and mathematical induction

Number Theory & Induction: Properties of integers, Division Theorem, The Greatest

Common Divisor, Euclidean Algorithm, Least Common Multiple(without proofs), Testing

for Prime Numbers, The Fundamental Theorem of Arithmetic, Modular Arithmetic.

Mathematical Induction: Principle of Mathematical Induction, Examples.


Objectives: Focuses on sets and relations and their operations

Set Theory:

Introduction, Operations on Binary Sets, Principle of Inclusion and Exclusion.

Relations: Properties of Binary Relations, Relation Matrix and Digraph, Operations on

Relations, Partition and Covering, Transitive Closure, Equivalence, Compatibility and

Partial Ordering Relations, Hasse Diagrams, The Principles of Inclusion – Exclusion,

Pigeonhole Principle and its Application.


Objectives: Functions, Types of Functions

Functions: Bijective Functions, Composition of Functions, Inverse Functions,

Permutation Functions, Recursive Functions.


Objectives: Exposure of graphs, their representation, types, trees and tree

variants

Graph Theory: Basic Concepts of Graphs, Sub graphs, Matrix Representation of Graphs:

Adjacency Matrices, Incidence Matrices, Isomorphic Graphs, Paths and Circuits, Eulerian

and Hamiltonian Graphs, Multigraphs, (Problems and Theorems without proofs) Planar

Graphs, Euler’s Formula, Graph Colouring and Covering, Chromatic Number, (Problems

and Theorems without proofs) Trees, Directed trees, Binary Trees, Decision Trees.


Objectives: Overview of algebraic structures, Group theory

Algebraic Structures, Lattice: Properties, Lattices as Algebraic Systems, Algebraic

Systems with one Binary Operation, Properties of Binary operations, Semi groups and

Monoids: Homomorphism of Semi groups and Monoids, Groups: Abelian Group,

Cosets, Subgroups (Definitions and Examples of all Structures) Algebraic Systems with

two Binary Operations, Rings.

Course Outcomes: Upon completion of this course, the students will be able to: CO1: Demonstrate inference theory of mathematical logic and basic algorithms of

number theory.

CO2: Illustrate the fundamentals of set theory, relations, functions and graphs.

CO3: Select appropriate methods for providing solutions using mathematical logic.

CO4: Identify principles of number theory, set theory for framing different algebraic

structures.

CO5: Apply various graph algorithms to real time problems.

CO6: Analyze mathematical logic statements and number theory concepts.

CO7: Classify algebraic structures based on the concepts of set theory, relations

and functions.

CO8: Compare various graph theory concepts to suit to real time applications


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 3 3 3 - - - - - - - - - -

CO2 3 3 3 3 2 2 - - - - - - - -

CO3 3 3 3 3 - - - - - - - - - -

CO4 3 3 3 3 - - - - - - - - - -

CO5 3 3 3 3 2 2 - - - - - - - -

CO6 3 3 3 3 - - - - - - - - - -

CO7 3 3 3 3 - - - - - - - - - -

CO8 3 3 3 3 2 2 - - - - - - - -

TEXT BOOKS:

1. Tremblay, Manohar, Discrete Mathematical Structures with Applications to Computer

Science, TMH.

2. Mott, Kandel, Baker, Discrete Mathematics for Computer Scientists & Mathematicians,

2/e, PHI.

3. Swapan Kumar Chakrborthy, Bikash Kanti Sarkar, Discrete Mathematics, Oxford.

4. Biswal, Discrete Mathematics and Graph theory, 3rd ed, PHI.

REFERENCE BOOKS:

1. CRC Press, Discrete Mathematics, Proofs, Structures and applications, 3rd ed.

2. S.Santha, Discrete Mathematics, Cengage.

3. JK Sharma, Discrete Mathematics, 2/e, Macmillan.

OBJECT ORIENTED PROGRAMMING



Prerequisites: Knowledge in C programming language.

Course Objectives: To teach the basic concepts and techniques which form the

object oriented programming paradigm. Student completing the course should know

the model of object oriented programming, Fundamental features of Java such as

class, object, interface, exception, multithreading and libraries of object collections

and build applications using Applet and swing components.

Syllabus: UNIT I: (8 Lectures) Introduction to OOP: Need of object oriented programming, principles of object oriented languages, OOP languages and Applications, history of JAVA, Java Virtual Machine, Java features. Programming Constructs: Primitive data types, Identifiers- Naming Conventions, Keywords, Literals, Operators- Binary, Unary and Ternary, Expressions, Primitive Type conversion and casting, Control statements. UNIT II: (8 Lectures) Classes and Objects- Classes, Objects, Creating objects, methods, constructors- constructor overloading, cleaning up unused objects- Garbage collector, class variable and methods, method overloading, static keyword, this keyword, arrays, Command line arguments, String and StringTokenizer.

UNIT III: (8 Lectures) Inheritance: Types of Inheritance, Deriving classes using extends keyword, super keyword, method overriding, abstract class, final keyword. Interfaces: Creating Interface, Extending Interface, Interface Vs Abstract class. Packages: Creating Packages, using Packages, Access protection. Exceptions: Introduction, Exception handling techniques-try…catch, throw, throws, finally block, user defined Exception.

UNIT IV: (9 Lectures) Multithreading: Java.lang.Thread, the main Thread, creation of new Threads, multiple Threads, using isAlive() and join(),Thread priority, Synchronization, Communication between Threads, suspending and resuming Threads.

UNIT V: (8 Lectures) Applets- Applet class, Applet structure, an example Applet program, Applet life cycle, paint() and repaint(). Event Handling- Introduction, Delegation Event Model, Events, Event Sources, Event Listeners, Adapter classes, Inner classes.

UNIT VI: (8 Lectures) Swing Components: Introduction, Swing Components hierarchy, Layout

Managers, JFrame, JPanel, JButton, JTextField, JPasswordField, JTextArea, JList,

JCombobox, JCheckBox, JRadioButton, JScrollPane, JSplitPane, JTabbedPane,

JOptionPane, JProgressBar.


CO 1. Understand the object oriented programming principles and various java

programming constructs.

CO 2. Design the GUI applications for the end users using applets and swings

with event handling.

CO 3. Apply the concepts of classes, objects and their relationship in solving the

computational problems.

CO 4. Analyze the usage of interfaces, packages, exception handling and

multithreading.


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 3 - - - - - - - - - - - -

CO2 - 3 3 - - - - - - - - - 3 -

CO3 3 3 3 - - - - - - - - - - -

CO4 3 3 3 - - - - - - - - - - -

TEXT BOOKS: 1.Herbert Schildt, Java The Complete Reference, McGraw Hill. REFERENCE BOOKS: 1. P.J.Dietel, Java for Programming, Pearson Education.

2. P.Radha Krishna, Object Oriented Programming through Java, Universities Press.

3. Bruce Eckel, Thinking in Java, Pearson Education.

4. S.Malhotra and S.Choudhary, Programming in Java, Oxford University Press.

DATA STRUCTURES LAB

Subject Code: UGCS3P0518 L T P C

II Year / I Semester 0 0 3 1.5

Prerequisites: Students should have the familiarity with the concepts of programming along with basic constructs of C language to implement the data structure algorithms. Course Objectives: The course is designed to introduce various techniques for representation of the data. Further, develop skills to design and analyze simple linear and non-linear data structures, to Strengthen the ability to identify and apply the suitable data structure for the given real-world problem, to Gain knowledge in practical applications of data structures. List of Experiments:

Exercise 1:

a) Write a recursive C program to calculate Factorial of an integer.

b) Write a recursive C program which computes the nth Fibonacci number, for

appropriate values of n.

Exercise 2:

a) Write a recursive C program to calculate GCD (n, m).

b) Write a recursive C program for Towers of Hanoi: N disks are to be transferred

from peg S to peg D with Peg I as the intermediate peg.

Exercise 3:

a) Write a C program that implements Selection sort, to sort a given list of integers

in ascending order.

b) Write a C program that implements Insertion sort, to sort a given list of integers

in ascending order.

Exercise 4:

a) Write a C program that implements Quick sort, to sort a given list of integers in

ascending order.

b) Write a C program that implements Radix sort, to sort a given list of integers in

ascending order.

c) Write a C program that implements Merge sort, to sort a given list of integers in

ascending order.

Exercise 5:

a) Write a C program that implements Stack (its operations) using arrays.

b) Write a C program that uses Stack operations to convert infix expression into

postfix expression.

Exercise 6:

a) Write a C program that implements Queue (its operations) using arrays.

b) Write a C program that implements Circular Queue (its operations) using arrays.

Exercise 7:

a) Write a C program that uses functions to create a singly linked list and its

operations(insert, delete, search).

b) Write a C program to reverse elements of a singly linked list.

Exercise 8:

a) Write a C program that implements Stack (its operations) using Linked list.

b) Write a C program that implements Queue (its operations) using Linked list.

Exercise 9:

a) Write a C program to create a Circular Linked list and its operations(insert,

delete, search).

b) Write a C program to create a Doubly Linked list and its operations( insert,

delete, search).

Exercise 10:

a) Write a C program to create a Binary Search Tree and its operations.

b) Write a recursive C program for traversing a Binary Search Tree in preorder,

inorder and postorder.

Exercise 11:

a) Write a C program to perform BFS traversal on given graph.

b) Write a C program to perform DFS traversal on given graph.


CO 1. Apply recursive and iterative methodologies to solve complex engineering problems.

CO 2. Solve searching and sorting techniques and evaluate time & space complexities.

CO 3. Develop solutions to create and implement operations of linear and nonlinear data structures.

CO 4. Identify and apply suitable data structure for a given real time problem. Mapping of COs to POs:

POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 3 3 3 - - - 3 3 3 - 3 3 -

CO2 3 3 3 3 - - - 3 3 3 - 3 3 -

CO3 3 3 3 3 - - - 3 3 3 - 3 3 -

CO4 3 3 3 3 - - - 3 3 3 - 3 3 -

TEXT BOOKS:

1. Richard F, Gilberg, Forouzan, Data Structures, 2nd edition, Cengage

2. Aaron M. Tenenbaum, YedidyahLangsam, Moshe J Augenstein, Data Structures

usingC, Pearson.

3. Mark Allen Weiss, Data structures and Algorithm Analysis in C, 2nd edition,

Pearson Education. Ltd.

REFERENCE BOOKS:

1. Jean-Paul Tremblay Paul G. Sorenson, An Introduction to Data Structures with

Applications, 2nd edition, Mc Graw Hill Higher Education

2. Seymour Lipschutz, Data Structure with C, TMH

3. Reema Thareja, Data Structures using C, 2nd edition, Oxford

OBJECT ORIENTED PROGRAMMING LAB


II Year / I Semester 0 0 3 1.5

Prerequisites: Student should have problem solving skills where knowledge in C is

added advantage.

Course Objectives: The main objective of this course is to teach student how to use

java compiler and get familiarity with any IDE(Netbeans, Eclipse) to develop solutions

for practical problems. Understanding the usage of different keywords in programming

and build GUI based applications using applet and swing.


1. Write a JAVA program to display default value of all primitive data types of JAVA.

2. Write a JAVA program to displays the roots of a quadratic equation ax2+bx+c =0. Calculate the discriminate D and basing on the value of D, describe the nature of roots.

3. Write a JAVA program to check the compatibility for multiplication, if compatible multiply two matrices.

4. Write a JAVA program to give the example for ‘this’ operator. And also use the ‘this’ keyword as return statement.

5. Write a JAVA program to demonstrate static variables, methods, and blocks. 6. Write a JAVA program that illustrates simple inheritance. 7. Write a JAVA program that illustrates multi-level inheritance. 8. Write a JAVA program to give the example for ‘super’ keyword. 9. Write a JAVA program demonstrating the difference between method

overloading and method overriding. 10. Write a JAVA program demonstrating the difference between method

overloading and constructor overloading. 11. Write a program to accept a string from the console and count the number of

vowels, digits, characters in that string.

12. Write a JAVA program, using StringTokenizer class, which reads a line of

integers and then displays each integer and the sum of all integers.

13. Write a JAVA program to create an abstract class named Shape, that contains an empty method named numberOfSides(). Provide three classes named Trapezoid, Triangle and Hexagon, such that each one of the classes contains only the methodnumberOfSides(), that contains the number of sides in the given geometrical figure.

14. Write a JAVA program illustrating multiple inheritance using interfaces. 15. Write a JAVA program to create a package named p1 and implement this

package in ex1 class. 16. Write a JAVA program to read array of integer values and formulate to create

both “division by zero” exception and “array index out of bound” exception. 17. Write a JAVA program to read two numbers, and sum these two values if the

first value is positive number, otherwise generate a user define exception. 18. Write a JAVA program to implement a Queue and handle its exceptions using

throw, throws mechanisms. 19. Write a JAVA program to illustrate creation of threads using Runnable

Interface(start method start each of the newly created thread. Inside the run method there is sleep () for suspend the thread for 500 milliseconds).

20. Write a JAVA program to illustrate creation of threads using extends Thread class(start method start each of the newly created thread. Inside the run method there is sleep () for suspend the thread for 1000 milliseconds).

21. Write a Java program that correctly implements producer consumer problem using the concept of inter thread communication.

22. Write a JAVA program that describes the life cycle of an applet. 23. Write a JAVA program to create a simple calculator. 24. Write a JAVA program that displays the x and y position of the cursor

movement using Mouse. 25. Write a program to display selected image on left panel. Design the GUI using

JSplitPane and JScrollPane.

Course Outcomes: Upon completion of this course, the students will be able to: CO1: Implement the programs using various basic programming constructs related to

language.

CO2: Apply the concepts of Object oriented programming using Java to design the

solutions of various problems.

CO3: Develop the applications by using different exception handling mechanisms and

also multithreading

CO4: Write simple GUI interfaces for computer applications to interact with users, and

to understand the event-based GUI handling principles


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 2 3 - - - - 3 3 3 - - 3 -

CO2 3 3 3 - - - - 3 3 3 - - 3 -

CO3 3 3 3 - - - - 3 3 3 - - 3 -

CO4 3 3 3 - 3 - - 3 3 3 - - 3 -

TEXT BOOKS: 1. Herbert schildt and Dale skrien, Java Fundamentals- A Comprehensive introduction, TMH. 2. P.J.Dietel and H.M.Dietel, Java: How to Program , PHI. REFERENCE BOOKS: 1. P.Radha Krishna, Object Oriented Programming through java, Universities Press. 2. Bruce Eckel, Thinking in Java, Pearson Education. 3. S.Malhotra and S.Choudhary, Programming in Java, Oxford University Press.

ESSENCE OF INDIAN TRADITIONAL KNOWLEDGE



Syllabus:

UNIT-1: INDIAN PHILOSOPHY & MODERN SCIENCE Origin of Indian philosophy- philosophy of Charvaka, Samkhya, Nyaya, Mimensa, Buddist and Jaina. Modern science in India. UNIT-2: MODERN SCIENCE IN JAIN GRANTHAS Introduction, Jain Ethics and Mortality, Non-violence and its facts: Root of non-violence, Meditation, Food, Thirthankars, Ritus, Ganadharas. UNIT-3: TRADITION OF INDIAN SCIENCE Historical evolution of medical tradition in ancient India. Ayurveda: Principles of Ayurvedic Healing -Treating diseases to restore health. Environmental Knowledge: Nature, flora and fauna, Manusmriti. UNIT-4: TRADITION OF INDIAN MATHS Early Historical period, Classical period, Vedic mathematics, Baskaracharya, Lilavati Bijaganitha, Srinivasa Ramanujan - Magic squares. UNIT-5: HOLISTIC HEALTH History, Holistic approach: Enhance living – Mind fullness skills- Spirituality and Healing, Stress Management - Food—Work and Life style. UNIT-6: PURE DIET AND PURE BODY Macro Nutrients: Carbohydrates, Proteins and Lipids. Micro Nutrients: Vitamins and Minerals, Diet plans for individuals. Yoga –Healthy Body: Introduction to Yoga, - Pranayamam, Surya Namaskara and Personality Development. Course Outcomes: Upon completion of this course, the students will be able to:

CO 1. Summarize the Essence of Indian philosophy, Jain philosophy and Buddist philosophy. CO 2. Outline the evaluation process of Ayurvedic healing to restore health and tradition of

Indian mathematics. CO 3. Make use of holistic health practices, spirituality ,stress management techniques for

healthy life Style. CO 4. Relate with proper diet plans and Yoga practices to attain good personality.


POs/

COs

PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12

CO1 - - - - - - - - - - - 1

CO2 - - - - - - - - - - - 1

CO3 - - - - - - - - - - - 1

CO4 - - - - - - - - - - - 1

REFERENCES

1. S. Radhakrishna, Indian Philosophy, Vol. 1 (London: George Allen and Unwin,1962), 287. 2. J. P. Jain, Religion and Culture of the Jains (Delhi: Bhartiya Jnanpith, 1977) 168 3. D. P. Sen Gupta, Current Science, 78 (12), 1569 (2000) 4. C.N.Srinivasa Iyengar, History of Indian Mathematics, World Press, Calcutta, 1967. 5. G. H Hardy, Ramanujan (Cambridge, 1940). 6. Nutritive Value of Indian Foods, C.Gopalan, B.V.Raman Sastri & S.C. Balasubramanian. 7. George Feuerstein: The Yoga Tradition (Its history, literature, philosophy and practice) 8. Swami Sivananda, Practice of Karma Yoga (The Divine Life Society, Shivananda Nagar,

P.O., U.P., Himalayas, India)

II Year

II Semester

COMPUTER ORGANIZATION AND ARCHITECTURE


II Year / II Semester 3 0 0 3 Prerequisites: Familiarity with Digital Electronics.

Course Objectives: Main objective of the course is to familiarize students about hardware design including logic design, basic structure and behavior of the various functional modules of the modern computer and how they interact to provide the processing needs of the user. It will cover machine level representation of data, instruction sets, computer arithmetic, CPU structure and functions, memory system organization and architecture, system input/output, multiprocessors, and digital logic. Syllabus:


Basic Structure of Computers: Computer Types, functional unit, basic operational concepts, bus structures. Data Representation: Data types, Complements, fixed point representation, floating- point representation. UNIT II: (8 Lectures) Register Transfer Language and Micro Operations: Register Transfer Language. Register Transfer Bus and memory transfers, Arithmetic Micro operations, logical micro operations, shift micro operations, Arithmetic logic shift unit. Basic Computer Organization and Design: Instruction codes, Computer

Register, Computer Instructions, Timing and Control, Instruction cycle, Memory-

Reference Instructions. Input-Output and Interrupt, Design of basic computer,

Design of Accumulator Logic.


Central Processing Unit: General Register Organization, STACK Organization,

Instruction formats, Addressing modes, DATA Transfer and manipulation, Program

control, Reduced Instruction Set Computer.

Micro Programmed Control: Control memory, Address sequencing, micro

program example, design of control unit.


Computer Arithmetic: Addition and subtraction, multiplication algorithms, division

algorithms, floating- point arithmetic operations.


The Memory System: Memory Hierarchy, Main memory, Auxiliary memory,

Associative memory, Cache memory, Virtual memory.


Input- Output Organization: Peripheral Devices, Input- Output Interface,

Asynchronous data transfer, modes of transfer, priority interrupts, direct memory

access. Introduction to Multi Processors: Characteristics, Inter connection structures

and Cache coherency. Introduction to pipelining.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Understand basic structures, functions of CPU, and Input /Output organization

in computer system. CO 2. Make use of RTL for various classes of instruction types such as data

movement, arithmetic, logical and flow control and study about various control unit design

CO 3. Apply numerous algorithms to perform arithmetic operations and propose suitable hardware for them.

CO 4. Analyze and emphasize various communication media in the basic computer system using design of numerous memory structures and multiprocessor systems.

CO 5. Identify the different types of memory technologies and organization, and thereby discuss the cost-performance trade offs


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 3 3 - - - - - - - - - - -

CO2 3 3 3 3 - - - - 2 2 - 3 - -

CO3 3 3 3 3 - - - - 2 2 - 3 - -

CO4 3 3 3 - - - - - 2 2 - 3 - -

CO5 3 3 3 - - - - - 2 2 - 3 - -

TEXT BOOKS: 1. M. Moris Mano, Computer System Architecture, 3rd ed, Pearson/PHI. 2. Carl Hamacher, Zvonks Vranesic, SafeaZaky, Computer Organization, 5th ed,

McGraw Hill. 3. William Stallings,Computer Organization and Architecture, 6th ed, Pearson/PHI. 4. B. Ram, Computer Fundamentals Architecture and Organization, 5th ed., New

Age International Publications. REFERENCE BOOKS: 1. Andrew S. Tanenbaum, Structured Computer Organization, 4th ed. PHI/ Pearson. 2. Sivaraama Dandamudi, Fundamentals or Computer Organization and Design,

Springer Int. Edition. 3. John L.Hennessy and David A.Patterson, Computer Organization a quantitative

approach, 4th ed, Elsevier.

DATABASE MANAGEMENT SYSTEMS


II Year / II Semester 3 0 0 3

Prerequisites: Familiarity with Data Structures, concepts of file storage and accessing. Course Objectives: Databases form the backbone of all major applications today. This course introduces relational data model, entity-relationship modeling, SQL, normalization and database design. This course would examine transaction management, concurrency control, recovery, file organizations and indexing. Syllabus: UNIT I: (10 Lectures) Introduction: Database System Applications, Database System Vs File System, View of Data, Data Abstraction, Instances and Schemas, Data Models, ER Model, Relational Model, Object Oriented Model, Semi-Structured Model, Database Access from Applications Programs, Database Users and Administrator, Database System Structure, Storage Manager, the Query Processor, History of database systems. Database Design with E-R Model: Database design, Beyond ER Design, Entities, Attributes and Entity sets, Relationships and Relationship sets, Additional features of ER Model, Conceptual Design with the ER Model. Conceptual Design for Large Enterprises.

UNIT II: (6 Lectures) Relational Model: Introduction, Integrity Constraints over relations, Enforcing Integrity constraints, Querying relational data, Logical database Design, Introduction to Views , Destroying /altering Tables and Views. Relational Algebra: Selection and Projection, Set operations, Renaming, Joins, Division, Examples of Algebra queries.

UNIT III: (9 Lectures) Form of Basic SQL Query: Examples of Basic SQL Queries, Introduction to Nested Queries, Correlated Nested Queries, Set Comparison Operators, Aggregative Operators, NULL values , Comparison using Null values, Logical connectives AND, OR and NOT, Impact on SQL Constructs , Outer Joins, Disallowing NULL values, Complex Integrity Constraints in SQL, Triggers and Active Databases. UNIT IV: (7 Lectures) Schema Refinement: Problems Caused by redundancy, Decompositions, Problem related to decomposition, Functional dependencies, Reasoning about FDS, FIRST, SECOND, THIRD Normal forms, BCNF, Lossless Join Decomposition, Dependency Preserving Decomposition, Schema Refinement in Database Design. Multivalued dependencies, Fourth normal form, Fifth normal form. UNIT V: (9 Lectures)

Transaction Management: The ACID Properties, Transactions and Schedules, Concurrent Execution of Transactions, Lock Based Concurrency Control. Concurrency Control: Serializability, and Recoverability, Introduction to Lock

Management, Dealing with Deadlocks. Concurrency Control without Locking. Crash Recovery: Introduction to ARIES, the Log, other Recovery related Structures, the Write-Ahead Log Protocol, Check pointing, Recovering from a System Crash. UNIT VI: (9 Lectures) Overview of Indexing: File organizations and Indexing, Clustered and Unclustered Indexes, Primary and Secondary Indexes, Index specification in SQL. Tree Structured Indexing: Intuitions for tree Indexes, Indexed Sequential Access Methods (ISAM), B+ Trees: Format of a Node, Search, Insert and Delete. Hash Based Indexing: Static Hashing, Extendable hashing, Linear Hashing, Extendable vs. Linear hashing. Course Outcomes:

Upon completion of this course, the students will be able to: CO1: Demonstrate the database system design and its functionality.

CO2: Utilize the knowledge of SQL and PL/SQL to construct the queries and

programmatic constructs for efficient data access and manipulation.

CO3: Inspect database problems and utilize the normalization theory to refine the

database schema.

CO4: Analyse and solve the transaction processing issues through concurrency control

and recovery mechanisms.

CO5: Illustrate different Indexing mechanisms for efficient data access.


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

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PO

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PO

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PO

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PO

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PO

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PO

12

PSO

1

PSO

2

CO1 3 3 3 - - - - - - - - - - -

CO2 - 2 3 - 3 - - - - - - - - -

CO3 2 3 3 - 3 - - - - - - - - -

CO4 2 2 - - - - - - - - - - - -

CO5 2 3 - 3 - - - - - - - - - -

TEXT BOOKS:

1. Raghurama Krishnan, Johannes Gehrke, Database Management Systems, 3rd

Edition, TATA McGraw hill.

2. Silberschatz, Korth, Database System Concepts, 5th Edition,TATA McGraw hill. REFERENCE BOOKS:

1. C.J.Date, Introduction to Database Systems, 8th Edition, Pearson Education. 2. Peter ROB and Carlos Coronel, Database System Concepts, Cengage Learning. 3. Ramez Elmasri , Shamkant B. Navathe , Fundamentals of Database Systems, 5th

Edition,Pearson Education.

DESIGN AND ANALYSIS OF ALGORITHMS



Prerequisites: Familiarity with Problem Solving Skills, Discrete Mathematics and Data

Structures.

Course Objectives: Upon completion of this course, students will be able to do

the analyze the asymptotic performance of algorithms, write precise correctness proofs

for algorithms, demonstrate a familiarity with major algorithms and data structures,

and apply important algorithmic design paradigms and methods of analysis.

Syllabus: UNIT I: (8 Lectures) Introduction: Algorithm, Pseudo Code for Expressing Algorithms, Performance

Analysis, Space Complexity, Time Complexity, Asymptotic Notation- Big Oh Notation,

Omega Notation, Theta Notation and Little Oh Notation, probabilistic analysis,

Amortized analysis.

UNIT II: (8 Lectures) Disjoint Sets: Disjoint Sets, Disjoint Set Operations, Union and Find Algorithms,

Connected Components and Bi-Connected Components. Divide and Conquer:

General method, Applications Binary Search, Quick sort, Merge Sort, Strassen‘s Matrix

Multiplication.

UNIT III: (8 Lectures) Greedy Method: General Method, Applications-Job Sequencing with Deadlines,

Knapsack Problem, Minimum Cost Spanning Trees, Single Source Shortest Path

Problem.


Dynamic Programming: General Method, Applications-Matrix Chain Multiplication,

0/1 Knapsack Problem, All Pairs Shortest Path Problem, Travelling Sales Person

Problem, Reliability Design

UNIT V: (8 Lectures) Backtracking: General Method, Applications-N-Queen Problem, Sum of Subsets

Problem, Graph Coloring, Hamiltonian Cycles. Branch and Bound: General Method,

Applications, Travelling Sales Person Problem, 0/1 Knapsack Problem, LC Branch and

Bound Solution, FIFO Branch and Bound Solution.

UNIT VI: (6 Lectures) NP-Hard and NP-Complete Problems: Basic Concepts, Non Deterministic

Algorithms, NP Hard and NP Complete Classes, Cook‘s Theorem.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Understand the fundamentals of algorithmic design steps, performance analysis concepts and various algorithm design methods. CO 2. Apply the algorithm design techniques to design efficient algorithms for different kinds of computing problems. CO 3. Analyze the asymptotic performance of algorithms and write formal correctness proof for algorithms. CO 4. Classify a problem as computationally tractable or intractable and discuss the strategies to address intractable.

CO 5. Apply the algorithms and design techniques to solve real time problems and analyze the complexities of problems in different domains.

Mapping of Cos to Pos:

POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

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PO

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PO

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PO

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PO

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PO

11

PO

12

PSO

1

PSO

2

CO1 3 2 2 3 2 - - - - - - 2 2 3

CO2 3 3 3 3 2 2 2 2 - - - 3 3 2

CO3 2 3 3 3 2 3 - - - - - 3 3 3

CO4 2 3 3 3 2 - - - - - - 2 2 2

CO5 3 3 3 3 3 3 2 2 2 - 2 3 3 3

TEXT BOOKS: 1. Ellis Horowitz, Satraj Sahni and Rajasekharan, Fundamentals of Computer

Algorithms, Galgotia publications Pvt. Ltd.

2. S Sridhar, Design and Analysis of Algorithms, Oxford.

3. T.H.Cormen, C.E.Leiserson, R.L.Rivest,and C.Stein, Introduction to Algorithms, 2nd

edition, Pearson Education.

REFERENCE BOOKS: 1. M.T.Goodrich, R.Tomassia, Algorithm Design: Foundations, Analysis and Internet

examples, John wiley and sons. 2. R.C.T.Lee, S.S.Tseng, R.C.Chang and T.Tsai, Introduction to Design and Analysis of

Algorithms A strategic approach, Mc Graw Hill.

3. Allen Weiss, Data structures and Algorithm Analysis in C++, Second edition,

Pearson education.

4. Aho, Ullman and Hopcroft, Design and Analysis of algorithms, Pearson education.

5. Richard Johnson Baugh and Marcus Schaefer,Algorithms –Pearson Education.

FORMAL LANGUAGES AND AUTOMATA THEORY



Prerequisites: Familiarity with Discrete Mathematics.

Course Objectives: This course serves as an introduction to the basic theory of Computer Science & formal methods of computation which will develop an ability to design grammars and automata (recognizers) for different language classes. Syllabus: UNIT I: (8 Lectures) Fundamentals: Strings, Alphabet, Language, Operations, Chomsky Hierarchy of

Languages, Finite State Machine, Definitions, Finite Automaton Model, Acceptance

of Strings and Languages, Deterministic Finite Automaton and Non Deterministic

Finite Automaton, Transition Diagrams and Language Recognizers.


Finite Automata: NFA with ɛ Transitions - Significance, Acceptance of Languages.

Conversions and Equivalence : Equivalence between NFA with and without ɛ

Transitions, NFA to DFA Conversion, Minimization of FSM, Equivalence Between Two

FSM‘s, Finite Automata With Output- Moore And Melay Machines.

UNIT III: (10 Lectures) Regular Languages: Regular Sets, Regular Expressions, Identity Rules,

Constructing Finite Automata for a given Regular Expressions, Conversion of Finite

Automata to Regular Expressions. Pumping Lemma of Regular Sets, Closure

Properties of Regular Sets (Proofs Not Required).

Grammar Formalism: Regular Grammars -Right Linear and Left Linear Grammars,

Equivalence between Regular Linear Grammar and FA, Inter-Conversion.

UNIT IV: (8 Lectures) Context Free Grammars: Context Free Grammar, Derivation Trees, Sentential Forms, Right Most and Leftmost Derivation of Strings. Ambiguity in Context Free Grammars. Minimization of Context Free Grammars. Chomsky Normal Form, Greiback Normal Form, Pumping Lemma For Context Free Languages. Enumeration of Properties Of CFL (Proofs Omitted). UNIT V: (8 Lectures) Push Down Automata: Push Down Automata, Definition, Model, Acceptance of

CFL, Acceptance by Final State and Acceptance by Empty State and Its Equivalence.

Equivalence of CFL and PDA, InterConversion. (Proofs Not Required). Introduction

to DCFL and DPDA.

UNIT VI: (8 Lectures) Turing Machine: Turing Machine, Definition, Model, Design of TM, Computable

Functions, Recursively Enumerable Languages, Church’s Hypothesis, Counter

Machine, Types of Turing Machines (Proofs Not Required), Linear Bounded

Automata and Context Sensitive Languages.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Summarize the fundamental concepts of automata and hierarchy of formal

languages.

CO 2. Develop variants of finite automata and convert one form of automata to other form of automata.

CO 3. Construct grammars and automata for different language classes.

CO 4. Develop abstract machines that demonstrate the properties of physical machines and able to specify the possible inputs, processes and outputs of their machines.


POs/

COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO1 PSO2

CO1 3 2 2 - - - - - - - - - - -

CO2 3 3 3 2 - - - - - - - - - -

CO3 3 2 3 2 - - - - - - - - - -

CO4 3 3 3 2 - - - - - - - - - -

TEXT BOOKS:

1. Hopcroft H.E, Ullman J. D ,Introduction to Automata Theory Languages and

Computation.. Pearson Education.

2. Nasir S.F.B, P.K. Srimani, A text book on Automata Theory, Cambridge University Press.

3. Sipser, Introduction to Theory of Computation, Second Edition. REFERENCE BOOKS: 1. Daniel I.A. Cohen, Introduction to Computer Theory, John Wiley. 2. John C Martin, Introduction to languages and the Theory of Computation , TMH 3. Lewis H.P. & Papadimition C.H ,Elements of Theory of Computation,

Pearson/PHI. 4. Mishra and Chandrashekaran Theory of Computer Science – Automata

Languages and Computation, 2nd Edition, PHI.

SOFTWARE ENGINEERING Subject Code: UGCS4T0518 L T P C


Prerequisites: Basic concepts of programming and algorithm design. Course Objectives: This course enables the learners to have exposure towards software development life cycle and its phases. It focuses on various principles and methods related to identifying project requirements, transforming requirements into design, product development models, product testing and deployment. Learners will get exposure to various real time practices and approaches of the software industry through this course. Syllabus: UNIT I: (6 Lectures) Introduction to Software Engineering: The evolving role of software, Changing Nature of Software, Software myths. The software problem: Cost, schedule and quality, Scale and change.

UNIT II: (10 Lectures) Software Process: Process and project, component software process, Software development process models : Waterfall model, prototyping, iterative development, relational unified process, time boxing model, Extreme programming and agile process, using process models in a project, Project management process.


Software requirement analysis and specification: Value of good SRS, requirement process, requirement specification, functional specifications with use-cases, other approaches for analysis, validation. UNIT IV: (8 Lectures)

Planning a software project: Effort estimation, project schedule and staffing, quality planning, risk management planning, project monitoring plan, detailed scheduling.


Software Architecture and Design: Role of software architecture, architecture views, components and connector view, architecture styles for C & C view, documenting architecture design, evaluating architectures. Characteristics of Good Design, Design Principles, Modular Design, Design Methodologies, Detailed design, Design Verification. UNIT VI: (8 Lectures) Software Implementation and Testing: Structured coding Techniques, Coding Styles, Standards and Guidelines, Documentation Guidelines, Software Quality, CMM Levels, Testing Concepts, Testing Process, Black-Box and White- Box Testing Techniques, Art of Debugging.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Interpret the basic principles of software development and process models in

its life cycle. CO 2. Construct the software requirements specifications with relevant use-cases. CO 3. Identify the project management strategies and various components to build

the architecture using suitable design strategies. CO 4. Classify best coding standards and testing strategies to develop high-quality

software products. Mapping of COs to POs: POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 - 3 - - 2 - - - - - 2 - -

CO2 2 - 2 - 2 2 - - 2 2 - 2 - -

CO3 3 - 3 - 2 2 - - 2 2 3 2 - -

CO4 2 - 2 - 2 2 - - - - - 2 - -

TEXT BOOKS:

1. Pankaj Jalote, A Concise Introduction to Software Engineering (Undergraduate Topics in Computer Science), Springer International Edition.

2. Roger S Pressman, “Software Engineering – A Practitioner’s Approach”, 7th Edition, McGrawHill.

3. Ugrasen Suman, Software Engineering Concepts and Practices, Cengage Learning Publications.

4. Ian Sommerville, “Software Engineering”, 9th Edition, Pearson Education.

REFERENCE BOOKS:

1. K.K.Agarwal & Yogesh Singh. Software Engineering, New Age International Publishers.

2. Rajesh Naik and Swapna Kishore: Software Requirements and Estimation, 1st edition, Tata Mc Graw Hill.

3. Waman S Jawadekar , Software Engineering Principles and Practice, Tata Mc Graw Hill.

DATABASE MANAGEMENT SYSTEMS LAB


II Year / II Semester 0 0 3 1.5

Prerequisites: Basic knowledge in Programming. Course Objectives:

The major objective of the DBMS lab is to provide a strong formal foundation in database concepts, technology and practice to the participants to groom them into well-informed database application developers. List of Experiments: Experiment 1: Working with ER Diagram Example: ER Diagram for Sailors Database Entities:

1. Sailor 2. Boat

Relationship: Reserves Primary Key Attributes:

1. SID (Sailor Entity) 2. BID (Boat Entity)

Experiment 2: Working with DDL, DML, DCL and Key Constraints Creating, Altering and Dropping of Tables and Inserting Rows into a Table (Use Constraints While Creating Tables), Examples using Select command. Experiment 3: Working with Queries and Nested Queries Queries (along with sub Queries) using ANY, ALL, IN, EXISTS, NOTEXISTS, UNION, INTERSECT and Constraints. Experiment 4: Working with Queries using Aggregate Operators & Views Queries using Aggregate Functions (COUNT, SUM, AVG, MAX and MIN), GROUP BY, HAVING, Creation and Dropping of Views. Experiment 5: Working with Conversion Functions & String Functions Queries using Conversion Functions (to_char, to_number and to_date), String Functions (Concatenation, lpad, rpad, ltrim, rtrim, lower, upper, initcap, length, substr and instr), Date Functions (Sysdate, next_day, add_months, last_day, months_between, least, greatest, trunc, round, to_char, to_date). Experiment 6: Working with Triggers using PL/SQL Develop programs using BEFORE and AFTER Triggers, Row and Statement Triggers and INSTEAD OF Triggers. Experiment 7: Working with PL/SQL Procedures Develop programs using Procedures, passing Parameters IN and OUT of Procedures. Experiment 8: Working with Loops using PL/SQL and Exception Handling

Develop programs using WHILE loops, FOR loops, Nested loops using ERROR handling, BUILT-IN Exceptions, USER defined Exceptions, and RAISE_APPLICATION_ERROR. Experiment 9: Working with Functions using PL/SQL Develop programs using stored Functions, invoke Functions in SQL statements and write complex Functions. Experiment 10: Working with Cursors using PL/SQL Develop programs using Cursors, parameters in a Cursor, FOR UPDATE Cursor, WHERE CURRENT OF clause and Cursor variables. Course Outcomes: Upon completion of this course, the students will be able to:

CO 1. Demonstrate the database design using ER Diagrams.

CO 2. Develop SQL Queries to manipulate the data in the database.

CO 3. Inspect and handle errors using exception handling mechanism.

CO 4. Apply Procedural Language constructs to execute block of SQL statements.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 2 2 2 - - - 3 3 3 - - - -

CO2 3 2 - 3 3 - - 3 3 3 - - - -

CO3 3 - - - 3 - - 3 3 3 - - - -

CO4 2 - 2 2 3 - - 3 3 3 - - - -

TEXT BOOKS: 1. Benjamin Rosenzweig, Elena Silvestrova Rakhimov, Oracle PL/SQL by Example,

3rd Edition,Pearson Education. 2. Scott Urman, Ron Hardman,Michael Mclaughlin,Oracle Database 10G PL/SQL

Programming, Tata Mc-Graw Hill. 3. Dr .P.S. Deshpande,SQL and PL/SQL for Oracle 11g, Black Book.

OBJECT ORIENTED ANALYSIS AND DESIGN LAB


II Year / II Semester 2 0 3 3.5

Prerequisites: Basic understanding of Software Engineering and Object Oriented

Programming paradigms.

Course Objectives: The focus of the course is to give basic knowledge on the

concepts of Object Oriented Analysis & Design and provide deep insight into the

importance of Modeling in Software Development Life Cycle. It will facilitate the

students to learn Unified Modeling Language that enables to create UML Diagrams

to visualize, specify, construct, and document the artifacts of a real world software

intensive system in Multiple Views.

List of Case Studies: 1) ATM System 2) Online Reservation System 3) Online Quiz System 4) Banking System 5) Stock Maintenance System 6) Student Marks Analysis System 7) Course Registration System 8) Library Management System 9) Real-time Scheduler List of Experiments: 1) Draw Use case diagrams for all case studies. 2) Draw Class diagrams for all case studies. 3) Draw Object diagrams for all case studies. 4) Draw Sequence diagrams for all case studies. 5) Draw Collaboration diagrams for all case studies. 6) Draw Activity diagrams for all case studies. 7) Draw State chart diagrams for all case studies. 8) Draw Component diagrams for all case studies. 9) Draw Deployment diagrams for all case studies. Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Interpret software requirements of various real-time applications. CO 2. Construct structural elements of the application in terms of object-oriented-

design. CO 3. Classify the modelling of interaction diagrams of the application to represent

functionalities of a software system.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 - 3 2 - 3 3 3 - 2 - -

CO2 3 3 3 - 3 2 - 3 3 3 - 2 - -

CO3 3 3 3 - 3 2 - 3 3 3 - 2 - -

TEXT BOOKS: 1. Grady Booch, James Rumbaugh, Ivar Jacobso, The Unified Modeling Language

User Guide, Pearson Education. REFERENCE BOOKS: 1. Meilir Page-Jones, Fundamentals of Object-oriented Design in UML,

Pearson Education. 2. Martina Seidl, Marion Scholz, Christian Huemer, Gerti Kappel,

UML@Classroom - An introduction to Object-Oriented Modeling, Springer.

MINI PROJECT-1

Subject Code: UGCS4J0818 L T P C


Course Objectives :

Mini project will let the students apply the programming knowledge into a real world

situation or problem and expose the students to how programming skill will help

them develop a product.

Guidelines/Instructions :

Group of students can form as a team and the team has to submit the Mini Project

abstract to the Project Coordinator by consulting with the guide at the beginning of

the semester.

The team has to implement the Mini Project and submit the Mini Project report in

the prescribed format at the end of the semester to the department. The Viva–Voce

shall be conducted along with respective semester lab external examinations.

Course Outcomes:

Upon completion of this course, the students will be able to:

CO 1. Aquire practical knowledge within the chosen area of technology for project

development.

CO 2. Identify, analyse, formulate and handle projects with a systematic approach.

CO 3. Contribute as an individual or in a team in development of technical projects.

CO 4. Develop effective communication skills for presentation of project related

activities.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 3 3 3 3 - - - 3 3 3 -

CO2 3 2 3 3 3 3 3 3 - - 3 - 3 -

CO3 - - - - 3 2 2 3 3 3 3 3 3 -

CO4 - - - - - - - 3 3 3 - 3 - -

Effective Technical Communication



COURSE OBJECTIVES:

To expose students to different contexts through right vocabulary.

To inculcate the habit of reading and understanding any text.

To enable students to acquire the ability of writing for business purposes.

To enable students to acquire interview skills and group discussion dynamics.

UNIT I: (2 sessions)

Selected High GRE Words, Idioms & Phrases – Discourse Skills – using visuals –

Synonyms and antonyms, word roots, one word substitutes, prefixes and suffixes,

study of word origin, business vocabulary, analogy, idioms and phrases, collocations

& usage of vocabulary.

UNIT II: (2 sessions)

Reading Comprehension – General Vs Local Comprehension, reading for facts,

guessing meanings from context, scanning, skimming, inferring meaning.

UNIT III: (2 sessions)

Writing Skills – Structure of Resume writing – Portfolio writing –Short Report Writing

Business/Technical).

UNIT IV:

Presentations (Technical).

UNIT V: (2 sessions)

Group Discussion – Dynamics of Group Discussion, Intervention, summarizing,

modulation of voice, body language, relevance, fluency and organization of ideas

and rubrics for evaluation.

UNIT VI: (3 sessions)

Interview Skills – Concept and process – pre-interview planning, opening strategies,

answering strategies, interview through teleconference & video-conference and

mock interviews.

COURSE OUTCOMES:

Upon completion of this course, the students will be able to: CO 1. Develop skills in analogy, a wide range of vocabulary including business

vocabulary for academic purpose. CO 2. Analyze various types of reading comprehension through different methods of

reading. CO 3. Construct resumes, portfolio writing and short business/technical

reports. CO 4. Make use of skills through presentations, rubrics of group discussion and

Interview skills through teleconference, video conference and mock interviews.


POs/

COs PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12

CO1 - - - - - - - - 3 3 - 3

CO2 - - - - - - - - 3 3 - 3

CO3 - - - - - - - - 3 3 - 3

CO4 - - - - - - - - 3 3 - 3

SUGGESTED SOFTWARE:

1. K-Van solutions Software with CD 2. The Rosetta stone English library. 3. Clarity pronunciation power –part I. 4. Oxford advanced learner’s compass, 7th Edition. SUGGESTED READING: 1. Technical Communication by Meenakshi Raman & Sangeeta Sharma, Oxford

University Press 2009. 2. Business and Professional Communiction: Keys for Workplace Excellence. Kelly

M.Quintanilla & Shawn T. Wahl. Sage South Asia Edition. Sage Publications. 2011.

3. English Vocabulary in Use Series, Cambridge University Press 2008. 4. Communication Skills by Leena Sen, PHI Learning Pvt. Ltd., New Delhi, 2009. 5. A Course Book of Advanced Communication Skills Lab published by University

Press, Hyderabad.

III Year

I Semester

COMPILER DESIGN


III Year / I Semester 3 0 0 3

Prerequisites: Familiarity with Formal Languages and Automata Theory, and Data

Structures.

Course Objectives: This course introduces the basic principles of compiler and depicts the phases of the compilation process with implementation approach of each phase. Syllabus: UNIT I: (8 Lectures) Overview of language processing, pre-processors, compiler, assembler, interpreters, pre-processors, linkers & loaders, structure of a compiler, phases of a compiler, Lexical Analysis, Role of Lexical Analysis, Lexical Analysis Vs Parsing, Token, patterns and Lexemes, Lexical Errors, Regular Expressions, Regular definitions for the language constructs, Strings, Sequences, Comments, Transition

diagram for recognition of tokens, Reserved words and identifiers, Examples.

UNIT II: (8 Lectures) Syntax Analysis, discussion on CFG, LMD,RMD, parse trees, Role of a parser, classification of parsing techniques, Brute force approach, left recursion, left factoring, Top down parsing, First and Follow, LL(1) Grammars, Non-Recursive predictive parsing, Error recovery in predictive parsing. UNIT III: (10 Lectures) Bottom up parsing, Types of Bottom up approaches, Introduction to simple LR, Why LR Parsers, Model of LR Parsers, Operator Precedence, Shift Reduce Parsing, Difference between LR and LL Parsers, Construction of SLR Tables,More powerful LR parses, construction of CLR (1), LALR Parsing tables, Dangling ELSE Ambiguity, Error recovery in LR Parsing, Comparison of all bottom up approaches with all top down approaches. UNIT IV: (8 Lectures) Semantic analysis, SDT Schemes, evaluation of semantic rules. Intermediate code, three address code, quadruples, triples, abstract syntax trees. Types and declarations, type Checking. UNIT V: (8 Lectures) Symbol tables: use and need of symbol tables. Runtime Environment: storage organization, stack allocation, access to non-local data, heap management, parameter passing mechanisms, introduction to garbage collection, Reference counting garbage collectors. Code generation: Issues, target language, Basic blocks & flow graphs, Simple

code generator, Peephole optimization, Register allocation and assignment.

UNIT VI: (8 Lectures) Machine independent code optimization, semantic preserving transformations, global common sub expression elimination, copy propagation, dead code elimination, constant folding, strength reduction, loop optimization. Instruction scheduling, inter procedural optimization. Course Outcomes:


CO 1 Demonstrate an understanding of the design of a compiler including its

phases and components.

CO 2 Distinguish the lexical, syntactic and semantic analysis into meaningful

phases for a compiler to undertake language translation.

CO 3 Analyze the runtime structures used to represent language constructs and

typical programming languages.

CO 4 Analyze the techniques used for intermediate code generation and

optimization.

CO 5 Apply appropriate parsing techniques to design a parser for the given

language.


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 2 3 3 2 - - - - - - - - -

CO2 3 2 3 2 2 - - - - - - - - -

CO3 3 2 3 2 - - - - - - - - - -

CO4 3 2 3 2 - - - - - - - - - -

CO5 3 3 3 2 2 - - - - - - - - -

TEXT BOOKS: 1. Alfred V Aho, Monica S Lam, Ravi Sethi, Jeffrey D. Ullman ,Compilers Principles

Techniques and Tools-,2nd ed, Pearson. 2. Kenneth C Louden, Compiler construction, Principles and Practice, CENGAGE. REFERENCE BOOKS: 1. K. Muneeswaran, Compiler Design, Oxford. 2. Keith D.Cooper & Linda Torczon, Engineering a compiler, 2nd edition, Morgan

Kaufman. 3. http://www.nptel.iitm.ac.in/downloads/106108052/ 4. V. Raghavan, Principles of compiler design, 2nd ed, TMH. 5. Yunlinsu, Implementations of Compiler, A new approach to Compilers including

the algebraic methods, SPRINGER.

COMPUTER NETWORKS



Prerequisites: Familiarity with Computer Organization and Architecture.

Course Objectives: Students will be able to master in the computer network terminology and concepts of the OSI model and the TCP/IP model, summarize with wired and wireless networking concepts and routing protocols, and solve current issues in networking technologies.

Syllabus: UNIT I: (8 Lectures) Data Communication: Components, Representation of data and its flow, Networks, Various connection topologies, Protocols and Standards, OSI model, TCP/IP Model. Physical Layer: Guided media (copper, twisted pair, coaxial, fiber optic cable), Unguided media (Electromagnetic spectrum). Data performance, Multiplexing- Frequency division, Time division. UNIT II: (9 Lectures) Data Link Layer: Framing methods, Error Detection and Error Correction - Fundamentals, Block coding, Hamming code, CRC, Checksum, Flow Control and Error control. Wired LANs, Wireless LANs, Bridge, Switch. UNIT III: (8 Lectures) Medium Access Sub Layer: Protocols - Stop and Wait, Go back – N ARQ, Selective Repeat ARQ, Sliding Window, Piggybacking, Random Access, Multiple access protocols -Pure ALOHA, Slotted ALOHA, CSMA/CD, CDMA/CA, bridges. UNIT IV: (8 Lectures) Network Layer: Switching, Logical addressing – IPV4, IPV6; Address mapping –

ARP, RARP, BOOTP and DHCP–Delivery, ICMP, Routing algorithms - shortest path

routing, Flooding, Hierarchical routing, Broadcast routing, Multicast and distance

vector routing, Firewall.

UNIT V: (8 Lectures) Transport Layer: Process to Process Communication, User Datagram Protocol (UDP), Transmission Control Protocol (TCP), SCTP Congestion Control; Quality of Service, QoS improving techniques: Leaky Bucket and Token Bucket algorithm. UNIT VI: (9 Lectures) Application Layer: Domain Name Space (DNS), TELNET(Remote Login), EMAIL(SMTP,POP3), File Transfer Protocol (FTP), HTTP.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Explain the principles of networking protocols and standards; and Identify

different concepts of layered architectures in networking. CO 2. Identify the design issues and Classify the different framing methods and

various multiple access protocols. CO 3. Compare and contrast the different routing algorithms to analyze the

optimum routing path. CO 4. Describe the functionality of transport layer and to demonstrate how to

control the congestion. CO 5. Illustrate some basic tools/utilities for network analysis and Employ basic

techniques and protocols to connect devices. Mapping of COs to POs:

POs/

COs PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9

PO

10

PO

11

PO

12 PSO1 PSO2

CO1 3 2 3 3 3 2 3 - - - - 3 2 3

CO2 3 3 2 3 2 3 2 - - - - 2 2 2

CO3 3 3 3 3 3 3 2 - - - - 3 3 3

CO4 3 3 3 3 2 2 3 - - - - 2 3 2

CO5 3 3 3 3 3 3 2 2 2 3 3 3 3 3

TEXT BOOKS: 1. Andrew S. Tanenbaum, Computer Networks, 8th Edition, Pearson New

International Edition. 2. Behrouz A. Forouzan, Data Communication and Networking, 4th Edition, McGraw-

Hill. REFERENCE BOOKS: 1. William Stallings, Data and Computer Communication, 8th Edition, Pearson

Prentice Hall India. 2. Douglas Comer, Internetworking with TCP/IP, Volume 1, 6th Edition, Prentice Hall

of India. 3. W. Richard Stevens, TCP/IP Illustrated, Volume 1, Addison-Wesley, United States

of America.

MICROPROCESSORS AND MICROCONTROLLERS



Prerequisites: Familiarity with Digital Electronics and Computer Organization.

Course Objectives: The Students will gain the knowledge of 8086 microprocessor

architecture, functionalities and exposure towards instruction set of 8086. Develop

application programs for 8086 microprocessor and interrupt service routines, as well

as data processing tasks and its applications. Gain the knowledge of 8051

microcontroller and its programming.

SYLLABUS:

UNIT I: (8 lectures)

Overview of microcomputer structure and operation: execution of a three

instruction program, microprocessor evolution and types, the 8086 micro processor

family , 8086 internal architecture, introduction to programming the 8086.

8086 family assembly language programming: Program development steps,

constructing the machine codes for 8086 instructions, writing programs for use with

an assembler, assembly language program development tools.


Implementing standard program structures in 8086 assembly language:

Simple sequence programs, jumps, flags and conditional jumps, if-then, if-then-else

and multiple if-then-else programs, while-do programs, repeat-until programs,

instruction timing and delay loops.


Strings, procedures and macros: The 8086 string instructions, writing and using

procedures, writing and using assembler macros.

8086 instruction descriptions and assembler directives : Instruction

descriptions, assembler directives , DB, DD, DQ, DT, DW, end-program, endp, ends,

equ ,even-align on even memory address, extrn , global, public / extrn, group,

include, label, length- not implemented IBM MASM, name – off set, ORG, proc, ptr,

segment, short, type.


8086 interrupts and interrupt applications: 8086 interrupts and interrupt

responses, hardware interrupt applications, Software Interrupts, priority of

interrupts, software interrupt applications, programming.

8086 assembly language programs - Bit & Logic operations, strings, procedures,

Macros, Number Format, Conversions, ASCII operations, signed Numbers Arithmetic,

Programming using High level language constructs.

UNIT V: (8 lectures)

8051 Microcontroller: Introduction to microcontrollers, Understand the basic

building blocks of microcontroller, CISC and RISC processors, Harvard and Von

Neumann architectures, 8051 Microcontroller architecture. Pin description, Memory

organization, Register organization of 8051.

UNIT VI: (8 lectures)

Programming with 8051 Microcontroller: Addressing modes of 8051,

Instruction set of 8051, Interrupts, timers & counters, serial communication,

Interrupt structure of 8051, Basic Assembly language programs.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Recall and apply a basic concept of digital fundamentals to Microprocessor

based personal computer system.

CO 2. identify a detailed s/w & h/w structure of the Microprocessor.

CO 3. illustrate how Arithmetic, Logical and modular programming work in

Microprocessors.

CO 4. Distinguish and analyze the properties of Microprocessors & Microcontrollers.

CO 5. Analyze the data transfer information and interrupts of Microcontrollers.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 - 3 - - - - - - - - -

CO2 3 3 3 - 3 - - - - - - - - -

CO3 3 3 3 - 3 - - - - - - - - -

CO4 3 3 3 - 3 - - - - - - - - -

CO5 3 3 3 - 3 - - - - - - - - -

TEXT BOOKS:

1. Douglas V Hall, Microprocessors and Interfacing, Revised 2nd ed, TMH.

2. Barry Bray,The Intel Microprocessors, Architecture, programming and interfacing,

8th ed, Pearson.

3. Lyla B Das, The X86 Microprocessors, architecture, Programming and Interfacing

(8086 to Pentium), PEA.

4. AJAY V Deshmukh, Microcontroller, TATA McGraw Hill publications.

REFERENCE BOOKS:

1. Walter A Triebel, Avtar Singh, The 8088 and 8086 Microprocessors, Programming, Interfacing, Hardware and Applications,4th ed,Pearson.

2. Liu,Micro Computer System 8086/8088 Family Architecture, Programming and Design, Prentice Hall.

3. Muhammad Ali Mazdi, 8051 Microcontrollers & Embedded Systems, Pearson

Education.

OPERATING SYSTEMS



Prerequisites: Familiarity with Data Structures and Computer Organization & Architecture. Course Objectives: The course teaches the basic operating system abstractions, mechanisms, and their implementations. The core of the course contains concurrent programming (threads and synchronization), inter process communication. Also, gives insight to the concepts including file systems, virtual memory and disk management.

Syllabus:

UNIT I: (9 lectures)

Introduction: Concept of Operating Systems, Operating Systems Objectives and

Functions, Generations of Operating systems, Types of Operating Systems, OS

Services, System Calls, Structure of an OS - Layered, Case study on UNIX and

WINDOWS Operating System.


Process Management: Process concept, process scheduling, operations, inter

process communication, Multi Thread programming model, Process scheduling

criteria and algorithms (FCFS, SJF, Priority, RR, Multilevel queue Scheduling), and

their evaluation.


Process synchronization: the critical- section problem, Peterson’s Solution,

synchronization Hardware, semaphores, classic problems of synchronization,

monitors, Producer Consumer problem, Readers & Writers Problem, Dining

Philosopher Problem.


Deadlocks: Definition, Necessary and sufficient conditions for Deadlock, Deadlock

Prevention, Deadlock Avoidance: Banker’s algorithm, Deadlock detection and

Recovery.

UNIT V: (8 lectures) Memory Management : Swapping, contiguous memory allocation, paging, structure of the page table, segmentation, Virtual memory, demand paging, page replacement algorithms, allocation of Frames, Thrashing. UNIT VI: (8 lectures) File Management: Concept of File, Access methods, File types, File operation, Directory structure, File System structure, Allocation methods (contiguous, linked,

indexed), Free-space management (bit vector, linked list, grouping), directory implementation (linear list, hash table), efficiency and performance. Disk Management: Disk structure, Disk scheduling - FCFS, SSTF, SCAN, C-SCAN,

Disk reliability, Disk formatting, Boot-block, Bad blocks.

Course Outcomes: Upon completion of the course the students able to:

CO 1. Understand the fundamental concepts of operating systems and its services.

CO 2. Demonstrate the principles of process management and analyze performance of process scheduling algorithms.

CO 3. Illustrate the importance of process coordination and solve process synchronization problems to avoid deadlocks.

CO 4. Analyze various memory allocation and access time by making use of

various memory management techniques.


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 3 - - - - - - - - - - - -

CO2 3 3 3 - - - - - - - - - - -

CO3 3 3 3 3 - - - - - - - 3 - -

CO4 3 3 3 3 - - - - - - - 3 - -

TEXT BOOKS: 1. Abraham Silberchatz, Peter B. Galvin, Greg Gagne, Operating System Concepts,

9th edition, John Wiley. 2. Stallings, Operating Systems-Internal and Design Principles, 6th edition, Pearson

education. REFERENCE BOOKS: 1. http://nptel.iitm.ac.in/courses/Webcourse-contents/IISc-

BANG/Operating%20Systems /New_index1.html

2. D.M.Dhamdhere, Operating systems- A Concept based Approach, 2ndedition,

TMH.

3. Crowley, Operating System A Design Approach, 1st edition, TMH.

4. Andrew S Tanenbaum, Modern Operating Systems, 3rd edition, PHI.

5. Gary J. Nutt, Operating Systems: A Modern Perspective, 2nd Edition, Addison-

Wesley.

ADVANCED DATABASES

(Professional Elective-I)



Prerequisites: Familiarity with Database Management Systems.

Course Objective: The objective of this course presents new developments in

database technology and summarizes the impact of emerging database standards

and introduces Distributed databases to implement emerging technologies and

applications.

Syllabus:


Query Processing and Optimization: Translating SQL Queries into Relational

Algebra, Basic Algorithms for Executing Query Operations, Query Optimization Using

Heuristics, Using Selectivity and Cost Estimates, Semantic Query Optimization.


Database Recovery Techniques: Recovery Techniques Based on Deferred

Update, Immediate Update, Shadow Paging, Aries Recovery Algorithm, Recovery in

Multidatabase Systems, Database Backup And Recovery From Catastrophic Failures.

Database Security and Authorizations: Discretionary Access Control Based on

Privileges, Mandatory Access Control for Multilevel Security, Statistical Database

Security.


Concepts for Object Oriented Database: Overview, Object identity, Structure

and Type Constructors, Encapsulation of Operations, Methods and Persistence. Type

Hierarchies and Inheritance, Complex Objects. Object Database Standards

Languages and Design: Overview of ODMG, Object Definition Language, Object

Query Language, C++ Language Binding, Object Database Conceptual Design,

Examples of ODBMS.


Distributed DBMS Architecture: DBMS Standardization, Architectural Model,

DDBMS Architecture, Global Directory Issues. Distributed Database Design:

Alternative Design Strategies, Distribution Design Issues, Fragmentation, Allocation.

Semantic Data Control: View Management, Data Security, Semantic Integrity

Control.


Overview of Query Processing: Query Processing Problem, Objectives,

Complexity of Relational Algebra, Characterization of Query Processors, Layers of

Query Processing. Query Decomposition and Data Localization, Optimization

of Distributed Queries: Query Optimization, Centralized Query Optimization, Join

Ordering in Fragment Queries, Distributed Query Optimization Algorithms.


Introduction to Transaction Management: Definition, Properties and Types of

Transactions, Architecture. Distributed Concurrency Control: Serializability

Theory, Taxonomy of Concurrency Control Mechanisms, Locking Based Concurrency

Control, Time-Stamp Based, Optimistic Algorithms, Deadlock Management and

Relaxed Concurrency Control.

Course Outcomes:

Upon completion of this course, the students will be able to: CO1: Apply query evaluation and query optimization techniques.

CO2: Propose, implement and maintain database security mechanisms.

CO3: Identify, describe and categorize database objects.

CO4: Design transaction processing system with concurrency control.


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 3 3 2 - - - - - - - 3 -

CO2 3 2 3 - - - - - 2 - - - - 2

CO3 3 3 2 - - - 2 - - - - 2 -

CO4 3 3 2 3 2 - - 2 - - - - - 2

TEXT BOOKS:

1. Elmasri Ramez & Navathe Shamkant ,Fundamentals of Database Systems,3rd

Edition, Addison-Wesley-Longman.

2. Ozsu,M.Tamer,Valduriez& Patrick,Principles of Distributed database systems, 2nd

Edition, Pearson.

REFERENCE BOOKS:

1. Fred R.McFadden, Jeffrey A.Hoffer, Mary B.Prescott, Modern Database

Management, 5th Edition, Addison Wesley .

2. Raghuramakrishnan, Johannes Gehrke, Database Management Systems, 3rd

edition, Mc Graw Hill Education.

COMPUTER GRAPHICS

(Professional Elective-I)



Prerequisites: Basic knowledge in Mathematics and Computer Organization.

Course Objectives: The objective of this course presents the basic concepts, the

tasks of computer graphics and its main algorithms and models. The course

examines the principles of functioning of graphic devices and the various limitations,

description of the geometric objects and their presentation in the computer, the

main functions of graphics package.

Syllabus:

UNIT I: (7 Lectures) Introduction: Application areas of Computer Graphics. Overview of graphics systems: video-display devices, raster-scan systems, random scan systems, graphics monitors and work stations, input devices. UNIT II: (8 Lectures) Output primitives: Points and lines, line drawing algorithms, mid-point circle algorithm, Bresenham's circle algorithm and midpoint ellipse algorithms. Filled area primitives: Scan line polygon fill algorithm, boundary-fill algorithm, flood-fill algorithms, Inside-outside tests.

UNIT III: (9 Lectures) 2-D geometric transformations: Translation, scaling, rotation, reflection and shear transformations, matrix representations and homogeneous coordinates, composite transformations, Other transformations, transformations between coordinate systems, affine transformations. 2-D viewing: The viewing pipeline, viewing coordinate reference frame, window to view-port coordinate transformation, viewing functions, Cohen-Sutherland and Cyrus-beck line clipping algorithms, Sutherland –Hodgeman polygon clipping algorithm. UNIT IV: (10 Lectures) 3-D object representation: Polygon surfaces, quadric surfaces, spline representation, Hermite curve, Bezier curve and B-Spline curves, Bezier and B-Spline

surfaces.

UNIT V: (7 Lectures) 3-D geometric transformations: Translation, rotation, scaling, reflection and shear transformations, composite transformations. 3-D viewing: Viewing pipeline, viewing coordinates, projection, view volumes and general projection

transformations and clipping.


Visible surface detection methods: Classification, back-face detection, depth-

buffer, A-buffer, scan-line, depth sorting, BSP-tree, area sub-division, octree and

ray-casting methods. Computer animation: Design of animation sequence,

general computer animation functions, raster animation, computer animation

languages, key frame systems, motion specifications.

Course Outcomes:

Upon completion of this course, the students will be able to: 1. Understand the graphical system by explaining various concepts and algorithms.

2. Analyze the relationship between algebra and geometry for developing

computational algorithms.

3. Compare various visible surface detection methods and apply the algorithms to

create an animated graphical display.


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 2 - - - - - - - - - - - -

CO2 3 3 3 2 - - - - 2 2 - 2 - -

CO3 3 2 3 3 3 - - - - - - - 2 3

TEXT BOOKS:

1. Donald Hearn and M.Pauline Baker, Computer Graphics C version, 2nd edition,

Pearson Education.

2. Foley, VanDam, Feiner and Hughes, Computer Graphics Principles & practice,

second edition in C, Pearson Education.

REFERENCE BOOKS:

1. Neuman and Sproul, Principles of Interactive Computer Graphics, TMH.

2. Steven Harrington, Computer Graphics,TMH.

ARTIFICIAL INTELLIGENCE

(PROFESSIONAL ELECTIVE–I)



Prerequisites: Familiarity with Discrete Mathematics, Linear Algebra and

Probability.

Course Objectives: The objective of the course is to present an overview of artificial intelligence principles and approaches.

Syllabus:


Introduction to artificial intelligence: Introduction, history, intelligent systems,

foundations of AI, applications, tic-tac-toe game playing, development of AI

languages, current trends in AI. Problem solving: state-space search and

control strategies: Introduction, general problem solving, characteristics of

problem.


Search Strategies: exhaustive searches, heuristic search techniques, iterative-

deepening a*, constraint satisfaction. Problem reduction and game playing:

Introduction, problem reduction, game playing, alpha-beta pruning, two-player

perfect information games.


Logic concepts: Introduction, propositional calculus, proportional logic, natural

deduction system, axiomatic system, semantic tableau system in proportional logic,

resolution refutation in proportional logic, predicate logic.


Knowledge representation: Introduction, approaches to knowledge

representation, knowledge representation using semantic network, extended

semantic networks for KR, knowledge representation using frames. Advanced

knowledge representation techniques: Introduction, conceptual dependency

theory, script structure, cyc theory.


Expert system and applications: Introduction phases in building expert systems,

expert system versus traditional systems, rule-based expert systems blackboard

systems truth maintenance systems, application of expert systems, list of shells and

tools.


Uncertainty measure: probability theory: Introduction, probability theory, Bayesian belief networks, certainty factor theory, dempster-shafer theory. Fuzzy

sets and fuzzy logic: Introduction, fuzzy sets, fuzzy set operations, types of membership functions, multi valued logic, fuzzy logic, linguistic variables and hedges, fuzzy propositions, inference rules for fuzzy propositions, fuzzy systems.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1 Summarize and formulate appropriate logic concepts and AI methods for

solving a problem. CO 2 Applying various searching, game playing, and knowledge representation

techniques to solve the real world problems. CO 3 Analyze different expert systems and its applications. CO 4 Explain the concepts of probability theory, fuzzy sets and fuzzy logic for

uncertainty measure.


POs/ COs

PO1

PO2

PO3

PO4

PO5

PO6

PO7

PO8

PO9

PO10

PO11

PO12

PSO1

PSO2

CO1 3 - - - - - - - - - - - - -

CO2 3 3 3 - - - - - - - - - - -

CO3 2 3 - - - - - - - - - - - -

CO4 3 - - - - - - - - - - - - -

TEXT BOOKS: 1. Saroj Kaushik, Artificial Intelligence, CENGAGE Learning. 2. Stuart Russel, Peter Norvig, Artificial intelligence, A modern Approach, 2nd ed,

PEA. 3. Rich, Kevin Knight, Shiv Shankar B Nair, Artificial Intelligence, 3rd ed, TMH. 4. Patterson, Introduction to Artificial Intelligence, PHI.

REFERENCE BOOKS: 1. George F Lugar ,Artificial intelligence, structures and Strategies for Complex

problem solving, 5th ed, PEA.

2. Ertel, Wolf Gang, Introduction to Artificial Intelligence, Springer.

3. Nils J Nilsson, A new Synthesis Artificial Intelligence, Elsevier.

LINUX PROGRAMMING

(PROFESSIONAL ELECTIVE-I)



Prerequisites: Familiarity with general Operating System concepts, Computer

Architecture and knowledge in Computer Networks.

Course Objectives:

This course provides Linux utilities and Shell scripting language (bash) to solve

Problems. Develops the skills necessary for systems programming including files,

process and signal management, and interprocess communication.

Syllabus:


Linux Utilities: File handling utilities, Security by file permissions, Process

utilities, Disk utilities, Networking commands, Filters, Text processing utilities

and Backup utilities, Sed – scripts, operation, addresses, commands, applications,

awk – execution, fields and records, scripts, operation, patterns, actions, functions,

system commands in awk.


Working with the Bourne Again Shell (Bash): Introduction, shell

responsibilities, pipes and Redirection, here documents, running a shell script, the

shell as a programming language, shell meta characters, file name substitution, shell

variables, command substitution, shell commands, the environment, quoting, test

command, control structures, arithmetic in shell, shell script examples, interrupt

processing, functions, debugging shell scripts.


Linux Files: File Concept, File System Structure, File metadata-Inodes, File types,

Kernel support for files, system calls for file I/O operations- open, create, read,

write, close, lseek,dup2, file status information- stat family, file and record locking-

fcntl function, file permission-chmod, fchmod,file ownership-chown, lchown,fchown,

links- soft links & hard links - unlink, link, symlink.

Directories: creating, removing and change Directories (mkdir, rmdir, chdir),

obtaining current working directory(getcwd), Directory contents, Scanning

Directories (opendir, readdir, closedir,rewinddir, seekdir, telldir functions).


Linux Process: Process concept, Layout of C program image in main memory,

Process environment- environment list, environment variables, getenv, setenv,

Kernel support for process, process identification, process control - process creation,

replacing a process image, waiting for a process, process termination, zombie

process, orphan process, system call interface for process management-fork, vfork,

exit, wait, waitpid, exec family, Process groups, Session and Controlling Terminals,

Difference between threads and processes.


Linux Signals: Introduction to signals, Signal generation and handling, Kernel

support for signals, Signal function, unreliable signals, reliable signals, kill, raise,

alarm, pause, abort, sleep functions.

Interprocess Communication: Introduction to IPC, IPC between processes on a

single computer system, IPC between processes on different systems, pipes-

creation, IPC between related processes using unnamed pipes, FIFOs- creation, IPC

between related processes using FIFOs, difference between unnamed and named

pipes, popen, pclose functions.


Message Queues: Kernel support for messages, Linux APIs for messages,

client/server example. Semaphores: Kernel support for semaphores, file locking

with semaphores. Shared Memory: Kernel support for shared memory, shared

memory example. Sockets: Introduction to Sockets, Client Server Model.

Course Outcomes:

Upon completion of this course, the students will be able to

CO 1. Understand the basic commands of Linux operating System and can

implement Shell Script.

CO 2. Build file system and directories and perform different operations on them.

CO 3. Construct processes background and foreground by using fork() system calls.

CO 4. Make use of shared memory segments, pipes, semaphores and message

queues and exercise on interprocess communication.

CO 5. Develop various client server applications using Sockets.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 2 - - 3 - - - - - - - 2 - -

CO2 2 - 3 3 - - - - - - - 2 - -

CO3 2 - 3 3 - - - - - - - 3 - -

CO4 3 - 2 3 - - - - - - - 3 - -

CO5 3 - 3 2 - - - - - - - 3 - -

TEXT BOOKS:

1) N.Matthew, R.Stones, Beginning Linux Programming, 4th edition,Wiley Publishing.

2) Mark G. Sobell, A Practical Guide to Linux Commands, Editors, and Shell

Programming, 3rd edition, Pearson Education.

3) Robert Love, Linux System Programming, 1st edition, O’Reilly, SPD.

REFERENCE BOOKS:

1) Stephen G. Kochan, Patrick Wood, Shell Programming - In Unix, Linux and OS X,

4th edition, Pearson.

2) https://www.coursera.org/learn/unix

3) https://www.pluralsight.com/courses/linux-systems-programming

4) https://www.edx.org/course/introduction-linux-linuxfoundationx-lfs101x-1

https://www.flipkart.com/author/stephen-g-kochan

https://www.flipkart.com/author/patrick-wood

SOFTWARE TESTING METHODOLOGIES

(PROFESSIONAL ELECTIVE–I)



Prerequisites: Basic concepts of software engineering and real-time problem

analytical skills.

Course Objectives:

This course enables the learners to have a higher level knowledge related to

software testing methodologies of a product in IT industry. It focuses on various

principles, methods and techniques related to various types of software testing as

well as efficient testing strategies, software quality management, and automation &

testing tools. Learners will get exposure to various real time testing practices testing

different types of software through this course.

Syllabus:


SOFTWARE TESTING

Introduction, Evolution, Myths & Facts, Goals, Psychology, Definition, Model for

testing, Effective Vs Exhaustive Software Testing.

Software Testing Terminology and Methodology: Software Testing

Terminology, Software Testing Life Cycle, relating test life cycle to development life

cycle, Software Testing Methodology.


VERIFICATION AND VALIDATION

Verification & Validation Activities, Verification, Verification of Requirements, High

level and low level designs, How to verify code, Validation.

Dynamic Testing I: Black Box testing techniques: Boundary Value Analysis,

Equivalence class Testing, State Table based testing, Decision table based testing,

Cause-Effect Graphing based testing, Error guessing.


DYNAMIC TESTING II

White-Box Testing: need, Logic coverage criteria, Basis path testing, Graph

matrices, Loop testing, data flow testing, mutation testing.

Static Testing: inspections, Structured Walkthroughs, Technical reviews.


VALIDATION ACTIVITIES

Unit testing, Integration Testing,. Function testing, system testing, acceptance

testing.

Regression testing: Progressives Vs regressive testing, Regression testability,

Objectives of regression testing, When regression testing done?, Regression testing

types, Regression testing techniques.


EFFICIENT TEST SUITE MANAGEMENT

Test case design Why does a test suite grow, Minimizing the test suite and its

benefits, test suite prioritization, Types of test case prioritization, prioritization

techniques, measuring the effectiveness of a prioritized test suite.

Software Quality Management: Software Quality metrics, SQA models

Debugging: process, techniques, correcting bugs, Basics of testing management

tools, test link and Jira.


AUTOMATION AND TESTING TOOLS

Need for automation, categorization of testing tools, selection of testing tools, Cost

incurred, Guidelines for automated testing, overview of some commercial testing

tools.

Testing Object Oriented Software: basics, Object oriented testing

Testing Web based Systems: Challenges in testing for web based software,

quality aspects, web engineering, testing of web based systems, Testing mobile

systems.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Interpret the basic principles of software testing and its process.

CO 2. Classify different types of verification & validation techniques to ensure the

functioning of a software system.

CO 3. Build efficient test suites with regression techniques to assess the quality of

software applications.

CO 4. Apply automation testing tools on software applications in various domains.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 2 - 2 - - - - - - - - 2 - -

CO2 3 - 3 - 2 2 - - 2 2 - 2 - -

CO3 3 - 3 - 2 2 - - 2 2 - 2 - -

CO4 3 - 3 - 2 2 - - - - - 2 - -

TEXT BOOKS:

1. Naresh Chauhan, Software Testing Principles and Practices, Oxford. 2. Aditya P Mathur, Foundations of Software Testing, 2nd Edition, Pearson.

3. Yogesh Singh, Software Testing, Cambridge.

REFERENCE BOOKS:

1. Baris Beizer, Software Testing Techniques , 2nd Edition, International Thomson

Computer Press.

2. M G Limaye, Software Testing, Principles, Techniques and Tools, TMH.

3. Willian E Perry, Effective Methods for Software testing, 3rd Edition, Wiley.

COMPILER DESIGN LAB


III Year / I Semester 0 0 3 1.5

Prerequisites: Familiarity with C or Java Programming.

Course Objectives: This course is aimed at providing the implementation of basic

parsers and tools of compiler design. List of Programs:

1. Write a Program to implement Lexical Analyzer.

2. Write a Program to implement the Lexical Analyzer using LEX Tool.

3. Write a Program for implementation of Predictive Parser.

4. Write a Program to compute FIRST of Non-Terminals.

5. Write a Program to compute FOLLOW of Non-Terminals.

6. Write a Program to implement Top-Down Parser for a given Grammar.

7. Write a Program to implement LL(1) Parser for a given Grammar.

8. Write a Program to implement the LALR Parser for a given Grammar.

9. Write a Program to convert Infix Expression to Post Expression.

10. Write a Program to construct the Predictive Parser for a given Grammar.

11. Write a Program to construct the Shift-Reduce Parser for a given Grammar.

12. Write a Program to construct the CLR Parser for a given Grammar.

13. Generate the Three Address Code for a given Expression.

14. Generate the optimized Three Address Code for a given Expression.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Apply the algorithms and design techniques to solve problems. CO 2. Design parser generator using compiler constructor tools to build a simple

Compiler. Mapping of COs to POs:

POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 - 3 3 2 3 - - 3 3 3 - 1 3 -

CO2 - 3 3 2 3 - - 3 3 3 - 1 3 -

TEXT BOOKS: 1. Alfred V Aho, Monica S Lam, Ravi Sethi, Jeffrey D. Ullman ,Compilers Principles

Techniques and Tools-,2nd ed, Pearson. 2. Kenneth C Louden, Compiler construction, Principles and Practice, CENGAGE. REFERENCE BOOKS: 1. K. Muneeswaran, Compiler Design, Oxford. 2. Keith D.Cooper & Linda Torczon, Engineering a compiler, 2nd edition, Morgan

Kaufman.

COMPUTER NETWORKS AND OPERATING SYSTEMS LAB



Prerequisites: Familiarity with C or Java Programming.

Course Objectives: The students will learn and implement the Various Error correction, Detection Mechanisms, concepts of routing algorithms, and OS concepts like Processor scheduling and Deadlock mitigation Techniques and Analyze Various file, disk and memory management mechanisms.


PART A: Computer Networks Lab

Week 1: Implement the Data Link Layer Framing methods such as Character Stuffing and Bit Stuffing. Week 2: Implement CRC and checksum methods. Week 3: Implement one bit error correction in the received frame using Hamming code. Week 4: Write a program to implement distance vector routing algorithm. Week 5: Write a program to implement Broad cast routing algorithm. Week 6: a. Write a program to develop a simple Chat TCP application. b. Write a program to develop a simple Chat UDP application.

PART B: Operating Systems Lab

Week 7: Simulate the following CPU Scheduling Algorithms a. FCFS b. SJF c. Priority Week 8: Simulate Bankers Algorithm for Deadlock Avoidance. Week 9: Simulate the following Page Replacement Algorithms

a. FIFO b. LRU

Week 10: Simulate the following File Allocation Strategies

a. Sequential b. Indexed Week 11: Simulate the following disk scheduling algorithms a. SCAN b. SSTF

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Implement various techniques for error free transmission.

CO 2. Identify and apply the algorithm best suited for finding the optimal path.

CO 3. Design an application by selecting the appropriate service and protocols.

CO 4. Apply the appropriate algorithm to address the processor scheduling and

deadlock situation.

CO 5. Implement various algorithms for memory management.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 3 2 - - 3 3 3 - 3 2 3

CO2 3 3 3 3 2 - - 3 3 3 - 3 3 3

CO3 3 3 3 3 2 3 2 3 3 3 3 3 3 3

CO4 3 3 3 3 2 - - 3 3 3 - 3 3 2

CO5 3 3 3 - 2 - - 3 3 3 - 3 3 3

TEXT BOOKS: 1. Behrouz A. Forouzan, Data Communications and Networking, 5th Edition, TMH,

2013.

2. A.S. Tanenbaum, Computer Networks, 4th Edition, Pearson Education.

3. Abraham Silberchatz, Peter B.Galcin,Greg Gagne,Operating System Concepts,

8th Edition, John Wiley.

4. Stallings, Operating systems-internals and design principles, sixth Edition,

Pearson education -2009.

MICROPROCESSORS AND MICROCONTROLLERS LAB



Prerequisites: Familiarity with Digital Electronics and Assembly Language

Programming.

COURSE OBJECTIVES: In this laboratory the students get the opportunity to apply the theoretical

knowledge they acquired in their microprocessor course to real hardware and

software. The course uses a TASM as a development platform tool, so students can

experience assembly language programming techniques. They also Learn the

programming with ADRUINO UNO.

List of Experiments: Write 8086 microprocessor - Assembly Language Programs (ALP) for the following list of experiments using TASM/MASM. 1. ALP to display the String ‘Hello, welcome to SVECW’. 2. ALP to add two 16-bit integer numbers. 3. ALP to compute average of two 16-bit integer numbers. 4. ALP to multiply two 16-bit integer numbers. 5. ALP to divide two 16-bit integer numbers. 6. ALP to swap two numbers. 7. ALP to check whether a given number is odd or even number. 8. ALP to find GCD of two numbers. 9. ALP to find LCM of two numbers. 10. ALP to convert a unpacked BCD numbers into packed BCD number. 11. ALP to find the sum of numbers in an array. 12. ALP to copy a string from one location to another location. 13. ALP to reverse a string. 14. ALP Evaluate an arithmetic expression. 15. ALP to find the largest number in the given list of numbers. 16. ALP to find the Factorial of a given number. 17. ALP to perform Linear Search in a given list of numbers. 18. ALP to perform Binary Search in a given list of numbers. 19. ALP to perform Bubble Sort in a given list of numbers. 20. ALP to implement Macros for computing square of a given number. 21. ALP to convert binary to decimal and decimal to binary formats. Getting started with ARDUINO UNO 1. Perform a basic experiment to switch on buzzer and LED according to the input. 2. Perform a basic experiment to read temperature from the sensor with arduino using and display on LCD.

3. Perform a basic experiment to control the speed of DC motor.

Course Outcomes:


CO 1. Develop assembly language programs using Arithmetic, Logic and Shift instructions. CO 2. Design Applications that uses Decision, Repetitive and Modular structures. CO 3. Create Programs for various applications to use with ARDUINO UNO.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 - 3 - - 3 3 3 - - - -

CO2 3 3 3 - 3 - - 3 3 3 - - - -

CO3 3 3 3 - 3 - - 3 3 3 - - - -

TEXT BOOKS: 1. Douglas V Hall, Microprocessors and Interfacing,Revised 2nd ed, TMH.

2. Barry Bray,The Intel Microprocessors, Architecture, programming and

interfacing, 8th ed, Pearson.

3. Lyla B Das, The X86 Microprocessors, architecture, Programming and Interfacing

(8086 to Pentium), PEA.

4. AJAY V Deshmukh,Microcontrollers, TATA McGraw Hill publications.

REFERENCE BOOKS: 1. Walter A Triebel, Avtar Singh, The 8088 and 8086 Microprocessors,

Programming, Interfacing, Hardware and Applications,4th ed,Pearson.

2. Liu,Micro Computer System 8086/8088 Family Architecture, Programming and

Design, Prentice Hall.Muhammad Ali Mazdi, 8051 Microcontrollers & Embedded

Systems, Pearson Education.

LOGICAL REASONING



Course Objectives:

To train students to critically evaluate various real life situations by resorting to

logical analysis of key issues and factors.

To prepare students to read between the lines and understand various sentence

structures.

Chapter 1 : Probability Basic problems - Addition theorem of probability for 2, 3, or 4 events - Conditional Probability. Chapter 2 : Permutations & Combinations Sum & Product Rules, Permutations and Combinations without repetitions, with repetitions and with constrained repetitions – ncr, npr & n! formulas – Binomial coefficients – Principle of inclusion and exclusion. Chapter 3 : Coding, Decoding, Letter and Number Series Letter Coding, Direct Letter coding, Number / Symbol coding, Substitution Coding, Deciphering message word coding and its types, Number series, Letter Series, Analogy.

Chapter 4 : Calendar Odd days - Ordinary year-Leap year - Day for given date - Years with same Calendar. Chapter 5 : Clocks Minute divisions - Angle between two hands - Time in the Clock for given Angle – Incorrect Clock-Direction of Minute/Hour hand at given Time-Mirror time. Chapter 6 : Directions Direction Names - Starting Direction - Ending Direction – Distance. Chapter 7 : Data Analysis and Interpretation Tabulation- Pie Charts – Bar Diagrams – Line Graphs.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Distinguish the basic elements of arguments and recognize the different types

of arguments. CO 2. Construct natural language statements in the language of propositional and

predicate logic. CO 3. Examine logical relations among statements; and analyze logically complex

statements into their truth- functional or quantificational components. CO 4. Distinguish valid deductive arguments from invalid ones CO 5. Make use of appropriate arithmetic formulae to draw conclusions on logical

problems Mapping of COs to POs:

POs/COs

PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO 10

PO 11

PO 12

CO1 - - - - - -

- - - - - 2

CO2 - - - - - - - - - - - 2

CO3 - - - - - - - - - - - 2

CO4 - - - - - - - - - - - 2

CO5 - - - - - - - - - - - 2

REFERENCE BOOKS: 1. M.Tyra, Magical book on Quicker Maths, BSC Publishing Co. Pvt. Ltd. 2. R.S. Aggarwal, A modern approach to Logical reasoning, S. Chand Publications. 3. Edgar Thorpe, Test of reasoning for competitive Examinations, TMH publications. 4. R.V. Praveen, Quantitative Aptitude and Reasoning, 3rd ed., PHI publications.

III Year

II Semester

DATA WAREHOUSING AND DATA MINING


III Year / II Semester 3 0 0 3

Prerequisites: Familiarity with Database Management Systems. Course Objectives: The objective of this course is to teach the basic data mining concepts with

particular emphasis on the association, classification, prediction and clustering

techniques. Students will be enabled to understand and implement classical models

and algorithms in data warehousing and data mining. They will learn how to analyze

the data, identify the problems and choose the relevant algorithms for different

kinds of data.

Syllabus:


Introduction: Fundamentals of data mining, Data mining functionalities,

Classification of Data mining Systems, Data mining primitives, Major issues in data

mining.

Data Preprocessing: Needs for preprocessing the Data, Data Cleaning, Data

Integration and Transformation, Data Reduction, Data Discretization and Concept

Hierarchy Generation.


Data Warehouse: Introduction, Multidimensional Data Model, Data Warehouse

Architecture, Data Warehouse Implementation, From Data Warehousing to Data

mining.


Mining Association Rules in Large Databases: Basic Concepts, Frequent item set

Mining Methods, Mining Multilevel Association Rules, Mining Multidimensional

Association Rules from Relational Databases and Data Warehouses, From

Association Mining to Correlation Analysis.


Classification and Prediction: Issues Regarding Classification and Prediction,

Classification by Decision Tree Induction, Bayesian Classification, Classification by

Back propagation, Associate Classification, Prediction, Accuracy and measures,

Evaluating the accuracy.


Cluster Analysis: Introduction, Types of Data in Cluster Analysis, A Categorization of

Major Clustering Methods, Partitioning Methods, Hierarchical Methods, Model-Based

Clustering Methods, Outlier Analysis.


Mining Different Kinds of Data: Mining Time-Series and Sequence Data, Social

Network Analysis, Mining Text Databases, Mining the World Wide Web.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Outline data mining functionalities and use data preprocessing techniques to

improve the overall quality of the pattern mined from the data. CO 2. Apply data warehouse computation techniques on large data set. CO 3. Experiment with association, classification and clustering algorithms on

different kinds of data to extract knowledge.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 3 3 - - - 2 2 - 3 - 3

CO2 3 3 3 3 3 - - - 2 2 - 3 - 3

CO3 3 3 3 3 3 - - - 2 2 - 3 - 3

TEXT BOOKS:

1. Jiawei Han, Jian Pei & MichclineKamber, Data Mining - Concepts and Techniques,

3rd edition, Morgan Kauffman Publishers. 2. Pang- Ning tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining,

1st edition, Pearson.

REFERENCE BOOKS:

1. Margaret H.Dunham, Data Mining: Introductory and Advanced Topics, 1st

edition Pearson.

2. Arun K Pujari, Data Mining Techniques, Universities Press.

3. Paulraj Ponniah, Data Warehousing Fundamentals, Wiley Student Edition.

INFORMATION SECURITY



Prerequisites: Familiarity with Probability & Statistics and Computer Networks.

Course Objectives: The students will able to learn the different attacks,

confidentiality, integrity, authentication and availability, and how to detect and

prevent the various attacks.

Syllabus: UNIT I: (10 Lectures) Introduction: Security Attacks, Security Services, Security Mechanisms, and a Model for Network Security. Non-Cryptographic Protocol Vulnerabilities-DoS, DDoS, Session Hijacking and Spoofing, Software Vulnerabilities- Phishing, Buffer Overflow, Format String Attacks, SQL Injection. Basics of Cryptography – Steganography, Symmetric Cipher Model, Substitution Techniques, Transportation Techniques, Other Cipher Properties- Confusion, Diffusion, Block and Stream Ciphers.


Secret Key Cryptography: S-DES, Data Encryption Standard (DES), Strength of DES, Block Cipher Design Principles and Modes of Operations, Triple DES, AES. Number Theory: Divisibility and the Division Algorithm, Prime and Relatively Prime Numbers, Modular Arithmetic, Fermat’s and Euler’s Theorems, the Chinese Remainder Theorem, Discrete Logarithms.

UNIT III: (8 Lectures) Public Key Cryptography: Principles of Public Key Cryptosystems, RSA Algorithm, Diffie-Hellman Key Exchange, Introduction to Elliptic Curve Cryptography. Cryptographic Hash Functions: Applications of Cryptographic Hash Functions, Secure Hash Algorithm, Message Authentication Codes – Message Authentication Requirements and Functions, HMAC, Digital signatures, Digital Signature Standards. UNIT IV: (10 Lectures)

Authentication Applications: Kerberos, Key Management and Distribution, X.509 Directory Authentication service, Public Key Infrastructure, Electronic Mail Security: Pretty Good Privacy.


IP Security: Overview, Architecture, Authentication Header, Encapsulating Security Payload, Combining security Associations, Internet Key Exchange. Web Security: Web Security Considerations, Secure Sockets Layer and Transport

Layer Security, Electronic Payment.

UNIT VI: (7 Lectures) System Security: Malicious Software – Types, Viruses, Virus Countermeasures, Worms. Firewalls: Characteristics, Types of Firewalls, Placement of Firewalls, Firewall Configuration, Trusted systems. Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Identify the basic concepts of cryptography. CO 2. Analyze the various algorithms to ensure the security services. CO 3. Compare and contrast the systems for encryption and hashing. CO 4. Associate algorithms for better security. CO 5. Apply security mechanisms to detect and prevent various attacks.


COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 2 - - - - - 2 - - - 2 - -

CO2 3 3 2 2 2 - - - - - - 3 3 3

CO3 3 3 3 3 3 - - - - - - 2 - -

CO4 3 3 3 3 - - - - - - - 2 - -

CO5 3 3 3 3 2 - - 2 - - - 3 3 3

TEXT BOOKS: 1. William Stallings, Cryptography and Network Security, 4th Edition, Pearson

Education,. 2. Atul Kahate, Cryptography and Network Security, 2nd Edition, Mc Graw Hill. REFERENCE BOOKS: 1. Mark Stamp, Information Security - Principles and Practice, Wiley India. 2. Forouzan Mukhopadhyay, Cryptography and Network Security, 2nd Edition, Mc

Graw Hill. 3. C K Shyamala, N Harini, Dr T R Padmanabhan, Cryptography and Network

Security: 1st Edition, Wiley India.

WEB TECHNOLOGIES



Prerequisites: Familiarity with OOPs concepts, core Java concepts and Internet.

Course Objectives: The student will be familiar with client-server architecture and

able to develop a web application using HTML, JavaScript, PHP, Servlets, JSP, JDBC

and also AJAX. The Students will acquire the necessary skills and techniques needed

for developing Web based Projects.

Syllabus: UNIT I: (8 Lectures) HTML: Tags, Lists, Tables, Images, forms, Frames. CSS: Introduction, CSS Properties, Controlling Fonts, Text Formatting, Pseudo classes, Selectors, CSS for Links, Lists, Tables. UNIT II: (8 Lectures) JavaScript: Variables, Operators, Functions, Control structures, Events, Objects, Form validations, Dynamic HTML with JavaScript. Working with XML: Document type Definition, XML schemas, Document object model, XSLT, DOM and SAX.

UNIT III: (8 Lectures) PHP: Creating PHP script, Running PHP script, Using variables, Using constants,

Data types, Operators, Conditional statements, Control statements, Arrays,

functions, working with forms and Database.

UNIT IV: (8 Lectures) Web Servers and Servlets: Tomcat web server, Introduction to Servlets: Lifecycle of a Servlet, JSDK, The Servlet API, The javax.servlet Package, Reading Servlet parameters, and Reading Initialization parameters, The javax.servlet HTTP package, Handling Http Request & Responses, Using Cookies-Session Tracking, Security

Issues.

UNIT V: (8 Lectures) Introduction to JSP: The Problem with Servlet, The Anatomy of a JSP Page, JSP Processing, JSP Application Design with MVC. JSP Application Development: Generating Dynamic Content, Using Scripting Elements Implicit JSP Objects, Conditional Processing – Displaying Values Using an Expression to Set an Attribute, Declaring Variables and Methods Error Handling and Debugging Sharing Data between JSP pages, Requests, and Users Passing Control and Date between Pages – Sharing Session and Application Data.

UNIT VI: (10 Lectures) Database Access: Database Programming using JDBC, Studying Javax.sql.* package, Accessing a Database from a Servlets and JSP Page, Application – Specific

Database Actions, Deploying JAVA Beans in a JSP Page, Introduction to struts framework. AJAX A New Approach: Introduction to AJAX, Integrating PHP and AJAX. Consuming WEB services in AJAX: (SOAP, WSDL, UDDI).

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Develop interactive WebPages with improved GUI.

CO 2. interpret scripting language techniques using cross platform language.

CO 3. Acquire knowledge on server side scripting language.

CO 4. Apply knowledge to access different databases using web services.


POs/ Cos

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 - - 3 - 3 - - - 3 - 3 - 3 -

CO2 - - 3 - 3 - - - 3 - 3 - 3 -

CO3 - - 3 - 3 - - - 3 - 3 - 3 -

CO4 - - 3 - 3 - - - 3 - 3 - 3 -

TEXT BOOKS:

1. Web Technologies – Black Book, Kogent Learning solutions Inc sol. Dreamtech

press. (Units- 1,2,3,8)

2. Patrick Naughton and Herbert Schildt, The complete Reference Java 2, 7th

Edition. TMH (Units- 4,5,6,7)

3. Wang, Katila, An Introduction to Web Design + Programming, CENGAGE.

REFERENCE BOOKS:

1. Uttam K Roy , Web Technologies, – Oxford.

2. Dietel and Nieto, Internet and World Wide Web – How to program, PHI/Pearson

Education Asia.

3. Wang-Thomson, An Introduction to web Design and Programming.

4. Robert W Sebesta, Programming the World Wide Web – Pearson publications,

Fourth edition.

5. Godbole, Atul Kahate , Web Technologies, TCP/IP Architecture and Java

programming- 2nd ed, TMH.

6. N P Gopalan, Akhilandeswari,Web Technologies, A developer’s Perspective, PHI.

BIG DATA TECHNOLOGIES

(PROFESSIONAL ELECTIVE–II)



Prerequisites: The student should have knowledge of high level programming

languages and SQL for analyzing the data.

Course Objectives: The student will be able to understand Big Data as a popular

term used to describe the exponential growth, availability and use of information,

both structured and unstructured. It is imperative that organizations and IT leaders

focus on the ever-increasing volume, variety and velocity of information that forms

Big Data. Hadoop is the core platform for structuring BigData, and solves the

problem of making it useful for Analytics.


Introduction to Big Data - What is Big Data and where it is produced? Rise of Big Data, Compare Hadoop vs traditional systems, Limitations and Solutions of existing Data Analytics Architecture, Attributes of Big Data, Types of data, other technologies vs Big Data. Hadoop Architecture and HDFS: Topics - What is Hadoop? Hadoop History,

Distributing Processing System, Core Components of Hadoop, HDFS Architecture,

Hadoop Master – Slave Architecture, Daemon types - Learn Name node, Data node,

Secondary Name node.


Hadoop Clusters and the Hadoop Ecosystem- What is Hadoop Cluster? Pseudo

Distributed mode, Type of clusters, Hadoop Ecosystem, Pig, Hive, Oozie, Flume,

SQOOP.

HadoopMapReduce Framework- Overview of MapReduce Framework,

MapReduce Architecture, Learn about Job tracker and Task tracker, Use cases of

MapReduce, Anatomy of MapReduce Program.

MapReduce programs in Java- Basic MapReduce API Concepts, Writing

MapReduce Driver, Mappers, and Reducers in Java, Speeding up Hadoop

Development by Using Eclipse, Unit Testing MapReduce Programs, and Demo on

word count example.


Hive and HiveQL- What is Hive?, Hive vs MapReduce, Hive DDL –

Create/Show/Drop Tables, Internal and External Tables, Hive DML – Load Files &

Insert Data, Hive Architecture & Components, Difference between Hive and RDBMS,

Partitions in Hive.


PIG - PIG vs MapReduce, PIG Architecture & Data types, Shell and Utility

components, PIG Latin Relational Operators, PIG Latin: File Loaders and UDF,

Programming structure in UDF, PIG Jars Import, limitations of PIG.


Apache SQOOP, Flume: Why and what is SQOOP? SQOOP Architecture, Benefits

of SQOOP, Importing Data Using SQOOP, Apache Flume Introduction, Flume Model

and Goals, Features of Flume, Flume Use Case.


NoSQL Databases- What is HBase? HBase Architecture, HBase Components,

Storage Model of HBase, HBase vs RDBMS, Introduction to Mongo DB, CRUD,

Advantages of MongoDB over RDBMS, Use case.

Oozie and Zookeeper-Oozie – Simple/Complex Flow, Oozie Workflow, Oozie

Components, Demo on Oozie Workflow in XML, What is Zookeeper? Features of

Zookeeper, Zookeeper Data Model.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Outline importance of big data in solving real time problems in data analytics.

CO 2. Make use of distributed systems and Hadoop and can write mapreduce

programs to solve complex problems.

CO 3. Explain Hadoop Ecosystem and its components.

CO 4. Compare NoSQL Databases and traditional databases and understand the

importance of NoSQL databases.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 3 3 - - - - - - - 3 3

CO2 3 3 3 3 3 - - 3 - - - - 3 3

CO3 - - 3 3 3 - - - - - - - 3 3

CO4 - - 3 3 3 - - - - - - - 3 3

TEXT BOOKS:

1. Tom White, Hadoop : The Definitive Guide, 3rd Edition, O’reilly

2. Chuck Lam, Hadoop in Action by MANNING Publications.

3. Dirk deRoos, Paul C.Zikopoulos, Roman B.Melnyk, Bruce Brown, Rafael Coss, Hadoop for

Dummies, Wiley Brand.

REFERENCE BOOKS:

1. Alex Holmes, Hadoop in Practice, MANNING Publications.

2. Srinath Perera, Thilina Gunarathne, Hadoop MapReduce Cookbook, Packt publishing.

IMAGE PROCESSING




Prerequisites: Basic knowledge in Mathematics and Computer Graphics.

Course Objectives: The course objective is to provide introduction to basic

concepts and methodologies to digital image processing, and to develop a

foundation that can be used as the basis for further study and research in this field.

Syllabus:

UNIT I: INTRODUCTION (8 Lectures)

Introduction to Digital Image Processing, Fundamental steps in image processing

systems, Image acquisition, Sampling and quantization, Basic relationship between

pixels, Mathematical tools used in image processing, Camera model of Image, Need

for image transform and spatial frequencies in image processing, 2-D DFT, DCT,

DST transforms.

UNIT II: IMAGE ENHANCEMENT (8 Lectures)

Some basic intensity transformation functions, Histogram processing, Fundamentals

of spatial filtering –smoothing spatial filters and sharpening spatial filters, Combining

spatial enhancement methods, Transformation and spatial filtering, Image

smoothing using frequency domain filters Selective filtering and implementation.

UNIT III: IMAGE RESTORATION & RE-CONSTRUCTION (9 Lectures)

Image degradation/restoration model, Noise models, Restoration in the presence of

noise, linear Position invariant degradation, Estimation of degradation function and

inverse filtering, Wiener filtering, Constrain least square filtering.

UNIT IV: COLOR IMAGE PROCESSING (9 Lectures)

Color fundamentals, Color models, Pseudo color Image Processing, Basics of full

color image processing, Color transformations, Smoothing and sharpening.

UNIT V: IMAGE COMPRESSION AND WATER MARKING (8 Lectures)

Lossless Compression: Variable length coding, Dictionary-based coding, LZW

compression, Lossy Compression, Image Compression standards, JPEG, JPEG 2000,

Digital Water Marking, Frequency Domain Water Marking, Security Attacks.

UNIT VI: SEGMENTATION & MORPHOLOGICAL PROCESSING (7 Lectures)

Erosion and Dilation, Opening and closing, Hit or miss transformation, some basic

Morphological algorithms, Gray-Scale Morphology, Point , line and edge detection,

Thresholding, Region oriented segmentation, Segmentation using morphological

watersheds, Use of motion in segmentation.

Course Outcomes:


CO 1. Understand the fundamentals steps in image processing.

CO 2. Analyze different filters and transformations for the enhancement of an

image.

CO 3. Apply image processing techniques for restoration, reconstruction and

compression of images.

CO 4. Compare various color models to perform color image processing.

CO 5. Explain the concepts of segmentation and distinguish basic morphological

algorithms.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 2 - - - - - - - - - - - -

CO2 3 3 2 - 2 - - - - - - - - -

CO3 3 - 2 2 2 - - - 2 2 - 2 2 3

CO4 2 2 - - 3 - - - 2 2 - 2 2 3

CO5 2 2 2 - 2 - - - - - - - - -

TEXT BOOKS:

1. Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, 2011,

Pearson Education.

2. Anil K jain, Fundementals of Digital Image Processing, 2012, Prentice Hall of

India.

REFERENCE BOOKS:

1. S.Jayaraman,S,Esakkirajan,T.Veerakumar, Digital Image Processing, 2009,

McGraw Hill Publisher.

2. B.Canda and D DuttaMjumder, Digital Image Processing and analysis, 2011/12,

Prentice Hall of india.

NATURAL LANGUAGE PROCESSING

(PROFESSIONAL ELECTIVE-II)



Prerequisites: Familiarity with Compiler Design.

Course Objectives: The main objective of the course is to learn how to develop

practical computer systems capable of performing intelligent tasks on natural

language analyze, understand and generate written text.

Syllabus:


Introduction: What is Natural Language Processing, NLP tasks in syntax,

semantics, and pragmatics. Applications such as information extraction, question

answering, and machine translation. The problem of ambiguity. The role of machine

learning. Brief history of the field.


N-gram Language Models: The role of language models, Simple N-gram models.

Estimating parameters and smoothing. Evaluating language models.

Part of Speech Tagging and Sequence Labeling: Lexical syntax. Hidden

Markov Models. Maximum Entropy Models. Conditional Random Fields.


Syntactic Parsing: Grammar formalisms and tree banks. Efficient parsing for

context-free grammars (CFGs). Statistical parsing and probabilistic CFGs (PCFGs).

Lexicalized PCFGs.


Semantic Analysis: Lexical semantics and word-sense disambiguation.

Compositional semantics. Semantic Role Labeling and Semantic Parsing.


Information Extraction (IE) and Machine Translation (MT): Named entity

recognition and relation extraction. IE using sequence labeling. Basic issues in MT.

Statistical translation, word alignment, phrase-based translation, and synchronous

grammars. Dialogues: Turns and utterances, grounding, dialogue acts and

structures.


Natural Language Generation: Introduction to language generation,

architecture, discourse planning (text schemata, rhetorical relations).

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Relate the basics of NLP and study the role of machine learning in processing

NLP.

CO 2. Analyze various Language Models and process part of speech tagging for

static NLP.

CO 3. Discover how to analyze the words and extract meaning from the text.

CO 4. Identify various ways to draw inferences from text and language translation.

CO 5. Summarize the mechanisms to generate natural language.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 - 2 1 - - - - - - - - - - -

CO2 - 3 2 3 - 3 - - - - - 3 - -

CO3 - 3 3 - - 3 - - - - - 3 - -

CO4 - 3 3 - - 2 - - 1 - - 3 - 3

CO5 - 2 2 2 - - - - 1 - - 3 - 3

TEXT BOOKS:

1. D. Jurafsky, J. H. Martin, Speech and Language Processing- An introduction to

Language Processing, Computational Linguistics, and Speech Recognition,

Pearson Education.

2. Manning and Schutze, Foundations of Statistical Natural Language Processing,

MIT Press.

REFERENCE BOOKS:

1. Allen, James Benjamin/Cummings, Natural Language Understanding, Benjamin-

Cummings Publishing Co, 2ed.

2. Bharathi, A., Vineet Chaitanya and Rajeev Sangal, Natural Language Processing-

A Pananian Perspective, Prentice Hll India, Eastern Economy Edition.

CLOUD COMPUTING




Prerequisites: Familiarity with Operating Systems, Computer Networks and Database

Management Systems.

Course Objectives: The objective of this course is to provide students with the

comprehensive and in-depth knowledge of Cloud Computing concepts, technologies,

architecture and applications.

Syllabus:


Introduction to Cloud Computing: Trends in Computing - Distributed Computing, Grid

Computing, Cluster Computing, Utility Computing, Cloud Computing, Definition of Cloud

Computing, Characteristics, Service Models, Deployment Models, Cloud Service Models

Providers, Advantages and Disadvantages of Cloud Computing , Cloud-based Services &

Applications.


Cloud Concepts & Technologies: Virtualization and its types, Software Defined

Networking, Network Function Virtualization(NFV).

Cloud Services: Compute Services, Storage Services, Database Services, Application

Services.


Cloud Application Design: Design Considerations for Cloud Applications, Reference

Architectures for Cloud Applications, Cloud Application Design Methodologies: SOA, Cloud

Component Model, and MVC, Data Storage Approaches.


Cloud Security: Cloud Security Architecture(CSA), Authentication, Authorization, Identity &

Access Management, Data Security, Key Management.


Migrating into a Cloud: Broad Approaches to Migrating into the Cloud, The Seven-Step

Model of Migration into a Cloud, Migration Risks and mitigation, Phases of Migrating to

Cloud, benefits and risks of Migrating to Cloud.


SLA Management in Cloud Computing: Service Level Agreements(SLA), Considerations

for SLA, SLA Requirements, Types of SLA, Life Cycle of SLA, SLA Management in Cloud.

Case Study: Amazon AWS: EC2, Amazon Simple DB, Amazon S3, Amazon Cloud Front and

Amazon SQS.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Illustrate key technologies, strengths, and limitations of cloud computing and the

possible applications for state-of-the-art cloud computing.

CO 2. Choose the appropriate methodologies and considerations for Cloud application

design.

CO 3. Interpret the core issues of Cloud Computing such as security, Privacy and

Interoperability.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 2 2 2 - - - - - - - - - 3

CO2 3 3 2 2 - - - - - - - - - 3

CO3 3 3 - 3 - 2 - - - - - - - 3

TEXT BOOKS:

1. Arshdeep Bahga, Vijay Madisetti, Cloud Computing : A Hands-on Approach, Universities Press.

2. Rajkumar Buyya, James Brogerg, Andrzej Goscinski, Cloud Computing : Principles and Paradigms, WILEY Publication.

REFERENCE BOOKS:

1. Michael Miller, “Cloud Computing – Web Based Applications That Change the way you Work and Collaborate Online”, Pearson Education.

2. Anthony T. Velte Toby J. Velte, Robert Elsenpeter, “Cloud Computing : A Practical Approach”, McGraw-Hill,(2010).

3 Arshdeep B, Vijay M, “Cloud computing: A Hands-on Approach”, Universities Press.

SOFTWARE PROJECT MANAGEMENT




Prerequisites: Basic concepts of Software Engineering.

Course Objectives: This course enables the learners to understand the importance of software

project management in a product life cycle in IT industry. It focuses on various

principles and methods related to management of cost, time, human resources,

risks, procurement, monitoring and controlling related to a product development.

Learners will get exposure to various real time project management practices to

build quality products with in time through this course.

Syllabus:


INTRODUCTION TO SOFTWARE PROJECT MANAGEMENT

Project Stakeholders, Project Management Knowledge Areas, Project Management

Tools and Techniques, Program and Project Portfolio Management, the Role of the

Project Manager, the Project Management Profession, Project Phases and the

Project Life Cycle.


SOFTWARE PROJECT TIME AND COST MANAGEMENT

Time management The Importance of Project Schedules, Estimating Activity

Resources, Estimating Activity Durations, Developing the Schedule, Controlling the

Schedule, Using Software to Assist in Project Time Management. Cost management:

The Importance of Project Cost Management, Basic Principles of Cost Management,

Estimating Costs, Types of Cost Estimates, Cost Estimation Tools and Techniques,

Determining the Budget, Controlling Costs.


HUMAN RESOURCES MANAGEMENT

The Importance of Human Resource Management, Keys to Managing People,

Developing the Human Resource Plan, Acquiring the Project Team, Developing the

Project Team, Managing the Project Team, Using Software to Assist in Human

Resource Management.


RISK MANAGEMENT

Planning Risk Management, Common Sources of Risk on Information Technology

Projects, Identifying Risks, Performing Qualitative Risk Analysis, Performing

Quantitative Risk Analysis, Planning Risk Responses, Monitoring and Controlling

Risks, sing Software to Assist in Project Risk Management.


PROJECT INTEGRATION MANAGEMENT

Strategic Planning and Project Selection, Developing a Project Charter, Developing a

Project Management Plan, Directing and Managing Project Execution.


MONITORING AND CONTROLLING

Project Work, Performing Integrated Change Control, Closing Projects or Phases.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Interpret the importance of software project management with roles and

responsibilities of the team in the real-time project life cycle.

CO 2. Classify different methods required in project management related to

time, cost and human resource management.

CO 3. Identify risks in project life cycle and plan for risk management strategies.

CO 4. Develop a project charter by integrating all the project management

knowledge areas.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 2 - - - - - - - - - 3 2 - -

CO2 3 3 - - 3 - - - 2 2 3 2 - -

CO3 2 2 - - 2 - - - 2 2 3 2 - -

CO4 3 3 - - - - - - - - 3 2 - -

TEXT BOOKS:

1. Kathy Schwalbe, Information Technology Project Management, 6th edition, Cengage Learning, 2011.

2. Walker Royce, Software Project Management A Unified Framework, Pearson Edition.

REFERENCE BOOKS:

1. Ramesh, Gopalaswamy, "Managing Global Projects", Tata McGraw Hill, 2001.

2. Jalote, “Software Project Management in Practice”, Pearson Education, 2002.

INTRODUCTION TO ANALYTICS (ASSOCIATE ANALYTICS – I)




Prerequisites: Familiarity with Database Management Systems and Data

Warehousing & Data Mining.

Course Objectives:This course gives insight about how to apply analytics on data

using R. Statistical data can be summarized and revisited easily using R and

connecting NoSQL databases easily. Through this course can become professional

and build projects for business applications using R and also learn soft skills which

helps to work effectively in the Industry. Associate analysts are basically involved in

the research and investigation for a specific business process or a department. Their

findings help the senior staff to take further decisions for a process or project.

Syllabus:

UNIT I: SQL using R & Correlation and Regression Analysis (8 Lectures)

Introduction to NoSQL, Connecting R to NoSQL databases, Excel and R integration

with R connector, Regression Analysis, Assumptions of OLS Regression, Regression

Modelling, Correlation, ANOVA, Forecasting, Heteroscedasticity, Autocorrelation,

Introduction to Multiple Regression etc.

UNIT II: Understand the Verticals (9 Lectures)

Understanding systems viz. Engineering Design, Manufacturing, Smart Utilities,

Production lines, Automotive, Technology etc., Understanding Business problems

related to various businesses.

UNIT III: Manage your work to meet requirements (9 Lectures)

Understanding Learning objectives, Introduction to work & meeting requirements,

Time Management, Work management & prioritization, Quality & Standards

Adherence. Work effectively with Colleagues : Introduction to work effectively,

Team Work, Professionalism, Effective Communication skills, etc.

UNIT IV: Data Management & Introduction to Big Data Tools (8 Lectures)

Design Data Architecture and manage the data for analysis, Understand various

sources of Data like Sensors/signal/GPS etc.Export all the data onto Cloud ex.

AWS/Rackspace etc. Introduction to Big Data tools like Hadoop, Spark, Impala etc.,

Data ETL process, Identify gaps in the data and follow-up for decision making.

UNIT V: Big Data Analytics & Machine Learning Algorithms (8 Lectures)

Run descriptive to understand the nature of the available data, collate all the data

sources to suffice business requirement, Run descriptive statistics for all the

variables and observe the data ranges, Outlier detection and elimination, Hypothesis

testing and determining the multiple analytical methodologies, Train Model on 2/3

sample data using various Statistical/Machine learning algorithms, Test model on

1/3 sample for prediction etc.

UNIT VI: Data Visualization (8 Lectures)

Prepare the data for Visualization, Use tools like Tableau, QlickView and D3, Draw

insights out of Visualization tool.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Apply appropriate regression model by getting awareness on both relational

and distributed databases. CO 2. Relate the verticals in engineering, financials in pursuit for excellence and

adhere quality and standard in both time and work management. CO 3. Outline various data design architectures and sources of data, by getting

exposed to big data tools. CO 4. Apply descriptive statistics on all available data sources, for model prediction

by using machine learning algorithms. CO 5. Draw insights out of Visualization tool and prepare the data for Visualization.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 - 3 - - - - - - - 2 -

CO2 3 3 3 - - 3 3 3 3 3 3 3 - -

CO3 3 3 3 - 3 - - - 3 3 - 3 - -

CO4 3 3 3 3 3 - - - - - - - - 3

CO5 3 3 3 3 3 - - - - - - - - 3

TEXT BOOKS:

1. G. Jay Kerns, Introduction to Probability and Statistics Using R, 1e, IPSUR. 2. Associate analytics-1

https://drive.google.com/open?id=0B_ySwMoI8wFWMjlGSXE0MmZ4STA 3. Venables and Smith, An Introduction to R, R Development Core Team.

REFERENCE BOOKS:

1. Montgomery, Douglas C., and George C. Runger, Applied statistics and probability for engineers. John Wiley & Sons.

2. Yanchang Zhao, Time Series Analysis and Mining with R. 3. The Basic Concepts of Time Series Analysis.

http://anson.ucdavis.edu/~azari/sta137/AuNotes.pdf

DATA WAREHOUSING AND DATA MINING LAB


III Year / II Semester 0 0 3 1.5

Prerequisites: Familiarity with DBMS and C or Java Programming .

Course Objective: The students can understand data warehouse & data mining principles and aware the environment of WEKA Tool. In addition to that, they can perform various data mining activities through available preprocessing and data mining algorithms on various data sets and will perform qualitative analysis on them.


1. Performing preprocessing on dataset student.arff. 2. Performing preprocessing on dataset labor.arff. 3. Performing Association rule mining on dataset contactlenses.arff using apriori Algorithm. 4. Performing classification on dataset student.arff using j48 algorithm. 5. Performing classification on dataset employee.arff using id3 algorithm. 6. Performing classification on dataset employee.arff using naïve bayes algorithm. 7. Performing clustering on dataset student.arff using simple k-means. 8. Implementation of Apriori algorithm. 9. Implementation of Decision tree classification algorithm. 10. Implementation of K-Means clustering algorithm. 11. Implementation of K-Medoids clustering algorithm.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Describe all components of WEKA Tool. CO 2. Develop data in different formats and apply pre-processing and association

rules to find hidden patterns and interestingness in data. CO 3. Analyze and discover knowledge in different datasets using classification and

clustering algorithms. Mapping of COs to POs:

POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 3 3 - 3 - - - - - - - - -

CO2 3 3 3 3 3 - - 3 3 3 - 3 - 3

CO3 3 3 3 3 3 - - 3 3 3 - 3 - 3

TEXT BOOK:

1. Lan H. Witten & Eibe Frank, Data Mining Practical Machine Learning Tools and

Technology, 2nd edition, Elsevier.

INFORMATION SECURITY LAB Subject Code: UGCS6P1118 L T P C


Prerequisites: Familiarity with C or Java Programming .

Course Objectives: The students will able to create the different attacks, protect the data by using data confidentiality, integrity and authentication. List of Experiments:

1. Simulate Buffer Overflow. 2. Simulate Denial of Service attack. 3. Simulate Sniffing and Spoofing attacks. 4. Simulate Web Based Password Capturing. 5. Implementation of Chinese Remainder Theorem. 6. Implementation of Diffie-Hellman Key Exchange. 7. Implementation of DES algorithm for data encryption. 8. Implementation of RSA algorithm. 9. Implementation of Simple server for Secure socket. 10. Implementation of digital signatures using RSA algorithm.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Deploy various information and network attacks. CO 2. Analyze the symmetric key algorithms for data confidentiality and

authentication in various scenarios. CO 3. Implement asymmetric encryption systems for data confidentiality,

authentication and integrity. CO 4. Simulate the scenario of Security communication among two or more entities. Mapping of COs to POs:

POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 3 3 - - 3 3 3 - - - -

CO2 3 3 3 3 3 - - 3 3 3 - - 2 3

CO3 3 3 3 3 3 3 - 3 3 3 - - 3 3

CO4 3 3 3 3 3 3 - 3 3 3 - - 3 3

TEXT BOOKS: 1. William Stallings, Cryptography and Network Security, 4th Edition, Pearson Education. 2. Atul Kahate, Cryptography and Network Security, 2nd Edition, Mc Graw Hill. REFERENCE BOOKS: 1. C K Shyamala, N Harini, Dr T R Padmanabhan, Cryptography and Network Security: 1st Edition, Wiley India. 2. Mark Stamp, Information Security, Principles and Practice, Wiley India.

WEB TECHNOLOGIES LAB



Prerequisites: Familiarity with OOPs concepts, core Java concepts and Internet.

Course Objectives: The students will learn to develop web applications using the

technologies HTML, Java Script, PHP, XML, Servlets, JSP and database programming

using JDBC.

List Of Experiments: Week-1: Design the following static web pages required for an online book store website. 1) HOME PAGE: The static home page must contain three frames. Top frame : Logo and the website name and links to Home page, Login page, Registration page, Catalogue page and Cart page (the description of these pages will be given below). Left frame: At least four links for navigation, which will display the catalogue of respective links. For e.g.: When you click the link “CSE” the catalogue for CSE Books should be displayed in the Right frame. Right frame: The pages to the links in the left frame must be loaded here. Initially this page contains description of the website.

2) LOGIN PAGE: This page looks like below:

Logo

Website Name

Home

Login

Registration

Catalogue

Cart

CSE ECE EEE

CIVIL

Description of the Website

Logo Website Name

Home Login Registration Catalogue Cart

CSE

ECE

EEE

Civil

Login : Password:

Reset Submit

3) CATOLOGUE PAGE: The catalogue page should contain the details of all the books available in the Website in a table. The details should contain the following:

1. Snapshot of Cover Page 2. Book Name 3. Author Name 4. Publisher 5. Price 6. Add to cart button

Logo Website Name


CSE

ECE

EEE

CIVIL

Book : XML Bible Author : Winston Publication : Wiely Book : AI Author : S.Russell Publication : Princeton hall Book : Java 2 Author : Watson Publication: BPB Publications Book : HTML in 24 hours Author : Sam Peter Publication : Sam publication

$ 40.5 $ 63 $ 35.5 $ 50

Note: Week 2 contains the remaining pages and their description. Week-2: 4) CART PAGE: The cart page contains the details about the books which are added to the cart. The cart page should look like this:

Logo Website Name


CSE

ECE

EEE

CIVIL

Book name Price Quantity Amout Java 2 $35.0 2 $70

XML bible $40.5 1 $40.5

Total Amount - $110.5

5) REGISTRATION PAGE: Create registration“ form “with the following fields

1) Name (Text field) 2) Password (password field) 3) E-mail id (text field) 4) Phone number (text field) 5) Sex (radio button) 6) Date of birth (3 select boxes) 7) Languages known (check boxes – English, Telugu, Hindi, Tamil) 8) Address (text area)

Week-3: Design a web page using CSS (Cascading Style Sheets) which includes the following: 1) Use different font, styles: In the style definition you define how each selector should work (font, color etc.). Then, in the body of your pages, you refer to these selectors to activate the styles. For example:>

<HEAD><style type=

<HTML> <HEAD> <style type="text/css"> B.headline {color:red. font-size:22px. font-family:arial. text-decoration:underline} </style> </HEAD> <BODY> <b>This is normal bold</b><br> Selector {cursor:value} For example: <html> <head> <style type="text/css"> .xlink {cursor:crosshair} .hlink{cursor:help} </style> </head> <body> <b> <a href="mypage.htm" class="xlink">CROSS LINK</a> <br> <a href="mypage.htm" class="hlink">HELP LINK</a> </b> </body> </html> <b class="headline">This is headline style bold</b> </BODY> </HTML>

text/css">headline { <body>

2) Set a background image for both the page and single elements on the page. You can define the background image for the page like this:

BODY {background-image:url(myimage.gif).}

3) Control the repetition of the image with the background-repeat property. As background-repeat tiles the image until the entire page is filled, just like an ordinary background image in plain HTML.

4) Define styles for links as

A:link A:visited A:active A:hover

Example: <style type="text/css"> A:link {text-decoration: none} A:visited {text-decoration: none} A:active {text-decoration: none} A:hover {text-decoration: underline. color: red.} </style>

5) Work with layers: For example:

LAYER 1 ON TOP: <div style="position: relative. font-size:50px. z-index:2.">LAYER 1</div> <div style="position: relative. top:-50. left:5. color: red. font-size:80px.z-index:1">LAYER 2</div>

LAYER 2 ON TOP: <div style="position: relative. font-size:50px. z-index:3.">LAYER 1</div> <div style="position: relative. top:-50. left:5. color: red. font-size:80px.z-index:4">LAYER 2</div> 6) Add a customized cursor:

Selector {cursor:value} For example:

<html>

<head >

BODY {background-image:url(myimage.gif).}

<html>

<head> <style type="text/css"> .xlink {cursor:crosshair} .hlink{cursor:help} </style> </head> <body> <b> <a href="mypage.htm" class="xlink">CROSS LINK</a> <br> <a href="mypage.htm" class="hlink">HELP LINK</a> </b> </body> </html>

WEEK 4: VALIDATION: Write JavaScript to validate the following fields of the above registration page.

1. Name (Name should contains alphabets and the length should not be less than 6 characters).

2. Password (Password should not be less than 6 characters length). 3. E-mail id (should not contain any invalid and must follow the standard

pattern [email protected]) 4. Phone number (Phone number should contain 10 digits only).

Note : You can also validate the login page with these parameters. Week-5:

Write an XML file which will display the Book information which includes the following:

1) Title of the book 2) Author Name 3) ISBN number 4) Publisher name 5) Edition 6) Price

Write a Document Type Definition (DTD) to validate the above XML file.

Display the XML file as follows. The contents should be displayed in a table. The header of the table should be in color GREY. And the Author names column should be displayed in one color and should be capitalized and in bold. Use your own colors for remaining columns. Use XML schemas XSL and CSS for the above purpose. Note: Give at least for 4 books. It should be valid syntactically. Hint: You can use some xml editors like XML-spy.

Week-6: Develop PHP script for

1) Event Handling with forms. 2) Connect Form with Web Server. 3) Connect Form with Mysql for data transfer.

Week-7:

1. Install TOMCAT web server and APACHE.

While installation assign port number 4040 to TOMCAT and 8080 to APACHE. Make sure that these ports are available i.e., no other process is using this port.

2. Access the above developed static web pages for books web site, using these servers by putting the web pages developed in week-1 and week-2 in the document root. Access the pages by using the urls : http://localhost:4040/rama/books.html (for tomcat)

Week-8: User Authentication: Assume four users user1, user2, user3 and user4 having the passwords pwd1, pwd2, pwd3 and pwd4 respectively. Write a servelet for doing the following. 1. Create a Cookie and add these four user id’s and passwords to this Cookie. 2. Read the user id and passwords entered in the Login form (week1) and authenticate with the values (user id and passwords) available in the cookies. If he is a valid user (i.e., user-name and password match) you should welcome him by name(user-name) else you should display “ You are not an authenticate Use init-parameters to do this. Store the user-names and passwords in the webinf.xml and access them in the servelet by using the getInitParameters() method. Week-9:

Install a database (Mysql or Oracle).

Create a table which should contain at least the following fields: name, password, email-id, phone number (these should hold the data from the registration form).

Practice 'JDBC' connectivity. Write a java program/servelet/JSP to connect to that database and extract data from the tables and display them. Experiment with various SQL queries. Insert the details of the users who register with the web site, whenever a new user clicks the submit button in the registration page (week2).

Week-10: Write a JSP which does the following job: Insert the details of the 3 or 4 users who register with the web site (week9) by using registration form. Authenticate the user when he submits the login form using the user name and password from the database ( similar to week8 instead of cookies). Week-11: Create tables in the database which contain the details of items (books in our case like Book name , Price, Quantity, Amount ) of each category. Modify your catalogue page (week 2) in such a way that you should connect to the database and extract data from the tables and display them in the catalogue page using JDBC.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Analyze and apply the role of languages in the working of web applications.

CO 2. Create dynamic web applications using server side application programs.

CO 3. Design database connectivity for different data sources.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 - - 3 - 3 - - 3 3 3 3 - 3 -

CO2 - - 3 - 3 - - 3 3 3 3 - 3 -

CO3 - - 3 - 3 - - 3 3 3 3 - 3 -

TEXT BOOKS:

1. Achyut S Godbole and Atul Kahate, “Web Technologies”, Second Edition, Tata McGraw Hill.

2. HTML 5, Black Book, Dreamtech Press. 3. Herbert Schildt , The Complete Reference Java, 7th edition, Tata McGraw Hill. 4. Steven Holzner, “The Complete Reference - PHP”, Tata McGraw Hill. 5. Mike Mcgrath, “PHP & MySQL in easy Steps”, Tata McGraw Hill. 6. Hans Bergsten, Java Server Pages, SPD O’Reilly.

REFERENCE BOOKS:

1. David Flanagan, “JavaScript: The Definitive Guide, Sixth Edition”, O'Reilly Media, 2011.

2. Chris Bates , Web Programming , building internet applications, 2nd edition, Wiley Dreamtech.

3. Beginning PHP and MySQL: From Novice to Professional, Fourth Edition, Dreamtech Press, 2010.

MINI PROJECT-2


III Year /II Semester 0 1 2 2

Course Objectives :

Mini project will let the students apply the programming knowledge into a real world

situation or problem and expose the students to how programming skill will help

them develop a product.

Guidelines/Instructions :

Group of students can form as a team and the team has to submit the Mini Project


the semester.

The team has to implement the Mini Project and submit the Mini Project report in

the prescribed format at the end of the semester to the department. The Viva–Voce

shall be conducted along with respective semester lab external examinations.

Course Outcomes:


CO 1. Aquire practical knowledge within the chosen area of technology for project

development.

CO 2. Identify, analyse, formulate and handle projects with a systematic approach.

CO 3. Contribute as an individual or in a team in development of technical projects.

CO 4. Develop effective communication skills for presentation of project related

activities.

Mapping of COs to Pos:

POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 3 3 3 3 - - - 3 3 3 3

CO2 3 2 3 3 3 3 3 3 - - 3 - 3 3

CO3 - - - - 3 2 2 3 3 3 3 3 3 3

CO4 - - - - - - - 3 3 3 - 3 - -

QUANTITATIVE ABILITY



Course Objectives: To train students to critically evaluate various real life situations by resorting to

Analysis of key issues and factors. To prepare students to learn various principles involved in solving arithmetic

problems. Chapter 1 : Ratio, Proportion & Variation Ratio-Duplicate, Triplicate, Sub-Duplicate, Sub-Triplicate and Inverse Ratio-Proportion - Mean, Third and Fourth Proportionals - Rules of Proportion, Variation-Direct, Inverse and Joint variations.

Chapter 2 : Percentages Percentage-Conversion of fraction to percentage and Percentage to Fraction-percentage excess & shortness, Effect of percentage change on a number-Effect of two step change-Effect of percentage change on product.

Chapter 3 : Simple & Compound Interest Simple Interest-Effect of change in principal, Rate of interest or Time period-Interest as Multiples of principal-equal installment to repay-Compound Interest-Conversion period-Formula for EMI.

Chapter 4 : Profit, Loss &Discount Cost price, Selling price-Gain-Loss-Percentage-Relation among Cost price & selling price, Gain %, Loss %-Discount-Marked price-Use of False Scale, %Gain or % Loss on Selling Price.

Chapter 5 : Partnership Partners-Managing-sleeping – investment ratio - profit ratio - Investment for different durations.

Chapter 6 : Time & Distance Speed - Average Speed - problems on trains - Relative speed - Boats and streams – Races - Flat & Circular.

Chapter 7 : Mixtures & Alligation Ratio of Mixtures-Mean price-Rule of Alligations.

Chapter 8 : Time & Work Rate of work - Work as a single unit - No. of persons working together - No. of man days. Pipes & Cisterns: Pipe – Drain - Amount of work done-Time to fill tank.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Build a strong base in fundamentals of Arithmetic. CO 2. Illustrate the approaches and strategies to solve problems with speed and

accuracy. CO 3. Develop appropriate skills to succeed in the selection process for recruitment.


POs/COs

PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO 10

PO 11

PO 12

CO1 - - - - - - - - - - - 2

CO2 - - - - - - - - - - - 2

CO3 - - - - - - - - - - - 2

REFERENCE BOOKS: 1. Abhijit Guha, Quantitative Aptitude for Competitive Examinations, 4th ed., TMH

Publications. 2. Dinesh Khattar, The Pearson guide to Quantitative Aptitude for Competitive

Exams, 3rd ed., Pearson. 3. R.S. Aggarwal, Quantitative Aptitude, S.Chand Publications. 4. R.S. Aggarwal, Objective Arithmetic, S. Chand Publications. 5. M.Tyra, Magical book on Quicker Maths, BSC Publishing Co. Pvt. Ltd.

IV Year

I Semester

MANAGEMENT SCIENCE

Subject Code: UGMB7T0118 L T P C

IV Year / I Semester 3 0 0 3

Prerequisites: General awareness about principles of Management and insight

about Management concepts.

Course Objectives:

1. To create awareness about different Managerial concepts like Management,

Production, Marketing, Human Resource and Strategic Management.

2. To make the students equip with knowledge on techniques of PERT and CPM

in project management.

Syllabus:


Introduction to Management : Concept and importance of Management,

Functions of management, Evaluation of Management thought, Fayol’s principles of

Management, Maslow’s need hierarchy & Herzberg’s two factor theory of

Motivation, Decision making process, Designing organizational structure, Principles

of Organization, Types of organization structures.


Operations management: Principles and types of plant Layout , Work study, Statistical Quality control. Charts – R Chart, c chart, p chart, Simple problems on R, c and p charts, Materials Management: Objectives - Need for inventory control- Inventory control techniques EOQ , ABC , HML, SDE, VED and FSN analysis.


Human Resources management (HRM): Concepts of HRM,HRD & Personnel

management and industrial relations, Basic functions of HR manager ,Wage

payment plans (simple problems), Job Evaluation and Merit Rating.


Marketing Management: Functions of marketing , Marketing Mix, Marketing

strategies based on Product life cycle, Channels of distribution.


Project Management(PERT/CPM): Network analysis, Programme Evaluation

and Review Technique (PERT), Critical path method(CPM) - Identifying critical

path, Difference between PERT & CPM, Project Crashing (simple problems).


Strategic Management: Mission, Goals, objectives, policy, strategy, Elements of

corporate planning process, Environmental scanning, SWOT analysis Steps in

strategy formulation and implementation Generic strategy alternatives.

Course Outcomes:

Upon completion of this course, the students will be able to: CO1: Understand the Fundamentals of Management with specific insight as its

function and role.

CO2: Learn the Concepts of production, Management of human Resources and

Management of Marketing activities along with business environment.

CO3: Apply the problem solving skills to demonstrate logical solution to real life

problems.

CO4: Explain the business strategies to deal with the dynamic business

environment.


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

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PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 - - - - - - - - 2 - - - - -

CO2 - - - - - 2 - - - - - - - -

CO3 - - - - - - - - - - 2 - - -

CO4 - - - - - - - - - - 2 - - -

TEXT BOOKS:

1. Dr. Arya Sri, “Management Science”, TMH 2011.

2. L.M.Prasad, “Principles & Practices of Management”, Sultan chand & Sons, 2007.

REFERENCE BOOKS:

1. K.Aswathappa and K.Sridhara Bhat, “Production and Operations Management”,

Himalaya Publishing House, 2010.

2. Philip Kotler, Kevin Keller, Mairead Brady, Malcolm Goodman,Torben Hansen,

“Marketing Management” Pearson Education Limited, 05-May-2016.

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Philip+Kotler%22

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Kevin+Keller%22

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Mairead+Brady%22

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Malcolm+Goodman%22

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Torben+Hansen%22

DATA SCIENCE



Prerequisites: Basic knowledge in Probability & Statistics and Data Mining.

Course Objectives: Data Science course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. The course covers practical implementation of issues in statistical computing, concepts such as linear and logistic regression, cluster analysis, and forecasting with predictive data analytics, hypothesis testing, Data Manipulation, Exploratory Data Analysis, Ensemble of Decision trees, Collaborative filtering etc. to make students industry ready. Syllabus: UNIT I: (9 Lectures) Introduction, How to run R, R Sessions and Functions, Basic Math, Variables, Data Types, Vectors, Conclusion, Advanced Data Structures, Data Frames, Lists, Matrices, Arrays, Classes. R Programming Structures, Control Statements, Loops, - Looping Over Nonvector Sets,- If-Else, Arithmetic and Boolean Operators and values, Default Values for Argument, Return Values, Deciding Whether to explicitly call return- Returning Complex Objects, Functions are Objective, No Pointers in R, Recursion. UNIT II: (8 Lectures) Basic Data Analytics using R, R Graphical User Interfaces, Data Import and Export, Attribute and Data Types, Descriptive Statistics, Exploratory Data Analysis, Visualization Before Analysis, Dirty Data, Visualizing a Single Variable, Examining Multiple Variables, Data Exploration Versus Presentation. Discover R’s packages to do graphics and create own data visualizations. Graphics, Creating Graphs, The Workhorse of R Base Graphics, the plot() Function, Customizing Graphs, Saving Graphs to Files. Doing Math and Simulation in R, Math Function, Extended Example. UNIT III: (9 Lectures) Calculating Probability- Cumulative Sums and Products-Minima and Maxima- Calculus, Functions Fir Statistical Distribution, Sorting, Linear Algebra Operation on Vectors and Matrices, Extended Example: Vector cross Product- Extended Example: Finding Stationary Distribution of Markov Chains. Probability Distributions, Normal Distribution- Binomial Distribution- Poisson Distributions Other Distribution, Basic Statistics, Correlation and Covariance, T-Tests, ANOVA. UNIT IV: (8 Lectures) Introduction of Data Science, Exploring data, cleaning and munging, manipulating data, rescaling, data wrangling, dimensionality reduction, PCA, overfitting, under fitting, bias-variance, trade-off, feature extraction and selection, association rule mining, outlier analysis.

UNIT V: (8 Lectures) Linear Models, Simple Linear Regression, Multiple Regression, Generalized Linear Models, Logistic Regression, Poisson Regression, other Generalized Linear Models, Survival Analysis, Nonlinear Models, Splines, Decision- Random Forests. UNIT VI: (8 Lectures) Overview of Clustering, K-means, Perform K-means Analysis using R, Classification, Decision Trees, Evaluating a Decision Tree, Decision Tree in R, Bayes’ Theorem, Naïve Bayes Classifier, Smoothing, Naïve Bayes in R, and k-nearest neighborhood algorithm. Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Acquire the knowledge on exploratory data analysis, statistics, regression

models, machine learning and R language. CO 2. Analyze the real word datasets presented in different formats using R

libraries to perform exploratory data analysis. CO 3. Build testable hypotheses for the given dataset by selecting appropriate

tests. CO 4. Apply the principles of the different regression, machine-learning

techniques to predict and forecast the outcome of real-world problem. Mapping of COs to POs:

POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

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1

PSO

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CO1 3 3 3 3 - - - - 2 2 - 3 3 3

CO2 3 3 3 - - - - - 2 2 - - - -

CO3 3 3 3 - - - - - 2 2 - - - -

CO4 3 3 3 3 - - - - 2 2 - 3 3 3

TEXT BOOKS: 1. Norman Matloff, The Art of R Programming, Cengage Learning. 2. David Dietrich, Barry Heller and Beibei Yang, Data Science and Big Data

Analytics: Discovering, Analyzing, Visualizing and Presenting Data, Wiley.

REFERENCE BOOKS: 1. Rob Kabacoff, R in Action, Manning. 2. Nathan Marz and James Warren, Big Data-Principles and best practices of

scalable real-time data systems, DreamTech Press. 3. http://www.rdatamining.com/docs

MACHINE LEARNING



Prerequisites:

Basic programming skills (in Python), algorithm design and basics of probability &

statistics.

Course Objectives:

The main objective of this course is to understand the key algorithms and theory

that form the foundation of machine learning and computational intelligence, as well

as to Identify and apply the appropriate machine learning technique for

classification, pattern recognition, optimization and decision problems.

Syllabus:


Introduction : Well-posed learning problems, Designing a learning system,

Perspectives and issues in machine learning. Concept learning and the general to

specific ordering – Introduction, A concept learning task, Concept learning as

search, Find- S: finding a maximally specific hypothesis, Version spaces and the

candidate elimination algorithm, Remarks on version spaces and candidate

elimination, Inductive bias.


Linear Regression & Logistic Regression: Predicting numeric values: regression

– Finding the best fit lines with linear regression, Locally weighted linear regression,

Shrinking Coefficients, The bias / Variance tradeoff. Logistic Regression:

Classification with logistic regression and the sigmoid function, Using optimization to

find the best regression coefficients.


Decision Tree Learning: Decision tree representation, appropriate problems for

decision tree learning, basic decision tree learning algorithm, and hypothesis space

search in decision tree learning, inductive bias in decision tree learning, and issues

in decision tree learning.


Artificial Neural Networks: Introduction, Neural network representation,

Appropriate problems for neural network learning, Perceptions, Multilayer networks

and the back propagation algorithm, Remarks on the back propagation algorithm,

An illustrative example face recognition, Advanced topics in artificial neural

networks.


Support Vector Machines & Dimensionality Reduction Techniques:

Separating data with the maximum margin, finding the maximum margin, efficient

optimization with SMO algorithm, speeding up optimization with full platt SMO,

Using Kernels for more Complex data. Dimensionality Reduction techniques:

Principal Component analysis, Example.


Instance-Based Learning - Introduction, k -Nearest Neighbor Learning, Locally

Weighted Regression, Radial Basis Functions, Case-Based Reasoning, Remarks on

Lazy and Eager Learning.

Course Outcomes:


CO 1. Summarize the concepts and methods related to machine learning such as classification, regression, clustering, bias/variance, kernel functions, and optimization.

CO 2. Predict the expected outcome of the problem based on the training data by applying specific machine learning algorithm.

CO 3. Implement and compare the relevant algorithms using performance metrics. CO 4. Design and build the model using various machine learning algorithms in a

range of real-world applications.


POs/COs

PO1

PO2

PO3

PO4

PO5

PO6

PO7

PO8

PO9

PO10

PO11

PO12

PSO1

PSO2

CO1 3 - - - - - - - - - - - - 3

CO2 3 3 - - - - - - - - - - - 3

CO3 3 3 3 - - - - - - - - - - 3

CO4 3 3 3 - - - - - - - - - - 3

TEXT BOOKS:

1. Tom M. Mitchell, Machine Learning, MGH.

2. Peter Harington, Machine Learning in Action, Cengage.

3. Sebastian Raschka, Python Machine Learning, Packt Publishing.

REFERENCE BOOKS:

1. Ethem Alpaydin, Introduction to Machine Learning, PHI.

2. Drew Conway & John Miles Wine, Machine Learing for Hackers, O'Reilly Media.

BLOCKCHAIN TECHNOLOGIES

(PROFESSIONAL ELECTIVE–III)



Prerequisites: Familiarity with Information Security and Computer Networks.

Course Objectives: This course introduces the fundamentals and implementation

issues of Block Chain Technologies.

Syllabus:


Grasping Blockchain Fundamentals

Tracing Blockchain’s Origin, The shortcomings of current transaction systems,The

emergence of bitcoin,The birth of blockchain,Revolutionizing the Traditional

Business Network,Exploring a blockchain application, Recognizing the key business

benefits, Building trust with blockchain.


Taking a Look at How Blockchain Works

Why It’s Called “Blockchain”, What Makes a Blockchain Suitable for Business?,

Shared ledger, Permissions, Consensus, Smart contracts ,Identifying Participants

and Their Roles.


Propelling Business with Blockchains

Recognizing Types of Market Friction, Information frictions, Interaction frictions,

Innovation frictions, Moving Closer to Friction-Free Business Networks, Reducing

information friction, Easing interaction friction, Easing innovation friction,

Transforming Ecosystems through Increased Visibility.


Blockchain in Action: Use Cases

Financial Services,Commercial financing,Trade finance,Cross-border transactions,

Insurance, Government, Supply Chain Management, Healthcare, Electronic medical

records Healthcare payments pre-authorization, The Internet of Things. (IoT)


Hyperledger, a Linux Foundation Project

Hyperledger Vision,Hyperledger Fabric,How Can IBM Help Developers Innovate With

Blockchain? Offering an easily accessible cloud anddevelopment

platform,Individualized attention and industry expertise.


Problems with Block chain

Security and Safeguards, Protection from attackers, Hacks on exchanges, What is

stopping adoption?, Scalability problems , Network attacks to destroy bitcoin , Case

Study: Failed currencies & blockchain.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Infer and summarize the fundamentals of Block chain.

CO 2. Analyze the working of Block Chain.

CO 3. Explain how business can be easily made with Block chain.

CO 4. Interpret how Block Chain can be integrated with various current

technologies.

CO 5. Examine and test the Block chain strength in providing solutions.

CO 6. Investigate and understand the Problems with Block chain.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 - - - - - - - - - - - -

CO2 3 2 3 3 - - - - - - - - - -

CO3 3 3 3 3 - - - - - - - 3 - -

CO4 3 2 3 3 - - - - - 3 - 3 - -

CO5 3 3 3 3 2 - - - - - - 3 - 3

CO6 3 3 3 3 3 - - - - - - 3 - 3

TEXT BOOKS:

1. Manav Gupta, Blockchain for Dummies, IBM Limited Edition, John Wiley & Sons.

REFERENCE BOOKS:

1. Swan, Melanie. Blockchain: Blueprint for a new economy. O'Reilly Media, Inc.

PATTERN RECOGNITION

(PROFESSIONAL ELECTIVE-III)



Prerequisites: Familiarity with Probability & Statistics and Image Processing.

Course Objectives: The objective of the course is to make students learn the

fundamentals of pattern recognition and its relevance to classical and modern

problems. To be able to identify where, when and how pattern recognition can be

applied.

Syllabus:

UNIT I: (8 Lectures) Introduction: Is Pattern Recognition Important features, feature vectors, and classifiers, supervised, unsupervised and semi supervised learning. Bayes Decision Theory: Introduction, Bayes Decision Theory. discriminant

functions and decision surfaces. Bayesian classification for normal distributions- the

Gaussian probability density function, the Bayesian classifier for normally distributed

classes.

UNIT II: (9 Lectures) Linear & Non linear Classifiers: Introduction, linear discriminant functions and

decision hyper planes, the perceptron algorithm, Nonlinear Classifiers: introduction,

the xor problem, the two-layer perceptron -classification capabilities of the two-layer

perceptron. three-layer perceptron.

UNIT III: (8 Lectures) Feature Selection: Introduction, Preprocessing- outlier removal, data

normalization, missing data. the peaking phenomenon. class separability measures-

divergence, chernoff bound and Bhattacharya distance scatter matrices.

UNIT IV: (8 Lectures) Supervised Learning: Introduction, error-counting approach, exploiting the finite

size of the data set. a case study from medical imaging. semi supervised learning-

generative models, graph-based methods, and transductive support vector

machines.

UNIT V: (7 Lectures) Un-supervised learning and clustering: Introduction, mixture densities and

identifiability, maximum likelihood estimates, application to normal mixtures, K-

means clustering. Date description and clustering – similarity measures, criteria

function for clustering.

UNIT VI: (9 Lectures) Graph-based methods: Introduction, Hyper graph matching and Algorithms,

Parquet graphs-similarity function, Local Feature Detectors.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Summarize various learning mechanisms, understand Bayesian classification

and concept of Perceptron.

CO 2. Analyze the concept of supervised learning using a case study.

CO 3. Apply the concepts of unsupervised learning and clustering.

CO 4. Compare various graph-based methods in the implementation of pattern

recognition techniques.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 2 3 2 3 - - - 2 2 - 2 - -

CO2 3 3 2 3 2 - - - 2 2 - 2 - -

CO3 3 2 2 3 2 - - - - - - - - -

CO4 3 3 2 2 3 - - - - - - - 2 2

TEXT BOOKS:

1. Sergios Theodoridis, Konstantinos Koutroumbas, Pattern Recognition, Fourth

Edition, Elsevier.

2. Horst Bunke, Abrahmkadel, MarksLast, Applied Pattern Recognition, 2008,

Springer –Verlag Berlin Heidelberg.

REFERENCE BOOKS:

1. Devi & Murthy, Pattern Recognition, Universities Press. 2. Gose, Johnsonbaugh, Jost, Pattern Recognition and Image Analysis, PHI.

SOFT COMPUTING




Prerequisites: Basic knowledge in Mathematics and Artificial Intelligence.

Course Objectives The main objective of the course is to expose the students to

soft computing, various types of soft computing techniques and applications of soft

computing.

Syllabus:


Introduction: Neuron, Nerve Structure and Synapse, Artificial Neuron and its Model, Activation Functions.


Neural Network Architecture: Single Layer and Multilayer Feed Forward

Networks, Recurrent Networks. Various Learning Techniques, Perception and

Convergence Rule, Auto-Associative and Hetro-Associative Memory.


Backpropagation Networks Architecture: Perceptron Model, Solution, Single Layer Artificial Neural Network, Multilayer Perception Model, Back Propogation Learning Methods, Effect of Learning Rule Co-Efficient, Back Propagation Algorithm, Factors Affecting Backpropagation Training, Applications. UNIT IV: (8 Lectures)

Fuzzy Logic Introduction: Basic Concepts of Fuzzy Logic, Fuzzy Sets and Crisp Sets, Fuzzy Set Theory and Operations, Properties of Fuzzy Sets, Fuzzy and Crisp Relations, Fuzzy to Crisp Conversion.


Fuzzy Membership and Rules: Membership Functions, Interference in Fuzzy Logic, Fuzzy If-Then Rules, Fuzzy Implications and Fuzzy Algorithms, Fuzzyfications and Defuzzificataions, Fuzzy Controller, Industrial Applications.


Genetic Algorithms: Basic Concepts, Working Principle, Procedures of GA, Flow Chart of GA, Genetic Representations, (Encoding) Initialization and Selection, Genetic Operators, Mutation, Generational Cycle, Applications.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Demonstrate the nomenclature and basics of soft computing. CO 2. Explain the architecture of Neural Network.

CO 3. Identify the significance of Back propagation Networks Architecture.

CO 4. Analyze the importance of Fuzzy Logic in addressing various real time

problems.

CO 5. Evaluate the fuzziness in the terms of rules and various other parameters.

CO 6. Implement and understand the basics of genetic algorithms.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 2 3 - - - - - - - - - - -

CO2 3 3 3 - - - - - - - - - - -

CO3 3 2 3 - - - - - - - - - - -

CO4 3 3 3 3 - - - - - - - 3 - 3

CO5 3 3 3 3 3 - - - - - - 3 - 3

CO6 3 3 3 3 3 - - - - - 2 3 2 3

TEXT BOOKS:

1. S. Rajsekaran, G.A.Vijayalakshmi Pai ,Neural Networks,Fuzzy Logic and Genetic Algorithm:Synthesis and Applications, , Prentice Hall of India.

2. N.P Padhy ,Artificial Intelligence and Intelligent Systems, Oxford University Press.

REFERENCE BOOKS:

1. Simon Haykin, Neural Networks, Prentice Hall of India. 2. Timothy J.Ross ,Fuzzy Logic with Engineering Applications, McGraw-Hill. 3. Davis E.Goldberg, Genetic Algorithms: Search, Optimization and Machine

Learning, , Addison Wesley, N.Y.

CYBER SECURITY




Prerequisites: Familiarity with Computer Networks and Information Security.

Course Objectives: The course will focus on the models, tools, and the

techniques for enforcement of cyber security policies, with some emphasis on the

use of cryptography.

Syllabus:


Introduction to Computer Security: Definition, Threats to security, Government

requirements, Information Protection and Access Controls, Computer security

efforts, Standards, Computer Security mandates and legislation, Privacy

considerations, International security activity.


Cyber Crime Issues: Unauthorized Access to Computers, Computer Intrusions,

White collar Crimes, Viruses and Malicious Code, Internet Hacking and Cracking,

Virus Attacks, Pornography, Software Piracy, Intellectual Property, Mail Bombs,

Exploitation, Stalking and Obscenity in Internet, Digital laws and legislation, Law

Enforcement Roles and Responses.


Secure System Planning and administration: Introduction to the orange book,

Security policy requirements, accountability, assurance and documentation

requirements, Network Security, The Red book and Government network

evaluations.


Information security policies and procedures: Corporate policies- Tier 1, Tier

2 and Tier3 policies - process management-planning and preparation-developing

policies-asset classification policy-developing standards.


Information security: fundamentals-Employee responsibilities- information

classification Information handling- Tools of information security- Information

processing-secure program administration.


Organizational and Human Security: Adoption of Information Security

Management Standards, Human Factors in Security- Role of information security

professionals.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Specify tools and architectures to help secure computer and information

systems both proactively and reactively.

CO 2. Describe how cyber attacks against an organization can be monitored and

investigated for actionable intelligence.

CO 3. Apply skills and knowledge to create new responses to emerging cyber

security problems so that they can respond to new attacks as they evolve.

CO 4. Identify components of a modern information system and the threats that

Challenge their security.

CO 5. Identify the risks an organization faces due to cyber threats and recommend

steps to combat those risks.

POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 2 2 - - 3 2 2 - - - 3 3 3

CO2 3 2 2 2 2 3 3 3 - - - 2 - -

CO3 3 3 3 3 2 3 2 3 - - - 3 3 3

CO4 3 2 2 - 2 2 2 2 - - - 3 - -

CO5 3 2 2 3 2 3 3 2 - - - 3 - 3

TEXT BOOKS:

1. Debby Russell and Sr. G.T Gangemi, "Computer Security Basics (Paperback)”,

2ndEdition, O’ Reilly Media, 2006.

2. Nelson Phillips and Enfinger Steuart, “Computer Forensics and Investigations”,

Cengage Learning, New Delhi, 2009.

3. Thomas R. Peltier, “Information Security policies and procedures: A Practitioner’s

Reference”, 2nd Edition, Prentice Hall.

REFERENCE BOOKS:

1. Kenneth J. Knapp, “Cyber Security and Global Information Assurance: Threat

Analysis and Response Solutions”, IGI Global, 2009.

2. Thomas R Peltier, Justin Peltier and John blackley, ”Information Security

Fundamentals”, 2nd Edition, Prentice Hall.

3. Kevin Mandia, Chris Prosise, Matt Pepe, “Incident Response and Computer

Forensics “, Tata McGraw -Hill, New Delhi, 2006.

DESIGN PATTERNS




Prerequisites: Basic knowledge in Software Engineering and Object Oriented

Analysis & Design.

Course Objectives:

This course enables the learners to understand the importance of design patterns

and its principles in object oriented design. It focuses on various principles and

methods related to Identification, functionalizing and summarizing of various

patterns in executing real time problems.

Syllabus:


Introduction: What Is a Design Pattern?, Design Patterns in Smalltalk MVC,

Describing Design Patterns, The Catalogue of Design Patterns, Organizing the

Catalogue, How Design Patterns Solve Design Problems, How to Select a Design

Pattern, How to Use a Design Pattern.


Creational Patterns: Abstract Factory, Builder, Factory Method, Prototype,

Singleton, Double Checked Locking Pattern, Object Pool Pattern Management of

Objects.


Structural Patterns: Adapter, Bridge, Composite. Decorator, Façade, Flyweight,

Proxy.


Behavioral Patterns - 1: Chain of Responsibility, Command, Interpreter, Iterator,

Mediator.


Behavioral Patterns - 2: Memento, Observer, State, Strategy, Template Method,

Visitor.


A Case Study: Designing a Document Editor: Design Problems, Document

Structure, Formatting, Embellishing the User Interface, Supporting Multiple Look-

and-Feel Standards, Supporting Multiple Window Systems, User Operations Spelling

Checking and Hyphenation.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Identify the design patterns to solve object oriented design problems.

CO 2. Determine Creational and Structural Patterns for given Application.

CO 3. Evaluate Design Solutions by using Behavioral Patterns.

CO 4. Design new patterns by Analyzing and Combining existing patterns in

software design.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 - - - - - - - - - - -

CO2 3 3 3 3 3 - 1 2 - - - - - -

CO3 3 3 3 - 3 - 1 2 - - - - 2 2

CO4 3 3 3 - 3 - - 2 3 2 3 2 3 2

TEXT BOOKS:

1. Erich Gamma, Richard Helm, Ralph Johnson and John Vlissides, Design Patterns, Pearson Education.

2. Eric Freeman, Kathy Sierra, Head First Design Patterns, 1st Edition, O'Reilly Media.

3. Jason McColm Smith, Elemental design Patterns, 1st Edition, Pearson Education.

REFERENCE BOOKS:

1. Mark Grand, Pattern’s in JAVA Vol-I, Wiley DreamTech. 2. Mark Grand, Pattern’s in JAVA Vol-II, Wiley DreamTech. 3. Mark Grand, JAVA Enterprise Design Patterns Vol-III, Wiley DreamTech. 4. Alan Shalloway, James R.Trott, Design Patterns Explained, 2nd Edition, Pearson

Education.

DATA ANALYTICS (ASSOCIATE ANALYTICS – II)




Prerequisites: Familiarity with Database Management Systems and Data

Warehousing & Data Mining.

Course Objectives: This course provides an introduction to big data analytics for

all business professionals, including those with no prior analytics experience.

Students will learn how data analysts describe, predict, and inform business

decisions in the specific areas of marketing, human resources, finance, and

operations, and students will develop basic data literacy and an analytic mindset

that will help you make strategic decisions based on data.

Syllabus:

UNIT I: Maintain Healthy, Safe & Secure Working Environment

(8 Lectures)

Introduction, workplace safety, Report Accidents & Emergencies, Protect health &

safety as your work, course conclusion, assessment.

UNIT II: Provide Data/Information in Standard Formats (8 Lectures)

Introduction, Knowledge Management, Standardized reporting & compliances,

Decision Models, course conclusion, Assessment.

UNIT III: Introduction to Predictive Analytics & Linear Regression

(9 Lectures)

What and Why Analytics, Introduction to Tools and Environment, Application of

Modelling in Business, Databases & Types of data and variables, Data Modelling

Techniques, Missing imputations etc.Need for Business Modelling, Regression –

Concepts, Blue property assumptions-Least Square Estimation, Variable

Rationalization, and Model Building etc.

UNIT IV: Logistic Regression Objective Segmentation (9 Lectures)

Model Theory, Model fit Statistics, Model Conclusion, Analytics applications to

various Business Domains etc, Regression Vs Segmentation – Supervised and

Unsupervised Learning, Tree Building – Regression, Classification, Overfitting,

Pruning and complexity, Multiple Decision Trees etc.

UNIT V: Time Series Mothods/Forecasting, Feature Extraction

(9 Lectures)

Arima, Measures of Forecast Accuracy, STL approach, Extract features from

generated model as Height, Average, Energy etc and Analyze for prediction.

Develop Knowledge, Skill and Competences: Introduction to Knowledge skills

& competences, Training & Development, Learning & Development, Policies and

Record keeping, etc.

Unit VI: Working with Documents (7 Lectures)

Standard Operating Procedures for documentation and knowledge sharing, Defining

purpose and scope documents, Understanding structure of documents – case

studies,articles, white papers, technical reports, minutes of meeting etc., Style and

format, Intectual Property and Copyright, Document preparation tools – Visio,

PowerPoint, Word, Excel etc., Version Control, Accessing and updating corporate

knowledge base, Peer review and feedback.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Understand and apply the procedures in knowledge managements, reporting

& compliances and practice how to maintain healthy, safe & secure working

environment.

CO 2. Experiment with tools and environment to conduct predictive analysis and

regression on different types of databases and variables.

CO 3. Build models with statistical fit using regression, segmentation, supervised

and unsupervised learning methods for applications to various business

domains.

CO 4. Model time series analysis, feature extraction with prediction accuracy, and

develop knowledge, skill and competence towards policy making and record

keeping.

CO 5. Summarize operating procedures for documentation, copyright, IPR with case

studies.


POs/

COs

PO

1

PO

2

PO

3

PO

4

PO

5

PO

6

PO

7

PO

8

PO

9

PO

10

PO

11

PO

12

PSO

1

PSO

2

CO1 3 3 - - - 3 3 3 2 2 - - - -

CO2 3 3 3 3 3 - - - - - - 3 - 3

CO3 3 3 3 3 3 - - - - - - - - 3

CO4 3 3 3 3 3 - - - - - - - - -

CO5 3 3 3 3 - 3 - 3 - 3 - - - 3

TEXT BOOKS:

1. Tan, Steinbach and Kumar, Introduction to Data Mining, Addison Wesley. 2. M. Zaki and W. Meira, Data Mining Analysis and Concepts,

http://www.dataminingbook.info/uploads/book.pdf

REFERENCE BOOKS:

1. Jure Leskovec, Anand Rajaraman, Milliway Labs, Jeffrey D. Ullman, Mining of

Massive Datasets, Stanford Univ.

2. http://www.vistrails.org/index.php/Course:_Big_Data_Analysis.

DATA SCIENCE WITH R LAB


IV Year / I Semester 0 0 3 1.5

Prerequisites: Familiarity with R programming and Data Mining.

Course Objectives: Data Science with R labs lets students learn R programming language that is deployed for varied purposes like graphics representation, statistical analysis and reporting. With this R Programming lab students will be able to get a clear understanding of the core concepts, import data in various formats for statistical computing, data manipulation, business analytics, machine learning algorithms and data visualization. They will learn about the various functions, data structures, variables and flow of control. List of Programs:

1. Write a program to illustrate the working of Countdown function. 2. Write a program to Simulate Random Number Game. 3. Calculate the median of number using Vector. 4. Write a pogrom to compute Matrix Multiplication . 5. Write a program which simulates Filtering of Data using R. 6. Write a program which simulates Match and Sample in R. 7. Implement Linear Regression in R. 8. Write a program to write into CSV in R. 9. Write a program to Illustrate READING of .CSV FILE. 10. Write a program to Illustrate the use of cat() function with R code. 11. Write a program to Illustrate to save a plot as pdf image. 12. Perform k-means clustering algorithm. 13. Perform naïve bayes classifier algorithm. 14. Perform decision tree algorithm. 15. Perform PCA in R.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Demonstrate R language constructs and data visualization tools by applying

on various data files.

CO 2. Experiment with available pre-processing techniques in R language packages.

CO 3. Implement association, classification and clustering technique to discover

knowledge in datasets.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 3 3 - - 3 3 3 - - 3 -

CO2 3 3 3 3 3 - - 3 3 3 - 3 3 3

CO3 3 3 3 3 3 - - 3 3 3 - 3 3 3

TEXT BOOKS: 1. Robert I. Kabacoff, R in Action-Data analysis and graphics with R, 2e, Manning

Publications 2. David Dietrich, Barry Heller, and Beibei Yang, Data Science & Big Data Analytics:

Discovering, Analyzing, Visualizing and Presenting Data, EMC Education Services, John Wiley & Sons, Inc.

REFERENCE BOOKS: 1. Garrett Grolemund, Hands-On Programming with R, Orielly. 2. Paul Teetor, R Cookbook, O’Reill.

MACHINE LEARNING LAB


IV Year / I Semester 0 0 3 1.5

Prerequisites: Familiarity with Python programming.

Course Objectives: This course helps the students to implement various machine

learning techniques.


Week 1:

Introduction to numpy

1. Write a python program to check whether two random arrays A and B are

equal or not.

2. Write a python program to get the n largest values of an array.

Week 2:

Introduction to pandas

1. Load the energy data from the file ‘Energy%20Indicators.xls’

(http://unstats.un.org/unsd/environment/excel_file_tables/2013/Energy%20I

ndicators.xls), which is a list of indicators of energy supply and renewable

electricity production for the year 2013, into a DataFrame with name

‘energy’.

2. Write a python program to build the cartesian product (every combinations of

every item) for given arbitrary number of vectors.

Week 3:

Linear Algebra

1. Write a python program to get value of x for given linear equations.

2. Write a python program to find Eigen analysis for given a matrix.

Week 4:

Linear Regression

1. Write a python program to predict the age of abalone by using MNIST data

set.

Week 5:

Logistic Regression

1. Write a python program to estimate horse fatalities from collc by using

MNIST data set.

Week 6:

Decision Tree Learning

1. Write a python program to get contact lens type(MNIST data set) by using

decision tree.

Week 7:

Introduction to Tensorflow

1. Write a python program for Handwritten Digit Recognition(MNIST data set)

by using ANN.

Week 8:

Introduction to Scikit-learn

1. Write a python program for Handwritten Digit Recognition(MNIST data set)

by using KNN.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Perform experiments in Machine Learning using real-world data. CO 2. Apply preprocessing techniques on data sets using python libraries. CO 3. Design the neural network model for specific problem using both tensorflow

and scikit-learn libraries and compare their efficiency. CO 4. Interpret and present the predicted outcome of a problem after applying a

machine learning model on the training data.


POs/ COs

PO1

PO2

PO3

PO4

PO5

PO6

PO7

PO8

PO9

PO 10

PO 11

PO 12

PSO1

PSO2

CO1 3 3 3 - 3 - - 3 3 3 - - - 3

CO2 3 3 3 - 3 - - 3 3 3 - - - 3

CO3 3 3 3 - 3 - - 3 3 3 - - - 3

CO4 - 3 3 - 3 - - 3 3 3 - - - 3

TEXT BOOKS:

1. Tom M. Mitchell ,Machine Learning , MGH.

2. Peter Harington ,Machine Learning in Action, Cengage.

3. Sebastian raschka ,Python Machine Learning, Packt Publishing.

REFERENCE BOOKS:

1. Ethem Alpaydin, Introduction to Machine Learning, PHI.

2. Drew Conway & John Miles Wine ,Machine Learing for Hackers, O'Reilly Media.

IV Year II Semester

INTERNET OF THINGS

(FREE ELECTIVE-I)


IV Year / II Semester 3 0 0 3

Prerequisites: Familiarity with Microprocessors and Microcontrollers.

Course Objectives: Students will be explored to the interconnection and

integration of the physical world and the cyber space. They are also able to design

& develop IOT enabled Devices.

Syllabus:


Introduction to Internet of Things: Introduction: Definition of IoT,

Fundamental Characteristics of IoT, Design Considerations for IoT Applications.


Basic layered architecture for IoT: Device Layer, Network Layer, Service and

Application Support Layer, Application Layer, Structure of IoT, Logical design of IoT.


Key enabling Technologies: Platforms: Hardware, SoC, Sensors, Bluetooth, BT-

LE, iBeacon. Protocols: Identification and Tracking Technologies: RFID, NFC,

Zigbee and GPS Communication Technologies: Wireless Networks, WSN, 3G, LTE,

IPv6. IoT protocols: HTTP, CoAp, Websocket, MQTT, XMPP, DDS, AMQP, SDN and

NFV for IoT.


Services and attributes for IoT: Gateway, Raspberry Pi, Arduino, Cloud

Computing and IoT, Big-Data Analytics and Visualization, Dependability, Security,

Localization, Maintainability.


Internet of Things in Practice: IoT levels and Deployment templates, IoT for

Smart Cities, IoT for Agriculture, IoT for Traffic Management and Transportation, Iot

in the Home, Iot in Retail, IoT in Healthcare, IoT in Sports.


Challenges and Future Trends: Research challenges: Technical Challenges,

Standardization, Information Security and Privacy Protection, Research Trends.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Explain the fundamentals of IOT.

CO 2. Interpret the architectural layered view of the IOT.

CO 3. Analyze the basic protocols of IOT.

CO 4. Design IOT applications in various domains and able to analyze the

performance.

CO 5. Integrate IOT Applications with Embedded Platform to enhance the future.


POs/

Cos

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CO1 3 3 - - 3 - - - - - - - - -

CO2 3 3 - - 3 - - - - - - - - -

CO3 3 3 - - 3 - - - - - - - - 2

CO4 3 3 2 3 3 2 - 2 2 2 2 - - 2

CO5 3 3 3 3 3 3 2 2 3 2 3 3 - 3

TEXT BOOKS:

1. Arshadeep Bhaga, Vijay madisetti, IoT A hands on approach,University Press.

2. Ovidiu Vermesan, Peter Friess, Internet of Things – From Research and

Innovation to Market Deployment, River Publishers.

3. Ovidiu Vermesan, Peter Friess, Internet of Things – Converging Technologies for

Smart Environments and Integrated Ecosystems, River Publishers.

REFERENCE BOOKS:

1. Olivier Hersent, David Boswarthick, Omar Elloumi, The Internet of Things: Key

Applications and Protocols, Wiley.

2. Ovidiu Vermesan, Peter Friess, Building the Hyperconnected Society, River

Publishers.

HUMAN COMPUTER INTERACTION

(FREE ELECTIVE–I)



Prerequisites: Basic concepts of system analysis and design and exposure to

various user interface designs related to web and mobile.

Course Objectives: This course enables the learners to have skills towards

principles and theories influencing the human computer interaction and different

ways to select an effective style for a specific application. It focuses on concepts like

managing design processes, different user interface elements and commands,

interaction devices, quality of service, balancing function and fashion, user

documentation and online help information search, information visualization for an

effective applications design.

Syllabus:

UNIT I: (8 Lectures) Introduction: Importance of user Interface – definition, importance of good design, Benefits of good design, A brief history of Screen design. UNIT II: (9 Lectures) The graphical user interface – popularity of graphics, the concept of direct manipulation, graphical system, Characteristics, Web user – Interface popularity, characteristics- Principles of user interface. UNIT III: (9 Lectures) Design process – Human interaction with computers, importance of human characteristics human consideration, Human interaction speeds, understanding business junctions. UNIT IV: (8 Lectures) Screen Designing: Design goals – Screen planning and purpose, organizing screen elements, ordering of screen data and content – screen navigation and flow – Visually pleasing composition – amount of information – focus and emphasis – presentation information simply and meaningfully – information retrieval on web – statistical graphics – Technological consideration in interface design. UNIT V: (8 Lectures) Windows – New and Navigation schemes, selection of window, selection of devices based and screen based controls. UNIT VI: (8 Lectures) Components – text and messages, Icons and increases – Multimedia, colors, uses problems, choosing colors. Software tools – Specification methods, interface – Building Tools.

Course Outcomes:


CO 1. Interpret the basic principles of user interface & GUI design concepts. CO 2. Apply interactive design principles in real-time application development with

client and system requirements. CO 3. Classify various interface design components by using modern tools.


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CO1 3 - - - - - - - - - - 3 - -

CO2 3 - 3 - 3 3 - - 3 3 3 3 - -

CO3 3 - 3 - 3 3 - - - - - 3 - -

TEXT BOOKS:

1. Wilbert O Galitz, “The Essential Guide To User Interface Design”, Wiley DreamaTech.

2. Ben Shneidermann, “Designing The User Interface”, 3rd Edition, Pearson Education Asia.

REFERENCE BOOKS:

1. Alan Dix, Janet Fincay, Gre Goryd, Abowd, Russell Bealg, “Human Computer

Interaction”, Pearson.

2. Prece, Rogers, Sharps, “Interaction Design”, Wiley Dreamtech.

3. Soren Lauesen, “User Interface Design”, Pearson Education.

HIGH PERFORMANCE COMPUTING (FREE ELECTIVE–I)



Prerequisites: Familiarity with Computer Organization and Architecture.

Course Objectives: This course covers the design of advanced modern computing

systems. In particular, the design of modern microprocessors, characteristics of the

memory hierarchy, and issues involved in multi-threading and multi-processing.

Syllabus:


Introduction to Parallel hardware and software, need for high performance systems

and Parallel Programming, SISD, SIMD, MISD, MIMD models, Performance issues.


Processors, PThreads, Thread Creation, Passing arguments to Thread function,

Simple matrix multiplication using Pthreads, critical sections, mutexes, semaphores,

barriers and conditional variables, locks, thread safety, simple programming

assignments.


Open MP Programming: introduction, reduction clause, parallel for-loop scheduling,

atomic directive, critical sections and locks, private directive, Programming

assignments, n body solvers using openMP.


Introduction to MPI programming: MPI primitives such as MPI_Send, MPI-Recv,

MPI_Init, MPI-Finalize, etc., Application of MPI to Trepizoidal rule, Collective

Communication primitives in MPI, MPI derived datatypes, Performance evaluation of

MPI programs, Parallel sorting algorithms, Tree search solved using MPI,

Programming Assignments.


Introduction to GPU computing, Graphics pipelines, GPGPU, Data Parallelism and

CUDA C Programming, CUDA Threads Organization, Simple Matrix multiplication

using CUDA, CUDA memories.


Bench Marking and Tools for High Performance Computing Environments, Numerical

Linear Algebra Routines BLAS for Parallel Systems evaluation.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Demonstrate the need of high performance Computing systems.

CO 2. Relate Process synchronization concepts and tools for high performance

Computing systems.

CO 3. Summarize the architectural features in the GPU computing.

CO 4. Illustrate the techniques of MP and MPI programming.


POs/

COs

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1

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2

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3

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4

PO

5

PO

6

PO

7

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8

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9

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10

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12

PSO

1

PSO

2

CO1 3 3 - - - 1 - - 2 - - 2 - 3

CO2 3 3 - - 3 1 - 1 2 - - 2 - 3

CO3 3 3 3 3 3 1 2 - 2 - - 2 - 3

CO4 3 3 3 3 3 1 - - 2 - 3 2 - 3

TEXT BOOKS:

1. Peter S Pacheco ,An Introduction to Parallel Programming, Elsevier.

2. Kirk & Hwu ,Programming Massively Parallel Processors, Elsevier.

REFERENCE BOOKS:

1. Jason, Sanders, . Edward Kandrit, CUDA by example: An introduction to General

Purpose GPU Programming, Perason.

2. Shame Cook ,CUDA Programming, Elsevier.

3. Jack Dongarra, Alexey & Lastovetsky ,High Performance Heterogeneous

Computing, Wiley.

4. Michel J.Quinn ,Parallel computing theory and practice, TMH.

COMPUTER FORENSICS

(FREE ELECTIVE–I)



Prerequisites: Basic knowledge in Data Mining, Probability and Statistics.

Course Objectives: The aim of this course is to provide students with a

comprehensive overview of collecting, investigating, preserving, and presenting

evidence of cyber-crime left in digital storage devices. This course introduce topics

of forensic data examination of computers and digital storage media, understand file

system basics to locate hidden files, extract data and preserve it for analysis. Also,

students will get awareness of tools for e-discovery, Legal aspects for different types

of investigations.

Syllabus:


Introduction: Introduction to Computer Forensics, Uses of Digital Forensics-

Criminal Investigations, Civil Litigation, Intelligence, Benefits of Professional

Forensics Methodology, Phases of Computer Forensics, Locard's Exchange Principle,

Scientific Method, Organizations of Note- SWGDE, AAFS, ASCLD/LAB, NIST, ASTM,

Role of the Forensic Examiner in the Judicial System.


Evidence Collection: Why Collect Evidence? Collections Options, Obstacles, Types

of Evidence, The Rules of Evidence, Collecting Evidence-Crime Scenes and Collecting

Evidence, Documenting the Scene, Chain of Custody, Cloning, Live System versus

Dead System, Hashing, Final Report.


Duplication and Preservation of Digital Evidence: : Preserving the Digital

Crime Scene, Computer Evidence Preserving Processing Steps, Legal Aspects of

Collecting and Preserving Computer Forensic Evidence. Computer Image

Verification and Authentication: Special Needs of Evidential Authentication,

Practical Consideration.


Windows System Artifacts-Introduction, Deleted Data, Hibernation File (Hiberfile.Sys), Registry, Print Spooling, Recycle Bin, Metadata, Thumbnail Cache, Most Recently Used (MRU), Restore Points and Shadow Copy, Prefetch, Link Files. Current Computer Forensic Tools: Evaluating Computer Forensic Tool Needs, Computer Forensics Software Tools, Computer Forensics Hardware Tools, Validating and Testing Forensics Software. Computer Forensics Analysis and Validation: Validating Forensic Data, Addressing Data-Hiding Techniques, Performing Remote Acquisitions.

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Network Forensics: Network Forensics Overview, Performing Live Acquisitions,

Developing Standard Procedures for Network Forensics, Using Network Tools,

Examining the Honeynet Project. Capturing Network Traffic: Using

tcpdump/WinDump, Using Wireshark, Using SPAN Ports or Taps, Using Fiddler,

Firewalls, Decipherment of a TCP Segment, Network Forensics Evidence Generated

with Snort.


Email Investigations: Exploring the Role of E-Mail in Investigation, Exploring the

Role of Client and Server in E-Mail, Investigating E-Mail Crimes and Violations,

Understanding E-Mail Servers, Using Specialized E-Mail Forensic Tools. Cell Phone

and Mobile Device Forensics: Understanding Mobile Device Forensics,

Understanding Acquisition Procedures for Cell Phones and Mobile Devices.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Develop and implement computer forensics investigative procedures. CO 2. Conduct and evaluate the systematic collection of evidence at private-sector

incident scenes. CO 3. Discuss and analyze computer forensics findings. CO 4. Illustrate the use of computer forensics tools used in data analysis, such as

searching, absolute disk sector viewing and editing, recovery of files, password cracking, etc. CO 5. Implement and evaluate numbers of methodologies for validating and testing

computer forensics tools and evidence. CO 6. Exhibit forensics ethical behavior and comply with professional conduct

requirements.


POs/

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2

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PO

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PO

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PO

12

PSO

1

PSO

2

CO1 3 3 3 - - 3 3 3 - 3 3 3 3 3

CO2 3 2 2 2 2 3 3 3 - 2 3 3 2 2

CO3 3 3 3 3 2 3 2 3 3 - 3 3 2 3

CO4 3 2 2 - 2 2 2 2 - 3 3 3 2 2

CO5 3 2 3 3 2 3 3 2 - - 3 3 2 3

CO6 3 3 2 - - 3 3 3 3 - 2 3 3 3

TEXT BOOKS:

1. John Sammons, The Basics of Digital Forensics: The Primer for Getting Started in

Digital Forensics, Syngress Media.

2. Phillips Nelson, Steuart, Guide to Computer Forensics and Investigations, 3rd

Edition CENGAGE Learning.

3. JhonR.Vacca, Computer Forensics, Computer crime investigation, Firewall Media.

REFERENCE BOOKS:

1. Clint P. Garrison, Digital Forensics for network, Internet and Cloud Computing-A

Forensic Evidence Guide for moving Targets and Data, Syngress publications.

2. Christopher L. T. Brown, Computer Evidence: Collection and Preservation, 2nd

Edition, Cengage Learning.

3. Keith J. Jones, Richard Bejtlich, Curtis W. Rose, Real Digital Forensics, Addison-

Wesley Pearson Education.

4. Tony Sammes and Brian Jenkinson, Forensic Compiling, A Practitioner’s Guide,

Springer International edition.

5. Christopher L.T. Brown, Computer Evidence Collection & Presentation, Firewall

Media.

6. Robert M.Slade, Software Forensics Collecting Evidence from the Scene of a

Digital Crime, TMH, Wiley India Edition.

DEEP LEARNING

(FREE ELECTIVE–I)



Prerequisites: Familiarity with Probability & Statistics, Design and Analysis of

Algorithms.

Course Objectives: The objective of the course is to provide exposure to these

advances and facilitate in depth discussions on deep learning.

Syllabus:


Machine Learning Basics

Learning Algorithms, Capacity, Over fitting and Under fitting , Hyper parameters and

Validation Sets , Estimators, Bias and Variance , Maximum Likelihood ,Estimation

Bayesian Statistics.

Supervised Learning Algorithms ,Unsupervised Learning Algorithms , Stochastic

Gradient Descent , Building a Machine Learning Algorithm , Challenges Motivating

Deep Learning.


Deep Feedforward Networks

Example: Learning XOR, Gradient-Based Learning, Hidden Units, Architecture

Design, Back-Propagation and Other Differentiation Algorithms.

UNIT- III: (8 Lectures)

Regularization for Deep Learning

Parameter Norm Penalties, Norm Penalties as Constrained Optimization,

Regularization and Under-Constrained Problems, Dataset Augmentation, Noise

Robustness, Semi-Supervised Learning, Multitask Learning.


Optimization for Training Deep Models

How Learning Differs from Pure Optimization, Challenges in Neural Network

Optimization, Basic Algorithms, Parameter Initialization Strategies, Algorithms with

Adaptive Learning Rates, Approximate Second-Order Methods, Optimization

Strategies and Meta-Algorithms.


Convolutional Networks

The Convolution Operation, Motivation, Pooling, Convolution and Pooling as an

Infinitely Strong Prior, Efficient Convolution Algorithms, Random or Unsupervised

Features, The Neuroscientific Basis for Convolutional Networks.


Sequence Modeling: Recurrent and Recursive Nets

Unfolding Computational Graphs, Recurrent Neural Networks, Bidirectional RNNs,

Deep Recurrent Networks, Recursive Neural Networks, The Challenge of Long-Term

Dependencies, Optimization for Long-Term Dependencies, Explicit Memory.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Demonstrate the basics of Machine Learning.

CO 2. Analyze the importance of deep feed forward networks.

CO 3. Summarize the significance of regularization for Deep Learning.

CO 4. Implement optimization in DL.

CO 5. Perceive the importance of Convolutional Networks and its significance.

CO 6. Illustrate the knowledge on Sequence Modeling.


POs/

COs

PO

1

PO

2

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4

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1

PSO

2

CO1 3 3 3 - - - - - - - - - - -

CO2 3 3 3 2 - - - - - - - - - -

CO3 3 3 3 - - - - - - - - - - -

CO4 3 3 3 2 3 - - - - 3 - 3 - 3

CO5 3 3 3 3 - - - 3 - - - 3 - 3

CO6 3 3 3 3 - - - - - - - - - -

TEXT BOOKS:

1. Goodfellow, I., Bengio, Y., Courville, A., & Bengio, Y. Deep learning,Vol. 1. Cambridge: MIT press.

2. François Duval , Deep Learning: Deep Learning for Beginners. Practical Guide with Python and Tensorflow, Data Sciences Publishing.

REFERENCE BOOKS: 1. Sebastian Raschka, Vahid Mirjalili,Python Machine Learning: Machine. Learning

and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition, Packt

Publishing.

SOCIAL NETWORKS AND SEMANTIC WEB

(FREE ELECTIVE–II)



Prerequisites: Familiarity with Computer Networks and Data Mining.

Course Objectives: The objective of this course is to make understand the

students about the context based semantic integration of multiple Web resources

and expose semantically enriched social data to the public domain. In order to turn

these objectives into reality, the students will be taught with concepts such as

knowledge representation, management, extraction, integration and analysis, to

address and fix the challenging issues in social networking and semantic web.

Syllabus:


The Semantic web: Limitations of the current Web, The semantic solution,

Development of the Semantic Web, The emergence of the social web.


Social Network Analysis: What is network analysis?, Development of Social Network

Analysis, Key concepts and measures in network analysis. Electronic sources for

network analysis: Electronic discussion networks, Blogs and online communities,

Web-based networks.


Knowledge Representation on the Semantic Web: Ontologies and their role in the

Semantic Web, Ontology languages for the semantic Web.


Modeling and Aggregating Social Network Data: State of the art in network data

representation, Ontological representation of Social individuals, Ontological

representation of social relationships, Aggregating and reasoning with social

network data.


Developing social semantic applications: Building Semantic Web applications with

social network features, Flink- the social networks of the Semantic Web community,

Open academia: distributed, semantic-based publication management.


Evaluation of Web-Based Social Network Extraction: Differences between survey

methods and electronic data extraction, context of the empirical study, Data

collection, Preparing the data, Optimizing goodness of fit, Comparison across

methods and networks, Predicting the goodness of fit, Evaluation through analysis.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Demonstrate key concepts of semantic web and revolutionize the WWW. CO 2. Build knowledge base for semantic web using ontology engineering and

develop social semantic applications. CO 3. Illustrate social network analysis and model social network data.

CO 4. Analyze social network data to predict goodness of fit.


POs/

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CO1 3 3 3 3 - - - - - - - - - -

CO2 3 3 - - - - - - - - - 3 - 3

CO3 3 3 3 - - - - - - - - 3 - 3

CO4 3 3 3 3 - - - - - - - 3 - 3

TEXT BOOKS:

1. Peter Mika, Social Networks and the Semantic Web,Springer,2007.

2. J.Davies,Rudi Studer, and Paul Warren, Semantic Web Technologies,Trends and

Research in Ontology Based Systems, John Wiley & Sons.

REFERENCE BOOKS:

1. Liyang Lu Chapman and Hall, Semantic Web and Semantic Web Services, CRC

Publishers. (Taylor & Francis Group)

2. Heiner Stuckenschmidt and Frank Van Harmelen, Information Sharing on the

semantic Web, Springer Publications.

E-COMMERCE




Prerequisites: Basic concepts of business approach, marketing, project

management, computer architecture, computer algorithms and online business

transactional process.

Course Objectives:

This course enables the learners to have exposure towards modern e-business and

e-commerce systems in the present era. It focuses on various principles, challenges

and implementation processes related to electronic payment systems, inter-

organizational commerce, corporate digital library, consumer search and resource

discovery, and multimedia. Learners will get exposure to various real-time practices

and approaches of the e-commerce systems through this course.

Syllabus:


Electronic Commerce: Frame work, anatomy of E-Commerce applications, E-

Commerce Consumer applications, E-Commerce organization applications,

Consumer Oriented Electronic commerce, Mercantile Process models.


Electronic Payment Systems: Smart Cards, Credit Cards, Risks in Electronic

Payment systems.


Inter Organizational Commerce: EDI, EDI Implementation, Value added

networks, Intra Organizational Commerce - work Flow, Automation Customization

and internal Commerce, Supply chain Management.


Corporate Digital Library: Document Library, digital Document types, corporate Data Warehouses, Advertising and Marketing - Information based marketing, Advertising on Internet, on-line marketing.


Consumer Search and Resource Discovery: Information search and Retrieval,

Commerce Catalogues, Information, Filtering.


Multimedia - key multimedia concepts, Digital Video and electronic Commerce,

Desktop video processings, Desktop video conferencing.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Interpret the basic principles of e-commerce systems and its applications

from different perspectives. CO 2. Classify different types of electronic payment systems and inter-

organizational commerce. CO 3. Make use of technology trends, consumer search and resource discovery to

manage e-commerce. CO 4. Interpret different multimedia concepts applicable in e-business. Mapping of COs to POs:

POs/

COs

PO

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2

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CO1 3 - - - 2 - - - - - - 2 - -

CO2 3 - - - 2 - - - 2 2 - 2 - -

CO3 2 - 2 - 3 2 - - 2 2 - 2 - -

CO4 2 - 2 - 2 2 - - - - - 2 - -

TEXT BOOKS:

1. Kalakata and Whinston, Frontiers of electronic commerce , Pearson.

REFERENCE BOOKS:

1. Hendry Chan, Raymond Lee, Tharam Dillon and Ellizabeth Chang, E-Commerce Fundamentals and Applications, John Wiley.

2. S.Jaiswal, E-Commerce, Galgotia. 3. Efrain Turbon, Jae Lee, David King, H.Michael Chang, E-Commerce, Pearson. 4. Gary P.Schneider , Electronic Commerce, Thomson.

MOBILE APPLICATION DEVELOPMENT




Prerequisites: Familiarity with Computer Networks, Operating Systems and

Database Management Systems.

Course Objectives: The objective of this course is to understand how android

applications work, their life cycle, manifest, intents, and using external resources. To

design and develop useful android applications with compelling user interfaces by

using, extending and creating your own layouts and views and using menus. To

explain the differences between android and other mobile development

environments to build android apps.

Syllabus: UNIT I: (9 Lectures) Mobile Communications - Overview: Wireless transmission, voice and data communication standards – 1G/2G/3G/4G, WPAN, WLAN, applications, limitations, mobile computing architecture, overview on mobile devices and systems. GSM: services, system architecture, radio interface, localization, call handling, handover, security, GPRS, EDGE. UNIT II: (7 Lectures) Introduction to Android- Overview of Android, Android Architecture, Exploring the designer,Adding Components, Applying behaviors, Android- SDK, Emulators – What is an Emulator/Android AVD, Android Emulation – Creation and set up, First Android Application. UNIT III: (9 Lectures) Android Activities and GUI Design Concepts – Enabling buttons, Reading Text Input, Inserting images, painting canvas, picking list items, checking boxes, storing data, Intent, Activity, Activity Lifecycle and Manifest, Creating Application and new Activities, Activity and implicit intents. Controlling Progress- Composing Programs, Defining variables, performing operations, branching flow, providing alternatives, Notifying messages, Looping Concepts. UNIT IV: (8 Lectures) Advanced UI Programming- Input Controls, Alerts and Pickers, using an option with Menu and Radio buttons, using the App bar and Tabs for Navigation, Drawables, Styles and themes, Material Design: Lists, Cards and Colors. UNIT V: (9 Lectures) Working in the background- Background tasks- create an AsyncTask, connect to the AsyncTask and AsyncTaskLoader, Broadcast receivers, Triggering, Scheduling and Optimizing Background Tasks.

UNIT VI: (8 Lectures) Toast, Menu, Dialog, List and Adapter- Menu: Basics, Custom v/s System Menus, Create and Use Handset menu Button (Hardware), Dialog : Creating and Altering Dialogs, Basic operation of SQLite Database, Android Application Priorities. Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Demonstrate knowledge of different voice and data communication

standards.

CO 2. Outline the android architecture.

CO 3. Identify the various features and the processes to develop the android

application.

CO 4. Design and develop the android applications by considering the legal and

Security issues.


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CO4 3 3 3 3 3 2 - 2 - - - - 3 -

TEXT BOOKS:

1. Raj Kamal, Mobile Computing, Second Edition, Oxford press. 2. Mike Mcgrath, Building Android Apps in easy steps, McGraw-Hill Education.

REFERENCE BOOKS:

1. Reto Meier, Professional Android 2 Application Development, Wiley India Pvt Ltd.

2. Mark L Murphy, Beginning Android, Wiley India Pvt Ltd.

3. Android Developer Fundamental Course, Practical Workbook, developed by

Google Developer Training Team.

4. https://developer.android.com/guide/platform/index.html.

SCRIPTING LANGUAGES




Prerequisites: Familiarity with programming language constructs of Java, HTML

and JavaScript.

Course Objectives: This course demonstrates an in depth understanding of the

tools and the scripting languages necessary for design and development of

applications.

Syllabus:


Introduction to Scripting and PERL: Scripts and Programs, Origin of Scripting,

Scripting Today, Characteristics of Scripting Languages, Uses of Scripting

Languages, Web Scripting and the Universe of Scripting Languages. PERL- Names

and Values, Variables, Scalar Expressions, Control Structures, Arrays, List, Hashes,

Strings, Pattern and Regular Expressions, Subroutines.


Advanced PERL: Finer Points of Looping, Pack and Unpack, File System, Eval,

Data Structures, Packages, Modules, Objects, Interfacing to the Operating System,

Creating Internet Ware Applications, Dirty Hands Internet Programming, Security

Issues.


BootStrap: The Framework, BootStrap Grid, Components: Glyphicons, Button

Groups, NavBar, Pagination, BreadCrumb, Thumbnail.

jQuery- Introduction, Syntax, Selectors, Events, Jquery CSS Classes, Traversing.


Advanced JavaScript: Browser Management and Media Management, Classes,

Constructors, Object-Oriented Techniques in JavaScript, Object Constructor and

Prototyping , Sub Classes and Super Classes and JSON.


TCL: TCL Structure, Syntax, Variables and Data in TCL, Control Flow, Data

Structures, Input/Output, Procedures, Strings, Patterns, Files, Advance TCL-Eval,

Source, Exec and Uplevel Commands, Namespaces, Trapping Errors, Event Driven

Programs, Making Applications Internet Aware, Nuts and Bolts Internet

Programming, Security Issues, C Interface. Tk-Visual Tool Kits, Fundamental

Concepts of Tk, Tk By Example, Events and Binding , Perl-Tk.


AngularJS: Introduction, MVC Architecture, Simple Application, Directives,

Expressions, Controllers, Filters, Tables, HTML DOM, Modules, Forms, Events, Input,

Validation, Http, Includes, Views, Scopes, Services and Custom Directives.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Analyze requirements of software systems for the purpose of determining the

suitability of implementing scripts in Perl.

CO 2. Build Responsive Web Applications using Bootstrap and jQuery.

CO 3. Experiment with JavaScript to construct dynamic applications and JSON to

upload data to a back-end web server.

CO 4. Explain fundamental concepts and various scripting constructs of TCL/TK

and run scripts using TCL/TK.

CO 5. Develop an Angular JS application from scratch.


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CO5 3 3 3 - 3 - - - - - - - 3 -

TEXT BOOKS:

1. David Barron, The World of Scripting Languages, Wiley Publications.

REFERENCE BOOKS:

1. Thomas A Powell, Fritz Schneider, JavaScript: The Complete Reference, Third

Edition, TataMcGraw Hill.

2. Riwanto Megosinarso, Step By Step Bootstrap 3: A Quick Guide to Responsive

Web Development Using Bootstrap.

3. Learning AngularJS: A Guide to AngularJS Development 1st Edition, Kindle

Edition.

INNOVATION AND NEW PRODUCT DEVELOPMENT




Prerequisites: Basic concepts of various products and their models, problem-

solving skills, critical thinking and business approach.

Course Objectives:

The objective of this course is to introduce a new product development approach to

learners. It includes concepts like innovation management, fuzzy front-end of

innovation, product design, project management development and launching.

Learners will get exposure of exhibiting their creativity in terms of a innovative

product development in a structured process through this course.

Syllabus:


Introduction to New Product Development (NPD): Creativity, Innovation and

Invention - differences; Creativity types; Innovation types - Jugaad Innovation,

Social Innovation, Sustaining Innovation, Disruptive Innovation, Open Innovation.


Innovation Management: Causes of failure in NPD; Structured process of

innovation; Stage-GateTM process of Innovation - 5 stages and 4 gates model -

Opportunity Identification stage, Concept generation stage, Concept Evaluation

stage, Development stage and Commercialization stage.


Fuzzy Front-End of Innovation: Opportunity Identification - Internal and

External sources - Market Opportunity Analysis (MOA); Concept Generation - Brain

Storming, Problem Analysis, Scenario Analysis, Convergent and Divergent Thinking.


Product Design: Usability and User experience design; Product Architecture;

Industrial Design; Design for Manufacturing. Concept Evaluation: Estimating

revenues for the innovation using Sales Forecasting ATAR model, Concept Testing.


Project Management: Triple Constraint, Work Breakdown Structure, Gantt chart

and Risk Management; Typical metrics used in NPD.


Development and Launch: Manufacturing planning for pilot production; Sales &

Service planning.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Interpret the basic principles & types of innovation in new product

development.

CO 2. Apply innovation process management with opportunity identification and

concept generation.

CO 3. Analyze innovative product design and study it’s working.

CO 4. Apply project management strategies in new product development,

production and its launch.


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TEXT BOOKS:

1. Anthony Di Benedetto and Merle Crawford, New Products Management, Tata

McGraw Hill.

2. Clayton Christensen, Innovators Dilemma, Harper Collins Publishers.

REFERENCE BOOKS:

1. Karl T Ulrich, Steven D Eppinger and Anita Goyal, Product Design &

Development, Tata McGraw Hill.

2. List of web sites suggested to enrich student's learning on NPD:

a. http://www.pdma.org

b. http://www.ennovient.com (Read FREE online courses on Creativity and

Innovation)

INFORMATION SECURITY MANAGEMENT (SECURITY ANALYST – I)




Prerequisites: Familiarity with Computer Networks.

Course Objectives: The Students learn different types of threats and attacks, data

leakage, prevent them by applying policies, roles and responsibilities of information

security, in addition to that security audits, mechanisms for auditing, generating of

audit reports and post audit actions to be taken, and social engineering.

Syllabus:

UNIT I: Information Security Management (8 Lectures) Information Security Overview, Threats and Attack Vectors, Types of Attacks, Common Vulnerabilities and Exposures (CVE), Security Attacks, Computer Security Concerns, Information Security Measures etc., Key Elements of Networks, Logical

Elements of Network, Critical Information Characteristics, Information States.

UNIT II: Data Leakage (8 Lectures) What is Data Leakage and statistics, Data Leakage Threats, Reducing the Risk of Data Loss, Key Performance Indicators (KPI), and Database Security.

UNIT III: Information Security Policies, Procedures and Audits (7 Lectures)

Information Security Policies necessity key elements & characteristics, Security Policy Implementation, Configuration, Security Standards-Guidelines & Frameworks. Security Roles & Responsibilities, Accountability, Roles and Responsibilities of Information Security Management, team-responding to emergency situation-risk

analysis process.

UNIT IV: Information Security Performance Metrics and Audit (9 Lectures)

Security Metrics and Reporting, Common Issues and Variances of Performance Metrics, Introduction to Security Audit, Servers and Storage devices, Infrastructure and Networks, Communication Routes, Information Security Methodologies (Black-box, White-box, Grey-box), Phases of Information Security Audit and Strategies,

Ethics of an Information Security Auditor.

UNIT V: Information Security Audit Tasks, Reports and Post Auditing Actions (8 Lectures) Pre-audit checklist, Information Gathering, Vulnerability Analysis, External Security Audit, Internal Network Security Audit, Firewall Security Audit, IDS Security Auditing, Social Engineering Security Auditing, Web Application Security Auditing, Information Security Audit Deliverables & Writing Report, Result Analysis, Post Auditing Actions, Report Retention.

UNIT VI: Vulnerability Management (10 Lectures) Information Security Vulnerabilities – Threats and Vulnerabilities, Human-based Social Engineering, Computer-based Social Engineering, Social Media Countermeasures, Vulnerability Management – Vulnerability Scanning, Testing,

Threat management, Remediation etc.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Identify and analyze the types of threats and vulnerabilities, security policies

and data leak.

CO 2. Critically evaluate security audits methodologies and post audit actions to be

taken.

CO 3. Analyze and identify the threats and vulnerabilities of the system at network

and web application levels.

CO 4. Classify protection mechanisms for different types of social engineering.

CO 5. Protect the website from attacks by using vulnerability management.


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CO4 3 3 3 3 - - - - - - - - -

CO5 2 3 3 2 - - - - - - - 2 - -

CO6 2 3 3 2 - - - - - - - 2 - -

TEXT BOOKS:

1. Michael E.Whitman and Herbert J.Mattord, Management of Information Security ,

2nd edition from course Technology.

2. A Vladimirov, K.Gavrilenko, and A.Michajlowski, Assessing Information Security

(strategies, tactics, logic and framework) , BPB publications.

REFERENCE BOOKS:

1. Peter Szor, “The Art of Computer Virus Research and Defense.” Addison-Wesley

Professional, 2005.

2. Richard O'Hanley, James S. Tiller, Information Security Management Handbook,

Sixth Edition, CRC Press.

3. Harold F. Tipton, Micki Krause Nozaki, Information Security Management

Handbook, Sixth Edition, CRC Press.

WEB SERVICES

(FREE ELECTIVE–III)



Prerequisites: The student should have knowledge in Java programming, Software

architecture and design.

Course Objectives: This course is concerned with the evolution, emergence, design, implementation and deployment of web services. The course covers theory with an emphasis on SOAP based web services and associated standards such as XML, WSDL and UDDI. The study of SOAP based Web Services is complemented by coverage of REST based Web Services. Syllabus: UNIT I: (8 Lectures) Evolution and Emergence of Web Services: Evolution of distributed computing, core distributed computing technologies- Client/server, COBRA, JAVA, RMI, Microsoft DCOM, MOM, challenges in distributed computing, role of J2EE and XML in distributed computing, Common characteristics of contemporary SOA, Emergence of web services and Service Oriented Architecture(SOA). Introduction to Web Services: The definition of web services, How a Web Service Works , Basic operational model of web services, Tools and technologies enabling web services, Benefits and challenges of using web services. UNIT II: (7 Lectures) Web Services Architecture: Web Services Architecture and its characteristics, Core building blocks of web services, Standards and technologies available for implementing web services, Web services communication models, Basic steps of implementing web services. Describing Web Services: WSDL- WSDL in the world of Web Services, Web Services life cycle, anatomy of WSDL definition document, WSDL bindings, WSDN tools, limitation of WSDL, Introduction to RESTful WS. UNIT III: (8 Lectures) Core Fundamentals of SOAP: SOAP message structure, SOAP encoding, SOAP message exchange models, SOAP communication and messaging, SOAP security. Developing Web Services using SOAP: Building SOAP Web Services, developing SOAP Web Services using java and Axis, limitations of SOAP, Advanced messaging. UNIT IV: (9 Lectures) Discovering Web Services: Service discovery, role of services discovery in a SOA, Service discovery mechanisms, UDDI- UDDI Registries, uses of UDDI Registry, Programming with UDDI, UDDI data structures, Publishing API, publishing, Searching and deleting information in a UDDI Registry, Limitations of UDDI. UNIT V: (8 Lectures) Web Services Interoperability: Means of ensuring interoperability, Overview of .NET, creating an .NTE client for an Axis web service, creating java client for a web service, Challenges in web services interoperability. Web Services Security: XML

security frame work, goals of cryptography, hash cipher, symmetric cipher, asymmetric cipher, XML encryption, digital signature, digital certificate, XML encryption, SAML, structure. UNIT VI: (8 Lectures) Overview of Service Oriented Architecture: SOA concepts, key service characteristics, Technical Benefits of SOA. SOA and Web Services: Web services Platform, service–level data models, discovery, Security and interaction patterns, Atomic and composite services, Service-level communication and alternative transports. Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Critically evaluate different architectural alternatives, techniques and

methodologies for composing Web services.

CO 2. Analyze the Core Fundamentals of SOAP for developing web service Communication model.

CO 3. Design web service by Understand UDDI registry. CO 4. Discover the web services interoperability along with web services security. CO 5. Infer the knowledge of SOA concepts and characteristics its technical benefits

and the importance of SOA and web services in solving business problems.


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TEXT BOOKS:

1. R.Nagappan, R.Skoczylas, R.P.Sriganesh, Developing java web services,Wiley India.

2. Eric Newcomer and Greg Lomow, Understanding SOA with web services, Pearson Edition.

3. James McGovern, Sameer Tyagi, Michael Stevens Sunil Mathew, Java web service architecture, Morgan Kaufmann Publishers.

REFERENCE BOOKS:

1. S.Graham and others, Building web services with java, 2nd Edition, Pearson Edition.

2. D.A.Chappell and T.Jewell, Java web services, O’Reilly. 3. Richard Monson-Haefel, J2EE web services, Pearson Education. 4. G.Alonso, F.Casati and others, Web services, Springer-2005. 5. S.Chatterjee, J.Webber, Developing enterprise web services, Pearson

Education. 6. F.P.Coyle, XML, web services and data revolution, Pearson Education.

VIRTUAL REALITY




Prerequisites: Familiarity with Computer Graphics and Pattern Recognition.

Course Objectives: This course introduces virtual reality, emphasizing basic

applications in education and other fields. Students can select special projects

according to their interests, and build a virtual environment.

Syllabus:


Introduction: The three I’s of virtual reality, commercial VR technology and the

five components of a VR system.


Input Devices: (Trackers, Navigation and Gesture Interfaces): Three- dimensional

position trackers, navigation and manipulation, interfaces and gesture interfaces.

Output Devices: Graphics displays, sound displays and haptic feedback.


Modeling: Geometric modeling, kinematics modeling, physical modeling, behavior

modeling, model management.


Human Factors: Methodology and terminology, user performance studies, VR

health and safety issues.


Applications: Medical applications, military applications, robotics applications.


VR Programming-I: Introduction JAVA 3D, loading and manipulating external

models, using a lathe to make shapes. VR Programming-II: 3D Sprites, animated

3D sprites, particle systems.

Course Outcomes: Upon completion of this course, the students will be able to: CO 1. Illustrate the fundamental techniques, processes used in virtual reality.

CO 2. Identify the required input/output devices and human factors for developing

VR applications.

CO 3. Analyse various modeling techniques in Virtual reality and its management for

different application domains.

CO 4. Demonstrate various applications of VR environment through VR

Programming.


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TEXT BOOKS: 1. Gregory C. Burdea & Philippe Coiffet, Virtual Reality Technology, Second

Edition, John Wiley & Sons Inc. 2. Andrew Davison, Killer Game Programming in Java, Oreilly-SPD.

REFERENCE BOOKS:

1. William R.Sherman, Alan Craig, Understanding Virtual Reality, interface,

Application and Design, Elsevier (Morgan Kaufmann).

2. Bill Fleming, 3D Modeling and surfacing, Elsevier (Morgan Kauffman).

MOBILE ADHOC AND SENSOR NETWORKS

(FREE ELECTIVE-III)




Course Objectives: Upon completion of this course, students will be able to know

the characteristics of adhoc and sensor networks, study various MAC and routing

protocols, and provide security to MANET and WSN.

Syllabus: UNIT I: (8 Lectures) Introduction: Fundamentals of Wireless Communication Technology, The Electromagnetic Spectrum, Radio propagation Mechanisms, Characteristics of the Wireless Channel, mobile adhoc networks (MANETs) and wireless sensor networks (WSNs) :concepts and architectures, Applications of adhoc and Sensor networks. Design Challenges in adhoc and Sensor Networks. UNIT II: (7 Lectures) MAC Protocols for Adhoc Wireless Networks: Issues in designing a MAC Protocol, Classification of MAC Protocols, Contention based protocols, Contention based protocols with Reservation Mechanisms, Contention based protocols with Scheduling Mechanisms, Multichannel MAC Protocol. UNIT III: (9 Lectures) Routing Protocols and Transport Layer in Ad-hoc Wireless Networks: Issues in designing a routing and Transport Layer protocol for adhoc networks, proactive routing, reactive routing (on-demand), hybrid routing, Classification of Transport Layer solutions, TCP over Adhoc wireless Networks. UNIT IV: (9 Lectures) Wireless Sensor Networks (WSNS) and MAC Protocols: hardware and software components of a sensor node, WSN Network architecture, data dissemination, data gathering, MAC layer protocols: self-organizing, Hybrid TDMA based MAC- IEEE 802.15.4. UNIT V: (8 Lectures) WSN Routing, Localization and WSN QOS: Issues in WSN routing, LEACH, CBRP, Localization-Based Routing, QOS in WSN. UNIT VI: (8 Lectures) Security in MANETS and WSNS: Security issues in mobile adhoc networks (MANETs), Key management mechanisms in MANETs, Security issues in wireless sensor networks (WSNs), Key management mechanisms in WSNs.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Distinguish the various concepts and architectures of adhoc networks and

the analyze the challenges at various layers and applications. CO 2. Summarize the protocols used at the MAC layer and develop MAC and routing

protocols for sensor and mobile networks. CO 3. Outline various information dissemination protocols for sensor and mobile

Networks. CO 4. Describe the principles of wireless sensor networks and mobile adhoc

and their impact on protocol design. CO 5. Illustrate the various mechanisms needed to address the issue of the security

in adhoc networks.

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CO5 3 2 2 3 2 3 3 2 - - - 3 3 3

TEXT BOOKS: 1. C. Siva Ram Murthy, and B. S. Manoj, AdHoc Wireless Networks: Architectures

and Protocols, Prentice Hall Professional Technical Reference, 2008. 2. Carlos De Morais Cordeiro, Dharma Prakash Agrawal, AdHoc & Sensor Networks:

Theory and Applications, World Scientific Publishing Company, 2006. REFERENCE BOOKS: 1. Feng Zhao and Leonides Guibas,Wireless Sensor Networks, Elsevier Publication

– 2002. 2. Holger Karl and Andreas Willig, Protocols and Architectures for Wireless Sensor

Networks, John Wiley, 2005. 3. Kazem Sohraby, Daniel Minoli, & Taieb Znati, Wireless Sensor Networks-

Technology, Protocols, and Applications, John Wiley, 2007.

ETHICAL HACKING




Prerequisites: Familiarity with Computer Networks and Information Security.

Course Objectives: This course introduces the concepts of Ethical Hacking and

gives the students the opportunity to learn about different tools and techniques in

hacking and security. This makes students to understand how perimeter defenses

work, escalate privileges and lead them to know about scanning and attacking of

networks. Students will also learn about Intrusion Detection, Policy Creation, Social

Engineering, DDoS Attacks, Buffer Overflows and Virus Creation.

Syllabus:

UNIT I: Introduction (9 Lectures) Hacking (Effects, Types, Purpose, advantages and disadvantages), Types of Hackers, Types of Cybercrimes, Ethical Hacking, Types of Data Stolen from the Organizations and its protection, Elements of Information Security (Confidentiality, Integrity, Availability, Authentication, Non – repudiation and Access control), Information Security Challenges, Penetration Testing (Objectives, Types, preliminary knowledge of Process), Role of Security Penetration Tester, Benefits of a Penetration Testing Methodology, Penetration Testing Methodology, Networking and Computer Attacks and its protection. UNIT II: Malicious Software (7 Lectures) Protection and detection of malicious software (Virus, Macro virus, Worms, Trojan programs, Spyware & Adware), Protection against from all Malware, Intruder Attacks on Networks and Computers (including Proxy and Packet Filtering, Denial of Service, Sniffer.), Addressing Physical Security, Key Loggers and its types, Back Doors. UNIT III: Pre – Attack Phase (9 Lectures) Foot Printing: Web Tools for Foot Printing (Purpose, Types, Techniques), Conducting Competitive Intelligence and Techniques, Google Hacking, Scanning (Types and Methodologies), Steps of Scanning, Types of port scanning, Scanning Tools: NMAP, Angry IP Scanner, Advanced IP Scanner, Types of Pings, Enumeration and its different tools. Social Engineering: Shoulder Surfing, Dumpster Driving, Piggybacking. UNIT IV: Data Security (8 Lectures) Physical Security - Attacks and Protection, Steganography – Methods, Attacks and Measures, Cryptography – Methods and Types of Attacks, Wireless Hacking, Windows Hacking, Linux Hacking.

UNIT V: Network Protection System (9 Lectures) Routers, Firewalls & Honeypots, Web Filtering, Vulnerability, Penetration, Testing, Session Hijacking, Web Servers, SQL Injection, Cross Site Scripting, Exploit Writing, Buffer Overflow, Reverse Engineering, E-mail Hacking, Bluetooth Hacking, Mobile Phone Hacking. UNIT VI: Ethical Hacking Laws and Tests (8 Lectures) Legal, Professional and Ethical Issues, Ethical Responsibilities, Professional Integrity, Host Reconnaissance, Session Hijacking, Hacking Web servers, Databases, Password Cracking, Methodical Penetration Testing.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Interpret several types of hacking, elements and challenges in information

security, penetration testing methodology for data protection.

CO 2. Learn techniques to detect and protect networks and computers from

malicious software’s by using Foot Printing and Scanning Tools.

CO 3. Summarize data protection techniques and network protection systems.

CO 4. Choose relevant legal and ethical hacking laws to apply on Hackers and

Intruders.


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TEXT BOOKS:

1. Michael T. Simpson, Kent Backman, James E Corley, Hand-On Ethical

Hacking and Network Defense, Second Edition, CENGAGE Learning.

REFERENCE BOOKS:

1. Manthandesai, Basics of Ethical hacking, Hacking for beginners, Hacking

Tech.

2. Patrick Engebretson, The Basics of Hacking and Penetration Testing

Ethical Hacking and Penetration Testing Made Easy, Syngress –Elsevier.

INFORMATION RETRIEVAL SYSTEMS




Prerequisites: Basic concepts of Database Management Systems, Data Mining

and Web.

Course Objectives:

The course focuses on learning the difference between Information Retrieval and

Data Base Management Systems. The course focuses on the basic concepts of

Information Retrieval systems and its working principles. It focuses concepts of

cataloging and indexing, Inverted Files, signature files, automatic indexing, user

search and visualization techniques, text search algorithms, information system

evaluation. It also provides an emphasis on various real time applications of the IRS.

Syllabus:


Introduction: Definition, Objectives, Functional Overview, Relationship to DBMS,

Digital libraries and Data Warehouses, Information Retrieval System Capabilities -

Search, Browse, Miscellaneous.


Cataloging and Indexing: Objectives, Indexing Process, Automatic Indexing,

Information Extraction.


Data Structures: Introduction, Stemming Algorithms, Inverted file structures, N-

gram data structure, PAT data structure, Signature file structure, Hypertext data

structure. Automatic Indexing: Classes of automatic indexing, Statistical indexing.


Automatic Indexing: Natural language, Concept indexing, Hypertext linkages.

Document and Term Clustering: Introduction, Thesaurus generation, Item

clustering, Hierarchy of clusters.


User Search Techniques: Search statements and binding, Similarity measures

and ranking, Relevance feedback, Selective dissemination of information search,

Weighted searches of Boolean systems, Searching the Internet and hypertext.

Information Visualization: Introduction, Cognition and perception, Information

visualization technologies.


Text Search Algorithms: Introduction, Software text search algorithms, Hardware

text search systems. Information System Evaluation: Introduction, Measures

used in system evaluation, Measurement example – TREC results.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Interpret the basic principles of information retrieval systems.

CO 2. Relate the indexing process and data structures used in real-time IRS

CO 3. Relate the implementation of automatic indexing; document & term

clustering in IRS.

CO 4. Analyze user search techniques and information visualization in the IRS.

CO 5. Interpret the implementation of text search algorithms along with the

evaluation of information retrieval.


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PSO 1

PSO 2

CO1 2 - - - - - - - - - - 2 - 2

CO2 3 3 - - - - - - 2 2 - 2 - 2

CO3 3 3 3 3 - - - - 2 2 - 2 - 2

CO4 3 3 3 3 3 - - - 2 2 - 2 - 2

CO5 3 3 3 3 3 - - - - - - 2 - 2

TEXT BOOKS:

1. Kowalski, Gerald, Mark T May bury Kluwer , Information Storage and

Retrieval Systems: Theory and Implementation, Academic Press (Chapter

1,2- Unit I, Chapter 3,4-Unit-II,Chapter 5,6-Unit-III, Chapter 7,8 Unit-IV,

Chapter 9,11 Unit-V).

2. David A Grossman and Ophir Frieder, Information Retrieval: Algorithms and

Heuristics, 2nd Edition, Springer International Edition (Chapter 3 Unit-II,

Chapter 3 Unit III).

REFERENCE BOOKS:

1. William B Frakes, Ricardo Baeza-Yates, Information Retrieval Data Structures

and Algorithms, Pearson Education.

2. Robert Korfhage , Information Storage & Retrieval, John Wiley & Sons.

3. Christopher D. Manning and Prabhakar Raghavan, Introduction to

Information Retrieval, Cambridge University Press, 2008.

INFORMATION SECURITY INCIDENT RESPONSE & MANAGEMENT

(SECURITY ANALYST–2)





Course Objectives: The Students will learn the Vulnerability Assessment with

phases, the configuration network devices, router, banner, firewall, VPN,

identification of unauthorized devices, strategy for incident management and data

backup policies, and malicious codes and its handling incidents.

Syllabus: UNIT I: Information Security Assessments (10 Lectures)

Vulnerability Assessment, Classification, Types of Vulnerability Assessment, Vulnerability Assessment Phases, Vulnerability Analysis Stages, Characteristics of a Good Vulnerability Assessment Solutions &Considerations, Vulnerability Assessment Reports – Tools and choosing a right Tool, Information Security Risk Assessment, Risk Treatment, Residual Risk, Risk Acceptance, Risk Management Feedback Loops. UNIT II: Configuration Reviews (7 Lectures)

Introduction to Configuration Management, Configuration Management Requirements-Plan-Control, Development of configuration Control Policies, Testing Configuration Management. Managing Information Security Services: Configuring Network Devices, Identifying Unauthorized Devices, Testing the Traffic Filtering Devices, Configuring Router, Configuring Modes – Router/Global/Interface/Line/Privilege EXEC/ROM/User EXEC, Configuring a banner/Firewall/Bastion Host/VPN server. UNIT III: Troubleshooting Network Devices and Services (7 Lectures)

Introduction & Methodology of Troubleshooting, Troubleshooting of Network Communication-Connectivity-Network Devices-Network Slowdowns-Systems-Modems. Information Security Incident Management & Data Backup: Information Security Incident Management overview-Handling-Response, Incident Response Roles and Responsibilities, Incident Response Process. Data Back introduction, Types of Data Backup and its techniques, Developing an Effective Data Backup Strategy and Plan, Security Policy for Back Procedures. UNIT IV: Log Correlation (8 Lectures)

Computer Security Logs, Configuring& Analyzing Windows Logs, Log Management-Functions & Challenges, Centralized Logging and Architecture, Time Synchronization – NTP/NIST. UNIT V: Handling Network Security Incidents (8 Lectures)

Network Reconnaissance Incidents, Network Scanning Security Incidents, Network Attacks and Security Incidents, Detecting DoS Attack, DoS Response Strategies, Preventing/stopping a DoS Incident etc.

UNIT VI: Handling Malicious Code Incidents (10 Lectures)

Incident Handling Preparation, Incident Prevention, Detection of Malicious Code, Containment Strategy, Evidence Gathering and Handling, Eradication and Recovery, Recommendations etc.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Demonstrate critical thinking and systematically apply Risk Management

concepts to address strategic organisational IS/IT/Information security issues.

CO 2. Critically reflect on and evaluate the challenges and impact of a multitude of

factors to IS/IT/Information Security management.

CO 3. Evaluate the mechanisms of data backups and Identify different types

security logs.

CO 4. Analyze network security incidents from attacks and their presentation.

CO 5. Identification & removal of malicious code and recommendation for

recovering the system.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 - - - - - - - - - - - -

CO2 3 2 3 3 - - - - - - - 3 - 3

CO3 3 3 3 2 3 - - - - - - 3 - 3

CO4 3 3 3 3 3 - - - - - - 3 - 3

CO5 2 3 3 3 3 - - - - - - 2 - 3

TEXT BOOKS:

1. Leighton R. Johnson, Computer Incident Response and Forensics Team

Management:Conducting a Successful Incident Response, Syngress.

2. Gerard Johansen, Digital Forensics and Incident Respons, Packt Publishing Limited.

REFERENCE BOOKS:

1. Peter Szor, “The Art of Computer Virus Research and Defense.” Addison-Wesley Professional, 2005.

2. Richard O'Hanley, James S. Tiller, Information Security Management Handbook, Sixth Edition, CRC Press.

3. Harold F. Tipton, Micki Krause Nozaki, Information Security Management Handbook, Sixth Edition, CRC Press.

MAJOR PROJECT



Course Objectives: The objective of this course is to apply the knowledge gained by the students in the previous courses to develop a project in their interested domain.

Guidelines/Instructions:

Group of students can form as a team and the team has to submit the Project


the semester. The team has to implement the Project and submit the Project report

in the prescribed format at the end of the semester to the department.

Students shall prefer the latest technologies like Artificial Intelligence, IOT, Big Data

Analytics, Cyber Security, Augmented Reality etc in implementing their projects. The

Internal evaluation marks shall be on the basis of two seminars given by each

student on the topic of her project. The Viva–Voce shall be conducted before

semester end examinations.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Apply the domain specific knowledge to sove a real world problem. CO 2. Choose appropriate development procedure and implement requirements at

various phases of Software development. CO 3. Develop and test the solution at every stage. CO 4. Interpret the ideas and discuss the project outcomes in oral and written form


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 3 3 3 3 - 3 3 3 3 3 3 3 3 3

CO2 3 3 3 3 - 3 - - 3 3 3 3 3 3

CO3 3 3 3 3 3 3 3 - - - - 3 3 3

CO4 - - - - 3 - - 3 3 3 - 3 - -

SEMINAR

Subject Code: UGCS8S1918 L T P C


Course Objectives :

Seminar will let the students expose to emerging trends and market needs and also

train the students towards best presentation skills.


Each student shall collect the information on a specialized topic from IEEE/ACM

journals and it should be different from the project work. The topic must be selected

from latest trends and technologies in the IT field, which has to be approved by the

department. The student has to submit the seminar abstract to the Seminar

Coordinator by consulting with the guide at the beginning of the semester.

The student has to submit the seminar report(showing her understanding over the

topic) in the prescribed format at the end of the semester to the department and

the student has to give the presentation before the Departmental Committee.

Course Outcomes:

After completion of this course, the students will be able to:

CO 1. Identify and gain knowledge on the state of art of recent advances in

computer science & engineering domains.

CO 2. Utilize the technical resources effectively for the preparation of presentation

and documentation.

CO 3. Elaborate well-organized technical presentations with effective oral

communications.

CO 4. Solve the queries raised by the group of audience with their technical skills.

Mappng of COs to POs:

POs/

COs PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2

CO1 3 3 - 3 - 3 - 3 3 3 3 3 3 3

CO2 3 - - - 3 - - 3 3 3 - 3 3 3

CO3 3 3 3 - - - - 3 3 3 - 3 - -

CO4 3 3 3 - - - 3 3 3 3 - 3 - -

Internship/Certification Course/EPICS/Foreign Languages/Yoga

Subject Code: UGCS8I2018 L T P C


Course Objective:

This course will enable students to develop competencies expected by the industry.


The student can do anyone of the following courses at anytime from first year to fourth year.

Internship

Certification Course

EPICS

Foreign Language

Yoga

Internship: The student should do the Internship in a reputed company which is approved by the department. The minimum period of Internship shall be one month. However it can be completed in 3 to 4 slots/intervals which shall be a minimum of five days slot.

Certification Course: The student shall be permitted to take certification courses preferably from NPTEL/Swayam/Coursera or any other standard platform, which has to be approved by the department and it must be at least for a period of 8 weeks.

EPICS: EPICS is a service-learning design program in which teams of students partner with local and global community organizations to address human, community, and environmental needs. EPICS was founded at Purdue University in Fall 1995. Students who are interested can register for this program and should get completion certificate from Purdue University.

Foreign Languages: The student shall learn any Foreign Language and get certified from EFLU or a standard organization which has to be approved by the college.

Yoga: The student shall undergo training on Yoga for a period of 2 months and get certified by a standard organization which has to approved by the college.

Course Outcomes:

Upon completion of this course, the students will be able to: CO 1. Prove personal commitment to ethical behaviour, competent practice, taking

responsibility for their own work and acknowledging the work of others. CO 2. Appropriate engagement with relevant stakeholders, and identify, assess and

manage risk. CO 3. Demonstrate effective communication, initiative, effective work practices in a

multi-disciplinary team. CO 4. Develop proficient application and exploration of real-world problems and

evaluation of the outcomes and impact of their work.


POs/ COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

PSO 1

PSO 2

CO1 - - - - - 3 3 3 3 3 - 3 - -

CO2 3 3 - 3 - 3 3 3 3 3 3 3 - -

CO3 - 3 3 3 - 3 3 - 3 3 - 3 3 3

CO4 3 3 3 3 3 3 3 - - - - 3 3 3

B. TECH. FOUR YEAR DEGREE COURSE R18 - SVECW

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