The Curriculum Book
BACHELOR OF TECHNOLOGY
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COMPUTER SCIENCE AND ENGINEERING
FOUR YEAR PROGRAMME Choice Based Credit System vy. e. f. JuIy ZAlg (70:30)
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DEPARTMENT OF COMPUTER SCIENCE AI\D BNGINEERING
GURU JAMBHESHWAR UNIVERSITY OF
SCIENCE & TECHNOLOGY
tr j HISAR.125OO1, HARYANA scheme & syllabi2019
GURU JAMBHESHWAR UNIVERSITY OF SCIENCE & TECHNOLOGY, HISAR (Established by state Legistature 'A',Grade,. Act 17 of lggs) NA.AC Accreditid state Govt. university
Acad /AC-ilt,tFqc_1 Vot. 3DAlgJf 7 7 Dated: Ulfr:f To
The Controller of Examinations GJUS&T, Hisar.
sub: Approval of scheme of examination & syllabi of various B.Tech. progralle(sJ being run in university Teachiig Departments as welt as affil iated En g i neeri ng c oilege(s)/r nstitutelsy. AND Recommendations of Faculty Engineering open & Technology regarding Elective, Format of Minor Quu.ti;;-of papei Mooc strength for programme courses, minimum Erective, semester Registration etc.
Sir,
I am directed to inform you that the vice-chancellor, on the recommendations of the Faculty of Engineering & Technology, vide resolutions no. 2to 13 in its meeting held on 1B 07'2a19, is pleased to approve . the following scheme & syllabi of B.Tech. programme(s) w'e'f' the academic session batch / mentioned against each being run in University Teaching Departments as well as affiliated colleges/institutions and recommendations of Faculty of Engineering & Technolcgy, regarding open Elective, format of Minor Question Paper, Mooc courses, minimum strength for programme Elective' semester Registration etc under sectio n 11(5) in anticipation of approvat of the Acadenric councir of the University Act, 1995.- 1' B'Tech (Printing Technology), B Tec.h (Packaging Technology) (Printing & Packaging i""r'norogD-ath ""un',i""o,,,& B.Tech. Departments ye; k; Teaching and affiLtJd coileg;; i"r. za16-17 batch 2' onwards. B'Tech (Printing & Technotogy) (part{ime)-3rd affiliated -lagkagtng & 4th year for colleges for 20 1T-18 o-atcrr onwards. 3' B'Tech (csE) B'Tech & (lr)-2nd atr year for University Departments and affiliated ]9 Teaching colleges for 2a1B-1g tnwards batch. 4' B'Tech' (EcE)- 2nd 4th year for University Teaching affiliated .-to , Departments and coileges for 2a1B-1g onwards batch 5' B'Tech' (EE)- 2nd 4th year for university affiliated 1" Teaching Departments and coileges for 2o1B-1g onwards batch.
Condt. .pZf- scheme & syllabi 2019
-3- 6' B'Tech' (Printing Technology), B.Tech (Packaging Technology) (Printing & Packaging . & B.Tech. recnnoiggy)--.2nd io atn year and only for university sylabi of 2nd year ieacning olprnments ano e""!slvvarriliated onwards batch. colleges\'\"'.sv for 2018-1g 7 ' B'Tech' (Agricultural Engg-) & B.Tech (Aer.onautical Engineering)- year for affiriated 2nd to 4th coileges for 2018-1g onwards oatcn. B' scheme and syllabi of B.Tech. (Mechanical Engineering )- 2nd to 4th year for University Teaching Departmenti and affiliated batch. lolt"g", for 2o1g-1g onwards 9' B'Tech'.(civil Engg')--?lg to 4th year for University affiliated Teaching Departments and coileges for 2o1B-1g onwards batch. 10' B'Tech' (Food rechnology) 2nd to 4th year for University Teaching Departments for 2018-19 onwards baich. 11' The list and syllabus of open Electives and Mandatory programmes for B.Tech. courses w.e.f. 2Aft_19 batch onwards 12. The format of Minor Question paper for (B'Tech students of zolg-1g batch onwards 2nd to Final Year) and level of Assignment Education. in light of outcome based
13' The students of B'Tech2a1B-19 batch (2nd to Finar year) will have choice for MOOC course (not more to opt than one in each semester) which he/she studied earlier' in lieu of courses had not mentioned in every programme Electives with the prior approval of ah;;p;rson of :#?.iJedit withiril5 days of srart of 14' The minimum 30% of existing class strength shoulo opt for any programme ' elective' Decimal part will be trlncated in cale zo"t"is not whote number. 15' The semester- Registration process being followed in FET. Faculty appreciated the process of semester Registration in Frr as it has helped in timely classes and has improved attendance start of in ctasses. Faculty further recommended not be ailowed to resisi"iln",^ ffl:l{:::srrourd prrrrg; lr on" month or A copy of the scheme and syllabi of aforementioned B.Tech. programmes other and recommendations of Faculty of Engineering and rechnology are enclosed hei'ewith.
This is for your information and further necessa ry alttonat your end.
DA. As above Deputy Registiar (n6Oeln ii) For Registrar
Endst No Acad / AC-il vtFac_1 vor sr_(doc_#// oatea, &_c f fl L7 the above is forwarded to necessari"ffSl,-"t the to,,o*,nffiiJformation and 1. Dean Academic Affairs, GJUS&T, Hisar. 2. Dean of Colleges, GJUS&T, Hisar.
conid. p/3 scheme & syllabi 2019
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3. Dean, Facurty of Engg. -g.Tecrr-g Technorogy: GJUS&T, Hisar (arong scheme & syllabi oi j with copy of Engineering) tngril,lltur"r rngg a B.Tech (Aeronauticar 2nd to 4th year; ano oin"i ,".ommendations from sr. no. 1 Further' he is requestedt.o get 1 to 15. upload the syllabi of above said programme the website of the Universityl on 4. chairperson, Department of csE, GJUS&T- Hisar (alongwith syllabi copy of scheme & of B.Tech. (CSE) & B Tect-r (tT)__ 2nd recommendations from to 4th year and other sr' no. 11 to 15. Further, nL is'requested the syllabi of above said programme to get upload on the website of the University. tr chairperson' Department of Food Tech., GJUS&T, Hisar (alongwith scheme & syllabi of B Tech. copy of (Food recrrnotogyf znd'to year recommendations from sr' '.r," 4th ancJ other no. 1 1 to 15. Furthei, I requested the syllabi of above said programme to get upload on the website of the University. 6. chairperson, Department of..rlec.h. Engg_, GJUS&T, scheme & Hisar (arongwith copy of syllabi of B'Tech- (Mechanica'i Engineering) recommendations 2nd to 4th year and other from sr' no. 1 1 to 1 5 . Furt ur, hJ i, ,"qr"rted the syllabi of above said programme to get upload on the website of the University. 7. chairperson' Department of Environmental science & Engineering, Hisar (alongwith copy of schemu a GJUS&T, year rviilui of B.Tech. (civil Engg.) 2nd and other recommendations riom to 4th s, no. 11 to 1s. Further, he is upload the svllabi or above |?H:',ni:?Jfil said prosrammo on the website
8. chairperson' Department of Electronics & communication GJUS&T, Hislr (arongwith Engineering copy of scheme & syilani g.rech. 4th year and B'Tech' or (ECE) Znd to (EE) znd to +ilr and sr no 11 to vear other recommendations from 15. Further, he is ,uqr"ri"J to said programme get uptorJ tnu sygabi of above on tlre website of tiru uniuersity.
I chairperson' Department df Printing Tech.,_GJUS&T, Hisar (alongwith scheme & syrabi of B Tech. copy of Technorogy) tpri"tirg Technoro;;), B.Tech (packaging & B-Tech. (printilS a. pr"rJging. (Printing & Packaging TechnolJgv) leghnoiogy)- 4th year, B.Tech. examination lnart-t"rme; ero & 4th-year and scherne of -- to 4th vear and sv[abi Technorogy), ?nd -a.r".n.of B Tech (printing B.Tech lpackaging re.r,norogy):;;Jy;;; [i Packaging Technology) ano otiuiru.o*mendaiions (printing & from sr. no. u' ; p;o;i 11to 1s. it"',vr r, bi or a fiYff t#';,i?:t;l;S,:"-fl oove sa id pros ramme on
10. Director-Principal, Manav lnstitute or ru.n & Mgt., Village- copy of scheme & sy,abi or Jevra, atongwith (Aeronautical qcitl3e;+;,, (,tj; (civit Engg ) and ?(Agriculiure J":,,. 'Engg.) Enss.), (EE), recommendations programmes and other from sr no. 1 1 to 15. 11.. Director-principar, om rnstituie of Tech. &,Inlal:glr.l. scheme & sv'abi of B Tech arongwith copy of &Packaging Technorogy), JCSE), D r*=r, trqEi lcirir Engg.), (priniing (printing'&6;;r.aging recnnotogy) part (EE), programmes and ofhei ,"ro**endations rirne from sr. no. 11 to 1s. Preface The overall r'vell-being of a nation depends on the eminence of its human resource. providing quality education plays a vital role in trans-forming people into valuable human resource. well educated students of today will become innovators and leaders of tornooou' rvho are going to ensure a constructively competitive but sustainable and peaceful rvorld for everyone. To meet this eno, erctE has developed a model curriculum for Engineering graduates. The AICTE model curriculurn is no way an ideal document and lacks quality it ought to have' rhe model curriculum has no uniformity frorn one course to another. The course outcomes are ill- dehned, and, references are incomplete and inconsistently formatted in the rnodel curriculum, nonetheless it has given us an opportunity to revise the curriculum of our graduate engineering programmes. we have revised the curriculum for Bachelor of Teclrnology Programme in computer science and Engineering of the Department of computer Science and Engineering, Guru Jambheshwar University of Science and Technology; Hisar' The curriculum is designed around the framework of outcome-based education in rvhich students are at the centre of teaching learning process. The salient features of the curriculum follows: design are as
To programme l. start with, four Educational outcomes are defined. 2. The twelve Programme outcomes (Pos) are taken from the Self Appraisal Report fbrmat of National Board of Accreditation (NBA) fbr undergraduate engineering piogru-*es and three programme Specilic outcomes (PSos) are outlined to ciprure the specialisations of the B. Tech. (csE) prograilmle. 3. An induction progranune three of weeks duration has been introduced to make the lately admitted students comfortable in their new environment. The induction prografirme continues in the form of participation in Sports club or Green club or cultural, Literature'urJFil* CIub etc. for the remaining period of the programme. It is mandatory tbr every student to join in one of these clubs. I 4. In addition to the professional core and elective courses, there is a provision for many courses fiom Basic Sciences, Engineering sciences, Iv{athematics and Humanities. irrl r"r-..Jii-."datory courses are included to make students aware about constitution of India, issues related to environmental and sustainable development, and Indian traditional wisdom. 5. For gvery course, 4 to 6 Course outcomes (Cos) are defined which are concrete and measurable. 6. Guidelines for prep*i,g sessional examination question papers and assignments have been frarnecl for measuring the attainment levels of COs. -f The internal and external evaluation criteria for various courses has been succinctly described. 8. The course outcomes (cos) are mapped to Programme outcomes (pos) by defining a co:po articulation matrix for every course. 9. The methodology computing for the attairunent levels for the Course outcomes and programme Outcomes is laid out.
10. The new curriculum has a focus on the problem solving and learning capabilities of the students. There are many laboratory courses rvhich give students a hands-on in problem solving. Further, provisions for industry internship/training "^p.I"n"e and project works -uk" students ready to accept challenges and do research to solve diffrcurt engineering piobi.*r. lt. overall, the new curriculum is made keeping in the view the continuous cycle of improvement teaching in Iearning process of outcome-based education strategy.
'.-,l -.:w \ syllabus Revision committee: Team Members L Professor Saroj (Convener)
2. Dr. Ritu Nagpal, Associate professor, (Mernber) - . 3. Dr. Sunita Beniwal, Assistant professor), (Member) 1. Mr. N{anoj, Assistant professor (Member) 5. Dr. Jyoti Vashishtha 6. Dr. Anju Sangwan
In addition. all the faculty members of the Department have participated in revising the syllabus of the various courses.
t. t rl l! -- e Chapter L= General Information
i 1.1- Vision and l\{ission of the Department of Computer Science ancl Engineering
1.1.1 \'ision The vision of the Department is to become a centre of excellence fbr eclucatiop in Computer Science and Engineering- Infbrmation Technology and Computer Applications. \\'e r.isualize ourselves as an agency [o nurture young minds to be the f.rture leaders in the field of fiigher education, research and development, and information technology industry. Our aim is to bnlg out creators and innovators who will work towards the overall well-being of the society.
I.1.2 Mission
' Impaning state-of-the-art lorowledge in Conrputer Science and Engineering, Information Technology and Computer ApplicatiorLs. o Ensuring that our students graduate with a sound theoretical basis and wide-ranging practical experience. o Fostering linkages between the Department and, public and private sectors, traversing research establishments as well as Infomation Technology industry. . promoting ethical research ofhigh quality.
' Adopting the best pedagogical methods in order to maximize knowledge transfer. . r . Inculcating a culture of free and open discussions in the Department. o I Engaging students in evolving original ideas and applying them to solve complex engineering problems.
o Inspiring a zest into students for lifelong leaming. Infusing scientific temper, enthusiasm, professionalism, team spirit and leadership qualities in ' students. o Sensitizing snrdents to look for environmentally sustainable engineering solutions. o Upholding democratic values and an environment ofequal opportudty for everyone. 1,2 B. Tech. (CSE): Programme [ducational Objectives (PEOs)
The Programme Educational Objectives ofthe B. Tech. (CSE) Programme are:
PEOI. To prepare responsible and ethical professionals to be successfirlly employed in Computer Science and Information Technology industry, who will be able to apply the principles of science, engineering and project management to develop and deploy solutions for real world problems after assessing their environmental, culhlal and societal implications.
PEO2. To train shdents for analysing, evaluating and designing complex engineering solutions individually or in teams by doing a syslematic and in-depth research in the related problem domains, by using modern tools and by communicating effectively among the various stake holders.
PEO3. To groom the professionals and entrepreneurs of tomorrow with leadership qualities and deep societal concems who can move up in their professional career or start their o\rr ventures.
PEO4. To guide the graduates to develop a positive attitude towards leaming and motivate them to take up higher studies and research. t.3 B. Tech. (CSE): Programme Outcomes (pOs)
POl. Engineering knor*'ledge: Apply the knowlecige of mathematics. science, engineering fundamentals, and an engineering specialization to the solution of complex engineering pioblems. PO2. Problem analvsis: Identify, formulate. review' research literature, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, nafural sciences, and engineering sciences.
PO3. 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 .rri-o-ental considerations.
PO4- 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.
PO5' I\Iodern tool usage: Create, select, ancl apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.
PO6. The engineer and society: Apply reasoning infonned by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
PO7- 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.
PO8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO9' Individual and team lvork: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
POl0- Communication: Communicate effectively on complex engineering activities t rith the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentatiorr, ond give and rs:eive clear instructions. POI 1. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one's orvn work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
POl2- LifeJong 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. Program Specific Outcomes (pSOs)
PSOI Developing Computational Systems: Use principles of electronics and Micro-Processors, various programming languages, data structures, database management systems, computer algorithms, theory of computation and software engineering for designifg and implemelting computational systems. PSO2 Devising Nefworking Solutions: Apply the knowledge of systems in the areas related to network technologies, mobile ad hoc and sensor networks, cloud computing, IoT and, information and web security for devising networking solutions.
PSO3 Doing Data Anatytics and Designing Intelligent Systems: Utilize the approaches and tools of artificial intelligence and soft computing, data analytics and machine learning for designing and working with intelligent systems that can extract valuable information from large amount of data and learn from their environment.
\ l\t7 i0 Chapter 2: Programme Structure and Scheme of Examination B, Tech.[CSE] Y?
1t 2,1 Programme Structure and Credit Distribution in Various Components of the Curriculum
. 2.|.tDefinition of a Credit
Type of Teaching Learning Activit,v No. of credits I Hour Lecture (L) per week I credit I Hour Tutorial (T) per week i credit 2 Hours Practical (Lab) per week 1 credit
2.1-2 Credits for Different Curriculum Components of B. Tech. Programme Distribution of Credits Sr. Category Course Code Credit No. Breakup 1 Humanities and Social Sciences including Management courses HSMC 07 2. Basic Science courses BSC 22 a Engineering Science courses including workshop, dro*irg, b*i.. of ESC 16 electricaUmechanicaVcomputer etc. including labs. 4. Professional core courses +Professional Core Lab. Courses PCC-CSE 76 5. Proibssional Elective courses relevant to chosen PEC-CSE l8
) spec ialization/branch 6. Open subjects - Electives from othei a..hrri.@ OEC 09 subjects 7. Project work, seminar and internship in industry or elsewhere PROJ-CSE t2 8. Mandatory Courses MC [Environmental Sciences, Induction program, Indian constitution, Essence of lndian Knowledge Traditionl 9. Lab. Courses PCC-CSE-P/ PEC-CSE-P Total Credits r60
b e,
t2 2.1.3 Mandatory Courses (MC)
Sr. No. Course Code Nomenclature of Course flours per rveek Total Semester Credits L T P
I MCIOl-T Induction Training 0 0 0 0 I
) MCIO3-T Indian Constitution 3 0 0 0 II
1 3. MCIO2-T Environmental S crences J 0 0 0 III
a 4. MCIO4-T Essence of Indian Traditional J 0 0 0 V Knowledge
Total Credits 0
2.1.4 Humanities and Social Sciences Including Management Courses (HSMC)
Sr. No. Course Code Nomenclature of Course Hours per week Total Semester Credits L T P
I HSMClOl-T English 2 0 2 ., II
2. HSIvIC30l -T Humanities-I (Economics for 2 0 0 2 V Engineers)
3. HSMC302-T Humanities-Il (Fundamentals of 2 0 0 2 VI Management for Engineers)
Total Credits 7
2.1.5 Basic Science Courses (BSC)
Sr. No. Code No. Nomenclature of Course Hours per week Total Semester Credits L T P
I BSCIOl-T Physics 3 I J 5.5 II BSC 101.P
) BSC 105-T Mathematics-I JI I 0 4.0 I
a J. BSCIO2-T Chemistry-I J I 3 5.5 I BSC I O2-P
4. BSC I 06-T Mathematics-II 3 I 0 1.0 II
5. BSC2Ol-T Mathematics-III Ja 0 0 3.0 III
Total Credits 22
\ i L""
l3 2.7.6 Engineering Science Courses (ESC)
Sr. No. Course Code Nomenclature of Course Hours per n'eek Total Semester Credits L T P I ESCr 0l -(T/P) Basic Electrical Engineering J I 2 5 II 2. ESCr 02-(TtP) Engineering Graphics & Design 1 0 4 J I 3. ESC 103-(T/P) Programming for problern Solving 3 0 4 5 I 4. ESC 104-(T,P) Workshop,Manufacturing Practices 1 0 4 J Ii Total Credits t6
2.1.7 Professional Core Courses (PCC-CSE)
Sr. No. Course Code Nomenclature of Course Hours per week Total Semester Credits L T P I PCC-CSE20r-(TtP) Data Structures and Algorithms 3 0 4 5 III ') PCC-CSE202-(TtP) a Object Oriented Programming J 0 4 5 III using C++ J.a PCC-CSE2O3-T Discrete Mathematics J 0 0 J III 4. PCC-CSE2O4-T - Computer Organisation and J 0 0 J III Architecture 5. PCC-CSE205-(T/P) Microprocessor and Interfacing 3 0 2 4 IV 6. PCC-CSE2A6-gtP) Computer Networks J 0 2 4 IV 7. PCC-CSE2}7 -(T tP) Database Management System 3 0 2 4 I\/ 8. PCC-CSE2O8-T Analysis and Design ofAlgorithms J 0 0 J IV
9. PCC-CSE2A9-T Software 1 Engineering J 0 0 -l IV 10. PCC-CSE2l0-(r1P) Java Programming J 0 4 5 IV 1l PCC-CSE30l -(T/P) 1 Computer Graphics J 0 2 4 V 12. PCC-CSE302-(T tP) Python Programming J 0 J 4.5 V
13. PCC-CSE303-T a High Speed Networks 3 0 0 J V 14.. PCC-CSE3O4-T a Cryptography and Network J 0 0 ) V Security
15. PCC-CSE305-(T,") Operating Systems 3 0 2 4 VI
16. PCC-CSE306.T I Formal Language and Automata 3 0 0 J VI Theory t7. PCC-CSE3O7-T Data Anqlytics using R 2 0 )- 3.5 VI 18. PCC-CSE308-(TP) .NET using C# 2 0 2 3.0 VI 19. PCC-CSE4OI-T Compiler Design 3 0 0 J VII 20. PCC-CSE4O2-T Artifi cial Intelligence 3 0 0 3 VII
2t PCC-CSE4O3-T 1 Data Mining Techniques 3 0 0 J WII
Total Credits 76
t4 2.1.8 Professional Elective Courses (PEC-CSE)
Sr. Course Code Nonrencla ture of Course Hours per lveek Total Semester No. Credits t. T P
a I PEC-CSE3O I -T Embedded System De-sign, Soft J 0 0 3 VI to Computing, Graph Theory PEC-CSE604-T Bioinformatics
2. PEC-CSE4OI-T Software Proj ect Management, J 0 0 3 VII to Wireless and Mobile PEC-CSE4O4-T Comnrunications, Distributed Operating Systems, Cloud Computing
a J. PEC-CSE40s-(T/P) Advanced Microprocessor, Iv{obile J1 0 4 VII to Application Development, PEC-CSE408-(T,{P) Multimedia Technologies, Digital Image Processing
4. PEC-CSE409-(T/P) Internet of Things, Software Defined )I 0 I 4 VIII to Networks, Netrvork Administration PEC-CSE4t2-(TtP) and lVlanagement, Software Testing and Quality Assurance
5. PEC-CSE4l3-(T/P) Machine Learning, Big Data 3 0 4 VIII to Analyics, Web Development, PEC-CSE4r7-(TtP) Statistical Computing, Digital Forensics
Total Credits 18
2.1.9 Open Elective Courses (OEC)
Sr. No. Course Nomenclature of Course Hours per week Total Credits Semester Code L T P
1 I OEC-I Open Elective-l 3 0 0 J V
2. OEC-II Open Elective-Il J 0 0 3 VI
J. OEC-III Open Elective-Ill Ja 0 0 ) WI
Total Credits 9
2.1.10 Project work
Sr. Course Code Nomenclature of Course Hours per week Total Semester No. Credits L T P
I TNT:CSE3OI Industrial Training/lnterns hi p 0 0 2 I After IV'h Sem.
2 PROJ-CSE4O2 Mini-ProJect using open 0 0 I 1 After VI'h Sem. source tools a J PROJ-CSE4O1 Major Project I 0 0 8 1 VI]
4 PROJ-CSE4O3 Major Project II 0 0 12 6 VIII To al Credits t2 15 0/ 2.2. B. Tech- (Computer Science and Engineering): Semester-rvise Scheme
Induction Programme It is mandatory conduct to an induction progranrme for newly admitted studenrs ri-eht at tire beginring of the first semester The objective of the induction prograrnme is to create a bond betg,eel the ipstitution and the newly admitted students. The new students enter an institution with diverse backgrounds and expectations. It is important to help thenr adjust to the nerv environment. To meet this purpose, there ivill be three rveek-long induction programmsbetbre the normal classes start' The induction program shall prol'ide students the opportunify to settie clor.vn and be comfortable in the nelv environment. The new students w'ill come to know their seniors, faculty nrembers, department and university. The student u,ould be engaged in the following acti'ities.
L Familiarization with the Department and the university 2- Physical activities like morning walks, cvcling or pla-,,-ing one or the other games. 3. Creative arts like painting, music and dancing erc. Talks 4. and lectures by eminent people, and group discussion on universal Fluman r,,alues 5. Literary activities like reading rvriting or debating
The scheduie for organizing the induction programme shall be prepared every year at university le'el. Students will be engaged in diverse activities at the level of Department. Depending on the interest. e'ery student must opt for one the of activities during all the semesters. For this purpose. the lollor.ving clubs shall be established in the Department.
l. Sports Club 2. Green Club 3. Culture, Literature and Film Club 4. Social Serv'ice CIub 5. Technologv Innovation Cluo
Each student will spend 3 to 5 hours for these activities per week.
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l6 SENIESTER I Sr. No. Course Code Nomenclature of the Course Hours per rveek Credits .I L P I BSClOI-T Physics (Group A) J I J 5.5 BSClOI-P BSCI O2-T Chemistry (Grciup B1 BSCl02-P 2. BSC I O3-T Mathemal cs -I J 0 4.0 BSCI05-T lv{athemat cs -l (flor CSE,IT') 3. ESC IO1-T Basic Electrical Engirrcering (Group A) 3 I ) 5.0 ESCIOl-P ESClO3-T Prograrnming lor Problcnr Solving (Group B) J 0 4 ESCI03-P 4. ESClO4-T Workshop,'Manufacturins l)ractices (Croup A) I 0 l J1 ESCIO4-P ESClO2-T Engineering Graphics ct Design (Group B) I 0 4 ESCIO2-P 5. MC1O1 Induction Training (Group A & B) J 0 0 0 weeks Total Credits 17.5
SEMESTER II Sr. No. Course Code Nomenclature of the Course Hours per rveek Credits
L T P I I BSCIOI-T Physics (Group B) J J 5.5 BSC I O I.P BSC I 02-T Chemistry (Group A) BSCIO2.P 1 2. BSC 1OqT Mathematics -II J 0 I 4.0
BSC I 06-T Mathematics (for CSETIT) - -lI ). ESCIOI-T Basic Electrical Engineering (Group B) J 1 2 5.0 ESCIOI-P ESCl03-T Programming for Problern Solr.ing (Group A) J1 0 4 ESCI03-P 4. ESC I O4-T WorkshoprManufacturing Practices (Group B) I 0 4 J ESCIO4-P ESClO2-T Engineering Graphics & Design (Group A) I 0 4 ESCIO2-P 5. HSMCIOI-T English (Group A and B) 2 0 2 ) HSMCIOI-P 6. MC 102-T Environmental Sciencei; (Group A) 3 0 0 0 MClO3-T Indian Constinrtion (Group B) J 0 0 Total Credits 24.5
{- 1l SEMESTER.III Sr. No. Course Code Nomenclature of the Course Hours per lveek Credits L T P
f I BSC2O I -T Mathematics-III 3 0 U
) PCC-CSE2OI-TI Data Structures and Algorithms ) 0 0 3 PCC-IT2O I -T
a -). PCC-CSE2O2-TI Object Oriented Programming J 0 0 J1 PCC-IT:202-T using C++
4. PCC-CSE2O3.TI Discrete Mathematics J 0 0 J PCC-IT2O3-T
5, a PCC-CSE2O1-TI Computer Organisation and Architecrure J 0 0 J PCC-IT204-T
1 6. MClO2-T Environmental Science J 0 0 0
7. PCC.CSE2OI PI Data Structures and Algorithms using 0 0 4 ) PCC-IT2OI-P CIC++ Yv6.
8. PCC-CSE2O2-PI Object Oriented Programming using 0 0 4 ) PCC-IT2O2-P C++ Lab.
Total Credits 19
SEMESTER IV
Sr. No. Course Code Nomenclature of the Course Hours per rveek Credits L T P 1 t PCC-CSE205-TI Microprocessor and Interfacing J 0 0 J PCC-IT2O5-T
1 2. PCC-CSE2O6-TI Computer Networks J 0 0 J1 PCC-IT3O I -T
3. PCC-CSEZO7 -TI Database Management System J 0 0 3 PCC-IT2O7 -T
4. PCC-CSE2O8-TI Analysis and Design of Algorithms .) 0 0 Ja PCC.IT2O8-T
5. 1 a PCC-CSE2O9-TI Software Engineering J 0 0 J PCC-IT2O9-T
a 6. PCC-CSE2IO-TI Java Programming J 0 0 J PCC-IT21O-T
7. PCC-CSE2O5-P Microprocessor and Interfacing Lab. 0 0 2 I PCC-IT2O5-P
8. PCC-CSE2O6-PI Computer Networks Lab, 0 0 2 I PCC-IT3O1-P 9. PCC-CSE2O7 -P Database Management System Lab. 0 0 2 1 PCC-IT2O7-P
10. PCC-CSE2IO-PI Java Programming Lab. 0 0 4 2 PCC-IT2 1O-P
Total Credit 23 Industrial Training of 4-6 weeks after IVth semester
? &- ;:'*4-.. t8 .-.,* Semester V
Sr. No. Course Codes Nomenclature of the Course flours per rveek Credits L T P
a I PCC-CSE3O I -Ti Computer Graphics J 0 0 J PEC-IT4O9-T
2. PCC-CSE3O2-TI Pyhon Programming ) 0 0 J PEC-IT3O8-T
3. PCC-CSE3O3-TI High Speed Network Technologies J 0 0 3 PEC-IT3O5.T
4. PCC-CSE3O4-TI Cryptography and Netr.vork Security )1 0 0 J PEC-IT-402_T
5. OEC-I Open Elective Course offered by J1 0 0 J other Departments
6. HSMC3O I -T Economics for Engineers 2 0 0 2
7. MCIO4-T Essence of Indian Traditional Knowledge J1 0 0 0
8. PCC-CSE3O 1-P/ Computer Graphics Lab. 0 0 ) l PEC-IT:409-P
1 9. PCC-CSE3O2.PI Python Programming Lab. 0 0 ) 1.5 PCC-IT3O8-P
10. INT:.CSE3O1 Industrial Training/lnternship 0 0 0 Total Credits 20.5
\,- e' \
i9 SEMESTER VI Sr. No. Course Codes Nomenclature of the Course Hours per rveek Credits L T P I PCC-CSE305-Ti Operating Systems 3 0 0 J1 PCC-IT2O6-T .) PCC-CSE3O6-TI Formal Language and Automata Theory 0 0 Ja PCC-IT303-T
a J, PCC-CSE3O7-TI Data Analytics using R 2 0 0 2 PEC-IT4O7-T
4. PCC-CSE3O8-Ti .NET using C# 2 0 0 2 PCC-IT302.T
). PEC-CSE3O 1 1.T Professional Elective Course to be J 0 0 -) to opted by students PEC-CSE3O4-T 6. HSMC302-T Fundamentals of Management for Engineers 2 0 0 2
1 7. OEC-II Open Elective Course offered J 0 0 J1 by other Departments 8. PCC-CSE305-P/ Operating Systems Lab. (IINIX/LINUX) 0 0 2 I PCC-IT2O6.P
9. PCC-CSE3O7-P/ Data Analytics using R Lab. 0 0 Ja 1.5- PEC.IT407-P 10. PCC-CSE3O8-P/ .NET using C# Lab. 0 0 2 PCC-IT3O2-P
Total Credits 21.5 AMin -Project/Training based on open source tools/ NET
List of Electives I
l. PEC-CSE 3O!-T/PEC-IT301-T: Embedded System Design 2. PEC-CSE302-T/PCC-IT40I-T: WirelessandMobileCommunications 3. PEC-CSE3}3-TIPEC-IT3O3-T: GraphTheory '4. ffi%fifxh,ryPEC-CSE3A4-TIPEC-IT304-T: Bioinformatics * -ril..f- ore&*s
lt, SEMESTER VII
Sr. No. Course Codes Nomenclature of the Course Hours per rveek Credits L T P
I PCC-CSE4OI-TI Compiler Design 3 0 0 3 PCC-IT306-T
2. PCC-CSE4O2-TI Artificial Intelligence Ja 0 0 .,1 PCC.IT3O4-T
a a 3. PEC-CSE4OI-T Professional Elective Course to be opted by students J 0 0 -) to PEC-CSE4O4-T
4. PEC-CSE4O5-T Professional Elective Course to be opted by students J 0 0 J to PEC-CSE4O8-T
5. OEC-III Open Elective Course offered by other Departments J 0 0 J1
6. PEC-CSE4O5-P Professional Elective Course Lab. 0 0 2 I to PEC-CSE 408-P
PROJ-CSE4O 1 Major Project I 0 0 8 4
8. PROJ-CSE4O2 Mini Project using open source tools/.NET 0 0 2 I Total Credits 2t
List of Blectives II
l.' PEC-CSE4O!-T/PEC-IT40l-T: Software Pro-iect Management 2. PEC-CSE3AZ-TIPEC-IT302-T:SoftComputing 3.' PEC-CSE4A3-TIPEC-IT403-T: Distributed Operating Systems 4. PEC-CSE4}4-T| PEC-IT4O4-T: Cloud Comoutins . h - - s A,n-r d^o-E tt^ *i;;.;#'[io"llefl, e.'cu'-!--ed t "o;rA " List orur$tive ur "t .-q/t f c'- i i I h. P\ J .:4 .t' k0', .!J..7 21 Mathe e lrrformation lsCe: BSC20l -T C:--_re'rseAsSessmentMethods(internaI:30;,ga1.'nal:70) 4 fL ,'- COUI___.(F> Content . Transforms: -r*- tnd Fourier Euler's forrrr I G, conditions for a Fourier expansion, change of interval, and - 'square :qn of odd even functions, Fourie-- e--pansion of wave, rectangulai o,ave, saw-toothed full rectified wave, half range sine an d- <=->sine serres. ls, Fourier fansforms, Shifting theore on time --rr 1. OEC-II Open Elective Course offered 3 0 0 3 by other Departments 8. PCC-CSE3O5-P/ Operating Systerns Lab. (UNIX/LINUX) 0 0 2 I PCC-IT2O6-P 9. PCC-CSE3O7 -P I Data Analytics using R Lab. 0 0 j 1.5. PEC-IT4O7-P 10. PCC-CSE3O8-P/ .NET using C# Lab. 0 0 2 1 PCC-IT3O2-P Total Credits 21.5 AMi i-Project/Training based on open source tools/.NET List of Electives I l. PEC-CSE 301-T IPEC-IT301 -T: Embedded System Design 2. PEC-CSE302-Tl PCC-IT401 -T: Wireless and Mobile Communications J.1 PEC-CSE303-T I PEC-IT303-T: Graph Theory 4. PEC-C SE 304-T I PEC-IT3 04-T: Bioinformatics t Fil^rl crl.ar- WLo o c^rt, ^tLr, 4S", L rnltT *l';j-r't-l .6a;!*')t, -\,, -" f t. ' e&Ldr-.5 €..l}j.e.Y ci\4.I -H_- *ery-.)- creJ+-s @ 20 SEMESTER VII Sr. No. Course Codes Nomenclature of the Course Hours per rveek Credits L T P a I PCC-CSE4OI-T I Compiler Design J 0 0 3 PCC-IT3O6-T a 2. PCC-CSE4O2-TI Artifi cial Intelligence 3 0 0 J PCC-IT304-1' 3. PEC-CSE4O 1-T Professional Elective Course to be opted by students Ja 0 0 ) to PEC-CSE4O4-T 4. PEC-CSE4O5-T Professional Elective Course to be opted by students Ja 0 0 Ja to PEC-CSE4O8-T 5. OEC-III Open Elective Course offered by other Departments Ja 0 0 J1 6. PEC-CSE4O5-P Professional Elective Course Lab. 0 0 2 to PEC-CSE 408-P 7. PROJ_CSE4O I Major Project I 0 0 8 4 8. PROJ-CSE402 Mini Project using open source tools/.NET 0 0 2 I Total Credits 2t List of Electives II 1. PEC-CSE40l-T I PEC-IT4O I -T: Softrvare Project Management ) PEC-CSE302-T I PEC-IT302-T: Soft Computing J. PEC-CSE 403-T I PEC-IT403-T: Distributed Operating Systems 4. s. List ih:#3d-wq._ r:-'e--{ 1. PEC-CSE405-TIPEC-IT405-T:AdvancedMicroprocessor 2. PEC-CSE406-Tl PCC-IT403-T: MobileApplication Development 3. PEC-CSE407-Tl PEC-IT411-T: MultimediaTechnologies 4. PEC-CSE4O8-TIPEC-1T408-T: Digitalrlmage,Procqssing \ -. O:O!_fef ,t. ffvt^1 D|'12 4 t\^{. [nqDC h Et. ,[+ud.t:(+ e- d { *L eqpal_ .recL-,Lx, List of Elective III (Labs.)"-ru{ D Y l. PEC-CSE405-Pl PEC-IT405-P:AdvancedMicroprocessor(Lab.) 2. PEC-CSE406-Pl PCC-1T403-P: MobileApplicationDevelopment (Lab.) 3. PEC-CSE 407 -P I PEC-IT4 I I -P: Multimedia Technologies (Lab.) 4. PEC-CSE408-P/ PEC-1T408-P: Digital Image Pr6cessing (Lab.) ;.11 '1|" k@' 21 SEMBSTER VIII Sr. No. Course Codes Nomenclature of the Course Hours per week Credits L T P PCC-CSE4O3-T I I Data Mining Techniques 3 0 0 3 PCC-IT4O2-T PEC-CSE4O9-T 2. Professional Elective Course to be opted by students J 0 0 3 to PEC-CSE4I2-T a PEC-CSE4I3-T -t a J. Professional Elective Course to be opted by students J 0 0 J to PEC-CSE4I]-T 4. PEC-CSE4O9-P Professional Elective Course Lab. 0 0 2 I to PEC-CSE412-P 5. PEC-CSE4I3-P Professional Elective Course Lab. 0 0 2 1 to PEC-CSE4I7-P PROJ-CSE4O3 6. Major Project II 0 0 12 6 Total Credits ll List of Electives IV 1. PEC-CSE409-TIPEC-IT4O9-T: InternetofThings 2. ' PEC-CSE4l0-T/ PEC-IT4|0-T: Software Defined Networks 3. PEC-CSE4ll-TIPCC-IT305-T: NetrvorkAdministration and Managemenr --h+tnq-lr 4. _PEC-CSE412-T/ PEC-IT412-T: Software andOualirxAs *:' lesti4g I i"+!'*. .,, t Fi,q";ili-;T S; a,Lb6uviffi"rflilAiuffE*i[r.v C }4"L**"ie-rdr List of El0ctives IV (Labs.) % eq)Jilt- {re4lS65 1. PEC-CSE409-Pl PEC-IT4O9-P: Inrernet of Things (Lab.) 2. PEC-csE4l0-PIPEC-IT4l0-P: SoftwareDefinedNetworks (Lab.) 3. PEC-CSE411-PIPCC-IT305-P: NetrvorkAdministration and Management(Lab.) 4. PEC-CSE412-Pl PEC-IT4 12-P Software Testing and Quality Assurance (Lab.) List of Electives V 1 . PEC-CSE 413-T I PEC-IT4 t 3-T: Machine Learning 2. PEC-CSE4l4-TIPEC-IT4l4-T:BigDataAnalytics 3. PEC-CSE4l5-TIPEC-IT415-T: Web Developme.nt 4. PEC-CSE416-TIPEC-IT416-T: Statistical Compuring o!^J l. PEC-CSE4l3-Pl PEC-IT4l3-P: Machine Learning (Lab.) 2. PEC-CSE414-P/PEC-IT4l4-P: Big Data Analytics (Lab.) 3. PEC-CSE4l5-Pl PEC-IT415-P: Web Development (Lab.) 4. PEC-CSE4l6-Pl PEC-IT416-P: Statistical Computing (Lab.) 5. PEC-CSE4l7-PIPEC-IT406-P: DigitalForensics(Lab.) 22 Chapter 3: Detailed SyIIabi of Various Courses 23 rf) o U) tu (\I r.) ?f, ?.) .+ ?.) ao (\l (\I N N (\l 6l ?o ac tu t\ (f, ro ca t) N N o I C t t oo\ t-r I I 6 6l A.t U I O r- na I l-( I H \o l- ! U) I r') I (! 1 I q) t I \- c.t 6l ro c.) ro a ccf) X .I N (\l t\ (\t L (\l (\T tN a t) CE ca c.l t\l ro I Ib aa, t) (.) I I=U g ,r I e ,E (l)cn e,; l;^1fl^l I J- tt I lEb =9 E5 II! c 2 o.) A t tra I I u);E c 6F U I lb; -oo I l';q.) /ggg I I U) t; /ff/gg I I on3=-o tro0 ;c'i, r I I Ir-'- =: .Oa I +i LqtI !Ha I ltss 2q) (\,^L;() Fi lie I 3r I;'s I lgs r- o' tsr I H; I ooii5l r& C)q) ,aQ 6g P:E 'E oo I I I I |IsEE '= e-o -r(B 5J I ;€ I l tstrq)=!; E OF lq.)vo)I EI tr- .= ='E | * 2 tr oo! gI gf dL E .=(g sE I I E€ I a Ese 2a l ro TE Iqf,IEH IEEE E I E B= -uEs l SE I EE l SEi i I 3t" 9 0) t- 5 -ooo0) 6)tl- I 5 E-S (r) I al .OA a6 LIE\F,t-- ^ I .i oa L 5 I b EQ >.=7 etfl[:liclIEg u I a Eii C)E General Course Information Course Code: PCC-CSE2}| -T I course Assessment PCC-IT2O I -T Methods (internal: 30; external: 70) Two minor examinations (20 marks), crass performance Course Credits:3 measured through percentage of lectures attended (4 marks), assignments (6 Type: ?rofessional Core marks), and the end- semester examination (70 marks). Contact Hours: 3hours/week For the end semester examination, nine questions are to be set Mode: Lectures (L) by the examiner. A candidate is required to attempt 5 questions in all. All questions carry Examination Duration: 3 hours equal marks. euestion number I will be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Programming in C About the Course: Data Structure and Algorithms core is a and an essential course for every graduate in Computer Science and Engineering. This course introduces data structures like arrays, linked lisis, trees and graphs etc. and various operations to be implemented on these data structures for solving real world problems. It includes various sorting and searching algorithms as well. Further, it incorporates complexity analysis of algorithms implemented on various data structures. course outcoryes: By the end of the course students will be able to: COI' describe various types of data structures and operations that can be implemented on these data structures. (LOTS: Level l: Remember) CO2. demonstrate the use of various data structures and their related operations. (LOTS: Level 2: Understand) CO3' apply data structure to solve computational problems. (LOTS: Level 3: Apply) CO4' compare the suitability of alternative data structures and prescribed operations for various problem situations. (HOTS: Level 4: Analyse). CO5. defend solutions with respect to effective storage of data and efficiency of the required operations for solving real world problems. (HOTS: Level 5: Evaluate) Course Content Unit I Introduction to data structures and their types, Abstract data typeq, Linear lists: Arrays and linked lists: memory representations, implementing operations like traversing, searching, inserting and dlleting etc. Applications of alrays and linked lists. Representing sets and polynomials using linked lists. Unit II Stack and Static and Queue: linked implementations, Operations and Applications. tircular queues, Tress, Binary trees and related teiminology, Tree traversals (Recursive), glr..y implementationandoperations,PriorityqueueS.i;i,Thread.d Birury Tree!, i.rr.i, fr.., ' i "1" 5''n ve- '"" ' ", Unit III Height Balanced or AVL trees and B trees. Graph definitions and related terminology, memory representations and related operations (traversal, insertion, deletion, search), Path Matrix, Warshall's Shortest path algorithm Hashing, Hash tables, hash function and collision resolution. Unit IV Sequential and binary search, Sorting algorithms: Bubble sort, Selection sort, Insertion sort, Quick sort, Merge sort, Count sort, Heap sort, Comparison of searching and sorting techniques based on their complexity analysis, Time and space complexity of algorithms: Asymptotic analysis, Big O, Omega, Theta notations. Text and Reference Books: l. Aho, A. V., Ullman, J. D., and Hopcroft, J. E., Data Structures ancl Algorithms, Addison-Wesley, I 983. 2. LangsamYedidyah, Augenstein J Moshe, Tenenbaum M Aaron, Data Structures ttsing C ond C++, 3'dedition, PHI,2009 3. Cormen, T. H., Leiserson, C.E., Rivest, R. L. and Stein, C., Introduction to Algorithms,MlT press, 2009. 1. Robert L. Kruse, Data Structure and Progratn Design in C,Pearson Education India ,2007. 5. Weiss, M. A., Data Structures and Algot'ithm Analysis in C+-r, Addison-Wesley, 2007. 6. Sahni, 5., Data Structures, Algorithms, and Applications in C t+, WCB/McGraw-Hill,200l. 28 ro ao (-.I c.l 6l N o V) I N a.l c\l (a an co a.l c.) co al o I 1 I FI t-{ i I t (\ r-'l a- U I U U t I q) € (t) I fr ! r- U an \o I t L ra bo I C! I 41 :f, (n ca q) I o\ f( I \ a-l c) N I C-.l a.J ca tr a orlol c.l C..I ca e) I vt l.= lClo-l X a L 13 l€ I r le 0) s lr I l.'( Ig (, lH,^. -oo a I ldg IrE o. Ed lSe: ;{ lE;x I oZ la 5J I o ..) IEE IEE 5E l9Ea I c) IEH lsi :) l?T lec-.r o- L l.= o) le- I laalaC) ;l l*sg o I a c) l= >l (-) 0)I sE l:gE lti 2t\, !l l€:El:Ii aol o O -,1>.1 8I I r e E I cl P :E lria lnl e3l-l rrHElr?l General Course Information Course Code: PCC-CSE2}2-T / Course Assessment Methods (internal: 30; external: 70) PCC-IT2O2-T Two minor examinations (20 marks), Class Performance measured through percentage of lectures attended (4 marks), Course Credits: 3 assignments (6 marks), and the end- semester examination (70 marks). Type: Professional Core For the end semester examination, nine questions are to be set Contact Hours: 3 hours/week by the examiner. A candidate is required to attempt 5 Mode: Lectures (L) questions in all. All questions carry equal marks. Question number I will be compulsory and based on the entire syllabus. Examination Duration: 3 hours It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-reqtrisites: Knowledge of computer fundamentals and probiem solving using C programming About the Course: Objected Oriented Programming using Q++ is an essential course for every graduate in Computer Science and Engineering. This course introduces the Object Oriented concepts such as data encapsulation, data hidin g, data abstraction, reusability, exception handling etc., and their implementation using C++. Course outcomes: By the end of the course students will be able to: COl. List the concepts related to object oriented paradigms. (LOTS: Level 1 : Remember) CO2. Distinguish between structured and object oriented approaches to programming. (LOTS: Level2: Understand) CO3. Apply object oriented constructs for problem solving. (LOTS: Level 3: Apply) CO4. Detect logical and run time errors and suggest appropriate modifications. (HOTS: Level 4: Analyse) CO5. Justify the design of a program for a given problem. (HOTS: Level 5: Evaluate) CO6. Design solutions to progranrrning problents using multiple object orientecl programming constructs together. (HOTS: Level 6: Create) Course Content Unit I . Introduction to object oriented programming, C++ standard library, basics of a typical C++ environment, illustrative simple C++ programs, new features of ANSI C++ standard, OOPs concepts: Information hiding, encapsulation, data abstraction, access modifiers, controlling access to a class level, method, or variable (public, protected, private, block level, scope and mutable), other modifiers. Structure of class and struct in memory, accessing members of strucfures, Class scope and accessing class members, separating interface from implementation, pre-processors directives, macro programs, header files and namespaces, default constructors, chained constructor, default arguments with constructors, constant object and const member functions, object as member of class, use of destructors, virtual destructors, controlling access function and gtility functions, function overloading. ',.. ,r#tfli{i' ttf tu' :.f | .*t 30 t! Unit II Inline function, friend function and friend classes, using this pointer, dynamic memory allocation with new and delete' static class members, proxy class, polymorphism concepts, overloading, overriding methods, abstract classes' reusability, class's behaviors, inheritance, base classes and derived classes, protected members, base-class pointers casting to derived-class pointers, using member functions, overriding base-class members in a derived-class, public, protected and private inheritance, using constructors and destructors in derived classes, implicit derived-class object to base- class object conversion, composition vs. inheritance. Unit III virrual functions, abstract base classes and concrete classes, new classes and dynamic binding, virtual destructors' fundamentals of operator overloading, restrictions on operators overloading, operator functions as class members vs. as friend functions, ((, overloading, )) overloading unary operators, overloading operators' binary I/o streams, files handling, creating a sequential access file, reading data from a sequential access file' updating sequential access files, random access files, creating a random access file, writing data randomly to a random access file, reading data sequentially from a random access file. Unit IV Managing colrsole I/o, stream input/output classes and objects, stream output, stream input, unforrnatted (with read I/o and write), stream manipulators, stream format states, stream error states, exception handling, basics of c++ exception handling(try, throw, catch), rethrowing an exception, specific exception, processing unexpected exceptions, stack unwinding, exception handling in constructors and destructors, exception inheritance with introduction to generic classes, function tenrplates, overloading template functions, class template, non-type parameters, templates and inheritance, templates and friends, templates and static members, container, iterator, algorithm and functional classes. Text and Reference Books: l. H. M. Deitel and P. J. Deitel, prograffi, C++ 11o* To 6,h Ed., prentice Hall, 200g. 2. Robert Lafore, Object-Oriented programming in C++,3d Ed., Sams publishing 2001. 3. D. Ravichandran, programmingwith , C++,3d Ed., T.M.H, 2lll. 4. E. Balagurusamy, Object orientecl programming with C++,6,h Ed., Tata McGraw_Hill, 2013. 5. Horstmann, Computing Concepts with C++ Esientials, 3.d Ed., John Wile y,2003. 6. Herbert Schildt The , Contplete Reference in C+*, 5,h Ed., TMH ,2012. 3l cro U) N a (ao a\t rn co ca aa aa .I FI 6l ric.t a l U I U U c) o\ v) U @ + + r- U bo \o U) u0 rn C! l a! = bo (.a N ca .I () N co ca q) tr C.l (-.l c.,l cn CJ lo a q) IF F a C) F l() lo o y't cg (, lz" l-r | .< l" ti< I la bb l=\-/ l< ; IFE L IE () 't o. () t.-lb0 lao l'o o (g -o 6 (.) a laSl.E IE l- a !< z Ica E 0) o. l)6-) o q a0 Ia oD lo. 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U, j c-.i r. d.o r- od 6 o oc oo (-, c (J ()L) a) U sl UU U U J Discrete Mathematics General Course fnformation Course Code: PCC-CSE 203 -T I Course PCC-IT203-T Assessment Methods (internal: 30; external: 70) Two minor examinations (20 marks), crass performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Core marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required Mode: Lectures (l) to attempt 5 questions in all. questions All carry/ equal marks. euestion number I will Examination Duration: 3 hours be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question fromeach of the four units. Pre-requisites: Basic knowledge of Number Theory calculus and Algebra About the Course: Discrete Mathematics is a core and an essential course for every graduate in computer Science and Engineering. This branch of mathematics rnainly deals with discrete objects (as computer runs on discrete steps). It provides a mathematical language for computer science to resolve many real world problems by incorporating different methods applicable to various discrete structures. This course introduces set theory propositional calculus, algebraic structures, recurrence relations and graph theory. course outcomes: By the end of the course a student lvould be able to: COl outline various discrete ' structures and the related operations. (LOTS: Level l: Remember) co2' illustrate different discrete structures with the help of examples. (LoTS: Level 2: understand) Co3' apply appropriate techniques to solve problems related to discrete structures.(LoTS: Level 3: Apply) CO4. justify the solutions with the help of proofs. (HOTS: Level 5: Evaluate) Co5' combine techniques related to discrete structures for solving real world problems. (HorS: Level 6: Create) Course Content Unit I . Set Theory: Introduction to Set Theory, venn Diagrams, Set operations, Algebra of Sets, Duality, Finite, Infinite Sets and Counting Principle, Classes partitions, of Sets, Power Sets, Multi Sets, Relations: Cartesian Product, Representation of Relations, Types of Relation, Equivalence Relations and partitions, partial ordering Relations, Functions: Definition, Types of Functions, composition of Functions, Inverse Functidn, Recursively Defined Functions \ ) i :l.:7 I I JJ Unit II Logic and Propositional Calculus: Introduction, Propositions and Compound Propositions, Basic Logical Operations, Propositions and Truth Tables, Tautologies and Contradictions, Logical Equivalence, Algebra of Propositions, Conditional and Bi-conditional Statements, Algebraic Structures: Group Axioms, Monoid, Semi- Groups, Subgroups, Abelian Group, Cosets, Normal Subgroup, Cyclic Croup, Permutation Group, Lagrange's Theorem, Homomorphism, Isomorphism, Automorphism, Rings, Integral Domains and Fields (Also, some basic and standard results related to Groups, Rings, ID and Fields). Unit III Recursion and Recurrence Relation: Polynomials and their evaluation, Sequences, Introduction to AP, GP and AG Series, Partial Fractions, Recurrence Relation, Linear Recurrence Relations with Constant Coefficients, Linear Homogeneous Recurrence Relations with Constant Coefficients, Particular Solution- Homogeneous Linear Difference Equations, Non-Homogeneous Linear Difference Equations, Total Solution, Generating Functions. Unit IV Graphs Theory: Introciuction to Graphs, Ir4ulti Graph, Directed and UndirecteC Graphs, Subgraphs, Bipartite Graphs, Regular Graphs, Connected Graphs, Homomorphic and Isomorphic Graphs, Cut points and Bridges, Paths and Circuits, Euler Graph, Hamiltonian Graph, Planar Graph, Euler Fonnula, Weighted Graphs, Dijkstra's Shortest Path Algoritlun for Weighted Graphs, Trees, Spanning Trees, Mininrultr Spanning Tree (Prirn's and Kruskal's Algorithm). Text and Reference Books: 1. J.P. Trembley and R. Manoh ar, Discrete Mathematical Structures with Applications ro Computer Science, Tata McGraw Hill - 13th reprint, 2012. 2. Kenneth H. Rosen , Discrete Mathematics and its applications,6th Edition, Tata McGraw Hill, 201 l. 3. Richard Jolursonbaugh, Discrete Mathematics,6th Edition, Pearson Education Asia, 2011. 4. S. Lipschutz and M. Lipson, Diso'ete Mathematics,TataMcGraw Hill, 3'd Edition, 2010. 5. B. Kolman, R. C. Busby and S. C. Ross, Discrete Matheruaticol stntctr.u'es,6'h Edition, PHI, 2}rc. 6. C. L. Liu, Elements of Discrete Mathematics, Tata McGraw Hill, 3rd Edition, 2008. -'- _-*.'.:l-/!:$f 'f"' *-* r@, T 34 F roI c.l E] U) U I U U a) a L U (a c) q) \ at- c) tr) q) aa L q) v) xl e) LI ul 6El alF{ I oltrl 6{l ()l +1;l : LI *.{ ",:'# / cl, \F"tt +l; UIcl- t, OV) q)}' 5^=F sE3 6 3\o .h (J .n O!r= \J Q).A\ c) boy l< () )_ -: c.i ..r; (J L' + Q - o U O Computer Organization and Architecture General Course Information Course Code: PCC-CSE2}4-T Course Assessrnent Methods (internal: 30; external: 70) PCC-IT2O4-T Two minor examinations each of 20 marks, Class performance Course Credits:3 measured through percentage of lectures attended (4 marks) Assignment and quiz (6 marks), and end semester examination Type: Professional Core of 10 marks. Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set Mode: Lectures by the examiner. Question number one will be compulsory and based on the entire syllabus. It will contain seven short Examination Duration: 3 hours answers type questions each of marks 2. Rest of the eight questions are to be given by setting two questions from each <-rf the four units of the syllabus. A candidate is required to attempt any other four questions selecting one from each of the remaining four units. All questions carry equal marks. Pre-requisites: Digital Electronics and computer systems. About the Course: Conrputer Architecture and organizatton describes the role of instruction set architecture in digital cornputer, main memory and input/output devices. It illustrates the sirnple data path and control design for processors. It helps to understand the different operations and concept of instructions. It would enable the students to learn the basic function and architecture of modern computer systems. Course outconres: By the end of the course students will be able to: COl. outline the general concepts of digital electronics and computer organisation and architecture. (LOTS: Level l: Remember) CO2. discuss the basic components and their interfacing.(LOTS: Level 2: Understand) CO3. apply instructions for performing different operations. (LOTS: Level 3: Apply) CO4. analyse the effect of addressing modes on the execution time of a program.(HOTS: Level 4: Analyse) CO5. contrast different types of memory, their architecture and access methods. (HOTS: Level 5: Evaluate) CO6. Design of simple computer with different instruction sets. (HOTS: Level 6: Create) Course Content Unit I Basic Principles: Boolean algebra and Logic gates, Combinational logic blocks (Adders, Subtractors, Multiplexers, Encoders, decoders, demultiplexers, KMaps), Sequential logic blocks (Flip-Flops, Registers, Counters); Flynn's classification of computers (SISD, MISD, MIMD); Performalce metrics: MIPS, MFLOpS; CPU Architecture tlpes: computer register, (accumulator, register, stack, memory/ register) detailed data path of a typical register based CPU. + .;. ,i... \gu -.'S \36 Unit II computer organization: Store program control concept, Instruction codes, timing and control, instruction cycle; type of instructions: memory reference, register reference, I/o reference; Basics of Logic Design, accumulator logic' control memory; Micro Programmed control: address sequencing, micro-instruction formats, micro- program sequencer, Implementation of control unit. Unit III Instruction SetArchitecture & Parallelism: Instruction set based classification of processors (RISC, GISC, and their comparison); Stack organization, Instruction Formats; addressing modes: register, immediate, indirect' indexed; direct, operations in the instruction set: Arithmetic and Logical, Data Transfer, control Flow; Types of intemrpts; Introduction to Parallelism: Goals parallelism of (Exploitation of concurrency, throughput enhancement); Anrdahl's law; Instrtlction level parallelism (pipelining, super scaling -basic features); processor level parallelism (Multiprocessor systems overview). Unit IV Memory Hierarchy & rlo Techniques: The need for a mernory hierarcrry (Locality of reference principle, Memory hierarcliy in practice: cache, main menrory and secondary mernory, Menrory time' parameters: access/ cycre cost per bit); lvlain memory (Semiconductor RAI'I RoM & organization, memory expansion, Static & dynamic memory types); cache memory (Associative & direct mapped cache organizations; interface, input-output mode of transfer, DMA (Direct memory trans{br). :-r. Text and Reference Books: 1 Mano, M' Morris Digital ' , Logic crncl Computer Desigr, Prentice pvt. gg Hall of India Ltd., l l . 2' M' Morris Mano, contpttter system Architecture,Prentice Hall of India pvt. Ltd., 1993. 3 ' Milles J' Murdocca, vincent P' Heurin g, Computer Architectltre ancl organization, An Integratecl Approach, JohnWiley & Sons Inc., 2A07. 4' william Stallings, lOth edition, computer organizcttion ancl Architecture,prentice Hall, 2016. 5' Heuring, v'P-, Jordan, H.F., Compttter systemts Design ancl Arcltitecture, Addison wesley, lgg7. 6' R'P Jain, Modern Digitat Elecrronics,3'd Edition ,TataMcGraw Hill,, 2003. T.tw J/ CO a I 6t .ac a N r^ rn co cn cn N F-'( r+! (\t ari U c I I U U l*{ I a0) o\ U q) fr 6 (.) C) r- a) c \o o in s l C\ co N cn = bo L( C (,O li q) ol o a{ N C..l - :.."i- !r\:,r' o U t{'t" .--tA * C.l c.l N ca F( e t9 + l>l6 lu- Ic) t: l- o) IJ 'O a\ I,,^ lu lo) lv oJ !- I'o Ir- I'6 ca :.- 0) l- c 1.0.) ()P =6 lr -t 15F l- (s J^t l'6 s lq- .0) 0.) a.=o) l-a. t^ lY a lao iF r- la F l->.H *< 9E A l= b ao -b tL: E It)(,0) I-O E ov fr Itr c oO rF -q \i, 1 Ir D ()!=(h '=o.> F ,90- I: a I Itr 6r ac q-E=o q) General Course Information Course Code: PCC-CSE20l -P / course Assessment Methods (internal: PCC-IT2O I -P 30; external: 70) The internal and external assessment is based on the level of Course Credits:2 participation in lab. Sessions and the timely submission of lab experiments/assignments, Type: Professional Core Lab. Course the quality of solutions designed for the assignments, the performance in vIVA-vocE, the quality Contact Hours: 4 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignments The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the controller of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Programming in C language. About the Course: This lab' cotlrse involves itnplernentation of basic and advance data structures and various operations on these data strucfures' The objective of the lab course is to train the students to solve the problerns related to data structures and choose the appropriate data structure for solving computational problem efficiently. Course Outcomes: By the end of the lab course a student lvould be able to: COl. Implement various data structures and the related operations. (LOTS: Levels 3: Apply) CO2. Analyse space and time complexity of algorithms. (HOTS: Level4: Analyse) Co3' io-put. solutions on the basis of the appropriateness of data structure used and the efficiency of the operations irnplemented. (HorS: Level 5: Evaluate) Co4' Integrate knorvledge of data structures to solve real world problems related to data structure and algorithms. (HOTS: Level 6: Create) CO5' Create written records for the given assignments with problem definition, design of solution and conclusions. (HOTS: Level 6: Create) CO6' Demottstrate ethical practices while solving problems individually or in groups (LoTS: Level 3: Apply). List of experiments/a ssignments l Two assignments ' related to creating and manipulating matrices and linear lists. Two assignments 2' associated with linked list, operations on linked Iists and their applications. 3. Two assignments on alTay and linked implementation of stacks and queues. 4. Two assigrunents on trees and their applications. ( 5. Two assignments on graphs and their applications. 6' Two assignments on different searching and sorting methods along with their complexity analysis. 7 ' One assignment on challenging problems on data structures to be given in groups. Note: The actual experiments/assignments will be designed by the course coordinator. One assighment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and- JhaOrt" of subntission will be prepared by the course coordinator tl at the beginning of the semester. \p"trl'-Y t '\ -r" ,L 39 7 .,. ./\ r- \"v( (P\-v t .o ao I N a t I , a c.l ca cn CO t1.{ ! .l I I c-) 6l r-l a-l U I U C U () a I an L{ o\ U (-.l (a J a a aa r- $ tr uo 41 \r- \ I I l V .i \ .,, rn 0 \ () I :ii \ ,r "-d,d+' !f, c.) I I rd L a ra ca l-,i X c.l ,r I N N zt-( C.l c{ N ca lo lE le la ta qi l^-\o IF t-lo- I I'O l=o) IJ lcra d lo IY-g) t-tvlo l! (g lo l6 - l= -o = lc t, ? L lb 3 = l5 q l q2 dr^:q l= b0 4l\ l0 e l'n i E lP E-J l.:.e a .E- l= 02 l0) (g l:3 t-- I ho.: c l.= e t! ta Y.a a ,- I; -l loIF lo i.9 o)v o- l+J \v A tE u) I{ lia l3< l8 ?-\ -CeC)= I t = i6=\Jv- lirt- O (J LI O(g q- tYt -I ItE;e v)Y =rJo leIJO ()0) ! c\ t(di-. oEa (ho)X a(J-: r! U !0) (s lL, ! o-.. 0()o)c; a la q) =ai;-3eii oal h0- (B.:= (J L3 I T or --n-(D q, .'- EE:or-= o-O r-r U) EA 2 Fl r< !- o-)O\v O q) .4.e i CdF 5k€ol L -c.=.l.p\ Q 0)^ 5alP o,n o.h .nl o <-r X t-a o)'='.=== ol o, E q) eO-I ._al E'E'6 9l L0)L-^ ^ . -t U) ts^l I+ r-) t- el EO r- a'a 9ltrnl o.6 c!'r-.l tr o q- o.ll x E:(j1 E: r-l '6=, trL General Course Information Course Code: PCC-CSE 202-P I PCC.IT202-P Course Assessment Methods (internal: 30; external: 70) The internal and external assessment is based on the level of Course Credits: 2 participation in lab. sessions and the timely submission of lab Type: Professional Core Lab. Course experiments/assignments, the quality of solutions designed for Contact Hours: 4hours/week the assignments, the performance in vIVA-vocE, the quality of lab. file and ethical practices followed. Mode: Lab practice and assignments The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the Controlrer of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Problem solving using C Lab. About the course: The lab course provides the opportunity io students to solve problems using Object Oriented Framework in C++ language. This includes implementing the concepts of data abstraction, data hiaing, and encapsulation, reuse of code and, compile and runtirne polymorphism. course outconres: By the end of the course students will be able to: COl. implement problems with object oriented framework. (LOTS: Level 3:Apply) CO2. analyse the structure of programs for modular design. (HOTS: Level 4: Analyse) CO3. evaluate robustness of a program by testing it on test/use cases. (HOTS: Level 5: Evaluate) design CO4. class hierarchies for implementing inheritance/polymorphism. (IIOTS: Level 6: Create) create a lab CO5- record of assignments including problem definitions, desigl of solutions and conclusions. (HOTS: Level 6: Create) CO6' demonstrate practices ethical and solve problems individually or in a group. (LOTS: Level 3: Applv) List of assignments l. Create two classes DM and DB which store the value of distances. DN{ stores distances in meters and centimeters and DB in feet and inches. Write a program that can read values for the class objects and add one object of DM with another object of DB. Use a friend function to carry out the addition operation. The object that stores the results maybe a DM object or DB objects, depending on the units in which the result is required. The display should be in the format of feet and inches or meters and centimeters depending on the object on display 2. create a class rational wltich represents a numerical vdlue by two double values- NUMERATOR & DENOMINATOR. Include the following public member Funciions: . constructor with no arguments (default). . constructor with two arguments. void reduce 0 that reduces the rational number by eliminating the highest oommon factor between' i t,ir, ' the numerator and denominator. ' Overload + operator to add two rational number. 41 ' Overload >> operator to enable input through cin. ' Overload << operator to enable output through cout. Write the main 0 function to test all the functions in the class. 3. A hospital wants to create a database regarding its indoor patients. The information to be stored includes a) Name of the patient b) Date of admission c) Disease d) Date of discharge Create a structure to store the date (year, month and day as its members). Create a base class to store the above information. The member function should include functions to enter information and display a list of all the patients in the database. Create a derived class to store the age of the patients. List the information about all the pediatric patients (less than twelve years in age). 4. Make a class Employee with a name and salary. Make a class Manager inherited from Employee. Add an instance variable named department of tlpe string. Supply a method to to Stringthat prints the manager's narne, departntent and salary. Make a class Bxecutive inherited from Manager. Supply a method to Stringthat prints the string "Executive" followed by the information stored in the Manager superclass object. Supply a test program that tests these classes and methods. 5. Imagine a tollbooth with a class called'tollBootlr'. The two data items are of type unsigned int to hold the total number of cars, and a type double to hold the total amount of money collected. A constructor initializes both to 0. A member ftrnction called 'payingCar0' incrernents the car total and adds 0.50 to the cash total. Another function, called 'nopayCar 0', increnrents the car total but arjds nothing to the cash total. Finally, a member function called displays the two totals. Include a program to test this class. This program should allow the user to push one key to count a paying car, and another to count a nonpaying car. Pushing the ESC kay should cause the prograrn to print out the total cars and total cash and then exit. 6. Write a function called 'revers_itQ' that reverses a string (an array of char). Use a for loop that swaps the first and last characters, then the second and next to last characters and so on. The string should be passed to 'revers_it 0' as an argument. Write a program to exercise 'revers_it 0'. The prograrn sl'rould get? string from the usercall ofrevers_it 0 function and print out the result. Use an input method that alloivs ernbedded blanks. Test the program with phrase, "Glolt Jcmtblteshwcrr (Jniversity of Science & Technology, Hisar". 7. Write a program related to file handling with all the exception handling provisions. 8. C++ program to write and read tirne in/from binary file using fstream. Use exception handling wherever possible. 9. Write a,program to implement string classusing STL. 10. Write a program to implentent run time polymorphism. Note: The experiments/assignments may vary from session to session and will be designed by the course coordinator. The assignments must meet the objective of the course and the levels of the given course outcomes. The course coordinator will provide the schedule for submission of the assignment. L r'. rpl .5 4 ).y i 42 Fr 6l! 6t arc U t U U t] + + U bo i l),t q) ..1:l bo / L obo L l*t sca q) q) fr I e) q) c a 7, ; U) P lil :i eo c, 0)=? \-,/ +. I o a) 0) a 6 '-' Gi B () 0d 0) () ZvL o :< cn E l- .\ 63 EI Q boo .e .7 ,ts bo o\ ol .i, .= .n 1< {-I bO* rC]= o. ca 0.) dl U) -0) )o q) (-) ! 96 q) !- =q')0) F/ co (JI=l ti .o o cA)oq gt o U) -o Aa LI o 6? CA 0) (d =0) o-h o)co (gF ,- i6 'rA a(1 3 bo bo= o: J:. ol o fo.9 o-l c!t Arl l.IoJ!^ a (+- €i a= o-: C..t >-. a (c- aa (go (H 1-) tI] dl Aa an o-o a ()cd b,; o9< L. ()l- Q UI eo. (n() -rf o Ebo ,l (t) 0)< (-) 0)hr d ,d .9C6 () o t-I r General Course Information : Course Code: PCC-CSE2A5-T I Course Assessment Methods (internal: 30; external: 70) PCC-IT2O5-T Two minor examinations (20 marks), Class Performance measured through percentage of lectures attended (4 marks), Course Credits: 3 assignments (6 marks), and the end- semester examination Type: Professional Core (70 marks). Contact Hours: 3 For the end semester examination, nine questions are to be set by the examiner. A candidate is required attempt 5 Mode: Lecture (L) to questions in all. All questions carry equal marks. Question Examination Duration: 3 Hours number I will be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: The students are expected to have a strong background in the Computer Organization Digital System Design. About the Course By the end of the course students will be able to: COl. outline the architecture of 8085 and 8086 Microprocessor. (LOTS: Level 1: Remember) CO2. discuss the basic principles of addressing modes, pin diagrams. (LOTS: Level 2: Understand) CO3. describe the functionality of various peripheral chip (LOTS: Level 2: Understand) CO4. apply the concepts of interfacing of Memory Input/output with Microprocessor. (LOTS: Level 3: Apply) CO5. compare and contrast the working of 8085 and 8086 microprocessors. (HOTS: Level 5:Evaluate) CO6. develop Assembly Language programs for 8085 and 8086 microprocessor.(HOTS: Level 6: Create) Course Content Unit-I Introduction to microprocessor, 8085 microprocessor architecture, instruction set, interrupt structure, Architecture of 8086, block diagram of 8086, details of sub-blocks such as EU, BIU; memory segmentation and physical address computations, program relocation. Unit II Addressing modes, instruction formats, pin diagram and description of various signals, Instruction execution timing, assembler instruction format, data transfer instructions, arithmetic instructions, branch instructions, looping instructions, NOP and HLf instructions, flag manipulation instructions, Iogical instructions, shift and rotate instructions, directives and operators. Unit III Assembler directives, Programming with an assembler, Programrning examples, coding style, the art of assembly language programming. Software Development with Intemrpts, Introduction to Stack, Stack Structure of 80 Introduction to Subroutines, Recursion, MACROS. BIOS (Basic Input/Output System), DOS (Disk 44 Unit IV The 8255 PPI chip: Architecture, control words, modes and examples. Introduction to DMAprocess, 8237 DMA controller. 8259 Programmable intemrpt controller, Programmable interval timer chips. Text and Reference Books: 1. Ramesh S Gaonkar; Microprocessor Architecture, Programming & Applications with B0B5,Wiley Eastern Ltd.,5th edition, 2002. 2. Brey, The Intel Microprocessors 8086- Pentium processor, PHI, 8'l' edition ,2009. 3. Douglas V Hall; Microprocessors and Interfacing, TMH, 2000. 4. Triebel & Singh; The B0BB & 8086 Microprocessors-Programming, interfacing, Harclyvore & Apptications, PHI, 4th editio n, 2003. 5. Yu-Chang Liu & Glenn A Gibson ; Microcontputer systems; the 8086/80B8 Family.- architecture, Programming &Design, PHI, 1986. i\ ,\ \ ,t Alt :A wry- -.ti\ ' .; , - .t:. .: - ,,.'l/ 45 t-( rnI a.l af-l U I U U o U) L( I U bo CJ ti 0) )r( \o \f, t- $ U) rt) q) q) l- L I a :r F \o lrl ao z a o oo 0) J O o \o @ t-o 'a o. co o o O. oo = l- c); -o tr) .9 (_, d oo o !- ,F U 'a? l General Course Information Course Code: PCC-CSE2O6-T / course Assessment PCC-IT3O I -T Methods (internar: 30; externar: 70) Two minor examinations (20 marks), crass performance Course Credits:3 measured through percentage of lectures attended (4 marks), assignments Type: Professional Core (6 marks), and the end- semester examination (70 marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set Mode: Lectures (L) by the examiner. A candidate is required to attempt 5 questions in all- Examination Duration: 3 hours All questions carry equar marks. eueition number I will be compursory and based on the entire sylrabus. It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the sylrabus. A candidate is required to attempt the remaining four questions by selecting or" question from each of the four units. Pre-requisites: Basic knowledge of Digital and Analog communication. About the Course: This course has been designed with an aim to provide students with an overview of the concepts and fundamentals of data communication and computer networks. The learner is given an opportunity to grasp various algorithms for routing of data, for*aiding data and switching the data from hop to hop. Layered Architecture adds value to the subject contents. Course outcomes: By the end of the course students will be able to: col ' outline various tnodels, topologies and devices of computer Netrvorks. (LorS: Level l: Remember) co2' explain the functions of various layers in Network Reference Model. (LorS: Level 2: understand) co3' apply different network concepts in various network communication protocols. (LorS: Level Applv) 3: CO4' analyse performance of various protocols in different scenarios. (HOTS: Level 4: Analyse) co5. design network for an organisation. (Hors: Level 6: create ) Course Content Unit I Data communication: components, Data representation and Data flow; Network: IJses, Topologies, Network Services' oSI and TCP/IP Reference Modeis; Network.*g"ri*, iaN, MAN, wAN; Guided Transmission Media' wireless Transmission Media, Switching Techniqu.J, ci..* Switching, packet Switching, Message Switching, Networking Devices: Hubs, Repeater{ Bridges, Modems, Switches, Routers, and Gateways. Unit II Data Link Layer-design issues, Framing & Error protocols, Handling: Framing Error detection and correction mechanisms; Flow control'Protocols: Stop-and-wait, stialng winiow protocols: Go-back-N and Selective Repeat; Medium Access sub layer: channel allocation meth-ods, Multiple Access communication: Access-ALoHA, Slotted-ALoHA, Random csMA, csMA-cD, LAN Standardi: Ethernet, Ethenret. Fast Erhernet & Gigabit 47 Unit III Network l:yer-Design issues, store and forward packet switching connection less and comection oriented networks, , Routing algorithms: optimality principle, shortest path, flooding, Distance Vector Routing, Count to Infinity Problem, Link State Routing, Hierarchical Routing, Congestion control algorithms, admission control. Internetworking: IPV4 and IPV6, IP Addressing (Classful Addressing, Private Ip Addresses, Classless - Addressing,Sub-netting),ARP,RARp,ICMp,IntemetRoutingprotocol. Unit IV Transport Layer: Transport layer Services: Addressing, Multiplexing, Flow control, Buffering and Error control. Internet Transport Protocols: UDP, TCP, TCP Segment, TCp connection. Application Layer: Introduction to DNS, FTP, TELNET, HTTP, sMTp, Electronic Mail, www and Multimedia. Text and Reference Books: l - Andrew S Tanenbaum, Computer Networks, 5th Edition, Pearson publications, 2010. 2. Forouzan, Data Communication and networking,5th Edition, Tata McGrawH ill,2Al2. 3. William Stalling, Data & Contputer Communication 6th edition, LPE Pearson Education ,20t3. 4. Todd Lammle, CCNA Study Guide,6th Edition,2013. 5. RFCs and Intemet Drafts available from Internet Engineering Task Force. er.- 48 Fr \oI N r-'l a Q I U U q) O lr U a li zq) ()li \) o\ $ UIol XI '-l Y ztF{l oltrL .t-. I l' - "ffi c.)l (a () EI Q N 2 .=a-0) ' ;;r q) (Jl-)a -;r' tr6 -i tu cl € L- O, I a(.) (gU rl c 0.) t-l ()H 3< cl ao) .; =.v t- 0.)J .-Fi" an t') UI '- 0.) o bo ,.; (n if- o q.)? (tr o'ql- lq) a F 5-r o9 (J) I (J t- t- \o o- OY (g OJ ()o- l" (, bn q-< -o CN U) l-:l t O62 tll U) oO o.Yr-= Eb a 6+ a)I (g!(g () ov 0) I oy .r- (_) .:o^(J 6.e dut d) L'- V E? U 9) j\o a. Eg L L 3z A\ L>-- A L ,Ee Itro. (k=jEC oo) o .g) o- t- 0) u- EB q.) :e?9\./(6 = &; = 'o \u qts 3i -Era t) :- >rP ooFtra 'a= aeV - 6 ,g) xg= a.i-- i9 o,t4) q. esi General Course Information Course Code: PCC- CSE201-T| Course Assessment Methods PCC-IT2O7 -T (internal: 30; external: 70) Two minor examinations (20 marks), class Performance measured Course Credits: 3 through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Core marks). For the end semester examination, nine questions Contact Hours: 3 hours/week are to be set by the examiner. A candidate is required to attempt 5 questions in all. Mode: Lecmres (L) All questions carry equal marks. Question number l will be compulsory and based on the entire syllabus. Exam Duration: 3 hours It will contain seven parts of 2 marks each. Question numbers 2 to 9 will be given by setting two questions frorn each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Prerequisite: Knowledge of IINIX, Windows, a. programming language and data structures About the Course: This course includes a detailed coverage of principles of database design and models. Students leam querying a database using SQL, normalization techniques, transaction processing etc. course outcomes: By the end of the course students will be able to: CO1. describe fundamental elements of Database Management System. (LOTS: Level l: Remember) CO2. discuss principles of relational Database modelling. (LOTS: Level 2: Understanding) CO3. apply SQL for designing queries for Relational Databases. (LOTS: Level 3:Apply) CO4- contrast various concurrency control and recovery techniques with concurrent transactions in DBMS. (HOTS: Level 5: Evaluate) CO5' design models of databases using ER modelling and normalization for real life applications.(HOTS: Level 6: Create) Course Content Unit I Overview: Overview of File Systems and Database Systems, Characteristics of the Data Base Approach, Database users, Advantages and Disadvantages of a DBMS, Responsibility of Database Administrator. Data Base Systems Concepts and Architecture: DBMS architecture and various views of Data, Data Independence, Database languages, Data Models: Relational Database Model, Hierarchical Data Model, Network Data Model, Schemas and Instances. Unit II E-R Model: Entity Types, Attributes & Keys, Relationships, Roles and Structural Constrainrs, E-R Diagrams, Reduction of an E-R Diagram to Tables. Relational Model and Query Language: Overview of Relational Database, Key Integrity Constraints, Relational Algebra, Relational Calculus, SQL fundamentals, Basic Operators, Missing information and NULL values, Advanced SQL features ._ ..,.....,.,.- 50 Unit III Relational Database Desig,: overview of normalization, Database Anomalies, Functional candidate and Super Key, Dependencies, Integrity constraints, Decomposition, Normal Boyce forms: ri.r,, Second, Third Normal, codd' Normal Form, Multi-valued Functional Dependencies 'vrvo andsrrLr Fourthr uur tr Normal Form; Join Dependencies and Fifth Normar Form, Denormar ization. ) Unit - IV concurrency control Techniques: overview of database Transactions, Transaction states, ACID Transaction' Transaction Recovery, properties of a concurrency control, Locking ibchniques, Time-stamp version Techniques, ordering, Multi- Deadrock, Recovery Techniques in centrarized DBMS. DDBMS Design: Replication and Fragmentation Techniques. Text and Reference Books: 1' Elmasri' R'' and Navathe, s. B., Fundamentals of Database systems,3.d Edition, 2002. Addison wesley, 2' silberschatz, A', Koiih, H. F., and Sudarshan, S., Databa se system concepts,McGraw Hill, 201l. 3 ' Pannerselvam R., Datobase Mcrnagement systems, pHI 2nd Eaition, Learning, 20 I L 4' Desai, B' C', An Jntroclttctiott to Dntabase Svstem,Galgotia publication, 2010. 5' Leon, A', and Leon, M-, Databose Monogement systents,I't Edition, Vikas publishin g,200g. 6' Mata-Toledo, R', cushl,an, P., Sahoo, D., Datctbase Managemenr systems, Scliau,rs, outline series, TMH, 2007. .tY. 51 F.r I F. 6l akl U I U U c) Lra U e) U) O c) e) bo N tr) z o) O X I aEr () -b an c) bO o. a).= 'If L (u AE e cd ."i E,; I t< d, a) -oa(gP oP$) r-o.> PA ,9 o-) r-Ca I! FH :o)c.) g c v o-) () a0H I T HE o.r: b tr C r- r)v I YJ ! 3 3- u)d 6a 9a -L) =d\o o 6F I5H (r= U (.) (, 'E (-l 6 0x q).Yo) ooo L-,J< 6J E9 CJ r<=v SS.t () 6 >a 9 -:: bo ca dH (s:a ;tr - >.1 -d) 6 'a9 6 'o Ye o2 (-) Y an ,L =td b? 3n ".2 a o !r(g 2 do E O- >. d 6 >.J< t(, o\ LY cd UL q)- U -tt- -O=a tEo.>'t< ;Q t< F32 o E R o- bo V(g 'PE^ or t) a= A h'i s2 =ooE -Q 7' .= d ':. bo= aD4 -o (!;i<.rtg 50 6 .ii 689 (,-O=(l) cc v)== q)o O. Ud C) .lu d) *0) 35+ <& 3ugfr A E H' ooi oao ar; U U (J Analysis and Design of Algorithms General Course fnformation Course Code: PCC-CSE 208-T I course Assessment PCC-IT2O8-T Methods (internar: 30; externar: 70) Two minor examinations (20 marks), crass performance Course measured Credits: 3 through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester eximination Type: Professional Core (70 marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. Mode: Lectures (L) A candidate is required to attempt 5 questions in all. AII questions carry, .qrul marks. number euestion Examination Duration: 3 hours I will be compulsory and based on th; entire syllabus. It will conrain seve, parts of 2 marks each. Question numbers 2 to 9 will be given by setting rwo questions frorn each of the four uniis of the syilabus. A candidate is required to attempt trre remaining four questions by selecting one question from each of the four units. Pre-requisites: Knowledge of Data Structure and a programming Language About the Course: This course focus on effective and efficient desig. algorithms. of In this course various algorithm design techniques and their analysis is to be studied. After studying this course, a student is expected to apply techniques for solving better computational problems efficiently and prove it a,alytically. Course Outcomes: By the end of the course students rvill be able to: col ' state terminology and concepts algorithmic techniques. (LOTS: Level l: Remember) CoZ' discuss various algorithmic techniques. (LorS: Level 2: Ulderstand) CO3' apply appropriate algorithmic techniques to solve cornputational problerns. (L6TS: Level 3: Apply) co4' analysing algorithms for their efficiency by determining rheir cornplexity. (HoTS: Level 4: Analyse) Co5' compare the pros and cons of applying the different algorit6mic techniques to solve problems. (HOTS: Level 5: Evaluate) Co6' formulate efficient and effective algorithmic solutions ibr different real- world problems. (HOTS: Level: 6 Create) Course Content Unit I . Algorithms' Algorithms as a technology, Insertion sort, Analyzittgalgorithms, asymptotic notations, Divide and conquer: General method, binary search, merge soft, quick sort, Strassen"s matrix multiplication algorithms and analysis of algoritllns for these problems. '''. Unit II - la\ Sorting and Data Structures: Heapsort, Hash rables, Red and Black dree$y Method:|\leneral merhod, knapsack problem, minimum spanning trees, singre source paths u.l&, oIthese -problems,,h a.rl ,.,. -6n 53. t Unit III DYnamic Programming: General method, matrix chain multiplication, longest common subsequence, opLimal binary search trees, - Back Tracking: General method, 8 queen's problem, graph colouring, Hamiltonian cycles, Analysis ofthese - problems. Unit IV Branch and Bound: Method, O/I knapsack and traveling salesperson problem, Np Completeness: polynomial time, NP-completeness and reducibility, NP-complete problems. Text and Reference Books: 1. Thomas H. Cormen, Charles E. Leiserson, Ronalde L. Rivest, Clifford Stein, Introdttction to Algorithms, MIT press, 3rd Edition,2OO9. 2. Ellis Horowitz, Satraj Sahni, Sanguthevar Rajasekaran, Funclctnrental of Computer Algorithms, Galgotia publication Pvt. Ltd., 1999. S. Dasgupta, yazirani, 3. C. Papadimitriou, and IJ. Algorithms, McGraw_Hill Higher Education ,2006_ ,ts ;"i:*-'g;- -*'*=*e**"' *_,I 54 FI oo N arI] U I U U -'i q) l.u) U a li bo qr :l I boI 0l s\ e)l ot \n -"1 tr) r3ltrl .2v)l I t-) I \ cl '/. lt .L d l) ol)-l .ar, I 5sI og L) o >\ (.) tt) C) 0) t(h General Course Information Course Code: PCC-CSE2}? -T I Course Assessment Methods (internal: PCC-IT2O9-T 30; external: 70) Two minor examinations (20 marks), Class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Core marks). Contact Hours: 3hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. All questions carry equal marks. euestion number I will be compulsory Examination Duration: 3 hours and based on the entire syllabus. It wil contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting tr,vo questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Knowledge of algorithms, flow charts and a programming language. About the Course: Software Development is generally a quite complex and time-consunring process. Moreover, depending on the nature and complexity of the software requirements, Software Engineering plays an important role. This course will help the students to understand the systematic approach to requirement analysis, design, development, operations and maintenance of software systems. Besides this, it also guides students in developing the optimal software syslems. Course outcomes: By the end of the course students rvill be able to: COl. define the various concepts related to software engineering. (LOTS: Level l: Remember) COz. demonstrate the use of stages of various Software Life Cycle Models. (LOTS: Level 2: Understanding) CO3. ,|PPIV the Software Requirement Analysis and Software Design Process. (LOTS: Level 3: Apply) CO4- ,a,nalyse the size, cost, complexity, reliability, quality and maintenance of a software system. (HOTS: Level 4: Analyse) COS. construct software model according to the requirements . ,l- of a customer. (HOTS: Level 6: Create) -;,, I Course Content Unit I l. Introduction: Software Crisis, Software Process, Evolution of Software Engineering, Software Characteristics, Software Metrici and SDLC. Software Life Cycle Models: Water Fall Model, Increment process Model, Evolutionary Procels Models, Unified Process. Selection of Life Cycle Model. Software Requirements, Analysis and Specifications: Requirement Engineering, Requirements Elicitation, Requirements Analysis: Data FIow Diagram, Data Dictionary, Entity-Relationship Diagrams, Decision Table, Decision Tree and Strucfured Charts. Requirements Documentation and Requirements validation. 1 f,. V;Yryn'{ ..r' ,{ , O, |,,{ ,'/ Unit II Software Project Management: Size Estimation, Cost Estimation, Constructive Cost Model (CoCoMo), Putnam Resource Allocation Model. Software Risk Management: Software Risks, Risk Identification, Risk Projection, Risk Refinement, Risk Mitigation, Monitoring, and Management, RMMM plan. Unit III Software Design: Software Design Fundamentals, principles, Modularity, Design Strategy of Design, Function oriented Design, and object oriented Design, IEEE Recommended Practice for Software Design Descriptions. Software Quality: Basic concepts, ISo 9126, Mccall's Quality Factors, Software euality Assurance, seA Activities, Software Review Process, Formal Technical Review, ISO 9000 euality Standards, and CMM. Unit IV Software Testing: Testing fundamentals, Verification plan, and Validation, Test Test Case, Levels of Software Testing: Unit Testing, Integration Testing, Top Down and Bottom up Testing Integration Testi,g, Alpha and Beta Testing, system Testing, white Box Testing and Black Box Testing, Debugging and Software Testing Tools. Maintenance and Reengineering: Software Maintenance, Software Supportability, Reengineering, Business Process Reengineering, Softrvare Reengineering, Reverse Engineering, Restructuring, Forward Engineering and The Economics of Reengineering. Text and Reference Books: 1. K. K. Aggarwal and yogesh Singh, sofnvare Engineering, 3.d Edition, New Age International Publishers Ltd., Reprint 2014. 2. Roger S. Pressman, software Engineering; practitioners A Approach 7,h Edition, Mc Graw Hill Education ,2014. 3' Rajib Mall, Fundamental of Software Engineering,Prentice Hall India ,2004. 4' Pankaj Jalote, An integrcrted Approach to sofnuare Engineering,3'd Edition, Narosa publications, 2014. 5. Ian Sommerville, sofnvare Engineering, r0'h Edition, Addison-wesrey, 20r5. 6' carlo Ghezzi, Mehdi lazayeri and Dino Mandrioli , Funclamentcrls of sofnvare Engireering,2ndEdition, Pearson, 2007. 7 Waman ' S Jawadekar, Sofhuare Engineering-Principles and Practice,TataMcGraw- Hill,2004. \ rT"Y- 57 ?o a I I N o I I 0 aC ra (n a.l c.l ce c.l I I A.. F o\I N N cn 6I a14 U I I N c! I U U o\ I a! () a L € I U b! t-- I I I () () \o o I bo frl rn co q) I c{ N cn tr) L w (r. I V) >< r) lr I c\l C\ t-l z N aa ao CJ N cn () t I I,^ 0) I o-r la I o.t lu7 FL 0) () It.- tr l= t\ l>r : lo J lLv O() daf' i.l'{ l';- lF- I lA a Pra bo .. {0) -1 .ia \J D- l> F - :< EF (,) I,'t 0.) l!oVJ .ag+ a\i ()!/ oU u O 6EE VI F l- U) I bod (l) t/, 6 d. e- (t) E-s ) o\ 2? '= F General Course fnformation Course Code: PCC-CSE2lO-T / Course Assessmer, PCC-I}2I O-T Two minor examinations Course Credits:3 (20 marks), crass performance measured through percentage of rectures Type: Professional Core attended (4 marks), assignments (6 marks), Contact Hours: and the end- semester examination 3 hours/week (70 marks). Mode: Lectures (L) For the end semester examination, Examination Duration: nine questions are to be 3 Hours set by the examiner. A candidate is required to attempt questions 5 in all. AII questions carry equar marks. number I will euestion be compulsory and based on the entire syllabus. It wirt contain .",u.r, parls of 2 marks each. Question numbers g 2 to wiil be given by setting two questions from each of the four units or tne rviiuurr. A candidate is required to attempr tt ,"-rind f#;estions by selecting " one question from each of the four units. About the Course: Java is a general-pu{pose, concurrent, class-based, object-oriented computer programming Ianguage that specifically designed to have as ferv irnplernentation is dependencies as possible. The provide the students aim of this course is to basic Iorowledge about object-oriented development and programming and in-depth knowredge about syntax techniques in Java'The course is very comprehensive and cover all the concepts' e'g'' Java basics, object-oriented important Java Programming, Multithreading, File and more. handling, Exception handling course outcomes: By the end of ilre course students wiil be abre to: col' Iist object oriented characteristics peculiar to JAVAprogramming. (LorS: Level co2' describe object-oriented l: Remember) principles and paradigms impremented by Java programming ranguage. (LOTS: Level 2: Understand) co3' apply object-oriented principles for solving problems using JAVA. (LoTS: Level 3: co4' identify classes, Apply) interfaces methods, hierarchy in the classes for a given programming probrem in JAVA. (HOTS: Level 4: Analyse) co5' design Graphical User Interface applications and web based applications in Java AWT and by importing applet, SWING packages. (HOTS: Level 6: Creare) Course Content Unit I . obiect 'oriented Progranlming concepts: object, classes, Instantiation, procedural Reuse, and object Features or object-oriented programming: ,T:Xfii:".:ffffi;11:*-'' Encapsuration, Abstraction, Java Programming Fundamentals: History of Java, Features of Java architectu re, javaarchitecfure security, Garbage collections an'd Memory Management- Java programming ranguage syntax, types' operators' constants, variabres, data expressions 'type conversion and casting. contror statements: if-erse, for, loops and switch statements' while, & do-whire Methods, constructors, access specifiers and modifiers, overloading methods overloading constructors. Recursion, and buirding strings, exproring string crass. 59 Unit II -- Implernenting OOP : Inheritance - Inheritance hierarchies, super and sub classes, super keyword, - Implementing inheritance, overriding methods, and interfaces. Implementing multiple inheritance using interfaces. Polymorphism- dynamic binding, Method Overiding, Abstract Methods and Classes. - - Exception Handling: Exceptions in java, exception classes, built-in exceptions, try, catch and finally statements. Multiple catch statements, throw and throws statement. Creating and handting user-defined exceplions. Working with Packages: Packages-Defining, Creating and Accessing a Package, Java API Packages, Using System Packages, Understanding CI-ASSPATH, importing packages. Unit III Working with GUI: Introduction to an Applet, life cycle of an applet, passing parameters to applets, applet security issues. AWT and Swing components, Layout Managers. Event Handling: Delegation event model, event listeners and event handlers, Working with frames, working with buttons and Text Fields, working with combo-boxes, working with List Boxes etc. Threads: Multitlireading, Thread class and Runnable interlace. life cycle of a thread, Thread priority, tlread synchroni zation. Unit IV -n File Handling: File class and Random Access File class, Input and output streams, character sheams, Object . serialization, Serializable interface, Remote Method Invocation (RMI). Database qonnectivity: Intuoduction to SQL statements, ODBC/JDBC API: Connection, Statements, Prepared Statements, Record Set and execute statements. Text and Reference Books: l. Paul Deital, Harvey Deital, JavorM; Hovv to Program,g'h Edition, Pearsol Education (prentice Hall), 2012. 2. Herbert Schildt, JatarM; The Complete Reference,T'h Edition, McGraw-tlitl,2O0l. 3. Kathy Sierra, Bert Bates , Heacl First Jot,a,2'd Edition, O'Reill y, 2005 . 4. Ralph Bravaco , Shai Simoson, Java Programnting From tlte Grouncl Up,Tata McGraw-Hill, 2OOg. 5. Sachin Malhotra, Saurabh Chaudhary Programming in Java, Oxford University Press, 2011. 6- E. Balagurusamy, Programming with Java: A Prentiet, 3'd Edition, Tata McGraw-Hill, New Delhi, 2007. 60 ?o ao I 0( 6l o I C'l V) 0. a a.l c.l c.r ca c.} N Fr I I I I I t\ H a I U ! U }\ U I C! q) a )c I L I I I U a0 \ I \o I uo tn I I N (\ or a 'f, fa I >< l< ca I cn co zti (\l I N ao aa 4, (.) a{ N cn L o l- c.i .t J le lu) c { o-r lE 9 lg !- nQ) 16)lq o)l U )) t- l€b lo- - l-J l*,E I 2a l'; Y a lo-r v l- (g F lr IsESE F as N l rr er \-/ Itr< IE o: 1 lt i J )v o- '=: J>1 .l3-v aJ IF ? (\ o-r'O-: IJ.] iuo Yo l'lf,la; a z,o=(c s lq).j = U lP 6 I 311 )= f E; lEf Eg Q =trbnY:- .q v) trli ;, (v) U El.sItr (,=i^ (.)-a! A. ol ! u. I ca (lco a1'Hd^3; :l v al-l- -(J E* 3 rEgIIe () 6 ;ge )O-0) F cl : u!d !a LIY o l< € - boca E fllt)ad -r-- A ':. q.) ;eFil:,Eiin =l* qr=Srt, E i,€ ut- e u o-LVLh c,-) -^0) g q* i; E Hilr $l 7,s o ol I I_ r-.i an $ lrrr -l0Jl Elc o LJ olo >l JIL U O u lr-r -31 Microprocessors and Interfacing Lab. General Information Course Code: PCC-CSE205-P PCC-IT2O5-P Course Assessment Methods (internal: 30; external: 70) The internal assessment is based on the percentage of rab Course Credits: I sessions attended (4 marks), timely submission of lab Type: Professional Core Lab. Course experiments/assignments and the quality of solutions provided in the assignments (16 marks), and an internal VIVA-VOCE Contact Hours: 2 hours/week (10 marks) conducted towards the end of semester Mode: Lab practice and assignments The external examination is of 70 marks. The break-up of marks for external examination is based on quarity of lab reports (20 marks), quality of solution(s) for the given problem(s) at the time of examination (written work + execution of program(s)) (30) and vIVA-vocE examination (20). Pre-requisites: Basic concepts of Digital Electronics and Logic Design, Computer Organization About the Course: The objective of the lab course is to equip the students to design the Assembly Language programs for 80g5 and 8086 microprocessors. Course outcomes: By the end of the course students will be able to: CO1. describe the working of microprocessor kit/ TASM .(LOTS: Level 3: Apply) CO2. apply interfacing of supporting chips with microprocessor. (LOTS: Level 3: Apply CO3. design assernbly language programs for the 8085 and 8086 microprocessors. (HOTS: Level 6: Create) CO4. analyse the output of assembly language programs. (HOTS: Level 4: Analyse) CO5. create lab records for the solutions of assignments. (HOTS: Level 6: Create) CO6. demottstrate use of ethical practices, independent enquiry and team spirit. (LOTS: Level 3: Apply) List of experiments/assignments l. Two assignments to write assembly language programs using data transfer instructions 2. Two assignments to write assembly language programs using arithmetic instructions 3 Two assignments to write assembly language programs using flag manipulation instructions 4. Twp assignments to write assembly language programs using shift and iotate instructions 5. Two assignments to write assembly language prog.u*r using stacks for 8086 micro-processor. 6 Two'assignments to write assembly language progranls using subroutines for 8086 micro-processor. 7 - Two assignments on interfacing of supporting chips with 8085 and 8086 microprocessors. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. k62 Frt r$I N t.l O U ! U U t+t ao) t U F] bo o q)L F< 6 cn tr a) \o U) oU) I L ll LI \ c)I atl-( I XI tftrl v 6Bl at # ol I -€.i a.) +. I dt -q !. =!-A 0) o oo CJI U) a6 €F (g a 7i J,^ Q) ,^. o- u)O b0() bo tre ()X dU, ()':- EI gE E: (g 23 ca ,- 6i Olr o. o. uo bD? ou7 0-) PO CI (-) Eu L.F cn L' E-3 o.6 O..l o a.) (n() q.) tr* o.J o-l9? o=<+ (E€ dl C) o- cox g6 er .9=-. t) o) U)F=a EJ c- :- /-r UI coJ b0x (* 0) l< 6 .ga CY OJ ,oa (+- O- ';a tsq .F -^ - t-F h0'g s.9 cn 6.r43 On t-,^ gL-=a E(J!-ts 00)- (Jo a:ca B: 3\ogl, oo 6 o )o)= 0.)Y .EA iO() =oO'r 9a U E* ()or- a.) Yco.t ov z. aqv ptn ii q) g969 H Ya L \o o)F ih -i .= lr1 ; = =4 - o-l7 v6(-i 3a ot- .10 .n 6 (€ bO 7)\ Eb tq)^ C.).= a)OO) ,aa9'; ()EY 'OooJ cg o- l/(g ltnC-J ,: _ ro + ar; \o (-) U Computer Networks Lab. General Course Information Course Code: PCC- CSE206-P/ Course Assessment Methods (internal: 30; external: 70) The PCC-IT3O I -P internal and external assessment is based on the level of Course Credits: I participation in lab. sessions and the timely submission of lab Type: Professional Core Lab. Course experiments/assignments, the quality of solutions designed for the Contact Hours: 2 hours/week assignments, the performance in VIVA-VOCE, the quality of lab. Mode: Lab. practice and assignments file and ethical practices followed. The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the controller of Examination in association with the internal examiner appointed by the Chairperson of the De t. Pre-requisites: knowledge of programming, digital and analog communication. About the Course: This course has been designed with an aim to provide students with an overview of the concepts and fundamentals of data communication and computer networks. Students learn about various topologies, network devices, routing protocols, firewall amongst other features and devices of Computer Networks. course Outcomes: By the end of the course students will be able to: COl. demonstrate various network topologies and networking devices.(LOTS: Level: 3: Apply) CO2. justify a particular routing protocol for any implemented data communication networks.(HOTS: Level: 5: Evaluate) CO3. construct a network and implement various network protocols.(HOTS: Level: 6: Create) CO4. devise solutions for various routing and switching problems in Computer Networks. (HOTS: Level: 6: Create) CO5. create lab records for the solutions of the assignments. (HOTS: Level: 6: Create) CO6. demonstrate ethical practices, self-learning and team spirit. (LOTS: Level: 3: Apply) List of Experiments/assignments : 1. A) Famil$rization with networking components and devices: LAN Adapters - Hubs -Switches Routers etc. T B)Familiarization with transmission media and Tools: Co-axial cable - U-fp Cable Crimping -. Tool- Connectors etc. 2. Installation ahd introduction of Sirnulation tools PacketTracer/ GNS3. 3. Preparing th8 UTP cable for cross and direct connections using crimpingtool. 4. Introduction to.various interior and exterior routing protocols. 5. Configuration of RIP protocol on routers to configure a netrvork topology. 6. Implementation EIGRP protocol on router. -."#r* '5i9 7. Implementation OSPF protocol on a larger network. . 8. Configuration ofARP protocol in network. i I 9. configuration of a wireless device in simulated environment. 10. Implementation BGP protocol betrveen two different n6tworks. I l. Implementation of static routing in simulation environment. 12. Configuration of TELNET protocol on router for remote access. 13. Configuration of access lists on network to stop unwanted traffic on network. 14. Configuration of zone based firewall in network. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. 64 ?n o I I U) I I oN a I I A( o co cn cn co C') I ca o I (r) I A N l*l I t I o I I cn \o N f.l a I o I I A UI U U I l+{ I I aa J I I ca U) )o ) I I )i ca ze) r- I I I e) R) tr) \o \o F I U in * o I (-.l r.) L I \x v a ra I co I N ca ca (.) (\l N CN .a I o ! C C! a! "{y' ca U ',: t General Course Information Course Code: PCC-CSE -2A7 -P I Course Assessment Methods (internal: 30; external: 70) The internal and external assessment is based PCC-IT2O7 -P on the level of participation in lab. sessions and the timely submission of lab Course Credits: 2 experiments/assignments, the quality of solutions.designed for the assignments, the performance in VIVA-VOCE, the Type: Professional Core Lab. Course quality of lab. file and ethical practices followed. Contact Hours: 2 hours/week The internal examination is conducted by the course Mode: Lab practice and assignments. coordinator. The external examination is conducted by external examiner appointed by the Controller of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Exposure to a programming language, MS Access. About the Course: This lab. course on DBMS involves a rigorous training on Oracle programming. It provides a strong formal foundation in database concepts, technology and practice to the students to groom them into well-informed database application developers. The objective of the lab course is to develop proficiency in the cxecution of commands of the database design and query using Oracle. course outcomes: By the end of the course students will be able to: COl. implement database problems using Oracle DML/DDL commands. (LOTS: Level 3: Apply) CO2. enforce integrity constraints on a database using a state-otthe-art RDBMS. (LOTS: Level 3: Apply) CO3. arialyse the design of a relational database. (HOTS: Level 4: Analyse) CO4. design a relational database for a given schema. (HOTS: Level 6: Create) CO5. create lab assignment record that includes problem definitions, solutions, results and conclusions. (HOTS: Level 6: Create) co6. demonstrate ethical practices, self-learning and team spirit. List of experiments/assignments: l. Use oracle software and login with valid user id and password. Explore its GIII and practice some basic commands of it. 2. Three assignments ielated to creation of database with tables having diflerent fields and datatypes. 3. Two assignments on the creation of table with different types of constraints. 4. Two assignments on insert, delete and modifo records from the tables. 5. lwo assignments on modifying the table using the alter command. 6- Two assignments on exploring select statement using rlarious clauses like where, order by, group by, having and aggregate functions. -.:!. .' 1 ',. \,- 7. Two assignments on the use of set operations to query the tables. a4*i J'11 q. ' '-t' 8. Two assignments on creating joins 3' ,.,u and views on the tables. I* i' 9. One assignment on generating sub-queries. :/ Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of subrnission will be prepared by the course coordinator at the beginning of the semester. 66 rO (t) I oN I (a I l]( o cn aa ca ca (a I I Frr N I I I I co 0r F-l t-I I N I I arc U I ol U ol I ca U nl O\l I Cl I .a 0. I JJ 6l I Cl I I () AI I r.r u) O r- I I q) \o q) c bo I G rn C! o N N a! ca I r- a= I \o q) a ,.:f, o I I cn 6 d cc.l X C\ ii d .l c N ca aa a I I N c.t ca ca (.) ()I c-il al I L al (sl6l 3E I I EI I sr o)l E I d7 €l!l = gb I (sl CI rol zl P e Alpt I qr. I d-r bol 63 I vt I I (aI (!l Z(v General Course Information Course Code: PCC-CSE2I}-P / Course Assessment Methods (internal: 30; external: 70) PCC-IT21O-P The internal and external assessment is based on the level of Course Credits: 2 participation in lab. sessions and the timely submission of lab experiments/assignments, the quality of solutions designed for Tlpe: Professional Core Lab. Course the assignments, the performance in VIVA-VOCE, the quality Contact Hours: 4 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignments The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the Controller of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: The course assumes knowledge of Object-Oriented Concepts and programming. About the Course: This Java course will provide a strong understanding of basic Java programrning elements and data abstraction using problem representation and the object-oriented framework. The objective of the lab course is to inculcate proficiency in students to design and develop market-based software applications. Course outeomes: By the end of the course students will be able to: COl. implemertt Java programs using object oriented concepts for problem solving. (LOTS: Level 3: Applv) CO2. detect syntax and logical errors in java programs (HOTS: Level 4: Analyse) CO3. apply exception handling for making robust JAVA code. (HOTS: Level 3: Apply) CO4. design java applications using File IiO and GUI. (HOTS: Level 6: Create) CO5. create lab record of the solutions of assignments that includes problem definitions, solutions and conclusions. (HOTS: Level 6: Create) CO6. demonstrate ethical practices, self-learning and team spirit. (LOTS: Level 3:Apply) List of experimen ts/assignmen ts : I ' Use eclipse or NetBeans platform and acquaint with the various menus, create a test project, add a test class and run it to see how you can use auto suggestions and auto fill functionalities. Try code formatter and code refactoring like renaming variables, ,iltnoa, ind classes. Try debug step by step with a small progtam of about l0 to 15 lines which contains at least one if else condition and a for loop. 2. Two:ispignments illustrating class, objects, methods, arrays and various data types in java. 3. Two assignments on the use of control, looping statements and user defined functions. 4. One assignment illustrating the implementation of various forms of inheritance. 5. One assignment on method overloading. 6. One assignment on polymorphism and method overriding. 7. One assignment on implementing exception handling. 8. One assignment to illustrate interfaces in java. 9. One assignment to create package in java. @ 68 10. one assignment to design of multithreaded programs in java. I l. One new assignment on event handling. 12. Two assignments related to java applets. 13. One assignment to design a GUI application. 14' One assignment to access and update data from a database using JDBC. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment designed to should be be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission prepared by the course will be coordinator at the beginning of the semester. \/Y. 69 ca ao I I nr \ ,) I I I I ],i o cn co ca C' V) (\l I I co o I c I I 6t I I ca H I a O{ U I o\ U I C. U I ii.{ I 00 E I I c7l d 11 bo r- o I I \o I I bo L rn I+( C.l a{ I ca r- t I X L co C-.l N aa at='{ I al (-.1 I C.l ca () C\ I C..l ca L I ls l-o t{ l(gItr I lo- l6 lo t(d t- lo) bO t> t\lo I o-> U la .= l,o)l-d ^ lrt lH l.* ? I -:z c. I o-r lo 6 laB g, l(g l= I o.r loo o l.E a.i lz t'6 la ld6 l= - lq- lX o.l t.- lr'a = I ^a c I oo ,-. l.:bE lo r* I r la lo lc 0) lE o c lr o-)= lci l&s General Course Information Course Code: PCC-CSE3}L -T I Course Assessment Methods (internal: PEC-IT409-T 30; external: 70) Two minor examinations (20 marks), Class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination Type: Professional Core (70 marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate required Mode: Lectures (L) is to attempt 5 questions in all. All questions carry equal marks. euestion Examination Duration:3 hours number 1 will be compulsory and based on the entire syllabus. It will contain seven parts of 2 nrarks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Programming skills in cic++ and Data Structures. About the Course: This course involves studying graphic techniques, algorithms and imaging models. Moreover, sfudents learn about the techniques for clipping, cropping, representing2-D and 3-D objects. Course Outcomes: By the end of the course students lvill be able to: COI. state basic concepts related to graphics. (LOTS: Level 1: Remember) CO2- describe the principles of creating graphical objects and graphical user ilterface applications. (LOTS: Level 2: Understand) CO3. apply 2-D and 3-D transformations (rotation, scaling, translation, shearing) on geometric objects. (LOTS: Level 3:Apply) CO4. use different techniques for clipping and filling geometric objects. (LOTS: Level 3: Apply) CO5' compare different graphics algorithms for different geometric objects. (HOTS: Level4: Analyse) CO6. create user-friendly interfaces for computer applications. (HOTS: Level 6: Create) Course Content Unit I Introduction to Computer Graphics: What is Computer Graphics, Computer Graphics Applications, Computer Graphics Hardware and softrvare, Two dimensional Graphics Primitives: Points and I ines, Line drawing algorithms: DDA, Bresenham's circle drawing algorithnrs: Using polar drawing, mid-point circle drawing algorithm; Filled area algorithms: Scll boundary fi lled algorithm. @ 71 Unit II ^- Two/Three Dimensional Viewing: The 2-D viewing pipeline, windows, viewports, window to view port - mapping; Clipping: point, clipping line (algorithms): 4 bit code algorithm, Sutherland-cohen algorithm, , parametric line clipping algorithm (Cyms Beck). Polygon clipping algorithm: Sutherland-Hodgeman polygon Two dimensional transformations: transformations, translation, scaling, rotation, reflection, composite transformation. Three dimensional transformations: Three-dimensional graphics concept, Matrix representation of 3-D Transformations, Composition of 3-D transformation. Unit III Viewing in 3D: Projections, tlpes ofprojections, the mathematics of planner geometric projections, coordinate systems. Hidden surface removal: Introduction to hidden surface removal, Z- buffer algorithm, scanline algorithm, area sub-division algorithm. Unit IV a Representing Curves and Surfaces: Parametric representation of curves: Bezier curves, B-Spline curves. - Parametricrepresentationofsurfaces;Interpolationmethod. --':' Illumination, shading, image manipulation: Illumination models, shading models for polygons, shadows, transparency. What is an image? Filtering, image processing, geometric transformation ofimages. Text and reference books: 1. James D. Foley, Andeies van Dam, Stevan K. Feiner and Johb F. Hughes , Computer Grophics Principles and Practices, second edition, Addision wesley, 2000. 2- Pradeep K Bhatia, Contputer Graphics,3'd edition, I K International Pub, New Delhi, 2013. 3. Donald Hearn and M. Pauline Baker, Compttter Graphics 2"d Edition, PHI, lg9g. David F. Rogers 4. , Procedural Elements for Computer Grapftics Second Edition, T.M.FI, 2OOl . 5. Alan Watt, Funclaruentals of jDimensional Computer Graphics,Addision Wesley, 1999. 6. corrign John, Computer Graphics: secrets and solutions,BpB,1994. 7 . Pilania & Mahendra, Graphics, G(JI, Games & Multimedia Projects in C, Standard pub., 2002. 8- N. Krishanmurthy, Introduction to computer Graphics, T.M.H, 2002. , --- 7 -.."'- ' r4'*- P '.i,: 72 ?o c I I a I I O. 6l o (, I C a.l ao co ca ca V) cn I 6l I I F I I ca 14 I U) I I I U I I I U o\ U l*( I q) O 6 fr I I I I I I a U r-- (n I I \o d I tr o I I I I rfl I d tr q) lf-) (..t a.l c-t co I r- , I I I C.I U o.ldt I \ X .ol fi Ol r c\ N nI I r=.( a t\tl nlCl r a\l a{ ci T 5l C.J o-l c! t-I ,=L ci v -o t"; olal Fr,r I ls c'.1 rl PF lo-l= .() co() ol I(g 6 .F I lL. L)ep9 EH; Ej UI J! I.i l50 Xa lo =-c S) ft- i(Jr-;\(sa q o- :, t - E sE I: C t- l--: EJ 'l l- I () l- l;r lE 3 ! .i';a.oo F o H'J J=a;, le8v ljra ld lv o li I t-v I- .na (.) lo.l o-) (g a Al o. 15 I rD l:- 3bD l- e \-/l 95 l.- E-o a e ,() l9 6 L Lvla Jl 5Eo Jpl l"i Gen er a I C oGSer*+*.Uation Course Code: PCC-CSE3}2-T I Course Assessment (internal: PCC-IT3O8-T Methods 30; external: 70) Two rninor examinations (20 marks), Class performance Course Credits: 3 measured througtr percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Core marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. All questions cary equal marks. euestion number I will be compulsory Examination Duration: 3 hours and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisite: Exposure to programming languages About the Course: popular Pyhon is a open source programming language used for both standalone programs and scripting applications in a wide variety of domains. It is free, portable, and powerful and is both relatively easy and remarkably fun to use- In today's era Pyhon has found great applicability in machine learning, data analytics and many other data science application. This is introductory course and covers most of the basic concepts required for basic python programming. Some of the contents are advanced may be useful for data analytics purpose. Course outcomes: By the end of the course students will be able to: CO I outline ' various basic programming constructs including operators, character sets, basic data types and control statements. (LOTS: level l: Understand) CO2. explain Pyhon packages and their functionalities for data analysis. (LOTS: level 2: Understand) co3. solve problems using python programming. (Lors: level 3: Apply) CO4- analyse the results of data analysis or machine learning programs (HOTS: level 4:Analyse) CO5. evaluate solutions according to the problem definition. (HOTS: level 5: Evaluate) co6. devglop database applications in pyhon. (HorS: Ievel 6: create) .f Course Content Unit I Introduction to Pyhon, ,.u.-..? History of Pyhon, Features of Python, Python Identifiers, python eharacier jet, Keywords and Indentation, Comments, Command Line Arguments, Assignment Operator, Operators and Expressions, print) Furiction, input0 Function, et,al0 Function, Python Data Types: int, Jloat, complex, Variables, Mutable vs Immutable variables, Namespaces, Decision Statements: Boolean Type, Boolean y'statement, Operators, else statement, Nested Conditionals Statements, Multi-way Decision Statements (elif statement). l4 Unit II Loop' Break Function, For Loop, Nested Loops, Infinite Contror statements: L'tthire loop, rangeL Loop to Strings, String operations: Indexing and Statement, pass statement, Introduction Statement , continue searching and Sorting' slicing, Inbuilt Functions for Lists, List Processing: Slicing, Lists: operations on List: Deietion; creation, Addition' Retrieving Valucs' Need of Dictionary operuiio* on Directories: Dictionaries: to Sets, cperations on sets' Inbuilt Functions for Tuples, Introduction Tuples, operations on Tuples, Defining and calling Function' Mainfunction, user Defined- functions, python Functions, Inbuilt functions, variables' Recursion' paramcters, Default Parameters, Global and Local passing, Actual and Formal parameter Packages' Modules' Importing Own Module' passing FunctionJ as Data, LamclaFunction, Unit III and reatllines|' writing Text Files' files, read functions, reacrL, recrcllineT operations on File: Reading text file pointer using seek, Appending to Files' functions, writey and writelines0,Manipulating write class and objects, Accessing attributes' Builrln python oriented: overview of oop, classes object objects, Polymorphism' overlapping and crass and Instance variables, Destroying Attributes, Methods, Handl rng' Tty-except-else e: superL, lvtetnoa oveniding, Exception overloading of operators, class Inheritanc User-Defined Exceptions clause, Python Standard Exceptions' Unit IV and update and delete operation' DML connectio n, crewte, insert, read, Databases in python: create Database OPeration with Databases' DDL Array using arrays and Scalars, Indexing Arrays' python for Data Anarysis: numpy.. creating arrays, Processing' Array Input and output universal Array Function, Array Transposition, Data Sortin g' Matptottib: Python for paner, Index objects, Re-indexing, Iteration, pancras:Series, Data Frame, Model Persistence' of dataset, learning and predicting' visualization, visuarization Section, skrearn'.loading Text and Reference Books: 1. Ashok Namdev Kamthane' ProgrammingondProblentsolvingwithPython,McGrawHillEducatton Publication' 2018' Revised and /a^-^a,,tntinn nn, sing Pyihon, Springer' 2.JohnGuttag,IntroductiontoConlputationandProgrctnltnmgu' (Referred by MIT)' 2013 ' Expanded version programmirg. Media' Inc'' 2013' python: po,erfur obiect-oriented o'Reilly 3. Lutz,M., Learning and Algorithms Micheal s Goldwa sser, Data stt'utctttres 4. Michael r Goodrich and Robertto. Thamassia, in PYthon, WileY, 2016' 5.Y.DanielLiang,IntrocluctiontoProgrammingUsingPyrhon,Pearson,20|3. oxford Publications' 2017' python programmirg (Jsing probrem sorving Approach, 6. Reema Thareja, o'Reilly Media' y, core python'Progromnting , Think Pythott' 7. Dr. R. Nageswara Rao, Allen B. Downe 2012. Learning,20ll' of python: First Programs, cengage 8. Kenneth A. Lambert, The Funclamentals 15 oco U) c{ ca c.I ca ca c.) 0< ol a I a I I I co (\l I I I I t-( (\tI I I I I CO rd a o\ U I I I ! U 6 U ,^.A -"^'. "| / r- .*iiti':/ q) Fg .i U) I L I _*y.l \ I \o J U I I aa ca i: bo rn I \f, L a\ (\ a.l ro bo ?a L \o I I N c.l N r- (\t C.l ca (f) c.) l{ ca (-.l >< c! ca d a l; I lg=l; lIl;l= q) l*lI fr lr tY I Ei,IE"IEIEIE l5 I l*t I I U lr iill#ElH li$lE lEI; ItI E.I H *f ;l-il' l€ ;l- * trAlc-r lB ta q) e ld ls I € ;;?li5li li sl€I -(rlcE le e. 19tr () o UI .a q) .= \lUl ^lHl 6 et E U saglgrlrelglllg aulf, .lo o l.' 1.. l* l-' ,,) - B le J 8 ls ls ls ls u l_3 High Speed Network Technologies General Course Information Course Code: PCC-CSE 3Bn course Assessment PEC-IT3O5-T Methods (internar: 30; externar: 70) Two minor examinations (20 performance Course marks), crass Credits:3 measured through percentage of lecfures attended (4 marks), assignments (6 Type: Professional Core marks), and the end- semester examination (70 marks). Contact Hours: 3 hours /week For the end semester examination, nine questions are to be set Mode: Lecture(L) by the examiner. A candidate is required to attempt 5 questions in all. All questions Examination Duration: 3 hours carry equar marks. euestion number I will be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of trre four units of the sylrabus. Acandidate is requi..a io attempt the remaining four questions by selecting or" dJ;;;; each of the four units. Pre-requisites:Basicknowledgeofcomputernetworks,IayersofoSIreferencemode,,ffi layers of OSI reference model. About the course: High Speed Network Technologies is a professional core course based around Network used across the Architectures, protocols layers, techniques used in communication and modes of data transfer. The course deals creating High Speed Networks for any organization/institute with with its various phases/life cycles. course outc5mes: By the end of the course stutlents lvill be able to: col ' define different high speed network technologies. (LorS: Level l: Remember) co2' explain working of different wired wireless / technologies suitable for LAN and wAN communication. (LOTS: Level 2: Understand) co3' illustrate the mapping of oSI reference model to different high speed technologies and Internet Suite , of Protocols. (LOTS: Level 3: Apply) co4' analyze the performance of different high speed technologies in different scenarios / situations. (HOTS: Level 4: Analyse) co5' design a network for any organization using high speed technologies - along------o with"r'r Internet connectivity.v\-'r'Lrrsu (HOTS: Level 6: Create) ^rrlvrrrwL Course Content Unit I (High Speed LAN) Gigabit Ethernet: overview of fast Ethemet, Gigabit Ethernet _ overview, architecture, frame specifications, layered protocol format, network design urirrg Ergaurt Ethernet, applications, 1OGB Ethernet overview, layered protocol architecture, frame formai. - Fiber channel - overview, topologies, porrs, layered protocol #:L::annel: architecture, frame structure, class I' w. 7l ! .iiib, UNIT II (High Speed WAN) Frame Relay: Protocol architecture and frame format. !. ^ - ISDN & B-ISDN: Channels, interfaces, addressing, protocol architecture, services. - ATM: Virtual circuits, cell switching, reference model, traffic management. Unit III (Wireless LAN) Wireless Networks: Existing and emerging standards, Wireless LAN (802.11), Broadband Wireless (g02.16), Bluetooth (802.15) their layered protocol architecture and security. Mobile Networks - GSM, CDMA. Unit IV (Internet Suite of Protocols) Internet Layer: lPY4 and IPV6, Ip addressing, Ip crasses, CIDR. Transport Layer: UDP/TCP protocols & architecture, TCP connection management. Application Layer: DNS, E-Mail, Voice over Ip. Text and Reference Books: l. Jochen Schiller, Mobile communication,2nd Edition, pearson,2oag. 2. Andrew S Tanenbaum, computer Nehyorks,5'h Edition, pearson 2013. William 3' C Y Lee, Mobile Communication Engineering: Theory ancl Applications,2'd Edition, McGraw Hilt, tgg7. , t r,..il : i5-l*)t?) - : l' l:.-2-- - -.''' . -a I I I t8 co (t)o (-l o (t) a{ co ca ca ca C U) .l I I I cn FI ca I ca c I r-l OEt U I c I I U U |rl I I a{ () ra li 00 c I I U r- u) I I q) I bo \o o I I ra I c I I C.l ca e) F s ti A I a-'t a.l () I (\ c., o\ F- z Hl ' c) CI c.l co q) HI a H o-l5l N ci uol-i EI XI 'ir I .ar. dl I lr{ I z. I oltrl ,Y s. I 63 I EI9t EI +lCI UIcl Cryptography and Network Security General Course Information Course Code: PCC-CSE3}4-T I PEC-IT4O2-T course Assessment Methods (internal: 30; external: 70) Course Credits:3 Two minor examinations (20 marks), crass performance Type: Professional Core measured through percentage of lectures attended (4 marks), Contact Hours: 3hours/week assignments (6 marks), and the end- semester examination Mode: Lecfures (L) (70 marks). For the Examination Duration: 3 hours end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions in all. All questions carry equal marks. euestion number I will be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the sylrabus. A candidate is required to attempt the remaining four questions by selecting one uestion from each of the four units. Pre-reqrrisites:Basicknow1edgeofNumb"r'vst"- Abotrt the Course: The increase in techniques to penetrate into systems has led to variety of information and Network attacks, To nritigate the exploitation of the wlnerabilities leading to these attacks we need to adopt robust security architecture into our premises. We have to choose between various security technologies such as cryptography, Digital Signatures, Key Management, Program Security,Database security, wifi .".rity. In the current scenario we require to secure end-to-end devices, Networks, Networking devices and clouds. Course outcomes: By the end of the course students will be able to: COI recognize ' need of cr}ptography and cryptographic Algorithms.(LOTS: Level l: Remember) CO2' represetlt security in terms of various techniques and algorithms. (LOTS: Level2:Understand) Co3' apply mathematical techniques to cryptography for solving problerns related to security issue. (LOTS: Level 3:Apply) CO4' iOeS,tifV various types of attacks for their mitigation/proactive and reactive treatment. (HOTS: Level 4: Analyze) CO5' judge the security of an organization/institute by means of Network security devicesimodels/controls. (HOTS: I.ivel 5: Evaluate) *diff.r.n, CO6' integrate types of securities under one environment and evaluate its perlbrmance.(HOTS: Level 6: Create) : 11. Course Content |: Unit I t', t Cryptography: classical Qverview of cryptosystems, stream and block ciphers, ciphers & cipher modes, Substitution Ciphers: Mono-alphabetic Substirution and Poly-alphabetic Substitutior, T.urrposition Ciphers: Rail Fence, ScyTale, Book cipher, Vernam cipher, vigenere TaLluae, Hill Cipher. Cryptanalysis of Classical Cryptosystems. Unit II Mathematical Foundations: Elementary Number theory, Finite fields, Groups and Subgroups, Matrix representations, Symrnetric matrices and diagonalization, Number theory: Divisibility, gcd, prime numbers, primality testing. Congruences, solution of congnrences, Chinese renrainder theorem, Fermat hnd Euler's theorem, Modular Arithmetic and its properties, Modular exponentiatio "o/ ''- i-#4{,,' 80 'r ,-."{'' b\ Unit III crlptographic Algorithms and techniques: Private/Symmetric Key cryptography: DES and its variants, AES, Feistel networks, Modes of operation, Public/Asymmetric Key Cryptograpny: nSa Algorithm, Elliptic cryptography' Diffie Curve Hellman Key Exchange Algorithm, Digital Silnatures, Knapsack Algorithm, public Infrastructure, Key Kerberos, secret sharing schetes, iigitat Certi-ficater,"X.509 Certificates. Unit IV Network Security: Attacks: types, detection, mitigation. Network Security Foundations, Defense Models, Access Control: Authentication and Authonzation Controls, Network Architecture, Network Device Security, wireless Security, Firewalls, Intrusion Detection Systems, Network Role-Based Security: Email- pcp, pEM, MIME' Proxy s_ servers. SSL, TLS. SET, SHTTP, IPSec. Virrual Private Networks security. Text and Reference Books l' William Stallings, Cryptography ancl Network security-Principles and proctices, pearson Education, Ninth Indian Reprint 2005. 2' Charlie Kaufman , Network Security ; Private commtrnication in public worlcl, prentice-Hall International, Inc. April 2008. 3' Roberta Bragg, Mark Rhodes-ousley, Keith Strassberg, The Complete Reference Network Security, McGraw hill Educa tion, 20A4. 4' Charles P. Fleeger, Security in Compttting,2"d Edition, Prentice Hall International rnc., 1996. \ \ I tu t ffi .,i ;fil .;.,^is#' 8t ?a a I I I 0r (\t a ao ca co ca co cO a (\l I I I F r+I c I I I rO r--l (n ca U I U o\ U I I -{ a I co L F-. I I I I e) a \o L rn I (-.l cO cn e) o co z t c I a\ c.) cn co nr eo C{ I N c.l C.l c'l co ot bo crl c\ co co h cn 6l co CN U 'r r'l' ) X t0) | .. lE bO It* trl I q..r P L l€ o- ltr oJ''Y d l3 -.,'' ta o f e U) Ht lEa '. {, () F.] E .o lols l't I ll (H t.- 7- l= l: o) >. l&x l? (g l.= E ie3!/lu'i lg i (r) l$ bo .t lq,r Y q L ls l: lx5s a* lE 1 l€ o l= o lE T lE e() l-J €5 l:s I lz. ls ./) ) l\) 0llA a lTa l(Bt- xs lils r-l LJ tl IlH ,^ .f,1 U d9 I H ,^l ls 6l; I *€. l€ *t E o :l lovlf col () () -'l rrl I e ,\-l -rl ()tru)e al l* EI: 0-o € 3 IBE c-l I E s tl >,tr 2-,-o I= b ,jl .n(d UI Ili fi E3-;l :JC) 3'r 1.6 e al ll; =r-?_l E :c) EIg TIgq ,,, Eft!-0)l sl =lc ? l= D (g )l H HI 6ril .q-}/,(.)le=r fi ol : :l F r.i .), C.l ^l: gltnErlS=,! IE E H(J ; l General Course Information Course Code: PCC-CSE 3Ol -p / course Assessment Methods (internar: 30; externar: 70) The PEC-IT4O9-P internal and external assessment is based on the level of participation in lab. sessions Course Credits: I and the timely submission of lab experiments/assignments, the quality of solutions designed for Type: Professional Core Lab. Course the assignments, the performance in vIVA-vocE, the quarity of lab. file and Mode: Lab practice and assignments ethical pracrices followed. The internal Contact Hours: 2 hours / week examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the controller of Examination in association with the internar examiner appointed by the Chairperson of the Department. Pre-requisites: Knowledge of C/C+* and Data Structures. About the Course: This lab course provides opportunity to students to implement various algorithms to do graphics. This drawing include lines, circles and ellipses. In addition, students learn to rotate, move and transform graphical obj ects. course outcomes: By tlre end of the course students will be able to: cof implement various graphics algorithms for drawing and filling of geometric objects. (LorS: Apply) Level 3: CO2' demonstrate transformation of geometric objects. (LOTS: Level 3: Apply) Co3' compare strengths and weakness of various graphics algorithms. (LoTS: Level 4: Analyse) co4' design algorithms for creating scenes like flying a kite and solar eclipse. (HorS: Level 6: create) co5' create Iab assignment record that includes problem definitions, solutions and conclusions. (HorS: Level: 6: Create) Co6' demonstrate use of ethical practices, self-learning and team spirit. (LoTS: Level 3:Apply) List of experiments/assignments l A program to ' draw a line using Digital Differenti al Analyzer (DDA) Algorithm 2' A program to draw a line using Bresenharn's Line Algorithnr (BLA) for lines with slopes (a) negative and less than I (b) positive and less than I. ( . (c) positive and greater than l. (d) negative and greater than l. 3. A program to draw a circle using Bresenhanr,s circle Algorithm. 4. A program to draw a circre using Midpoint circre Argorithm 5. Aprogram to draw an ellipse using Midpoint Ellipse Algorithm. 6' Aprogram to fill'different tlpes of geometric shapes using Flood Fill. Algorithm 7. Aprogram to fill different types of geometric shapes using Boundaryhitil no. 8. A prograrn to demonstrate window to view-port mapping. -.-.fW":-; ' 9 - A program to clip a line segment using 4-bit code,argorithm. ':' ,, ' ,r' Q1 \ k@/ ()J \ .,ifi 10. Aprogram to draw a C-Curve of nth order. 11. Aprogram that shows a scene of flying kite. 12. Aprogram to rotate a line about its mid-point. 13. Aprogram that shows a scene of eclipse. 14. Aprogram that translate and rotate a circle along a horizontal line. l5- A program to rotate an ellipse about its major axis and minor axis alternatively. Note: The actual experiments/assignments may vary and will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. 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IC) J IU E ICilslsFsli *l IoI i1 q O IC ' J u lci ls leIle ki I il Python Programming Lab. General Course Information Course Code: PCC-CSE3}2-P I Course Assessment Methods (internal: PCC-IT3O8-P 30; external: 7A) The internal and external assessment is based on the level of Course Credits: 1.5 participation in lab. sessions and the timely submission of lab experiments/assignments, the quality Type: Professional Core Lab. Course of solutions designed for the assignments, the performance in VIVA-VOCE, the quality Contact Hours: 3 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignments The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the controller of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Basic programming skills About the Course: Pyhon is a scripting programming language known for both its simplicity and wide breadth of appiications. For this reason it is considered one of the best languages for beginners. Used for everything from web development to scientific computing Python is referred to as a general purpose language by the greater programming community. The major objective of Pyhon language is to make the students solve real word problem efficiently using python library. course outcomes: By the end of the course students will be able to: COl. implement solutions to the given assignments in Python. (LOTS: Level 3: Apply) CO2. use various Python packages for solving different programming problems. (LOTS: Level 3: Apply) CO3. devise solutions for complex problems of data analysis and machine leaming. (HOTS: Level 6: Create) CO4- Evaluate the output of data analysis and machine learning models. (HOTS: Level 5: Evaluate) CO5. create lab records of the solutions for the given assignments. (HOTS: Level 6: Create) CO6' demonstrate use of ethical practices, self-learning and team spirit.. (LOTS: Level 3:Apply) List of experi ntents/assignments l. Install Python and explore various popular IDE like IDLE, PyCharm, and Anaconda. 2. Assignments to perform various number operations like a. Find maximum from a list of numbers b. GCD of two number e c. Square root of a number d. Check number is prime or not. e. Print first N prime numbers f. Remove duplicate numbers from list g. Print the Fibonacci series. 3. Assignments to perform various operations on Strings like creation, deletion, concatenation. 4- Create a List L: [ 0,20,30]. Write programs to perform following operations: a. Insert new numbers to list L. b. Delete numbers from list L. c. Sum all numbers in list L. "**,L 86 e-' $e ,* k ,4'zi, d. Sum all prime numbers in list L. e. Delete 5' the list L. {'Nanre': 'Allen" 'Age': 27, 5:123456}. ffi,,}"?'::",,:x ': write prosrams to perform a. Insert new entry in D. b. Delete an entry from D. c. Check whether a key present in D. d. Update the value of a key. e. Clear dictionary D. 6' Two assignments on Sets to perform various operation like union, intersection, difference 7 ' Two assignments related to searching etc. operation like linear search, binary 8' Three assignments search. related to sortingiike selection sort, bubble sort, insertion sort. 9' Demonstrate the use of dictionary t.,n.urrring student marks in five subjects the student having maximum and you have to find and minimum average marks. l0' Two assignment on usage of different available packages a' print like random package to perform N random numbers ranging fronr I00 print to 500. b- r 0 random strings whose rength between 3 and 5. I I ' Two assignments on usage of packag. ,u.h as Numpy, pandas. 12' Implement and demonstrate the functions of a simple calculator. on implementing object orienrerd concepr " ;J;*l;il:*t such as crasses, inherirance, a,d 14' One assignment on file handling that how data is read and written to a file. Note: The actual experiments/assignments will be designed by the course coordinator. designed to be done in groups one assignme,t shourd be of two or three students- The and the assignments must meet the objective levels'of the given course outcomes. of the course The list of assilnments and sched,re prepared by the course coordinator of submission wi, be at the beginning of the semester. le ,:t 1-\, .ffi 'i'i .r'* \ ..u..n 87 o?o o rn ca ca a.l al o U) I I A o U) I I n. N I I co tu tl{ C I I (\I ro o E] o I I a n. (J I o\ U I co U a I I c.) () trV) r- I U \o I I I J rf-) bo aa ca C' an I !f, aar o ca an I L .a bo co o I I oo L (-t, o ar) ca ca C.l on ca ca I iti A X l.( 'ot c lan ; (tr q.) : o Alt l.= lF d \ 3(s l- b0 C,i a c.) () PI 1',., c) A l'' ,C) 6l (.) () E l- ,,f*##r' el \-_l_,t., lill ul 1l ". ./.' 4 lr lil =l !! l'-t/) =l (-) ;I a l,=l I r =l oo l:3I U ItIa all .2 511;lvl Cg bo :E lr !- Y I:-lal o-l '"+.1'l lflsl* P lj: o-l -o It 3 lErlE l- EI;'11?cal t! Ib.6 l: o o.rl((glt 0.) t: l- bOl( CIC s ao !li lEi l; '= -iEl al i (c s l; 3- I .s .s l+ E C) )iEI vl L'- ol( = a0) P l-:-;l .5 aolE Lbl s EA trlt A= r,: l< t*l t :ligli- -l b -; .f, l.r \J o lcilE il' I' O (-) lc'li Operating Systems General Course Information Course Code: PCC-CSE3}I-T I course Assessment Methods PCC-IT2O6-T (internal: 30; external: 70) Two minor examinations (20 marks), class performance measured Course Credits:3 through percentage of lectures attend ed (4 marks), assignments (6 marks), and the end- semester examination (70 marks). Type: Professional Core For the end semester examination, nine questions are to be set Contact Hours: 3 hours/week by the examiner. A candidate is required to attempt 5 questions in all. All questions carry equal marks. Mode: Lectures (L) euestion number I will be compulsory and based on the entire syllabus. It will contain parts Examination Duration: 3 hours seven of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four uestions by selecting one question from each of the four units. Pre-requisites: programming in C and knowledge of computer fundamentals. About the Course: The objective of this course is to help students become familiar with the fundamental concepts of operating systems and provide them with enough understanding of operating system design. course outcomes: By the end of the course students will be able to: COI Iist various functions ' and design characteristics of operating systems (LOTS: Level 1: Remember) CO2. explain fundamental concepts of operating systems. (LOTS: Level2: Understand) Co3' apply operating system design concepts for solving problems regarding scheduling, memory management, disk managentent and deadlocks etc. (f ,OTS: Level 3: Apply) CO4- analyze the issues related to various operating systems. (HOTS: Level4: Analyse) CO5' design solutions for the memory and process management problems. (HOTS: Level 6: Create) Course Content Unit I Introductory Concepts: operating systems functions and characteristics, operating system services and systems calls, system programs, operating system structure, operating systems generations, Types of Operating systems: Batch operating system, Tirne-sharing OS, Distributed operating system, Realtime systems. File Systems: Types of Files and their access methods, File allocation methods, Directory Systems: Structured Organizations, directory and file protection mechanisms, disk scheduling and its associated algorithms. Unit II Processes: Process concept, Process Control Block, operations on processes, cooperating processes. CpU scheduling: Levels of Scheduling, scheduling criteria, Comparative study of scherJuling algorithms, Algorithm evaluation, multiple processor scheduling. Critical-section problem, Semaphores. \ t f . i* 1 t :{- ;u'rj-"':''i)":i:'i' pL i}" ,ur,ri**r,rrr- i (, \,f ,f ri"* t ,wi!' 91 Unit III Storage Management: Storage allocation methods: Single contiguous allocation, non-contiguous memory allocation, Paging and Segmentation techniques, segmentation with paging, Virtual memory concepts, Demand Paging, Page replacement Algorithms, Thrashing. Unit IV Deadlock: System model, Deadlock characlerization, Methods for handling deadlocks, Deadlock prevention, Deadlock avoidance, Deadlock detection, Recovery from deadlock case Studies: comparative study of wINDow, uNIx & LINUX system. Text and Reference Books: 1. Silberschatz,Peler B. Galvin and Greg Gagne, Operating System Concepts,Sth Edition, Wileylndian Edition,2010. 2. Andrew S Tanenbaum, Modern Operoting System.s, Third Edition, Prentice Hall India, 2008. 3. Naresh Chauhan, Principles of Operating Systems, Oxford Press, 2014. 4. D.M. Dhamdhere, Operating Systen,.i,2ndedition, Tata McGraw Hill, 2010. 5' William Stallings, Operating Systems- Internals ancl Design Principles, 5th Edition, prentice Hall India,2000. ,ffr i 92 (,a a I I ?.I I I a I a co ca co cn cn N I I I F( I rnI ro a\ I arc I U I oo U I U t{ r- I I q) a I I U rn c'l o..l c.l q) a t o c.l b0 co ro o\ aa co I q) al c\| ol *) x cn ca CN l- (n a o0 a C .E F () 6 1- 0) ()L J General Course Information Course Code: PCC-CSE306-T I Course Assessment Methods (internal: PCC-IT3O3-T 30; external: 70) Two minor examinations (20 marks), class performance Course Credits:3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Core marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. AII questions carry equal marks. euestion number I will be compulsory Examination Duration: 3 hours and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining fbur questions by selecting one question from each of the four units. Pre-requisites: The students are expected to have a strong background in the fundamentals of discrete rnathematics like in the areas of symbolic logic, set, induction, number theory summation, series, combinatorics, graph, recursion, basic proof tecirniques. About the Course: Formal Languages and Automata theory presents the theoretical aspects of computer science, which lay the foundation for students of Computer Science. The course introduces some fundamental concepts in automata theory and formal languages including grammar, finite automaton, regular expression, formal language, pushdown automaton, and Turing machine. Course outcomes: By the end of the course students will be able to: COl. define terminologyrelated to theoryof computation. (LOTS: Level l: Remember) CO2. explain the basic concepts and applications of Theory of Computation. (LOTS: Level 2: Understand) CO3. apply principles the of Theory of Computation to solve computational problems.(LOTS: Level 3: Apply) CO4. compare and contrast the hierarchy of grammars (HOTS: Level 5: Evaluate). -\ CO5- design various types of automata for given problerns. (HOTS: Level 6: Create) i ,.+-*$,:* "\v f' Course Content Unit I Finite Automata airrd Regular Expressions: Finire state Systems, Basic Definitions Non-Determipistirfi'm-iij automata CNDFA), Deterministic finite automata (DFA), Equiv?lence of DFA and NDFA Flniie automata with E-moves, Regular Expressions, Equivalence of finite automata and Regular Expressions, Regular expression conversion and vice versa, Conversion ofNFA to DFA by Arden's Method. Unit II lntroduction to Machines: Concept of basic Machine, Properties and limitations of FSM. Moore and mealy Machines, Equivalence of Moore and Mealy machines. Properties of Regular Sets: The Pumping Lemma for Regular Sets, Applications of the pumping lemma, Closure properties of regular sets, Myhill-Nerode Theorem and minimization of finite Automata, Minimization Algorithm. 94 Unit III Grammars: Definition, context free and context sensitive grammar, Ambiguity regular grammar, Reduced forms' Removal of useless Symbols and unit production, chomsky Normal Form (cNF), Form (G}.IF). Griebach Normal Pushdown Automata: Introduction to Pushdown Machines, Application of pushdown Machines Unit IV Turing Machines: Deterministic and Non-Deterministic Turing Machines, Design of T.M, Halting problem T.M., PCP Problem. of chomsky Hierarchies: chomsky hierarchies of grammars, flnrestricted grammars, context sensitive languages, Relation between languages of classes. computability: Basic concepts, primitive Recursive Functions. Text and Reference Books: I' Hopcroaft & o' D' Ullman, R Mothwani, Int,ocluction to automata theory, AW200l. longuage & computat[ons, 2' K' L' P'Mishra & N' chandrasekaran, Theory of Computer sc.(Artontata, Languages o pHI, and c mput a t ion), 2000 . 3 Peter ' Linz, Introcluction to formal Langttages & Atttomato,Narosa, publicatio n, 2001 . 4' Ramo,d Greenlaw and H' Jantes Hoover, Funtlamentals of the Theory of computation- principles and Practice, Harcourt India pvt. Ltd., 199g. 5' H' R' Lewis & C. H. Papaditriou, Elements of theory of Comptttation,pHc, 199g. 6' John c' Martin, Jntrocluction to Languages and the Theory dCompuration,T.M.H., 2003. e 9s ro V) I I I I (\l o U) I a ca cn ca ca ca F (\I \oI I I CO tEl a I I U I U U I q) o\ ta t 6 U I I h F- () I I I Fr \c I I ia I a{ a{ N 1 !? c..l N ro \o N C.t 6I () o\ bo (\l I c'l a.t bo J c.l ca ra tr q- a U () F f-. o I>r : >l 9-.; t! o U) .\t) X (/) , ':'.-'a-t .Y'.,,'? o t3 .A l. - 'tLz le o ! ' tr C) -q -/: IF -o o--.'r.' Ir L e l^ d= o- | .c r l- o loc a0 (.)= q- l'=tg a '"; q< .z 13"? ;d) U u0 x l=q.l (L) :< i I o- ' General Course Information Course Code: PCC-CSE 307 -T / course PEC-IT4O7-T Assessment Methods (internar: 30; externar: 70) Two minor examinations (20 marks), clais performance Course Credits:2 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Core marks). Contact Hours: 2 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate Mode: Lectures (L) is required to attempt 5 questions in all. questions All carry equar marks. euestion number I will be Examination Duration: 3 hours compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Basic programming skills, probability and Statistics About the Course: Data analytics is a growing and stimulating field that turns data into valuable insights. This course includes programming in R for acquiring, cleaning, visualizing and analyzing d,ata. In addition, it also involves predictive modeling' This course will introduce students to the basic principles, tools and the craft for devising solutions for problems that come in the domain of data science. The emphasis of the course is on integratio, and synthesis of concepts and their applications for effective engineering solutions. course outcomes: By the end of the course students rvil be abre to: col outline concepts related to R programming ' and data analysis. (LoTS: Level 1: Remember) Co2' explain the basic concepts and tools that are used to solve problems in data analytics. (L9TS: Level 2: Understand) CO3' interpreting results of descriptive and inferential statistics. (LOTS: Level 2: Understand) Co4' apply R programming for reading, cleaning, visualizing and analysing data. (LOTS: Level 3: Apply) co5' analyse the trends in data through exploratory data analysis. (HoTS: Level4: Analyse) CO6' devise solutions for descriptive and predictive modelling. (HOTS: Level 6: Create) Course Content Unit I Introduction to R programming: Data types or objects in R, Creating and manipulating objects like factors, vectors and matrices, Iists and data frames, Subsetting matrices and data frames, Vectorized operations for vectors and matrices and data frames. Unit II Control structure in R: If-else statements, for and while loops, loop functions like lapgly, apply, sapply and mapply etc.; writing user defined functions in R. Getting data in and out of R. Ke, 97 Unit III Doing basic'descriptive statistics: Data tlpes for data analysis and their mapping to R objects, Mean, Median, Mode, Quantiles, Five-point summary, Variance, Correlation and Covariance, normal distribution, uniform distribution using R, Hypothesis testing: Chi-Square test and student's T test. Unit IV Exploratory Data Analysis: Visualizing data through various plots and charts (bar charts, histogram, frequency polygon, scatter plot, box plots etc.), Applying KNN and Bayesian predictive models. Text and Reference Books: 1. Hadley Wickham and Garrett Grolemund., R for Data Science Import, Ticly, Transform ancl model Data, O'Reilly, 2017. 2. Roger D. Peng, R Programmingfor Data Science, Lean Publishing, 2015. 3. Paul Teeter, R Cookboofr, O'Reilly,20ll. 4. W. N' Venables, D. M. Smith and the R core Team, An introcluction to R, Notes on R; A programming Environment for Dotcr Analysis ancl Graphics, version 3 .3.2, 2016. 5. Michael J. Crawley, Statistics, An introduction using R, Second edition, John Wite y, 2015 6- Han, J', Kamber, M, Pei, 1., Dato Mining Concepts and kchniques, Third edition, Morgan Kaufmann, 2012. 7. Trevor Hastie, Robert Tibshirani, Jerome Friedman, The Elentents of Statistical Learning: Data Mining, Inference and Prediction,springer, 2'd edition, 2009. i ;? t 98 ro o (\ a ca cn aa co oN I a I I I a I I 0r N I I I F,. I t\ C I I tr) (t)tEl I I U I I ) U tr U o\ -t c I a.l q) (n L 6 c I o A I I U fr F-l r Ol I I ao A-l (r) \ot Cl r ar) I () 0. I I rf-) c c.} rO co d o\ r+ t A ca (^.l r.) ti X co ir a't N \( a= al (..l I ca ro 63I c cn ca (.'l ol=l ao -l-. I Ll hol EI P I 9t -f, I FI (\Jl / dl cl Fl - 'ol^l 'ol el EI =t = I -t:l(\ll 6t \o El I +l PI 3 EN JI i: u6 | CI 30jj I 8 6r El s)6 I l-I 3ry I €na I EB I O-()I P0)L AI iri. UI I 9\l € oJ :.{ !i (d5 I i. ed I !(s tr,'-rltl.*; I a5 I oJ I es l-=rlJ*t gFF €l en I vl. l\ :i HAI 0)F General Course Information : Course Code: PCC-CSE308-T/ course Assessment Methods (internal: 30; external: 70) Two minor examinations (20 PCC-IT3O2-T marks), class Performance measured through percentage of lectures attended (4 marks), assignments (6 marks), Course Credits: 2 and the end- semester examination (10 marks). For the end semester examination, nine questions Type: Professional Core are to be set by the examiner. A candidate is required to attempt 5 questions in all. All questions Contact Hours: 2 hours/week carry equal marks. Question number I will be compulsory and based on the entire syllabus. It will contain seven parts Mode: Lectures of 2 marks each. Question numbers 2 to 9 will be given by setting two Examination Duration: 3 hours questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Object oriented languages About the Course: .NET using C# is a core and an essential advanced course for every graduate in Computer Science and Engineering. This course introduces .NET Framework basics with object orielted technology like CLS, CTS, CLR, Assembly, Typelnfo, Delegates and Reflector etc., and various operations to be implemented surrounding these features for solving real world problems. It includes ADO.NET franrework with its classes for database connectivity. Course outeomes: By the end of the course students lvill be able to: CO1. define the concepts related to .NET Framework. (LOTS: Level 1: Remember) co2. explain various c# constructs. (LorS: Level 1: understand) CO3. apply .NET framework using C# for solving moderate/complex problems. (LOTS: Level 3: Apply) CO4. use advanced features of C# like Reflector, andAssembly. (LOTS: Level 3:Apply) CO5. identifynlogical errors in given .Net using C# programs. (LOTS: Level 3:Analyse) CO6. Design'iiand-alone applications in the .NET framework using C#. (HOTS: Level 6: Create) i Course Content .- Unit - I 'NET Framework;, Beginning of NET Technology, Overview of, .NET Framervork, .NET Framework Class Libraries, NET Pi.ogramming Languages, NET Namespaces 4rrd Type. Architecture of .NET Framework. Common Language'.Runtime (CLR) - Common Type Specification (CTS), Commol Language Specifications (CLS), Assemblies of .NET Base Classes, CLR Debugger. Unit - II Evolution of C#: Overview of C#, C# and .NET, Similarities & Differences irom JAVA, Structure of C# program. Data Types inciuding out and Ref, Identifiers, variables & Constants, Flow Control and Iteration, object-oriented Programming in C# - Encapsulation, Inheritance, and Polymorphism, Object and Classes, Basics of C# Classes, *,l **.*3s#-Sfu, ,*n ;'r-- \ i,' ) ,i" 100 UniIIII Creating DLL files, Assemblies of multiple versions. GAC Utility and Strong Name, Arrays and Strings, Boxing and unboxing, - Exception Handling in c#, Garbage collectio4 & Its stages, Files and Sreams, Deligates and their usefulness and Events, Attributes, I/O in C# and Windows Applications. Unit - IV Architecture of ADO.NET, Database Connection, Connected and Disconnected Enyironment, Create connection using ADO.NET object Model, connection class, command class, Data Adapter class, Dataset Class. Text and Referenc€ Books: l. Benjamin Perkins, Jacob Vibe Hammer and Jon D. Rei d, c# 6 programming,with wsual studio,wrox publication, 2016. 2. Matt Telles, C# Programming,Black Book, Coriolis Group, 2001. 3. Stephen C. Perry. Atul Kahate, ,ss", tial of .NET and Related Tbchnologies,Pearson Education 2009. -, :l ,,;jfu l0t o?o a I I (.l a I I a C\ ca cft cn c.! co t\l I I I I I I I FI oo Or m I E] U) U 00 t I U U F- l-l I I I () a \o I U rn +t on C..t ca U tf bo C I I N U) co c.l F o I C.l O H t .a) q)c) J ac/, Embedded System Design General Course Information Course Code: PEC-CSE 3Al -T / course Assessment PEC-IT3OI.T Methods (internal: 30; external: z0) Two minor examinations (20 marks), class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester Tlpe: Professional Elective examination (70 marks). Contact Hours: 3 For the end semester examination, nine questions are to be Mode: Lectures (L) set by the examiner A candidate is required to attempt 5 questions in all. All questions carry equar marks. Examination Duration: 3 hours. euestion number I will be compulsory and based on the entire syllabus- It will contain seven parts of 2 marks each. Question numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Introduction to Microprocessors and operating Systems. About the Course: An embedded system is a self-contained unit that have a dedicated purpose within a device. We come across a variety applications of of embedded systems in navigation toois, telecom applications, and networking equipment to name just - a few. An Embedded System's Architecture begins with a view of embedded development and how it differs from the other systems. Students learn ibout setting up a development environment and then move on to the core system architectural concepts, exploring pragmatic designs, boot-up mechanisnrs,'and memory management- They are also explored to programrning interface and device drivers to establish communication via TCP/IP and take measures to increase ihe iecurity of IoT solutions. Course outcomes: By the end of the course students will be able to: COI state - the concepts related to embedded system design. (LOTS: Level l: Remember) CO2. discuss the principles of embedded systems and their applications. (LOTS: Level 2: Understand) CO3. apply the principles of embedded design for problem solving. (LOTS: Level 3: Apply) CO4- analyze architectural design patterns and engineering tradeoffs. (HOTS: Level 4: Analyse) CO5. design architectural patterns for connected and distributed devices in the IoT. (HOTS: Level 6: Create) Course Content Unit I Embedded Systems: A Pragmatic Approach- Domain definitions, Embedded Linux systems, Low-end g-bit microcontrollers, Hardware architecture, Understanding the challenge, Multithreading, RAM, Flash memory Interfaces and peripherals, Asynchronous UART-based serial communication:-Spl - IZC - USB, Connected systems, The reference platform, ARM reference design, The Cortex-M microprocessor Work Environment and Workflorv Optimization: Workflow overview, C compilel Linkel Build automation, Debugger, Embedded workflow, The GCC toolchain, The cross-compiler, Compiling the compiler, Linking the executable, Binary format conversion, Interacting with the target, The GDB ..rrion, Validation, Functional tests, Hardware tools, Testing off_target, Emulators. , ,..',r,lj.* . \ -"' ro3 *: W e/ u{' Unit II Architectural Patterns: Configuration management, Revision control, Tracking activities, Code reviews, Continuous integration, Source code organization, Hardware abstraction, Middleware epplication code, The life cycle of an embedded project, Defining project steps, Prototyping Refactoring, API and dtcumentation, The Boot-Up Procedure: The intemrpt vector table, Startup code, Reset hancller, Allocating the stack, Fault handlers, Memory layout, Building and running the boot code, The makefile, Running the application, Multiple boot stages, Bootloader, Building the image, Debugging a multi-stage system, Shared libraries Unit III Distributed Systems and IoT Architecture: Network interfaces, Media Access Control, Ethernet, Wi-Fi, Low- Rate Wireless Personal Area Networks (LR-WPAN), LR-WPAN industrial link-layer extensions, 6LoWpAN, Bluetooth, Mobile networks, Low-power Wide Area Networks (LPWANs), Selectiirg the appropriate network interfaces, The Internet Protocols, TCP/P implementations, Network device drivers, flurmlng tne fCpZlp stack, Socket communication, Mesh networks and dynamic routing, Transport l-ayer Security, Securing socket communication, Application protocols, Message protocols, REST architecturai pattern, Distributed iystems; single points of failure, Surnmary Unit IV Lolv-Porver Optimizations: System configuration, Hardware design, Clock management, Voltage control, Low-power operating modes, Deep-sleep configuration, Stop mode, Standby ,rrld", Wake-up intervals, Measuring power, Development boards, Designing low-power embedded applications, Replacing busy loops with sleep mode, Deep sleep during longer inactivity periods, Choosing the clock speed, porver state transitions Embedded Operating Systems: Real-time application platforms, FreeRTOS, ChibiOS, Low-power IoT systems, Contiki OS, Riot OS, PoslX-compliant systems, NuttX, Frosted, The future of safe embedded systems, Process isolation; Tock, Summary. Text and Reference Books: 1 . Daniele Lacamera , Embedded Systems Architecture, Packt Publishing, May 201g, ISBN: 978 I 78 88 32502. 2. Raj Kamal, Embedded Systems, TMH, 2004. 3. M.A- Mazidi and J. G. Mazidi, The B05l Mict'ocontroller ancl Embertctert Systems,p1l,2AO4. 4. David E. Simon, An Embedclecl Sofnuare Printer,Pearson Education ,lg9g. 5. K.J. Ayala , , The 805 I Microcontroller, penram Internation al, 1991. 6. Rajiv Kapadia, 805I Microcontroller' & Embecldecl Systems, Jaico Press, 2004. 7. Prasad, Embedded Real Time systent, wiley Dreamtech,2004. 8. John B. Peatman, Design wilh PIC Microcontrollers,Pearson Education Asia, 2002. 9. Wayne Wolf, Computers as components: Principles of Embectdetl Comptrting System Design,Morgan Kaufman Publicatio n, 2000. 10. Tim Wilmshurst, The Design of Small-Scale embetklecl systems,Palgrave,2003. I 1. Marwedel, Peter, Entbeddecl System Design, Kluwer Putlishers ,2004. / a -*1 104 o?o U) I I I I ol (r) I U) ro cn cn .a a^ N I I c I I F I c ro El o\ U) U I t U oo H c I I t{ r- e) I I l-U) \o I U I ra bo N a{ ra ()U) s I C..l aa q) tl (n I I an N (t) tr) ot O q) .J ca ca e) c{ ca aa rI] d >< *)L al- ;l,l;lglsl V FElF?l c, L U q J Wireless and Mobile Communication -I General Course Information Course Code: PEC-CSE3}2-T I course Assessment PCC-IT4O I -T Methods (internal: 30; external: 70) Two minor examinations (20 marks), class performance measured Course Credits: 3 through percentage of lectures attended (4 marks), assignments (6 marks), Type: Professional Elective and the end- semester examination (70 marks). For the end semester Contact Hours: 3 examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions in Mode: Lectures (L) all. All questions carry equal marks. euestion number I will be compulsory and based on Examination Duration: 3 the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Basic knowledge of computer networks, Network Architecture and reference nrodel, High speed Network technologies, Ethernet, TCP/IP architecture. About the course: This course attunes the students with mobile and wireless communication using the Networking infrastructure of organizations/institutes. Students learn to analyse Networks'Architecture for wireless conrnrunication and the protocols various for layers in the Wireless Networks, technologies used and application arena of Wireless Networks. course outromes: At the end of this course students will be able to: COI- recall different mobile and wireless communication concepts. (LOTS: Level l: Remember) CO2- explain working of different Mobile Communication Technologies used now a days. (LOTS: Level2: Understand) CO3. demonstrate application of different mobile protocols for different Mobile and Wireless communication Technologies. (LorS: Level 2: understand) CO4. analyze performance the of different Mobile Communication technologies in different scenarios / situations. (HOTS: Level 4: Analyse) CO5' design a mobile network for any citylstatelcountry using combination of different Mobile Technologies. (HOTS: Level 6: Create) ourse Content unit I Mobile Communication:' Wireless Transmission--- F."qr.nli.r, signals, antennas, signal propagation, multiplexing, modulation, spread spectrum, cellular system. Specialized MaC, SDMA, FDMA, TDMA- fixed TDM, classical ALOHA, slotted ALOHA, CSMA, DAMA, PRMA, reservarion TDMA. Collision avoidance, polling inhibit sense multiple access. CDMA, GSM- mobile services, architecture, radio interface, protocol, localization, calling, handover, security, new data services, Introduction to WLL. Unit II Wireless LAN IEEE 802.1 1-System and protocol architecture, physical layer. Frame fornrat. Bluetooth--- Protocol architecfure, Frame fonnat. i' wiMAx - Layered Protocol architecture, frame types, format, Applications lntroduction to LTE, LTE advanced, VoLTE 106 u Unit III Mobile network Layer: Mobile IP- goals, assumption, requirement, entities, terminology, Ip packet delivery Agent advertisement and discovery registration, tunnelirrg, .rr.upsulation,'optimrzation , reverse tunneling, Desiination ll"Yf;"n3ffit,*|,ff )[ff]|]-#|,::- , Seque,." Dirtunce vecto., ay,,amic source routing, Unit IV Mobile Transport Layer: Traditional TCP, Indirect TCP, Snooping TCp, Mobile TCp fast retransmissior/ recovery, transmission/time out freezing, selective retransmission, Transaction oriented TCp. Text and Reference Books: l. Jochen Schiller, Mobile Communication,2nd Edition, pearson ,2009. 2- Andrew S Tanenbaum, Compttter Nehuorks,5rh Edition, p"urro, 2013. 3' william c Y Lee, Mobite Communication Engineering: Theory ancl Applications,2nd Edition, Hill, lgg7. McGraw .t 1 t ,. , I{' -=r{,f*--/ _1. -,.L'' I j t -._J q\ w\ 107 ca o V) I I N o c.) V) cn ca r.l ra U) I I N I N F! c.l o N ra ord U o I I I I U 01 14 Fi () oo a I ir I o r- U I I I C) rf.) I N aa =f a.l co U c.) e) I I N aa co ta .I a N rO N ca U) ()U) \o Lc) x lr zlrl lgl=glgs rErEglfE q) / liilisl ,F'.'''q nil tr lEi liE *s-, , c L Frt I lf,l; U s I' ltl Graph Theory General Course Information Course Code: PEC-CSE 303-T I Course Assessment PEC-IT303-T Methods (internal: 30; external: 70) Two minor examinations (20 marks), class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type : Professional Elective marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt questions Mode: Lectures (L) 5 in all. All questions carry equal marks. euestion number t will Examination Duration: 3 hours be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the foui units. Pre-requisites: Basic knowledge of Abstract Algebra, Set Theory and Counting Tec6niques About the Course: Graph Theory is an elective course for every graduate in Computer Science and Engineering. The importance of Graph Theory reveals from the fact that it can be applied to solve any practical problem in electrical networks, operation research, data strucfure or social sciences etc. Also, Graph Theory provides easy representation of mathematical facts with insightful theories behind them. This course explains different types of graphical structures, related properties, various operations and facts related to these graphical structures with the help of proofs, course outcomes: By the encl of the course students lvill be able to: col. recognize different kinds of Graphs. (LorS: Level l:Remember) Coz' demonstrate various types of graphical structures with the operations implemented on these structures. (LOTS: Level 2: Understand) CO3. apply graph theory constructs for solving problems. (LOTS: Level 3: Apply) CO4' justify various facts and results associated rvith graphical structures with the help of proofs. (HOTS: Level 5: Evaluate) CO5' sketch the graph to solve any problem in pictorial and easy {gpresentation. (HOTS: Level 6: Create) Course Content Unit I . Introduction to graphs, Types of graphs -Regular, Complete, Bipartite, .Isomorphic, Connected, Applications, operations on Graphs, Walks, Path, Circuits, Euler Graphs, Flamiltonian path and Circuits, Trees, properties of Trees, Spanning Trees (Standard Results with proofs based on all mentioned topic). Unit II Cut-Sets, Properties of Cut-Set, AII Cut-Sets in a graph, Fundamental Circuits and Cut-Sets, Connectivity and r-Isomorphism, 2- Iso':,prphisrn, tSH#eKuratowski's rrvo Graphs ,T,'.XT.T'iL.)llJ,iJ""rLl toer * a^) ' **- Unit III Sets with one operation, Sets with two operations, Modular Arithmetic and Galois Fields, Vector and Vector " . Spaces, Vector Space associaled with a graph, Basic Vectoru of a graph, Circuits and Cut-Set Subspaces, Orthogonal Vectors and Spaces, Interse ction and, lon of ll/ and lV,. Unit IV Matrix representation of graphs,Incidence Matrix, Submatrices, Circuit Matrix, Fundamental Circuit Matrix and Rank, Coloring of graphs: Chrornatic Number, Vertex Coloring of graphs, Edge Coloring of graphs, Coloring of Planar Graphs. Text and Reference Books: 1. v. K. Balakrishnan, Graph Theory, Tata McGraw Hill, l" Edition ,2004. 2. Narsingh Deo, Graph Theory with Applications to Engineering oncl Conrputer Science,Prentice-Hall of India, Reprint, 2004. 3. Frank Harary, Graph Theory, Narosa/Addison Wesley, Indian Student Edition, 1988. 4. Bollobas, Bela, Modern Groph Theory, Springer Verlag New York, 1't Edition, 1998. 5. R. Diestel , Graph Theory, Springeq 2"d Edition,2000. 6. Douglas B. West, Introcluction to Graph Theory,Prentice I-Iall of India, 2'd Edition,2A02. .,\ I, !.-t a r 't .-rF"*,',:', -l''/ ./ 110 o?o I a I I N u) I I o U) N c-) co ca CO 6l o I N N A o I I { o I FI TO o\ ta o I frl I V) U € I I U f-l r- o I I I nr I o a \o L o I U rA h I c.l 6l N o .+ o I a^ a{ F ?a o I (-.1 A rtir 6l o c^ a'l X lr o c..l a.l c'l ca ca a= () (.) C) L ) :II?lgrlgl 4 a c F o ;? l* l;Ils I t -] U' EE lr lsEl;sl U o (g #u q-o o $I lf lI Eli;l _ L igglEflgE/gg/g U i/3F/; l- l= l: , l,l. 13 lS li Bio-informatics General Course Information: Course Code: PEC-CSE 304-T I Course Assessment Methods (internal: PEC-IT304-T 30; external: 70) Two minor examinations (20 marks), class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Tlpe: Professional Elective marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. All questions carry equal marks. euestion number I will be Examination Duration: 3 hours compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: None About the Course: The scope of Bio-informatics is growing rapidly. Analysing data related to bio-informatics is not possible without computational skills. This course is designed to impart fundamental knowledge of bio-informatic .,uvhich would enable students to understand the intricacies of Bioinformatics. The students will learn about the characteristic of bio-infonnatic data and the tools for analysis of such data. Course Outconres: By the end of the course students lvill be able to: COl. list the applications of bioinformatics and biological databases. (LOTS: Level l: Remember) CO2. explain storage and retrieval of bioiogical data from various biological databases. (LOTS: Level 2: Understand) CO3. apply the knogle'dge of bio-informatic concepts. (LOTS: Level 3: Apply) CO4. identify challepges in bioinformatics and computational biology. (HOTS:Level 4: Analyse) CO5. compare and;cotttrast various algoritluns for sequence alignment and scoring algorithms. (HOTS: Level 5: Evaluate) -.,, CO6. devise schenres'for addressing bb-informatic problems. (LOTS: Level 6: Create) :t, 1.4 f, Course Content Unit: I Bioinformatics: Introduction to Bioinformatics, Scope, Overview of molecular biology & genetics, Nucleic acid; structure & function, Protein structure & function; DNA Replication, Transcription, Translations, Genetic code, Codon Bias, Molecular Biology Techniques used in Bioinformatics. \ Computer applications in.molecular biology, Protein domains and human genome alalysis program (BLAS+,, FASTA etc.). Search and retrieval of biological information and databases sequence, databank (]jCBI)l2hrs \ 'r-.-#GN "{ 112 Unit: II Sequence Alignment PairwiseSequenceAlignment:EvolutionaryBasis,SequenceHomologyversusSequenceSimilarity,Sequence Similarity versus Sequence Identity, Methods, Scoring Matrices, Sratistical Significance ofSequence AligDment DatabaseSimilaritySearching:UniqueRequirementsofDatabaseSearching,HeuristicDatabaseSearching, Basic I-ocal Alignment search Tool (BLAST), FASTA, comparison of FASTA and BLAS! Database searching with the Smith-Waterman Method. Unit: III Multiple Sequence Alignment: Scoring Function, Exhaustive Algoritbms, Heuristic AJgorithms, practical Issues. Profiles and Iridden Markov Models: Position-Specific profiles, Scoring Matrices, Markov Model and Hidden Markov Model. Protein Motifs and Domain Prediction: Identification of Motifs and Domains in Multiple Sequence Aligrunent, Motif and Domain Databases using Regular Expressions, Motif and Domain Databases using Statistical Moders, protein Famiry Databases, MotifDiscovery in Unaligned Sequences, Sequence Logos. Unit: tV Molecular Phylogenetics Phylogenetics Basics: Molecular Evolution and Molecular Phylogenetics, Terminology, Gene phylogeny versus Species Phylogeny, Forms of Tree Representation, procedure. Phylogenetic Tree construction Methods and Programs: Distance-Based Methods, Character-Based - Methods, Phyiogenetic Tree Evaluation, phylogenetic f.ograms Text and References Books: l TKAttwoodandDJParrysmith,IntroducliontoBioitorlnalics,PearsonEducationAsia,Singapore, 2001. 2. Sensen, C.W-, Essentials of Genomics arul Bioinformarics,lolnWiley and Sons. 2002 pary-Smith, 3. Attwood, T. and D., .Iz troducrion to Bioinformatics, preriiceHall.lggg 4' Baxevanis, A.D. and ouellette' B F.F. ' . Bioitonnatics: A Prqctical Gukle to the Analysis of genes and Protein, Wlley- lnterscience, 2001 5 Stuart M. Brcwn, Bioinfotmotics: A Biologists Guide to Compuling and the Internet,NKU Medical centre. NY USA, 2000. ffi 113 ro o U) C\ cn co C. aa co cN V) I I I I q I N I I I I I I F I .+I o\ ca aFi I U oo t I U H r- I I I I q) U) \o U rrl U) I I c\ C\I c) t I ao +< co -f, I I a.l (-.l I (\l I C\ ca co >< a\ c! r.) z a o :- CC | ()d lq ls H l= I bo ,l- lJ le lE s Cg C3 l-,e r; li I (J li 5 o) rB o,= l*r l: IE I I t- E; a b0- lE ox .e: l- ,) '9 c.i : to U 0) tr() q<() 5e lE I .o6 OJ E IE E =* S rzt eE l:? ()! E l€ $ I l- -o I o .. I Fa l4 ;()5- t-v .r lI \* ()-- ts 15 I \., c) U)J E I€ E E General Course fnformation Course Code: PCC-CSE3}S-P / Course Assessment Methods (internut, 30; erte.nal: 70) PCC-IT2O6-P The internal and external assessment is based on the level of Course Credits: I participation in lab. sessions and the timely submission of lab Tlpe: Professional Core Lab. Course experiments/assignments, the quality of solutions designed for Contact Hours: hours/week 2 the assignments, the performance in vIVA-vocE, th; quality Mode: Lab practice and assignments of lab. file and ethical practices followed. The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the controler of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Basic programming skills. About the Course: This lab' course on data science involves a rigorous training on R programming. It ilcorporates solving problerns related to data sciettce in statistical and predictive modelling framework. The objective of the lab course is to equip the students to solve the practical data science problems related to intelligent data analysis using R. Course outcomes: By the end of the course students will be able to: COl' apply commands related to and vi Emacs editors, general utilities and file systems. (LOTS: Level 3: Apply) Co2' rvrite basic shell scripts and use sed commands as well as awkprogramming. (L6TS: Level 3: Apply) CO3' analyse the results memory of management and disk management commands. (HOTS: Level 4: Analyse) co4. evaluate solutions for different operating system problems such as scheduling, memory management and file management. (HOTS: Level 5: Evaluate) CO5' create lab record assignments for that includes problem definitions, design of solutions and conclusions. (HOTS: Level 6: Create) CO6- demonstrate use of ethical practices, self-learning and team spirit. (LOTS: Level 3: Apply) List of experiments/assignments: Srudy of WINDOWS ' and Linux operating system (Linux kernel, shell, basic commands pipe & filter conunands). o Study vi editor. . Administration of LINUX Operating System. . Writing of Shell Scripts (Shell programming). d o AWK programming. . write a c program to simulate different scheduling algorithms ' Write a C program to simulate different file allocation strategies Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be objective of the course and the levels of the given course outcomes. The list of assignments and of submission will be prepared by the course coordinator. at the beginning of the semester. U,v 115 ocA q I I (\l a I I a c.t ca c.) (\t I I I cn I I P. I I I aa raI ra o\ I r.) ard U 00 I U I ao U r- I I \o -] I I ln 0) ai a.l a I V) v 6l a.l bo cA \o I I I q) (\t, N c{ I X o.l a.l ol zF{ (g oL o cO () .i ,:. L ;o- U< ocna I ftBc() U EJ i'Elga,gi (\JA '-F Ol -C l+ s l igliilgiglg;lgslu ilE rl' jlE ;lj ul). C) l< rglisligrllgsllilg 3lE E li ( ( .vll;=l;i l3,ld 15 l5 li Data Analytics using R Lab. General Course fnformation Course Code: PCC-CSE 307 -p / Course Assessment PEC-IT4O7-P Methods (internar: 30; externar: 70) The internal and externar assessment is based on the level of Course Credits: 1.5 participation in lab. sessions and the timely submission of lab experiments/assignments, Type: Professional Core Lab. Course the quality of solutions designed for the assignments, the performance in vIVA-vocE, the quarity Contact Hours: 3 hours/week of Iab. file and ethical practices followed. Mode: Lab. practice and assignments The internal examination is conducted by the course coordinator. The external examination is conducted by.external examiner appointed by the controller of Exarnination in association with the internar examiner appointed by the Chairperson of the Department. Pre-requisites: Basic programming skills and knowledge of statistics About the Course: This lab' course on data science involves a rigorous training on R progranlrning. It incorporates solving problems related to data science in statistical and predictive modelling framework. The objective course of the lab is to equip the students to solve the practical data science problems related to intelligent data analysis using R. course oulcirmes:.By the end of the course students lvirl be abre to: Col implement R programming ' concepts for data analysis. (LoTS: Level 3: Apply) Co2' analyse the trends in data tlrough explorato ry dataanalysis. (HoTS: Level 4: Analyse) co3' evaluate the results of descriptive and inferential statistics. (H0TS: Level 5: Evaluate) CO4' devise solutions for descriptive and predictive modelling. (HoTS: Level 6: create) co5' create lab' Record of assignment solutions that include problem definition, solutions and interpretation of resurts. (Hors: Lever 6: create) co6' demonstrate use of ethical practices, independent enquiry and self-learning, and team spirit to solve unseen problems. (LOTS: Level 3: Apply) List of experi ntents/assignnren ts l ' Install R studio and explore its GuI- Explore the base R package- datasets. See the list of datasets available in the package. write description for the following datasets: i. HairEyeColor ii. Iris iii. Airquality iv. mtcars In addition to general description of the dataset, it should include the number of attributes and instances, class of the datasets. It should also include the type of each attribute. Apply summety) and str0 functions to these datasets. 2. Tlrree assignment related to creating a,d manipulating objects factors, nratrices, lists and data frames. 117 ,o'' 3. Two assignments on the use ofconlrol, looping statements and user defined functions. 4. Two assignment on finding descriptive statistics and exploratory data analysis. ;' 5. Two assignments on - making diflerent charts and writing the finding on the basis ofthese charts. 6- Two assignments on hypothesis testing for descriptive and inferential statistics. .- Two assignments 7. on predictive modelling using R packages in groups of two or th.ree students . depending on the size ofthe assignment. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. --_v ?' r18 n c{ cn ca ,) co I 1. N o U) I I U) I I (-l I I I I cn I I l-( I f- r.l ?a I ari o\ U I I I ca I U oo U I co r- ."&1 I I I J \o q\* tl I I *d6=- bo rn -4 cn aa .A c CO ca q) $ \ a) ca co ca *) I I ca N t\t C.J ca ca I I ; X a! C! CO c.) \-. fr I z ,h o ab I I ; l. a q lo= I =F ll$ lE i I =D = Y-o nY c/) g l€v I () 3 l.=h I l$ P JC) lf <() L C) r l-E= l;62 t- ,0) lF l)) ls )a i) IEE ll cl lE ls -o I'5 X ll +l aA^o I la lr lE la t:ri l;g l! UI ts lE rr l';r.E I IH IE : li E ll t'il loo le : l= a l( ii l+ 6- i l.:o 5 l. ,3l General Course Information Course Code: PCC-CSE308-P Course Assessment Methods (internal: 30; external: 70) The internal and external PCC-IT3O2-P assessment is based on the level of participation in lab. sessions and the timely submission of lab Course Credits: I experiments/assignments, the quality of solutions designed for the assignments, Type: Professional Core Lab. Course the performance in vIVA-vocE, the quarity of lab. file and ethical practices followed. Contact Hours: 2 hours/week The internal examination is conducted by the course coordinator. Mode: The external examination is conducted by external examiner appointed by the Controller of Examination in association with the internal examiner appointed by the chairperson of the Department. Pre-requisites: Programrning knowledge of c++ and HTML basics , About the Course: This lab course involves implementation of basic and advanced programs of C#. The objective of the lab. course is to train the studenfi[to solve the problems related to Object Oriented Technology, ADO.NET Connectivity and Web Applications using XML. Course Outcomes: By the end of the Iab course a student tvould be able to: Co1. implenrent c# programs in.NET framework. (LorS: Level 3:Apply) CO2. apply ADO.NET for developing database applications. (LOTS: Level 3: Apply) CO3- arialyse given programs for their correctness and efficiency for given inputs and expected outputs. (HOTS: Level 4: Analysis) CO4. integrate HTML code with ASP.NET and HTML code for designing a web pages. (HOTS: Level 6: Create) CO5. create written records for the given assignments with problem definition, desigl of solution and conclusions. (HOTS: Level 6: Create) CO6. demonstrate ethical practices while solving problems individually or in groups (LOTS: Level 3: Applv). List of experi ments/assignments 1. Write a console application that obtains four int values llom the user and displays the product. 7t., .,,, 2. Write an application that receives the following information from a set of students: .,?r4," ?' I Student Id: ,' !r Student Name: Course Name: Date of Birth: The application should also display the information of all the students once the data Implement this using an Array of Structures. !/ 120 3' Database programs with ASP.NET and ADO.NET create a Login Module which adds Username and Password in the database. Username in the database should be a primary key. 4' Create a web application to insert 3 records inside the SQL database table having following fields (Deptld, DeptName, EmpName, Salary). Update the salary for any one employee and increment it to t 5Yo of the present salary. Perform delete operation on I row of the database table. 5' Create a web page to display the cricket score from the table event(id, name, score). Refresh the website automatically after every 30 seconds. 6' write a C# Sharp program to extract the Date properfy and display the Date Time value in the formatted output 7 ' write a program in C# Sharp to count a total number of alphabets, digits and special characters in a string. 8. Create a web page to display animation using Jeuery. 9' Create a web page to display hide, show, slidedown, slideup and Toggle eff-ects for paragraph tags, using JQuery Note: The actual experiments/assignments will be designed by the course coordinator. o,e assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. i&,i* \gY,,b,f i ,.#1 tF 121 oca (a c\ ca c.} aa I c6t I a I I U) I I I N c I I c.) I I I I l.a I € o\ I aa m nr aE] € U I I a-) I U r- I U I \o I I J rr') +t r.) co aa (a U I bo .+ d I CN ca ca I U2 .o c'I F C'l rq I 4 al, u a{ cn aa X I L G C.l C! ca H C' I z, ', ',, ; ':i.- i I .)-: i / \l,^ | 4..i"l + .di.,i l' C' ri L F{ I ?/+l€rt!l,lg*/ U E/g/$?rEf/Fi/s*r L v Compiler Design General Course Information PCC-CSE 401 -T I Course Code: Course Assessment Methods (internal: 30; external: 70) PCC-IT3O6-T Two minor examinations (20 marks), Class Performance measured through percentage of lectures attendbd (4 marks), Course Credits: 3 assignments (6 marks), and the end- semester examination (70 Type: Professional Core marks). questions are to be set Contact Hours: 3 hours/week For the end semester examination, nine by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. All questions carry equal marks. Question number I will Examination Duration: 3 hours be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Brief knowledge of programming languages,Data Structure, and Algorithm Design. About the Course: Conrpilers have become part and parcel of today's conrputer systents. These are responsible for making the user's conrputing requirernents, specified as a piece of program, understandable to the underlying machine. There tools work as interface between the entities of two different domains - the human being and the machine. The actual process involved in this transformation is quite complex. Compiler design covers basic translation mechanism ahd, error detection and recovery It includes lexical, syntax, and semantic analysis as front end, and code generation and optimization as back-end. Course Outcomes: By the end of the course students rvill be able to: COl. state principles of compiler design. (LOTS: Level l: Remember) CO2. illustrate the essential phases for automatically converting source code into object code. (LOTS: Level 2: Understand) CO3. apply 1exical analysis, syntax analysis and code optimization techniques for solving problems. (LOTS: Level 3:APPIY) CO4. analyse a parse tree and a given BNF grammar. (LOTS: Level 4: Analyse) CO5. compare and contrast syntax-oriented translation schemes (HOTS: Level 5: Evaluate) CO6. desigl a lexical analyser from the specification of a language's lexical rules. (HOTS: Level 6: Create) Course Content Unit I Introduction To Compilers: Compilers and translators, need of translators, structure of compiler its different phases, Compiler construction tools. Lexical Analysis: Role df lexical analyzer, design of lexical analyzer, regular expressions, Specification and recognition of tokens, input buffering, A language specifying lexical analyzer. Finite,automata, conversion from regular expression to finite automata, and vice versa, minimizing number ofsgffiDIA, Intplementation of le.xical analyzer. "y"f--[ 7 * ' { (0, n3t/'r \r,w \Y\-/ ,.2' Unit II S)mtax Analysis: Role of parsers, context free grammars, definition of parsing. parsing Technique: Shift- reduce parsing, operator precedence parsing, top down parsing, predictive parsing. Unit III LR parsers, SLR, LALR and Canonical LR parser. Syntax Directed Translations: Syntax directed definition, construction of syntax trees, syntax directed translation scheme, implementation of syntax directed translation, three address code, quadruples and triples. Unit IV Symbol Table & Error Detection and Recovery: Symbol tables, its contents and data structure for syrnbol tables; trees, alTays, linked lists, hash tables. Errors, lexical phase error, syntactic phase error, semantic error. Code Optimization & Code Generation: Code generation, fonns of objects code, machine dependent code, optimization, register allocation for temporary and user defined variables. Text and Reference Books: l. Alfread V' AHO, Ravi Sethi and J.D. Ullman, Compilers Principle, Techniques ctncl Tools, Addison Wesley, 2001. 2- Tremblay and Sorenson, Theory and practice of compiler writing,Mc. Graw Hill, 19g5. 3. Dhamdare, System software, MGH, 1986. 4. Alfred V. Aho, Jeffrey D. Ullman , Principles of Compiler Desigre, Narosa Publicatio n, 2002. 7 I '4"L "'. a "Je. .- r*-l l '. -- -!r /' t" j, ) _-/-/ o _n--- 124 cro V) I I oi t\t I I a I I c U) a.l c-) aa ca co ca (\l I I I I C I I I I I FI t-.l o\ \J o I tf, I H a U) U I I I U r- U I I Frt v \o q) (r) I I )_fr o u) U I c\ a.l ca F T tf, bo .- I U) a\ e) l-lA ca fr I a.l q) .- (\l tr) N .tf I -a I N c'l a^ x g, U a\ X ca N aa L lt z t-3 tn () lbO l=ld = lP 6s 16 <.) 2 l- E IE E lc \ a 1.9 o E IE t{ lq .t I q ;c o 160)ls^ U D lth )i .jf - ld) o) ,,'ii ^l-L t l- (J (l- F / : tS\o I o \f, ,(Blo-r0))ol:9 t 4 J tr.l 3 =laI >. .. a : =Y IG A () :trl ltrF I i\l(B .. I l, O C) 5 IJ< i ; lE a ;Blr 3 i J I; F q.) ial= -, E !FloocB .G .e i +lQo l'a Xl l/\ d) I vtl-t'r. (k orl"l I >l ls ol I c-., I JI Artifi cial Intelligence General Course Information Course Code: PCC-CSE 402-T I Course Assessment Methods (internal: PCC-IT304-T 30; external: 70) Two minor examinations (20 marks), Class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Core marks). Contact Hours: 3hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. All questions carry equal marks. euestion number I wiil be compulsory Examination Duration: 3 hours and based on the entire syllabus. It will contain seven parts of 2 marks each. Question nurnbers 2 to g will be given by setting two questions fronr each of the four units of the syllabus. A candidate is required to atternpt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Basic knowledge of Algorithms and probability. About the Course: Artificial Intelligence is a core and an essential course for every graduate in Computer Science ald Engineering. This course introduces the concepts of Artificial Intelligence and challenges inherent in building intellige,t systems. It includes the role of knowledge representation in problem solving and hor,v these are usecl in maki,g intelligent machine. Further it incorporates the concepts of expert system and its applications. Course o,,t.o-.s: By the end of the course students rvill be able to: COl. outline various Artificial Intelligence techniques. (LOTS: Level 1: Remember) CO2. illustrate reasoning under uncertainty. (LOTS: Level 2: Understand) CO3. apply search and knowledge representation techniques to solve AI problems.(LOTS: Level 3: Apply) CO4. compare strengths and wealaresses of AI algorithms (HOTS: Level 4: Analyse). CO5. combine various AI techniques to solve intelligent systelns'problenrs. (HOTS: Level 6: Create) Course Content Unit I Introduction to AI: Introd.uction, Turing Test, AI problems, State Space Search, production system Problem Solving Using Search: Blind search techniques - Breadth first search, Depth first search. Heuristic search techniques - Generate and test, Hill Climbing, Best fiist search, A* Algorithm, AO+ Algoritl,n, The Minimax Search Procedure, Adding Alpha-Beta Cut-offs 'i- -#''^r*rig,;l.n a"' .-j" ir/v , Unit II Knowledge Representation: Introduction, Knowledge Representation- Representation and Mappings, Symbolic Logic - Propositional logic, Predicate logic- Representing simple facts in logic, Represeqting. Instances and ISA Relationship, Computable functions and Predicates, ...- 'n* Unification, Resolution .-.. -,-- Representing Knowledge Using Rules: Procedural versus Declarative Knowledge, l-ogi. programming, Forward versus Backward Reasoning, Matching, control Knowledge. 126 u Unit III Reasoning Under Uncertainty: Introduction to Nonmonotonic Reasoning, probability and Baye,s Theorem, certainty Factors and Rule-based Systems, Bayesian Networks. Fuzzy logic system: Introduction, crisp Set, Fuzzy Sets, Fuzzy Membership Functions, operations on Fuzzy Sets, Fuzzy Relations. Unit IV Planning: Introduction, components of Planning planning, System, Goal Stack Nonlinear planning using Constraint Posting, Hierarchical planning. Expert System and Applications: Introduction, Architecture, Rule based Expert Systems, Applications of Expert Systems. Text and Reference Books: 1' Elaine Rich, Kevin Knight and Shivashankar B Nair, Artificial intelligence, McGraw Hill Education. 3'd edition , 2009. 2' Stuart Russel and Peter Nor-vig, Arti,ficial intelligence; A moclern Approoch, pearson Education, 3d edition, 2015. 3' Dan w' Patterson, Introcluction to Artificial Intelligence and Expert System, pearson Education.lrr edition, 2007. 4' Deepak Khemani, A course in Artificial first Intelligence, McGraw Hill Education. 3d edition, 1., edition, 2013. 5' George F Luger, Artificial Intelligence; Structures and Strategies for Complex problem Solving, Pearson Education, 5'h editio n, 2A09. \& 127 ra o cn U) ca cn ca co oc.I O I (o I I I I N o I C' FI 6l I I r () a U) I I r-. U I I q) (J \o q) I .\t oo rf-) q) I a! C\ )r{ \f, I a.l a-.l ca q) c+.( in oo 6l C.l fr 4, (\l X I c.l 6t aa zFI a'l c.l cn d c, t( 44 th ls l*lg I I la loall lE I c =u lEElS I U , l>.ls lE. le i lE I $ lElg lL:lHlH- I l"lElgglf*lgilu 0l< ;;tp t-?l'lg{l=;l ? trl:Ol" 3li !16 iElr.l;€leilrsl u 5l;lr 0)l.: !-l+ =l= i;lgElitlf Hlt{l € Elc c*l ol -l-olr^ JIC i I' Ir l, k li Software Project Management General Course Information Course Code: PEC-CSE 4Ol -T I course Assessment PEC.IT4O I -T Methods (internal: 30; externar: 70) Two minor examinations (20 marks), class performance Course Credits:3 measured through percentage of rectures attended (4 marks), assignments (6 Type: Professional Elective marks), and the end- semester examination (7'0 marks). Contact Hours: 3 hours For the end semester examination, nine questions are to be set Mode: Lectures (L) by the examiner. A candidate is required to attempt 5 questions in all. All questions Examination Duration: 3 hours carry equar marks. euestion number I will be compulsory and based on the entire sylrabus. It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the syilabus. A candiJate is required to attempt the remaining four questions by serectirrg or" qr.restion from each of the four units. Pre-req,isites: Preliminary knowledge of Softrvare Engineering. About the Course: The course involves training students in software project management and project planning. It focuses need for careful planning, monitoring on the and control for delivering quality projects in learn time. Besides this student to measure the success of a pro;ect in meeti,g its objectives. course outcomes: By the end of the course students will be able to: CO1. oritline basic concepts related to stepu'ise project planning. (LorS: Lever r: Remember) CO2. demonstrate the knowledge about Quality control, Standard and Risk Management. (LorS: Level 2: Understand) co3' illustrate the Activity Planning, and Resource process. Allocation (LorS: Level 2: Understand) CO4' apply the concept of team structure and organ izationstructure. (LOTS: Level 3: Apply) Co5' compare various Project Evaluation and Estimation Tecluriques. (HoTS: Level 4: Analyse) co6' plan activities necessary for completing the software projects successfully. (HorS: Level 6: create) Course Content Unit I Introduction to Softrvare Project Management(SPM): Definition of Software project, Software project vs other types of projects, activities covered bv sPM, categorizing software projects, prolect as system, control, Requirement specification, Information il::;ffIent ,rd .oitror in orga,rirutio,r, projLct manaiement stepwise Project Planning: Introduction, selecting a project, identifying identifying project scope and objectives, project infrastrucfure, analysing project characteristics, identifying the project products and activities, estimate effor-ts for each activity, ia.rlrying activity risk, allocate resources, review/publicize plan. Unit II analysis, cash flow forecasrins, ::1r""*,:"'Ilt::,i-"11 ^r_stimltion: .cost-Benefit..h":":; cosr benefit evaluation application I,uusls' rap 3#*::,:::::::i'..11^3llTl11',:,f':j"",development, waterfall r process modelm.,.lot i,,ai.d*e;;;",;ffi."5i .-r,"-, ;;-::r::.-t'"'oo. ;":":T:J:]?H: tg..lJ and spiral model,-i^rl, Arbrecht function poinr unuiysis. Activify Planning: Objectives projeQt schedule, projects and activities, sequencing scheduling activities, networ ) and ''\, ..u UnitIII --- Risk Management: Introduction, the nature of risk, managing risk, risk identification, risk analysis, reducing : the risks, evaluating risks to schedule, calculating z-values. Resource Allocation: Introduction, the nature of resources, identifuing resowce requirements, scheduling ,'* rcsources, creating critical paths. Unit IV Managing Contracts and People: Introduction, types of contract, stages in contract placement, terms of contract, contract management, acceptance, managing people and organizing teams: Introduction, understanding orgaruzation behaviour: a back ground, selecting the right person for job, instruction in best methods, motivation, working in groups, becoming a team, decision making, leadership, organization structures. Software Quality: Introduction, the place of software quality in project plaming, the importance of software quality, defining software quality, McCall's software quality factors, product versus process quality management, external standards, techniques to enhance software quality. Text and Reference Books: 1 . Bob Hughes and Mike Cotterell , Sofh,vare Project Management, Sixth Edition, TMH, 2018. 2- walker Royce , soiftv,are Project Management, ,Addison wesley, r998. 3. Pankaj Jalote , Sofh,vare Project Management in Practice, Pearson, 2002. 4. Ramesh, Managing Global Sofnvare Projects,TMH, 2005. / 130 c?o a I I I cN a I o c\ ca co co ca ca N I I N FI F( I a.l ca -+ 0{ trl O I I I U C! I U o\ I ri N I I l*{ oo q) an I I ti r- I U I I \o () I q) bo rn c I 6l 6l N an t36 t+ z I (\ co c) () a.) I I I N L cn lLl ol q)' L N c.'l ca C..l a.l ca a Xi oo LI .t-. I 63 I Ett 3 l= I cl o. u ol trl () jj q) c{ $t OI 'a oEC EI ,El I EI EI o- ls 3 6'I .() ; 6l d) (6l () l trt I a I tl s ls 'rr I co U) 3 l= I C LI c (d ^lo)l *ild ,. I tzJ\-/ )- I '5.o1 1l () alE o--l a E EIg I 5;l(sI 0)l CI o E -ol ; r lE Fl =J g-ql Arl o) s -o lC :-l = General Course Information Course Code: PEC-CSE 402-T I Course Assessment Methods (internal: PEC-IT302-T 30; external: 70) Two minor examinations (20 marks), Class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type : Professional Elective marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. All questions cary equal marks. Question number I will be compulsory Exarnination Duration: 3 hours and based on the entire syllibus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-reqrrisites: Basic knowledge of Probability Theory Set Theory and, Data Structure and Compurer Algorithms About the Course: We need to learn soft computing techniques to make intelligent machines that possess human like abilities to reason, learn and handle the uncertainty and vagueness often inherent in real world problems. Unlike conventional computing, soft computing techniques are tolerant of imprecision, uncertainty and approximations, and provide low cost, robust and tractable solutions to the complex real-world problems where conventional methods fail to do so. This introductory course on soft computing is going to cover Genetic Algorithms, Artificial Neural Networks and Fuzzylogic. Course outcomes: By the end of the course students will be able to: COl. define the terrninology and concepts related to soft computing techniques. (LOTS: Level l: Remember) CO2. discttss soft computing techniques including genetic algorithms, fuzzy systems and neural letworks. (LOTS: Level 2: Understand) CO3. solve problems related to Genetic algorithms, Fuzzy logic and Neural Networks. (LOTS: Level 3: Applv) CO4. analyse the design of Genetic Algorithms, Neural Networks and Fuzzy Systems. (HOTS: Level 4: Analyse) justify CO5' the design of a soft computing algorithm for a given problem. (HOTS: Level 5: Evaluate) CO6. design Genetic Algorithms and Neural Networks to solve optimization and pattern recognition problems. (HOTS: Level 6: Create) ! Course Content Unit I Introduction to Soft Computing and related definitions: Defining soft computing, Differentiating the situations for application of hard and soft computing; Working of a simple Genetic Algorithm: Representation/Encoding Schemes, initializing a GA population, evaluation function, genetic operators, Function optimizatlon using GA. Study of parameters of genetic algorithms and its performance, sampling and selection mechanisffi,Sealing of GA population. *fooi',* -ri. t32 \ Unit II Designing Genetic Algorithms for different applications: Different types encoding schemes, role of fitness function, different tlpes of genetic operators, Designing GAs for numerical optimization, knapsack problem and travelling salesperson and other similar problems. Unit III Fuzzy sets: Basic terminology and definitions, operations on Fuzzy sets, MF formulations and parameterisation, MFs of one and two dimensions, Derivatives of parameterised MFs, Fuzzy numbers, Extension principle and fuzzy relations, operations on Fuzzy relations, Linguistic variables, Fuzzy If-Then Rules, Compositional rule of inference. Unit IV Neural networks: Basic terminology and definitions, Model of an artificial neuron, Sigmoid function, Neural Network Architectures, Rosenblatt's Perceptron, Fixed increment perceptron learning algorithm for a classification problem, Examples of learning of AND/oR gate by perceptron, XoR problem. Back propagation Neural Networks: Architecture of a backpropagation network, Model for multi-layer perceptron, Back propagation learning, Delta or gradient descent learning rule and effect of learnirrg rate, Back propagation Iearning algorithm. Text and Reference Books: l' David' E' Goldberg, Genetic Algorithms in search, optimizcttion ond ntacltine learning, Addison Wesley, 1999. 2. Zbigniew Michalewicz, Genetic algorithms * Data Stntctures : Evolution prograns, Springers_ Verlpg, 1999. 3' M' Mitchell, An Introduction to Genetic Algorithms, prentice-Hall, 199g. 4' S' Rajasekaran & G. A. vijayarakshmi pai, Nenrar Neh,vorks, Fuzz1, Logic ancr Getretic Argorithnrs; Synthesis & Applications, pHI, 2003. 5' S' N' Sivanandam & S- N. Deepa, Prtnciples of Soft Comptrting, Wiley - India, 2007. 6' J-S' R' Jang, C.-T. Sun, E. Mizutani, Neuro-Fuzzy and Soft Contptttittg, pHI, lgg7. 7 Simon O' Haykin Neural ' , Networks, A Contprehensive Founclatign, pHl, 1gg4. u ^i# > :{/ r33 o?a a co co ca ca co ca N o V) I 0r o a I I I I (\l I o I I I F I I I (-lI \f, o\ at-l U I U co tI] I I I () r- irU) I I I \o U I I bo rn C.l N ea Br rt I a.l on ca U t) -d- +r I (\l c.) ! a t\ x o' ca aa c^ ca L A l- 2, o cn ca cn co (Dt I :l l$ lE l* oc.n I i,i I 'l N lcoI lE Its an 5l o lo i E lA li3 lE (.)I (-) I J I c-r O IO IC) l_5 Distributed Operating System General Course Information Course Code: PEC-CSE -403-T/ Course Assessment PEC-IT403-T Methods (internar: 30; externar: 70) Two minor examinations (20 marks), crass performance Course Credits:3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and Tlpe: Professional Elective the end- semester examination (70 marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set Mode: by the examiner. Lectures (L) A candidate is required to attempt 5 questions in all. All questions cany equar Examination Duration: marks. euestion number I wilr 03 hours be compulsory and based on the entire sylrabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Knowledge of operating system, computer networks and a programming language About the Course: This course focuses on the study of distributed systern concepts and its applications. advantages In this course various of distributed computing system are studied. After .trdyirrg this cturse, a sfudent will be expected understand the design issues of the to distributed operating systems ,rra propose solutions the domain. fbr problems specific to Course Outcomes: By the end of the course sturlents rvill be able to: col ' state the basic concepts of distributed systerns and their advantages over simple client server based computer networks. (LorS: Lever r: Remember) CO2' explain strategies for synchronization, scheduling policies and deadlock avoidance in distributed environment. (LorS: Lever 2: Understand) co3' apply distributed operating system's concepts to solve the problems inherent in distributed systems. (LOTS: Level 3: Apply) co4- analyse trends in distributed fire systems. (HorS: Lever 4: Anaryse) co5' compare and contrast strategies for synchroni zation, scheduiing policies and deadlock avoidance and distributed file systems. (HorS: Level 5: Evaluate) Course Content Unit I Introduction: Introduction to distributed system, Goals of distributed system, Hardware and Software Design issues, communication in distributla concepts, ,yrt.*: Layered protocols, ArM networks, client- Server Remote Procedure calls and model, Group communicution, Middlewaie and #ffi;;$tjil%Systems. unitrr V:.f lA synchronization in Distributed System: clock synchroni zation,Mutual Exclusion, Election algorithm, Bully algorithm, Ring algorithm, Atomic Transactions, Deadlock in Diitributed Sysrems, Distribrrted Deadlock Prevention, Distributed Deadlock Detection. ,,,\ UniI-III Processes and Processors in distributed systems: Threads, System models, Processors Allocation, Scheduling in Distributed System, Real Time Distributed Systems. Unit IV Distributed file systems: Distributed file system design, Distributed file system Implementation, Trends in Distributed file systems. Distributed Shared Memory: What is shared memory, Consistency models, page based distributed shared memory shared variables distributed shared memory. Text and Reference Books: Tanenbaum l. A.S., Van Steen M., Distributed Systems; Principles ancl Paracligms, pearson Education, I 2. Pradeep K Sinha, Distributed Operating Systems: Concepts crnd Design,Prentice Hall of In dia,2007. 3. Liu M.L., Distributed computing, Principles and Applications,Pearson Education ,2004. 4. Nancy A Lynch, Distributed Algorithms,Morgan Kaufman Publishers, IJSA, 2003. ) 136 ro o a I I I N o I a I a C\ c-) ca co co n al I I I FI I ?a I t 14 a I U I U o\ I r-l I Ft I l+l 00 c) a I L r- o I I U I \c q) I €(a) a tt) I bo I I .+ L I N co q) (..) I F- o I N ca co q) al I C.l a.t LI v)l c C\l C.l a.l .rl5l .ar. I dl trl t .1); .eI :'.t- t tt. EI ;;hi 'br; ' OI-l : r:;l' 'r','.'il FI ,:lY,ll it .,i, CI /,I' o-lrl UICI Cloud Computing General Course Information Course Code: PEC-CSE 404-T / Course Assessment Methods (internal: PEC-IT-404-T 30; external: 70) Two minor examinations (20 marks), Class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Elective marks). Contact Hours: 3hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. All questions cary equal marks. Question number I will Examination Duration: 3 hours be compulsory and based on the entire sylrabus. It wiil contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions frorn each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Basics of computer Network, Distributed System. About the Course: The objective of the course is to give students a comprehensive view of storage and networking infrastructures for highly virtualized cloud ready deployments. The course discusses the concepts and features related to Virlualized data-centre and cloud, information storage and design of applications. Course outcomes: By the end of the course students will be able to: COl. define concepts related to cloud computing. (LOTS: Level 1: Renrember) CO2. express deployment models for clouds. (LOTS: Level 2: Understand) CO3. apply cloud computing techniques for various applications. (LOTS: Level 3: Apply) CO4. analyse cloud computing services used at various levels. (HOTS: Level 4: Analyse) co5. assess real time cloud services. (Hors: Level 5: Evaluate) ,-t .-$, 'l:: ' 1,..'l :.i; ', -' Course Content :.; Unit I .,. ? Introduction: Distributed Computing, Cluster Computing, Grid Computing, Overvieu, of Cloud Computing, History of Cloud Computing, Defining a Cloud, Benefits of Cloud Cornputing, Cloud Cornputing Architecture, Services Models (XaaS), Infrastructure as a Service, Platform as a Service, Software as a Service. '' Unit II Deployment Models, Public Cloud, Private Cloud, Hybrid Cloud, Community Cloud, Dynamic provisioning and Resource Management, Virtualization: Characteristics of Virfualized Environment, Taxonomy of Virttralization Techniques, Pros and Cons of Virtualization,Xen, VMware, Hyper-V. +, ii..k:{tfu '--q.F- i.-- l' t. -r" 138 Unit III cloud Platform in Industry: Amazon web Services- Compute Services, Storage Services, communication Services, Additional Services, Google App Engine- Architecture and core concepts, Application Life cycle, cost Model, Microsoft Azure - Azure Core Concepts, SQL Azure, windows Azure platform Appliance. Unit IV cloud Application: Scientific Applications- ECG Analysis in cloud, Protein Structure prediction, Gene Expression data analysis for cancer Diagnosis, Satellite Image Processing, Business and Consumer Applications-cRM and ERp, productivity, Social Networking, Media Applications, Multiplayer Online gaming. Cloud Security. Text and Reference Books: 1' Rajkumar Buyya, christian vecchiola and S ThamaraiS elvi, Masrering cloud Comprting, Tata McGraw Hill Education pvt. Ltd.,2013. 2' Kai Hwang, Geofferyu C. Fox and Jack J. Dongarra, Distributed ancl Cloucl contputing, Elsevier, 2012. 3' John w' Ritting and Jamcs F. Ransonrc, cloncl computing; Implementation Manctgentent and security, CRC press, 2012. ,A_t^o t39 cro a I I (\t V) c..l co ca ca c.I a I I N N I I t-r I r+ I .+ ari I I U I oo riU I I I tr{ r.- I 0,) u) \o I o.l U rn b4 N C.l ca \f, I I aa ca .o U c{ C.l a.) $ (\t c! cn ca U X ti a\ a^ ca z l9 ls le (.) lo L lrl 1 I oi, l.= al l9 ol o-= I EIE ololo () U !I otd-l'd q)lol- taI Llo =l- l olc I UIg I :lE I 'l$al ls El ,g l€ I l"-l ls I Advanced Microprocessor General Course Information Course Code: PEC-CSE 40 S -TJ Course Assessment Methoas PEC-IT4O5-T linterru@ Two minor examinations (20 marks), crass performance measured through Course Credits: 3 percentage of lectures attend ed (4 marks), assignments Tlpe: Professional Elective (6 marks), and the end- semester examination (70 marks). Contact Hours: 3hours/week For the end semester examination, Mode: nine questions are to be set Lectures (I.) by the examiner. A candidate is required to attempt 5 Examination Duration: 3 hours questions in all. AII questions carry equal marks. number euestion I will be compulsory and based on the entire syilabus. It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the sylrabus. A candidate is required to atterlpt the remaining four questions by serecting on" qulstion from each of the four units.. Pre-requisites: Basic knorvledge of Digital Electronics, computerArchitecture and organ izationr. About the Course and its Outcomes: A microprocessor incorporates the functions of a central processing unit (cpu) The advent on a single integrated circuit. of microprocessors and their increased capacity made th-em to be used in everything be it a smallest embedded system or handheld device, or the largest mainframe and supercomputer. It is applications such process being used in variety of as control systems] security systems, household technologies' appliances, and mobile phone This course aims to introduce the archite.Lr", programming circuits and interfacing of various hardware with microprocessors' It would help the students learn the advanced techniques in the n:odern microprocessors and give them exposure to memory interfacing and management, monitoring applications, pnd the latest teclmologies. and control course outcomes: By the entl of the course a student lvould be abre to: col describe the features ' and use of the real and protected modes of microprocessors. (LOTS: Level l: Remember) co2' explain the internal architecture of the I6, 32, and,l4-bitmicroprocessors and compare.and the features of different contrast Intel microprocessors. (LOTS: Level 2: Understand) co3' analyse men1ory input/output and intemrpt interfaces to the microprocessors. Analyze) (HoTS: Level 4: co4' to-fott the state-of-tlre-art technologies in the field of microprocessors.(HorS: Level 5: Evaluate) Co5' design the microprocessoi based contlol ,y.r.., and develop the software to control them. (HOTS: Level 6: Creare) Course Content Unit I Microprocessor 8086- Internal architecture, Real mode memory protected addressing, addressing, mode memory Memory paging, Data addressing modes, program *..,,ory addressing modes, stack memory addressing modes, Directives and operators, Data transfer inJructions, Arithmetic program control instructions, & logic instructions, Data conversions, Assembly language programming. v t4t R Unit II The Pin-Outs and pin functions of 8086 microprocessors and 8088 co-processor, Clock generator, Bus buffering and latching, Bus timings, READY and WAIT state, maximum mode and minimum mode configuration, Memory devices, Memory interface, Address decoding, 16 bit, 32 bit and 64 bit memory interface, I/O Programming, Programmed I/O, IntemrptllO and DMA, I/O addresses and I/O ports . Unit III 80286- features, Internal Architecture, bus interface, addressing modes; 80386-features, Internal Architecture, bus interface, addressing modes; 80486-features, Internal Architecture, bus interface, addressing modes; 16550 Programmable communications interface, Asynchronous serial data, Data acquisition system, Temperature monitoring system etc Unit IV Pentium processor, The memory system, llo system, Branch prediction logic, cache structure, superscalar architecture, special Pentium registers, Pentium memory management, Introduction to pentium pro, pentium II, Pentium III, Pentium IV and Core 2 microprocessors, Multi-core microprocessor architectuie, Intel Hyper- Threading technology, Turbo Boost technology, state-of-the-art multi-core microprocessors. Text and Reference Books: l. Barry B. Brey, INTEL Microprocessot's,8th Edition, Prentice-Hall Inc., U.S.A., 200g. 2. Yu-cheng Liu, Glenn A. Gibson, Microcompltter systems; The Ba86 /B0SB Family ctrcltitecture, Programming oncl Design, Second Edition, Prentice Hall of In dia,2003 3. Walter A. Triebel, The 80386, 80486, ancl Pentium Microprocessor; Ilarcl,,vare, Soffivare, ancl Intetfacing, Prentice-Hall Inc., U.S.A., I 998. 4. K. Ray and K.M- Bhurchandi, Intel Microprocessors; Architecture, Progrctntming ancl Interfacing, Mc,Graw Hill Inc., 2001. 5. Shameem Akhter and Jason Roberts, Multi-Core Programming,lntel press, 2006. 6. Douglas V. Hall, Microprocessors and Interfcrcing: Programnring oncl Hctrclware, TataMcGraw-Hill, t999. 7. James L. Antonakos , The Pentium Microprocessot; Pearson Education , lgg7. .-i# r \{/t{ 142 ?4 I I U) I N I U) I c\ a ca ca ca cn co (tl I I I t-t I a,I .+ I rc I I O U I o\ I I r-)U I l-l FLI @ I q) I U) L r- I I I U L I (a I I (n q) rn () I c-l N a.f L !+ ,( I .J N N C) al- ro C.I C.l a{ (\ .f,ce () () N I ca a^ aa ca (-il a.l c.) ca xi {rll-l f3I I - 361 I ol-l Lale: l /g, {B :l li gflrE t,. I ..i:.fu b, CJI=l -;" t, !:: ,y .'e i ,/ . ., / EI E;l 63 I .-,/ 4I\l g { 3lC E I '1 .i AI ',i rl t -l8 tr I ol i5l;E I UI €/i8/fr/Ef,/id I;I;; IE iglg: lt rflEi | F *,^l lEF '.9- l;n I sl E €lAisl 5 ts rs Ir ls It I' I si Mobile Application Development General Course Information Course Code: PEC-CSE 406-T I PCC-IT4O3-T Course Assessment Methods (internal: 30; external: T0) Two minor examinations (20 marks), Class performance Course Credits:3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Elective marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. candidate Mode: Lectures (L) A is required to attempt 5 questions in all. All questions carry equal marks. Question number r will Examination Duration: 3 hours be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Java Programming and Object-Oriented progranlming, Knowledge of RDBMS and OLTp. About the Course: Mobile Application Development has been introduced as a Professional Elective course for Srudents of BTech(CSE/lT) keeping in view the Employers'requirenrents. Android Platform forms the basis for developing Mobile Applications since the last decade as compared to IOS Platform for Apple Products. The Environment requires User Interface to be developed using Buttons, Check-Boxes, Alert Dialog and its kind. Course outcomes: By the end of the course students will be able to: COl. state basic of Android , its Evolution and its Architecture. (LOTS: Level l: Remember) CO2. demonstrate the Lifecycle of Software for Android Mobile Applications. (LOTS: Level 2: Understand) CO3. prepare Mobile Applications on the Android Platform. (LOTS: Level 3: Apply) CO4- compare working with Buttons and other Widgets for Visual Environment. (FIOTS: Level 4: Analyse) CO5' develop Mobile Applications using data storage in SQLite Database and evaluate its Performance. , (HOTS: Level 6: Create) Course Content Unit I .: " Mobile OS Architecture: Ardroid, Blackberry OS, Firefox OS, IOS, Window OS, ARM and MIPS processor, Challenges of the mobile platform, Hello Android example, Intemal Details, Dalvik VM, Software Stack, -: Android Core Building Blocks, Android Emulator, AndroidManifest.xml, Rjava file, Hide Title Bar, Screen ' Orientalion. k, A4 Unit U Ulwidgets:workingv/ithButton,Toast,Cu,stomToast,Button,ToggleButton'SwitchButton,ImageButton, Checksox,AlertDialog,Spirmer,AutoCompleteTextview,RatingBar,DatePicker,TimePicker,ProgressBar' and Digital Clock, Working with hardware Button' File Download' Quick Contact Budge, Analog Clock Unit III Activity,Intent&Fragm€nt:ActivityLifecycle,ActivityExample'Implicitlntent'Explicitlntent'Fragment Lifecycle, Fragment Example, Dynamic Fragment' Android Menu: Option Menu, Context Menu, Popup Menu Layout Manager: Relative Layout, Linear Layout, Table Layout, Grid Layout' Unit IV Adaptor: Aray Adaptor, Arrayl-ist Adaptor, Base Adaptor' View:Gridview,WebView,ScrollView,SearchView,TabHost,D)'namiclistview'ExpandedListView' SQLite: SQLite API, SQlite6'pinner, SQLite Listvieu' XML&JSON:XMLParsingSAX,XMLParsingDOM,XMLPullParser'JSONbasics'JSONPaning' Text and Reference Books: 1. Redazione Io Programmo, Android Programming,20ll packt publishing 2015 2. John,Hort on, Androicl Programming for Beginners, ' 3. Jason wei, Anclroitl Database Programming, packt publishing ,2012 4. Mark L Murphy, Anclroicl Programming Tutorials,3rd Edition, 2010 5. Bill Phillips et al., Anclroid Programming - The "Big Nerd Ranch" Guide 2017 Google Rick Rogers et al., Anctroid Application Development: Prograrnmingwith the 6. 'DK,2009 $;# \ a\ 145 o?a (a I I cN a I N I c.) V) cn c-) ca ca co al c a{ F{ \oI s o I I 0lE1 U I I I a U ri o\ O{ c.i q) ta € li I I U r- q) \o I I an rn q) ...l ca q) t - I I aa ?o \o I a.I a{ C{ O $ (\l, I N (\ d q) c'l I ca a x I t, \ ti l, l€ lE l> ztrl 6g IilE () ,k IEg L lslgslgil tt 515 lE € sl'= lts )E =13 la l: lrn,*E I ?l;61: + U !l€€lsq ri'lgflg l* !lE*li9 Ig Qls 5 IrilEE 3lE $ Aafli;li oi,l E l# =1" = l" " I i lol'- lolc.t I c-.r I r-l s ld l5 li Multimedia Technologies General Course fnformation Course Code: PEC-CSE4O7-T / course Assessment PEC-IT4I I -T Methods (inter,ar: 30; externar: 70) Two minor examinations (20 marks), crass performance Course Credits: 3 measured through percentage of rectures attended (4 marks), assignments (6 marks), Type: Professional and the end- semester examination Elective (70 marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner- candidate Mode: Lectures (L) A is requi.ed to attempt 5 questions in all. Ail questions carry .qrir marks. euestion Examination Duration: number I will 3 hours be compursory and based on the entire syllabus' It wiil contain r.r.n parts of 2 marks each. Question numbers g 2 to wilr be given by setting two questions from each of the four units of the rvliuurr. A candidate is required to attempt the remaining four questions by selecting one question from each of the rorL rrits. Pre-requisites: Basics of Computer Graphics About the Course: Multimedia is a core and an essentiar course for every graduate in Computer objective Science and Engineering The of this course is to make students learn how to develop multimedia programs and still images, sound, demonstrate how and video can be digitized on the computer. course outcomes: By the end of the course students wiII be abre to: col ' outline the basic concepts of multimedia technorogy. (LorS: Level l: Remember) co2' discuss the concepts of animation,digitizedsound, video control, and scanned images. 2: Understand) (LorS: Level co3' use basic instructional design principles in the development of Multimedia. (LorS: Level 3:Apply) co4' compare various audio and video file fomrats. (HorS: Level 4: Analyse) co5. devise solutions for murtimedia probrems. (HorS: Lever 6: create) Course Content Unit I Introduction to Multimedia concepts, Types of Murti-rnedia Apprications, Methods to deliver Multimedia, Introduction to Multimedia Database, Multimedia Input and output Devices. Unit II Introduction about font and faces, using Text in Multimedia, Applying different types of text rB multimedia FontEditingandDesigntools,HypermediaandHypertextapplication..**:#9b ,&* . {{tu/ 147 \ @,Y,/ &\ Unit III - . The power of sound, MIDI Vs. Digital Audio, Audio File Formats (AIFF, WAV MPEG, MOV etc.) , r- Adding Sound to multimedia project. Unit IV Working of a Video and its Display, Digital Video Containers (Codecs & Video Format Converters) Obtaining Video Clips, Shooting and editing Video, Non Linear Editing(NlE) in Videos The stages of Multimedia Project, Hardware and Software requirements ,Authoring Systems Team for Multimedia Development, Different stages of multimedia, The internet and multimedia Text and Reference Books: l. Tay vaughan, Multintedia: Making It work, Tata McGraw Hills, 200g. 2. James E Shuman, Multimedia in Action, Vikas Publishing House, lggl. 3. Andreas Holzinger, h[ultimeclie Basics Technology, Volume 1, Firewall Media, 2005. 4. Rangan Parekh, Principles of Multimedia,TataMcGrawHills, 2ool. u t , :.r1*y.*, ' I I \ 148 o?o I I a I I nr N I U) I I I o (n N ca ca C' ca A N I I o I FI l-- I r+ E] o\ CN o I I U I I t U a o I tEl I Frt r-l q) r Ol I a p'{I \c I U I I q)a ra bo I a.l ca $ I ca (.) e) (.o F-r I c.l (\ c.t o\ w t\ () I a-.l C{ ca )-. c C! C..l ca a13 X .- I O I \ii +)L AIH IY 6l tt- a >'' F BI z bo tr o o il - o I cAl .-v / FI *) ;g/fu) ..1 o I ,,, CI IY o - (.) '{, E I l€ I )- td { .-C' | .- o rFi .lT :ltrl t( Dlc) () ()l )l'E:'l E -ol A el V )l= 1) al l+i CgI I ilr ;{/*s/,; .v A qrlo a 5l U I lr- U l.lls 3 -lr e :to=lr- llSI(J() ielusl: :f|.f, L'lc F ? 11 lr! : lE r . = ta 13#l (Jlt i 91.9 0I 5 lo .t) .. | 'J=IHJIU -lr (t) I o I O ,..] G_l(-l gI .o ol( ,sl;;li i lH e Bl:t l.= E I i :la PJI* \l+ !,slo: o ..1 u =lq. ;IE .= f General Course Information Course Code: PEC-CSE 408-T / PEC-IT4O8-T Course Assessment Methods (internal: 30; external: 70) Two minor examinations (20 marks), Class performance Course Credits:3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Elective marks). Contact Hours: 3hours/week For the end semester examination, nine questions are to be set by the Mode: Lectures (L) examiner. A candidate is required to attempt 5 questions in all. All questions carry equal marks. euestion number I will Examination Duration: 3 hours be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: knowledge of basic linear algebra, basic probability theory basic programmilg techniques, and Fourier Transforms. About the Course: Digital Image Processing is a Professional Elective course that provides a theoretical foundation of digital image processing concepts. This course provides a mathematical foundation for digital manipulation of images, image acquisition, pre-processing, enhancement, segmentation and compression. Sfudents learn algorithms that perform basic image processing operations (e.g., histogram processing, noise removal and image enhancement and restoration). Algorithms for image analysis (e.g., image compression, irnage segmentation and image representation) are explained. course outcomes: By the end of the course students rvill be able to: COl. state concepts related to image acquisition and processing. (LOTS: Level I : Remember) CO2. illustrate the principles and methods in image processing. (LOTS: Level 2: Understand) CO3. apply mathematical functions for digital manipulation of images such as image acquisition, pre- processing, segmentation, compression and representation. (LOTS: Level 3: Apply) CO4. compare various image processing techniques. (HOTS: Level 4: Analyse) CO5. assess the various image processing techniques for a given problem. (HOTS: Level 5: Evaluate) CO6. design and implement algorithms for digital image processing operations such as histogram equalization, filtering, enhancement, restoration and denoising, segmentation, compression. (HOTS: Level 6: Create) . _, ,"_, *;r* ''r' "' Course Content _.r-" Unit I Introduction and fundamental to digital image processing: What is digital image processing, Origin of digital image processing, '-. Examples that use digital image processing, Fundamental steps in digital image processing ,. Components of digital image processing system, Image sensing and acquisition, Image sampling, euantization and representation, Basic relationship between pixels.lmage enhancement in spatial domain and frequency domain: Background, Basic gray level transformation, Histogram processing, Basics of spatial filtering, Smoothing and sharpening spatial and the frequency domain filters. 150 Unit II Image Restoration: Image degradation/restoration Process, Noise models, Restoration in presence of noise, Inverse filtering, Minimum mean square filtering, Geometric mean filteE Geometric transformations. Color Image Processing: color fundamentals, color models, Basics of full color image processing, transformations. Color Unit III Image compression: Fundamentals, Image compression models, Error free compression, Lossy compression. Image Segmentation: Detection of discontinuities, Edge linking and boundary detection, Thresholding, Region based segmentation. Unit IV Representation, Description and Recognition: Representation-chain codes, polygonal approximation and skeletons' Boundary descriptors-simple descriptors, shape numbers, Regional descriptors- simple, topological descriptors. Recognition: Pattern and pattern classes. Text and Reference Books: l ' Rafael c' Gonzalez and Richard E- woods Digital pearson , Intctge Processing, Education, Ed, 2001. 2' Anil K' Jain, Funclomentals of pearson Digital Image Processinp, Education, pHI, 2001. 3' Tink-u Acharya and Ajoy K. Ray, Imcrge Processing-Principles ancl Appliccrtions,John wiley & Sons, 4. Inc.,2005. 5' Chanda and D. Dutta Majumda r, Digital Intage Processing ancl Analysrs, pHI, 2003. 6' Milan Sonka, vaclav Hlavac, Roger Boyle, Image Processing, Analysfs, ancl Machine pubrishing vision, 2nd edition, Pws cornpany, Thomson Learning , rggg. \I w" T kv - ,tiJ' I l5l ?o C V) C.l ca c7) (n co co A c.I U) I 0r ct) I I I I N I o'l c I t-( €I \f, I I I ar--l 0.. U o\ I I I U r-l € ,*( I q) a r- ir C I I U \o bo I I I rn U) U) q) I cn (.) ir = C I a! N ca l*l J () bo co c! I C! C.I c..t tr) (.I ca I C' c^ co \ bo aa C.l c.) C..) X tr a= q) f. I t{ I U Advanced Microprocessor Lab. General Course Information Course Code: PEC-CSE 405-p / Course Assessment Methods (internrf@ PEC-IT4O5-P The internal and external assessment is based on the Ievel Course Credits:2 of participation in lab. sessions and the timely submission of lab Type: Professional Elective Lab. Course experiments/assignments, the quality of solutions designed for Contact Hours: 3hours/week the assignments, the performance in vIVA-vocE, the quality Mode: Lab. practice and assignments of lab. file and ethical practices followed. The internal examination is conducted by the course coordinator. The external examination is tonducted by external examiner appointed by the controller of Examination in association with the internar examiner appointed by the Chairperson of the Department. Pre-requisites: Knowledge of assembly language. About the Course: The Lab work on Advanced Microprocessors cultivate the ability to write the programs by mastering the assembly language programming using various concepts like addressing modes, assemblers, directives, operators, interrupts' It makes students to get acquainted with the hardware specifications of variousprocessors and operations between the microprocessor and input/output and/or memory devices. This Lab. fosters the ability to design microprocessors based apprications. Course outconres: By the end of the lab course students will be able to: col ' describe the internal architecture of an X86 processor showing the general purpose registers, the segment registers, the ALU, the flags register, the instruction pointer (Ip) register, and the instruction register. (LOTS: Level 2: Understand) co2' implement the assembly language programs for interfacing of peripherals/devices with processors. (HOTS: Level 6: Create) CO3. analyse microprocessor controlled systems. (HOTS: Level 4:Analyse) CO4- evaluate microprocessor controlled systems. (HOTS: Level 4: Analyse) co5' create Lab record for the assignments including aim, hardware and software requirements and solutions to given problems. (HorS: Lever 6: create) Co6' demonstrate independent enquiry, self-learning and ethical practices to solve unseen problems. (LOTS: Level 3: Apply). List of experiments/assignmen ts: l Three assignments ' on assembly language programs using 8086 Microprocessor. 2' Two assignments depicting the use of intemrpts and intemrpt structure. 3 ' Two/Three assignments based addressing on modes, operators and use of directives in assembly language programs. . 4' Three assignments to show interfacing of 8086 with peripheral devices (I/o devices and memory). 5' Two assignments to design microprocessor-based applications such as rolling display. 6' Two assignments to program EEPROM chips to be used in applications such as traffic light controllers. 7 Two assignments based on ' Pentium multi-core microprocessors of 2.4 GHzlcompatible bandwidth. Note: The actual experiments/assignments will be designed by the course coordinator. one assignment &ould be designed to be done in groups of two or three students. The assignments must meet the"gbjective of tlb course ji.". ;.; ;; il ilffi ; #,i,,, o. ;,$ f;:1,: ::# :;::: #;ffi LH #: #: m5 Wr#i'iffi "?A, r53 '\ ^ T*/{ A \-t0 'Q/ 1 " P)-;,P'J ro o u) I cal I a I I a (\ ca co ao N I o I ca F{ rnI I $ 0.r F.l V) U I I I ra U o I l,,l e, q) o\ U) I I a^ U € I I aa d J F- o I I (A0 q) (.) \o c I L () ro tr)s FI o I N I z I q) (.) r+ N I c.) X o I N N tr !r (\l " x l.''j' \ a (\ I ,#,1.r" k ,.s i "y' .#, { 'I"/ N a.l N '' :': c.) it;t ,rE I l,.l cl l= = la l= 9) s., a t9,^ lg, u!< Io o-) l6 a d l^- rl f :a u) CI roo p E sl= Aa - lE 3 0 s g .'; 3a l; eP g.= E lora l= E.a 6 Lit: UI IE t.: co luo o co 9.> lJ O o) s3 lc c !* g 5< 13< lb 8 e \nI oo- lE r E: i sl,J .. lH.i : : l* o sl' l-$ lo cu c '- -f, I oos.. g; lo- p 00)ov) J JE,:'I lE: F l: /rQ) lE .o 6 -o C6F r! l- ^i tg e d L c./) ?oa> e6 6 0-t? (J (, lr Jr oJ l€i€s .a-J I Gl lc if sS )EJ a;cdv (J tr l(6()() fiO rgia;ili rr.t l E Lu) IEE in L-Cd :'-c)-- ? b S'$all )F a.rl o.i rLf,A) E b - EI; Eili .9 0lle General Course Information Course Code: PEC-CSE 406-p I Course PCC-IT4O3-P Assessment Methods (internar: 30; externar: 70) The internal and externar assessment is based on the level of Course Credits: I participation in lab. sessions and the timely submission of lab experiments/assignments, Type: Professional Elective Lab. Course the quality of solutions designed for the assignments, the performance in vIVA-vocE, the quarity Contact Hours: 2 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignments The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the controller of Examination in association with the internar examiner appointed by the Chairperson of the Department. Pre-requisites: Java programming, object-oriented programming, RDBMS and oLTp About the Course: This course on Mobile Application Development is a developmental rab. work on Mobile programming. incorporates It creating Applications related to Android Studio framework. The objective of the lab course is to equip the students to solve the practical Mobile problems related to Application development. course outcomes: By the end of the course students rvill be able to: col apply Android programming ' concepts for calling, display, creation and validation. (LorS: Apply) Level 3: Co2' generate solutions for content providers and permissive models. (HoTS: Level 6: Create) co3' compare the visual effects generated by Android and visual studio frameworks. (HorS: Level Analyse) 4: co4' design applications for Android Programming by using Android studio framework. (H6TS: Level Create) 6: Co5' create lab record the of solutions for assignment. (FIOTS: Level 6: Create) co6' demonstrate ethical practices, indepe,dent enquiry and self-rear,ing to solve unseen problems. (LOTS: Level 3:Apply) List of experimen ts/assignmen ts: t. create "Hello world" application to display "FIello world,, in the nriddle of the screen in red color with white background. ' 2. create sample application with login module. (check username and password), validate it for login screen or alert the user with a Toast. a create and valid ate a login application using username as Email ID else login button must remain disabled. 4. create a Login application and open a browser with any one search engine. 5. Create an application to display "Hello World" string the nurnber of times user in meric value. (Exarnple. If ,,Hello user enters 5, tlte next screen should print World,, nr. **.d 155 v 6. Create spinner with strings Aom the resource folder (res >> value folder). On changing spinner value, change image. . 7, Create an application to change screen color as per the user choice from a menu. _ 8. Create a background application that will open activity on specific time. ' 9 . Create an application that will have spinner with list of animation names. On selecting animation name, that animation should effect on the images displayed below. 10. Create an UI listing the engineering branches. If user selects a branch name, display the number of semesters and subjects in each semester. 11. Use content providers and permissions by implementing read phonebook contacts with content providers and display in the list. 12. Create an application to call a phone number entered by the user in the Edir Text box. I 3 . Create an application that will create database to store usemame and password. 14. Create an application to insert, update and delete a record from the database. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three sfudents. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the se.mester. 156 (..) o I V) I 6l o I I a I o (n cn ca ca cf} A \o! N I I tf, I I cn f-l V) U I ! o I I U rd Frt I co I q) u) fr o\ I I I e.} U a I I I (o F] r- I q) F{ \o I I I I q) ra aa ca (a aa q) I -t t c I c'n C\ ca I I ra CJ c N c.l (-.t CN I iar- (\I a! 6l aa c\ I c) a.l (\I a-.t c^ I a= X d. I L =an bo lg I sel li lsl ;l .2 I a I F3l EI '1t-.aI \ lp .l o)l '5 ;l -o()!-n G I E-EI slCI t rr-) isl; I IE FI (9t;l =rol= ..1 I E () r-lal aAl cil 'oFl L 1JI =rlS I c sjls I *q{N Islvl lgEl ol s+ e ; l€ I G) L I 15,;l E.al be ?l- E ?I F.< bqi ; ul A1 eBl =Elil !-l I b0* 3 El: I E6l l-', g€l+ UI E 3l o ..1 e a E gl.l - d c3 arllr i El; f; ; r l-s l( 5i clfll o IU IE/f/ iJtt (j HE II)=-:l .. I .Al; l Eli !o,1 O ,91: D tr_l E E IJlFl: u ilq >l (] o - o) l= i E lg sl:uElo. €EIIq I ll ; -f e c El( r 5ls if 3ll () >.oli 0lc iEII li t) o.Eli lelS i.-I ryl A. q.rla El!.Tlu b:l*;l!: r-l (s olc ) sloi r cul ts= U tl; * =l: ' I {l O , 'l: 'li J 5 tt I u l<-l ls It IE I il Multimedia Technologies Lab. General Course Information Course Code: PEC-CSE 407 -P I Course Assessment Methods (internal: PEC-IT41 I -P 30; external: 70) The internal and external assessment is based on the level of Course Credits: I participation in lab. sessions and the timely submission of lab experiments/assignments, Type: Professional Elective Lab. Course the quality of solutions designed for the assignments, the performance in vIVA-vocE, the quality Contact Hours: 2 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignments The intemal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the Controller of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Basic programming skills and knowledge of computer graphics. About the Course: This lab. course on Multimedia technologies involves a rigorous training on Adobe photoshop, Macromedia Flash and blender. incorporates It solving problems related to animation and modelling framework. The objective of the lab course is to Learn to navigate and use modelling tools that will help students to gain a strong foundation in 3D design software Blender. Course Outcomes: By the end of the course students will be able to: COI' apply the fundamental principles of different elements of rnultimedia. (LOTS: Level 3: Apply) CO2. use modern tools for applying state-of-the art multimedia technologies. (LOTS: Level 3: Apply) CO3. analyse various tools for an application. (HOTS: Level 4: Analyse) CO4. create posters, elegant sceneries, animated stories and movie clips. (HOTS: Level 6: Create) co5. creating record of lab experiments. ((HorS: Level 6: create) CO6. denlonstrate ethical practices, self-learning and team work. (LOTS: Level 3: Apply) List of experimentyassignments: Adobe Photoshop l. Introduction to Photoshop Basics. 2 Design a poster for 2019 elections and show the difference in quality and resolution for prjnt and Web. Pick 3. any picture ofa magazine cover page and make ctianges using selection tool. 4. Draw a landscape using multiple Layers. 5. Paint a scenery ofa park using differenr rools ofpholoshop. 'i ,, , 6. Take image from different lmage Sources show variarion in resolution. ,rt-',' 7. Use effecrive cropping techniques ro design a collage. 'r'' t ,/ 8. Design a scenery showing correction of image tonalit r. 9. Make a poster by adjusting Image Colours. 10. Paiuting the coverpage ofyour magazine with Special photoshop - Tools. -,._ I l. Design a card on thc occasion ofDiwali using at least 3 different filters. _..-' 12 Make your passport size picture with all editing and print multiple copies ofthe same on 44 s ize pag{. r58 Macromedia Flash 13. Introduction to the layout and tools of Flash. 14. Move a car from left to right of the screen using symbols. 15. Design a movie clip. 16. using timeline, design the casting of the movie directed by you. 17. Depict a small story using 2 D animation. Blender 18. Introduction to Blender and its various tools. 19. create an object using blender and show its motion. 20. Using Selections and Transform make a scenery. 21. Design a character for your game using modelling. 22' Depict the change in Materials, Lights and Rendering in 3 different frames. 23. Using Blender show compositing. Note: The acf'ral experiments/assignments will be designed by the course coorcJinator. One assignment should be designed to be done in groups of two or three sfudents. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and sc6edule of submission will be prepared by the course coordinator at the beginning of the semester. *rY* ,I \@- 159 cro I U) I I cN (t) I o a! c-! ca u) cn I N I ca I I ! I I r-. \f, OtEl c I ca U I o\ riU I I cn 00 q) I I cf} q L r-- I I U \o I I I -t (al U) C) ca c-l bo Pl ' , I ca o-I5l I () col e) Cl r c-l I Ed o-l L (\tt \o ol I I c\ () 6-l Hl :l llrlt, z X L \ l€ a= lclv l.=IB IH I.J t6 l= .,.,.Mi, l= ,rt' A lcl3 t: ,,. i I le lels IE L l# General Course Information Course Code: PEC-CSE 408-P / course Assessment Methods (internal: PEC-IT4O8-P 30; external: 70) The internal and external assessment is based on the level of Course Credits: I participation in lab. sessions and the timery submission of lab expdriments/assignments, the quality Type: Professional Elective Lab. Course of solutions designed for the assignments, the performance in vIVA-vocE, the quality Contact Hours: 2 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignments The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the Controller of Examination in association with the internal examiner appointed by the Chairperson of the Deparlment. Pre-requisites: The students are expected to have a knowledge of computer graphics concepts. About the Course: This Lab course on Digital hnage Processing is a developmental lab. work. It rncorporates transformation of images in spatial and frequency domains, compression, restoration and reconstruction of images in SCILAB/MAILAB. The objective of the lab course is to equip the students to solve the practical Image processing problems. Course outcomes: By the end of the course students rvill be able to: implement COf digital image processing concepts for image compression, restoration and reconstruction in SCILAB/MAfLAB.(LOTS : Level 3 : Apply) CO2. verify the results of applying image processing problems to images (compression, expansion, multi- resolution processing etc.) (HOTS: Level 4: Analyze) CO3' measure the quality of image after the digital image processing techniques are implemented to an image. (HOTS:Level 5: Evaluate) CO4. devise solutions for Image Processing tasks problems. (HOTS: Level 6: Create) CO5. design Lab record for the assignments including aim, hardware and software requirements and solutions to the given problems. (HorS: Level 6: create) CO6. use ethical practices, independent enquiry, self-learning and team spirit. (LOTS: Level 3: Apply). List of experiments/assignmen ts l. Two/Three introductory assignmenrs on SCILAB/MATLAB. 2. Two assignments on Point processing and Pixel Operations e.g scan your signature and make it clean with thresholding.) 1 J. One/Two assignments on Image flipping. 4. Two assignments'on Image Arithmetic such as Addition, subtraction, multiplication and division. 5. Create an application to display "Hello World" string the number of times user inputs a numeric value. (Example. If userenters 5, the next screen should print',Hello world,,fi) 16r ,@/ / 6. TwoiThree assignments on performing Logical operations on Digital images such as NAND, NOR, EX-OR on these images. 7. Two/Three assignments on calculation and equalization of histogram for an input image. 8. Two/Three assignments on geometric transformation !- of image such as translation, Scaling, Rotation, Shrinking, Zooming. 9. One/Two assignments on adding noise to the image and apply image restoration techniques to improve quality of image. 10. Perform low pass and high pass filtering in frequency domain. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels the given of course outcomes. The list of assignments and schedule of submission rvill be prepared by the course coordinator at the beginning of the semester. t62 o?a V) c.l af) cn co I oN I I I 0 I I I I I o I I (-t I I I co I 6 !+ rIl c I O U I I c I ao U I El o. F*rl o\ o I q) I I c.} U) li € I U co r- I (! I -] \o bo I I I a U) rn q) ce () C' cn co tr .+ o I I aa q) I I bo .n C.l N a{ CN ca -( \o t\l 6l cn ca (a bo I -t a{ aa aa ca X I L a0 I ocl a a= F I tE I o En63 rF I () ; I c l$ €a I oo ()- (g o0 := I (g -E l=: lF 50 ol q) '.= I -;l _.= E lrys If /g l .=)l 63d fr lS s= Al * lE-= ls lc'E o-I gr I .99 o 3^lx ce Z!q lg -o 'o'I ls3 General Course Information course code: PRoJ-csE40l I Course Assessment Method (100) Course Credits: 4 | rne evaluation is done jointly by internal examiner and external examiner appointed by CoE. The Mode: Self learning under rhe guidance of I break-up of marks for evaluation given faculty members. I is below. t Literature contact hours: g hours/week I ' review: 20 2. Problem formulation: 20 3. Basic knowledge of the tools: 20 4. Organisation and presentation of synopsis: 20 5, Level of Ethics followed: 20 About the major project I: Srudents start rvorking on their project '.vork in seventh sernester. Student do the background research for identifying appropriate problems, methodology and tools for their respective project works to be culminated in eighth semester. They prepare a synopsis of the project work to be carried out. At the end of sevcnth semester, each student required is to prepare a synopsis in the format provided and present it in front of a committee constituted by the Chairperson of the Department. Students can carry out projects in groups of two- In case of group project, the size of the problem should be significant, and members of the group must specify their individual contribution. Course Outcomes: After doing Major Project Part I students wiil be able to: COl. evaluate critically the existing solutions and methodologies through reviewing literature. (HOTS: Level 5: Evaluate) CO2. formulate suitable problems to be addressed. (HOTS: Level 6: Create) CO3. identify tentative modern tools to solve the problem. (HOTS: Level 4: Analyse) CO4- organise and communicate (written and oral) ideas effectively. (HOTS: Level 6: Create) CO5. develop rnethodologies that meet ethical, societal and legal considerations. (HOTS: Level 6: Create) 164 ?.) o I U) I I 6l o U) I I I A o (r) I I I I .| c.) o e.l I c.) I o I co I o c I I I (..) o\ \f, I I .o r{ A.. a oo U I I .a I f-! r- tv I I I i.rl \o I o I I H tu a.) (J rn €) '= I .o I fr I+{ rf, c.) c.) fr c I ra l- o ?a ro (\t lr) a I \o X (\I fr C co rO I I I aF{ al c.l (\l (J ()ao f( (t) -t oO Ar U7 t- UI lcs q) (B '', : lpt: () lo) i- Q t; \i) IE 6 \i lsle 0) t; J $= I o-> i! t.- a a lbo F U I U o E I o- o ,n A Q - 6 ^l U) .- I =, EI () c) 'olbl tt) 6 'al '== el o q) dt U iqi,/gg/gg General Course Information Course Code: PROJ-CSE4}2 | Course Assessment Method (100) Evaluation is *Course Credits: I I _done by internal examiner appointed by the chairperson of the Department. The break-up of marks for is given below' Mode: Design and development of I "'ul'ation t - Significan." of the problem mini-project in lab. I lld.or]ginality addressed and the I solution provided: 20 2. of the problem No. of hours per week: domain and the tool used (VIVA- I VOCE):259"I:1*: 3. Report Writing: 20 4. Judgement of the open source tools learnt and quarity of the solution developed: 20 5. Level of Ethics followed: l5 About the mini project: Students do a mini project using open source software after sixth semester They are expected to learn any open source software and develop applications that can be completed within 4 to 6 weeks. \ After doing mini-projects students will be able to 991 identify a suitable problem from the environment around. (HOTS: Level 4: Analyse) Co2. survey the design of similar problems (IIorS: Level 5: Evaluate) CO3. select suitable engineering specialisation and modern IT tools. (LOTS: Level 3:Apply) CO4. address the problem in an original and innovative manner. (HOTS: Level 6: Create) CO5. communicate orally as well as in written (mini project report) about the application developed. (HOTS: Level 6: Create) CO6. engage in ethical practices, individual and team work, and lifelong learning. (LOTS: Level 3:Apply) e, s# > ^q+!{ \l I 166 ?.) (,C cN I I a I I o U) I I 6t I ca 6l A \f, fEl I I o I I U I C ao & l-i o,\ I I I I ca 'h)q) z a cn U) o r- o C\ I F.t I () o \o fr cn ('J O rn I a-) I o) t o o a.l ca ca I bo co U) I N c-l r- I \o t\ ()I c ra ca ca o 0r I L itrl N ca I el-r X lr o \-l Cg lgE I a ! ; l; ls lr (.) E o t- i l; lE lsr l€ I I () () L rIilElsF l3l Fetrr + st' :l l+l ,t I I E l() ^l-()l' 4{ U lE ;l I l$el i,lf ; lE l= / I E. 3I: I / sl# 1l i EI; EIJ =1(g Jlj ? lf tl; 5ls slil,/fi/gl/gi,/ir/g It =lt _lq ls l' I' lii Data Mining Techniques General Course Information Course Code: PCC-CSE403-T I PCC-IT4O2-T course Assessment Methods (internal: 30; external: 70) Two minor examinations (20 marks), class performance Course Credits:3 measured through percentage of lectures attended (4 marks), assignments (6 Type: Professional Core marks), and the end- semester examination (70 marks). Contact Hours: 3 hours /week For the end semester examination, nine questions are to be set Mode: Lectures (L) by the examiner. A candidate is required to attempt 5 questions in all. All questions carry equal marks. Exarnination Duration: 3 hours euestion number I will be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by serecting one question from each of the four units. Pre-requisites: Knowledge of database systems, elementary knowledge of statistics and probability. About the Course: t Today's era is the era of infonnation. Data is growing exponentially day by day. There is a need to process and analyse the data to extract knowledge from it, so that one can use that knowledge for decision making. This course provides introductory concepts of data mining and data warehousing. Thelourse will be taught with a database as well as machine learning perspectives. The objective of the is to provide a comprehensive understanding prep-processing, "ou.r. of data data mining tasks and evaluation of results obiained out of data mining processes. course outconres: By the end of the course students will be able to: CO1. outline various types of data mining and data warehouse concepts and techniques. (LOTS: Level 1: Remember) CO2. explain characteristics, architecture of a data warehouse, OLAP operations and data mining tasks. (LOTS: Level 2: Understand) CO3. apply various pre-processing and data.mining techniques for extracting valuable information fronr data. (LOTS: Level 3: Apply) CO4- evaluate the descriptive and predictive data rnining models. (HOTS: Level 5: Evaluate) CO5. plar a data mining process for discovering knowledge from real-world databases. (HOTS: . .-,-*y,i*'-" , ' \.*- 1' ' r? .,'' Course 1, Conten{ \,. /' {.rL ,i Unitl..r.. Introduction to Data Mining: Kind of data to be mined, Data Mining Functionalities, Technologi.r,.rrijji, ' Data Mining, Applications of data Mining, Major Issues in Data Mining. ,,..'/ Data Pre-Processing: Need for preprocessing, Data Objects and Attribute types, Statistical description of data, Data Visualization, Measuring similarity and dissimilarity of data, Data Cleaning, Data Integration, Data Reduction, Data Transfonnation and Data Discretization. ,68 q Unit II Data warehouse: Introduction, Data warehouse and Database Systems, Data Warehouse Architecture, Data warehouse Models, Data cube and oLAp, Multidimensional data Model, Concept Hierarchies, OLAP operations, D ata Warehouse Implementation Unit III Mining Associations and Correlations: Mining Frequent Patterns, Associations and Correlations, Frequent Itemset Mining using Apriori Algorithm, Generating Association Rules from Frequent Itemsets. Improving efficiency of Apriori, Pattern Growth Approach for Mining Frequent Itemsets, pattern evaluation Methods. Advanced Pattern Mining: Pattern Mining in Multilevel and Multidimensional Space, constraint-Based Frequent Pattern Mining. Unit IV Classification: Introduction, Classification using Decision Tree Induction, Bayesian Classification Methods, Rule Based Classification, Model Evaluation and Selection, Techniques to Improve Classification Accuracy. Classification by Backpropagation, Support Vector Machines andLazy Leamers. Cluster Analysis: Introduction, Basic Clustering Methods, Partitioning Methods, Hierarchical Methods, Evaluation of Clustering. Text and Reference Books: l Jiawei Han, ' Micheline Kamber and Jian Pei, Data Mining Concepts and Techniques,Morgan Kaufmann Publishers, Third Edition, July 201 l. 2' AIex Berson, stephen J. Smith, Data wrehousing, Data Mining & oLAp,Tata McGraw Hill, 2004. 3' Pang-Ning Tan, Michael Steinbach and Vipin Kumar, Introcluction to Data Mining,pearson Education, 2014. 4' K' P' Soman, Shyam Diwakar and v. Aiay, Insight into Data Mining Theory ancl practice, Easter Economy Edition, prentice Hall of In dia,2009. 5' G' K' Gupta, Jntroduction to Data Mining with Case Studies,Prentice Hall of India, 2006. 6. Daniel T. Larose, Data Mining Methods and Models, wiley, 2006. 7. w. H. Inrnan, Buitding the Data warehouse, wiley India, 2005. rffil ,/ Y/r{, ,. 169 o?a o ol ca .n co cn 0r c.l a I I c a I I I .I c I c I I o F I I I ca o\ r-lv a c I I U I a U I U 0r l*{ r- I I (t) q) \o I I rn () q) I c..l I t-t !+ bo I I ca ao .a tsl z I c.n ca r- t\t a..l ca X L a\ .a ra zFI f ,**''.f P,*. X,.o-,'../ il .f :V: ./ (.) 1g/ E lf l; t3 I -rf 41 I.glE I F- sl lH looO c lss la; El=f It 19..v I x l9; lE,E : lo o) U $? lrE ; alts 3 E..i Ig ;.' lE -oHEI;€ -o F = i lfi (.)I crrllra-o l E E (glch-l f lE E El; e -t I I! eIlH 5' a o->lo--- | O l tt) sslPq I O c) O $FlEiflIEf s aol A zl= (r) I I 3 E ; gbl=,1 3l p 3 t € l€ ?: : glf; s"6l 0) +r l-d rtrl ., I q) C!cnl-C)\Ol E o o E * s E E E IS E I (t- U =€ilE;ilir?3lsi i =ls tt q) (, o lS lS i 0) I u lc-r lr-r I d ls I J Internet of Things General Course Information Course Code: PEC-CSE 409-T / Course PEC-CSE4O9-T Assessment Methods (internar: 30; externar: 70) Two minor examinations (20 marks), crass performance Course measured Credits: 3 through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Elective marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the Mode: Lectures (L) examiner. A candidate is required to attempt 5 questions in all. All questions carry equar marks. euestion number r will Examination Duration: 3 hours be compulsory and based on the entire syilabus. It wiil contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions frorn each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question frorn each of the four units. Pre-requisites: Fundamentals of Computer Networks About the Course: The field of Internet of Thi,gs is growing very fast. The purpose of this course is to impart the knowledge on basic concepts of IoT, its Architecture, various protocols and applications in real world scenarios. course outcdmes: By the end of the course stuclents will be able to: col state the basic concepts ' and key technologies of IoT. (LorS: Level l: Remember) co2' discuss the pros and cons of various protocols for IoT. (LoTS: Level 2: understand) Co3' apply the IoT models for business applications. (LOTS: Level 3: Apply ) Co4' analyse applications of IoT in real time scenario. (HOTS: Level 4: Analyse) co5. desig, business model scenarios (HorS: Level 6: create) Course Content Unit I what is the Internet of Things? : History of Io! About IoT, overview and Motivations, Applications, Examples of Internet of Things Definitions and Frameworks : IoT Definitions, IoT Architecture, General observations, ITU-T views, working Definition, IoT Framewprks, Basic Nodal capabilities, Basics of Microcontroller, Microprocessor vs Microcontroller, Types of Sensor, Actuators and their Applications. Unit II Identification of IoT objects and Services, Structural Aspects of the Io! Environment characteristics, Trafiic Technology-Introduction, principle of RFID, components of an RFID system, I ttrplectuology. r .,y / 171 .i, --rl ,/ /I ,/ Unit III IoT Access Technologies: Physical and MAC layers, Topology and Security of IEEE 802.15.4,802.15.49, 802.15.4e, l90l .2a,8A2.llah and LoRaWAN, Network Layer: IP versions, Constrained Nodes and Constrained Networks, Optimizing IP for IoT: From 6LoWPAN to 6Lo, Routing over Low Power and Lossy Networks, Appllqton Transport Methods: Supervisory Control and Data Acquisition, Application Layer Protocols: CoAp and Mqi r. Unit IV Business Models and Business Model Innovation, Value Creation in the Internet of Things, Business Model Scenarios for the Internet of Things- Internet of Things Applications: Smart Metering Atlvanced Metering Infrastructure, e-Health Body Area Networks, City Automation, Automotive Applications, Home Automation, Smart Cards, Srnart Transportation and Smart Shopping. Text and Reference Books: 1' David Hanes, Gonzalo Salgueiro, Patrick Grossetete, Rob Barton and Jerome Henry, IoT Fundamentals-'Netuvorking Tbchnologies, Protocols ancl (Jse Casesfor Internet oJ'Tltings, Cisco press, l " Edition ,2\ll . 2' Olivier Hersent, David Boswarthick, Omar Elloumi , The Internet of Things - K"y applications ancl Protocols,Wiley, 2"d Edition, 2012. 3' DieterUckelmann, Mark Harrison, Michahelles, Florian (Eds), Architecting the Internet of Things,l,l Edition, Springer, 2011. 4' Michael Margolis, Arduino Cookbook,"Recipes to Begin, Expand, oncl Enhance your projects,,, 2nd Edition, O'Reilly Media, 20ll. 5' Arshdeep Bahga, Vuay Madisetti, Internet of Things - A hancls-on opproach, l" Edition, Universities Press,20l5. *-, t -_-'.' 'rrul b- ".T '' /-, ii \ 112 co I 6l C.l oa I I art c.) C.l oa (\ ca ca 0r c! CN a 6l I c.l I I l flo\r OI l I rl c HIaI I UIrl I UI 0. F]I o\ Ail I I I 0) (r) t co u I U r- v) I bo \o F I eFa ln cn ca I CN q) t- $ () c.) I I C.l ca crl c t-. co C.I c-.1 \ I ol al C\l co co (J I s C-l ca c.) ,t L WT I x \.s# vi t li i bt #& *#" j.J e I i I/ d I () i I tr _) cI (.) Software Defined Networks General Course Information Course Code: PEC-CSE 410-T I Course Assessment Methods (internal: PEC-IT4I O-T 30; external: 70) Two minor examinations (20 marks), Class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type : Professional Elective marks). Contact Hours: 3hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt questions Mode: Lectures (L) 5 in all. All questions carry/ equal marks. Question number I will Examination Duration: 3 hours be compulsory and based on the entire syllabus. It wiil contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Programming in CIC++/ Java About the Course: Software Defined Networks is a result of improvement of flexibility of Network Control. To make the Networks Programmable it was deemed necess ary to separate the Control Plane from the Data plane. SDN Controllers are inserted into the Network to realize Network Virtualization. Openflow protocol and Mininet framework are used to design SDN. This Course is considered as a necessary addition in the Curriculum of B. Tech. (CSE/IT) from professional point of view. course outcomes: By the end of the course students will be able to: COl. outline Software Defined Networks and its various conlponents. (LOTS: Level l: Remember) CO2. explain techniques to rnake the Network Programmable for better flexibility. (LOTS: Level 2: Understand) CO3. use of modern tools to implement SDN Controllers in a Network scenario. (LOTS: Level 3: Apply) CO4. breakdolvn Virtual Networks into its components for controlling of networks. (HOTS: Level 4: Analyse) CO5. compare and contrast the working of SDN through various protocols. (HOTS: Level 5: Evaluate) CO6. generate SDN using Application Programming Interface and cornpute its performance for a given scenario. (HOTS: Level 6: Create) Course Content Unit I Introduction: The need for Programmable Networks, Evolution of Software Defined Networks, Software Defined Networks' Architecture and Design, Traditional Switch Architecture, Centralized and decentralized Control Plane and Data Plane, IETF SDN framework, Scalability (Service provider Networks, ISp Automation), Reliability (QoS and Service Availability), Consistency (Configuration management and Access Control violations). ,., i :',1r.tr './ ., 174 ,/' Unit II Open{Iow and Software Defined Networks Controllers: Control and Data Plane Separation, Evolution of openflow, sDN controllers(poX, floodlight, openDaylight), Applicability of Openflow protocols in SDN controllers, scalable programming for sDN controllers. Unit III Network Yirtualization: virtual Network, Abstraction of physical Network, components (virrual of virrual Network Switch, Bridge, Host-virtual adapter, NAT device, DHCP server, Network Adapter), Network as a Service (NaaS), Network Virtual Machine. Unit IV Software Defined Networks Programming: Programming Software Defined Networks, NortSbound Application Programming Interface, current Languages and tools, Network Functions Virtualization, Software Networks Defined implementation and Applications, Bandwiclth Calendaring- Data Ce,ter orchestration, Mininet. Use_ cases(Network Access control, virtual customer Edge, Data center optimization), Latest trends in SDN. Text and Reference Books: 1' Paul Goransson and chuck Black, so.fnvare Defined Networks; A Contprehensive Approach. First Edition, Morgan Kaufmann ,2014. 2' Thomas D.Nadeau, Ken Gray, Software Defined Networks,o,Reilly Media, 2013. siamak 3' Azodolmolky, software Definetl Nenuorking with openflow, packt publishing,2013. 4. Kingston Smiler, openJrow Cookbook packt pubrishing,20r5. 5' Doug Marschke, Jeff Doyle, PeteMoyer, Sofnvare Definecl Networking; Anatomy of openJlow, Volume-I, Lulu publishing Services, 2015. {yr \ lls co o U) I I 6t V) N co ca cn ca C.) V) I I N I I I F I a tf, I H I I I U) U I U I I td lJ( oo I 6) q) i< r-- I I I I U \o ' rt) v I I L rn ca aa CN ca q) z t o I N ca aa N l- .a \o () I C.l a.l on C{ ^ F-' q) 6t l. o I C.l a{ C. ca +r i- f ,: c'.1 aa ca aa rt V ..' a *)-1.1:-.,.u ,J!1 ,-,ii ,, ..*t ,: X General Course Information 4ll-T / Course Code: PEC-CSE Course Assessment Methods (internal: 30; external: 70) PCC-IT3O5-T Two minor examinations (20 marks), Class Performance measured through percentage of lectures attended (4 marks), Course Credits: 3 assignments (6 marks), and the end- semester examination (70 Type : Professional Elective marks). questions are to be set Contact Hours: 3 hours/week For the end semester examination, nine by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. All questions carry equal marks. Question number I will Exarnination Duration: 3 hours be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. pre-requisites: Netlvorking, protocols defined in layered Architecture, programming fundamentals. About the Course: Network Administration and Management is a Professional Elective course deemed to be necessary during the present era of Information Technology and Computer Science. This course deals with analyzing Network for statistics such as protocols, servers, memory, CPU etc. Network Monitoring and Management deals with different events in various types of platforms for response- Course Outcomes: By the end of the course students will be able to: COl. define Network Administration and its various components. (LOTS: Level l: Remember) CO2. distinguish Network Administration and its Management on various platforms. (LOTS: Level 2: Understand) CO3. classify the output for different responses to events by interpreting Network Monitoring statistics. (LOTS: Level 3:ApplY) CO4. separate portions of Network for troubleshooting using various tools. (HOTS: Level 4: Analyse) CO5. combine Network Administration, Network Management and Network Monitoring into a one scenario and compute the performance of the integrated environment. (HOTS: Level 6: Create) Course Content Unit I Network Administration: Introduction to Network Administration Approaches, Addressing, Subnetting and Supemetting, Fixed Vs Variable Masks, VLAN Principles and Configuration, Routing Concepts: Static and Dynamic Routing, Routirig Protocols: RlP, OSPF, BGP. Network Address Translation (NAT), Configuring a DNS Windows Box as a Router, Dial-up configuration and Authentication: PPP, Radius, +SS Configuring a Server in windows, Configuring Sendmail Service, Configuring a Web Server,.@ryguyfrg a Proxy Server, TCPiIP Troubleshooting: ping, traceroute, ifconfi g, netstat, ipconfi g. t71 k Unit II Linux Network Administration: Setting up a file seryer, setting up samba server, configuring Network services: installing and configuring DHCP seryer, installing and configuring DNS server, setting up internal NTp seryer, hosting http content via Apache, sharing resources in a Network. Unit III Network management: Management Standards and models, Configuration Management and auto discovery, Fault Management, Fault identification and isolation, Event correlation techniques, SNMPvl, SNMpv2: Structure of Management Information, Standard Management Information Base (MIBs), MIB-II, Network Management Functions: Accounting Management, Perfonnance Management, Network Usage, Metrics, and Quotas, SNMPv3: Protocol, MIB. Unit IV Network Monitoring: Network Performance Monitoring, Remote Network Monitoring (RMONI): Statistics Collection, Alarms and Filters, RMON2: Monitoring Network Protocol Traffic, Application-Layer Visibility, Management Tools, Systems and Applications: Test and Monitoring tools, Integrating tools, Development tools, Web-based Entemrise Manageinent. Text and Reference Books: I' Mark Burgess, Principles of Ne:nvork and System Administration,2nd Edition, Wiley publications, 2004. 2- Craig Hunt, TCP/P Network Administration,3rd Edition, O'Reilly Publications,2002. 3. George Splading, ll/indows 2000 Administration,Tata McGraw-Hill, 2000. 4- Tony Bautts, Terry Dawson, and Gregor N. Purdy, Linux Nehvork Administrator's Guide,3'd Edition, O' Reil ly publicariorrs, 2005. 'I', / ( .rf"*"\",4 ,, I ,11 .r it* ; 178 ?o C U) I I (-l a cn co ca co co I O I I .l , I L' I 0. .+ I frl C I I O U I I I riU F-l o\ q) I (a L € I I I U r- I q) \o q) I a0 I I ta G zF( I c.t cn cn .c I a.) C{ aa co c.l C{ a{ G fi (\II o\ t-- rt) I N co ca ?l ' 5t 0-l a.l c.l an L o U' )I )l Ll 0)l o ,il o 'N{ zl )' XI f I LI o i. {-. I o ,,i dl a F{l -"d zt o trl / t, ol (r) r. I I 6dl CJI=l lE l, FI l= I Arlol il IE EI. UIIU li e l! lsIo *-li lc,lc IE lc #li I 0.) lvt L E U 5li lc- .2 o lc J U IU Softlvare Testing and Quality Assurance General Course Information Course Code: PEC-CSE 412-T I course Assessment Methods PEC_IT412-T (internal: 30; external:.70) Two minor examinations (20 marks), class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 rnarks), and the end- semester examination Type: Professional Elective (70 marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 Mode: Lectures (L) questions in all. All questions carry equal marks. euestion number Examination Duration: 3 hours I will be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one uestion from each of the four units. Pre-requisites: Software Engineering. About the Course: This course introduces students to software testing process ancl describes the quality assurance process and its role in software development. During the course students learns about the testing methods and tools, creating good test cases to irnprove the quality of software. Course outcomes: By the end of the course students will be able to: COl. recall the process of software testing life cycle and quality assurance. (LOTS: Level l: Remember) CO2. demonstrate reusability testing on software applications. (LOTS: Level 2: Understand)) CO3. apply software testing tools for predicting the behavior of software applications. (LOTS: Level 3: Apply) CO4. identify the test cases for software applications. (HOTS: Level 4: Analyse) CO5. plan test cases and quality managernent activities. (HOTS: Level 6: Create) predict CO6. softrvare quality based on quality parameters ancl quality models. (HOTS: Level 6: Create) Course Content Unit I Introduction to Basic of soffware testing & Terminology, Software Development & Software Testing Life Cycle- role and activities, Necessity and Objectives of testing; Quality Concepts, euality Control, McCall,s factor model; Different Software Development Model; Object- oriented testing, Web testing, GUI testing; Elements of Software quality assurance; Quality Assurance Activities, Statistical euality Assurance; Software Reliability, SQAplan, euality Standards:-IEEE, CMM, ANSI. Unit II Testing Concepts, Issues and Techniques, Levels of Testing, Verification and Validation Model ; Techniques of Verification:-Peer Review, Walkthrough, Inspection, FTR Unit testing, ; Integration testing, Function Testing ; System testing, Installation Testing, Usability Testing, Regression testing, ; Performance testing:-Load Testing, Stress Testing, Security testing, Volume testing ; Acceptance testing:-Alpha testing, Beta testing, testing. Gamm-a rsob@-r(,'li)"r"'),- , $..,yr"i 1i Unit III BlackBoxTestingMethods:Equivalencepartitioning,Borrndary.vaIueanaIysis,Errorguessing,graph.based testing methods, Decision Table Testing; white Box Testing Methods: statement coverage, Decision coverage, Condition coverage, Path testing, Data flow testing. Test Planning & Docurnenration: Deveropment pran and quarity pran objectives; Testing stategy, Tesr. Management, strategic Management, operationar rest Management, Managing the Test Team, Test prans, ..rest Cas€s, Test Data, Risk Analysis. Unit IV Testing Tools, Features oftest tool; Guidelines for selecting a tool; Tools and skills of tester; static testing tools, Dynamic testing tools, Advantages and disadvantages ofusing tools, Introduction to open source testing t"ool. Text and reference books: l. M. G. pinciples, Limaye, Software Testing Techniques and Toots,TMH,2009- 2. Yogesh Singh, Software Tesling, Cambridge University press. 2016. 3. Ron Pattom, So1,ipa re ksring,2"d edition, Sams, 2005. 4' Roger s. Pressnran, software Engineering- practitioners a approach, g,h edition, McGraw Hilr, 2014 5' Jeff Tian, software Engineering: Quality Testing, Quality Assur.tnce and Improvement, Wiley,2005. euantiJiable 6 Stephan H' Kan, Melrics and Moders in sofnvare Quality Engineering, 2nd edition, Addison-wesrey, 2009. 7. William E. Perry, Efective Methods of Sofware Testing,2d editior., Wiley,2000. r@\ \t/ qy, r81 m U) I c6l U) I I I I r a C.) ca cn ca ca co , N I I I I I I N r+ rI] a I I U 0r I U r-l I *r () o\ I LU) I I I 00 U I () O r- I C! \o q I U) I I I rr) ca ao co !f, cy I a{ ca co aa ca a.l I (..l on (a c.i oo bo (\l ..T aa c.) u) o ro q) ,r L c) C\l a\l L ca aa q-r a x li ls l: li ls le lf 1l? lE I a,= li l! liF l;i l,E: l; c) () .E El= Ig L frslg.l*; I €EllEl;5 U t oaa rilr:lg; U r:l: ile E i gl2 ..1>, s) u ,) E s lE H la s r J ) &,*l^rlt;l s lg l5 I Machine Learning General Course Information Course Code: PEC-CSE 413-T / Course Assessment PEC-IT413-T Methods (internal: 30; external: 70) Two minor examinations (20 marks), class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination Type: Professional Elective (70 marks). Contact Hours: 3 For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 Mode: Lectures (L) questions in all. All questions cany equal marks. euestion Examination Duration: 3 hours number I will be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. Question ,umbers 2 to g will be given by setting t\vo questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Basics of Linear Algebra probability and Statistics, Basics of Theory Data Structures and Computer Algorithms. About the Course: Machine learning is the study of computer algorithms that improve their performance through experience. Machine learning draws its conceptual foundation from the fields like artificial intelligence, probability and statistics, computational complexity, cognitive science, biology and information theory etc. The course introduces spme of the key machine learning algorithms and the theory that form the backbone of these algorithms' The examples of such algorithms are classification algorithms for Iearning patterns from data, clustering algorithms grouping for objects based on similarity, neural network algorithms for pattern recognition, genetic algorithms for searching large and complex search spaces etc. course outcomes: By the end of the course students will be able to: COI' outline the concepts and working of different machine learning algorithms. (LOTS: Level l: Remember) CO2. interpret the results of machine learning algoritluns. (LOTS: Level 2: Understand) CO3' apply machine learning concepts and algorithms to given problems. (LOTS: Level 3: Apply) CO4- analyse the performance of machine learning algorithms. ((HOTS: Level 4: Analyse) CO5. compare and contrast different machine learning algorithms. (HOTS: Level 5: Evaluate) CO6' design machine learning algorithms for optirnizatiortr pattern recognition a,d search problems. (HOTS: Level 6: Create) ? Course Content Unit I Introduction: Well posed learning problems, designing a learning system, Issues in machine learning, the concept learning task, Concept learning as search, Finding a maximally specific hypothesis, Version spaces and candidate elimination algorithm, Remarks on version spaces and candidate-eliminationq 183 \v Unit II supervised Learning: Introduction to linear regression, estimating the coefficients, Accessing the accuracy of the coefficient estimates, Accessing the accuracy of the regression model, Multiple linear ,.ir.rrior, iogirti, regression' basic decision tree leaming (ID3) algorithm, Hypothesis space search in decision tree learning algorithm, Inductive bias in decision tree learning, Issues in decision tree learning, k-nearest neighbour learning. Unit III unsupervised Learning: About clustering, type of data in clustering analysis, k-means and k-medoids, DBSCAN density-based clustering method, Performance analysis of clustering algorithms, Artificial Neural netlvorks: Neural Network representations, Appropriate problems for neural network learning, Perceptron' The perceptron training rule, Gradient descent and delta rule, Multilayer Networks and back propagation algorithm. Unit IV Bayesian Learning: Bayes theorem, Bayes theorem and concept learning, Maximum likelihood and least_ squared error hypotheses, Naive Bayes Classifier. Evaluating flypotheses: Estimating hypothesis Accuracy, Basics of sanrpling theory, Error estimation and estimating Binomial proportions, the binomial distribution, Mean and variance, Bias and variance, confidence intervals' Trvo sided or one sicled bounds, central limit theorem, Flypothesis testing, comparing algorithms learning Text and Reference Books: 1. Torn M. Mitcheil, Machine Learning,rVlcGraw-H iil, rggr. 2' Bishop Christopher, Pattern Recognition and Mcrchine Learning,Springer verlag, 2006. 3 ' Trevor Hastie, Robert Tibshirani, Jerome Friedman, Tlte Elentents of statistical Leorning: Data Mining, In"ference ancl Prediction, springer,2"d edition, 2009..J. FIan and M. Kamber, Data Mining Concepts a,d Tech,iques, 3rd Edition, Elsevie r, 2012. 4' S' Rajeshkaran, G' A' vijayalakshmi Pai, Neural Netuvorks, Fuzzy Logic and Genetic AlsoNthm;"'6"'\""'' Synthesi.s and Applications,pHl,2003 184 ro o c.l a cn cn aa aa ca N o (a I I I (n I I t\l I I I I C I Fr I I I ?a o\ rf, I I H a oo I U I I I U r-'] r- I I I (,) \o U) I L I .n U I I b, I r$ ca (^.l ca fr co cO d () .O I (\l F] a'l c.l N C.l e) N tr) co o N (^.l co ca I c.) f-{ a.l z N ca CO ca X ,r zt-r () 6l al ;f o o =l aot 0_3 I Q =l CI tsl €-oe6 .=l ?l 'El f ol I E] anl aot !r ,l EI cl I I .'-6 e.- I FI .oF -l ol cl I (j-. () cDl a:E CI =9.. I oY I HI I --tcl d >)l C) sl l.al q-Ee lf, o-I ^lorl -c al()l +l LI c o-l C) ?l o €Eo? I o a\l tt) I CI d .a General Course Information Course Code: PEC-CSE 414-T / a Course Assessment Methods (internal: PEC-IT4I4-T 30; external: 70) Two minor examinations (20 marks), class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type : Professional Elective marks). Contact Hours: 3hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 Mode: Lectures (L) questions in all. All questions carry equar marks. euestion number Examination Duration: 3 hours I will be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: Basics of statistics and data mining. About the Course: This course aims to provide students with the knowledge of current challenges, rnethodologies and technologies processing in big data. Emphasis will be placed on the students' understanding of the rationales behind the technologies and the students' ability to analyse big data using professional packages and tools. Course Outcomes: By the end of the course students rvill be able to: COI. reiall the concepts of big data analysis. (LOTS: Level 1: Remember) CO2. interpret the outcomes of big data analysis. (LOTS: Level 2: Understand) CO3' apply technical skills and modern tools for descriptive and predicative modelling. (LOTS: Level 3: Applv) CO4. analyse a fratnework for visualization of big data analytics for business user. (HOTS: Level 4: Analyse) CO5. critically the results of mining to support business decision-maki1g. (HOTS: Level 5: Evafuate)"xllrrine '', CO6' design schemes for big data analytics for solving big data problems i1 efficient manner. (HOTS: Level 6: Create) Course Content Unit I Introtluction: Overviews of Big Data, State of the Practice in Ahalytics, The Data Scientist, Big Data Analyics Industry in Verticals, Data Analytics Lifecycle Challenges of Conventional Systems, Statistical Concepts: Sampling Distributions, Re-Sampling, Statistical Inference, Prediction Error, Regression Modelling, Multivariate Analysis, Bayesian Modelling. Unit II Mining Data Streams: Stream Data Model and Architecture, Stream Computing, Sampling Data in a Stream, Filtering Streams, Counting Distinct Elements in a Stream, Estimating Moments, Counting Oneness in a Window, Decaying Window, Real time Analytics, Platform (RTAP) Applications, Case Studies, Rea[ Time Sentiment Analysis, Stock Market Prediction ,.L. _, '/ q **{':''i '\ r86 1\ '"" t,,'/ ."." ,'A q Unit III Frequent Itemset and Clustering: Mining Frequent ]temsets, Market Based Model: Apriori Algorithm, Handling Large Data Sets in Main Memory, Limited Pass Algorithm, Counting Frequent Itemsets in a Stream, clustering based rechniques: Hierarchical, K-Means etc., clustering High Dimensional Data, cLIeuE And PROCLUS, Frequent Pattem based Clustering Methods, Clustering in Non-Euclidean Space, Clustering for Streams and Parallelism.. Unit fV Frameworks and Visualization: Overview of MapReduce, Hadoop, Hive, MapR, Sharding, NoSeL Databases, 53, HADOOP, Distributed File System (HDFS), Visualizations; Visual Data Analysis Techniques, Interaction Technique and Applications. Text and Reference Books: l. Michael Berthold, David J. Hand, Intelligent Data Analysis, Springer, 2007. 2. A. Rajaraman, J.D. Ullman, Mining of Massit,e Datasets, Cambridge University Press, 2012. 3. Bill Franks, Thnting the Big Data Tidal ll/ave: Finding Opportunities in Httge Data Streams with Advancecl Analytics, John Wiley & sons, 20i2. 4. Glenn J. Myatt, Making Sense of Dota, John Wiley & Sons, 2OO1 5. Pete Warden, Big Dota Glossaty, O'Reilly, 2011. rt ar'l ffr r) 181 ra (nc o.l cn ce c-) c.t C' cat (n I I I I U) I al I I I I I F I I I t+ I I t+ o\ E] a I U I a U I ri F. c) I I I U) tr \o I U (r) rn I I I I I d $ c.l a{ C' ca aa 41\ ao co a! C.l a! a.l o.t oo (\t bo a\ c.t a{ c.J .N X r\t f( ca c.l co ca t'- f FI .:, -j ,1" _f ..it ' ," ,/ - 0) E lst.- IlA u I o I= lc h" " t: a) o ,-; /.; I o-r J lJ' l'a lE ^l Its a E lE [-o / F -=' I lli lsfil q) o h lS 15 t, J lpcl L 6sl€ l3 l'; o I .i :ElY^l;6X o-I-o () l^ P ls .A G E l= l: I ! III:ili€ l>- lJ q.) l.Y < I c I! l3 al I lqIr I.; F U lctr E iol l- lE I 3lS : lS : 6'rl loo I 3;13 91.? 9 E el lE = * l.= 3 l= c) lbo * slAI ! gl: ULI l5(+' l: I la ; o = sl! !2= I: P 85lH I g l3 I, o- g=li3l;5= () 3 l: T T IE H IE P f Elt olo ^l: -lcs E bl o- c,l <-r eEI = =l'C'A I 9lVt 0()-l tn !l L ! l- ; le s l5 E HIP ! t1 I l/l€:l-3 s Lc)lrc)!-I U= EII Hlg l- -a- E d.)lj o-c l: EL El:.', I cal c( X- r- g l.r = aoi?l tr Lle tr i€l?:lE E o) !3ll s?l g =lQ) d, a'l l< t 3li p € dl.( l. lq- .-lol- .lo ..i1.; l+ l; l .glX-ln o lc u lcr 18 ls I s li Web Development General Information Course Code: PEC-CSE 415-T I c course Assessment Methods (internar: 30; externar: 70) PEC-IT4I5-T Two minor examinations (20 marks), class performance measured through percentage Course Credits:3 of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Type: Professional Elective marks). For the end semester Contact Hours: 3hours/week examination, nine questions are to be set by the examiner. A candidate is required io attempt 5 questions in all. Mode: Lectures (L) All questions carry equal marks. euestion number I will be compulsory and based on the entire syllabus. It will contain Examination Duration: 3 hours seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question from each of the four units. Pre-requisites: knowledge of Computer Basics About the Course: web development is a management of information. web Development is a core and an essential course for every graduate in Computer Science and Engineering. This course introduces web designing tools like HTML, xML' Java Script and ASPiJSP etc. and various web site will be designed with the help of these tools for solving real world problems- It includes various types of website. Further, It is more useful for dynamic programming as well. course outcomes: By the end of the course students lvill be able to: CO l enlist principles of Information ' Architecture lbr Web design. (LOTS: Level l: Remember) co 2. explain navigational systems, labeling systems, and taxonomies for websites. (LOTS: Level Understand) co 3. apply basic web designing tools (HTML, xML, ASp/JSp, JQuery, Java Scripr). (LOTS: Level 3: Apply) . co 4' evaluate critically design of webpages basecl on various technologies. (HorS: Level 5: Evaluate) co 5' create a report describing or making recomnrendations for a website design. (HorS: Level 6: create) Course Content Unit - I Information Architecture, Role of Information Architect, collaboration and communication, organizing Information, organi zational challenges, organizing web Sites and Intranets, creating cohesive organization Systems Designing, Navigation Systems, Types of Navigation Systems, Integrated Navigation Elements, Remote Navigation Elements, Designing Elegant Navigation Systems, Searching Systems, Designing the Search Interface, Indexing the Right Stuff, what to Search or not to search, Grouping content, conceptual Design, Architecture Blueprints, Architectural Page Mockups, Design Sketches. 189 Unit - II .-- structured Information, Design and Documentation, XML web 6.0, JDBC, Metadata, unstructured , Information, Techliques for Umtructured lnformation, HTML Basic Concepts, Good Web Design, process of Web Publishing, Phases of Web Site Development, Structure of Html Documents, Html Elements for Designing '. Pages. Text Level Events, Linking Basics, Linking In Html, - Images and Anchon Attributes, Image Maps, Semantic Linking Meta Information, Image Preliminaries, Images, Layout Design, Advanced Layout. Audio Support in Browsers, Video Support, Other Binary Formats. Style Sheets, Positioning With Style Sheets. Basic Interactivity and Html: Forms, Forms Control, Advance HTML and Web Designing. Unit - ilI Alternative Technologies for Designing, The Hypertext Transport Protocol, URLs, HTTp, Browser Requests, Server Responses, Proxies, Content Negotiation, The Common Gateway Interface, The CGI Environment Variables. CGI Output, Forms and CGI, Sending Data to the Server, Form Tags, Decoding Form Input, Architectural Guidelines, Coding Guidelines, Efficiency and Optimization. JSp Basics, Integrating Scripts in JSPs, ASP Objects and Components, JSP: Request and Response Objects, Retrieving the Contents of a HTML form, retrieving a Query String, cookies, Creating and Reading cookies. Unit - IV XML basics, Relationship between HTML, SGML, and XML, Valid Documents. Ways to use XIyIL, XML for Data Files, Embedding XML into HTML documents, Converling XML to HTML for DISpLAy, Displaying XML using CSS and XSL, Rewriting HTML as XML, Basics of Advance Web Development Tools. Text and Reference Books: 1. Thomas A Powell , HTML-The Complete Reference,TataMcGraw Hill, 2003. Scott 2. Guelich, Shishir Gundavaram, Gunther Birzniek, CGI Progrcrmming tvirh Perl 2"d edition, O'Reilly,2000. Doug 3. Tidwell, James Snell, Pavel Kulchenko, Programming II/eb Services tvith SOAP,O'Reilly, 2OOg. 4. Young, Xlv{L Step by Step,2nd edition, pHI. Paul J. Deitel, 5. Harvey M. Deitel, Abbey Deitel, Internet & Iltorld l,Iticte ll/eb How to progrom, 5th edition, 2008. Yy / -,j,,, /l/ r'/t'- 190 ro a I I N a I I an a-.1 o (r) (\ cn ca ca ('a 0. N o I I 0r I C! F{ I I ra I I cn. r+ rc o\ O .o U t € I U I I .o rI] F< r- () I (r) I tr \o o I ao .n U ra q) I ca aa c.) tf, o 6J ca cn () co q) o I I C.'l a.l d o\ - c.l C) o a.l ca I x tr cl cn d al- C! OI +. I Ll fl CI / TI ) UIol I jE/ *'/ j'/ !EF/ 3',/ fr Statistical Computing General Course fnformation Course Code: PEC-CSE 41 6-T I Course Assessment Methods PEC-IT4I6-T (internal: 30; external: 70) Two minor examinations (20 marks), Class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), assignments (6 marks), and the end- semester examination (70 Tlpe: Professional Elective marks). Contact Hours: 3 hours/week For the end semester examination, nine questions are to be set by the examiner. A candidate is required to attempt 5 questions Mode: Lectures (L) in all. AII questions carry equal marks. euestion number I will be compulsory Examination Duration: 3 hours and based on the entire syllabus. It will contain seven parts of 2 marks each. Question numbers 2 to g will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by selecting one question fiorn each of the four units. Pre-requisites: Basics of probability Atrout the Course: It is important to know essentials of statistics to become a successful data analyst or researcher. This course is tailored to introduce the graduating engineering to the fundamentals of statistics so that they can analy ze data and draw inference from it. course outbomes: By the end of the course students lvill be able to: col. define basic tools of data analysis. (LorS: Level l:Remember) CO2. explain the concepts given in descriptive and inferential statistics (LOTS: Level 2: Understand) CO3. apply statistical concepts to solve real world statistical computing problems. (LOTS: Level 3: Apply) CO4. analyse the trends in data using descriptive statistics. (HOTS: Level4: Analyse) CO5. interpret and evaluate statistical models. (HOTS: Level 5: Evaluate) CO6. conc'lude the findings of statistical analysis. (HOTS: Level 6: Create) Course Content Unit I Review of Descriptive Statistics and Probability Theory: Scale of measurement and data types, Descriptive statistics, Frequency Tables and graphs, Relative frequency tables and graphs, grouping data, histograms and ogive, mean, median, mode, variance and standard deviation of dample data, sample spaces and events, Axioms, Conditional Probability, Independent event, Bayes Theorem, Binomial Theorern. Unit II Random Variable and Bistributions: Random variables, type of random variables, Mean (Expectation) and variance of a discrete random variables, Discrete uniform distribution, Bernoulli's distribution, Binomial distribution, Geometric distribution, Poisson's distribution, Mean and variance of a continuous random variable, Unit III Hypothesis testing: determining levels of significance, Types of hypothesis testing errors, Hypothesis testing for population mean for large and small samples; Comparing two population means for large and small independent samples; Comparing two population means for paired samples; Comparing two population proportions, Chi-Square, t test and F test, Analysis of variance (ANovA). Unit IV Statistical Learning and Linear Regression: Definition of statistical learning, Estimating a function f, The trade of between prediction accuracy and model comprehensibility, Regression versus Classification problems, Measuring the quality of fit, Bias and Variance trade off, Linear Regression between variables, Estimating the Coefficients, accessing the accuracy of the coefficient estimates, assessing the accuracy of the model, Multiple linear regression, estimating the multiple regression. Text and Reference Books: 1 Ross Sheldon ' M', Introduction to Probability ancl Statistics for Engineers oncl Scientists,4th edition, Academic Press, 2009. 2' Douglas S. Shafer and Zhang Zhiyi, Beginning Stcttistics,2Ol2. [Available freely o,li,e under Creative Commons by-nc-sa 3.0 license] Brain 3. S- Everitt, A Handbook of Statistical Analysis (Jsing R, Second Edition, LLC 2014 4. Roger D. Peng, R Progrontming.for Data Science, Lean Publishin g,2015. Michael 5. J. Crawley, Statistics, An introcluction rtsingR, Second edition, Jo6n Wile y,2015 6' Trevor Hastie, Robert Tibshirani, Jerorne Friedman, The Elements of Statistical Learning; Dota Mining, Inference and prediction, Springer, 2,d edition ,2009. Itri J i'rl"?'*J i.r i :;' g 193 ta a a-l a.} cn (a cn co ol V) I I I o V) I I I al I I I I I F \o! I I I r+ I r--t o\ U) I U t co U I ri I F. I o I I LU) \c I U I I bo tr-) C' ca ca I a\l cf) ca ca Hl ' U .ol \f, Ol r a{ a\ o o-I a-l N o\ q) , a.t ao N C. 6( Hl I V) x "# lr a\=i tr) 6 () J a ,/,'/ F ,/ Q Qr L I 4t ,n 6 o tt I tr IG 8i lo lelE ,^luol General Course fnformation Course Code: PEC-CSE 417 -T / PEC-IT4O6-T course Assessment Methods (internal: 30; external: 70) Two minor examinations (20 marks), class performance Course Credits: 3 measured through percentage of lectures attended (4 marks), Type : Professional Elective assignments (6 marks), and the end- semester examination (70 Contact Hours: 3hours/week marks). For the end semester Mode: Lectures (L) examination, nine questions are to be set by the examiner. candidate Examination A is required to attempt 5 Duration: 3 hours questions in all. All questions carry equal marks. euestion number I will be compulsory and based on the entire syllabus. It will contain seven parts of 2 marks each. euestion numbers 2 to 9 will be given by setting two questions from each of the four units of the syllabus. A candidate is required to attempt the remaining four questions by serectirg on" question from each of the four units. Pre-requisites: working knowledge of Winclows/Macintoslr/Linux, Network security. About the Course: The course on Digital Forensics is an inevitable study in this information era. computer crimes are on a hike by the hackers and cyber criminals. The need to recover the deleted, hidden and comrpted files on windowsAvlacintosh/Linux platforms give an opportunity to offer digital forensics automating features. This will give students a chance to study larvs of court against computer crimes committed intentionally or inadvertently. Course outcomes: By the end of the course students will be able to: COl. determine the hardware and operating system requirements for digital forensics.(LOTS: Level l: Remember) CO2' represent digital forensics by organization of data and metadata in computer systems.(LOTS: Level 2: Understand) CO3' analyze file recovery and hidden file extraction techniques. (HOTS: Level 4: Analyze) CO4' identify various types of forensics in the arena of information technology. (HOTS: Level 4:Analyze) co5' critic the computer crimes by studying the security Laws and legal Landscape around the world.(HOTS: Level 5: Evaluate) Co6' integrate security of computer systems ',vith digital forensics and evaluate its perforrnance. (HoTS: Level 6: create) Course Content Unit I . Introduction to Digital Forensics: digital crimes, digital investigation, evidence, extraction, preservation overview etc.; of hardware and operating systems: structure of storage media/devices, Windows/Maci,tosh/Linux- registry, boot process; disk and file system analysis, data acquisiti-on of physical storage devices. Unit II Data recovery: identifying hidden data, recovering deleted files; digital evidence controls: uncovering attacks that evade detection by event viewer, task manager and other windows GUI tools; disk imasins recoverino .& Unit III Network Forensics: collecting and analyzing network-based evidence, reconstructing web browsing, email activity, intrusion detection, tracking offenders, windows registry changes, etc.; Mobile Network forensics: introduction, investigations, collecting evidences, where to seek digital data for funher investigations; Email and database forensics; memory acquisition. Unit IV Computer crime and legal issues: intellectual property, privacy issues, criminal justice system for forensic, audit/investigative sifuations and digital crime scene, investigative procedure/standards for extraction, preservation and deposition of legal evidence in a court of law. Text and Reference Books: 1. Thomas J Holt , Adam M Bossler, Kathryn C Seigfried-Spellar, Cybercrime and Digital Forensics.- An Introd uct ion, Routle dge, 20 I 5. 2. cory Altheide and Harlan cawey, Digital Forensics with open source Tbols, Elsevier publication, April 201t. B. Nelson, 3. A. Phillips, F. Enfinger, C. Steuart, Gtticle to Computer Forensics snd Investigations 4tt' edition, Thomson, 2009. 4. Michael Flale Ligh, Andrew Case, Jamie L.ry, AAron Walters, The Art of Memory Forensics; Detecting Malware ond T'hreats in wndows, Linux, and Mac Memory, july 2014. ..-;i4v'' \ t" - i ,.'' 196 co o I I a! U) I 6l o co a^ U) c! co co ao A (a I I o. N I I c I I I a.) 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General Course Information Course Code: PEC-CSE 409 -P I Course Assessment Methods (internal: 30; external: 70j PEC-IT4O9-P The internal assessment is based on the percentage of lab Course Credits: I sessions attended (4 marks), timely submission of lab Type: Professional Elective Lab. Course experiments/assignments and the quality of solutions Contact Hours: 2 hours/week provided in the assignments (16 marks), and an internal Mode: Lab practice and assignments vIVA-vocE (10 marks) conducted towards rhe end of semester- The external examination is of 70 marks. The break-up of marks for external examination is based on quality of lab reports (20 marks), quality of solution(s) for the given problem(s) at the time of examination (written work + execution of program(s)) (30) and vIVA-vocE examination 20). Pre-requisites: Basic knowledge of C/C++ language, Basics of Electronics. About the Course: This course focuses on significant contponents of Internet of Things. l'he objective of this lab course is to make the students familiar with prototype and key cornponents of networking for development of application based on Internet of Things. Course outcomes: By the end of the lab course students will be aLrle to: COI' solve the existing problems of traditional sensor networks and wireless communication using the concepts of Internet of fhings. (LOTS: Level 3:Apply) CO2. analyse the working of controllers and sensors. (HOTS: Level 4: Analyse) CO3. compare and contrast the existing solutions related to IOT. (HOTS: Level 5: Evaluate) CO4- design solutions forpractical assignments byusing Internet of Things technologies. (HOTS: Level 6: Create) CO5' create lab reports by presenting the ideas regarding solutions in an effective manner. (HOTS: Level 6: Create) CO6] demonstrate inclepenclent enquiry team spirit and ethical practices while solving problems. (LOTS: Level 3:Apply) List of experimen ts/assignments: l. In order to implement IoT practical assignments one needs the following: Hardware ' Setup- device capable of storage and network, e.g. Raspberry pi, Intel Galileo, Intel, Edison, Multiple sellsors etc. t . Software- Wiring Pi (C++ for Raspberry Pi), Wiring x86 (python for Intel Edison) . API to connect hardware to web server . Web Interface 2. Two assignments to figure out input and output devices. 3. Two assignments to interface digital and analogue devices with microcontroller unit. 4. Two assignmeni for calibration of sensors. 5. Trvo assignments for receiving data from sensors serially. 6. Two assigrunents to read the values from sensors. .1. ,a ..)' ') ,r& @, 7. Two assignments based on testing of temperature sensor, integrating of temperature sensor with microcontroller, temperature control over internet. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be groups done in of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. 199 co c.l U) a.l 6l cn t Ar (\t c co (n co aa ca I O. I (a I I t\t I I I I I (-O , o\ I c.) !+ aE] o\ U I I .o I U oo ri I c.) q) r- a) I I I L \o I U I ln J aa) c.) cn C' (a bo s N co aa ca I F .ol Ol c..l (-'l fH C.l I 0-l ^I c..l q) El .., I c-.l ca o. I I ^ a) N I )-,( Hl l-l'"1'" X Ck L loIE x z I .- o. l()ls l'o -; l(Blc I 6 lP'- () J0.) L a a 41 F 0) o J I ? U' q U ()t I i. o\ ()a @ bo trl=f, OJ= a 't O 0) I -o al U 0)I E] ; =l c! -cl>t a t) ;t () ()lol 'r= ()I I q) sl 6-I (+- o 6 0) J Software Defined Networks Lab. General Course Information Course Code: PEC-CSE 410-p I course Assessment Methods PEC-IT4I O-P (internal: 30; external: 70) The internal and external assessment is based on the level of Course Credits: I participation in lab. sessions and the timely submission of lab experiments/assignments, Tlpe: Professional Elective Lab. Course the quarity of solutions designed for the assignments, the performance in vIVA-vocE, the quality Contact Hours: 2 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignments The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the controller of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: knowledge of computer Networks and Java. About the Course: This course on Software Defined Netr,vorks is a development lab. which involves configuration of open switches for different platforms. It incorporates setting up of hosts to be connected to a Network through SDN controllers installed on servers. The objective of the lab course is to equip the students to solve the issues related to Openflow protocol through openFlow Standard, Mininet and OpenDaylight Controllers. course outcomes: By the end of the course students will be able to: CO1. implement SDN controllers using APl/mininer. (LOTS: Level 3: Apply) CO2' analyse results of SDN statistics for a given scenario. (HOTS: l-.u.t-+,Analyse) co3. assess performance of protocols for a given Network. . (HoTS: Level 5: Evaluate) Co4' hypothesize solutions for SDN controller issues by using Network statistics. (HoTS: Level 6: Create) CO5- create lab records for the assignment solutions. (HOTS: Level 6: Create) Co6' demonstrate use of ethical practices, selllearning and team spirit. (LoTS: Level 3:Apply) List of experi ments/assig.nmen ts l. Introduction to the OpenFlow Standard. 2. SDN Controller concepts and interfaces using open Day light controller (Java based implementation, REST interface, OSGI module interface) 1 J. Implementation of centralized static and dynamic routing protocols. 4. control plane distribution for increased availability and scalability. 5. open Day light in an open Networking Platform that enables SDN and constructs a solid foundation for Network functions Yirtualization for all Network sizes. Perform virtualization in the Data centre and in the Network. 6. open Day light Controller- Brokers and RPC calls, the Datastore, plugin Development workflow, Development environment setup. 7. Testing and perfornance evaluation using software switches (open vSwitch), hardware switches and ^'-t\ v Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. *,, - r'{. r- _^.1-,J. ,F ,u.";''-'J r' / 202 r.. oc.) V) I I 0. 6l o a co co co ca tu o V) I O. (\I I I c.) I -+ I I I r--! A a-t U I I cn I U rd o\ I c.) () v) € L I I aa U r- I J \o I I U) L rr) aa an cn an I () .+ a.t co ca f.) z I () .A tr c\ N c.l c-l I c) ca Ft (.I q) a.l cn ca ca a.l fr I c! co ca 5t'(\ I e) q< O. I O X (.) L (.) i I a ls z F J 6 lE I \/:E l"o I l.= I I 0) ;/;/sl e lr I ()l s l.q I FI ) I,l I 1l o 16 I 4. 3 l-- I "#.f it aO I nrlrl E ls ,,,fi' ah F, I ' CI lH UI s lLSl ^ s lESl * : l:^tl3lE;l iil g ly, ql Lj I-IE5I E i : Fl € ( ,lolE li U l;/3s/r;/,j l5 I il Network Administration and Management Lab. General Course Information Course Code: PEC-CSE 4ll -P / course Assessment Methods PCC-IT3O5-P (internal: 30; external: 70) The internal and external assessment is based on the level of Course Credits: I participation in lab. sessions and the timely submission of lab experiments/assignments, Type: Professional Elective Lab. Course the quality of solutions designed for the assignments, the performance in vIVA-vocE, the quality Contact Hours: 2 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignments The internal examination is conducterd by the course coordinator. The external examination is conducted by external examiner appointed by the controller of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: knowledge of Computer Networks, System Administration, Unix/Linux Command line. About the Course: This lab. course on Network Administration and Management involves configuration of servers for different platforrns- incorporates It setting tlp of otres' nrachine to be connected to a Netvyork and cSecking its status frequently for any intrusion. The objective of the lab. course is to equip the students to solve the practical Administration, Management and Monitoring related problems. Course outtomes: By the end of the course stndents will be able to: COl. configure a seryer to work as a DNS/DHCPiFTP/Web/MaiVPrint server (LOTS: Level 3:Apply) CO2. detect the trends in attacks through in depth attack analysis. (HOTS: Level 4: Analyse) CO3. formulate solutions for Monitoring assignrnents by using principles of Network statistics. (HOTS: Level 6: Create) plan CO4. solutions for overall security of Computer/Network systems. (FIOTS: Level 6: Create) CO5. create file records of solutions of assignments. (HOTS: Level 6: Create) CO6. demonstrate use of ethical practices, self-learning and team spirit. (LOTS: Level 3: Apply) List of experimen ts/assignmen ts : l. Management (creation, rnodification and deletion of left users) of the users & their domain. 2. Setting up the local security policy for the system, software. a J. Maintaining your systetn in Linux Networking and Setufr Linux for firewa]l and Ip filtering. 4. Configure the kernel for IP Accounting and Ip Masquerade. 5. Install sendmail distribution and create sendmail configuration files. 6. Start and stop services from user window and command prompt. 1. Use of event viewer and performance monitor. t 8. Management of the IIS and FTP server. ,- #7.*'',' -4" f ., j. 9. Setting up of router in window 2000 server and Linux server. ,f 10. Use of utilities (a) Ping (b) Tracert (c) netstat(d) net (e) IP configuration (f) path ping 204 I l. Monitor the Network using performance monitoring tools such as RMON, tcpdump etc. 12. Setting up of a DNS server. 13. Setting up and use "Terminal Client Services',. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be doue in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The Iist of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. 20s co a I I 6l o ao cf) c.l ca a I o I I FI a I t 6l c ca ari U I U I I I rI] -r I I cn ae) li o\ U c-) € J I ao r- () o I I I o \c a0 I c.l I 6( rn t- ao CN co C. 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General Course Information Course Code: PEC-CSE 412-p I course Assessment PEC-IT4 12-P Methods (internal: 30; external: 70) The internal and externar assessment is based on the level of Course Credits: 1 participation in lab. sessions and the timely submission of lab experimentslassignments, Type: Professional Elective Lab. Course the quality of solutions designed for the assignnlents, the performance in vIVA-vocE, the qualiry Contact Hours: 2 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignments The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the Controlrer of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Knowledge of Software Engineering programming along with inClC++/.lava or /MATLAB. About the Course: In this lab' course, students learn to clesign, generate, nrinimize, and prioritize test cases of a software application using programming language or with the help of software testing tools. The lab experiments involve designing testing datasets by taking case studies and applying software testing techniques on these datasets. The course has a special focus on understanding and implementation of test results of software testing techniques to improve software quality. course outcomes: By the end of the course students rvill be able to: Col. implement software testing using testing rools. (LOTS: Level 3: Apply) CO2' apply software testing techniques for the classification of test cases. (LOTS: Level 3: Apply) CO3' interpret the results of various software testing techniques. (HOTS: Level 4: Analyse) co4. plan test case activities. (HorS: Lever 6: create) CO5' prepare lab reports for software quality testing assignments. (HOTS: Level 6: Create) Co6' demonstrate use of ethical practices, self-leaming and team spirit. (LoTS: Level 3:Apply) List of experimen ts/assignments l write a program to count ' the nunlber of digits in a number. Its input is any number from interval 99991' Design the boundary [0, value analysis test cases and robustness test cases. 2. Write a program to calculate cyclomatic complexity. ? a J. Consider a program to perform binary search and generate the test cases using equivalence class testing and decision table based testing. 4. Write a program to determine whether a number is even or odd. Draw the program graph and DD path graph. Find the independent paths. 5. consider the program for classification of a triangle. consider all variables and generate program possible slices. Design at least one test case from every slice. 6. consider the problem statement of a university student Registration system. prepare the requirement software checklist with the details of faults in rhe given sRS. 2o7L'',,- u r#:.dp\ {, '{a .r 7. Write a program to g€nerate, minimize and prioritize test cases using any prograrnming ' language/Matlab Tool/Software Testing tool. 'a 8. Write the outline oftest plan document as per IEEE Srd B2g ,lggg. 9. One assignment to be done in groups. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or tlrree students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. f .t. , .'! !,i$r' L 4 . ...-rt) t;.,:\- t ?gC"! 2 ?' '--r' 208 af) I V) I I I I (\t U) I t{ I (\lI \f, ri U) cn co c.) ca O U 6t I I U I I I aa H q) I I ca a I U I ca o\ G I I I (a Fl I o€) a I aa L r- q) I 4a I \c I rn f-r .a cn I rf, c-l c.l ca aa I bo .i2) C! C.l co cn ()U) F r-l o\ q) C.l a.l a.l co I c{ ir I 6t (-.l +r N ca ca a) U) l; X t- I o-r L IB t,; IJ !i t.. IE a la sl l= l5 la l€l k ta l*r /E/ rn -lol(g t; sl olc0 I ()IE I l; I lE 5l l- l'- IE 3l OI; L rol*.. I c-r General Course Information Course Code: PEC-CSE -4 13 -P I course Assessment Methods (internal: 30; external: 70) PEC-IT413-P The internal and external assessment is based on the level of participation in lab. sessions and the timely submission of lab Course Credits: I experiments/assignments, the quality of solutions designed for the Type: Professional Elective Lab. Course assignments, the performance in vIVA-vocE, the quality of lab. file and ethical practices followed. Contact Hours: 2 hours/week The internal examination is conducted by the course Mode: Lab practice and assignments coordinator. The external examination is conducted by external examiner appointed by the Controiler of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Programming in Java, python, R and octave/MATLAB. About the Course: In this lab' Course, students learn to solve optimization, supervised and unsupervised learning problems using machine learning tools. Students will use machine learning tools available in WEKA, R, pyhon and octave etc. The lab experiments involve downloading datasets and applying machine learning techniques on these datasets. The course has a special focus on interpreting and visual izingresults of machine learning algorithrns. Course outcomes: By the end of the course students lvill be able to: COf implement machine learning algorithms using modern machine learning tools. (LOTS: Level 3: Apply) CO2- analyse the trends in datasets using rlescriptive statistics. (HOTS: Level 4: Analyse) co3. apply descriptive and predicrive modelling. (LorS: Level 3: Apply) CO4' compare attd contrast machine learning algorithms for a given problem. (describe datasets using descriptive statistics. (HOTS: Level 5: Evaluate) CO5' create lab records assignment of by incorporating problem definitions, design of solutions, results and interpfe4ations. (HOTS: Level 6: Creare) CO6. dernonshate use of ethical practices, self-learning and team spirit. (LOTS: Level 3: Apply) List of experi ments/assignments l. Install wEKA/R/Pyhon/octave and rearn to use these software packages. 2. Two assignments relate.d to classification algorithms and interpreting the results of these algorithms. 3. Two assignments related to clustering algorithms and interpreting the results of these algorithms. 4. Three assignment on designing neural networks for solving learning problems. 5. Two assignment on ranking or selecting relevant features. 6. Two assignments on linear regression and rogistic regression. 7. One assignment to be done in groups. 210 , l-' Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. 2tt ro cn CN U) a^ ca (\l I V) I I a U) I I t\ I I co I I I o l+t I c.) I raI r+ o\ ard I I ro U co I U I cn l*tr--t r- I I I q) 'irU) \o I I I U rn rn a-t cn a^ J .+ cn co ca ca bo I I t) t a! C-l c'l a-l q) .N >] F (a a^ c{ q) EI N ca I a. I ..r .-, ca co Q 5l I I c-l I Fr Z, X Ir I t- a ;Elgel*zlsr lEi l5i l5 i () 5 IEfi I l=lils l5 I lE Fle oo_ cr) flgili;lflr () U tro (r) FC) (g >.] (c q) -aoF- U) t, C) o- (Bv () I o tra c) !O () e)e q) tro0 U) o) ra) l- 6 o r0) U t) - J U Big Data Analytics Lab. General Course Information Course Code: PEC-CSE 414-p / course Assessment PEC-IT4I4-P Methods (internal: 30; external: 7a) The internal and external assessment is based on the level of Course Credits: I participation in lab. sessions and the timely submission of lab experiments/assignments, Type: Professional Core Lab. Course the quality of solutions designed for the assignments, the performance in vIVA-vocE, the quality Contact Hours: 2 hours/week of lab. file and ethical practices followed. Mode: Lab practice and assignnrents The internal examination is conducted by the course coordinator. The external examination is conducted by external exarniner appointed by the controller of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Some basic knowledge and experience of Java (JARS, Array, Classes, objects, etc.) About the Course: This lab course provides an overvier,v of key technology used in manipulating, storing, and analyzingbig ,cata. This incorporates big data analyics and use of Hadoop. corrse outcomes: By the end of the course students will be able to: col. implement solutions for big data problem. (LorS: Level 3: Apply) co2- apply Hadoop ecosystem components. (LorS: Level 3: Appry) CO3. analyse the results of big data algorithms. (IIOTS: Level 4:Analyse) CO4' build and maintain reliable, scalable, distributed systems. (HOTS: Level 6: Create) Co5' create lab record of the lab assignments that contains problem definitions, their solutions in big data perspective and the interpretation of the results. (HOTS: Level 6: Create) CO6' demonstrate ethical practices, self-learning and team spirit. (LOTS: Level 3: Apply) List of experiments/a ssignments I. Installing and configuring Hadoop cluster. 2. Manipulating files in HDFS using Hadoop fs comrnands. Hadoop 3. File Systems: IBM GPFS, MapR-FS, Lustre, Amazon s3 etc. 4. writing an Inverted Index MapReduce Apprication. 5. Distributed cache MapReduce Design patterns Sorting Joins. 6. Writing a streaming MapReduce job in Hadoop. 7 Big Data and R: Clustering, ' Simple Linear Regression, Decision Trees, Naive Bayesian Classification 8' Big Data Interactions: Big Data and cloud: Big Data and web Services iSoA:Big Data and Internet of Things (IoT) 9' Big Data Case Study: Healthcare Data: web click stream Dara: Social Media Dara I RSS, Tweets] Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course of submission will be prepared by the course coordinator at thp bperi the semester. t.) 213 _r& re o co ca c7) CN cn I N V) I I t. I (a I I I al I I ca A I I I I -+-l I r+ afr] I I C. U I o\ riU I c.) i-{ € () cO trU) r- c I I I U \o 6 I I I F] rn ()U) rn cn aa a^ c\r c..l an El ca I O. I ..'I N ca s Hl | ^ N Ft 8I N I^ N ca oo al I X N ." _ I I L Hl I - | | t e( ..Y.1.i, a\5 ia:rt' 'j I 4L I U I L U Web Development Lab. General Course Information Course Code: PEC-CSE 41 5_pl course Assessment Methods (internar: 30; externar: 70) The PEC-IT4I5-P internal and external assessment is sased on the lever of Course participation in lab. sessions Credits: I and the timely submission of lab experiments/assignments, the quarity Type: Professional of sorutions designed for Elective Lab Course the assignments, the performance in vIVA-vocE, the quarity of Contact Hours: 2 hours/week lab. file and ethical practices followed. Mode: Lab practice The internal examination and assignments is conducted by the course coordinator. The external examination is conducted by externar examiner appointed by the controiler bf Examination in association with the internal examiner appointed by the chairperson of the Department. Pre-requisites: Basic programming skiils and knowredge of surfing internet. About the Course: This lab' course on- web development involves learning web-based development of progralming ranguages. It incorporates web pages by siructuring information provided the course is ror ine website design. The objective to equip the students to design ,ireb pug., of the lab urirrg modern *"b-d"r.lopment tools. Course outcomes: By the end of the course students lvilr be abre to: cor ' website design using modern toors il:liH:r1lT:i lfffi#r rike HrML, XMLand rAVA scripring co2. analyse the design of websites. (HoTS: Lever 4: Anaryse) co3' test the design of websites. (HorS: Lever 5: Evaruate) co4' design websites that consider socio-cultural varues. (HorS: Level 6: create) co5' create a written report for website designed. (Hors: Lever 6: create) co6' use ethical practices and socio-cultural values while designing websites. (Lors: Lever 3: Apply) List of experiments/assignmen ts 1. Create a simple webpage using HTML. 2. Designing of registration form rvith tabre and use of hyperrink. 3. Design a page with frames to incrude Images and videos. 4. Add a cascading style sheet for designing the web page. ? 5. use user defined function to get array of values and sort them in ascending order on web page 6. Design a dynamic web page with varidation of form fierd using Javascript. 7. Design a catalogue in ASp. 8. Event Handling Validation of registration form. 9. open a window from the current window on Mouse over event. 10. create a simple application to demonstrate Servlets Request and R 11. Demonstrate Array objects and Date object's predefined rnethods 215 A 12. Display calendar for the month and year selected from combo box l3- Create a welcome Cookie (Hit for a page) and display different image and text content each time when the user hit the page 14. Demonstrate Request and Response object using HTML Form. -r, 15. Database connection to display all the values in the table. Note: The actual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective ofthe course and the levels of the given course outcomes. The list of assignments and schedule of submission will be prepared by the course coordinator at the beginning of the semester. ,/ a 216 t) (a I I I N I U) I I I A cn ca a.l aa o I N I o I co I I t{ rnI t-l rf, I I aa H U) U o\ t I I C. U rIl @ I I q) U) F- I U \o I I .n I rn Fl c co ca co ca () \+ C{ C! aa I I .al () Ol ..r (-.l C! ca r- () O. I (\ll C{ l-l Ol c\ aa ca c.t I I q) O. l' Ol .! C' a.I c.) X o. I L H a. l;=l (.) fi l$B I l().: I lT a ll ff.t I X{ U l; iliA ls Irr: J l, E i lj fdel* E {lr E*.;19t (ao o EE U ilr I c-t t) o to '] o lc-l Statistical Computing Lab. General Course Information I Course Code: PEC-CSE41 6-P I Course Assessment Methods (internal: 30; external: 70) PEC-IT416-P The internal and external assessment is based on the level of Course Credits: I participation in lab. sessions and the timely submission of lab Type: Professional Elective Lab. Course experiments/assignments, the quality of solutions designed for Contact Hours: 2 hours/week the assignments, the performance in VIVA-VOCE, the quality Mode: Lab practice and assignments of lab. file and ethical practices followed. The internal examination is conducted by the course coordinator. The external examination is conducted by external examiner appointed by the controller of Examination in association with the internal examiner appointed by the Chairperson of the Department. Pre-requisites: Basic Statistics and Programming in pyhon, R About the Course: In this lab. Course, students iearn to solve statistical cornputing problems using R or pyhon. 'fhe lab experiments involve applying statistical tools for at'talyzing and inferring information from real world datasets. ie* The course has a special focus on interpreting, evaluating and concluding from the results of statistiual analysis. t course outcomes: By the end of the course students will be able to: CO1. implement statistical tools for drawing inference from data. (LOTS: Level 3: Apply) CO2. explore the trends in datasets using descriptive statistics. (HOTS: Level4: Analyse) CO3. apply probability, hypothesis testing and regression for solving research questions. (LOTS: Level 3: Applv) CO4. Judge different problem situations for applying appropriate statistical tests (HOTS: Level 5: Evaluate) CO5. create lab records of assignment by incorporating problem definitions, design of solutions, results and interpretations. (HOTS: Level 6: Create) CO6. denronstrate use of ethical practices, self-learning and team spirit. (LOTS: Level 3: Apply) List of experiments/assignments l. Install R and i{ studio. 2. Two assignments related to descriptive statistics. 3. Two assignments related to visualizing trends in data. 4. Three assignments related to permutations, cornbinations and probability. 5. Four assignments on Hypothesis Testing. 6. Two assignments on linear regression 7. Two assignments on logistic regression. 8. One assignment to be done in groups. Note: The acfual experiments/assignments will be designed by the course coordinator. One assignment should be designed to be done in groups of two or three students. The assignments must meet the objective of the course and the levels of the given course outcomes. The list of assignments and schedule of submisr,"*,1,;k, prepared by the course coordinator at the beginning of the semester. ', *U,., 218 + cO V) cn ca cn ca N o I I U) I I (a I I I (\l c I co Far I I \oI r+ rIl I cn O I U I a\ U I I co tEl oo I I () I .a U) r-. I U \o I I I F] .n bo c ao cn ao cn I t? ca c! aa CN t.al Ol .! a.l U a.t ca I o\ o. I I a..l I (-l c.l N c^ ca U) c! C.J a! c.) a I I x 13 a /ils/E le l*s l€ () f. l,E lE I lfl ls I I {y' U rf/gr/gi/s lE,/E-/ Io a-l'- tr Lri;l;il$islEi v t'E < < .. lg .. L I I J .n - v !Fl!--1.E I b l; u7d)le()lJ E -q ls 3li q) u) E? l3 r I; U E3lSili U) J sIrL Digital Forensics Lab. General Course Information Course Code: PEC-CSE4l7 -P I course Assessment Methods (internal: 30; externat: 70J PEC-IT4O6-P The internal assessment is based on the percentage of lab Course Credits: I sessions attended (4 marks), timely submission of lab experiments/assignments and the quality of solutions Type: Professional Elective Lab. Course provided in the assignments (16 marks), and an internal Contact Hours: 2 hours/week vIVA-vocE (l0Tnarks) conducted towards the end of semester. Mode: Lab practice and assignments The external examiration is of 70 marks. The break-up of marks for external examination is based on quality ol lab reports (20 marks), quality of solution(s) for the given problem(s) at the time of examination (written work + execution of program(s)) (30) and vIVA-vocE examinarion (20). Pre-requisites: The students are expected to have a knowledge of components of computer system, operating systems like Windows, Macintosh, Linux. About the Course: This course on Digital Forensics is a developmental laboratory work. It incorporates file syster, recovery related to various operating systems. The objective of the lab course is to equip the students to solve the practical digital forensics issues. Course outcomes: By the end of the lab course student rvill be able to: COI employ - the digital forensics tools for file system analysis. (LOTS: level 3: Apply) CO2. test ethical practices while solving the problems at hand. (HOTS: level 4: Analyze) CO3' select open source tools for imaging various types of media by wiping a target drive. (HOTS: level 5: evaluate) CO4' develop solutions for disk imaging and like problems in different hardware conditions and for various operating systems. (HOTS: level 6: create) Co5' design Lab record for the assignments including aim, hardware and software requirements and solutions to given problems. (HorS: Level 6: create) Co6' demonstrate independent enquiry, use of ethical practices and self-learning to solve unseen problems. (LOTS: level 2: understand) List of experi ments/assignments : 1' Two assignments fbrensi on cally examining Window registry for evidences located in it. 2' Two assignments on wiping atargetdrive and ensure that ii is wiped, imaging various types of media such as hard drives, USB flash drives, optical drives, ZIp disks. 3 Two assignments ' on system restore points and how they are valuable in a forensic investigatio,. 4' Two assignments on open source tool autopsy for timeline analysis, hash filtering and file system analysis. . 5' Two-three assignments on open source tool caine for mobile forensics, Network forensics, data recovery. t' 6' Two-three t assignments on Helix3 for incident response and computer forensics. Note: -t'... :--- r- r The actual experirnents/assignments^ will be designed by the course coordinator. One assignment should b.e designed to be done in groups two of or three students. The assignments must meet the obiective of the .ou.r". and the levels of the given course outcomes. The list assignmenrs of and schedule -;.' prepared by the course coordinator "f'r*UfrSril""),li';;-{'' ? .' at the beginning of the semester. .g*__;.ir:r.,, ,,,' 220 + ro I oa I I 3 6l I c.l co I oa (a c.t : I I I a 0. N a.) c I 0r I C l cn I Orl I I 't I I o r- A a.t s I a\ I trIa I U ao I € I UtI r- I I I I 0)a l' \o I I I U rn f.) aa C.l ca I a { c.l I O ca c.l ra a e) c.l ca c.l I N tr I c-l o.l tu (-t c.l C.l d c'.1 cf) bo I N ca I t-{ ..i c.l x l' =a ta a lE o ln l9 .}.I I _a. loo ? "t ,' lo-E \s\aa\ia\1,\ I ( .;::l o lPr IE I !. l: a I l.,lr E I t.= tr I lr- t c I 1E IE€l= \t-\1a\ga\q1\ I I l= = o l'i =bo f U to c * t; It'la Hc lellEE I*€ l?? i le_E, i ,-lE fi . /1 I (# I - o ) I ; 16 (s S ljlc . El !2 :i\i ?IeE E\i E \EE alo)l'; + lil; E: El*l-. lc d) I ( ol i :. lJ ::9le€ q , I€ eo >'aliol>- ,.1 - {lj1Eli.e-l E i1\1a\1ga\ita\:gE 31, ll3 -1;'l; ,-l = I 3l;3- lollo al J IU I' I' Major Project II General Project Information Course Code: PROJ-CSE4O3 | Course Assessment Methods (Internal evaluation: 30 marks; External Evaluation marks: Course Credits: 6 I 70) Evaluation is done by the internal examiner (project Mode: Self learning unSer the I guide) and external examiner appointed by controller of Examination. guidance of a faculty member. I The criteria for evaluation are given below. l. Review of literature related to problem domain: l5 2- Significance and originality of the solution presented: 15 3. Application of software engineering principres and project management: 15 4. Significance and Scope of results: 20 5. organisation and presentation of major project report: 20 6. Level of Ethics and societal issues covered: l5 About the major project II: Students continue working on their project r,vork and they are required to complete their project work by the end ,l of 8th semester. Students carry out implementation of their respective projects based on the problem identified, f methodology and tools suggested in the synopsis prepared during seventh semester. They prepare the final project reports according to the format provided. At the end of eighth semester, each student is required to present his/her project work in front of internal project guide and external examiner appointed by Controller of Examination. Course outconres: After doing major project students rvill be able to: COl. review information critically for solving complex engineering problems. (HOTS: Level 4: Analyse) CO2- $ton the project according to principles of project management. (HOTS: Level 6: Create) CO3. 'devise original solutions to complex engineering problems using modern engineering tools. (HOTS: Level 6: Create) CO4. ju'stify the outcomes of the project work. (HOTS: Level 5: Evaluate) COs organise and communicate (written and oral) ideas effectively. (HOTS: Level 6: Create) \ CO6- develop soltrtions that meet ethical, societal and legal considerations. (HOTS: Level 6: Create) ",. I f 222 ?o (oo 6l ao a co cn a.l aa cn o\ ra 6 ra aa r+ r--l a F- U I * (\ c\l q) rn (t) (n (-) a? cn aa ca co * c.l a! .a AJ z c.l' ca ca (\l N c-l ca c) \ L c\l cn ca 41 () bo a t =S q) F '. 'i = 0) l- () - 66. q.) f - C) o- l- (g co J q- o :o) co .- o :,, Eg '5(J (r\ 8# tG .Ea 0.,a (.)o o E9 o o-: o\O {yf o(, ()CC J- ch tT. ()9) 6i 9p () 63 a) t-v 0) e\o 'xV 'F '= 02 +-<.o 0) 'd A X() () o.= o- (D P() ea (B- oa0 q) g,3 0() ,(- o-o oo> E 6 C).^ aQ),- v) trL) cn v =() tdC) qr .9 E (JLR iJi (-)'- o_ i- o s oo oa '5q)ii an = IJ] Qt- J V 0.) -C! lr7 a o'^ vv F ,-- a= (-) t< c6 L.) 6 L I :o) =a.) 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