C. Information & Communication Engineering Core
These courses stress fundamental Information & Communication Engineering concepts (a total of 81 credit hours).
Course Number and Name Credit Hours ICE 103 Structured Programming 4 ICE 107 Object Oriented Programming 4 ICE 109 Electrical Circuits 4 ICE 204 Discrete Mathematics 3 ICE 207 Data Structures 4 ICE 213 Electronic Circuits 4 ICE 216 Signals & Systems 3 ICE 217 Digital Electronics 4 ICE 245 Algorithms 4 ICE 275 Operating Systems 3 ICE 302 Computer Communications & Networks 4 ICE 305 Database Systems 4 ICE 310 Electromagnetic Theory 3 ICE 312 Communication Theory 3 ICE 313 Microprocessors & Interfacing 4 ICE 314 Digital Communications 4 ICE 322 Digital Signal Processing 4 ICE 370 Applied Numerical Methods 3 ICE 439 Engineering Ethics 3 ICE 441 Wireless & Mobile Communications 3 ICE 473 Project Management, Entrepreneurship and Industry Interaction 3 ICE 496 Capstone Project 6 Total 81
ICE103: Structured Programming
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: None
Course Contents: Programming Language: Concept of programming language and its classification; Programming logic and flow Chart; Structured Programming using C - Constants, variables and data types, arithmetic and logical operation, loops and decision making, user-defined functions, character and strings, arrays, pointers, structures, file management. The course includes lab work based on theory taught.
Recommended Textbook:
1. The C Programming Language, Brian W. Kernighan, Dennis M. Richie.
2. Programming in ANSI C, E. Balagurusamy, McGraw-Hill Education.
Reference Book:
1. Schaum's Outlines Programming with C, Byron Gottfried, McGraw-Hill.
Course Outcomes (COs): After completion of this course students will be able to
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Apply basic knowledge of C programming language to solve engineering problems.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Apply appropriate decision making and control statements, functions, and arrays to solve engineering problems.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures and brainstorming sessions
|
CO3
|
Apply pointers, strings, structures and unions to solve engineering problems.
|
PO1
|
Cognitive/
Apply
|
Written Exams, Assignment
|
Class lectures and brainstorming sessions
|
CO4
|
Develop and execute realistic C programs in the laboratory.
|
PO1
|
Cognitive/
Apply
|
Lab Reports
|
Conducting lab experiments
|
ICE107: Object Oriented Programming
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit
Hours
|
3
|
1
|
4
|
Contact
Hours
|
3 Hours/Week for 13 weeks+
Final Exam in the 14th week
|
2 hours/Week for 13 Weeks
|
5 Hours/Weeks for 13 Weeks+ Final Exam in the 14th week
|
Prerequisite: ICE103Structured Programming
Course Contents: Object Oriented Concepts: Classes, objects, methods, inheritance, and class methods.OO Programming in JAVA: Java foundation, control flow, abstract classes and packages, exception handling, applets, web-based Java application, multithreading.The course includes lab work based on theory taught.
Recommended Textbook:
1. Introduction to Java Programming, Daniel Liang, 11th edition.
Reference Book:
1. The Complete Reference Java 2, Herbert Schildt, McGraw-Hill Osborne Media.
Course Outcomes (COs): After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Apply basic knowledge of C programming language to solve engineering problems.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO1
|
Apply the basic concepts such as variables, conditional and iterative execution methods to write object-oriented programs.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Implement classes, objects, invoking methods, and exception handling mechanisms to write object-oriented programs.
|
PO1
|
Cognitive/
Apply
|
Written Exams, Assignment
|
Class lectures and brainstorming sessions
|
CO3
|
Apply the principles of inheritance, polymorphism, encapsulation and abstraction to write object-oriented programs.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures and brainstorming sessions
|
CO4
|
Develop and execute real-life object-oriented programs in the laboratory.
|
PO1
|
Cognitive/
Apply
|
Project reports,
Lab experiments,
Lab viva
|
Lab demonstration
|
ICE109: Electrical Circuits
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Pre-requisite: None.
Course Contents:
Basic concept of DC circuits: Fundamental electrical concepts and measuring units, DC voltage, current, resistance and power. Introduction to circuit theory and Ohm's law, Kirchhoff's current and voltage laws. Simple resistive circuits: Series and parallel circuits, voltage and current division, Wye-Delta transformation. Various techniques for solving circuit problems: Mesh and Nodal analysis. Network theorems: Superposition theorem, Source transformation, Thévenin's and Norton's theorems; maximum power transfer theorem. Energy storage elements: Inductors and capacitors, series parallel combination of inductors and capacitors.
Basic concept of AC circuits: sinusoids, phasors, impedance and admittance. Basic circuit laws for AC circuits. Nodal and mesh analysis, network theorems for AC circuits. AC power analysis: instantaneous, average, complex, apparent and reactive power due to sinusoidal excitation, RMS values, power factor calculation and improvement. Three phase circuits: balanced and unbalanced, magnetically coupled circuits and introduction to transformer. Series and parallel resonant circuits and passive filters.The course includes lab work based on theory taught.
Recommended Textbook:
1. Fundamental of Electric Circuits, Charles K Alexander and Mathew N O Sadiku, Tata, McGraw Hill.
Reference Book:
1. Introduction to Electric Circuits, RC. Dorf, John Wiley.
2. Introductory Circuit Analysis, Robert L Boylestad.
3. Introduction to Electrical Circuits, Nilsson, Addison-Wesley.
Course Outcomes: After successfully completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Apply basic circuit laws, analyze techniques, and theorem to solve DC and AC circuits in steady state.
|
PO1
|
Cognitive (Comprehension)
|
Written test,
Assignment
|
Class Lectures
|
CO2
|
Evaluate DC and AC response in RL, RC, and RLC circuits.
|
PO1
|
Cognitive (Comprehension)
|
Written test
|
Class lectures and brainstorming sessions
|
CO3
|
Analyze three phase circuits in phasor domain to compute voltages, currents and powers.
|
PO1
|
Cognitive (Comprehension)
|
Written test
|
Class lectures and brainstorming sessions
|
CO4
|
Build and simulate DC and AC circuits in the laboratory.
|
PO1
|
Cognitive (Comprehension), Psychomotor
|
Lab Viva and lab Test, Lab performance
|
Conducting lab experiments
|
ICE204: Discrete Mathematics
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
0
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: ICE103 Structured Programming
Course Contents: Propositional logic, propositional equivalences, predicates and quantifiers, nested quantifiers, rules of inference, introduction to proofs, mathematical induction, sets, set operations, functions, relations and their properties, the basics of counting, the pigeonhole principle, permutations and combinations, algorithms, the growth functions, complexity of algorithms, the integers and division, primes and greatest common divisor, graphs, graphs terminologies and special types of graphs, representing graphs and graphs isomorphism, introduction to trees.
Recommended Textbook:
1.Discrete Mathematics, Gary Chartrand and Ping Zhang, WAVELEND PRESS INC.
Reference Book:
1. Discrete Mathematics with Applications, Susanna S. Epp.
Course Outcomes (COs): After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Explain propositional logic, predicate logic, and proving theorem with
mathematical reasoning.
|
PO1
|
Cognitive (Comprehension)
|
Written Exam
|
Class Lectures
|
CO2
|
Interpret counting, permutations, and combinations in combinatorial
analysis.
|
PO1
|
Cognitive (Comprehension)
|
Written Exam
|
Class Lectures
|
CO3
|
Comprehend the growth of functions, complexity analysis of algorithms
and integer algorithms for algorithmic thinking.
|
PO1
|
Cognitive (Comprehension)
|
Written Exam
|
Class lectures and brainstorming sessions
|
CO4
|
Apply knowledge of discrete structures to solve realistic engineering problems.
|
PO3
|
Cognitive (Application)
|
Written Exam and/or Assignment
|
Class lectures and brainstorming sessions
|
ICE207: Data Structures
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: ICE107 Object Oriented Programming
Course Contents: Data types, abstract data types and data structures; Efficiency of algorithms; Sequential and linked implementation of lists; Linked list and applications; Stacks and queue and applications; Tree representations and traversals, Binary heaps, binary search tree, AVL tree, Searching; Graphs, DFS and BFS, shortest path and minimum spanning tree; Internal and external sorting. The course includes lab work based on theory taught.
Recommended Textbook:
1.Data Structures and Program Design in C, Kruse, Leung and Tondo, Prentice Hall.
Reference Book:
1.Data Structure and Algorithms in Java, Robert Lafore, Sams.
Course Outcomes (COs):
After completion of this course students will be able to:
COs | CO Statements | POs | Domain | Assessment Strategy | Teaching-Learning Strategy |
CO1 | Understand the basics of data structures and algorithm
|
PO1 | Cognitive (Comprehension+ Analysis)
|
Written Exam | Class Lectures |
CO2 | Develop knowledge of different data structures, arrays, linked lists, binary trees, stack, queues, and graphs etc.
|
PO1 | Cognitive (Analysis+ Synthesis) | Written Exam,
Assignment |
Class lectures and brainstorming sessions |
CO3 | Apply knowledge of data structures to implement algorithm for the creation, insertion, deletion, searching, and sorting. | PO1 | Cognitive (Comprehension+ Analysis) | Written Exam | Class lectures and brainstorming sessions |
CO4 | Choose appropriate data structures as applied to specific problem definition. | PO5 | Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response) |
Lab Experiments, Lab Exam, Laboratory Project, Project Report | Lab Demonstration |
ICE213: Electronic Circuits
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Pre-requisite: ICE109
Course Contents:
Diode: Physical operation, terminal characteristics, load line analysis, circuit analysis, and its applications: rectifier, clipper, clamper.
Op-Amp: Ideal op-amp, inverter, non-inverter, difference amplifier, integrator, differentiator, and weighted summer. Design of different amplifier and instrumentation circuits using op-amps.
BJT: Physical operation, terminal characteristics, operating modes. BJT as amplifier and switch, DC biasing and small signal operations.
MOSFET: Physical operation, terminal characteristics, operating modes, biasing, amplification, small signal model, gain and MOSFET switch.
The course includes lab work based on theory taught.
Recommended Textbook:
1. Microelectronic Circuits, Sedra and Smith, Oxford University Press.
Reference Book:
1. Electronic devices and circuit theory, Robert L Boylestad, Prentice Hall.
2. Microelectronic Circuits and Devices, M. N. Horenstein, Prentice Hall.
3. The Art of Electronics, P. Horowitz and W. Hill, Cambridge University Press.
Course Outcomes:
After successful completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Explain the physical operation and terminal characteristics of diodes, BJTs and MOSFETs.
|
PO1
|
Cognitive (Comprehension)
|
Written Exam
|
Class Lectures
|
CO2
|
Apply fundamental concepts to analyze diode with DC and AC biases.
|
PO1
|
Cognitive (Application)
|
Written Exam
|
Class lectures
|
CO3
|
Apply fundamental concepts to analyze BJT and MOSFET circuits with DC and AC biases.
|
PO1
|
Cognitive (Application)
|
Written Exam,
Assignment
|
Class lectures
|
CO4
|
Apply fundamental concept to analyze simple op-amp circuits.
|
PO1
|
Cognitive (Application)
|
Written Exam
|
Class lecture & Software Simulation
|
CO5
|
Build and simulate electronic circuits; and perform measurements using electronic equipment.
|
PO5
|
Cognitive (Analysis), Psychomotor
|
Designed lab or
open ended lab
and/ or report
|
Lab Demonstration
|
ICE216: Signals & Systems
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: MAT205 Linear Algebra & Complex Variables
Course Contents: Signals and their properties; Basic operations on signals; Different types of signals; Relation between signals and systems; Linear Time-Invariant Systems: Introduction; Convolution: Impulse Response Representation for LTI Systems; Properties of the Impulse Response Representation for LTI Systems; Differential and Difference Equation Representations for LTI Systems; Block Diagram Representations; State Variable Descriptions for LTI Systems. Fourier Representations for Signals (both continuous-time and discrete-time). Application of Fourier analysis in signals. The Laplace Transform; Transform Analysis of Systems; Applications of Laplace Transform.
Recommended Textbook:
1. Signals & Systems, S. Haykin and B. Van Veen, Wiley & Sons.
2. Digital Signal Processing, S. Salivahanan and A. Vallavaraj, Tata McGraw Hill.
Reference Book:
1. Signals & Systems, Alan V. Oppenheim, Prentice Hall.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Explain the characteristics of different properties of signals and systems.
|
PO1
|
Cognitive
(Comprehension)
|
Written exam
|
Class lectures
|
CO2
|
Analyze the response of LTI systems for different excitations.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO3
|
Analyze the stability of LTI system.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
ICE217: Digital Electronics
Credit Hours and Teaching Scheme:
|
Theory |
Laboratory |
Total |
Credit Hours |
3 |
1 |
4 |
Contact Hours |
3 Hours/Week for 13 Weeks + Final Exam in the 14th week |
2 Hours/Week for 13 Weeks |
5 Hours/Week for 13 Weeks + Final Exam in the 14th week |
Pre-requisite: ICE213
Course Contents:
Review of Number systems and codes; Boolean operators (NOT, AND, OR, NAND, NOR, XOR, and XNOR); Boolean algebra and logic circuits: De Morgan's Theorem; Simplification of Boolean functions using Boolean algebra and Karnaugh map. Combinational circuit analysis: Adders, Subtractor, Encoder, Decoder, Multiplexer, Demultiplexer, ROM, PLA. Sequential logic circuits Analysis: Latch, flip flops, counters, Shift Registers, Memory: Classification, capacity calculation, SRAM, DRAM. Different logic families (TTL, ECL, IIL, CMOS) and performance parameters (Fan-out, Noise margin, noise immunity, power dissipation, propagation delay, delay-power product).
The course includes lab work based on theory taught.
Recommended Textbook:
1. Digital Design, M. M. Mano, Prentice Hall.
Reference Book:
1. Digital Systems – Principles and Applications, Ronald J Tocci, Prentice Hall.
2. Digital Logic Design, Dr. Mozammel Huq Azad Khan, UGC.
Course Outcomes: After successful completion of this course students will be able to
COs | CO Statements | POs | Domain | Assessment Strategy | Teaching-Learning Strategy |
|
|||||||||||||
CO1 | Synthesize logic functions using Boolean algebra, Karnaugh map, truth tables and fundamental logic gates.
|
PO1 | Cognitive (Analysis) | Written Exam | Class Lecture |
|
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CO2 | Design combinational and sequential logic circuits based on the given problem statement incorporating different logic elements and blocks. | PO1 | Cognitive (Synthesis) | Written Exam,
Assignment |
Class Lecture |
|
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CO3 | Explain the working principles of semiconductor memories and logic families. | PO1 | Cognitive (Analysis) | Written Exam | Class Lecture |
|
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CO4 | Synthesize, create, and demonstrate digital systems using ICs and simulation tools. | PO5 | Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response) |
Lab Experiments, Lab Exam, Laboratory Project, Project Report | Demonstration and Feedback |
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CO4 |
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ICE245: Algorithms
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: ICE207 Data Structures
Course Contents: Complexity of Algorithms: worst case, average case, and amortized complexity. Algorithm analysis. Algorithm design paradigms. Lists: stacks, queues, implementation, garbage collection. Dictionaries: Hash tables, binary search trees, AVL trees, red-black trees, splay trees, skip-lists, B-trees. Priority queues. Graphs: Shortest path algorithms, minimal spanning tree algorithms, depth-first and breadth-first search. Sorting: Advanced sorting methods and their analysis, lower bound on complexity, order statistics. The course includes lab work based on theory taught.
Recommended Textbook:
1. Data Structures and Program Design in C, Kruse, Leung and Tondo, PrentECE Hall.
Reference Book:
1. Data Structure and Algorithms in Java, Robert Lafore, Sams.
Course Outcomes (COs):
After completion of this course students will be able to
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Apply asymptotic analysis to estimate worst-case running times of algorithm.
|
PO1
|
Cognitive (Comprehension + Analysis)
|
Written Exam
|
Class Lectures
|
CO2
|
Derive and solve recurrences based on performance evaluated by divide-and-conquer paradigm and explain when an algorithmic design situation calls for it.
|
PO1
|
Cognitive (Analysis + Synthesis)
|
Written Exam,
Assignment
|
Class lectures and brainstorming sessions
|
CO3
|
Synthesize dynamic-programming and greedy algorithms.
|
PO1
|
Cognitive (Comprehension + Analysis)
|
Written Exam
|
Class lectures and brainstorming sessions
|
CO4
|
Apply different algorithm to model engineering problems and execute them in the laboratory.
|
PO5
|
Cognitive (Application)
Psychomotor (Origination + Guided & Complex Response)
|
Lab Experiments, Lab Exam, Laboratory Project, Project Report
|
Lab Demonstration
|
ICE275: Operating Systems
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Prerequisite: ICE 245 Algorithms
Course Contents: Basic concepts of operating system; Operating systems hardware interaction; Process and thread management; Inter process communication; Scheduling algorithms for multi-tasking; Mutual exclusion principles and deadlock handling; Memory and I/O management. Storage Management; Implementing file management;
Recommended Textbook:
1. Operating Systems: Design and Implementation, Andrew Tanenbaum and Albert S. Woodhull, Prentice Hall.
Reference Book:
1. Operating System Concepts, Silberschatz, Galvin and Gagne, Wiley.
Course Outcomes (COs):After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Understand and distinguish different components of modern operating system for examining design goals.
|
PO1
|
Cognitive (Knowledge)
|
Written Exam
|
Class Lectures
|
CO2
|
Apply resource management techniques for solving resource constrained problems.
|
PO2
|
Cognitive (Application)
|
Written Exam
|
Class lectures and brainstorming sessions
|
CO3
|
Comprehend and describe different methods of resource management and
communication for operating system performance analysis and illustrate memory organization and I/O management techniques to demonstrate and master the knowledge for realistic problem analysis.
|
PO2
|
Cognitive (Analysis)
|
Written Exam and/or Presentation
|
Class lectures and brainstorming sessions
|
ICE302: Computer Communications & Networks
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE245 Algorithms
Course Contents: Use of computer networks, network hardware and software; Layering, reference models and their comparison. Theoretical basis for data communication, transmission media and impairments, IEEE802.3, switching systems. Design issues, framing, MAC address, error detection and correction, elementary and sliding window protocols, examples of data link layer protocols. Ethernet, data link layer switching. Routing algorithms, congestion control, QoS, internetworking, IPv4 and IPv6 addressing, subnetting, VLSM, NAT, CIDR. Transport service, elements of transport protocols, port address, TCP and UDP. Client/server model, peer to peer model, Email, DNS, HTTP, HTTPS, FTP. The course includes lab work based on theory taught.
Recommended Textbook:
1. Computer Networks, Andrew S. Tanenbaum, Prentice Hall.
Reference Book:
1. Data and Computer Communications, Stallings, MacMillan.
Course Outcomes (COs): After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Characterize network layers and related issues for designing computer networks
|
PO1
|
Cognitive (Comprehension)
|
Written exam
|
Class Lectures
|
CO2
|
Analyze different network algorithm and protocols for effective design of computer networks
|
PO2
|
Cognitive (Analysis)
|
Written exam
|
Class lectures and brainstorming sessions
|
CO3
|
Investigate several network security algorithms and future development trends in network security for Cyber-physical system
|
PO4
|
Cognitive (Analysis)
|
Term paper, Assignment
|
Class lectures and brainstorming sessions
|
CO4
|
Use software tools to design, test and evaluate real life computer network applications.
|
PO5
|
Cognitive (Analysis),
Psychomotor
|
Lab Experiments, Lab Exam, Laboratory Project, Project Report
|
Lab Demonstration
|
ICE305: Database Systems
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks +Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks +Final Exam in the 14th week
|
Prerequisite: ICE275Operating Systems
Course Contents: Concept & Overview of DBMS, Data Models, Database Languages, Database Administrator, Database Users, Three Scheme architecture of DBMS. Basic concepts, Design Issues, Mapping Constraints, Keys, Entity-Relationship Diagram, Weak Entity Sets, Extended E-R features. Structure of relational Databases, Relational Algebra, Relational Calculus, Extended Relational Algebra Operations, Views, Modifications Of the Database. Concept of DDL, DML, DCL. Basic Structure, Set operations, Aggregate Functions, Null Values, Domain Constraints, Referential Integrity Constraints, assertions, views, Nested Sub queries, Database security application development using SQL, Stored procedures and triggers. Functional Dependency, Different anomalies in designing a Database., Normalization using functional dependencies, Decomposition, Boyce-Code Normal Form, 3NF, Normalization using multi-valued dependencies, 4NF, 5NF. File & Record Concept, Placing file records on Disk, Fixed and Variable sized Records, Types of Single-Level Index (primary, secondary, clustering), Multilevel Indexes, Dynamic Multilevel Indexes using B tree and B+ tree.The course includes lab work based on theory taught.
Recommended Textbook:
1. Fundamentals of Database Systems, Elmasri and Navathe, Addison Wesley.
Reference Book:
1.Database System Concepts, Abraham Silberschatz, Henry Korth and S. Sudarshan, McGraw-Hill.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Adopt basic concepts of relational database and construct algebraic expressions.
|
PO1
|
Cognitive (Comprehension)
|
Written exam
|
Class Lectures
|
CO2
|
Analyze different query operations for data manipulation.
|
PO2
|
Cognitive (Analysis)
|
Written exam
|
Class lectures
|
CO3
|
Examine different models and optimization techniques to design efficient relational database system.
|
PO2
|
Cognitive (Analysis),
|
Written exam, Assignment
|
Class lectures and brainstorming sessions
|
CO4
|
Use software tools to build and test real life database.
|
PO5
|
Cognitive (Analysis),
Psychomotor
|
Lab Performance, Open-ended Lab Project, Lab report & Viva
|
Lab Demonstration
|
ICE310: Electromagnetic Theory
Credit Hours and Teaching Scheme:
|
Theory
|
Credit Hours
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Pre-requisite: PHY 209
Course Contents:
Electrostatics: Review of vector analysis & co-ordinate systems (Rectangular, Cylindrical and Spherical), Divergence and curl concepts, Divergence theorem, Stoke’s theorem, Gauss’s theorem and its application, electrostatic potential, Laplace’s and Poisson’s equations, energy of an electrostatics system, conductor and dielectrics.
Magnetostatics: Concept of magnetic fields, Ampere’s law, Biot-Savart’s law, Vector magnetic potential, energy of magnetostatic system, Mechanical forces and torques in electric and magnetic fields.
Maxwell’s equations: their derivations, and continuity of charges, concept of displacement current, Boundary conditions, Time-varying and time-harmonic electromagnetic fields, Wave equations and its solutions, & Poynting’s theorem, Propagation of uniform plane waves in lossy and lossless media.
Recommended Textbook:
1. Fundamental of electromagnetics, David K Cheng, Pearson.
Reference Books:
1. Advanced Engineering Electromagnetics, Constantine A Balanis, Wiley and Sons.
Course Outcomes: After successful completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Apply essential electrostatic theorems in solving various analytical & practical problems
|
PO2
|
Cognitive (Application)
|
Written Exam
Assignments
|
Class Lectures,
Brainstorming Sessions
|
CO2
|
Analyze the concepts of magneto-static fields and the relevant laws along with their applications for different structures.
|
PO2
|
Cognitive (Analysis)
|
Written Exam
|
Class Lectures, Brainstorming sessions
|
CO3
|
Analyze Maxwell’s equations & EM Wave equations to demonstrate the propagation of EM wave along with its basic properties, polarization states and birefringence.
|
PO2
|
Cognitive (Analysis)
|
Written Exam
Assignments
|
Class Lectures
Brainstorming Sessions
|
CO4
|
Comprehend time-harmonic EM fields and the properties of time-harmonic EM waves in different types of media such as lossy and lossless dielectrics, free-space & conductors.
|
PO1
|
Cognitive (Comprehension)
|
Written Exam
Assignments
|
Class Lectures
Brainstorming Sessions
|
ICE312: Communications Theory
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: ICE209 Signal & Systems
Course Contents: Stochastic Processes and Signals: Introduction; Definition of random processes and signals; Autocorrelation and cross correlation of random signals; Transmission of a random signal through a linear filter; Power spectral density functions of random signals; White noise; Stationarity; Ergodicity; Gaussian and Poisson processes; Narrow-band noise; Sine wave plus narrow-band noise. Continuous Wave Modulation and Noise: Introduction, Amplitude modulation and demodulation; frequency modulation and demodulation; Frequency-division multiplexing (FDM); Angle modulation; Noise in CW modulation systems; Noise in linear receivers; Noise in AM receivers; Noise in FM receivers; Phase-locked loop; Nonlinear effects in FM systems; Receiver model; Noise in DSB-SC receivers; Noise in SSB receivers; Noise in AM receivers; Noise in FM receivers. Pulse Modulation: Sampling process; Pulse-amplitude modulation; Time division multiplexing; Pulse-position modulation; Bandwidth-noise tradeoff; The quantization process; Pulse-code modulation; Noise consideration in PCM systems; Digital multiplexers; Linear prediction; Differential PCM; Delta modulation; Adaptive DPCM.
Recommended Textbook:
1. Communications System, Simon Haykin, Wiley.
2. Modern Digital & Analog Communication Systems, Lathi.
Reference Book:
1. Digital Communications, John J. Proakis, McGraw Hill.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Explain various fields of communication by using random process, auto correlation, cross-correlation and PSD.
|
PO1
|
Cognitive (Comprehension)
|
Written test
|
Class Lectures
|
CO2
|
Explain different base band and pass band modulation and demodulation techniques.
|
PO1
|
Cognitive (Comprehension)
|
Written test
|
Class Lectures
and
Group Activity
|
CO3
|
Analyze noise affect in AM and FM modulation and understand PCM.
|
PO2
|
Cognitive (Analysis)
|
Written test or Assignment
|
Class Lectures
|
ICE313: Microprocessors & Interfacing
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Pre-requisite: ICE217
Course Contents:
Microprocessor: Evolution and internal architecture of Intel8086 microprocessor. Addressing Modes. Data Movement Instructions, Arithmetic and Logic Instructions, Program Control Instructions. Intel 8086 Hardware Specifications: Pin outs and pin functions, clock generators, bus buffering and latching, bus timing, minimum and maximum mode operation. Memory Interfacing. Basic I/O Interfacing, Programmable Peripheral Interfaces (8255, 8254, 8279, ADC, DAC controllers). 8259 Programmable Interrupt Controller. DMA controller. Introduction to Pentium and upgraded processors. Introduction to Microcontrollers.
The course includes lab work based on theory taught.
Recommended Textbook:
1. The Inter Microprocessors 8088/8088, 80186, 80286, 80386 and 80486: Architecture, Programming and Interfacing, Barry B. Brey, Prentice-Hall.
Reference Book:
1. Microprocessor and Interfacing, Douglas Hall, McGraw Hill.
Course Outcomes: After successful completion of this course students will be able to
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Explain the architecture and different modes of microprocessor.
|
PO1
|
Cognitive (Knowledge)
|
Written Exam
|
Class Lectures
and
Classwork
|
CO2
|
Explain instruction set, ALP & illustrate the use of emulator.
|
PO1
|
Cognitive (Comprehension),
Psychomotor (Origination + Guided & Complex Response)
|
Written Exam, Practical Assessment
|
Class Lectures and on-spot simulation tasks
|
CO3
|
Analyze the interfacing of memory and I/O devices, interface of microprocessor with PPI.
|
PO2
|
Cognitive (Analysis)
|
Written Exam
|
Class lectures
And Brainstorming session
|
CO4
|
Comprehend DMA controller, Programmable Interrupt Controller and Advanced microprocessor.
|
PO1
|
Cognitive (Comprehension)
|
Written Exam
|
Class lectures
|
CO5
|
Design microcontroller based mini projects.
|
PO3
|
Cognitive (Synthesis),
Psychomotor (Origination + Guided & Complex Response)
|
Project Work
|
Individual or Group Project
|
ICE314: Digital Communications
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: ICE312 Communications Theory
Course Contents: Idea of baseband signal, Nyquist theorem of baseband signal and impulse response of such communication system, raised-cosine pulse in baseband communication, inter-symbol interference, eye diagram, power spectral density of different line codes, on-off binary transmission, the matched filter, properties of matched filter, linear and non-linear distortion channel, design of equalizer, concept of pass-band signal, digital modulation schemes (basic principle, modulator and demodulator, BER and constellation diagram): BFSK, BPSK, MPSK, QPSK and QAM, basic principle of OFDMA, PSD of analog band-pass and digital signals.
Recommended Textbook:
1. Digital and Analog Communication Systems, Leon W. Couch; Pearson Education
2. Digital Modulation Techniques; Fuqin Xiong, Artech House, Boston, London
Reference Book:
1. Communication Systems, Simon Haykin, Wiley.
2. Modern Digital & Analog Communication Systems, Lathi.
Course Outcomes:
After successful completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Discuss the desired properties of line codes and calculate their bandwidth from the generalized PSD of the digital signal.
|
PO1
|
Cognitive (Comprehension+ Analysis)
|
Written Exam
|
Class Lecture
|
CO2
|
Analyze and design optimum receiver to mitigate digital communication impairments.
|
PO1
|
Cognitive (Analysis+ Synthesis)
|
Written Exam
|
Class Lecture
|
CO3
|
Classify and analyze digital modulation techniques and compare their performance based on BER and bandwidth.
|
PO1
|
Cognitive (Comprehension+ Analysis)
|
Written Exam
|
Class Lecture
|
CO4
|
Design digital communication systems that meet specifications and evaluate the performance of the systems within realistic constraints.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
ICE322: Digital Signal Processing
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: ICE209 Signals & Systems
Course Contents: The z-transform: z-transform and ROC, properties of z-transform, analysis of LTI systems using z-transform; Discrete Fourier Transform: DFT and its inverse operation, circular and linear convolution using DFT; Fast Fourier Transform (FFT); IIR filter: Realization of IIR filters, direct form I and II, cascade and parallel, poly-phase decomposition, digital IIR filter design by bilinear transformation; FIR filter: frequency sampling structure, digital FIR filter design using window functions; Finite word length effect in digital filter; Multirate digital signal processing; Concept of adaptive filter.
Recommended Textbook:
1. Digital Signal Processing, John G. Proakis, Prentice Hall.
Reference Book:
1. Digital Signal Processing, Tarun Kumar Rawat, Oxford University Press.
2. Digital Signal Processing a Practical Approach, Emmanuel C. Ifeachor. Barrie W. Jervis; Addision-Wesley.
3. Digital Signal Processing a Computer Based Approach, Sanjit K. Mitra; Tata McGraw-Hill.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Adopt methodologies and properties of DT signals and LTI systems to analyze LTI systems in frequency and z-domain.
|
PO1
|
Cognitive (Application)
|
Written exam
|
Class Lecture
|
CO2
|
Implement different discrete-time LTI system by various structures.
|
PO1
|
Cognitive (Application)
|
Written exam
|
Class Lecture
|
CO3
|
Design filters of given specification under certain constraints.
|
PO3
|
Cognitive (Analysis),
Affective (Responding)
|
Assignment or project report and presentation
|
Class Lecture and demonstration in the lab.
|
CO4
|
Analyze the effect of finite precision in DSP
|
PO1
|
Cognitive (Analysis)
|
Written exam
|
Class lecture
|
CO5
|
Use suitable tools to simulate DT signal and LTI systems and filter design.
|
PO5
|
Cognitive (Analysis),
Psychomotor
|
Designed and/or open-ended lab performance and/or report
|
Class Lecture and demonstration in the lab.
|
ICE370: Applied Numerical Methods
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Pre-requisite: MAT205
Course Contents:
Basic Concept: Approximations and round-off errors, truncation errors.
Root of Equations: Bracketing methods – Bisection methods, Open methods – Newton-Raphson method.
Linear Algebraic Equations: Gauss Elimination – Naive Gauss, Gauss-Jordan. LU-decomposition, Gauss-Seidal method.
Curve Fitting: Least-square regression – Linear regression, polynomial regression. Interpolation – Newton divided-difference interpolating polynomials, Spline interpolation.
Numerical Differentiation and Integration: Newton-cotes integration formulae – Trapezoidal rule, Simpson’s rules, Numerical differentiation – Richardson Extrapolation, Derivatives of unequal spaced data.
Ordinary Differential Equation: Runga-Kutta Methods – Euler’s method.
The course includes lab work based on theory taught.
Recommended Textbook:
1. Advanced Engineering Mathematics, E. Kreyszig, John Wiley.
Reference Book:
1. Numerical Methods for Engineers, Steven C. Chopra and Raymond P. Canale.
2. Engineering Mathematics, Neil, Thomson Learning.
Course Outcomes: After successful completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Report comparative analysis among different algorithms through error analysis of existing numerical techniques.
|
PO1
|
Affective (Valuing)
|
Term Paper
|
Lecture and literature review
|
CO2
|
Formulate methods to represent engineering problems numerically.
|
PO2
|
Cognitive (Synthesis)
|
Assignment
|
Class lecture and Assignments
|
CO3
|
Identify the implications of approximations.
|
PO2
|
Cognitive (Comprehension)
|
Written Exam, Assignment
|
Class lecture and Assignments
|
CO4
|
Design numerical solutions using different techniques and simulation tools to analyze various engineering and practical problems.
|
PO5
|
Cognitive (Application), Psychomotor
|
Lab Experiments, Lab test,
Open-ended Lab Project & Lab Report
|
Lab Experiments, Python Simulation, Projects Supervision
and
E-learning
|
ICE 439: Engineering Ethics
Credit Hours and Teaching Scheme:
|
Theory
|
Credit Hours
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Pre-requisite: ENG102
Course Contents:
Introduction: Engineering philosophy, engineering ethics and professionalism, ethical terminology. Ethical Issues in Engineering: Understanding ethical problems, qualities of engineers, moral codes. Responsibilities of Engineers: Commitment to society, sustainable development, technology and society, risk, safety, and liability. Institutional Ethics: Code of ethics, key concepts, importance, limitations. Rights of Engineers: Workplace rights, whistle blowing. Professionalism for International Engineers: Challenges of globalization.
Recommended Textbook:
1. Engineering Ethics, Charles B. Fleddermann, Pearson.
Reference Book:
1. Introduction to Engineering Ethics (Basic Engineering Series and Tools), Mike Martin and Roland Schinzinger.
Course Outcomes:
After successful completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Adopt the professional codes of conduct in ethical frameworks as an Information and communication Engineer.
|
PO8
|
Affective (Valuing),
Affective
(Responding)
|
Written exam,
Role play
|
Class Lecture,
On-spot tasks
|
CO2
|
Demonstrate and evaluate the compatibility of professional engineering work with the ethical and legal framework related to ICE.
|
PO7
|
Cognitive (Comprehension), Affective (Valuing)
|
Assignment,
Case study
|
Class Lecture,
Role-play
|
CO3
|
Formulate documents, terms and policies related to ICE profession, in accordance with the legal frameworks.
|
PO
10
|
Cognitive (Analysis), Affective (Responding), Psychomotor
|
Term paper
|
Class Lecture
|
CO4
|
Analyze and justify the policies related to ICE, in accordance with the Local and International legislature and its impact on society and culture.
|
PO6
|
Affective (Valuing)
|
Written exam
|
Class lecture, Brainstorming
|
CO5
|
Perform effective oral presentation on terms and policies related to ICE profession, in accordance with the legal frameworks.
|
PO9
|
Affective (Responding)
|
Oral Presentation
|
Group Activity
|
ICE 441: Wireless & Mobile Communications
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE314 Digital Communications
Course contents: Radio propagation characteristics: models for path loss, shadowing and multipath fading, delay spread, coherence bandwidth, coherence time, Doppler Spread, Jake's channel model. Digital modulation for mobile radio: analysis under fading channels, diversity techniques and RAKE demodulator. Introduction to spread spectrum communication. Multiple Access Techniques: FDMA/TDMA/CDMA. The cellular concept: frequency reuse, basic theory of hexagonal cell layout, spectrum efficiency. FDMA/TDMA cellular system; channel allocation schemes. Handover analysis. Cellular CDMA; soft capacity. Erlang capacity comparison of FDM/TDM systems and CDMA. Discussion of GSM standards, signaling and call control, mobility management, location tracing. Wireless data networking, packet error modeling on fading channels, performance analysis of link and transport layer protocols over wireless channels, wireless data in GSM, IS-95, GPRS and EDGE.
Recommended Textbook:
- Wireless Communications & Networking, J.W. Mark and W. Zhauang
Reference Books:
- 1. Modern Wireless Communications, Simon Haykin and Michael Moher
- 2. Wireless Communications: Principles and Practice, Theodore S. Rappaport
Course Outcomes:
After successful completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Calculate the path loss, fading profiles and effects of multi-path propagation in the wireless channel.
|
PO2
|
Cognitive (Analysis)
|
Written Exam
|
Class Lecture
|
CO2
|
Analyze and model receiver and transmitter diversity techniques.
|
PO2
|
Cognitive (Analysis)
|
Written Exam
|
Class Lecture
|
CO3
|
Analyze the effect of wireless path loss and channel fading on digital modulation techniques using computer simulation.
|
PO4
|
Cognitive (Analysis)
|
Report+ Oral Presentation
|
Simulation
|
CO4
|
Design cellular network with given quality of service (QoS) constraints.
|
PO2
|
Cognitive (Application)
|
Written Exam
|
Class Lecture
|
CO5
|
Report differences between cellular generations and propose future development in cellular systems on the basis of a thorough understanding of existing systems and of systems under development.
|
PO
12
|
Affective (Valuing)
|
Term Paper,
Presentation
|
Demonstration, Brainstorming, Group Discussion and Feedback
|
ICE473: Project Management, Entrepreneurship and Industry Interaction
Credit Hours and Teaching Scheme:
|
Theory
|
Credit Hours
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Prerequisite: All 300 level courses
Course Contents:
General principles, process, and tools of project management. Teamwork and communication. Strategic issues in project management, cost analysis, risk and crisis management. Practical consideration in implementing project management in the industry. Project monitoring and evaluation. Project documentation and reporting. Role of entrepreneurship in the society, personality characteristics of successful entrepreneurs, sources of ideas for new ventures, sources of funding, development of the business plan.
Recommended Textbook:
1. A Guide to the Project Management Body of Knowledge, Project Management Institute.
Reference Book:
1. An introduction to Project Management, Kathy Schwalbe.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Explain the principles, process, and tools of project management.
|
PO
11
|
Cognitive (Comprehension+ Synthesis)
|
Written Exam
|
Class Lecture
|
CO2
|
Understand budgeting and risk management and demonstrate the ethical principles and responsibilities and other practical considerations in project management.
|
PO8
|
Affective (Characterization by a value or value complex)
|
Project Report, Group Discussion
|
Class Lecture,
Group discussion
|
CO3
|
Conduct project meetings, report progress, prepare documents.
|
PO
10
|
Cognitive (Comprehension+ Analysis)
|
Project Report
|
Class Lecture,
On-spot Classroom tasks
|
CO4
|
Value the importance of entrepreneurship in the society
|
PO6
|
Cognitive (Application)
|
Project Report
|
Class Lecture,
Brainstorming
|
CO5
|
Describe and demonstrate the basic requirements to become an entrepreneur with ability to evaluate the sustainability and the impact of professional engineering work in societal and environmental contexts.
|
PO7
|
Cognitive (Comprehension+ Application)
|
Written Exam,
Assignment
|
Class Lecture
|
CO6
|
Communicate effectively sources of ideas for new ventures, sources of funding, and development of the business plan.
|
PO9
|
Affective (Characterization by a value or value complex)
|
Oral Presentation
|
Group Discussion & Role-Play
|
ICE496: Capstone Project
Credit Hours: 6
Prerequisite: Students must complete at least 100 credits hours.
Course Contents:
The Capstone project provides opportunity to the students to apply and integrate the knowledge and skills gathered through the earlier course works. Students will take the primary responsibility to identify, organize, plan and execute different tasks associated with the designing of a practical Information and Communication Engineering System or Component. Students will work on the projects in teams.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Identify an appropriate topic that can be simulated and verified
|
PO
12
|
Affective (Characterization),
Psychomotor
|
Preliminary report based on the literature research mentioning identified problem (At the end of the first semester.)
|
Literature Review,
Brainstorming
|
CO2
|
Critically review and analyze the problem to identify theoretical possible solutions
|
PO2
|
Cognitive (Analysis)
|
Preliminary report based on the literature research mentioning possible theoretical solutions to the identified problem (At the end of the first semester.)
|
Literature Review,
Brainstorming
|
CO3
|
Investigate the feasibility of the different solutions to select the most suitable one
|
PO4
|
Cognitive (Synthesis),
Psychomotor
|
Presentation and/or preliminary report to deliver different possible identified solutions and justify the most suitable solution for the identified problem (At the end of the first semester.)
|
Literature Review,
Group discussion & feedback based on the available solutions of the similar problems
|
CO4
|
Plan a project and perform different tasks of project management
|
PO
11
|
Cognitive (Application),
Psychomotor
|
Presentation and/or written report to deliver viable project planning including financial aspect to implement the solution at the end of first semester
(Each of the members should demonstrate skill of individual and group collaboration to convince the evaluator about the success of the project.)
|
Supervision of project-works
|
CO5
|
Design a solution (algorithm and flow chart) that meets the specifications
|
PO3
|
Cognitive (Evaluation), Affective (Responding)
|
Design the project in pen and paper to meet the specification and present the design in the group presentation at the end of the second semester.
|
Supervision of
The Project Design
|
CO6
|
Incorporate the use of modern engineering tools (programming language) in the design, and verification processes
|
PO5
|
Cognitive (Evaluation),
Psychomotor
|
Use suitable simulating tool to simulate the design and provide a group presentation at the end of the second semester.
|
Supervision of the design, and the verification processes
|
CO7
|
Work effectively in a team
|
PO9
|
Affective (Organization), Psychomotor
|
Peer level review (end of the second semester.)
|
Supervision of the teamwork
|
CO8
|
Understand ethical and professional responsibilities in the practice of information and communications engineering related to the project.
|
PO8
|
Affective (Valuing)
|
Peer level group discussion.
(Identification and discussion on values related to the ethical issues of the project, these should be mentioned in the final thesis/report.)
|
Necessary Supervision
|
CO9
|
Asses societal, health, safety, legal and cultural issues related to the project
|
PO6
|
Affective (Valuing)
|
Peer level group discussion.
(Identification and discussion on societal, health, safety, legal and cultural issues related to the project, these should be mentioned in the final thesis/report.)
|
Necessary Supervision & Feedback
|
CO
10
|
Demonstrate the understanding of the impact of the project on environment and sustainability
|
PO7
|
Cognitive (Comprehension), Affective (responding)
|
Final presentation
|
Necessary Supervision & Feedback
|
CO
11
|
Write professional technical documents related to the project and orally present project results
|
PO
10
|
Affective (Responding)Psychomotor
|
Final report and final presentation
|
Supervision of the Project Outcomes
|
D. Technical Electives
These upper-class elective courses stress the rigorous analysis and design principles practiced in the sub-disciplines of Information & Communication Engineering. A student has to take total four courses, taking at least one course from each group.
Group A (Information Technology)
Course Number & Name Credit Hours ICE 453 Computer and Cyber Security 3 ICE 469 Computer Architecture 3 ICE 471 Network Programming 4 ICE 472 Speech & Image Processing 4 ICE 474 Computer Graphics & Visualizations 3 ICE 476 Artificial Intelligence 3 ICE 478 Machine Learning 3 ICE 479 Robotic Engineering 3 ICE 483 Data Science 3 ICE 484 Cyber Ethics and Legal Framework 3 ICE 485 Internet of Things 3 Group B (Communication) Course Number & Name Credit Hours ICE 401 VLSI Circuit Design 4 ICE 434 Microwave Engineering 4 ICE 442 Optical Fiber Communications 4 ICE 446 Satellite Communications 3 ICE 448 Information Theory and Coding 3 ICE 452 Multimedia Communications 3 ------------------------------------------------------------------------------
Group A (Information Technology)
ICE453: Computer and Cyber Security
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: ICE 302 Computer Communications and Networks
Course Contents: Fundamental concepts of computer security. Well known attack types and vulnerabilities. Social engineering attacks. Cryptography and classical cryptosystems. Authentication protocols and public key infrastructure. IPSec, VPNs, E-Commerce issues. Security evaluation and auditing of networked system. Intrusion Detection, Prevention, Response, Containment (Digital forensic evidence) and Disaster Recovery. Network defense tools: Firewalls, VPNs, Intrusion Detection, and filters.
Recommended Textbook:
1. Computer Networks, Andrew S. Tanebaum, Pearson Education.
2. Data Communications and Network Security, Houston H. Carr and Charles Snyder, Mc Graw Hill.
Reference Book:
1. Cryptography and Network Security, William Stallings, Prentice Hall.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Interpret the basic concepts related to computer security, and identify security vulnerabilities of networked system.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Interpret and apply cryptographic algorithms for authentication, cryptanalysis and steganography.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO3
|
Interpret, use and analyze the security threats on networked systems, assess the existing state of security and deduce realistic security policies.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO4
|
Examine and justify realistic prevention and disaster recovery; demonstrate this knowledge and write report justifying the actions and policies.
|
PO4
|
Cognitive (Analysis)
|
Term paper, Assignment
|
Class lectures and brainstorming sessions
|
ICE469: Computer Architecture
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
0
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE 275 Operating System.
Course Contents: Computer arithmetic: ALU, Integer representation and arithmetic and floating-point representation, computer memory system: main memory, cache memory, Instruction sets: Machine instruction, operands, and operations, instruction sets: addressing modes and addressing format. RISC instruction set architecture, CPU design: hardwire control and microprogrammed control, Input/Output: external devices, I/O modules, Programmed I/O, Interrupt driven and DMA, pipelining, multiprocessors.
Recommended Textbook:
1. Computer Organization & Design, David A. Patterson and John L. Hennessy, Morgan Kaufmann.
Reference Book:
1.Structured Computer Organization, Andrew Tanenbaum, Prentice Hall
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Understand the architectural concept of digital computers.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Understand, determine and analyze performance of processor, memory, and I/O subsystems.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO3
|
Understand, implement, examine, and justify instruction set design for performance improvement, execute and demonstrate this knowledge, and write report for problem solving.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
CO4
|
Implement, examine, and justify processor and control unit design, execute and demonstrate this knowledge and write report to synthesize functional units of digital computers.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
ICE471: Network Programming
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
2 hours/week for 13 weeks
|
5 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE 302Computer Communications & Networks.
Course Contents: Introduction to networking and internet protocols, Complete coverage of the Java networking and I/O APIs, Details of multithreading and exception handling, Byte, Character, Object and Message streams, IP, TCP, UDP, Multicast, HTTP, DNS, RMI, CORBA and Servlets, Fingers, DNS, HTTP, and ping, Clients and Servers, Multiprotocol chat systems and whiteboards
Recommended Textbook:
1. Java Network Programming, Elliotte Rusty Harold, O’REILLY Media.
Reference Book:
1. An Introduction to Network Programming with Java, Jan Graba.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Analyze the requirements of a networked programming environment and identify the issues to be solved.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO2
|
Create conceptual solutions to those issues and implement a programming solution.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
CO3
|
Understand the key protocols that support the internet and the use of TCP / UDP sockets.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO4
|
Apply advanced programming techniques such as broadcasting and multicasting.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
ICE472: Speech & Image Processing
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
|
5 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE 322Digital Signal Processing.
Course Contents: Speech Processing: Human speech communication - Speech production/ perception/linguistics. Time-Varying Signal Analysis: Short-time Fourier transform, Gabor transform, spectrograms. Quasi-Stationary Analysis: Cepstrum, linear-prediction (AR) and ARMA models. Feature Space Formulation: Mixture-Gaussian model, Fischer discriminant measure, feature transformations - linear and nonlinear. Maximum likelihood classification and pattern matching through dynamic programming; Hidden Markov modeling of speech.
Image Processing: Why Image Processing? Digital image fundamentals, Image transform, Image enhancement, Image restoration, Image compression, Image segmentation, Representation and description, Recognition and interpretation. The course includes lab work based on theory taught.
Recommended Textbook:
1. Digital Image Processing, Rafael C. Gonzalez, Richard E, Prentice Hall
2. Circuits, Signals and Speech and Image Processing, Richard C. Dorf, CRC Press
Reference Book:
1.Digital Image Processing Algorithms and Applications, Ioannis Pitas, Wiley-Inter-science.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Understand the digital image and speech fundamentals and apply different image and speech enhancement techniques for improving the quality of the image and speech.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Understand the basic color model and apply them for smoothing, sharpening, and/ or segmentation color image. Understand the basic speech signal and cepstrum coefficient, and apply linear-predictive coding for feature extraction.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures and brainstorming sessions
|
CO3
|
Understand, choose, examine, and devaluate different image and speech processing techniques; perform and demonstrate these skills and write report for better representation and / or better storage of the image.
|
PO1
|
Cognitive/
Apply
|
Written Exams, Assignment
|
Class lectures and brainstorming sessions
|
CO4
|
Choose, compare, and justify appropriate object detection and techniques for understand complex real-life speech and images; perform and demonstrate these skills and write report for realistic problem solving.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
ICE474: Computer Graphics & Visualization
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE 245 Algorithms.
Course Contents: Scientific Visualization: An Engineering Perspective; Overview of Computer Graphics for Visualization; Data Analysis for Visualization; Scalar Visualization Techniques; A Unified framework for flow Visualization; Continuous Volume Display; Animation and Examination of Behavior Over Time; System Aspects of Visualization Application, Visualization Geometry and Algorithm, Surface Extraction, Solid Representation Techniques, CSG, B-Rep, Octree, Modeling Complexity, Application of Visualization to design and Analysis, Research Issues using Solid Modeling for Visualization.
Recommended Textbook:
1. Graphics and Visualization: Principles & Algorithms, Georgios Papaioannou, Nicholas M. Patrikalakis, Nikolaos Platis, and Theoharis, CRC Press.
Reference Book:
1. Data Visualization, Principle and Practice, Alexandru Telea.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Understand computer graphics system and implement different graphics primitives for drawing a graphics scene.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Understand, apply, and examine different techniques of clipping, two dimensional transformations, and three-dimensional transformations and viewing for manipulating complex graphics scenario using OpenGL; perform and demonstrate these skills and write report for realistic problem solving.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO3
|
Understand and apply the basics of color perception and different color models used in computer graphics.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO4
|
Apply and Analyze different modeling, rendering, shading and animation techniques; develop and justify program by integrating these techniques to create 3D objects using OpenGL; perform and demonstrate this knowledge and write report for realistic problem solving.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
ICE476: Artificial Intelligence
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
0
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE 245Algorithms.
Course Contents: Intelligent agents: a discussion on what Artificial Intelligence is about and different types of AI agents Search: Searching as a problem-solving technique: a review of “conventional" searching methods including breadth-first, depth-first, bi-directional and best-first search. Heuristic functions and their effect on performance of search algorithms. Introduction to genetic algorithms. Knowledge Representation and Reasoning: Propositional Logic, First-Order Logic, Reasoning and Logical Inference. First-order logic as a basis for building intelligent agents capable of acting and reacting in a complex environment. Knowledge engineering: building knowledge bases and automated theorem proves. Production systems as an example of logical problem solving, Uncertain Knowledge: Bayes' Rule, Probabilistic Reasoning, Bayes Nets. Planning agents: representation of states, goals and actions. Learning: Supervised Learning, Unsupervised Learning, Reinforcement Learning.
Decision trees and the ID3 algorithm Applications of AI: Semantic Web. Philosophy of AI.
Recommended Textbook:
1. Computational Intelligence: An Introduction, Andries P. Engelbrecht, John Wiley
Reference Book:
1. Fuzzy Expert Systems and Fuzzy Reasoning, William Siler, James J. Buckley, John Wiley.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Interpret and apply the key components and classical algorithms of artificial intelligence for realistic problem solving.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Apply and examine game theoretical concepts and practices for solving non-conventional real-life situations.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
CO3
|
Apply and examine Genetic Algorithms and Artificial Neural Networks (ANN) for solving complex search and optimization problems
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO4
|
Use statistical methods and machine learning for solving complex AI related problems; perform and demonstrate skills and write report on complex AI related problems.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
ICE478: Machine Learning
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
0
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE 476Artificial Intelligence
Course Contents: Introduction to machine learning, Supervised learning setup, Linear prediction: Regression, Classification: Decision tree, Logistic regression, Probabilistic modelling: Bayesian method, Naive bias, Unsupervised learning: Clustering, Apriori, Principal component analysis, Clustering: Partitioning, Hierarchical, Artificial Neural Networks: perceptron, MLPs, back propagation, introduction to Deep learning, Support vector machines, Reinforcement learning and control.
Recommended Textbook:
1. Understanding Machine Learning: From theory to algorithms, Shai Shalev and Shai Ben-David, Cambridge University Press.
Reference Book:
1. Deep learning, Ian Goodfellow and Yoshua Bengio and Aaron Courville, MIT Press Book.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Formulate and use machine learning problems corresponding to different applications.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Understand and use a range of machine learning algorithms, both supervised and unsupervised along with their strengths and weakness.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO3
|
Understand, use, and determine appropriate machine learning methods / algorithms suitable for different types of learning problems, i.e., know about their most important weaknesses advantages.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
CO4
|
Examine and analyze appropriate software tools to implement algorithms in a range of real-world applications; implement and write report to represent the analysis results.
|
PO4
|
Cognitive (Analysis)
|
Term paper, Assignment
|
Class lectures and brainstorming sessions
|
ICE479: Robotic Engineering
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE 476Artificial Intelligence.
Course Contents: This course provides an overview of robot mechanisms, dynamics, and intelligent controls. Topics include planar and spatial kinematics, and motion planning; mechanism design for manipulators and mobile robots, multi-rigid-body dynamics, 3D graphic simulation; control design, actuators, and sensors; wireless networking, task modeling, human-machine interface, and embedded software. Weekly laboratories provide experience with servo drives, real-time control, and embedded software. The course includes lab work based on theory taught.
Recommended Textbook:
1. Handbook of Industrial Robotics, Shimon Y. Nof, 2nd Edition, John Wiley.
Reference Book:
1. An Introduction to AI Robotics, Robin R. Murphy, MIT Press.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Learn fundamental mathematical and computational models; solve and analyze kinematic problems involving robot manipulators and mobile robots.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Familiarize with robot sensors, sensor processing algorithms and navigation planning approaches; use them and examine their engineering trade-offs.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO3
|
Understand robot actuator movements and controlling managements; and explore the computational challenges within robotic tasks.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO4
|
Use, examine, and justify control programming strategies of industrial systems; demonstrate this knowledge and write report to develop simple mobile robot.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
ICE483: Data Science
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
0
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE476Artificial Intelligence
Course Contents: Introduction to data mining, data mining goals, stages of the data mining process, data mining techniques, knowledge representation methods, data preprocessing: data cleaning, data transformation, data reduction, data mining knowledge representation, representing input data and output knowledge, association rules, correlation analysis, classification rules, correlation analysis, classification, basic learning/mining tasks, decision trees, covering rules, prediction, prediction task, statistical classification, distance-based methods, linear models, clustering system, hierarchical methods, conceptual clustering, advanced techniques, data mining software and applications, text mining, web mining.
Recommended Textbook:
1. Data Science from Scratch: First Principles with Python, Joel Grus, O’Reilly Media.
Reference Book:
1. Data Science (MIT Press Essential Knowledge series), John D. Kelleher, Brendan Tierney
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Process raw input data to provide suitable input for a range of data mining algorithms.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO2
|
Discover and measure interesting patterns from different kinds of databases.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO3
|
Evaluate and select appropriate data-mining algorithms and apply, and interpret and report the output appropriately.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
CO4
|
Choose and justify software tools; perform and demonstrate skills, and write report to design and implement data-mining application using sample, realistic data sets.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
ICE484: Cyber Ethics and Legal Framework
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
0
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: None.
Course Contents: Computer and information ethics at Stanford Encyclopedia of Philosophy. ACM code of ethics and professional conduct. Software engineering code of ethics and professional practice. Data protection act, computer misuse act, impact of the computer misuse act. Copyright, designs and patents act, freedom of information act, security of internet communications. Bangladesh: Information and communication technology act of 2006 and its amendment in 2013. Bangladesh: copyright act of 2000. Bangladesh: telecommunication regulatory act of 2001. Pornography: pornography act of 2012.
Recommended Textbook:
1. Cyberethics, Spinello, Jones and Bartlett learning
Reference Book:
1. Investigating Cyber Law and Cyber Ethics: Issues, Impacts and Practices, Alfreada Dudley, James Bramen, and Giovanni Vincenti.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Interpret and comply with the professional codes of conduct and ethical frameworks as an ICT professional.
|
PO8
|
Affective (Valuing),
Affective
(Responding)
|
Written exam,
Role play
|
Class Lecture,
On-spot tasks
|
CO2
|
Describe and comply with the legislation related to Information and Communication Engineering.
|
PO8
|
Affective (Valuing),
Affective
(Responding)
|
Written exam,
Role play
|
Class Lecture,
On-spot tasks
|
CO3
|
Interpret, apply, and justify the standard ethical frameworks within computing.
|
PO8
|
Affective (Valuing),
Affective
(Responding)
|
Written exam,
Role play
|
Class Lecture,
On-spot tasks
|
CO4
|
Analyze, evaluate, and formulate documents, terms and policies related to computing profession, in accordance with legal frameworks; demonstrate this knowledge and write report justifying the actions and policies.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
ICE485: Internet of Things
Credit Hours and Teaching Scheme
|
Theory
|
LABORATORY
|
TOTAL
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
0
|
3 Hours/Week for 13 Weeks+
Final Exam in the 14th week
|
Prerequisite: ICE 302 Computer Communications & Networks.
Course Contents: Introduction to IoT, basics of networking, communication protocols, sensor networks: machine-to-machine communications, interoperability in IoT: integration of sensor and actuators, implementation of IoT with programmable devices, software defined networking (SDN) for IoT: data handling and analytics, cloud computing, Fog computing: smart cities and smart homes, connected vehicles: smart grid, industrial IoT: agriculture, healthcare, activity monitoring, and related case studies.
Recommended Textbook:
1. Precision: Principles, Practices and Solutions for the Internet of Things, Timothy Chou, lulu.com
Reference Book:
1. Smart Internet of Things Projects, Agus Kurniawan
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Understand the building blocks of IoTs and their characteristics with real-world applications.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Understand, apply, and examine different architectures for different levels of complex IoT applications.
|
PO4
|
Cognitive (Analysis)
|
Term paper, Assignment
|
Class lectures and brainstorming sessions
|
CO3
|
Examine IoT data analytics and justify various tools for IoT; perform and demonstrate skills and write report on realistic data analytics.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO4
|
Choose and justify software and hardware tools, develop source code for various IoT domains, perform and demonstrate skills and write report on realistic IoT development.
|
PO5
|
Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response)
|
Lab Experiments, Lab Exam, Laboratory Project, Project Report
|
Lab Demonstration
|
Group B (Communication)
ICE401: VLSI Circuit Design
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Pre-requisite: ICE313
Course Contents:
Review of semiconductor physics pertinent to VLSI design, NMOS and PMOS transistors, transistors as switches, CMOS inverters, NAND and NOR gates, cross section of an inverter, inverter mask sets, fabrication steps, simplified design rules, stick diagram, layout, CMOS circuit design, gate level and transmission gate based multiplexers, multiplexer based design, CMOS latches and flip-flops as basic building blocks of sequential circuit, standard cell layout, area estimation from stick diagram and layout, VLSI design flow, logic design, circuit design, physical design, structured design approach, design partitioning, hierarchical design, Verilog code at behavioral and structural level, gate level and transistor level netlist, CMOS transistor theory, cut-off, linear, saturation, non-ideal transistor behavior, mobility degradation, velocity saturation, channel length modulation, body effect on threshold voltage, subthreshold, gate and junction leakage, effect of process and environmental variation, pass transistor, dc and transient response, logic levels and noise margins, RC delay models, delay estimation, logical effort and parasitic delay, delay in multistage logic networks, dynamic and static power, activity factor, low power circuit design, pseudo-NMOS, dynamic and domino logic family, adders, six transistor static and four transistor dynamic memory cell, sense amplifier.
The course includes lab work based on theory taught.
Recommended Textbook:
1. CMOS VLSI design: A Circuit and System Perspective by Neil H. E. Weste, David Harris & Ayan Banerjee, Pearson Education, 4th Edition.
Reference Book:
1. Basic VLSI Design (3rd Edition) by Douglas A. Pucknell and Kamran Eshragian, Prentice Hall.
Course Outcomes: After successful completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Draw the Schematic diagram, stick diagram and layout of basic combinational and sequential circuit, estimate the area from stick diagram and calculate the same from layout satisfying design rules.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Design for equal rise and fall time, simulate and obtain voltage and current waveforms, measure delays as well as get transfer characteristics and parametric analysis for power, delays etc.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
CO3
|
Draw the Schematic diagram using modern tools such as dsch, generate the Verilog code, compile in micro-wind to generate the layout.
|
PO5
|
Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response)
|
Lab Experiments, Lab Exam, Laboratory Project, Project Report
|
Lab Demonstration
|
CO4
|
Design a basic building block such as a 1-bit full adder and use the block for implementing a structured, hierarchical design such as a 4-bit binary parallel adder.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab DemonstrationSimulation and Feedback
|
CO5
|
Design low power circuits and memory elements.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
ICE434: Microwave Engineering
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks +Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks +Final Exam in the 14th week
|
Prerequisite: ICE310 Electromagnetic Theory
Course Contents: Review of Maxwell's equations and transmission line theory, circuit models. Microwave network analysis: Scattering matrices and multiport analysis techniques. Impedance Matching: Design of matching networks including lumped elements, stubs and transmission line sections, circuit tuning. Passive Components: Theory of operation, practical design and implementation of power dividers, directional couplers and hybrids, resonators as well as system applications of these devices. Noise and distortion in RF Systems: Theory of noise in RF circuits, distortion of RF signals, dynamic range limitations, effects on channel capacity. Active Circuits: Theory of operation, practical design and implementation of amplifiers for low-noise or power applications, detectors, mixers; Overview of microwave tubes and solid state devices. Non-reciprocal Devices: Theory of operation and implementation of isolators, circulators and variable attenuators and phase shifters. Microwave Systems: Receiver and system performance calculations, RF link analysis, end-to-end microwave system ("the physical channel") analysis. Applications: Antennas, propagation and microwave filter synthesis. The course includes lab work based on theory taught.
Recommended Textbook:
1. Foundations for Microwave Engineering, R. E. Collin. McGraw Hill.
Reference Book:
1. Fields and Waves in Communication Electronics, S. Ramo, J.R. Whinnery, Wiley.
Course Outcomes (COs):
After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Understand the propagation mechanism of RF and microwave signal through free space and guided medium.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Analyze the performance of transmission lines and determine the parameters of transmission lines.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO3
|
Solve transmission line problems and impedance matching problems using Smith chart.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO4
|
Design microwave filter, microwave links and understand the basics about different antenna for practical implementation.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
ICE 442: Optical Fiber Communications
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
1
|
4
|
Contact Hours
|
3 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
2 Hours/Week for 13 Weeks
|
5 Hours/Week for 13 Weeks + Final Exam in the 14th week
|
Pre-requisite: ICE310, ICE314
Course Contents:
Overview of fiber optic communication systems: evolution, nature of light, advantages and applications, Characteristics of optical transmission media. Optical fibers: propagation and transmission characteristics, loss and dispersion mechanisms. Nonlinear Characteristics.
Optical sources: principles of operation, modulation characteristics and driver circuits.
Photo detectors: principles of operation, circuits and performance.
Fiber optic connectors, couplers, multiplexers and splices, wavelength converters, routers, optical amplifiers, post detection amplifiers, Fiber optic communication systems and link budget using direct detection. Coherent and WDM systems.
This course includes lab works based on theory taught.
Recommended Textbook:
1. Optical Fiber Communications: Principle and Practice, John M. Senior, Prentice Hall.
Reference Books:
1. Gerd Keiser, Optical Fiber Communications, third edition, McGraw Hill, 2000
2. Fiber-Optic Communication Systems, 4th Ed., G. P. Agrawal, John Wiley & Sons, 2010.
3. Understanding Optical Fiber Communications, A.J. Rogers, Artech House Publishers.
Course Outcomes:
After successfully completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Understand the fundamentals of the operation and transmission characteristics of optical fiber.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Analyze and calculate power coupling losses due to connectors, splices, source output pattern and fiber numerical aperture.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO3
|
Understand the structure and operational properties of optical source and detectors.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO4
|
Comprehend the knowledge of essential elements of optical fiber links and design optical fiber link and power budgeting.
|
PO3
|
Cognitive (Application+ Evaluation)
|
Laboratory Project+ Project Report
|
Lab Demonstration, Simulation and Feedback
|
CO5
|
Simulate and analyze propagation and transmission characteristics of optical fiber and establish a practical link.
|
PO5
|
Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response)
|
Lab Experiments, Lab Exam, Laboratory Project, Project Report
|
Lab Demonstration
|
ICE446: Satellite Communication
Credit Hours and Teaching Scheme:
|
Theory
|
Laboratory
|
Total
|
Credit Hours
|
3
|
0
|
3
|
Contact Hours
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
|
3 Hours/Week for 13 Weeks +
Final Exam in the 14th week
|
Prerequisite: ICE 441 Wireless and Mobile Communications
Course Contents: Orbits: Kepler's laws, Newton's law, orbital parameters, inclined orbits, geostationary orbit. space environment: mechanical effects, atmospheric effects (radiation, ionospheric effects, rain attenuation), polarization, propagation. link analysis: equivalent isotropic radiated power, received signal power, noise power at the receiver input, the uplink, the downlink, station-to-station link. Satellite access: FDMA, TDMA, CDMA, fixed and on-demand assignment, random access, inter-satellite links. Earth stations: standards, antennas, radio frequency subsystem, communication subsystem, network interface subsystem. the payload: transparent repeaters, multi-beam satellite repeater, regenerative repeater, antenna characteristics. The platform: the propulsion system, the power supply (solar power satellites), telemetry, tracking and command, thermal control. Satellite installation: installation in orbit, launch vehicles, reliability issues, cost issues and network.
Recommended Textbook:
1. Satellite Communications, D. Roddy, McGraw-Hill Professional.
Reference Book:
1. Satellite Communication System, M. Richharia, McGraw-Hill.
Course Outcomes (COs): After completion of this course students will be able to:
COs
|
CO Statements
|
POs
|
Domain
|
Assessment Strategy
|
Teaching-Learning Strategy
|
CO1
|
Understand the basics of satellite communications with their applications.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO2
|
Explain the working principles of orbits, satellite access, satellite installation, satellite payload, satellite services and link analysis of GEO, MEO and LEO.
|
PO1
|
Cognitive/
Apply
|
Written Exams
|
Class lectures
|
CO3
|
Evaluate up-link and down link power budget.
|
PO2
|
Cognitive (Analysis)
|
Written exam and/or assignment
|
Class lectures and
Assignments
|
CO4
|
Investigate and compare different types of satellite system with other communication systems.
|
PO4
|
Cognitive (Analysis)
|
Term paper, Assignment
|
Class lectures and brainstorming sessions
|