Semester Final Routine, Fall 2018
Acquire a good degree accepted all over the world
The principal aim of the Sylhet International University is to provide high quality education at undergraduate and postgraduate levels relevant to the needs of a dynamic society. The courses and curricula are so designed as to enable a student to enter into the world of work or pursue higher academic and professional goals with a sound academic foundation. The medium of instructions in Sylhet International University is English. The academic goal of the university is not just to make the students pass the examination and get the degree but to equip them with the means to become productive members of the community and continue the practice of lifelong learning.
The mission of the CSE Department is to provide quality education for those students who are able to compete nationally and internationally, able to produce creative and effective solutions to the national needs, conscious to the universal moral values, adherent to the professional ethical codes and to generate and disseminate knowledge and technological essentials to the local and global needs in the fields of Computer Science and Engineering.
The vision of the CSE Department is to become a nationally and internationally leading institution of higher learning, building upon the culture and the values of universal science and a center of education and research that creates knowledge and technologies which form the groundwork in shaping the future of the Computer Science and Engineering fields.
Sylhet International University ICT Fest 2019 The Sub-Committees for SIU ICT FEST 2019 has been Formed as Follow-
অত্র বিশ্ববিদ্যালয়ের সি.এস.ই বিভাগের ২-১ সেমিস্টার হইতে ৪-২ সেমিস্টার এর সকল শিক্ষার্থীর অবগতির জন্য জানানো যাইতেছে যে, আজ ২৭/১১/২০১৮ ইং রোজ মঙ্গলবার, আজ সি.এস.ই বিভাগের...
Welcome to the Computer Science and Engineering Department of Sylhet International University. You are here because you dream of a future with a strong foundation in knowledge and skill in the world of technology. We, the teachers of this department, nurture a congenial atmosphere for self-development. With utmost sincerity everyone here strives for the continual development of self and society. Our students enjoy what they learn and get hands on experience of all possible applications of the knowledge they gather. Thus, knowledge and practical application are developed hand in hand.
The department offers a healthy atmosphere of competitiveness in both skill development and academic research through initiatives of the SIU Computer Society, Center for Research, Testing & Consultancy (CRTC), Programmer’s Den etc. The academic atmosphere is enhanced by.......
Registration x 8 Semester | Semester Fees x 8 Semester | Total Fees |
14,000x 8 = 1,12,000 BDT | 16,000 x 8 = 1,28,000 BDT | 2,40,000 BDT |
Waiver | Rate | Applicable For | Registration x 8 Semester | Tuition Fee x 8 Semester | Total Fees |
Childreen of Freedom Fighters | 100% | All (limited) | 14,000x 8 = 1,12,000 BDT | 0 x 8 = 0 BDT | 1,12,000 BDT |
GPA 5.0 in both SSC and HSC | 100% | All (limited) | 14,000x 8 = 1,12,000 BDT | 0 x 8 = 0 BDT | 1,12,000 BDT |
Sum of GPA in SSC and HSC 8.00 to 9.99 | 50% | All | 14,000x 8 = 1,12,000 BDT | 8,000 x 8 = 64,000 BDT | 1,76,000 BDT |
Sum of GPA in SSC and HSC 5.00 to 7.99 | 30% | All | 14,000x 8 = 1,12,000 BDT | 11,200 x 8 = 89,600 BDT | 2,01,600 BDT |
Registration x 6 Semester | Semester Fees x 6 Semester | Total Fees |
14,000x 6 = 84,000 BDT | 16,000 x 6 = 96,000 BDT | 1,80,000 BDT |
Waiver | Rate | Applicable For | Registration x 6 Semester | Tuition Fee x 6 Semester | Total Fees |
For All | 30% | All | 14,000x 6 = 84,000 BDT | 11200 x 6 = 67,200 BDT | 1,51,200 BDT |
Course Code | Course Title | Credit Hours |
CSE-101 | Computer Fundamentals | 3.0 |
CSE-102 | Computer Fundamentals Lab | 1.0 |
PHY-101 | Mechanics, Properties of Matter, Waves. Optics, Heat and thermodynamics | 3.0 |
MTH-105 | Differential and Integral Calculus | 3.0 |
CSE-105 | Structured Programming Language | 3.0 |
CSE-106 | Structured Programming Language Lab | 1.5 |
HUM-105 | Oral and Written Communication in English Language | 3.0 |
HUM-113 | Bangladesh Studies: History and Society of Bangladesh | 3.0 |
Total | 20.50 |
Course Code | Course Title | Credit Hours |
CSE-107 | Object Oriented Programming I | 3.0 |
CSE-108 | Object Oriented Programming I Lab | 1.5 |
MTH-107 | Geometry and Linear Algebra | 3.0 |
PHY-103 | Electromagnetism and Modern Physics | 3.0 |
PHY-102 | Physics Lab | 1.5 |
ECE-101 | Basic Electrical Engineering | 3.0 |
ECE-102 | Basic Electrical Engineering Lab | 1.5 |
ECN-101 | Principles of Economics | 3.0 |
HUM-103 | Language Composition and Comprehension | 3.0 |
Total | 22.50 |
Course Code | Course Title | Credit Hours |
CSE-201 | Discrete Mathematics | 3.0 |
CSE-211 | Object Oriented Programming II | 3.0 |
CSE-212 | Object Oriented Programming II Lab | 1.5 |
CSE-205 | Data Structures | 3.0 |
CSE-206 | Data Structures Lab | 1.5 |
MTH-205 | Vector Analysis and Complex Variable | 3.0 |
ECE-201 | Electronic Devices and Circuits | 3.0 |
ECE-202 | Electronic Devices and circuits Lab | 1.5 |
ACN-203 | Cost and Management Accounting | 3.0 |
Total | 22.50 |
Course Code | Course Title | Credit Hours |
CSE-207 | Algorithms | 3.0 |
CSE-208 | Algorithms Lab | 1.5 |
CSE-209 | Numerical Methods | 3.0 |
CSE-210 | Numerical Methods Lab | 1.5 |
CSE-231 | Digital Logic Design | 3.0 |
CSE-232 | Digital Logic Design Lab | 1.5 |
MTH-207 | Differential Equations , Laplace Transforms and Fourier Analysis | 3.0 |
CSE-200 | Project Work | 2.0 |
Total | 18.50 |
Course Code | Course Title | Credit Hours |
CSE-321 | Database Systems | 3.0 |
CSE-322 | Database Systems Lab | 1.5 |
CSE-331 | Computer Architecture | 3.0 |
CSE-323 | Web Engineering | 2.0 |
CSE-324 | Web Engineering Lab | 1.5 |
MTH-301 | Statistics and Probability | 2.0 |
CSE-309 | Cyber crime and Intellectual Property Law | 3.0 |
CSE-310 | Technical Report Writing and Presentation | 1.5 |
CSE-326 | Engineering Drawing | 1.0 |
Total | 18.50 |
Course Code | Course Title | Credit Hours |
CSE-300 | Software Development | 2.0 |
CSE-303 | Operating Systems | 3.0 |
CSE-304 | Operating Systems Lab | 1.5 |
CSE-315 | Data Communication | 3.0 |
CSE-313 | Microprocessors and Microcontroller | 3.0 |
CSE-314 | Microprocessors and Microcontroller Lab | 1.5 |
CSE-337 | System Analysis and Software Engineering | 3.0 |
CSE-338 | System Analysis and Software Engineering Lab | 1.5 |
Total | 18.50 |
Course Code | Course Title | Credit Hours |
CSE-425 | Digital Signal Processing | 3.0 |
CSE-426 | Digital Signal Processing Lab | 1.5 |
CSE-403 | Compiler Design | 3.0 |
CSE-404 | Compiler Design Lab | 1.5 |
CSE-421 | Computer Network | 3.0 |
CSE-422 | Computer Network Lab | 1.5 |
CSE-4** | Option | 3.0 |
CSE-4** | Option Lab | 1.5 |
Total | 18.00 |
Course Code | Course Title | Credit Hours | |||||
CSE-415 | Artificial Intelligence | 3.0 | |||||
CSE-416 | Artificial Intelligence Lab | 1.5 | |||||
CSE-431 | Computer Graphics | 3.0 | |||||
CSE-432 | Computer Graphics Lab | 1.5 | |||||
CSE-435 | Computer Interfacing | 3.0 | |||||
CSE-436 | Computer Interfacing Lab | 1.5 | |||||
CSE-4** | Option | 3.0 | |||||
CSE-4** | Option Lab | 1.5 | |||||
CSE-400 | Project / Thesis | 3.0 | |||||
CVV-402 | Comprehensive Viva Voce | 1.5 | |||||
Total | 23.00 |
Course Code | Course Title | Credit Hours |
CSE-437 | Pattern Recognition | 3.0 |
CSE-438 | Pattern Recognition Lab | 1.5 |
CSE-411 | VLSI Design | 3.0 |
CSE-412 | VLSI Design Lab | 1.5 |
CSE-419 | Graph Theory | 3.0 |
CSE-420 | Graph Theory Lab | 1.5 |
CSE-423 | Computer System Performance Evaluation | 3.0 |
CSE-424 | Computer System Performance Evaluation Lab | 1.5 |
ECE-421 | Digital Communication | 3.0 |
ECE-422 | Digital Communication Lab | 1.5 |
CSE-407 | Simulation and Modeling | 3.0 |
CSE-408 | Simulation and Modeling Lab | 1.5 |
CSE-453 | Digital Image Processing | 3.0 |
CSE-454 | Digital Image Processing Lab | 1.5 |
CSE-455 | Wireless and sensor Networks | 3.0 |
CSE-456 | Wireless sensor Networks Lab | 1.5 |
CSE-409 | Computer Security and Cryptography | 3.0 |
CSE-410 | Computer Security and Cryptography Lab | 1.5 |
CSE-457 | Bioinformatics | 3.0 |
CSE-458 | Bioinformatics Lab | 1.5 |
CSE-461 | Neural Networks | 3.0 |
CSE-462 | Neural Networks Lab | 1.5 |
CSE-463 | Machine Learning | 3.0 |
CSE-464 | Machine Learning Lab | 1.5 |
CSE-465 | Contemporary course on CSE | 3.0 |
CSE-466 | Contemporary course Lab on CSE | 1.5 |
CSE-467 | Advanced Database Systems | 3.0 |
CSE-468 | Advanced Database Systems Lab | 1.5 |
CSE-469 | Natural Language Processing | 3.0 |
CSE-470 | Natural Language Processing Lab | 1.5 |
Total Credit Hours Required for Degree | 162.00 |
Detailed Syllabus
CSE-101 Computer Fundamentals
3 Credits
Introduction: Definition, history & some applications of computer. Classification of Computer: H/W and S/W computer components. Number systems : Binary, octal, hexadecimal number systems and operations, computer codes. Boolean algebra.Data processing techniques.Arithmetic e’ logic operation.Logic gates. Operating systems: MS-WINDOWS, UNIX. Application software’s: Word processors, word perfect, Ms-word Excel, Foxpro. Programming languages: M/c language, assembly language, high level languages, source & object language, 4th generation language, compilers, translators & interpreter. Elements of computer H/W. Data transmission & networking.
Books Recommended:
CSE-102 Computer Fundamentals Lab
1.0 Credits
Laboratory works based on CSE 101.
PHY-101 Mechanics, Properties of Matter, Waves, Optics, Heat & Thermodynamics
3 Credits
Mechanics : Measurements, Motion in one Dimension, Motion in a Plane, Particle Dynamics, Work & Energy, Circular Motion, Simple Harmonic Motion, Rotation of Rigid Bodies, Central Force, Structure of Matter, Mechanical Properties of Materials. Properties of Matter: Elasticity, Stresses & Strains, Young’s Modulus, Bulk Modulus, Rigidity Modulus, Elastic Limit, Poisson’s Ratio, Relation between Elastic Constants, Bending of Beams. Fluid Motion, Equation of Continuity, Bernoulli’s Theorem, Viscosity, Stokes’ Law. Surface Energy & Surface Tension, Capillarity, Determination of Surface Tension by Different Methods Waves : Wave Motion & Propagation, Simple Harmonic Motion, Vibration Modes, Forced Vibrations, Vibration in Strings & Columns, Sound Wave & Its Velocity, Doppler Effect, Elastic Waves, Ultrasonics, Practical Applications. Optics : Theories of Light, Huygen’s Principle, Electromagnetic Waves, Velocity of Light, Reflection, Refraction, Lenses, Interference, Diffraction, Polarization. Heat & Thermodynamics : Temperature and Zeroth Law of Thermodynamics, Calorimetry, Thermal Equilibrium & Thermal Expansion, First Law of Thermodynamics, Specific Heat, Heat Capacities, Equation of State, Change of Phase, Heat Transfer, Second Law of Thermodynamics, Carnot Cycle, Efficiency, Entropy, Kinetic Theory of Gases.
Books Recommended:
MTH-105 Differential and Integral Calculus
3 Credits
Differential Calculus: Real number System. Relations and functions, Functions of single variable, their Domain, Range, Graphs, Limit, Continuity and Differentiability. Successive Differentiation, Leibnitz’s theorem, Rolle’s theorem, Mean value theorem, Taylor’s theorem, Maclaurin’s theorem, Langrage’s and Cauchy’s forms of Remainder. Expansion of Function in Taylor’s and Maclaurin’s Series. Maximum and Minimum Values of Function. Evaluation of Indeterminate forms of limit, L’ Hospital’s Rule. Tangent and Normal. Curvature, Radius of Curvature, Centre of Curvature. Functions of more than one variable, Limit, Continuity, Differentiability, Partial Derivatives, Euler’s Theorem. Jacobians. Integral Calculus: Indefinite Integrals and its definition. Methods of Integration (Integration by substitution, Integration by parts, Integration by successive reduction). Fundamental theorem of Integral calculus. Definite Integral and its properties. Definite Integral as the limit of a sum. Improper Integrals, Beta and Gamma Function, Its application in evaluating Integrals. Evaluation of Arc length, Areas, Surfaces of Revolution, Volumes of solids of Revolution, Multiple Integrals.
Books Recommended:
CSE-105 Structured Programming Languages
3 Credits
Programming language: Basic concept; overview of programming languages, C-language: Preliminaries; Elements of C; program constructs; variables and data types in C; Input and output; character and formatted I/O; Arithmetic expressions and assignment statements; loops and nested loops; Decision making’ Arrays; Functions; Arguments and Local Variables; Calling functions and arrays; Recursion and recursive functions; structures within structure; Files; File functions for sequential and Random I/O. Pointers, Pointers and Structures; Pointers and functions; Pointer and arrays; Operations on pointers; Pointer and memory addresses; Operations on bits; Bit operation; Bit field; Advanced features; Standard and Library functions.
Books Recommended:
CSE 106 Structured Programming Languages Lab
1.5 Credits
Laboratory works based on CSE 105.
HUM-105 Oral and written Communication in English Language
3 Credits
Oral & written communication skills include communicative expressions for day to day activities, both for personal and professional requirement. Grammar items will mainly emphasize the use of articles, numbers, tense, modal verbs, pronouns, punctuation, etc. Sentence formation, question formation, transformation of sentence, simple passive voice construction, and conditionals will also be covered.
Books Recommended:
HUM-113 Bangladesh Studies : History and Society of Bangladesh
3 Credits
Bangladesh-Geography of Bangladesh-History of Bangladesh: ancient, medieval, British periods, politics of 1930’s and 1940’s, Language movement, 6-point & 11-point programs, liberation war and emergence of Bangladesh and constitutional transformation of the state. Social structure of Bangladesh-Social problems such as repression of women, eve-teasing, urbanization, terrorism, communalism, corruption etc.
Books Recommended:
CSE-107 Object Oriented Programming I
3 Credits
Introduction to Java: History of Java, Java class Libraries, Introduction to java programming, and a simple program. Developing java Application: Introduction, Algorithms, Pseudo code, control Structure, The If/Else selection structure, the while Repetition structure, Assignment operators, Increment and decrement operators, Primitive data types, common Escape sequences, Logical operator. Control Structure: Introduction, for Structure, switch structure, Do while structure, Break and continue Structure. Methods: Introduction, Program module in Java, Math class methods, method definitions, java API packages, Automatic variables, Recursions, Method overloading, Method of the Applet class. Arrays: Introduction, Arrays, declaring and allocating arrays, passing arrays to methods, sorting arrays, searching arrays, multiple subscripted Arrays. Inheritance: Introduction, Super class, Subclass, Protected members, using constructor and Finalizes in subclasses, composition vs. Inheritance, Introduction to polymorphism, Dynamic method building, Final methods and classes, Abstract super classes and concrete classes, Exception Handling.
Books Recommended:
CSE 108 Object Oriented Programming I Lab
1.5 Credits
Laboratory works based on CSE 107.
MTH-107 Geometry and Linear Algebra
3 Credits
Geometry: Two dimensional Geometry: Transformation of Co-ordinates. Pair of straight lines, General Equation of Second Degree, Circle, Parabola, Ellipse and Hyperbola. Three Dimensional Geometry: Three Dimensional Co-ordinates, Direction Cosines and Direction Ratios. Plane and Straight line. Linear Algebra: Determinant and properties of Determinants, Matrix, Types of matrices, Matrix operations, Laws of matrix Algebra, Invertible matrices. Elementary row and Column operations and Row-reduced echelon matrices, Rank of matrices. System of Linear equations (homogeneous and non-homogeneous) and their solutions. Vectors in R^{n} and C^{n }, Inner product, Norm and Distance in R^{n} and C^{n }. Vector Spaces, Subspace, Linear combination of vectors, Linear dependence and independence of vectors. Basis and Dimension of vector spaces. Inner product spaces, Orthogonality and Orthonormal sets, Eigen values and Eigen vectors, diagonalization, Cayley-Hamilton theorem and its application.
Books recommended:
PHY-103 Electromagnetism and Modern Physics
3 Credits
Electrostatics, Electric Charge, Coulomb’s Law, Electric Field & Electric Potential, Electric Flux Density, Gauss’s Law, Capacitors and Dielectrics, Steady Current, Ohm’s Law, Magnetostatics, Magnetic Field, Biot-Savart Law, Ampere’s Law, Electromagnetic Induction, Faraday’s Law, Lenz’s Law, Self Inductance & Mutual Inductance, Magnetic Properties of Matter, Permeability, Susceptibility, Diamagnetism, Paramagnetism&Ferroma-gnetism, Maxwell’s Equations of Electromagnetic Waves, Waves in Conducting & Non-Conducting Media, Total Internal Reflection, Transmission along Wave Guides. Special Theory of Relativity, Length Contraction & Time Dilation, Mass-Energy Relation, Photo Electric Effect, Quantum Theory, X-rays and X-ray Diffraction, Compton Effect, Dual Nature of Matter & Radiation, Atomic Structure, Nuclear Dimensions, Electron Orbits, Atomic Spectra, Bohr Atom, Radioactive Decay, Half-Life, a, b and g Rays, Isotopes, Nuclear Binding Energy, Fundamentals of Solid State Physics, Lasers, Holography.
Books Recommended:
PHY-102 Physics Lab
1.5 Credits
Laboratory works based on PHY-101 & PHY-103.
ECE-101 Basic Electrical Engineering
3 Credits
Fundamental electrical concepts, Kirchoff’s Laws, Equivalent resistance. Electrical circuits: Series circuits, parallel circuits, series-parallel networks. Network analysis: Source conversion, Star/Delta conversion, Branch-current method, Mesh analysis, Nodal analysis. Network theorems: Superposition theorem, Thevenin’s theorem, Norton’s theorem. Capacitors. Magnetic circuits, Inductors Sinosoidal alternating waveforms: Definitions, phase relations, Instantaneous value, Average value, Effective (rms)Value. Phasor algebra Series, parallel and series-parallel ac networks. Power: Apparent power, Reactive power, Power triangle, Power factor correction. Pulse waveforms and the R-C response. Three-phase system Transformers.
Books Recommended:
ECE 102 Basic Electrical Engineering Lab
1.5 Credits
Laboratory works based on ECE 101.
ECN 101 Principles of Economics
3 Credits
Introduction: The Nature, scope and methods of Economics, Economics and Engineering. Some Fundamental concepts commonly used in Economics. Micro Economics: The theory of demand and supply and their elasticity’s. Market price determination competition in theory and practice. Indifference curve technique. Marginal analysis. Factors of production and production function. Scale of production – Internal and external economies and diseconomies. The short run and the long run. Fixed cost and variable cost. Macro Economics: National income analysis. Inflation and its effects. Savings, Investments. The basis of trade and the terms of trade. Monetary policy, Fiscal policy, Trade policy with reference to Bangladesh. Planning in Bangladesh.
Books Recommended:
HUM-103 Language Composition and Comprehension
3 Credits
This course purports to make the student well up in composition and comprehension of English language used in formal write ups like articles, essays and treatises. Here text will be given for comprehension, exercises of writing essays, paragraphs and reports will be done and construction of proper sentences expressing formal ideas will be taught. Sufficient exercises of translation and re-translations will be included.
Books Recommended:
CSE-201 Discrete Mathematics
3 Credits
Mathematical Models and Reasoning: Propositions, Predicates and Quantifiers, Logical operators, Logical inference, Methods of proof. Sets: Set theory, Relations between sets, Operations on sets. Induction, The natural numbers, Set operations on å*. Binary Relations : Binary relations and Digraphs, Graph theory, Trees, Properties of relations, Composition of relations, Closure operations on relations, Order relations, Equivalence relations and partitions. Functions: Basic properties, Special classes of functions. Counting and Algorithm Analysis: Techniques, Asymptotic behavior of functions, Recurrence systems, Analysis of algorithms. Infinite sets: Finite and Infinite sets, Countable and uncountable sets, Comparison of cardinal numbers. Algebras: Structure, Varieties of algebras, Homomorphism, Congruence relations.
Books Recommended:
CSE-211 Object Oriented Programming II
3 Credits
String, String Buffer and String Builder classes, Files and Stream, Java Database Connectivity: Statement and Prepared Statement Interfaces, CRUD operations using Statement and Prepared Statement, JDBC Transaction Management, Object Relational Mapping, Java Persistency API: Introduction, Entity class annotations, Entity Manager interface, Entity Transaction interface, CRUD operations using JPA, Primary Key Generation Strategies, Entity Inheritance, Entity Mapping, Java Persistency Query Language: Select, Update, Delete and Named Queries, Servlets: Servlet Interface, Generic Servlet and HTTP Servlet, Servlet lifecycle, Java Server Pages: JSP Life cycle methods, Tags in JSP, JSP Implicit Objects, JSP Standard Tag Library, Java Server Faces: Introduction, JSF Architecture and Application Development, JSF Page Navigation and Managed Bean, JSF Core Tag Library, JSF Event Handling Model, JSF Validation Model, JSF Data Conversion Model, JPA JSF Integration, Java API, Utility classes, 2D Graphics, GUI, Swing, Events.
CSE-212 Object Oriented Programming II Lab
1.5 Credits
Laboratory works based on CSE 211.
CSE-205 Data Structures
3 Credits
Concepts and examples: Introduction to Data structures. Elementary data structures: Arrays, records, pointer. Arrays: Type, memory representation and operations with arrays. Linked lists: Representation, Types and operations with linked lists. Stacks and Queues: Implementations, operations with stacks and queues. Graphs: Implementations, operations with graph. Trees: Representations, Types, operations with trees. Memory Management: Uniform size records, diverse size records. Sorting: Internal sorting, external sorting. Searching : List searching, tree searching. Hashing: Hashing functions, collision resolution.
Books Recommended:
CSE-206 Data Structures Lab
1.5 Credits
Laboratory works based on CSE 205.
MTH-205 Vector Analysis and Complex Variable
3 Credits
Vector Analysis: Vector Algebra – Vectors in three dimensional space, Algebra of Vectors, Rectangular Components, Addition, Subtraction and Scalar multiplication, Scalar and Vector product of two vectors. Scalar and Vector triple product. Application in Geometry. Vector Calculus – Limit, Continuity and Differentiability of Scalar and Vector point functions. Scalar and Vector field. Gradient, Divergence and Curl of point functions. Vector Integration, Line, Surface and Volume Integrals. Green’s theorem, Gauss’s theorem, Stoke’s theorem. Complex Variable: Field of Complex numbers, D’Moivre’s theorem and its applications. Limit and Continuity of complex functions, Derivatives, Analytic function, Harmonic function, Cauchy-Rieman equation. Line Integral of Complex functions. Cauchy’s Integral theorem and Cauchy’s Integral formula. Lioville’s theorem, Taylors and Laurent’s theorem, Singularity Residue, Cauchy’s Residue theorem. Contour Integration. Bilinear transformation. Mapping of Elementary functions. Conformal mapping.
Book Recommended:
ECE-201 Electronic Devices & Circuits
3 Credits
Introduction to semiconductors, Junction diode characteristics & diode applications, Bipolar Junction transistor characteristics, Transistor biasing, Small signal low frequency h-parameter model & hybrid -pi model, AC analysis of transistor, Frequency response of transistor, Operational amplifiers, Linear applications of operational amplifiers, DC performance of operational amplifiers, AC performance of operational amplifiers, Introduction to JFET, MOSFET, PMOS, NMOS & CMOS, Introduction to SCR, TRIAC, DIAC & UJT, Active filters Introduction to IC fabrication techniques & VLSI design.
Book Recommended:
ECE 202 Electronic Devices & Circuits Lab
1.5 Credits
Laboratory works based on ECE 201.
ACN-203 Cost and Management Accounting
3 Credits
Introduction: Cost accounting: Definition, Limitations of Financial Accounting, Importance, Objectives, Functions and Advantages of Cost Accounting, Financial Accounting VS. Cost Accounting VS. Managerial Accounting, Techniques and Methods of Cost Accounting, International Cost Accounting Systems. Managerial accounting: Definition , Evolution , Objectives , Scope , Importance , Functions , Techniques , Differences among Managerial Accounting , Cost Accounting and Financial Accounting , Management Accounting for Planning and Control .Cost Classification : Cost Concepts , Cost Terms , Cost Expenses and Losses , Cost Center ,Cost Unit , Classification of Costs , Cost Accounting Cycle, Cost Statement , The Flow of Costs in a Manufacturing Enterprise ,Reporting and Results of Operation. Materials : Indirect & Direct Material , Procurement of Materials , Purchase Control , Purchase Department , Purchase Quantity , Fixed Order , Economic Order Quantity , Stock-out Cost , Re-order Level , Purchase Order , Receipts and Inspection ,Classification and Codification of materials ,Stock Verification , ABC Method of Store Control , Pricing of materials Issued , LIFO, FIFO and Average Pricing , Inventory Control; Labor: Labor Cost Control, Time Recording Systems, Manual and Mechanical Methods, Time Booking, Necessary Documents Maintained for Labor Control, Methods of Remuneration; Treatment for Idle and Over Time. Overhead: Definition , Classifications of Overheads , Methods of Overhead Distribution , Distribution of Factory Overhead to Service Departments, Redistribution of Service Department Cost , Uses of Predetermined Overhead Rates , Treatment of Over and under absorbed Overhead ,Treatment of Administration Overhead , Selling and Distribution Overheads , Calculation of Machine Hour rate . Job Order Costing: Feature Advantages, Limitation, Accounting for Materials, Labor and Factory Overhead in Job Costing, Accounting for Jobs Completed and Products Sold, Spoilage, Defective Work and Scrap in job Costing System, The Job Cost Sheet, Job Order Costing in Service Companies, Nature and Uses of Batch Costing, Determination of Economic Batch Quantity. Contract Costing: Introduction, Procedures, Types of Contract, Retention Money, Profit or Loss on Incomplete Contract, Cost plus Contract Systems; Operation Costing: Nature, Procedures, Costing for Transport and Hospital; Cost Behavior : Analysis of Cost Behavior , Measurement of Cost Behavior , Methods of Methods of Measuring Cost Functions , Analysis of Mixed Costs , High and Low Point Method , Scatter graph Method , Least Squares Method , Use of Judgment in Cost Analysis ; Cost – Volume Profit Relationship : Profit Planning , Break Even Point , Break Even Chart , Changes in Underlying Factors , Profit Volume Graph , Income Tax effect on Break Even Point , Break Even Point in Decision Making , Risk and Profit Analysis , Limitations .
Books Recommended:
CSE-207 Algorithms
3 Credits
Analysis of Algorithm: Asymptotic analysis: Recurrences, Substitution method, Recurrence tree method, Master method. Divide-and-Conquer: Binary search, Powering a number, Fibonacci numbers, Matrix Multiplication, Strassen’s Algorithm for Matrix Multiplication. Sorting: Insertion sort, Merge sort, Quick sort, Randomized quick sort, Decision tree, Counting sort, Radix sort. Order Statistics: Randomized divide and conquer, worst case linear time order statistics. Graph: Representation, Traversing a graph, Topological sorting, Connected Components. Dynamic Programming: Elements of DP (Optimal substructure, Overlapping subproblem), Longest Common Subsequence finding problem, Matrix Chain Multiplication. Greedy Method: Greedy choice property, elements of greedy strategy, Activity selector problem, Minimum spanning tree (Prims algorithm, Kruskal algorithm), Huffman coding. Shortest Path Algorithms: Dynamic and Greedy properties, Dijkstra’s algorithm with its correctness and analysis, Bellman-ford algorithm, All pair shortest path: Warshall’s algorithm, Johnson’s algorithm. Network flow: Maximum flow, Max-flow-min-cut, Bipartite matching. Backtracking/Branch-and-Bound: Permutation, Combination, 8-queen problem, 15-puzzle problem. Geometric algorithm: Segment-segment intersection, Convex-hull, Closest pair problem. And NP Completeness, NP hard and NP complete problems.
Books Recommended:
CSE-208 Algorithms Lab
1.5 Credits
Using different well known algorithms to solve the problem of Matrix-Chain Multiplication, Longest Common Subsequence, Huffman codes generation, Permutation, Combination, 8-queen problem, 15-puzzle, BFS, DFS, flood fill using DFS, Topological sorting, Strongly connected component, finding minimum spanning tree, finding shortest path (Dijkstra’s algorithm and Bellman-Ford’s algorithm), Flow networks and maximum bipartite matching, Finding the convex hull, Closest pair.
CSE-209 Numerical Methods
3 Credits
Errors and Accuracy. Iterative process: Solution of f(x)= 0, existence and convergence of a root, convergence of the iterative method, geometrical representation, Aitken’s D^{2}– process of acceleration. System of Linear Equations. Solution of Non-Linear equations. Finite Differences and Interpolation. Finite Difference Interpolation. Numerical Differentiation. Numerical Integration. Differential Equations.
Books Recommended:
CSE-210 Numerical Methods Lab
1.5 Credits
Laboratory works based on CSE 209.
CSE-231 Digital Logic Design
3 Credits
Binary Logic. Logic Gates: IC digital logic families, positive and negative logic. Boolean Algebra. Simplification of Boolean Functions: Karnaugh map method, SOP and POS simplification, NAND, NOR, wired-AND, wired-OR implementation, nondegenerate forms, Don’t care conditions, Tabulation method – prime implicant chart. Combinational Logic: Arithmetic circuits – half and full adders and subtractors, multilevel NAND and NOR circuits, Ex-OR and Equivalence functions. Combinational Logic in MSI and LSI: Binary parallel adder, decimal and BCD adders, Comparators, Decoders and Encoders, Demultiplexors and Multiplexors. Sequential Logic. Registers and Counters. Synchronous Sequential Circuits. Asynchronous Sequential Circuits. Digital IC terminology, TTL logic family, TTL series characteristics, open-collector TTL, tristate TTL, ECL family, MOS digital ICs, MOSFET, CMOS characteristics, CMOS tristate logic, TTL-CMOS-TTL interfacing, memory terminology, general memory operation, semiconductor memory technologies, different types of ROMs, semiconductor RAMs, static and dynamic RAMs, magnetic bubble memory, CCD memory, FPGA Concept.
Books Recommended:
CSE-232 Digital Logic Design Lab
1.5 Credits
Laboratory works based on CSE 231.
MTH-207 Differential Equations, Laplace Transforms and Fourier Analysis
3 Credits
Differential Equation: Formation of Differential equation, Degree and Order of differential equation, Complete and Particular solution. Ordinary differential equation – Solution of ordinary differential equation of first order and first degree (special forms). Linear differential equation with constant coefficients. Homogeneous linear differential equation. Solution of differential equation by the method of Variation of parameters. Solution of linear differential equations in series by Frobenius method. Bessel’s function and Legendre’s Polynomials and their properties. Simultaneous equation of the form dx/P=dy/Q=dz/R. Partial differential equation – Lagrange’s linear equation, Equation of linear and non-linear first order standard forms, Charpit’s method.
Laplace Transforms: Definition, Laplace transforms of some elementary functions, sufficient conditions for existence of Laplace transforms, Inverse Laplace transforms, Laplace transforms of derivatives, Unit step function, Periodic function, Some special theorems on Laplace transforms, Partial fraction, Solution of differential equations by Laplace transforms, Evaluation of Improper Integrals. Fourier Analysis: Fourier series (Real and complex form). Finite transforms, Fourier Integrals, Fourier transforms and application in solving boundary value problems.
Books Recommended:
CSE-200 Project Work
2 Credits
Project focusing on Object oriented programming approach and using standard algorithm is preferable. Every project should maintain a goal so that it can be used as a useful tool in the IT fields. Also innovative project ideas that require different types scripting/programming languages or programming tools can be accepted with respect to the consent of the corresponding project supervisor.
CSE-321 Database Systems
3 Credits
Introduction: Purpose of Database Systems, Data Abstraction, Data Models, Instances and Schemes, Data Independence, Data Definition Language, Data Manipulation Language, Database Manager, Database administrator, Database Users, Overall System Structure, Advantages and Disadvantage of a Database Systems. Data Mining and analysis, Database Architecture, History of Database Systems Relationship Entity-Model: Entities and Entity Sets, Relationships and Relationship Sets, Attributes, Composite and Multivalued Attributes, Mapping Constraints, Keys, Entity-Relationship Diagram, Reducing of E-R Diagram to Tables, Generalization, Attribute Inheritance, Aggregation, Alternative E-R Notatios, Design of an E-R Database Scheme.
Relational Model: Structure of Relational Database, Fundamental Relational Algebra Operations, The Tuple Relational Calculus, The Domain Relational Calculus, Modifying the Database. Relational Commercial Language: SQL, Basic structure of SQL Queries, Query-by-Example, Quel., Nested Sub queries, Complex queries, Integrity Constraints, Authorization, Dynamic SQL, Recursive Queries. Relational Database Design: Pitfalls in Relational Database Design, Functional Dependency Theory, Normalization using Functional Dependencies, Normalization using Multivalued Dependencies, Normalization using join Dependencies, Database Design Process. File And System Structure: Overall System Structure, Physical Storage Media, File Organization, RAID, Organization of Records into Blocks, Sequential Files, Mapping Relational Data to Files, Data Dictionary Storage, Buffer Management. Indexing And Hashing: Basic Concepts, Ordered Indices, B+ -Tree Index Files, B-Tree Index Files, Static and Dynamic Hash Function, Comparison of Indexing and Hashing, Index Definition in SQL, Multiple Key Access.
Query Processing and Optimization: Query Interpretation, Equivalence of Expressions, Estimation of Query-Processing Cost, Estimation of Costs of Access Using Indices, Join Strategies, Join Strategies for parallel Processing, Structure of the query Optimizer, Transformation of Relational Expression. Concurrency Control: Schedules, Testing for Serializability, Lock-Based Protocols, Timestamp-Based Protocols, Validation Techniques, Multiple Granularity, Multiversion Schemes, Insert and Delete Operations, Deadlock Handling. Distributed Database: Structure of Distributed Databases, Trade-off in Distributing the Database, Design of Distributed Database, Transparancy and Autonomy, Distributed Query Processing, Recovery in Distributed Systems, Commit Protocols, Concurrency Control. Data Mining and Information Retrieval: Data analysis and OLAP, Data Warehouse, Data Mining, Relevance Ranking Using Terms, Relevance Ranking Using Hyperlink, Synonyms, Homonyms, Ontology, Indexing of Document, Measuring Retrieval Efficiencies, Information Retrieval and Structured Data.
Books Recommended:
CSE-322 Database Systems Lab
1.5 Credits
Introduction: What is
database, MySQL , Oracle , SQL, Datatypes, SQL / PLSQL, Oracle
Software Installation, User Type, Creating User , Granting. Basic
Parts of Speech in SQL: Creating Newspaper Table,
Select Command (Where , order by), Creating View, Getting Text
Information & Changing it, Concatenation, Cut & paste
string(RPAD , LPAD , TRIM , LTRIM , RTRIM, LOWER , UPPER , INIT,
LENGTH , SUBSTR , INSTR , SOUNDEX). Playing The
Numbers: Addition , Subtraction , Multiplication ,
Division, NVL , ABS , Floor , MOD , Power , SQRT , EXR , LN , LOG ,
ROUND, AVG , MAX , MIN , COUNT , SUM, Distinct, SUBQUERY FOR
MAX,MIN. Grouping things together: Group By ,
Having, Order By, Views Renaming Columns with Aliases.When
one query depends upon another: Union, Intersect ,
Minus, Not in , Not Exists. Changing Data :
INSERT,UPDATE,MERGE,DELETE, ROLLBACK , AUTOCOMMIT , COMMIT,
SAVEPOINTS, MULTI TABLE INSERT, DELETE, UPDATE, MERGE. Creating
And Altering tables & views: Altering table,
Dropping table, Creating view, Creating a table from a table.
By What Authority: Creating User, Granting
User, Password Management.
An Introduction to PL/SQL: Implement few problems
using PL/SQL (eg Prime Number, Factorial, Calculating Area of
Circle, etc).An Introduction to Trigger and
Procedure: Implement few problems using Trigger
and Procedures. An Introduction to Indexing: Implement
indexing using a large database and observe the difference of
Indexed and Non-Indexed database.
CSE-331 Computer Architecture
3 Credits
Introduction to Computer Architecture: Overview and history; Cost factor; Performance metrics and evaluating computer designs. Instruction set design: Von Neumann machine cycle, Memory addressing, Classifying instruction set architectures, RISC versus CISC, Micro programmed vs. hardwired control unit. Memory System Design: Cache memory; Basic cache structure and design; Fully associative, direct, and set associative mapping; Analyzing cache effectiveness; Replacement policies; Writing to a cache; Multiple caches; Upgrading a cache; Main Memory; Virtual memory structure, and design; Paging; Replacement strategies. Pipelining: General considerations; Comparison of pipelined and nonpipelined computers; Instruction and arithmetic pipelines, Structural, Data and Branch hazards. Multiprocessors and Multi-core Computers: SISD, SIMD, and MIMD architectures; Centralized and distributed shared memory- architectures; Multi-core Processor architecture. Input/output Devices: Performance measure, Types of I/O device, Buses and interface to CPU, RAID. Pipelining: Basic pipelining, Pipeline Hazards. Parallel Processing.
Books Recommended:
CSE-323 Web Engineering
2 Credits
Introduction to Web Engineering, Requirements Engineering and Modeling Web Applications, Web Application Architectures, Technologies and Tools for Web Applications, Testing and Maintenance of Web Applications, Usability and Performance of Web Applications, Security of Web Applications, The Semantic Web.
Books References:
CSE-324 Web Engineering Lab
1.5 Credits
Understanding the Web Application: Web Engineering introduces a structured methodology utilized in software engineering to Web development projects. The course addresses the concepts, methods, technologies, and techniques of developing Web Sites that collect, organize and expose information resources. Topics covered include requirements engineering for Web applications, design methods and technologies, interface design, usability of web applications, accessibility, testing, metrics, operation and maintenance of Web applications, security and project management. Specific technologies covered in this course include client-side (XHTML, JavaScript and CSS) and server-side (Perl and PHP). Using the described concepts students should be able to understand the Web engineering concepts behind the frameworks of Joomla, Drupal, WordPress. Server-side technology: LAMP, Web application frameworks, (example: Silverlight, Adobe Flex), Web 2.0 and Web APIs. Front-end technology: HTML, XHTML, XML. CSS Styling, layout, selector, Document object model and JavaScript. Client-Programming: Web APIs with JavaScript (example: Google AJAX API). MVC: Understanding model, view and controller model. Understanding Web APIs: REST, XML, JSON, RSS Parsing. JavaScript Exercise: The goal of this assignment is to allow you to explore and use vas many of JavaScript’s objects, methods and properties as possible in a small assignment. Some functions must be written from scratch. Other functions, appropriately attributed, may be downloaded from the web and used as a part of the system or as the basis for your own functions. PHP Exercise: Build a set of PHP scripts that perform some dynamic server-side functionality. Understanding plug-ins: Develop a Firefox extension.
MTH-301 Statistics and Probability
2 Credits
Frequency distribution; mean, median, mode and other measures of central tendency, Standard deviation and other measures of dispersion, Moments, skewness and kurtosis, Elementary probability theory and discontinuous probability distribution, e.g. binomial, poison and negative binomial, Continuous probability distributions, e.g. normal and exponential, Characteristics of distributions, Hypothesis testing and regression analysis.
Books Recommended:
CSE-309 Cyber Crime and Intellectual Property Law
3 Credits
Introduction: the problem of computer crime, what is Cybercrime? Cybercrime: the invisible threat, Information and other assets in need of assurance, Computer focused and computer assisted crimes, the hacker, hacking tactics, the victim, Data: surveys, network flow and IPS/IDS, Data: honey pots and incidents, Cyber terrorism, Cyber laws and regulations, Investigating cyber crime , Preventing cyber crime and Future opportunities for managing cybercrime. Intellectual Property: Introduction, Philosophical Perspectives and Overview of Intellectual Property: Trade Secret; Patent; Copyright; Trademark/Trade Dress; Problem; Copyright and patent; need of intellectual Property laws, Copyright for software, software-copyright cases, Database, the focus shifts from copyright to patent, the nature of patent law, some software-patent cases. Filmy and video, Pornography meets the internet, different between downloads and publications, censoring videos.
Books Recommended:
CSE-310 Technical Report Writing and Presentation
1.5 Credits
Issues of technical writing and effective oral presentation in Computer Science and Engineering; Writing styles of definitions, propositions, theorems and proofs; Preparation of reports, research papers, theses and books: abstract, preface, contents, bibliography and index; Writing of book reviews and referee reports; Writing tools: LATEX; Diagram drawing software; presentation tools.
Books Recommended:
CSE-326 Engineering Drawing
1 Credit
Introduction; Instruments and their uses; First and third angle projection; Orthographic drawing; Sectional views and conventional practices; Auxiliary views; Isometric views; Missing lines and views.
Books Recommended:
CSE-300 Software Development
2 Credits
Students will work in groups or individually to produce high quality software in different languages. Students will write structured programs and use proper documentation. Advanced programming techniques in Mobile Application.
Books Recommended:
CSE-303 Operating Systems
3 Credits
Introduction: Operating Systems Concept, Computer System Structures, Operating System Structures, Operating System operations, Protection and Security, Special-Purpose Systems. Fundamentals of OS : OS services and components, multitasking, multiprogramming, time sharing, buffering, spooling Process Management: Process Concept, Process Scheduling, Process State, Process Management, Interprocess Communication, interaction between processes and OS, Communication in Client-Server Systems, Threading, Multithreading, Process Synchronization. Concurrency control: Concurrency and race conditions, mutual exclusion requirements, semaphores, monitors, classical IPC problem and solutions, Dead locks – characterization, detection, recovery, avoidance and prevention. Memory Management: Memory partitioning, Swapping, Paging, Segmentation, Virtual memory – Concepts, Overlays, Demand Paging, Performance of demand paging, Page replacement algorithm, Allocation algorithms. Storage Management: Principles of I/O hardware, Principles of I/O software, Secondary storage structure, Disk structure, Disk scheduling, Disk Management, Swap-space Management, Disk reliability, Stable storage implementation. File Concept: File support, Access methods, Allocation methods, Directory systems, File Protection, Free Space management Protection & Security : Goals of protection, Domain of protection, Access matrix, Implementation of access matrix, Revocation of access rights, The security problem, Authentication, One-time passwords, Program threats, System threats, Threat monitoring, Encryption, Computer-security classification. Distributed Systems: Types of Distributed Operating System, Communication Protocols, Distributed File Systems, Naming and Transparency, Remote File Access, Stateful Versus Stateless Service, File Replication. Case Studies: Study of a representative Operating Systems,
Books Recommended:
CSE-304 Operating Systems Lab
1.5 Credits
Thread programming: Creating thread and thread synchronization. Process Programming: The Process ID, Running a New Process, Terminating a Process, Waiting for Terminated Child Processes, Users and Groups, Sessions and Process Groups. Concurrent Programming: Using fork, exec for multi-task programs. File Operations: File sharing across processes, System lock table, Permission and file locking, Mapping Files into Memory, Synchronized, Synchronous, and Asynchronous Operations, I/O Schedulers and I/O Performance.
Communicating across processes: Using different signals, Pipes, Message queue, Semaphore, Semaphore arithmetic and Shared memory.
Books Recommended:
CSE-315 Data Communication
3 Credits
Introduction to modulation techniques: Pulse modulation; pulse amplitude modulation, pulse width modulation and pulse position modulation. Pulse code modulation; quantization, Delta modulation. TDM, FDM, OOK, FSK, PSK, QPSK; Representation of noise; threshold effects in PCM and FM. Probability of error for pulse systems, concepts of channel coding and capacity. Asynchronous and synchronous communications. Hardware interfaces, multiplexers, concentrators and buffers. Communication medium, Fiber optics.
Books Recommended:
CSE-313 Microprocessors and Microcontroller
3 Credits
Introduction to 8-bit, 16-bit, and 32-bit microprocessors: architecture, addressing modes, instruction set, interrupts, multi-tasking and virtual memory; Memory interface; Bus interface; Arithmetic co-processor; Microcontrollers; Integrating microprocessor with interfacing chips.
Books Recommended:
CSE-314 Microprocessors and Microcontroller Lab
1.5 Credits
Laboratory works based on CSE-313.
CSE-337 System Analysis and Software Engineering
3 Credits
Concepts of Software Engineering; Software Engineering paradigms;Different phases of software System Development; Different types of information, qualities of information. Project Management Concepts; Software process and project Metrics; Software Project Planning; Risk Analysis and management; Project Scheduling and Tracking. Analysis Concepts and principles: requirement analysis, Analysis modeling, data modeling. Design concepts and principles, Architectural design, User Interface design, Object Oriented software development and design: Iterative Development and the Unified Process. Sequential waterfall life cycles, Inception. Use case model for requirement writing, Elaboration using System Sequence Diagram, Domain Model. Visualizing concept classes. UML diagrams, Interaction and Collaboration Diagram for designing Software. Designing Objects with responsibilities. GRASP patterns with General Principles in assigning responsibilities: Information expert, Creator, Low Coupling and High Cohesion, Creating design class diagrams and mapping design to codes. Advanced GRASP patterns: Polymorphism, Pure Fabrication, Indirection, Project Variation. GoF Design Patterns: Adapter, Factory, Singleton, Strategy, Composite, Facade, and Observer. Software Testing: White Box and Black Box testing. Basis Path Testing. Testing for specialized environment. Software testing strategies: Unit Testing, Integration Testing, Validation Testing, System Testing, Art of debugging. Analysis of System Maintenance and upgrading: Software repair, downtime, error and faults, specification and correction, Maintenance cost models, documentation. Software Quality Assurance, Quality factors. Software quality measures.Cost impact of Software defects. Concepts of Software reliability, availability and safety. Function based metrics and bang metrics. Metrics for analysis and design model. Metrics for source code, testing and maintenance.
Books Recommended:
CSE-338 System Analysis and Software Engineering Lab
1.5 Credits
Software Engineering lab works is solely designed to attain hands on experience of architectural design, documentation and testing of software so that students can develop the software following the documents only.
Step1 (Requirement Engineering): Choose a company/institute/client for which software will be developed (make sure that they will provide required information whenever necessary). Follow the steps for eliciting requirements and generate use-case diagram. Also analyze the sufficiency of the requirement engineering outcome for steps to follow.
Step 2 (Analysis model to Architectural and Component level design): Generate Activity diagram, Data flow diagram (DFD), Class diagram, State diagram, Sequence diagram and follow other relevant steps for creating complete architectural and component level design of the target software.
Step 3 (User Interface design, Design evaluation, Testing strategies and Testing Tactics): Perform the user interface design with the help of swimlane diagram. Carry out the design evaluation steps. Generate all test cases for complete checking of the software using black box, white box testing concept.
Step 4 Software testing and debugging
Step 5 (Managing Software Projects): Analyze the estimation and project schedule.
CSE-425 Digital Signal Processing
3 Credits
Introduction to digital signal processing (DSP): Discrete-time signals and systems, analog to digital conversion, impulse response, finite impulse response (FIR) and infinite impulse response (IIR) of discrete-time systems, difference equation, convolution, transient and steady state response. Discrete transformations: Discrete Fourier series, discrete-time Fourier series, discrete Fourier transform (DFT) and properties, fast Fourier transform (FFT), inverse fast Fourier transform, z-transformation – properties, transfer function, poles and zeros and inverse z-transform. Correlation: circular convolution, auto-correlation and cross correlation. Digital Filters: FIR filters- linear phase filters, specifications, design using window, optimal and frequency sampling methods; IIR filters- specifications, design using impulse invariant, bi-linear z-transformation, least-square methods and finite precision effects. Digital signal processor TMS family, Application of digital signal processing
Books Recommended:
CSE-426 Digital Signal Processing Lab
1.5 Credits
Laboratory works based on CSE 425.
CSE-403 Compiler Design
3 Credits
Introduction to compilers: Introductory concepts, types of compilers, applications, phases of a compiler. Lexical analysis: Role of the lexical analyzer, input buffering, token specification, recognition of tokens, symbol tables. Parsing: Parser and its role, context free grammars, top-down parsing. Syntax-directed translation: Syntax-directed definitions, construction of syntax trees, top-down translation. Type checking: Type systems, type expressions, static and dynamic checking of types, error recovery. Run-time organization: Run-time storage organization, storage strategies. Intermediate code generation: Intermediate languages, declarations, assignment statements. Code optimization: Basic concepts of code optimization, principal sources of optimization. Code generation. Features of some common compilers: Characteristic features of C, Pascal and Fortran compilers.
Books Recommended:
CSE-404 Compiler Design Lab
1.5 Credits
How to use scanner and parser generator tools (e.g., Flex, JFlex, CUP, Yacc, etc). For a given simple source language designing and implementing lexical analyzer, symbol tables, parser, intermediate code generator and code generator.
CSE-421 Computer Network
3 Credits
Network architectures-layered architectures and ISO reference model: data link protocols, error control, HDLC, X.25, flow and congestion control, virtual terminal protocol, data security. Local area networks, satellite networks, packet radio networks. Introduction to ARPANET, SNA and DECNET. Topological design and queuing models for network and distributed computing systems.
Books Recommended:
CSE-422Computer Network Lab
1.5 Credits
Laboratory works based on CSE 421.
CSE-415 Artificial Intelligence
3 Credits
What is Artificial Intelligence: The AI problems, The underlying assumption, What is an AI technique. Problems, Problem spaces and Search: Defining the problem as a state space search, Production system, Problem characteristics. Heuristics Search Techniques: Generate and Test, Hill climbing, Best First Search, Problem Reduction, Constraint Satisfaction, Means-Ends Analysis. Knowledge Representation Issues: Representation and Mappings, Approaches to knowledge Representation, Issues in Knowledge representation. Using Predicate logic: Representing simple facts in logic, Representing Instance and Isa relationships, Computable functions and Predicates, Resolution. Representing Knowledge using Rules: Procedural versus Declarative Knowledge, Logic Programming, Forward versus Backward Reasoning, Matching. Game playing: Overview, The Mimimax Search Procedure, Adding Alpha-Beta cutoffs, Additional refinements, iterative Deepening, Planning: Overview, An example Domain: The Blocks World, Components of a planning system, Goal stack planning, Understanding: What is Understanding, What makes Understanding hard, Understanding as constraint satisfaction. natural Language Processing: Introduction, Syntactic Processing, Semantic Analysis, Discourse and Pragmatic Processing. Expert systems: representing and using domain knowledge, Expert system shells explanation, Knowledge Acquisition.
AI Programming Language: Python, Prolog, LISP
Books Recommended:
CSE-416 Artificial Intelligence Lab
1.5 Credits
Students will have to understand the functionalities of intelligent agents and how the agents will solve general problems. Students have to use a high-level language (Python, Prolog, LISP) to solve the following problems:
Backtracking: State space, Constraint satisfaction, Branch and bound. Example: 8-queen, 8- puzzle, Crypt-arithmetic. BFS and production: Water jugs problem, The missionaries and cannibal problem. Heuristic and recursion: Tic-tac-toe, Simple bock world, Goal stack planning, The tower of Hanoi. Question answering: The monkey and bananas problem.
CSE-431Computer Graphics
3 Credits
Introduction to Graphical data processing. Fundamentals of interactive graphics programming. Architecture of display devices and connectivity to a computer. Implementation of graphics concepts of two-dimensional and three-dimensional viewing, clipping and transformations. Hidden line algorithms. Raster graphics concepts: Architecture, algorithms and other image synthesis methods. Design of interactive graphic conversations.
Books Recommended:
CSE-432 Computer Graphics Lab
1.5 Credits
Laboratory works based on CSE 431.
CSE-435 Computer Interfacing
3 Credits
Interface components and their characteristics, microprocessor I/O. Disk, Drums, and Printers. Optical displays and sensors. High power interface devices, transducers, stepper motors and peripheral devices.
Books Recommended:
CSE-436 Computer Interfacing Lab
1.5 Credits
Laboratory works based on CSE 435.
CSE-437 Pattern Recognition
3 Credits
Introduction to pattern recognition: features, classifications, learning. Statistical methods, structural methods and hybrid method. Applications to speech recognition, remote sensing and biomedical area, Learning algorithms. Syntactic approach: Introduction to pattern grammars and languages. parsing techniques. Pattern recognition in computer aided design.
CSE-438 Pattern Recognition Lab
1.5 Credits
Laboratory works based on CSE 437.
CSE-411 VLSI Design
3 Credits
Design and analysis techniques for VLSI circuits. Design of reliable VLSI circuits, noise considerations, design and operation of large fan out and fan in circuits, clocking methodologies, techniques for data path and data control design. Simulation techniques. Parallel processing, special purpose architectures in VLSI. VLSI layouts partitioning and placement routing and wiring in VLSI. Reliability aspects of VLSI design.
Books Recommended:
CSE-412 VLSI Design Lab
1.5 Credits
Laboratory works based on CSE-411.
CSE-419 Graph Theory
3 Credits
Introduction, Fundamental concepts, Trees, Spanning trees in graphs, Distance in graphs, Eulerian graphs, Digraphs, Matching and factors, Cuts and connectivity, k-connected graphs, Network flow problems, Graph coloring: vertex coloring and edge coloring, Line graphs, Hamiltonian cycles, Planar graphs, Perfect graphs.
Books Recommended:
CSE-420 Graph Theory Lab
1.5 Credits
Laboratory works based on CSE 419.
CSE-423 Computer System Performance Evaluations
3 Credits
Review of system analysis, approaches to system development, feasibility assessment, hardware and software acquisition. Procurement, workload characterization, the representation of measurement data, instrumentation: software monitors, hardware monitors, capacity planning, bottleneck detection, system and program tuning, simulation and analytical models and their application, case studies.
CSE-424 Computer System Performance Evaluation Lab
1.5 Credits
Laboratory based on CSE 423.
ECE-421 Digital Communication
3 Credits
Introduction to modulation techniques: Pulse modulation; pulse amplitude modulation, pulse width modulation and pulse position modulation. Pulse code modulation; quantization, Delta modulation. TDM, FDM, OOK, FSK, PSK, QPSK; Representation of noise; threshold effects in PCM and FM. Probability of error for pulse systems, concepts of channel coding and capacity. Asynchronous and synchronous communications. Hardware interfaces, multiplexers, concentrators and buffers. Communication medium, Fiber optics.
Books Recommended:
ECE-422 Digital Communication Lab
1.5 Credits
Laboratory works based on ECE 421.
CSE-407 Simulation and Modeling
3 Credits
Simulation methods, model building, random number generator, statistical analysis of results, validation and verification techniques, Digital simulation of continuous systems. Simulation and analytical methods, for analysis of computer systems and practical problems in business and practice. Introduction to the simulation packages.
Books Recommended:
CSE-408 Simulation and Modeling Lab
1.5 Credits
Laboratory works based on CSE 407.
CSE-453 Digital Image
Processing
3 Credits
Image Processing: Image Fundamentals, Image Enhancement: Background, Enhancement by Point-Processing, Spatial Filtering, Enhancement in Frequency Domain, Color Image Processing. Image Restoration: Degradation Model, Diagonalization of Circulant and Block-Circulant Matrices, Algebraic Approach to Restoration, Inverse Filtering, Geometric Transformation. Image Segmentation: Detection of Discontinuities, Edge Linking and Boundary Detection, Thresholding, Region-Oriented Segmentation, The use of Motion in Segmentation. Image-Compression.
Books Recommended:
CSE-454 Digital Image Processing Lab
1.5 Credits
Laboratory works based on CSE 453.
CSE-455 Wireless Sensor Networks
3 Credits
Introduction: applications; Localization and tracking: tracking multiple objects; Medium Access Control: S-MAC, IEEE 802.15.4 and ZigBee; Geographic and energy-aware routing; Attribute-Based Routing: directed diffusion, rumor routing, geographic hash tables; Infrastructure establishment: topology control, clustering, time synchronization; Sensor tasking and control: task-driven sensing, information-based sensor tasking, joint routing and information aggregation; Sensor network databases: challenges, querying the physical environment, in-network aggregation, data indices and range queries, distributed hierarchical aggregation; Sensor network platforms and tools: sensor node hardware, sensor network programming challenges; Other state-of-the-art related topics.
Books Recommended:
CSE-456 Wireless Sensor Networks Lab
1.5 Credits
Laboratory works based on CSE 455.
CSE-409 Computer Security and Cryptography
3 Credits
Network Security Practice, Authentication Digital certificates and Public key infrastructure, X.500, Application, Electronic Mail Security, IP Security, Web Security, System Security, Intruders, Malicious Software, Firewalls, Threats and Attacks, Various Attack Techniques and Prevention; Cryptography: Overview, Terminology, Substitution and Transposition ciphers, One time pads, Symmetric Ciphers, classical Encryption Technique, Block Ciphers and the Data Encryption Standard, Introduction to Finite Fields, Advanced Encryption Standard, Contemporary, Symmetric Ciphers Confidentiality Using Symmetric Encryption, Public Key Encryption, One way functions and Hash Functions, Introduction to Number Theory, Prime number generation, Public-Key Cryptography and RSA, Key Management, Key exchange algorithm; Other Public-key Cryptosystems, Message Authentication and Hash Functions, Hash Algorithms, MD5, SHA, Digital Signatures and Authentication Protocols, DSA, Kerberos.
Books Recommended:
CSE-410 Computer Security and Cryptography Lab
1.5 Credits
Laboratory works based on CSE 409.
CSE-457 Bio-Informatics
3 Credits
Cell concept: Structural organization of plant and animal cells, nucleus, cell membrane and cell wall. Cell division: Introducing chromosome, Mitosis, Meiosis and production of haploid/diploid cell. Nucleic acids: Structure and properties of different forms of DNA and RNA; DNA replication. Proteins: Structure and classification, Central dogma of molecular biology. Genetic code: A brief account. Genetics: Mendel’s laws of inheritance, Organization of genetic material of prokaryotes and eukaryotes, C-Value paradox, repetitive DNA, structure of chromatin – euchromatin and heterochromatin, chromosome organization and banding patterns, structure of gene – intron, exon and their relationships, overlapping gene, regulatory sequence (lac operon), Molecular mechanism of general recombination, gene conversion, Evolution and types of mutation, molecular mechanisms of mutation, site-directed mutagenesis, transposons in mutation. Introduction to Bioinformatics: Definition and History of Bioinformatics, Human Genome Project, Internet and Bioinformatics, Applications of Bioinformatics Sequence alignment: Dynamic programming. Global versus local. Scoring matrices. The Blast family of programs. Significance of alignments, Aligning more than two sequences. Genomes alignment. Structure-based alignment. Hidden Markov Models in Bioinformatics: Definition and applications in Bioinformatics. Examples of the Viterbi, the Forward and the Backward algorithms. Parameter estimation for HMMs. Trees: The Phylogeny problem. Distance methods, parsimony, bootstrap. Stationary Markov processes. Rate matrices. Maximum likelihood. Felsenstein’s post-order traversal. Finding regulatory elements: Finding regulatory elements in aligned and unaligned sequences. Gibbs sampling. Introduction to microarray data analysis: Steady state and time series microarray data. From microarray data to biological networks. Identifying regulatory elements using microarray data. Pi calculus: Description of biological networks; stochastic Pi calculus, Gillespie algorithm.
Books Recommended:
CSE-458 Bio-Informatics Lab
1.5 Credits
Laboratory works based on CSE-457.
CSE-461 Neural Networks
3 Credits
Fundamentals of Neural Networks; Back propagation and related training algorithms; Hebbian learning; Cohonen-Grossberg learning; The BAM and the Hopfield Memory; Simulated Annealing; Different types of Neural Networks: Counter propagation, Probabilistic, Radial Basis Function, Generalized Regression, etc; Adaptive Resonance Theory; Dynamic Systems and neural Control; The Boltzmann Machine; Self-organizing Maps; Spatiotemporal Pattern Classification, The Neocognition; Practical Aspects of Neural Networks.
Books Recommended:
CSE-462 Neural Networks Lab
1.5 Credits
Laboratory works based on CSE 461.
CSE-463 Machine Learning
3 Credits
Introduction: Definition of learning systems. Goals and applications of machine learning. Aspects of developing a learning system- training data, concept representation, function approximation. Inductive Classification: The concept learning task. Concept learning as search through a hypothesis space. General-to-specific ordering of hypotheses. Finding maximally specific hypotheses. Version spaces and the candidate elimination algorithm. Learning conjunctive concepts. The importance of inductive bias. Decision Tree Learning: Representing concepts as decision trees. Recursive induction of decision trees. Picking the best splitting attribute: entropy and information gain. Searching for simple trees and computational complexity. Occam’s razor. Overfitting, noisy data, and pruning. Experimental Evaluation of Learning Algorithms: Measuring the accuracy of learned hypotheses. Comparing learning algorithms- cross-validation, learning curves, and statistical hypothesis testing. Computational Learning Theory: Models of learnability- learning in the limit; probably approximately correct (PAC) learning. Sample complexity- quantifying the number of examples needed to PAC learn. Computational complexity of training. Sample complexity for finite hypothesis spaces. PAC results for learning conjunctions, kDNF, and kCNF. Sample complexity for infinite hypothesis spaces, Vapnik-Chervonenkis dimension. Rule Learning, Propositional and First-Order: Translating decision trees into rules. Heuristic rule induction using separate and conquer and information gain. First-order Horn-clause induction (Inductive Logic Programming) and Foil. Learning recursive rules. Inverse resolution, Golem, and Progol. Artificial Neural Networks: Neurons and biological motivation. Linear threshold units. Perceptrons: representational limitation and gradient descent training. Multilayer networks and backpropagation. Hidden layers and constructing intermediate, distributed representations. Overfitting, learning network structure, recurrent networks. Support Vector Machines: Maximum margin linear separators. Quadractic programming solution to finding maximum margin separators. Kernels for learning non-linear functions. Bayesian Learning: Probability theory and Bayes rule. Naive Bayes learning algorithm. Parameter smoothing. Generative vs. discriminative training. Logisitic regression. Bayes nets and Markov nets for representing dependencies. Instance-Based Learning: Constructing explicit generalizations versus comparing to past specific examples. k-Nearest-neighbor algorithm. Case-based learning. Text Classification: Bag of words representation. Vector space model and cosine similarity. Relevance feedback and Rocchio algorithm. Versions of nearest neighbor and Naive Bayes for text. Clustering and Unsupervised Learning: Learning from unclassified data. Clustering. Hierarchical Aglomerative Clustering. k-means partitional clustering. Expectation maximization (EM) for soft clustering. Semi-supervised learning with EM using labeled and unlabled data.
Books Recommended:
CSE-464 Machine Learning Lab
1.5 Credits.
Students should learn the methods for
extracting rules or learning from data, and get the necessary
mathematical background to understand how the methods work and how
to get the best performance from them. To achieve these goals
student should learn the following algorithms in the lab: K Nearest
Neighbor Classifier, Decision Trees, Model Selection and Empirical
Methodologies, Linear Classifiers: Perception and SVM, Naive Bayes
Classifier,Basics of Clustering Analysis, K-mean Clustering
Algorithm, Hierarchical Clustering Algorithm. Upon completion of the
course, the student should be able to perform the followings: a.
Evaluate whether a learning system is required to address a
particular problem. b. Understand how to use data for learning,
model selection, and testing to achieve the goals.c. Understand
generally the relationship between model complexity and model
performance, and be able to use this to design a strategy to improve
an existing system.
d. Understand the advantages and disadvantages of the learning
systems studied in the course, and decide which learning system is
appropriate for a particular application. e. Make a naive Bayes classifier and interpret the results as probabilities. f. Be able to apply clustering algorithms to simple data sets for clustering analysis.
CSE-465 Contemporary Course on CSE
3 Credits
The course and course contents will be proposed from the department which will be more relevant with respect to present CSE technology.
CSE-466 Contemporary Course Lab on CSE
1.5 Credits
Laboratory works based on CSE 465.
CSE-467 Advanced Database Systems
3 Credits
Introduction : Object oriented Database, Data Model, Design, Languages; Object Relational Database: Complex data types, Querying with complex data types, Design; Distributed Database: Levels of distribution transparency, Translation of global queries to fragment queries, Optimization of access strategies, Management of distributed transactions, Concurrency control, reliability, Administration; Parallel Database: Different types of parallelism, Design of parallel database; Multimedia Database Systems: Basic concepts, Design, Optimization of access strategies, Management of Multimedia Database Systems, Reliability; Database Wire-housing/Data mining: Basic concepts and algorithms.
Books Recommended:
CSE-468 Advanced Database System Lab
1.5 Credits
Laboratory works based on CSE-467.
CSE 469 Natural Language Processing
3 Credits
Introduction; Word Modeling: Automata and Linguistics, Statistical Approaches and Part of Speech Tagging; Linguistics and Grammars; Parsing Algorithms; Parsing Algorithms and the Lexicon; Semantic; Feature Parsing; Tree Banks and Probabilistic Parsing; Machine Translation; Evolutionary Models of Language Learning and Origins.
Books Recommended:
CSE-470 Natural Language Processing Lab
1.5 Credits
Processing of words, Phrase structure parsing, Semantic Interpretation with Phrase Structure Grammars
Books Recommended:
CSE-400 Project / Thesis
3 Credits
Study of problems in the field of Computer Science and Engineering. This course will be initiated in the 3^{rd} year or early in 4^{th} year.
CSE-402 Comprehensive Viva Voce
2 Credits
Course Code | Course Title | Credit Hours |
HUM 103 | Language Composition & Comprehension | 3 |
CSE 103 | Computer Programming in C | 3 |
CSE 104 | Computer Programming in C Lab | 1.5 |
PHY 101E | Physics for Engineers | 3 |
PHY 102 | Physics for Engineers Lab | 1.5 |
MTH 101E | Geometry, Differential & Integral Calculus | 3 |
ECE 101 | Basic Electrical Engineering | 3 |
ECE 102 | Basic Electrical Engineering Lab | 1.5 |
ECN 101 | Principles of Economics | 2 |
ACN 201 | Principles of Accounting | 2 |
Course Code | Course Title | Credit Hours |
CSE 200 | Project Work | 2 |
CSE 201 | Discrete Mathematics | 3 |
CSE 203 | Object Oriented Programming Language | 3 |
CSE 204 | Object Oriented Programming Language Lab | 1.5 |
CSE 205 | Data Structures | 3 |
CSE 206 | Data Structures Lab | 1.5 |
ECE 201 | Electronic Devices & Circuits | 3 |
ECE 202 | Electronic Devices & Circuits Lab | 1.5 |
MTH 103E | Linear Algebra, Vector Analysis & Complex Variables | 3 |
IMG 201 | Principles of Management | 2 |
Course Code | Course Title | Credit Hours |
CSE 207 | Algorithms | 3 |
CSE 208 | Algorithms Lab | 1.5 |
CSE 209 | Numerical Methods | 3 |
CSE 231 | Digital Logic Design | 3 |
CSE 232 | Digital Logic Design Lab | 1.5 |
CSE 321 | Database Systems | 3 |
CSE 322 | Database Systems Lab | 1.5 |
CSE 331 | Computer Architecture | 3 |
MTH 203E | Differential Equations, Laplace Transforms & Fourier Analysis | 3 |
Course Code | Course Title | Credit Hours |
CSE 300 | Software Development | 2 |
CSE 301 | E-Commerce and Web Engineering | 3 |
CSE 302 | E-Commerce and Web Engineering Lab | 1.5 |
CSE303 | Operating Systems | 3 |
CSE 304 | Operating Systems Lab | 1.5 |
CSE 315 | Data Communication | 3 |
CSE 351 | Management Information System | 3 |
CSE 403 | Compiler Design | 3 |
CSE 404 | Compiler Design Lab | 1.5 |
MTH 301 | Statistics & Probability | 2 |
Course Code | Course Title | Credit Hours |
CSE 333 | Microprocessors and Assembly Language | 3 |
CSE 334 | Microprocessors and Assembly Language Lab | 1.5 |
CSE 339 | Theory of Computation | 2 |
CSE 401 | Software Engineering | 3 |
CSE 421 | Computer Network | 3 |
CSE 422 | Computer Network Lab | 1.5 |
CSE 435 | Computer Interfacing | 3 |
CSE 436 | Computer Interfacing Lab | 1.5 |
CSE 4** | Option | 3 |
CSE 4** | Option Lab | 1.5 |
Course Code | Course Title | Credit Hours |
CSE 405 | Artificial Intelligence & Expert Systems | 3 |
CSE 406 | Artificial Intelligence & Expert Systems Lab | 1.5 |
CSE 425 | Digital Signal Processing | 3 |
CSE 426 | Digital Signal Processing Lab | 1.5 |
CSE 431 | Computer Graphics | 3 |
CSE 432 | Computer Graphics Lab | 1.5 |
CSE 400 | Project /Thesis | 3 |
CVV 402 | Comprehensive Viva Voce | 2 |
CSE 4** | Option | 3 |
CSE 4** | Option Lab | 1.5 |
Course Code | Course Title | Credit Hours |
CSE 407 | Simulation & Modeling | 3 |
CSE 408 | Simulation & Modeling Lab | 1.5 |
CSE 411 | VLSI Design | 3 |
CSE 412 | VLSI Design Lab | 1.5 |
CSE 413 | Information System Design | 3 |
CSE 414 | Information System Design Lab | 1.5 |
CSE 419 | Graph Theory | 3 |
CSE 420 | Graph Theory Lab | 1.5 |
CSE 423 | Computer System Performance Evaluation | 3 |
CSE 424 | Computer System Performance Evaluation Lab | 1.5 |
CSE 437 | Pattern Recognition | 3 |
CSE 438 | Pattern Recognition Lab | 1.5 |
CSE 453 | Digital Image Processing | 3 |
CSE 454 | Digital Image Processing Lab | 1.5 |
CSE 455 | Wireless and Sensor Networks | 3 |
CSE 456 | Wireless and Sensor Networks Lab | 1.5 |
CSE 457 | Bioinformatics | 3 |
CSE 458 | Bioinformatics Lab | 1.5 |
CSE 461 | Neural Networks | 3 |
CSE 462 | Neural Networks Lab | 1.5 |
CSE 463 | Machine Learning | 3 |
CSE 464 | Machine Learning Lab | 1.5 |
CSE 465 | Contemporary course on CSE | 3 |
CSE 466 | Contemporary course on CSE Lab | 1.5 |
HUM-103 Language Composition and Comprehension
3 Credits
This course purports to make the student well up in composition and comprehension of English language used in formal write ups like articles, essays and treatises. Here text will be given for comprehension, exercises of writing essays, paragraphs and reports will be done and construction of proper sentences expressing formal ideas will be taught. Sufficient exercises of translation and re-translations will be included.
Books Recommended:
CSE-103 Computer Programming in C
3 Credits
Programming language: Basic concept; overview of programming languages, C-language: Preliminaries; Elements of C; program constructs; variables and data types in C; Input and output; character and formatted I/O; Arithmetic expressions and assignment statements; loops and nested loops; Decision making’ Arrays; Functions; Arguments and Local Variables; Calling functions and arrays; Recursion and recursive functions; structures within structure; Files; File functions for sequential and Random I/O. Pointers, Pointers and Structures; Pointers and functions; Pointer and arrays; Operations on pointers; Pointer and memory addresses; Operations on bits; Bit operation; Bit field; Advanced features; Standard and Library functions.
Books Recommended:
CSE-104 Computer Programming in C Lab
1.5 Credits
Laboratory works based on CSE 103.
PHY-101E Physics for Engineering
3 Credits
Properties of matter : Elasticity, Stress & Strain, Young’s Modulus, Surface Tension. Heat & Thermodynamics: Heat, Temperature, Zeroth Law of Thermodynamics, Thermal Equilibrium, Seebeck effect, Reversible & Irreversible Processes, First and Second law of Thermodynamics, Heat Engine, Carnot Cycle. Electromegnetism: Electric charge, Charge density, Coulomb’s and Ohm’s law, Electric field and electric potential, Electric dipole, Electric flux, Gauss’s law and its application, Capacitance, Magnetic field, Biot-Savert law, Ampere’s law and its application, Electromagnetic Induction, Faraday’s law, Lenz’s law, Self Inductance and Mutual Inductance. Optics: Nature and Propagation of light, Reflection and Refraction of light, Total Internal Reflection, Interference, Diffraction, Dispersion, Polarization. Modern Physics: Theory of Relativity, Length Contraction and Time Dilation, Mass-Energy Relation, Compton Effect, Photoelectric Effect, Quantum Theory, Atomic Structure, X-ray Diffraction, Atomic Spectra, Electron Orbital Wavelength, Bohr radius, Radioactivity, de Broglie theory, Nuclear Fission and Fusion.
Books Recommended:
PHY 102 Physics Lab
1.5 Credits
Laboratory works based on PHY 101E.
MTH-101E Geometry, Differential and Integral Calculus
3 Credits
Geometry: Two dimensional geometry: Straight lines, pair of straight lines, Circle, Parabola, Ellipse and Hyperbola, Equation of General equation of Second Degree. Third Dimensional Geometry: Three dimensional Co-ordinates, Direction Cosines and Direction Ratios, Plane and Straight line. Differential Calculus: Real number system. Functions of single variables, its Graphs, Limit, Continuity and Differentiability. Successive Differentiation, Leibnitz’s theorem, Rolle’s theorem, Mean value theorem, Taylor’s theorem, Maclaurin’s theorem, Langrage’s and Cauchy’s forms of Remainder. Expansion of Function in Taylor’s and Maclaurin’s Series. Maximum and Minimum Values of Function. Evaluation of Indeterminate forms of limit, L’ Hospital’s Rule. Tangent and Normal. Functions of more than one variable, Limit, Continuity, Differentiability, Partial Derivatives, Euler’s Theorem. Jacobians. Integral Calculus: Indefinite Integrals and its definition. Methods of Integration (Integration by substitution, Integration by parts, Integration by successive reduction). Fundamental theorem of Integral calculus. Definite Integral and its properties. Definite Integral as the limit of a sum. Improper Integrals, Beta and Gamma Function, Its application in evaluating Integrals. Evaluation of Arc length, Areas, Surfaces of Revolution, Volumes of solids of Revolution, Multiple Integrals.
Books Recommended:
ECE 101 Basic Electrical Engineering
3 Credits
Fundamental electrical concepts, Kirchoff’s Laws, Equivalent resistance. Electrical circuits: Series circuits, parallel circuits, series-parallel networks. Network analysis: Source conversion, Star/Delta conversion, Branch-current method, Mesh analysis, Nodal analysis. Network theorems: Superposition theorem, Thevenin’s theorem, Norton’s theorem. Capacitors. Magnetic circuits, Inductors Sinosoidal alternating waveforms: Definitions, phase relations, Instantaneous value, Average value, Effective (rms)Value. Phasor algebra Series, parallel and series-parallel ac networks. Power: Apparent power, Reactive power, Power triangle, Power factor correction. Pulse waveforms and the R-C response. Three-phase system Transformers.
Books Recommended:
ECE 102 Basic Electrical Engineering Lab
1.5 Credits
Laboratory works based on ECE 101.
ECN 101 Principles of Economics
2 Credits
Introduction: The Nature, scope and methods of Economics, Economics and Engineering. Some Fundamental concepts commonly used in Economics. Micro Economics: The theory of demand and supply and their elasticity’s. Market price determination competition in theory and practice. Indifference curve technique. Marginal analysis. Factors of production and production function. Scale of production – Internal and external economies and diseconomies. The short run and the long run. Fixed cost and variable cost. Macro Economics: National income analysis. Inflation and its effects. Savings, Investments. The basis of trade and the terms of trade. Monetary policy, Fiscal policy, Trade policy with reference to Bangladesh. Planning in Bangladesh.
Books Recommended:
ACN 201 Principles of Accounting
2 Credits
This course aims at developing basic concepts and principles of accounting. It will cover topics like working at journal entries, preparation of ledger, checking the accuracy through trial balance, and preparation of financial statements. Concepts and practices of cost accounting will be discussed by covering topics like job order and process costing, contract costing, differential costing and responsibility accounting. Contemporary practices of accounting principles will be discussed under the current legal framework.
Books Recommended:
CSE 200 Project Work
2 Credits
Project focusing on Object oriented programming approach and using standard algorithm is preferable. Every project should maintain a goal so that it can be used as a useful tool in the IT fields. Also innovative project ideas that require different types scripting/programming languages or programming tools can be accepted with respect to the consent of the corresponding project supervisor.
CSE-201 Discrete Mathematics
3 Credits
Mathematical Models and Reasoning: Propositions, Predicates and Quantifiers, Logical operators, Logical inference, Methods of proof. Sets: Set theory, Relations between sets, Operations on sets. Induction, The natural numbers, Set operations on å*. Binary Relations : Binary relations and Digraphs, Graph theory, Trees, Properties of relations, Composition of relations, Closure operations on relations, Order relations, Equivalence relations and partitions. Functions: Basic properties, Special classes of functions. Counting and Algorithm Analysis: Techniques, Asymptotic behavior of functions, Recurrence systems, Analysis of algorithms. Infinite sets: Finite and Infinite sets, Countable and uncountable sets, Comparison of cardinal numbers. Algebras: Structure, Varieties of algebras, Homomorphism, Congruence relations.
Books Recommended:
CSE 203 Object Oriented Programming Language
3 Credits
Introduction to Java: History of Java, Java class Libraries, Introduction to java programming, and a simple program. Developing java Application: Introduction, Algorithms, Pseudo code, control Structure, The If/Else selection structure, the while Repetition structure, Assignment operators, Increment and decrement operators, Primitive data types, common Escape sequences, Logical operator. Control Structure: Introduction, for Structure, switch structure, Do while structure, Break and continue Structure. Methods: Introduction, Program module in Java, Math class methods, method definitions, java API packages, Automatic variables, Recursions, Method overloading, Method of the Applet class. Arrays: Introduction, Arrays, declaring and allocating arrays, passing arrays to methods, sorting arrays, searching arrays, multiple subscripted Arrays. Inheritance: Introduction, Super class, Subclass, Protected members, using constructor and Finalizes in subclasses, composition vs. Inheritance, Introduction to polymorphism, Dynamic method building, Final methods and classes, Abstract super classes and concrete classes, Exception Handling.
Books Recommended:
CSE 204 Object Oriented Programming Language Lab
1.5 Credits
Laboratory works based on CSE 203.
CSE-205 Data Structures
3 Credits
Concepts and Examples: Introduction to Data structures. Elementary data structures: Arrays, records, pointer. Arrays: Type, memory representation and operations with arrays. Linked lists: Representation, Types and operations with linked lists. Stacks and Queues: Implementations, operations with stacks and queues. Graphs: Implementations, operations with graph. Trees: Representations, Types, operations with trees. Memory Management: Uniform size records, diverse size records. Sorting: Internal sorting, external sorting. Searching : List searching, tree searching. Hashing: Hashing functions, collision resolution.
CSE-206 Data Structures Lab
1.5 Credits
Laboratory works based on CSE 205.
ECE-201 Electronic Devices & Circuits
3 Credits
Introduction to semiconductors, Junction diode characteristics & diode applications, Bipolar Junction transistor characteristics, Transistor biasing, Small signal low frequency h-parameter model & hybrid -pi model, AC analysis of transistor, Frequency response of transistor, Operational amplifiers, Linear applications of operational amplifiers, DC performance of operational amplifiers, AC performance of operational amplifiers, Introduction to JFET, MOSFET, PMOS, NMOS & CMOS, Introduction to SCR, TRIAC, DIAC & UJT, Active filters Introduction to IC fabrication techniques & VLSI design.
Books Reccommended:
ECE 202 Electronic Devices & Circuits Lab
1.5 Credits
Laboratory works based on ECE 201.
MTH-103E Linear Algebra, Vector Analysis and Complex Variables
3 Credits
Linear Algebra: Matrix, Types of Matrices, Matrix operations, Laws of matrix algebra, Invertible matrices, System of Linear equations (homogeneous and non-homogeneous) and their solution. Elementary row and column operations and Row reduced echelon matrices, Different types of matrices, Rank of matrices. Eigen values and Eigen vectors. Vector Analysis: Vector Algebra – Vectors in three dimensional space, Algebra of Vectors, Rectangular components, Addition and Scalar multiplication, Scalar and Vector product of two Vectors, Scalar and Vector triple product. Vector Calculus – Vector differentiation and Integration. Gradient, Divergence and Curl. Green’s theorem, Stoke’s theorem. Complex Variable: Limit, Continuity and differentiability of complex functions. Analytic function, Harmonic function, Cauchy-Rieman equation. Complex Integration. Cauchy’s integral theorem and Cauchy’s Integral formula. Lioville’s theorem. Taylor’s and Laurent’s theorems. Singularities. Residue, Cauchy’s Residue theorem. Contour Integration.
Book s Recommended:
IMG 201 Principles of Management
This course aims at providing students with concepts and tools of general management. The course covers concepts of planning, organizing, motivating and controlling, and its importance in attaining organizational objectives. Some current issues and trends in general management will also be discussed.
Books Reccommended:
CSE-207 Algorithms
3 Credits
Analysis of Algorithm: Asymptotic analysis: Recurrences, Substitution method, Recurrence tree method, Master method. Divide-and-Conquer: Binary search, Powering a number, Fibonacci numbers, Matrix Multiplication, Strassen’s Algorithm for Matrix Multiplication. Sorting: Insertion sort, Merge sort, Quick sort, Randomized quick sort, Decision tree, Counting sort, Radix sort. Order Statistics: Randomized divide and conquer, worst case linear time order statistics. Graph: Representation, Traversing a graph, Topological sorting, Connected Components. Dynamic Programming: Elements of DP (Optimal substructure, Overlapping subproblem), Longest Common Subsequence finding problem, Matrix Chain Multiplication. Greedy Method: Greedy choice property, elements of greedy strategy, Activity selector problem, Minimum spanning tree (Prims algorithm, Kruskal algorithm), Huffman coding. Shortest Path Algorithms: Dynamic and Greedy properties, Dijkstra’s algorithm with its correctness and analysis, Bellman-ford algorithm, All pair shortest path: Warshall’s algorithm, Johnson’s algorithm. Network flow: Maximum flow, Max-flow-min-cut, Bipartite matching. Backtracking/Branch-and-Bound: Permutation, Combination, 8-queen problem, 15-puzzle problem. Geometric algorithm: Segment-segment intersection, Convex-hull, Closest pair problem. And NP Completeness, NP hard and NP complete problems.
Books Recommended:
Wesley Professional; 3rd edition, 1997.
CSE-208 Algorithms Lab
1.5 Credits
Using different well known algorithms to solve the problem of Matrix-Chain Multiplication, Longest Common Subsequence, Huffman codes generation, Permutation, Combination, 8-queen problem, 15-puzzle, BFS, DFS, flood fill using DFS, Topological sorting, Strongly connected component, finding minimum spanning tree, finding shortest path (Dijkstra’s algorithm and Bellman-Ford’s algorithm), Flow networks and maximum bipartite matching, Finding the convex hull, Closest pair.
CSE-209 Numerical Methods
3 Credits
Errors and Accuracy. Iterative process: Solution of f(x)= 0, existence and convergence of a root, convergence of the iterative method, geometrical representation, Aitken’s D^{2}– process of acceleration. System of Linear Equations. Solution of Non-Linear equations. Finite Differences and Interpolation. Finite Difference Interpolation. Numerical Differentiation. Numerical Integration. Differential Equations.
Books Recommended:
CSE-231 Digital Logic Design
3 Credits
Binary Logic. Logic Gates: IC digital logic families, positive and negative logic. Boolean Algebra. Simplification of Boolean Functions: Karnaugh map method, SOP and POS simplification, NAND, NOR, wired-AND, wired-OR implementation, nondegenerate forms, Don’t care conditions, Tabulation method – prime implicant chart. Combinational Logic: Arithmetic circuits – half and full adders and subtractors, multilevel NAND and NOR circuits, Ex-OR and Equivalence functions. Combinational Logic in MSI and LSI: Binary parallel adder, decimal and BCD adders, Comparators, Decoders and Encoders, Demultiplexors and Multiplexors. Sequential Logic. Registers and Counters. Synchronous Sequential Circuits. Asynchronous Sequential Circuits. Digital IC terminology, TTL logic family, TTL series characteristics, open-collector TTL, tristate TTL, ECL family, MOS digital ICs, MOSFET, CMOS characteristics, CMOS tristate logic, TTL-CMOS-TTL interfacing, memory terminology, general memory operation, semiconductor memory technologies, different types of ROMs, semiconductor RAMs, static and dynamic RAMs, magnetic bubble memory, CCD memory, FPGA Concept.
Books Recommended:
CSE-232 Digital Logic Design Lab
1.5 Credits
Laboratory works based on CSE 231.
CSE-321 Database Systems
3 Credits
Introduction: Purpose of Database Systems, Data Abstraction, Data Models, Instances and Schemes, Data Independence, Data Definition Language, Data Manipulation Language, Database Manager, Database administrator, Database Users, Overall System Structure, Advantages and Disadvantage of a Database Systems. Data Mining and analysis, Database Architecture, History of Database Systems Relationship Entity-Model: Entities and Entity Sets, Relationships and Relationship Sets, Attributes, Composite and Multivalued Attributes, Mapping Constraints, Keys, Entity-Relationship Diagram, Reducing of E-R Diagram to Tables, Generalization, Attribute Inheritance, Aggregation, Alternative E-R Notatios, Design of an E-R Database Scheme.
Relational Model: Structure of Relational Database, Fundamental Relational Algebra Operations, The Tuple Relational Calculus, The Domain Relational Calculus, Modifying the Database. Relational Commercial Language: SQL, Basic structure of SQL Queries, Query-by-Example, Quel., Nested Sub queries, Complex queries, Integrity Constraints, Authorization, Dynamic SQL, Recursive Queries. Relational Database Design: Pitfalls in Relational Database Design, Functional Dependency Theory, Normalization using Functional Dependencies, Normalization using Multivalued Dependencies, Normalization using join Dependencies, Database Design Process. File And System Structure: Overall System Structure, Physical Storage Media, File Organization, RAID, Organization of Records into Blocks, Sequential Files, Mapping Relational Data to Files, Data Dictionary Storage, Buffer Management. Indexing And Hashing: Basic Concepts, Ordered Indices, B+ -Tree Index Files, B-Tree Index Files, Static and Dynamic Hash Function, Comparison of Indexing and Hashing, Index Definition in SQL, Multiple Key Access.
Query Processing and Optimization: Query Interpretation, Equivalence of Expressions, Estimation of Query-Processing Cost, Estimation of Costs of Access Using Indices, Join Strategies, Join Strategies for parallel Processing, Structure of the query Optimizer, Transformation of Relational Expression. Concurrency Control: Schedules, Testing for Serializability, Lock-Based Protocols, Timestamp-Based Protocols, Validation Techniques, Multiple Granularity, Multiversion Schemes, Insert and Delete Operations, Deadlock Handling. Distributed Database: Structure of Distributed Databases, Trade-off in Distributing the Database, Design of Distributed Database, Transparancy and Autonomy, Distributed Query Processing, Recovery in Distributed Systems, Commit Protocols, Concurrency Control. Data Mining and Information Retrieval: Data analysis and OLAP, Data Warehouse, Data Mining, Relevance Ranking Using Terms, Relevance Ranking Using Hyperlink, Synonyms, Homonyms, Ontology, Indexing of Document, Measuring Retrieval Efficiencies, Information Retrieval and Structured Data.
Books Recommended:
CSE-322 Database Systems Lab
1.5 Credits
Introduction: What is database, MySQL , Oracle , SQL, Datatypes, SQL / PLSQL, Oracle Software Installation, User Type, Creating User , Granting. Basic Parts of Speech in SQL: Creating Newspaper Table, Select Command (Where , order by), Creating View, Getting Text Information & Changing it, Concatenation, Cut & paste string(RPAD , LPAD , TRIM , LTRIM , RTRIM, LOWER , UPPER , INIT, LENGTH , SUBSTR , INSTR , SOUNDEX). Playing The Numbers: Addition , Subtraction , Multiplication , Division, NVL , ABS , Floor , MOD , Power , SQRT , EXR , LN , LOG , ROUND, AVG , MAX , MIN , COUNT , SUM, Distinct, SUBQUERY FOR MAX,MIN. Grouping things together: Group By , Having, Order By, Views Renaming Columns with Aliases. When one query depends upon another: Union, Intersect , Minus, Not in , Not Exists. Changing Data : INSERT,UPDATE,MERGE,DELETE, ROLLBACK , AUTOCOMMIT , COMMIT, SAVEPOINTS, MULTI TABLE INSERT, DELETE, UPDATE, MERGE. Creating And Altering tables & views: Altering table, Dropping table, Creating view, Creating a table from a table. By What Authority: Creating User, Granting User, Password Management.
An Introduction to PL/SQL: Implement few problems using PL/SQL (eg Prime Number, Factorial, Calculating Area of Circle, etc).An Introduction to Trigger and Procedure: Implement few problems using Trigger and Procedures. An Introduction to Indexing: Implement indexing using a large database and observe the difference of Indexed and Non-Indexed database.
CSE-331 Computer Architecture
3 Credits
Introduction to Computer Architecture: Overview and history; Cost factor; Performance metrics and evaluating computer designs. Instruction set design: Von Neumann machine cycle, Memory addressing, Classifying instruction set architectures, RISC versus CISC, Micro programmed vs. hardwired control unit. Memory System Design: Cache memory; Basic cache structure and design; Fully associative, direct, and set associative mapping; Analyzing cache effectiveness; Replacement policies; Writing to a cache; Multiple caches; Upgrading a cache; Main Memory; Virtual memory structure, and design; Paging; Replacement strategies. Pipelining: General considerations; Comparison of pipelined and nonpipelined computers; Instruction and arithmetic pipelines, Structural, Data and Branch hazards. Multiprocessors and Multi-core Computers: SISD, SIMD, and MIMD architectures; Centralized and distributed shared memory- architectures; Multi-core Processor architecture. Input/output Devices: Performance measure, Types of I/O device, Buses and interface to CPU, RAID. Pipelining: Basic pipelining, Pipeline Hazards. Parallel Processing.
Books Recommended:
MTH-203E Differential Equations, Laplace Transforms and Fourier Analysis
3 Credits
Differential Equation: Formation, Degree and Order of differential equation, Complete and Particular solution. Solution of ordinary differential equation of first order and first degree (special forms). Linear differential equation with constant coefficients. Homogeneous linear differential equation. Solution of equation by the method of Variation of parameters. Solution of linear differential equations in series by Frobenius method. Solution of Simultaneous equation of the form = = . Laplace Transforms: Definition, Laplace transforms of some elementary functions, sufficient conditions for existence of Laplace transforms, Inverse Laplace transforms, Laplace transforms of derivatives, Unit step function, Periodic function, Some special theorems on Laplace transforms, Partial fraction, Solution of differential equations by Laplace transforms, Evaluation of Improper Integrals. Fourier Analysis: Fourier series (Real and complex form). Finite transforms, Fourier Integrals, Fourier transforms and application in solving boundary value problems.
Books Recommended:
CSE 300 Software Developments
1.5 Credits
Students will work in groups or individually to produce high quality software in different languages. Students will write structured programs and use proper documentation. Advanced programming techniques in Mobile Application.
Books Recommended:
CSE 301: E-Commerce and Web Engineering
3 Credits
E-Commerce Basics: E-Commerce Definition, Internet History and E-Commerce Development, Business-to-Business E-Commerce, Business-to-Consumer E-Commerce, E-Commerce Stages and Processes, E-Commerce Challenges, E-Commerce Opportunities.E-Commerce Options: Internet Access Requirements, Web Hosting Requirements, Entry-Level Options, Storefront and Template Services, E-Commerce Software Packages, E-Commerce Developers, E-Business Solutions.Marketing Issues: Online and Offline Market Research, Data Collection, Domain Names, Advertising Options, E-Mail Marketing, Search Engines, Web Site Monitoring, Incentives. Planning and Development: Web Site Goals, International Issues, Planning Stages, Resource Allocation, Content Development, Site Map Development, Web Site Design Principles, Web Site Design Tools, Web Page Programming Tools, Data-Processing Tools. E-Commerce Components: Navigation Aids, Web Site Search Tools, Databases, Forms, Shopping Carts, Checkout Procedures, Shipping Options. Payment Processing: Electronic Payment Issues, E-Cash, Credit Card Issues, Merchant Accounts, Online Payment Services, Transaction Processing, Taxation Issues, Mobile Commerce (M-Commerce). Security Issues: Security Issues and Threats, Security Procedures, Encryption, Digital Certificates, SSL and SET Technologies, Authentication and Identification, Security Providers, Privacy Policies, Legal Issues. Customer Service: Customer Service Issues, E-Mail Support , Telephone Support , Live Help Services, Customer Discussion Forums, Value-Added Options. ASP.NET programming model, Web development in Microsoft Visual Studio .NET, Anatomy of an ASP.NET page, ASP.NET core server controls, ADO.NET data providers, ADO.NET data containers, The data-binding model.
Books Recommended
CSE 302: E-Commerce and Web Engineering Lab
1.5 Credits
Laboratory works based on CSE 301.
303 Operating Systems
3 Credits
Introduction: Operating Systems Concept, Computer System Structures, Operating System Structures, Operating System operations, Protection and Security, Special-Purpose Systems. Fundamentals of OS : OS services and components, multitasking, multiprogramming, time sharing, buffering, spooling Process Management: Process Concept, Process Scheduling, Process State, Process Management, Interprocess Communication, interaction between processes and OS, Communication in Client-Server Systems, Threading, Multithreading, Process Synchronization. Concurrency control: Concurrency and race conditions, mutual exclusion requirements, semaphores, monitors, classical IPC problem and solutions, Dead locks – characterization, detection, recovery, avoidance and prevention. Memory Management: Memory partitioning, Swapping, Paging, Segmentation, Virtual memory – Concepts, Overlays, Demand Paging, Performance of demand paging, Page replacement algorithm, Allocation algorithms. Storage Management: Principles of I/O hardware, Principles of I/O software, Secondary storage structure, Disk structure, Disk scheduling, Disk Management, Swap-space Management, Disk reliability, Stable storage implementation. File Concept: File support, Access methods, Allocation methods, Directory systems, File Protection, Free Space management Protection & Security : Goals of protection, Domain of protection, Access matrix, Implementation of access matrix, Revocation of access rights, The security problem, Authentication, One-time passwords, Program threats, System threats, Threat monitoring, Encryption, Computer-security classification. Distributed Systems: Types of Distributed Operating System, Communication Protocols, Distributed File Systems, Naming and Transparency, Remote File Access, Stateful Versus Stateless Service, File Replication. Case Studies: Study of a representative Operating Systems.
Books Recommended:
CSE-304 Operating Systems Lab
1.5 Credits
Thread programming: Creating thread and thread synchronization. Process Programming: The Process ID, Running a New Process, Terminating a Process, Waiting for Terminated Child Processes, Users and Groups, Sessions and Process Groups. Concurrent Programming: Using fork, exec for multi-task programs. File Operations: File sharing across processes, System lock table, Permission and file locking, Mapping Files into Memory, Synchronized, Synchronous, and Asynchronous Operations, I/O Schedulers and I/O Performance.
Communicating across processes: Using different signals, Pipes, Message queue, Semaphore, Semaphore arithmetic and Shared memory.
Books Recommended:
CSE-315 Data Communication
3 Credits
Introduction to modulation techniques: Pulse modulation; pulse amplitude modulation, pulse width modulation and pulse position modulation. Pulse code modulation; quantization, Delta modulation. TDM, FDM, OOK, FSK, PSK, QPSK; Representation of noise; threshold effects in PCM and FM. Probability of error for pulse systems, concepts of channel coding and capacity. Asynchronous and synchronous communications. Hardware interfaces, multiplexers, concentrators and buffers. Communication medium, Fiber optics.
Books Recommended:
CSE-351 Management Information Systems
3 Credits
Introduction to MIS: Management Information System Concept. Definitions, Role of MIS, Approaches of MIS development. MIS and Computer: Computer Hardware for Information System, Computer Software for Information System, Data Communication System, Database Management Technology, Client-Server Technology. Decision-Support System: Introduction, Evolution of DSS, Future development of DSS. Application of MIS: Applications in manufacturing Sector, Applications in service sector, Case Studies.
Books Recommended:
CSE-403 Compiler Design
3 Credits
Introduction to compilers: Introductory concepts, types of compilers, applications, phases of a compiler. Lexical analysis: Role of the lexical analyzer, input buffering, token specification, recognition of tokens, symbol tables. Parsing: Parser and its role, context free grammars, top-down parsing. Syntax-directed translation: Syntax-directed definitions, construction of syntax trees, top-down translation. Type checking: Type systems, type expressions, static and dynamic checking of types, error recovery. Run-time organization: Run-time storage organization, storage strategies. Intermediate code generation: Intermediate languages, declarations, assignment statements. Code optimization: Basic concepts of code optimization, principal sources of optimization. Code generation. Features of some common compilers: Characteristic features of C, Pascal and Fortran compilers.
Books Recommended:
CSE-404 Compiler Design Lab
1.5 Credits
How to use scanner and parser generator tools (e.g., Flex, JFlex, CUP, Yacc, etc). For a given simple source language designing and implementing lexical analyzer, symbol tables, parser, intermediate code generator and code generator.
MTH-301 Statistics and Probability
2 Credits
Frequency distribution; mean, median, mode and other measures of central tendency, Standard deviation and other measures of dispersion, Moments, skewness and kurtosis, Elementary probability theory and discontinuous probability distribution, e.g. binomial, poison and negative binomial, Continuous probability distributions, e.g. normal and exponential, Characteristics of distributions, Hypothesis testing and regression analysis
Books Recommended:
CSE-333 Microprocessors and Assembly Language
3 Credits
Introduction to different types of microprocessors, Microprocessor architecture, instruction set, interfacing, I/O operation, interrupt structure, DMA, Microprocessor interface ICs. Advanced microprocessor concept of microprocessor based system design. Machine and Assembly instruction types and their formats. Character representation instructions. Instruction execution. Machine language programming. Instruction sets and their implementations. The Assembly process. Addressing methods. Subroutines, macros and files. I/O programming interrupts and concurrent processes.
Books Recommended:
CSE-334 Microprocessors and Assembly Language Lab
1.5 Credits
Laboratory works based on CSE 333.
CSE-339 Theory of Computation
2 Credits
Finite Automata: Deterministic and nondeterministic finite automata and their equivalence. Equivalence with regular expressions. Closure properties. The pumping lemma and applications. Context-free Grammars: Definitions. Parse trees. The pumping lemma for CFLs and applications. Normal forms. General parsing. Sketch of equivalence with pushdown automata. Turing Machines: Designing simple TMs. Variations in the basic model(multi-tape, multi-head, nondeterminism). Church-Turing thesis and evidence to support it through the study of other models. Undecidability: The undecidability of the halting problem. Reductions to other problems. Reduction in general.
Books Recommended:
CSE 401 Software Engineering
3 credits
Concepts of software engineering: requirements definition, modularity, structured design, data specifications, functional specifications, verification, documentation, software maintenance. Software support tools. Software project organization, quality assurance, management and communication skills.
Books Reccommended:
CSE-421 Computer Network
3 Credits
Network architectures-layered architectures and ISO reference model: data link protocols, error control, HDLC, X.25, flow and congestion control, virtual terminal protocol, data security. Local area networks, satellite networks, packet radio networks. Introduction to ARPANET, SNA and DECNET. Topological design and queuing models for network and distributed computing systems.
Books Recommended:
CSE-422 Computer Network Lab
1.5 Credits
Laboratory works based on CSE 421.
CSE-435 Computer Interfacing
3 Credits
Interface components and their characteristics, microprocessor I/O. Disk, Drums, and Printers. Optical displays and sensors. High power interface devices, transducers, stepper motors and peripheral devices.
Books Recommended:
CSE-436 Computer Interfacing Lab
1.5 Credits
Laboratory works based on CSE 435.
CSE-405 Artificial Intelligence & Expert System
3 Credits
What is Artificial Intelligence: The AI problems, The underlying assumption, What is an AI technique. Problems, Problem spaces and Search: Defining the problem as a state space search, Production system, Problem characteristics. Heuristics Search Techniques: Generate and Test, Hill climbing, Best First Search, Problem Reduction, Constraint Satisfaction, Means-Ends Analysis. Knowledge Representation Issues: Representation and Mappings, Approaches to knowledge Representation, Issues in Knowledge representation. Using Predicate logic: Representing simple facts in logic, Representing Instance and Isa relationships, Computable functions and Predicates, Resolution. Representing Knowledge using Rules: Procedural versus Declarative Knowledge, Logic Programming, Forward versus Backward Reasoning, Matching. Game playing: Overview, The Mimimax Search Procedure, Adding Alpha-Beta cutoffs, Additional refinements, iterative Deepening, Planning: Overview, An example Domain: The Blocks World, Components of a planning system, Goal stack planning, Understanding: What is Understanding, What makes Understanding hard, Understanding as constraint satisfaction. natural Language Processing: Introduction, Syntactic Processing, Semantic Analysis, Discourse and Pragmatic Processing. Expert systems: representing and using domain knowledge, Expert system shells explanation, Knowledge Acquisition. AI Programming Language: Prolog, LISP, Python.
Books Recommended:
CSE-406 Artificial Intelligence & Expert System Lab
1.5 Credits
Students will have to understand the functionalities of intelligent agents and how the agents will solve general problems. Students have to use a high-level language (Python, Prolog, LISP) to solve the following problems:
Backtracking: State space, Constraint satisfaction, Branch and bound. Example: 8-queen, 8- puzzle, Crypt-arithmetic. BFS and production: Water jugs problem, The missionaries and cannibal problem. Heuristic and recursion: Tic-tac-toe, Simple bock world, Goal stack planning, The tower of Hanoi. Question answering: The monkey and bananas problem.
CSE-425 Digital Signal Processing
3 Credits
Introduction to digital signal processing (DSP): Discrete-time signals and systems, analog to digital conversion, impulse response, finite impulse response (FIR) and infinite impulse response (IIR) of discrete-time systems, difference equation, convolution, transient and steady state response. Discrete transformations: Discrete Fourier series, discrete-time Fourier series, discrete Fourier transform (DFT) and properties, fast Fourier transform (FFT), inverse fast Fourier transform, z-transformation – properties, transfer function, poles and zeros and inverse z-transform. Correlation: circular convolution, auto-correlation and cross correlation. Digital Filters: FIR filters- linear phase filters, specifications, design using window, optimal and frequency sampling methods; IIR filters- specifications, design using impulse invariant, bi-linear z-transformation, least-square methods and finite precision effects. Digital signal processor TMS family, Application of digital signal processing.
Books Recommended:
CSE-426 Digital Signal Processing Lab
1.5 Credits
Laboratory works based on CSE 425.
CSE-431 Computer Graphics
3 Credits
Introduction to Graphical data processing. Fundamentals of interactive graphics programming. Architecture of display devices and connectivity to a computer. Implementation of graphics concepts of two-dimensional and three-dimensional viewing, clipping and transformations. Hidden line algorithms. Raster graphics concepts: Architecture, algorithms and other image synthesis methods. Design of interactive graphic conversations.
Books Recommended:
CSE-432 Computer Graphics Lab
1.5 Credits
Laboratory works based on CSE 431.
CSE-400 Project / Thesis
3 Credits
Study of problems in the field of Computer Science and Engineering. This course will be initiated in the 3^{rd} year or early in 4^{th} year.
CSE-402 Comprehensive Viva Voce
2 Credits
OPTIONAL COURSES
CSE-407 Simulation and Modeling
3 Credits
Simulation methods, model building, random number generator, statistical analysis of results, validation and verification techniques, Digital simulation of continuous systems. Simulation and analytical methods, for analysis of computer systems and practical problems in business and practice. Introduction to the simulation packages.
Books Recommended:
CSE-408 Simulation and Modeling Lab
1.5 Credits
Laboratory works based on CSE 407.
CSE-411 VLSI Design
3 Credits
Design and analysis techniques for VLSI circuits. Design of reliable VLSI circuits, noise considerations, design and operation of large fan out and fan in circuits, clocking methodologies, techniques for data path and data control design. Simulation techniques. Parallel processing, special purpose architectures in VLSI. VLSI layouts partitioning and placement routing and wiring in VLSI. Reliability aspects of VLSI design.
Books Recommended:
CSE-412 VLSI Design Lab
1.5 Credits
Laboratory works based on CSE 411.
CSE-413 Information System Design
3 Credits
Information, general concepts of formal information systems, analysis of information requirements for modern organizations, modern data processing technology and its application, information systems structures, designing information outputs, classifying and coding data, physical storage media considerations, logical data, organization, systems analysis, general systems design, detail systems design. Project management and documentation. Group development of an information system project. Includes all phases of software life cycles from requirement analysis to the completion of a fully implemented system.
Books Recommended:
CSE-414 Information System Design Lab
1.5 Credits
Laboratory works based on CSE 413.
CSE-419 Graph Theory
Introduction, Fundamental concepts, Trees, Spanning trees in graphs, Distance in graphs, Eulerian graphs, Digraphs, Matching and factors, Cuts and connectivity, k-connected graphs, Network flow problems, Graph coloring: vertex coloring and edge coloring, Line graphs, Hamiltonian cycles, Planar graphs, Perfect graphs.
Books Recommended:
CSE-420 Graph Theory Lab
Laboratory works based on CSE 420.
CSE-423 Computer System Performance Evaluations
3 Credits
Review of system analysis, approaches to system development, feasibility assessment, hardware and software acquisition. Procurement, workload characterization, the representation of measurement data, instrumentation: software monitors, hardware monitors, capacity planning, bottleneck detection, system and program tuning, simulation and analytical models and their application, case studies.
CSE-424 Computer System Performance Evaluation Lab
1.5 Credits
Laboratory based on CSE 423.
CSE-437 Pattern Recognition
3 Credits
Introduction to pattern recognition: features, classifications, learning. Statistical methods, structural methods and hybrid method. Applications to speech recognition, remote sensing and biomedical area, Learning algorithms. Syntactic approach: Introduction to pattern grammars and languages. parsing techniques. Pattern recognition in computer aided design.
CSE-438 Pattern Recognition Lab
1.0 Credits
Laboratory works based on CSE 437.
CSE-453 Digital Image Processing
Image Processing: Image Fundamentals, Image Enhancement: Background, Enhancement by Point-Processing, Spatial Filtering, Enhancement in Frequency Domain, Color Image Processing. Image Restoration: Degradation Model, Diagonalization of Circulant and Block-Circulant Matrices, Algebraic Approach to Restoration, Inverse Filtering, Geometric Transformation. Image Segmentation: Detection of Discontinuities, Edge Linking and Boundary Detection, Thresholding, Region-Oriented Segmentation, The use of Motion in Segmentation. Image Compression.
Books Recommended:
CSE-454 Digital Image Processing Lab
1.5 Credits
Laboratory works based on CSE 453.
CSE-455 Wireless and Sensor Networks
Introduction: applications; Localization and tracking: tracking multiple objects; Medium Access Control: S-MAC, IEEE 802.15.4 and ZigBee; Geographic and energy-aware routing; Attribute-Based Routing: directed diffusion, rumor routing, geographic hash tables; Infrastructure establishment: topology control, clustering, time synchronization; Sensor tasking and control: task-driven sensing, information-based sensor tasking, joint routing and information aggregation; Sensor network databases: challenges, querying the physical environment, in-network aggregation, data indices and range queries, distributed hierarchical aggregation; Sensor network platforms and tools: sensor node hardware, sensor network programming challenges; Other state-of-the-art related topics.
Books Recommended:
CSE-456 Wireless and Sensor Networks Lab
1.5 Credits
Laboratory works based on CSE 455.
CSE-457 Bio-Informatics
3 Credits
Cell concept: Structural organization of plant and animal cells, nucleus, cell membrane and cell wall. Cell division: Introducing chromosome, Mitosis, Meiosis and production of haploid/diploid cell. Nucleic acids: Structure and properties of different forms of DNA and RNA; DNA replication. Proteins: Structure and classification, Central dogma of molecular biology. Genetic code: A brief account. Genetics: Mendel’s laws of inheritance, Organization of genetic material of prokaryotes and eukaryotes, C-Value paradox, repetitive DNA, structure of chromatin – euchromatin and heterochromatin, chromosome organization and banding patterns, structure of gene – intron, exon and their relationships, overlapping gene, regulatory sequence (lac operon), Molecular mechanism of general recombination, gene conversion, Evolution and types of mutation, molecular mechanisms of mutation, site-directed mutagenesis, transposons in mutation. Introduction to Bioinformatics: Definition and History of Bioinformatics, Human Genome Project, Internet and Bioinformatics, Applications of Bioinformatics Sequence alignment: Dynamic programming. Global versus local. Scoring matrices. The Blast family of programs. Significance of alignments, Aligning more than two sequences. Genomes alignment. Structure-based alignment. Hidden Markov Models in Bioinformatics: Definition and applications in Bioinformatics. Examples of the Viterbi, the Forward and the Backward algorithms. Parameter estimation for HMMs. Trees: The Phylogeny problem. Distance methods, parsimony, bootstrap. Stationary Markov processes. Rate matrices. Maximum likelihood. Felsenstein’s post-order traversal. Finding regulatory elements: Finding regulatory elements in aligned and unaligned sequences. Gibbs sampling. Introduction to microarray data analysis: Steady state and time series microarray data. From microarray data to biological networks. Identifying regulatory elements using microarray data. Pi calculus: Description of biological networks; stochastic Pi calculus, Gillespie algorithm.
Books Recommended:
CSE-458 Bio-Informatics Lab
1.5 Credits
Laboratory works based on CSE-457.
CSE-461 Neural Networks
Fundamentals of Neural Networks; Back propagation and related training algorithms; Hebbian learning; Cohonen-Grossberg learning; The BAM and the Hopfield Memory; Simulated Annealing; Different types of Neural Networks: Counter propagation, Probabilistic, Radial Basis Function, Generalized Regression, etc; Adaptive Resonance Theory; Dynamic Systems and neural Control; The Boltzmann Machine; Self-organizing Maps; Spatiotemporal Pattern Classification, The Neocognition; Practical Aspects of Neural Networks.
Books Recommended:
CSE-462 Neural Networks Lab
1.5 Credits
Laboratory works based on CSE 461.
CSE-463 Machine Learning
3 Credits
Introduction: Definition of learning systems. Goals and applications of machine learning. Aspects of developing a learning system- training data, concept representation, function approximation. Inductive Classification: The concept learning task. Concept learning as search through a hypothesis space. General-to-specific ordering of hypotheses. Finding maximally specific hypotheses. Version spaces and the candidate elimination algorithm. Learning conjunctive concepts. The importance of inductive bias. Decision Tree Learning: Representing concepts as decision trees. Recursive induction of decision trees. Picking the best splitting attribute: entropy and information gain. Searching for simple trees and computational complexity. Occam’s razor. Overfitting, noisy data, and pruning. Experimental Evaluation of Learning Algorithms: Measuring the accuracy of learned hypotheses. Comparing learning algorithms- cross-validation, learning curves, and statistical hypothesis testing. Computational Learning Theory: Models of learnability- learning in the limit; probably approximately correct (PAC) learning. Sample complexity- quantifying the number of examples needed to PAC learn. Computational complexity of training. Sample complexity for finite hypothesis spaces. PAC results for learning conjunctions, kDNF, and kCNF. Sample complexity for infinite hypothesis spaces, Vapnik-Chervonenkis dimension. Rule Learning, Propositional and First-Order: Translating decision trees into rules. Heuristic rule induction using separate and conquer and information gain. First-order Horn-clause induction (Inductive Logic Programming) and Foil. Learning recursive rules. Inverse resolution, Golem, and Progol. Artificial Neural Networks: Neurons and biological motivation. Linear threshold units. Perceptrons: representational limitation and gradient descent training. Multilayer networks and backpropagation. Hidden layers and constructing intermediate, distributed representations. Overfitting, learning network structure, recurrent networks. Support Vector Machines: Maximum margin linear separators. Quadractic programming solution to finding maximum margin separators. Kernels for learning non-linear functions. Bayesian Learning: Probability theory and Bayes rule. Naive Bayes learning algorithm. Parameter smoothing. Generative vs. discriminative training. Logisitic regression. Bayes nets and Markov nets for representing dependencies. Instance-Based Learning: Constructing explicit generalizations versus comparing to past specific examples. k-Nearest-neighbor algorithm. Case-based learning. Text Classification: Bag of words representation. Vector space model and cosine similarity. Relevance feedback and Rocchio algorithm. Versions of nearest neighbor and Naive Bayes for text. Clustering and Unsupervised Learning: Learning from unclassified data. Clustering. Hierarchical Aglomerative Clustering. k-means partitional clustering. Expectation maximization (EM) for soft clustering. Semi-supervised learning with EM using labeled and unlabled data.
Books Recommended:
CSE-464 Machine Learning Lab
1.5 Credits.
Students should learn the methods for extracting rules or learning from data, and get the necessary mathematical background to understand how the methods work and how to get the best performance from them. To achieve these goals student should learn the following algorithms in the lab: K Nearest Neighbor Classifier, Decision Trees, Model Selection and Empirical Methodologies, Linear Classifiers: Perception and SVM, Naive Bayes Classifier, Basics of Clustering Analysis, K-mean Clustering Algorithm, Hierarchical Clustering Algorithm. Upon completion of the course, the student should be able to perform the followings: a. Evaluate whether a learning system is required to address a particular problem. b. Understand how to use data for learning, model selection, and testing to achieve the goals. c. Understand generally the relationship between model complexity and model performance, and be able to use this to design a strategy to improve an existing system. d. Understand the advantages and disadvantages of the learning systems studied in the course, and decide which learning system is appropriate for a particular application. e. Make a naive Bayes classifier and interpret the results as probabilities. f. Be able to apply clustering algorithms to simple data sets for clustering analysis.
CSE-465 Contemporary course on CSE
03 Credits
CSE-466 Contemporary course on CSE Lab
1.5 Credits
Laboratory works based on CSE 465