CHRIST (Deemed to University), Bangalore

DEPARTMENT OF PHYSICS AND ELECTRONICS

School of Sciences






Syllabus for

Academic Year  (2024)

 

ELE531 - EMBEDDED SYSTEMS AND IOT FUNDAMENTALS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This course on embedded systems provides the necessary theoretical background to understand and develop practical applications using the Arduino environment. It covers the basics of general embedded systems, standard peripherals and communication, operating systems and Arduino development environment and its applications. This course prepares students to acquire skills for their employability and also entrepreneurship in the future. Unit III caters to national and global needs. 

Learning Outcome

CO1: Describe embedded systems, their classification and explain the concept of standard peripheral communication

CO2: Differentiate between GPOS and RTOS concerning their functionalities

CO3: Discuss features of Arduino IDE and development board

CO4: Develop interfaces using I/O devices and write Arduino programs

Unit-1
Teaching Hours:15
Introduction to embedded systems and standard peripheral communication
 

Introduction, Comparison between embedded systems and general computing system, Major components of an embedded system, Block diagram, Processor embedded into a system, embedded hardware units in a system, Classification of embedded systems, applications, Case study of Digital thermometer, air conditioner, digital Camera,Pacemaker as embedded systems.

Classification of I/Os- synchronous serial input, synchronous serial output, Asynchronous serial input, Asynchronous serial output, parallel port on bit input, parallel port on bit output, parallel port input, parallel port output. Serial communication devices-basics of operating modes, Serial bus communication protocols. Fundamentals of I2C, CAN, USB and firewire (IEEE 1394) protocols, SPI and SCI. Basics of timer and counting devices.

Unit-1
Teaching Hours:15
Introduction to embedded systems and standard peripheral communication
 

Introduction, Comparison between embedded systems and general computing system, Major components of an embedded system, Block diagram, Processor embedded into a system, embedded hardware units in a system, Classification of embedded systems, applications, Case study of Digital thermometer, air conditioner, digital Camera,Pacemaker as embedded systems.

Classification of I/Os- synchronous serial input, synchronous serial output, Asynchronous serial input, Asynchronous serial output, parallel port on bit input, parallel port on bit output, parallel port input, parallel port output. Serial communication devices-basics of operating modes, Serial bus communication protocols. Fundamentals of I2C, CAN, USB and firewire (IEEE 1394) protocols, SPI and SCI. Basics of timer and counting devices.

Unit-2
Teaching Hours:15
Basics of operating systems and Arduino development environment
 

Operating system- services of an OS. User and supervisory mode structure, layers at the structure in the system, Kernel and process management function. Introduction to the real-time operating system (RTOS), Basic functions in RTOS, examples of RTOS, Hard real-time and soft real-time operations. Structural units and activities of an RTOS.

Introduction to Arduino environment, features, advantages, Programming overview, variables, logical and math operators. Digital and analog I/O functions, time functions, math functions, Control structure- for, while, case. Arduino IDE, basic program examples. Arduino hardware- types of boards, comparison of specifications, Arduino Uno board- specifications, basic architecture of AVR core, features of Atmega microcontroller.

Unit-2
Teaching Hours:15
Basics of operating systems and Arduino development environment
 

Operating system- services of an OS. User and supervisory mode structure, layers at the structure in the system, Kernel and process management function. Introduction to the real-time operating system (RTOS), Basic functions in RTOS, examples of RTOS, Hard real-time and soft real-time operations. Structural units and activities of an RTOS.

Introduction to Arduino environment, features, advantages, Programming overview, variables, logical and math operators. Digital and analog I/O functions, time functions, math functions, Control structure- for, while, case. Arduino IDE, basic program examples. Arduino hardware- types of boards, comparison of specifications, Arduino Uno board- specifications, basic architecture of AVR core, features of Atmega microcontroller.

Unit-3
Teaching Hours:15
Applications of Arduino and IOT fundamentals
 

Interfacing of I/O devices, simple analogue and digital input reading with a switch, reading analogue value, getting input from sensors- detecting light (LDR), movement (PIR sensor), sound (microphone, amplifier LM 386), heat (LM 35). Interface for visual output- LED, 7 segments LED and LCD module. Circuit and program examples for each.  Basics of motor driver circuit- H Bridge. Basics of stepper motor, Micro Servo motor interfacing and control programs.

Introduction to ARM processors, specifications, applications in embedded systems design Concept of IOT, basics of IOT architecture and applications.

Unit-3
Teaching Hours:15
Applications of Arduino and IOT fundamentals
 

Interfacing of I/O devices, simple analogue and digital input reading with a switch, reading analogue value, getting input from sensors- detecting light (LDR), movement (PIR sensor), sound (microphone, amplifier LM 386), heat (LM 35). Interface for visual output- LED, 7 segments LED and LCD module. Circuit and program examples for each.  Basics of motor driver circuit- H Bridge. Basics of stepper motor, Micro Servo motor interfacing and control programs.

Introduction to ARM processors, specifications, applications in embedded systems design Concept of IOT, basics of IOT architecture and applications.

Text Books And Reference Books:

[1]. Raj Kamal,(2015). Embedded systems- Architecture, programming and Design, (3rd Edition), Mc Graw Hill Education (India) private limited.

[2]. Prasad, K V K K,( 2004).Embedded/real-Time Systems: Concepts, Design and Programming: The Ultimate Reference, Wiley India.

[3]. Bailey, Oliver, (2005). Embedded Systems Design, Dream Tech Press.

[4]. Massimo Banzi, Michael Shiloh, (2007).Make Getting Started With Arduino, (3rd Edition.),.Shroff Publishers & Distributors.

Essential Reading / Recommended Reading

[1]. K.V. Shibu (2009). Introduction to the embedded system, (1st Edition.), McGraw Hill

[2]. Michael Margolis, (2011). Arduino Cookbook, O’Reilly Media Inc.

[3]. John Nussey, (2005). Arduino For Dummies, John Wiley & Sons Inc (Sea) Pvt Ltd, 

[4]. Dream Tech Software Team, (2002). Programming for Embedded Systems, Create Tomorrows Embedded Systems Today, Wiley India

Evaluation Pattern

No.

Components

Marks

CIA 1

Assignment/Test

10

CIA2

Mid Semester Exam

25

CIA 3

Quiz, online test, presentation, minor project,

Industry/Educational Visits

10

Attendance

 

05

ESE

 

50

Total

100

ELE541A - OPTOELECTRONIC DEVICES AND COMMUNICATION (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Optical fiber communication systems have revolutionized our global telecommunications network. With their very high data rates and capacity, optical fiber systems link continents, countries, cities and end-users. They have enabled the internet and changed our society. This paper provides comprehensive coverage of the field of electronic communication and various technologies using fibre optics. The principles of operation and properties of optoelectronic components, as well as the signal guiding characteristics of glass fibres, are discussed. Units I to III caters to local and regional needs. 

Learning Outcome

CO1: Develop an understanding of basic phenomena in the area of Optoelectronics devices and their working.

CO2: The knowledge acquired in the course helps apply their skills in designing communication link systems for national and global communication needs.

CO3: Demonstrate different network topologies

CO4: Illustrate various optical networks

Unit-1
Teaching Hours:15
Optoelectronic devices
 

Classification of photonic devices, Interaction of matter and radiations, LED, construction, heterojunction structures, materials, working, characteristics and applications, Semiconductor diode laser, condition for amplification, laser cavity, construction details, characteristics & applications, photodetectors, photoconductors, PIN photodiode, avalanche photodiode, metal-semiconductor-metal (MSM) photo-detector photo-transistor, photomultiplier tube, comparison of photo-detectors.

Unit-1
Teaching Hours:15
Optoelectronic devices
 

Classification of photonic devices, Interaction of matter and radiations, LED, construction, heterojunction structures, materials, working, characteristics and applications, Semiconductor diode laser, condition for amplification, laser cavity, construction details, characteristics & applications, photodetectors, photoconductors, PIN photodiode, avalanche photodiode, metal-semiconductor-metal (MSM) photo-detector photo-transistor, photomultiplier tube, comparison of photo-detectors.

Unit-2
Teaching Hours:15
Basics of optical fiber communication and optical amplifier networks
 

Introduction, Historical development, General OFC system, need for lightwave communication, advantages, disadvantages and applications of optical fiber communication, optical fiber waveguides, Ray transmission theory, cylindrical fiber, Types of rays, optical fiber modes and configurations, fiber profiles, cut-off wavelength, and mode field diameter. Optical fiber materials, plastic optical fiber, Speciality optical fiber, photonic crystal fiber, fiber optic cables. Indoor and Outdoor fiber optic cables

 

Optical amplifiers, Block diagram. Basic applications and types. Semiconductor optical amplifiers (SDA). EDFA (Erbium-doped fiber amplifier). Introduction to optical networks. Network topologies. Introduction to synchronous optical network/synchronous digital hierarchy (SONET/SDH)

Unit-2
Teaching Hours:15
Basics of optical fiber communication and optical amplifier networks
 

Introduction, Historical development, General OFC system, need for lightwave communication, advantages, disadvantages and applications of optical fiber communication, optical fiber waveguides, Ray transmission theory, cylindrical fiber, Types of rays, optical fiber modes and configurations, fiber profiles, cut-off wavelength, and mode field diameter. Optical fiber materials, plastic optical fiber, Speciality optical fiber, photonic crystal fiber, fiber optic cables. Indoor and Outdoor fiber optic cables

 

Optical amplifiers, Block diagram. Basic applications and types. Semiconductor optical amplifiers (SDA). EDFA (Erbium-doped fiber amplifier). Introduction to optical networks. Network topologies. Introduction to synchronous optical network/synchronous digital hierarchy (SONET/SDH)

Unit-3
Teaching Hours:15
Transmission characteristics of optical fiber, optical couplers, optical receivers and optical links
 

Introduction, Attenuation, absorption, scattering losses, bending loss, dispersion, Intra modal dispersion, and Intermodal dispersion. Introduction to couplers & connectors, fiber alignment and joint loss, single-mode fiber joints, fiber splices, fiber connectors and fiber couplers. Optical Receiver Operation, receiver sensitivity, quantum limit, coherent detection, Analog receivers & Digital receivers, Analog links, Introduction, an overview of analogue links, carrier noise ratio (CNR), multichannel transmission techniques,  Digital links – Introduction, Overview of digital links.

Unit-3
Teaching Hours:15
Transmission characteristics of optical fiber, optical couplers, optical receivers and optical links
 

Introduction, Attenuation, absorption, scattering losses, bending loss, dispersion, Intra modal dispersion, and Intermodal dispersion. Introduction to couplers & connectors, fiber alignment and joint loss, single-mode fiber joints, fiber splices, fiber connectors and fiber couplers. Optical Receiver Operation, receiver sensitivity, quantum limit, coherent detection, Analog receivers & Digital receivers, Analog links, Introduction, an overview of analogue links, carrier noise ratio (CNR), multichannel transmission techniques,  Digital links – Introduction, Overview of digital links.

Text Books And Reference Books:

[1]. Gerd Keiser, (2013). Optical fiber communications, (5th Edition), MGH company.

[2]. John M. Senior, (2013). Optical fiber communications- Principles & Practice, (3rd Edition), Pearson.

Essential Reading / Recommended Reading

[1]. Joseph c. Palais (2006). Fiber optic communications, (4th Edition), Pearson.

 [2]. J.Wilson, J.F.B . Hawkes(2010.). Optoelectronics-An Introduction, (2nd Edition), PHI.

Evaluation Pattern

No.

Components

Marks

CIA 1

Assignment

10

CIA2

MSE

25

CIA 3

Quiz, MCQ test, presentation, minor project, MOOC

10

Attendance

 

05

ESE

 

50

Total

100

 

ELE541B - ELECTRONIC INSTRUMENTATION (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This Paper will enable the students to get a thorough knowledge of measuring instruments and their measuring techniques. Any instrument consists of an input sensing element or transducer, signal conditioner and display unit. So the basic principles and applications of the transducers, signal conditioners, data acquisition systems and digital instruments are covered. The students are introduced to biomedical instrumentation as it is an emerging area of instrumentation and pc based on instrumentation. Units II and III caters to regional and national needs.

Learning Outcome

CO1: Analyse the performance characteristics and applications of electronic transducers and instruments

CO2: Demonstrate the signal conditioning concepts and analyse the circuits

CO3: Design and develop the data acquisition and conversion systems using various Electronic instruments and biomedical instruments

CO4: Design and develop PC based instrumentation systems

Unit-1
Teaching Hours:15
Transducers
 

Introduction, Basic concepts of measurement, Block diagram of a measurement system, Performance characteristics: static and dynamic Errors in measurement, Types of errors, sources of errors, dynamic characteristics.

 Electrical transducers,  Selecting a transducer, classification of transducers-, Resistive, capacitive and inductive transducers- Strain gauge- types- un-bonded, bonded metal wire, foil and semiconductor types, Thermistor - temp characteristics, Thermocouple, IC temperature sensors LM 34/35 Resistance thermometer,  Inductive transducers-Reluctance type- Linear variable differential transformer (LVDT), Capacitive transducer, Pressure transducer, Photoelectric transducers, Piezoelectric transducer.

Unit-1
Teaching Hours:15
Transducers
 

Introduction, Basic concepts of measurement, Block diagram of a measurement system, Performance characteristics: static and dynamic Errors in measurement, Types of errors, sources of errors, dynamic characteristics.

 Electrical transducers,  Selecting a transducer, classification of transducers-, Resistive, capacitive and inductive transducers- Strain gauge- types- un-bonded, bonded metal wire, foil and semiconductor types, Thermistor - temp characteristics, Thermocouple, IC temperature sensors LM 34/35 Resistance thermometer,  Inductive transducers-Reluctance type- Linear variable differential transformer (LVDT), Capacitive transducer, Pressure transducer, Photoelectric transducers, Piezoelectric transducer.

Unit-2
Teaching Hours:15
Signal conditioning and data acquisition
 

Introduction, Block diagram of signal conditioning, Voltage to Current converter, Current to Voltage converter, and the expression for output. Practical integrator and differentiator circuit, frequency response, Logarithmic amplifier, circuit description and output expression.Basic Instrumentation amplifier- important features, basic instrumentation amplifier- block diagram, realization using 3 op-amps, differential instrumentation amplifier using transducer Bridge, output voltage derivation.

Introduction, general data acquisition system (DAS), the objective of DAS, Single-channel and multi-channel DAS block diagrams qualitative description, Functional blocks of a data acquisition configuration, Digital to Analog converter- R-2R ladder and binary-weighted ladder circuits, brief analysis, D to A using op-amp summing amplifier, Analog to Digital converter- Successive approximation method, Flash ADC, block diagram explanation, Introduction to Lab view.

Unit-2
Teaching Hours:15
Signal conditioning and data acquisition
 

Introduction, Block diagram of signal conditioning, Voltage to Current converter, Current to Voltage converter, and the expression for output. Practical integrator and differentiator circuit, frequency response, Logarithmic amplifier, circuit description and output expression.Basic Instrumentation amplifier- important features, basic instrumentation amplifier- block diagram, realization using 3 op-amps, differential instrumentation amplifier using transducer Bridge, output voltage derivation.

Introduction, general data acquisition system (DAS), the objective of DAS, Single-channel and multi-channel DAS block diagrams qualitative description, Functional blocks of a data acquisition configuration, Digital to Analog converter- R-2R ladder and binary-weighted ladder circuits, brief analysis, D to A using op-amp summing amplifier, Analog to Digital converter- Successive approximation method, Flash ADC, block diagram explanation, Introduction to Lab view.

Unit-3
Teaching Hours:15
Electronic instruments and PC-based instrumentation
 

Digital voltmeter, performance characteristics, ramp type and dual slope type digital voltmeters, Digital multimeter, resolution and sensitivity of digital multimeter. LCR Meter, Signal generator, Function generator, CRT, vertical and horizontal deflection, Storage Oscilloscopes- analogue and digital, Bio-Medical instrumentation- Bioelectric potentials, ECG, EEG, EMG.                                                                                                 The general form of PC based instrumentation system Data acquisition using serial interfaces, serial connection formats, serial communication modes, serial interface standards (RS 232), Features of USB, i2c, spi BUS type of communication protocols.

Unit-3
Teaching Hours:15
Electronic instruments and PC-based instrumentation
 

Digital voltmeter, performance characteristics, ramp type and dual slope type digital voltmeters, Digital multimeter, resolution and sensitivity of digital multimeter. LCR Meter, Signal generator, Function generator, CRT, vertical and horizontal deflection, Storage Oscilloscopes- analogue and digital, Bio-Medical instrumentation- Bioelectric potentials, ECG, EEG, EMG.                                                                                                 The general form of PC based instrumentation system Data acquisition using serial interfaces, serial connection formats, serial communication modes, serial interface standards (RS 232), Features of USB, i2c, spi BUS type of communication protocols.

Text Books And Reference Books:

[1]. H.S.Kalsi,(2010). Electronic Instrumentation, (2nd Edition), TMH,.

[2]. W.D. Cooper, A.D. Helfrick, (2008). Electronic Instrumentation and Measuring Techniques, 3rd Edition, PHI.

Essential Reading / Recommended Reading

[1]. A.K. Sawhney, Dhanpat Rai & sons, (2008). A Course in Electrical, Electronics Measurement and Instrumentation, BPB publications.

[2]. C.S.Rangan, G.R.Sarma, VSV Mani, (2008).Instrumentation devices and systems,(2nd Edition.), TMH.

[3]. N. Mathivanan (2011).PC based instrumentation, (3rd Edition.), PHI.

Evaluation Pattern

No.

Components

Marks

CIA 1

Assignment

10

CIA2

MSE

25

CIA 3

Quiz, MCQ test, presentation, minor project, MOOC,

Industry/Educational Visits, Awareness campaign on E-waste, health hazards of mobile telephony etc

10

Attendance

 

05

ESE

Centralized written examination

50

Total

100

 

ELE541C - DIGITAL SIGNALS AND SYSTEM ARCHITECTURE (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This paper is designed to understand the fundamentals of signals, systems and digital signal processing. Digital and analogue signals are introduced, followed by their processing through various mathematical techniques. Basic concepts for continuous-time and discrete-time signals in the time and frequency domains are also covered. Electronic systems are introduced with the relation between the output and the input. The mathematical modelling of different types of systems is also detailed.

Learning Outcome

CO1: Illustrate different types of signals and their processing

CO2: Demonstrate the fundamentals and applications of signal processing.

CO3: Analyze how various kinds of signals and systems are processed practically

CO4: Illustrate the architecture of digital signal processors

CO5: Develop skills for international needs and cultivate entrepreneurship.

Unit-1
Teaching Hours:15
Signals and its classifications
 

Introduction and Classification of signals: Definition of signal and systems, communication and control systems as examples. Sampling of analogue signals, Continuous-time and discrete-time signals, Classification of signals as even, odd, periodic and non-periodic, deterministic and non-deterministic, energy and power. Elementary signals/Functions: exponential, sine, impulse, step and its properties, ramp, rectangular, triangular, signum, sync functions. Operations on signals: Amplitude scaling, addition, multiplication, differentiation, integration, time scaling, time-shifting and time folding.

Unit-1
Teaching Hours:15
Signals and its classifications
 

Introduction and Classification of signals: Definition of signal and systems, communication and control systems as examples. Sampling of analogue signals, Continuous-time and discrete-time signals, Classification of signals as even, odd, periodic and non-periodic, deterministic and non-deterministic, energy and power. Elementary signals/Functions: exponential, sine, impulse, step and its properties, ramp, rectangular, triangular, signum, sync functions. Operations on signals: Amplitude scaling, addition, multiplication, differentiation, integration, time scaling, time-shifting and time folding.

Unit-2
Teaching Hours:15
Digital Signal Processing and architecture
 

Signal sensing and acquisition: Basic Architectural features, DSP Computational Building Blocks, Bus Architecture and Memory, Data Addressing Capabilities, Address Generation Unit, Programmability and Program Execution, Speed Issues, Hardware looping, Interrupts, Stacks, Relative Branch support, Pipelining and Performance, Pipeline Depth, Interlocking, Branching effects, Interrupt effects, Pipeline Programming models.

Unit-2
Teaching Hours:15
Digital Signal Processing and architecture
 

Signal sensing and acquisition: Basic Architectural features, DSP Computational Building Blocks, Bus Architecture and Memory, Data Addressing Capabilities, Address Generation Unit, Programmability and Program Execution, Speed Issues, Hardware looping, Interrupts, Stacks, Relative Branch support, Pipelining and Performance, Pipeline Depth, Interlocking, Branching effects, Interrupt effects, Pipeline Programming models.

Unit-3
Teaching Hours:15
TMS320C67XX Processor
 

Commercial Digital signal-processing Devices, Data Addressing modes of TMS320C67XX DSPs, Data Addressing modes of TMS320C6713 Processor, Memory space of the Processor, Program Control, instructions and Programming, On-Chip Peripherals, Interrupts of the processor, Pipeline Operations. Qualitative transformations on signals - Fourier transformations (qualitative).

Unit-3
Teaching Hours:15
TMS320C67XX Processor
 

Commercial Digital signal-processing Devices, Data Addressing modes of TMS320C67XX DSPs, Data Addressing modes of TMS320C6713 Processor, Memory space of the Processor, Program Control, instructions and Programming, On-Chip Peripherals, Interrupts of the processor, Pipeline Operations. Qualitative transformations on signals - Fourier transformations (qualitative).

Text Books And Reference Books:

 [1]. Alan V. Oppenheim, Alan S.Willsky, S.Hamid Nawab, (2015). Signals and Systems, (62nd Edition), Peason.

 [2]. A. Anand Kumar, (2013). Signals and Systems (3rd Edition), PHI.

 [3]. P. Ramesh Babu, (2014). Digital Signal Processing, 6th Edition, Scitech.

Essential Reading / Recommended Reading

 [1]. Nagoor Kani, (2010). Signals and Systems,(2nd Edition.), McGraw Hill Education.

 [2]. Taan S. ElAli, (2012). Discrete Systems and Digital Signal Processing with Matlab, (2nd Edition.), Taylor and Francis.

Evaluation Pattern

 

No.

Components

Marks

CIA 1

Assignment, MCQ test.

10

CIA2

MSE

25

CIA 3

Quiz, MCQ test, presentation.

10

Attendance

 

05

ESE

 

50

Total

100

ELE551 - EMBEDDED SYSTEMS AND IOT FUNDAMENTALS LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

This practical course covers the study of the Arduino development platform, writing the programs and implementing practical applications using Arduino Uno.

The course has a provision for conducting all the experiments virtually using an online tool in tinkercad.com. This course focusses on electronics design skills for employment and entrepreneurship.

 

Learning Outcome

CO1: Acquire skills in using Arduino Environment and writing programs

CO2: Interface various I/O devices and implement applications using the Arduino Uno development board

CO3: Verify the design and programs using the Tinkercad web tool

Unit-1
Teaching Hours:30
List of Experiments
 

1. Installation and setting up of Arduino

2. Uploading and running sample programs

3. Interfacing of LED

4. Fading of LED using PWM

5. Reading analog voltage using Potentiometer

6. Interfacing of Pushbuttons

7. Interfacing of a Photo Resistor (LDR)

8. Interfacing of a Relay

9. Interfacing of a dc Motor

10. Interfacing of a Single Servo

11. Interfacing Liquid crystal display (LCD) module

12. Interfacing Ultra sound Sensor for distance measurement

Unit-1
Teaching Hours:30
List of Experiments
 

1. Installation and setting up of Arduino

2. Uploading and running sample programs

3. Interfacing of LED

4. Fading of LED using PWM

5. Reading analog voltage using Potentiometer

6. Interfacing of Pushbuttons

7. Interfacing of a Photo Resistor (LDR)

8. Interfacing of a Relay

9. Interfacing of a dc Motor

10. Interfacing of a Single Servo

11. Interfacing Liquid crystal display (LCD) module

12. Interfacing Ultra sound Sensor for distance measurement

Text Books And Reference Books:

[1] Web reference for Arduino Uno development board and programming, www. arduino.cc

[2].Michael Margolis, (2011).Arduino Cookbook, O’Reilly Media Inc.

Essential Reading / Recommended Reading

[3] Web reference for Arduino based projects, https://www.tinkercad.com/circuits

Evaluation Pattern

No.

Components

Marks

CIA

pre-lab work, class work, MSE/exhibition

25

ESE

(two examiners)

25

Total

50

ELE551A - OPTOELECTRONIC DEVICES AND COMMUNICATION LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

This course describes the technical features and specifications of the optical fiber communication training kit. Students will be able to perform different types of experiments to understand basic fiber optical communications. The kit demonstrates the properties of fiber optic transmitters and receivers, characteristics of fiber optic cables, different types of modulation and demodulation techniques, and PC to PC communication via fiber optic link using the RS232 interface. It can also be used to demonstrate various digital communication techniques via fiber-optic links.

Learning Outcome

CO1: Acquire and apply knowledge in Optoelectronics using real components and devices.

CO2: Acquire skills to meet the growing demand of the optoelectronic industry.

CO3: Design and analyze various digital and analog optical fiber systems.

CO4: Design, model, and simulate different optical systems using industry-relevant software.

Unit-1
Teaching Hours:30
List of Experiments:
 

1.     Setting up an Analog and Digital fiber link

2.     Measurement of Propagation or Attenuation Loss in the optical fiber

3.     Study of bending loss in optical fiber

4.     Calculation of Numerical Aperture of optical fiber

5.     Study of V I characteristics of Light-emitting diode

6.     Study the characteristics of Photodiode and phototransistor

7.     Study of voice transmission through fiber optic link

8.     PC to PC communications through fiber optic link

 9.     Study of modulation techniques (AM, FM, and PWM)

Unit-1
Teaching Hours:30
List of Experiments:
 

1.     Setting up an Analog and Digital fiber link

2.     Measurement of Propagation or Attenuation Loss in the optical fiber

3.     Study of bending loss in optical fiber

4.     Calculation of Numerical Aperture of optical fiber

5.     Study of V I characteristics of Light-emitting diode

6.     Study the characteristics of Photodiode and phototransistor

7.     Study of voice transmission through fiber optic link

8.     PC to PC communications through fiber optic link

 9.     Study of modulation techniques (AM, FM, and PWM)

Text Books And Reference Books:

[1]. Gerd Keiser, (2013). Optical fiber communications, (5th Edition), MGH company.

[2]. John M. Senior, (2013). Optical fiber communications- Principles & Practice, (3rd Edition), Pearson.

[3]. Scientech 2501 optical fiber communication trainer kit reference manual and tutorials.

[4]. Opti system 17.1 user’s manual and tutorials (www.optiwave.com).

Essential Reading / Recommended Reading

[1]. Joseph c. Palais (2006). Fiber optic communications, (4th Edition), Pearson.

[2]. J.Wilson, J.F.B . Hawkes (2010.). Optoelectronics-An Introduction, (2nd Edition), PHI.

Evaluation Pattern

 

No.

Components

Marks

CIA

pre-lab work, class work, MSE

25

ESE

(two examiners)

25

Total

50

ELE551B - ELECTRONIC INSTRUMENTATION LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

 

This course provides laboratory hours that allow students the opportunity to enhance their understanding of how to construct, analyse and troubleshoot basic signal conditioning and instrumentation amplifier circuits using basic ICs and discrete components. These topics will enhance their basic skills which in turn can be useful for global industrial requirements.

 

Learning Outcome

CO1: Impart the concepts of signal conditioning using op-amps and instrumentation amplifiers practically

CO2: Demonstrate the basic experimental techniques in the operation of instrumentation amplifier based circuits and their applications

CO3: Design and develop different data acquisition techniques using sensors

CO4: Design, simulate and analyse electronic instrumentation elements using software like EWB, Multisim, etc.

Unit-1
Teaching Hours:30
List of experiments
 

 

1.     Op-amp Integrator –Frequency response & waveforms.

 

2.     Op-amp Differentiator –Frequency response & waveforms.

 

3.     Capacitance Meter using IC 555

 

4.     Instrumentation amplifier.

 

5.     DAC with binary-weighted resistors 

 

6.     Study of DAC using IC 0804

 

7.     Interfacing of an ADC to a Computer port

 

8.     Flash ADC – IC Quad op-amp

 

9.     Frequency counter

 

10.  Familiarization with basic transducers by using a trainer kit.

 

11.  Characteristics of a phototransistor

12.  Acquisition of temperature sensor data through bridge circuit and Instrumentation amplifier.

Unit-1
Teaching Hours:30
List of experiments
 

 

1.     Op-amp Integrator –Frequency response & waveforms.

 

2.     Op-amp Differentiator –Frequency response & waveforms.

 

3.     Capacitance Meter using IC 555

 

4.     Instrumentation amplifier.

 

5.     DAC with binary-weighted resistors 

 

6.     Study of DAC using IC 0804

 

7.     Interfacing of an ADC to a Computer port

 

8.     Flash ADC – IC Quad op-amp

 

9.     Frequency counter

 

10.  Familiarization with basic transducers by using a trainer kit.

 

11.  Characteristics of a phototransistor

12.  Acquisition of temperature sensor data through bridge circuit and Instrumentation amplifier.

Text Books And Reference Books:

 

[1]. H.S.Kalsi,(2010). Electronic Instrumentation, (2nd Edition), TMH,.

 

[2]. W.D. Cooper, A.D. Helfrick, (2008). Electronic Instrumentation and Measuring Techniques, 3rd Edition, PHI.

 

Essential Reading / Recommended Reading

 

[1]. A.K. Sawhney, Dhanpat Rai & sons, (2008). A Course in Electrical, Electronics Measurement and Instrumentation, BPB publications.

 

[2]. C.S.Rangan, G.R.Sarma, VSV Mani, (2008).Instrumentation devices and systems,(2nd Edition.), TMH.

 

[3]. N. Mathivanan (2011).PC-based instrumentation, (3rd Edition.), PHI.

 

Evaluation Pattern

 

No.

Components

Marks

CIA

pre-lab work, class work, MSE

25

ESE

(two examiners)

25

Total

50

 

ELE551C - DIGITAL SIGNALS AND SYSTEM ARCHITECTURE LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

This practical course covers the fundamentals of signals and systems. Basic simulation of signals and systems and signal processing through various mathematical techniques using GNU Octave /MATLAB/Python will be carried out. 

 

Learning Outcome

CO1: Demonstrate the basic programming in MATLAB/Python/Octave

CO2: Simulate and analyze different types of signals and model how they can be processed

CO5: Develop skills toward national and international job requirements in the field of signals and systems

Unit-1
Teaching Hours:30
List of experiments
 

 

1. Introduction to Octave

 

2. Plotting Elementary signals

 

3. Plotting of continuous-time and discrete-time signals

 

4. Sampling of signals

 

5. Periodic and non-periodic signals

 

6. Even and odd signals

 

7. Operations on signals for the independent variable

 

8. Operations on signals for the dependent variable

 

9. Modulation of signals

 

Unit-1
Teaching Hours:30
List of experiments
 

 

1. Introduction to Octave

 

2. Plotting Elementary signals

 

3. Plotting of continuous-time and discrete-time signals

 

4. Sampling of signals

 

5. Periodic and non-periodic signals

 

6. Even and odd signals

 

7. Operations on signals for the independent variable

 

8. Operations on signals for the dependent variable

 

9. Modulation of signals

 

Text Books And Reference Books:

 

[1]. Alan V. Oppenheim, Alan S.Willsky, S.Hamid Nawab, (2015).Signals and Systems, (62nd Edition), Peason.

 

[2]. A. Anand Kumar, (2013).Signals and Systems, (3rd Edition.), PHI.

 

[3]. Nagoor Kani, (2010).Signals and Systems, (2nd Edition.), McGraw Hill Education.

 

Essential Reading / Recommended Reading

 

[1]. Alan V. Oppenheim, Alan S.Willsky, S.Hamid Nawab, (2015).Signals and Systems, (62nd Edition), Peason.

 

[2]. A. Anand Kumar, (2013).Signals and Systems, (3rd Edition.), PHI.

 

[3]. Nagoor Kani, (2010).Signals and Systems, (2nd Edition.), McGraw Hill Education.

 

Evaluation Pattern

 

No.

Components

Marks

CIA

pre-lab work, class work, MSE

25

ESE

(two examiners)

25

Total

50

 

MAT531 - LINEAR ALGEBRA (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description:

This course aims at developing the ability to write the mathematical proofs. It helps the students to understand and appreciate the beauty of the abstract nature of mathematics and also to develop a solid foundation of theoretical mathematics.

Course Objectives : This course will help the learner to

COBJ1. understand the theory of matrices, concepts in vector spaces and Linear Transformations.

COBJ2. gain problems solving skills in solving systems of equations using matrices, finding eigenvalues and eigenvectors, vector spaces and linear transformations.

Learning Outcome

CO1: On successful completion of the course, the students should be able to use properties of matrices to solve systems of equations and explore eigenvectors and eigenvalues.

CO2: On successful completion of the course, the students should be able to understand the concepts of vector space, basis, dimension, and their properties.

CO3: On successful completion of the course, the students should be able to analyse the linear transformations in terms of matrices.

Unit-1
Teaching Hours:15
Matrices and System of linear equations
 

Elementary row operations, rank, inverse of a matrix using row operations, Echelon forms, normal forms, system of homogeneous and non-homogeneous equations, Cayley Hamilton theorem, eigenvalues and eigenvectors, diagonalization of square matrices.

Unit-1
Teaching Hours:15
Matrices and System of linear equations
 

Elementary row operations, rank, inverse of a matrix using row operations, Echelon forms, normal forms, system of homogeneous and non-homogeneous equations, Cayley Hamilton theorem, eigenvalues and eigenvectors, diagonalization of square matrices.

Unit-1
Teaching Hours:15
Matrices and System of linear equations
 

Elementary row operations, rank, inverse of a matrix using row operations, Echelon forms, normal forms, system of homogeneous and non-homogeneous equations, Cayley Hamilton theorem, eigenvalues and eigenvectors, diagonalization of square matrices.

Unit-1
Teaching Hours:15
Matrices and System of linear equations
 

Elementary row operations, rank, inverse of a matrix using row operations, Echelon forms, normal forms, system of homogeneous and non-homogeneous equations, Cayley Hamilton theorem, eigenvalues and eigenvectors, diagonalization of square matrices.

Unit-1
Teaching Hours:15
Matrices and System of linear equations
 

Elementary row operations, rank, inverse of a matrix using row operations, Echelon forms, normal forms, system of homogeneous and non-homogeneous equations, Cayley Hamilton theorem, eigenvalues and eigenvectors, diagonalization of square matrices.

Unit-1
Teaching Hours:15
Matrices and System of linear equations
 

Elementary row operations, rank, inverse of a matrix using row operations, Echelon forms, normal forms, system of homogeneous and non-homogeneous equations, Cayley Hamilton theorem, eigenvalues and eigenvectors, diagonalization of square matrices.

Unit-1
Teaching Hours:15
Matrices and System of linear equations
 

Elementary row operations, rank, inverse of a matrix using row operations, Echelon forms, normal forms, system of homogeneous and non-homogeneous equations, Cayley Hamilton theorem, eigenvalues and eigenvectors, diagonalization of square matrices.

Unit-2
Teaching Hours:15
Vector Spaces
 

Vector space-examples and properties, subspaces-criterion for a subset to be a subspace, linear span of a set, linear combination, linear independent and dependent subsets, basis and dimensions, and standard properties.

Unit-2
Teaching Hours:15
Vector Spaces
 

Vector space-examples and properties, subspaces-criterion for a subset to be a subspace, linear span of a set, linear combination, linear independent and dependent subsets, basis and dimensions, and standard properties.

Unit-2
Teaching Hours:15
Vector Spaces
 

Vector space-examples and properties, subspaces-criterion for a subset to be a subspace, linear span of a set, linear combination, linear independent and dependent subsets, basis and dimensions, and standard properties.

Unit-2
Teaching Hours:15
Vector Spaces
 

Vector space-examples and properties, subspaces-criterion for a subset to be a subspace, linear span of a set, linear combination, linear independent and dependent subsets, basis and dimensions, and standard properties.

Unit-2
Teaching Hours:15
Vector Spaces
 

Vector space-examples and properties, subspaces-criterion for a subset to be a subspace, linear span of a set, linear combination, linear independent and dependent subsets, basis and dimensions, and standard properties.

Unit-2
Teaching Hours:15
Vector Spaces
 

Vector space-examples and properties, subspaces-criterion for a subset to be a subspace, linear span of a set, linear combination, linear independent and dependent subsets, basis and dimensions, and standard properties.

Unit-2
Teaching Hours:15
Vector Spaces
 

Vector space-examples and properties, subspaces-criterion for a subset to be a subspace, linear span of a set, linear combination, linear independent and dependent subsets, basis and dimensions, and standard properties.

Unit-3
Teaching Hours:15
Linear Transformations
 

Linear transformations, properties, matrix of a linear transformation, change of basis, range and kernel, rank and nullity, rank-nullity theorem, non-singular linear transformation, eigenvalues and eigenvectors of a linear transformation.

Unit-3
Teaching Hours:15
Linear Transformations
 

Linear transformations, properties, matrix of a linear transformation, change of basis, range and kernel, rank and nullity, rank-nullity theorem, non-singular linear transformation, eigenvalues and eigenvectors of a linear transformation.

Unit-3
Teaching Hours:15
Linear Transformations
 

Linear transformations, properties, matrix of a linear transformation, change of basis, range and kernel, rank and nullity, rank-nullity theorem, non-singular linear transformation, eigenvalues and eigenvectors of a linear transformation.

Unit-3
Teaching Hours:15
Linear Transformations
 

Linear transformations, properties, matrix of a linear transformation, change of basis, range and kernel, rank and nullity, rank-nullity theorem, non-singular linear transformation, eigenvalues and eigenvectors of a linear transformation.

Unit-3
Teaching Hours:15
Linear Transformations
 

Linear transformations, properties, matrix of a linear transformation, change of basis, range and kernel, rank and nullity, rank-nullity theorem, non-singular linear transformation, eigenvalues and eigenvectors of a linear transformation.

Unit-3
Teaching Hours:15
Linear Transformations
 

Linear transformations, properties, matrix of a linear transformation, change of basis, range and kernel, rank and nullity, rank-nullity theorem, non-singular linear transformation, eigenvalues and eigenvectors of a linear transformation.

Unit-3
Teaching Hours:15
Linear Transformations
 

Linear transformations, properties, matrix of a linear transformation, change of basis, range and kernel, rank and nullity, rank-nullity theorem, non-singular linear transformation, eigenvalues and eigenvectors of a linear transformation.

Text Books And Reference Books:

1. S. Narayan and P.K. Mittal, Text book of Matrices, 10th ed., New Delhi: S Chand and Co. Ltd, 2004.

2. V. Krishnamurthy, V. P. Mainra, and J. L. Arora, An introduction to linear algebra. New Delhi, India: Affiliated East East-West Press Pvt Ltd., 2003.

Essential Reading / Recommended Reading

1. D. C. Lay, Linear Algebra and its Applications, 3rd ed., Indian Reprint, Pearson Education Asia, 2007.

2. S. Lang, Introduction to Linear Algebra, 2nd ed., New York: Springer-Verlag, 2005.

3. S. H. Friedberg, A. Insel, and L. Spence, Linear algebra, 4th ed., Pearson, 2015.

4. Gilbert Strang, Linear Algebra and its Applications, 4th ed., Thomson Brooks/Cole, 2007.

5. K. Hoffmann and R. A. Kunze, Linear algebra, 2nd ed., PHI Learning, 2014.

Evaluation Pattern

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

 

MAT541A - INTEGRAL TRANSFORMS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description: This course aims at providing a solid foundation upon the fundamental theories on Fourier and Laplace transforms.

Course objectives​: This course will help the learner to

 

COBJ1. gain familiarity in fundamental theories of the Fourier series, Fourier Integrals, Fourier and Laplace transforms.
COBJ2. acquire problem solving skills in using Fourier Series, Fourier and Laplace transforms.

Learning Outcome

CO1.: On successful completion of the course, the students should be able to evaluate integrals by using Fourier series and Fourier integrals.

CO2.: On successful completion of the course, the students should be able to apply Fourier sine and cosine transforms for various functions.

CO3.: On successful completion of the course, the students should be able to derive Laplace transforms of different types of functions.

CO4.: On successful completion of the course, the students should be able to utilize the properties of Laplace transforms in solving ordinary differential equations.

Unit-1
Teaching Hours:15
Fourier series and Fourier transform
 

Fourier series and Fourier transform of some common functions. The Fourier integral, complex Fourier transforms, basic properties, transform of the derivative, convolution theorem, and Parseval’s identity. The applications of Fourier transform to ordinary differential equations.

Unit-1
Teaching Hours:15
Fourier series and Fourier transform
 

Fourier series and Fourier transform of some common functions. The Fourier integral, complex Fourier transforms, basic properties, transform of the derivative, convolution theorem, and Parseval’s identity. The applications of Fourier transform to ordinary differential equations.

Unit-1
Teaching Hours:15
Fourier series and Fourier transform
 

Fourier series and Fourier transform of some common functions. The Fourier integral, complex Fourier transforms, basic properties, transform of the derivative, convolution theorem, and Parseval’s identity. The applications of Fourier transform to ordinary differential equations.

Unit-1
Teaching Hours:15
Fourier series and Fourier transform
 

Fourier series and Fourier transform of some common functions. The Fourier integral, complex Fourier transforms, basic properties, transform of the derivative, convolution theorem, and Parseval’s identity. The applications of Fourier transform to ordinary differential equations.

Unit-1
Teaching Hours:15
Fourier series and Fourier transform
 

Fourier series and Fourier transform of some common functions. The Fourier integral, complex Fourier transforms, basic properties, transform of the derivative, convolution theorem, and Parseval’s identity. The applications of Fourier transform to ordinary differential equations.

Unit-2
Teaching Hours:15
Fourier sine and cosine transforms
 

Fourier cosine and sine transforms with examples, properties of Fourier Cosine and Sine Transforms, applications of Fourier sine and cosine transforms with examples.

Unit-2
Teaching Hours:15
Fourier sine and cosine transforms
 

Fourier cosine and sine transforms with examples, properties of Fourier Cosine and Sine Transforms, applications of Fourier sine and cosine transforms with examples.

Unit-2
Teaching Hours:15
Fourier sine and cosine transforms
 

Fourier cosine and sine transforms with examples, properties of Fourier Cosine and Sine Transforms, applications of Fourier sine and cosine transforms with examples.

Unit-2
Teaching Hours:15
Fourier sine and cosine transforms
 

Fourier cosine and sine transforms with examples, properties of Fourier Cosine and Sine Transforms, applications of Fourier sine and cosine transforms with examples.

Unit-2
Teaching Hours:15
Fourier sine and cosine transforms
 

Fourier cosine and sine transforms with examples, properties of Fourier Cosine and Sine Transforms, applications of Fourier sine and cosine transforms with examples.

Unit-3
Teaching Hours:15
Laplace transform
 

Laplace Transform of standard functions, Laplace transform of periodic functions, Inverse Laplace transform, solution of ordinary differential equation with constant coefficient using Laplace transform, solution of simultaneous Ordinary differential equations.

Unit-3
Teaching Hours:15
Laplace transform
 

Laplace Transform of standard functions, Laplace transform of periodic functions, Inverse Laplace transform, solution of ordinary differential equation with constant coefficient using Laplace transform, solution of simultaneous Ordinary differential equations.

Unit-3
Teaching Hours:15
Laplace transform
 

Laplace Transform of standard functions, Laplace transform of periodic functions, Inverse Laplace transform, solution of ordinary differential equation with constant coefficient using Laplace transform, solution of simultaneous Ordinary differential equations.

Unit-3
Teaching Hours:15
Laplace transform
 

Laplace Transform of standard functions, Laplace transform of periodic functions, Inverse Laplace transform, solution of ordinary differential equation with constant coefficient using Laplace transform, solution of simultaneous Ordinary differential equations.

Unit-3
Teaching Hours:15
Laplace transform
 

Laplace Transform of standard functions, Laplace transform of periodic functions, Inverse Laplace transform, solution of ordinary differential equation with constant coefficient using Laplace transform, solution of simultaneous Ordinary differential equations.

Text Books And Reference Books:

B. Davis, Integral transforms and their Applications, 2nd ed., Springer Science and Business Media, 2013.

Essential Reading / Recommended Reading
  1.  E. Kreyszig, Advanced Engineering Mathematics, 18th Ed., New Delhi, India: Wiley Pvt. Ltd., 2010.
  2.  B. S. Grewal, Higher Engineering Mathematics, 39th Ed., Khanna Publishers, July 2005.
  3. P. Dyke, An introduction to Laplace Transforms and Fourier Series, 2nd Ed., Springer Science and Business Media, 2014.
  4. M. D. Raisinghania, Advanced Differential Equations, S Chand and Company Ltd., 2018.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem-solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT541B - MATHEMATICAL MODELLING (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description: This course is concerned with the fundamentals of mathematical modeling. It deals with finding solution to real world problems by transforming into mathematical models using differential equations. The coverage includes mathematical modeling through first order, second order and system of ordinary differential equations.

 Course objectives​: This course will help the learner to

This course will help the learner to

COBJ1.  interpret the real-world problems in the form of first and second order differential equations. 

COBJ2.  familiarize with some classical linear and nonlinear models. 

COBJ3.  analyse the solutions of systems of differential equations by phase portrait method.

Learning Outcome

CO1.: On successful completion of the course, the students should be able to apply differential equations in other branches of sciences, commerce, medicine and others

CO2.: On successful completion of the course, the students should be able to understand the formulation of some classical mathematical models.

CO3.: On successful completion of the course, the students should be able to demonstrate competence with a wide variety of mathematical tools and techniques.

CO4.: On successful completion of the course, the students should be able to build mathematical models of real-world problems.

Unit-1
Teaching Hours:15
Mathematical Modeling through First Ordinary Differential Equations
 

Population Dynamics, Carbon dating, Newtons law of cooling, Epidemics, Economics, Medicine, mixture problem, electric circuit problem, Chemical reactions, Terminal velocity, Continuously compounding of interest.

Unit-1
Teaching Hours:15
Mathematical Modeling through First Ordinary Differential Equations
 

Population Dynamics, Carbon dating, Newtons law of cooling, Epidemics, Economics, Medicine, mixture problem, electric circuit problem, Chemical reactions, Terminal velocity, Continuously compounding of interest.

Unit-1
Teaching Hours:15
Mathematical Modeling through First Ordinary Differential Equations
 

Population Dynamics, Carbon dating, Newtons law of cooling, Epidemics, Economics, Medicine, mixture problem, electric circuit problem, Chemical reactions, Terminal velocity, Continuously compounding of interest.

Unit-1
Teaching Hours:15
Mathematical Modeling through First Ordinary Differential Equations
 

Population Dynamics, Carbon dating, Newtons law of cooling, Epidemics, Economics, Medicine, mixture problem, electric circuit problem, Chemical reactions, Terminal velocity, Continuously compounding of interest.

Unit-1
Teaching Hours:15
Mathematical Modeling through First Ordinary Differential Equations
 

Population Dynamics, Carbon dating, Newtons law of cooling, Epidemics, Economics, Medicine, mixture problem, electric circuit problem, Chemical reactions, Terminal velocity, Continuously compounding of interest.

Unit-1
Teaching Hours:15
Mathematical Modeling through First Ordinary Differential Equations
 

Population Dynamics, Carbon dating, Newtons law of cooling, Epidemics, Economics, Medicine, mixture problem, electric circuit problem, Chemical reactions, Terminal velocity, Continuously compounding of interest.

Unit-1
Teaching Hours:15
Mathematical Modeling through First Ordinary Differential Equations
 

Population Dynamics, Carbon dating, Newtons law of cooling, Epidemics, Economics, Medicine, mixture problem, electric circuit problem, Chemical reactions, Terminal velocity, Continuously compounding of interest.

Unit-2
Teaching Hours:15
Mathematical Modeling through Second Ordinary Differential Equations
 

The vibrations of a mass on a spring, free damped motion, forced motion, resonance phenomena, electric circuit problem, Nonlinear-Pendulum.

Unit-2
Teaching Hours:15
Mathematical Modeling through Second Ordinary Differential Equations
 

The vibrations of a mass on a spring, free damped motion, forced motion, resonance phenomena, electric circuit problem, Nonlinear-Pendulum.

Unit-2
Teaching Hours:15
Mathematical Modeling through Second Ordinary Differential Equations
 

The vibrations of a mass on a spring, free damped motion, forced motion, resonance phenomena, electric circuit problem, Nonlinear-Pendulum.

Unit-2
Teaching Hours:15
Mathematical Modeling through Second Ordinary Differential Equations
 

The vibrations of a mass on a spring, free damped motion, forced motion, resonance phenomena, electric circuit problem, Nonlinear-Pendulum.

Unit-2
Teaching Hours:15
Mathematical Modeling through Second Ordinary Differential Equations
 

The vibrations of a mass on a spring, free damped motion, forced motion, resonance phenomena, electric circuit problem, Nonlinear-Pendulum.

Unit-2
Teaching Hours:15
Mathematical Modeling through Second Ordinary Differential Equations
 

The vibrations of a mass on a spring, free damped motion, forced motion, resonance phenomena, electric circuit problem, Nonlinear-Pendulum.

Unit-2
Teaching Hours:15
Mathematical Modeling through Second Ordinary Differential Equations
 

The vibrations of a mass on a spring, free damped motion, forced motion, resonance phenomena, electric circuit problem, Nonlinear-Pendulum.

Unit-3
Teaching Hours:15
Mathematical Modeling through system of linear differential equations:
 

Phase plane analysis: Phase Portrait for Linear and Non-Linear Systems, Stability Analysis of Solution, Applications, Predator prey model: Lotka-Volterra Model, Kermack-McKendrick Model, Predator-Prey Model and Harvesting Analysis, Competitive-Hunter Model, Combat models: Lanchester Model, Battle of IWO Jima, Battle of Vietnam, Battle of Trafalgar., Mixture Models, Epidemics-SIR model, Economics.

Unit-3
Teaching Hours:15
Mathematical Modeling through system of linear differential equations:
 

Phase plane analysis: Phase Portrait for Linear and Non-Linear Systems, Stability Analysis of Solution, Applications, Predator prey model: Lotka-Volterra Model, Kermack-McKendrick Model, Predator-Prey Model and Harvesting Analysis, Competitive-Hunter Model, Combat models: Lanchester Model, Battle of IWO Jima, Battle of Vietnam, Battle of Trafalgar., Mixture Models, Epidemics-SIR model, Economics.

Unit-3
Teaching Hours:15
Mathematical Modeling through system of linear differential equations:
 

Phase plane analysis: Phase Portrait for Linear and Non-Linear Systems, Stability Analysis of Solution, Applications, Predator prey model: Lotka-Volterra Model, Kermack-McKendrick Model, Predator-Prey Model and Harvesting Analysis, Competitive-Hunter Model, Combat models: Lanchester Model, Battle of IWO Jima, Battle of Vietnam, Battle of Trafalgar., Mixture Models, Epidemics-SIR model, Economics.

Unit-3
Teaching Hours:15
Mathematical Modeling through system of linear differential equations:
 

Phase plane analysis: Phase Portrait for Linear and Non-Linear Systems, Stability Analysis of Solution, Applications, Predator prey model: Lotka-Volterra Model, Kermack-McKendrick Model, Predator-Prey Model and Harvesting Analysis, Competitive-Hunter Model, Combat models: Lanchester Model, Battle of IWO Jima, Battle of Vietnam, Battle of Trafalgar., Mixture Models, Epidemics-SIR model, Economics.

Unit-3
Teaching Hours:15
Mathematical Modeling through system of linear differential equations:
 

Phase plane analysis: Phase Portrait for Linear and Non-Linear Systems, Stability Analysis of Solution, Applications, Predator prey model: Lotka-Volterra Model, Kermack-McKendrick Model, Predator-Prey Model and Harvesting Analysis, Competitive-Hunter Model, Combat models: Lanchester Model, Battle of IWO Jima, Battle of Vietnam, Battle of Trafalgar., Mixture Models, Epidemics-SIR model, Economics.

Unit-3
Teaching Hours:15
Mathematical Modeling through system of linear differential equations:
 

Phase plane analysis: Phase Portrait for Linear and Non-Linear Systems, Stability Analysis of Solution, Applications, Predator prey model: Lotka-Volterra Model, Kermack-McKendrick Model, Predator-Prey Model and Harvesting Analysis, Competitive-Hunter Model, Combat models: Lanchester Model, Battle of IWO Jima, Battle of Vietnam, Battle of Trafalgar., Mixture Models, Epidemics-SIR model, Economics.

Unit-3
Teaching Hours:15
Mathematical Modeling through system of linear differential equations:
 

Phase plane analysis: Phase Portrait for Linear and Non-Linear Systems, Stability Analysis of Solution, Applications, Predator prey model: Lotka-Volterra Model, Kermack-McKendrick Model, Predator-Prey Model and Harvesting Analysis, Competitive-Hunter Model, Combat models: Lanchester Model, Battle of IWO Jima, Battle of Vietnam, Battle of Trafalgar., Mixture Models, Epidemics-SIR model, Economics.

Text Books And Reference Books:
  1. D. G. Zill and W. S. Wright, Advanced Engineering Mathematics, 4th ed., Jones and  Bartlett Publishers, 2010. 
  2. J. R. Brannan and W. E. Boyce, Differential equations with boundary value  problems: modern methods and applications, Wiley, 2011.
Essential Reading / Recommended Reading
  1. C. H. Edwards, D. E. Penney and D. Calvis, Differential equations and boundary value problems: computing and modeling, 3rd ed., Pearson Education Limited, 2010.
  2. D. G. Zill, Differential Equations with Boundary-Value Problems, I7th ed., Cenage learning, 2008.
Evaluation Pattern

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem-solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT541C - GRAPH THEORY (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description: This course is an introductory course to the basic concepts of Graph Theory. This includes a definition of graphs, types of graphs, paths, circuits, trees, shortest paths, and algorithms to find shortest paths.

Course objectives: This course will help the learner to

COBJ 1. gain conceptual knowledge on terminologies used in graph theory.

 

COBJ 2. understand the results on graphs and their properties.

COBJ 3. gain proof writing and algorithm writing skills.

Learning Outcome

CO1: On successful completion of the course, the students should be able to understand the terminology related to graphs

CO2: On successful completion of the course, the students should be able to analyze the characteristics of graphs by using standard results on graphs

CO3: On successful completion of the course, the students should be able to apply proof techniques and write algorithms

Unit-1
Teaching Hours:15
Introduction to Graphs
 

Graphs, connected graphs, classes of graphs, regular graphs, degree sequences, matrices, isomorphic graphs.

Unit-1
Teaching Hours:15
Introduction to Graphs
 

Graphs, connected graphs, classes of graphs, regular graphs, degree sequences, matrices, isomorphic graphs.

Unit-1
Teaching Hours:15
Introduction to Graphs
 

Graphs, connected graphs, classes of graphs, regular graphs, degree sequences, matrices, isomorphic graphs.

Unit-1
Teaching Hours:15
Introduction to Graphs
 

Graphs, connected graphs, classes of graphs, regular graphs, degree sequences, matrices, isomorphic graphs.

Unit-1
Teaching Hours:15
Introduction to Graphs
 

Graphs, connected graphs, classes of graphs, regular graphs, degree sequences, matrices, isomorphic graphs.

Unit-1
Teaching Hours:15
Introduction to Graphs
 

Graphs, connected graphs, classes of graphs, regular graphs, degree sequences, matrices, isomorphic graphs.

Unit-1
Teaching Hours:15
Introduction to Graphs
 

Graphs, connected graphs, classes of graphs, regular graphs, degree sequences, matrices, isomorphic graphs.

Unit-2
Teaching Hours:15
Connectivity
 

Bridges, trees, minimum spanning trees, cut-vertices, blocks, traversability, Eulerian and Hamiltonian graphs, digraphs. 

Unit-2
Teaching Hours:15
Connectivity
 

Bridges, trees, minimum spanning trees, cut-vertices, blocks, traversability, Eulerian and Hamiltonian graphs, digraphs. 

Unit-2
Teaching Hours:15
Connectivity
 

Bridges, trees, minimum spanning trees, cut-vertices, blocks, traversability, Eulerian and Hamiltonian graphs, digraphs. 

Unit-2
Teaching Hours:15
Connectivity
 

Bridges, trees, minimum spanning trees, cut-vertices, blocks, traversability, Eulerian and Hamiltonian graphs, digraphs. 

Unit-2
Teaching Hours:15
Connectivity
 

Bridges, trees, minimum spanning trees, cut-vertices, blocks, traversability, Eulerian and Hamiltonian graphs, digraphs. 

Unit-2
Teaching Hours:15
Connectivity
 

Bridges, trees, minimum spanning trees, cut-vertices, blocks, traversability, Eulerian and Hamiltonian graphs, digraphs. 

Unit-2
Teaching Hours:15
Connectivity
 

Bridges, trees, minimum spanning trees, cut-vertices, blocks, traversability, Eulerian and Hamiltonian graphs, digraphs. 

Unit-3
Teaching Hours:15
Planarity
 

Matching, factorizations, decompositions, graceful labeling, planar graphs, Embedding graphs on surfaces.

Unit-3
Teaching Hours:15
Planarity
 

Matching, factorizations, decompositions, graceful labeling, planar graphs, Embedding graphs on surfaces.

Unit-3
Teaching Hours:15
Planarity
 

Matching, factorizations, decompositions, graceful labeling, planar graphs, Embedding graphs on surfaces.

Unit-3
Teaching Hours:15
Planarity
 

Matching, factorizations, decompositions, graceful labeling, planar graphs, Embedding graphs on surfaces.

Unit-3
Teaching Hours:15
Planarity
 

Matching, factorizations, decompositions, graceful labeling, planar graphs, Embedding graphs on surfaces.

Unit-3
Teaching Hours:15
Planarity
 

Matching, factorizations, decompositions, graceful labeling, planar graphs, Embedding graphs on surfaces.

Unit-3
Teaching Hours:15
Planarity
 

Matching, factorizations, decompositions, graceful labeling, planar graphs, Embedding graphs on surfaces.

Text Books And Reference Books:
  1. G. Chartrand and P. Chang, Introduction to Graph Theory, New Delhi: Tata McGraw Hill, 2006.
Essential Reading / Recommended Reading
  1. N. Deo, Graph Theory with applications to engineering and computer science, Courier Dover Publications, 2017.
  2. J. A. Bondy and U. S. R. Murty, Graph Theory with Applications, Elsevier Science, 1976.
  3. F. Harary, Graph Theory, New Delhi: Narosa, 2001.
  4. D. B. West, Introduction to Graph Theory, New Delhi: Prentice-Hall of India, 2011.
  5. S. A. Choudum, A first Course in Graph Theory, MacMillan Publishers India Ltd, 2013.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ

Written Assignment

Reference work

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment / Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT541D - CALCULUS OF SEVERAL VARIABLES (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description​: This course aims to enlighten students with the fundamental concepts of vectors, geometry of space, partial differentiation and vector analysis such as gradient, divergence, curl, and the evaluation of line, surface and volume integrals. The three classical theorems, viz., Green’s theorem, Gauss divergence theorem and Stoke’s theorem are also covered.

Course objectives​: This course will help the learner to 

COBJ 1. gain familiarity with the fundamental concepts of vectors and geometry of space  Curves.

COBJ 2. illustrates and interprets differential and integral calculus of vector fields 

COBJ 3. demonstrate the use Green’s Theorem, Stokes Theorem, and Gauss’ divergence Theorem

Learning Outcome

CO1: On successful completion of the course, the students should be able to solve problems involving vector operations.

CO2: On successful completion of the course, the students should be able to understand the TNB framework and derive Serret-Frenet formula.

CO3: On successful completion of the course, the students should be able to compute double integrals and be familiar with change of order of integration.

CO4: On successful completion of the course, the students should be able to understand the concept of line integrals for vector valued functions.

CO5: On successful completion of the course, the students should be able to apply Green's Theorem, Divergence Theorem and Stoke's Theorem.

Unit-1
Teaching Hours:15
Vectors and Geometry of Space
 

Fundamentals: Three-dimensional coordination systems, Vectors and vector operations, Line and planes in space, Curves in space and their tangents, Integrals of vector functions, Arc length in space, Curvature and normal vectors of a space, TNB frame, Directional derivatives and gradient  vectors, Divergence and curl of vector valued functions.

Unit-1
Teaching Hours:15
Vectors and Geometry of Space
 

Fundamentals: Three-dimensional coordination systems, Vectors and vector operations, Line and planes in space, Curves in space and their tangents, Integrals of vector functions, Arc length in space, Curvature and normal vectors of a space, TNB frame, Directional derivatives and gradient  vectors, Divergence and curl of vector valued functions.

Unit-1
Teaching Hours:15
Vectors and Geometry of Space
 

Fundamentals: Three-dimensional coordination systems, Vectors and vector operations, Line and planes in space, Curves in space and their tangents, Integrals of vector functions, Arc length in space, Curvature and normal vectors of a space, TNB frame, Directional derivatives and gradient  vectors, Divergence and curl of vector valued functions.

Unit-1
Teaching Hours:15
Vectors and Geometry of Space
 

Fundamentals: Three-dimensional coordination systems, Vectors and vector operations, Line and planes in space, Curves in space and their tangents, Integrals of vector functions, Arc length in space, Curvature and normal vectors of a space, TNB frame, Directional derivatives and gradient  vectors, Divergence and curl of vector valued functions.

Unit-1
Teaching Hours:15
Vectors and Geometry of Space
 

Fundamentals: Three-dimensional coordination systems, Vectors and vector operations, Line and planes in space, Curves in space and their tangents, Integrals of vector functions, Arc length in space, Curvature and normal vectors of a space, TNB frame, Directional derivatives and gradient  vectors, Divergence and curl of vector valued functions.

Unit-2
Teaching Hours:15
Multiple Integrals
 

Double Integrals- Areas, Moments, and Centres of Mass – Double Integrals in Polar Form –Triple Integrals in Rectangular Coordinates, Masses and Moments in Three Dimensions, Triple Integrals in Cylindrical and Spherical Coordinates, Substitutions in Multiple Integrals.

Unit-2
Teaching Hours:15
Multiple Integrals
 

Double Integrals- Areas, Moments, and Centres of Mass – Double Integrals in Polar Form –Triple Integrals in Rectangular Coordinates, Masses and Moments in Three Dimensions, Triple Integrals in Cylindrical and Spherical Coordinates, Substitutions in Multiple Integrals.

Unit-2
Teaching Hours:15
Multiple Integrals
 

Double Integrals- Areas, Moments, and Centres of Mass – Double Integrals in Polar Form –Triple Integrals in Rectangular Coordinates, Masses and Moments in Three Dimensions, Triple Integrals in Cylindrical and Spherical Coordinates, Substitutions in Multiple Integrals.

Unit-2
Teaching Hours:15
Multiple Integrals
 

Double Integrals- Areas, Moments, and Centres of Mass – Double Integrals in Polar Form –Triple Integrals in Rectangular Coordinates, Masses and Moments in Three Dimensions, Triple Integrals in Cylindrical and Spherical Coordinates, Substitutions in Multiple Integrals.

Unit-2
Teaching Hours:15
Multiple Integrals
 

Double Integrals- Areas, Moments, and Centres of Mass – Double Integrals in Polar Form –Triple Integrals in Rectangular Coordinates, Masses and Moments in Three Dimensions, Triple Integrals in Cylindrical and Spherical Coordinates, Substitutions in Multiple Integrals.

Unit-3
Teaching Hours:15
Integration in Vector Fields
 

Line Integrals, Vector Fields, Work, Circulation and Flux, Path Independence, Potential Functions, and Conservative Fields, Green’s Theorem in the Plane, Surface Area and Surface  Integrals, Parametrized Surfaces, Stokes’ Theorem, The Divergence Theorem.

Unit-3
Teaching Hours:15
Integration in Vector Fields
 

Line Integrals, Vector Fields, Work, Circulation and Flux, Path Independence, Potential Functions, and Conservative Fields, Green’s Theorem in the Plane, Surface Area and Surface  Integrals, Parametrized Surfaces, Stokes’ Theorem, The Divergence Theorem.

Unit-3
Teaching Hours:15
Integration in Vector Fields
 

Line Integrals, Vector Fields, Work, Circulation and Flux, Path Independence, Potential Functions, and Conservative Fields, Green’s Theorem in the Plane, Surface Area and Surface  Integrals, Parametrized Surfaces, Stokes’ Theorem, The Divergence Theorem.

Unit-3
Teaching Hours:15
Integration in Vector Fields
 

Line Integrals, Vector Fields, Work, Circulation and Flux, Path Independence, Potential Functions, and Conservative Fields, Green’s Theorem in the Plane, Surface Area and Surface  Integrals, Parametrized Surfaces, Stokes’ Theorem, The Divergence Theorem.

Unit-3
Teaching Hours:15
Integration in Vector Fields
 

Line Integrals, Vector Fields, Work, Circulation and Flux, Path Independence, Potential Functions, and Conservative Fields, Green’s Theorem in the Plane, Surface Area and Surface  Integrals, Parametrized Surfaces, Stokes’ Theorem, The Divergence Theorem.

Text Books And Reference Books:

J. R. Hass, C Heil, M D Weir, Thomas’ Calculus, 14th ed., USA: Pearson, 2018.

Essential Reading / Recommended Reading
  1. J. Stewart, Multivariable calculus, 7th ed.: Belmont, USA: Brooks/Cole Cengage Learning., 2013. 
  2. M. Spivak, Calculus, 3rd ed., Cambridge University Press, 2006. 
  3. T. M. Apostol, Mathematical Analysis, 2nd ed., Wiley India Pvt. Ltd., 2011.
  4. S. Lang, Calculus of several variables, 3rd ed., Springer, 2012.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills.

 

10

CIA II

Mid-semester Examination

Basic, conceptual, and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual, and analytical knowledge of the subject

50

Total

100

MAT541E - OPERATIONS RESEARCH (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course description: Operations research deals with the problems on optimization or decision making that are affected by certain constraints / restrictions in the environment. This course aims at teaching solution techniques of solving linear programming models, simple queuing model, two-person zero sum games and Network models.

Course objectives: This course will help the learner to

COBJ1. gain an insight executing the algorithms for solving linear programming problems including transportation and assignment problems.

COBJ2. learn about the techniques involved in solving the two person zero sum game.

COBJ3. calculate the estimates that characteristics the queues and perform desired analysis on a network.

Learning Outcome

CO1: On successful completion of the course, the students should be able to solve Linear Programming Problems using Simplex Algorithm, Transportation and Assignment Problems.

CO2: On successful completion of the course, the students should be able to find the estimates that characterizes different types of Queuing Models.

CO3: On successful completion of the course, the students should be able to obtain the solution for two person zero sum games using Linear Programming.

CO4: On successful completion of the course, the students should be able to formulate Maximal Flow Model using Linear Programming and perform computations using PERT and CPM.

Unit-1
Teaching Hours:15
Introduction to Linear Programming Problems
 

Introduction to simplex algorithm –Special cases in the Simplex Method –Definition of the Dual Problem – Primal Dual relationships – Dual simplex methods. Transportation Models: Determination of the starting solution – iterative computations of the transportation algorithm. Assignment Model: The Hungarian Method.

Unit-1
Teaching Hours:15
Introduction to Linear Programming Problems
 

Introduction to simplex algorithm –Special cases in the Simplex Method –Definition of the Dual Problem – Primal Dual relationships – Dual simplex methods. Transportation Models: Determination of the starting solution – iterative computations of the transportation algorithm. Assignment Model: The Hungarian Method.

Unit-1
Teaching Hours:15
Introduction to Linear Programming Problems
 

Introduction to simplex algorithm –Special cases in the Simplex Method –Definition of the Dual Problem – Primal Dual relationships – Dual simplex methods. Transportation Models: Determination of the starting solution – iterative computations of the transportation algorithm. Assignment Model: The Hungarian Method.

Unit-1
Teaching Hours:15
Introduction to Linear Programming Problems
 

Introduction to simplex algorithm –Special cases in the Simplex Method –Definition of the Dual Problem – Primal Dual relationships – Dual simplex methods. Transportation Models: Determination of the starting solution – iterative computations of the transportation algorithm. Assignment Model: The Hungarian Method.

Unit-1
Teaching Hours:15
Introduction to Linear Programming Problems
 

Introduction to simplex algorithm –Special cases in the Simplex Method –Definition of the Dual Problem – Primal Dual relationships – Dual simplex methods. Transportation Models: Determination of the starting solution – iterative computations of the transportation algorithm. Assignment Model: The Hungarian Method.

Unit-1
Teaching Hours:15
Introduction to Linear Programming Problems
 

Introduction to simplex algorithm –Special cases in the Simplex Method –Definition of the Dual Problem – Primal Dual relationships – Dual simplex methods. Transportation Models: Determination of the starting solution – iterative computations of the transportation algorithm. Assignment Model: The Hungarian Method.

Unit-1
Teaching Hours:15
Introduction to Linear Programming Problems
 

Introduction to simplex algorithm –Special cases in the Simplex Method –Definition of the Dual Problem – Primal Dual relationships – Dual simplex methods. Transportation Models: Determination of the starting solution – iterative computations of the transportation algorithm. Assignment Model: The Hungarian Method.

Unit-2
Teaching Hours:15
Queuing Theory and Game Theory
 

Elements of a queuing Model – Pure Birth Model – Pure Death Model –Specialized Poisson Queues – Steady state Models: (M/M/1):(GD/∞/∞) – (M/M/1):(FCFS/∞/∞) - (M/M/1):(GD/N/∞) – (M/M/c):(GD/∞/∞) –  (M/M/∞):(GD/∞/∞).

Game Theory: Optimal solution of two person zero-sum games – Solution of Mixed strategy Games (only Linear programming solution).

 

Unit-2
Teaching Hours:15
Queuing Theory and Game Theory
 

Elements of a queuing Model – Pure Birth Model – Pure Death Model –Specialized Poisson Queues – Steady state Models: (M/M/1):(GD/∞/∞) – (M/M/1):(FCFS/∞/∞) - (M/M/1):(GD/N/∞) – (M/M/c):(GD/∞/∞) –  (M/M/∞):(GD/∞/∞).

Game Theory: Optimal solution of two person zero-sum games – Solution of Mixed strategy Games (only Linear programming solution).

 

Unit-2
Teaching Hours:15
Queuing Theory and Game Theory
 

Elements of a queuing Model – Pure Birth Model – Pure Death Model –Specialized Poisson Queues – Steady state Models: (M/M/1):(GD/∞/∞) – (M/M/1):(FCFS/∞/∞) - (M/M/1):(GD/N/∞) – (M/M/c):(GD/∞/∞) –  (M/M/∞):(GD/∞/∞).

Game Theory: Optimal solution of two person zero-sum games – Solution of Mixed strategy Games (only Linear programming solution).

 

Unit-2
Teaching Hours:15
Queuing Theory and Game Theory
 

Elements of a queuing Model – Pure Birth Model – Pure Death Model –Specialized Poisson Queues – Steady state Models: (M/M/1):(GD/∞/∞) – (M/M/1):(FCFS/∞/∞) - (M/M/1):(GD/N/∞) – (M/M/c):(GD/∞/∞) –  (M/M/∞):(GD/∞/∞).

Game Theory: Optimal solution of two person zero-sum games – Solution of Mixed strategy Games (only Linear programming solution).

 

Unit-2
Teaching Hours:15
Queuing Theory and Game Theory
 

Elements of a queuing Model – Pure Birth Model – Pure Death Model –Specialized Poisson Queues – Steady state Models: (M/M/1):(GD/∞/∞) – (M/M/1):(FCFS/∞/∞) - (M/M/1):(GD/N/∞) – (M/M/c):(GD/∞/∞) –  (M/M/∞):(GD/∞/∞).

Game Theory: Optimal solution of two person zero-sum games – Solution of Mixed strategy Games (only Linear programming solution).

 

Unit-2
Teaching Hours:15
Queuing Theory and Game Theory
 

Elements of a queuing Model – Pure Birth Model – Pure Death Model –Specialized Poisson Queues – Steady state Models: (M/M/1):(GD/∞/∞) – (M/M/1):(FCFS/∞/∞) - (M/M/1):(GD/N/∞) – (M/M/c):(GD/∞/∞) –  (M/M/∞):(GD/∞/∞).

Game Theory: Optimal solution of two person zero-sum games – Solution of Mixed strategy Games (only Linear programming solution).

 

Unit-2
Teaching Hours:15
Queuing Theory and Game Theory
 

Elements of a queuing Model – Pure Birth Model – Pure Death Model –Specialized Poisson Queues – Steady state Models: (M/M/1):(GD/∞/∞) – (M/M/1):(FCFS/∞/∞) - (M/M/1):(GD/N/∞) – (M/M/c):(GD/∞/∞) –  (M/M/∞):(GD/∞/∞).

Game Theory: Optimal solution of two person zero-sum games – Solution of Mixed strategy Games (only Linear programming solution).

 

Unit-3
Teaching Hours:15
Network Models
 

Linear programming formulation of the shortest-route Problem. Maximal Flow model:- Enumeration of cuts – Maximal Flow Algorithm – Linear Programming Formulation of Maximal Flow Model. CPM and PERT:- Network Representation – Critical path computations – Construction of the Time Schedule – Linear Programming formulation of CPM – PERT calculations.

Unit-3
Teaching Hours:15
Network Models
 

Linear programming formulation of the shortest-route Problem. Maximal Flow model:- Enumeration of cuts – Maximal Flow Algorithm – Linear Programming Formulation of Maximal Flow Model. CPM and PERT:- Network Representation – Critical path computations – Construction of the Time Schedule – Linear Programming formulation of CPM – PERT calculations.

Unit-3
Teaching Hours:15
Network Models
 

Linear programming formulation of the shortest-route Problem. Maximal Flow model:- Enumeration of cuts – Maximal Flow Algorithm – Linear Programming Formulation of Maximal Flow Model. CPM and PERT:- Network Representation – Critical path computations – Construction of the Time Schedule – Linear Programming formulation of CPM – PERT calculations.

Unit-3
Teaching Hours:15
Network Models
 

Linear programming formulation of the shortest-route Problem. Maximal Flow model:- Enumeration of cuts – Maximal Flow Algorithm – Linear Programming Formulation of Maximal Flow Model. CPM and PERT:- Network Representation – Critical path computations – Construction of the Time Schedule – Linear Programming formulation of CPM – PERT calculations.

Unit-3
Teaching Hours:15
Network Models
 

Linear programming formulation of the shortest-route Problem. Maximal Flow model:- Enumeration of cuts – Maximal Flow Algorithm – Linear Programming Formulation of Maximal Flow Model. CPM and PERT:- Network Representation – Critical path computations – Construction of the Time Schedule – Linear Programming formulation of CPM – PERT calculations.

Unit-3
Teaching Hours:15
Network Models
 

Linear programming formulation of the shortest-route Problem. Maximal Flow model:- Enumeration of cuts – Maximal Flow Algorithm – Linear Programming Formulation of Maximal Flow Model. CPM and PERT:- Network Representation – Critical path computations – Construction of the Time Schedule – Linear Programming formulation of CPM – PERT calculations.

Unit-3
Teaching Hours:15
Network Models
 

Linear programming formulation of the shortest-route Problem. Maximal Flow model:- Enumeration of cuts – Maximal Flow Algorithm – Linear Programming Formulation of Maximal Flow Model. CPM and PERT:- Network Representation – Critical path computations – Construction of the Time Schedule – Linear Programming formulation of CPM – PERT calculations.

Text Books And Reference Books:

A.H. Taha, Operations research, 9th ed., Pearson Education, 2014.

Essential Reading / Recommended Reading
  1. F.S. Hillier and G.J. Lieberman, Introduction to operations research, 9th Edition, McGraw-Hill, 2009.
  2. Chandrasekhara Rao & Shanthi Lata Mishra, Operations research, Alpha Science International, 2005.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ

Written Assignment

Reference work

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT551 - LINEAR ALGEBRA USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course description: This course aims at providing hands on experience in using Python functions to illustrate the notions vector space, linear independence, linear dependence, linear transformation and rank.

Course objectives: This course will help the learner to

COBJ1. The built in functions required to deal with vectors and Linear Transformations.

COBJ2. Python skills to handle vectors using the properties of vector spaces and linear transformations

Learning Outcome

CO1: On successful completion of the course, the students should be able to use Python functions in applying the notions of matrices and system of equations.

CO2: On successful completion of the course, the students should be able to use Python functions in applying the problems on vector space.

CO3: On successful completion of the course, the students should be able to apply python functions to solve the problems on linear transformations.

Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Operations on matrices
  2. Finding rank of matrices
  3. Reducing a matrix to Echelon form
  4. Inverse of a matrix by different methods
  5. Solving system of equations using various methods
  6. Finding eigenvalues and eigenvectors of a matrix
  7. Expressing a vector as a linear combination of given set of vectors
  8. Linear span, linear independence and linear dependence
  9. Linear transformations and plotting of linear transformations
  10. Applications of Rank-Nullity Theorem
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Operations on matrices
  2. Finding rank of matrices
  3. Reducing a matrix to Echelon form
  4. Inverse of a matrix by different methods
  5. Solving system of equations using various methods
  6. Finding eigenvalues and eigenvectors of a matrix
  7. Expressing a vector as a linear combination of given set of vectors
  8. Linear span, linear independence and linear dependence
  9. Linear transformations and plotting of linear transformations
  10. Applications of Rank-Nullity Theorem
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Operations on matrices
  2. Finding rank of matrices
  3. Reducing a matrix to Echelon form
  4. Inverse of a matrix by different methods
  5. Solving system of equations using various methods
  6. Finding eigenvalues and eigenvectors of a matrix
  7. Expressing a vector as a linear combination of given set of vectors
  8. Linear span, linear independence and linear dependence
  9. Linear transformations and plotting of linear transformations
  10. Applications of Rank-Nullity Theorem
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Operations on matrices
  2. Finding rank of matrices
  3. Reducing a matrix to Echelon form
  4. Inverse of a matrix by different methods
  5. Solving system of equations using various methods
  6. Finding eigenvalues and eigenvectors of a matrix
  7. Expressing a vector as a linear combination of given set of vectors
  8. Linear span, linear independence and linear dependence
  9. Linear transformations and plotting of linear transformations
  10. Applications of Rank-Nullity Theorem
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Operations on matrices
  2. Finding rank of matrices
  3. Reducing a matrix to Echelon form
  4. Inverse of a matrix by different methods
  5. Solving system of equations using various methods
  6. Finding eigenvalues and eigenvectors of a matrix
  7. Expressing a vector as a linear combination of given set of vectors
  8. Linear span, linear independence and linear dependence
  9. Linear transformations and plotting of linear transformations
  10. Applications of Rank-Nullity Theorem
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Operations on matrices
  2. Finding rank of matrices
  3. Reducing a matrix to Echelon form
  4. Inverse of a matrix by different methods
  5. Solving system of equations using various methods
  6. Finding eigenvalues and eigenvectors of a matrix
  7. Expressing a vector as a linear combination of given set of vectors
  8. Linear span, linear independence and linear dependence
  9. Linear transformations and plotting of linear transformations
  10. Applications of Rank-Nullity Theorem
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Operations on matrices
  2. Finding rank of matrices
  3. Reducing a matrix to Echelon form
  4. Inverse of a matrix by different methods
  5. Solving system of equations using various methods
  6. Finding eigenvalues and eigenvectors of a matrix
  7. Expressing a vector as a linear combination of given set of vectors
  8. Linear span, linear independence and linear dependence
  9. Linear transformations and plotting of linear transformations
  10. Applications of Rank-Nullity Theorem
Text Books And Reference Books:
  1. A. Saha, Doing Math with Python: Use Programming to Explore Algebra, Statistics, Calculus, and More!, no starch press:San Fransisco, 2015.
  2. H P Langtangen, A Primer on Scientific Programming with Python, 2nd ed., Springer, 2016.
Essential Reading / Recommended Reading
  1. B E Shapiro, Scientific Computation: Python Hacking for Math Junkies, Sherwood Forest Books, 2015.
  2. C Hill, Learning Scientific Programming with Python, Cambridge University Press, 2016.
Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT551A - INTEGRAL TRANSFORMS USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

This course will help students to gain skills in using Python to illustrate Fourier transforms, Laplace transforms for some standard functions and implementing Laplace transforms in solving ordinary differential equations of first and second order with constant coefficient.

Course Objectives​: This course will help the learner to

COBJ1. code python language using jupyter interface.

COBJ2. use built in functions required to deal with Fourier and Laplace transforms.

COBJ3. calculate Inverse Laplace transforms and the inverse Fourier transforms of standard functions using sympy.integrals

Learning Outcome

CO1.: On successful completion of the course, the students should be able to acquire skill in Python Programming to illustrate Fourier series, Fourier and Laplace transforms.

CO2.: On successful completion of the course, the students should be able to use Python program to solve ODE's by Laplace transforms.

Unit-1
Teaching Hours:30
Integral transforms using Python
 
  1.  Fourier series using sympy and numpy.
  2.  Practical harmonic analysis using math, sympy and numpy.
  3.  Fourier cosine and Fourier sine transforms using sympy and math.
  4.  Discrete Fourier transform using Python.
  5.  Laplace transforms using sympy, sympy.integrals and sympy.abc.
  6.  Inverse Laplace transforms using sympy, sympy.integrals and sympy.abc.
  7. Inverse Fourier transforms using sympy, sympy.integrals and sympy.abc.
Unit-1
Teaching Hours:30
Integral transforms using Python
 
  1.  Fourier series using sympy and numpy.
  2.  Practical harmonic analysis using math, sympy and numpy.
  3.  Fourier cosine and Fourier sine transforms using sympy and math.
  4.  Discrete Fourier transform using Python.
  5.  Laplace transforms using sympy, sympy.integrals and sympy.abc.
  6.  Inverse Laplace transforms using sympy, sympy.integrals and sympy.abc.
  7. Inverse Fourier transforms using sympy, sympy.integrals and sympy.abc.
Unit-1
Teaching Hours:30
Integral transforms using Python
 
  1.  Fourier series using sympy and numpy.
  2.  Practical harmonic analysis using math, sympy and numpy.
  3.  Fourier cosine and Fourier sine transforms using sympy and math.
  4.  Discrete Fourier transform using Python.
  5.  Laplace transforms using sympy, sympy.integrals and sympy.abc.
  6.  Inverse Laplace transforms using sympy, sympy.integrals and sympy.abc.
  7. Inverse Fourier transforms using sympy, sympy.integrals and sympy.abc.
Unit-1
Teaching Hours:30
Integral transforms using Python
 
  1.  Fourier series using sympy and numpy.
  2.  Practical harmonic analysis using math, sympy and numpy.
  3.  Fourier cosine and Fourier sine transforms using sympy and math.
  4.  Discrete Fourier transform using Python.
  5.  Laplace transforms using sympy, sympy.integrals and sympy.abc.
  6.  Inverse Laplace transforms using sympy, sympy.integrals and sympy.abc.
  7. Inverse Fourier transforms using sympy, sympy.integrals and sympy.abc.
Unit-1
Teaching Hours:30
Integral transforms using Python
 
  1.  Fourier series using sympy and numpy.
  2.  Practical harmonic analysis using math, sympy and numpy.
  3.  Fourier cosine and Fourier sine transforms using sympy and math.
  4.  Discrete Fourier transform using Python.
  5.  Laplace transforms using sympy, sympy.integrals and sympy.abc.
  6.  Inverse Laplace transforms using sympy, sympy.integrals and sympy.abc.
  7. Inverse Fourier transforms using sympy, sympy.integrals and sympy.abc.
Text Books And Reference Books:

J. Nunez-Iglesias, S. van der Walt, and H. Dashnow, Elegant SciPy: The art of scientific Python. O'Reilly Media, 2017. 

Essential Reading / Recommended Reading
  1. J. Unpingco, Python for signal processing. Springer International Pu, 2016.
  2. B. Downey, Think DSP: digital signal processing in Python. O'Reilly, 2016.
  3. M. A. Wood, Python and Matplotlib Essentials for Scientists and Engineers, IOP Publishing Limited, 2015.
Evaluation Pattern

Component

Parameter

Mode of Assessment

Maximum points

CIA I

Mastery of the fundamentals

Lab Assignments

20

CIA-II

Conceptual clarity and software skills

Lab Exam 1

10

Lab Record

Systematic

documentation of Lab exercises

e-Record work

07

Attendance

Regularity and punctuality

Lab Attendance

03

95%-100%-3

90%-94%-2

85%-89%-1

CIA III

Proficiency in executing the commands appropriately

Lab Exam 2

10

Total

50

MAT551B - MATHEMATICAL MODELLING USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course description: This course provides students with an understanding of the practical and theoretical aspects of mathematical models involving ordinary differential equations (ODEs) using Python programming.

Course objectives:

This course will help the learner to 

COBJ1. various models spanning disciplines such as physics, biology, engineering, and finance. 

COBJ2. develop the basic understanding of differential equations and skills to implement numerical algorithms to solve mathematical problems using Python.

Learning Outcome

CO1.: On successful completion of the course, the students should be able to acquire proficiency in using Python.

CO2.: On successful completion of the course, the students should be able to demonstrate the use of Python to understand and interpret applications of differential equations

CO3.: On successful completion of the course, the students should be able to apply the theoretical and practical knowledge to real life situations.

Unit-1
Teaching Hours:30
Propopsed Topics
 
  1. Growth of a population – Linear growth, Exponential growth, Logistic growth
  2. Decay Model - Radioactive Decay
  3. Numerical Methods
  4. A Simple Pendulum
  5. Spreading of a Disease
  6. Mixture problems
  7. Trajectory of a ball
  8. Spring mass system
  9. Electrical Circuits
Unit-1
Teaching Hours:30
Propopsed Topics
 
  1. Growth of a population – Linear growth, Exponential growth, Logistic growth
  2. Decay Model - Radioactive Decay
  3. Numerical Methods
  4. A Simple Pendulum
  5. Spreading of a Disease
  6. Mixture problems
  7. Trajectory of a ball
  8. Spring mass system
  9. Electrical Circuits
Unit-1
Teaching Hours:30
Propopsed Topics
 
  1. Growth of a population – Linear growth, Exponential growth, Logistic growth
  2. Decay Model - Radioactive Decay
  3. Numerical Methods
  4. A Simple Pendulum
  5. Spreading of a Disease
  6. Mixture problems
  7. Trajectory of a ball
  8. Spring mass system
  9. Electrical Circuits
Unit-1
Teaching Hours:30
Propopsed Topics
 
  1. Growth of a population – Linear growth, Exponential growth, Logistic growth
  2. Decay Model - Radioactive Decay
  3. Numerical Methods
  4. A Simple Pendulum
  5. Spreading of a Disease
  6. Mixture problems
  7. Trajectory of a ball
  8. Spring mass system
  9. Electrical Circuits
Unit-1
Teaching Hours:30
Propopsed Topics
 
  1. Growth of a population – Linear growth, Exponential growth, Logistic growth
  2. Decay Model - Radioactive Decay
  3. Numerical Methods
  4. A Simple Pendulum
  5. Spreading of a Disease
  6. Mixture problems
  7. Trajectory of a ball
  8. Spring mass system
  9. Electrical Circuits
Unit-1
Teaching Hours:30
Propopsed Topics
 
  1. Growth of a population – Linear growth, Exponential growth, Logistic growth
  2. Decay Model - Radioactive Decay
  3. Numerical Methods
  4. A Simple Pendulum
  5. Spreading of a Disease
  6. Mixture problems
  7. Trajectory of a ball
  8. Spring mass system
  9. Electrical Circuits
Unit-1
Teaching Hours:30
Propopsed Topics
 
  1. Growth of a population – Linear growth, Exponential growth, Logistic growth
  2. Decay Model - Radioactive Decay
  3. Numerical Methods
  4. A Simple Pendulum
  5. Spreading of a Disease
  6. Mixture problems
  7. Trajectory of a ball
  8. Spring mass system
  9. Electrical Circuits
Text Books And Reference Books:

H P Langtangen, A Primer on Scientific Programming with Python, 2nd ed., Springer, 2016.

Essential Reading / Recommended Reading
  1. B E Shapiro, Scientific Computation: Python Hacking for Math Junkies, Sherwood Forest Books, 2015.
  2. C Hill, Learning Scientific Programming with Python, Cambridge Univesity Press, 2016.
  3. A. Saha, Doing Math with Python: Use Programming to Explore Algebra, Statistics, Calculus, and More!, no starch press: San Fransisco, 2015.
  4. H. Fangohr, Introduction to Python for Computational Science and Engineering (A beginner’s guide), University of Southampton, 2015.

 

Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT551C - GRAPH THEORY USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course description: The course graph theory using Python is aimed at enabling the students to appreciate and understand core concepts of graph theory with the help of technological tools. It is designed with a learner-centric approach wherein the students will understand the concepts of graph theory using programming tools and develop computational skills.

Course objectives: This course will help the learner to

COBJ1. gain familiarity in Python language using jupyter interface and NetworkX package

COBJ2. construct graphs and analyze their structural properties.

COBJ3. implement standard algorithms for shortest paths, minimal spanning trees and graph searching..

Learning Outcome

CO1: On successful completion of the course, the students should be able to construct graphs using related matrices

CO2: On successful completion of the course, the students should be able to compute the graph parameters related to degrees and distances

CO3: On successful completion of the course, the students should be able to gain mastery to deal with optimization problems related to networks

CO4: On successful completion of the course, the students should be able to apply algorithmic approach in solving graph theory problems

Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to NetworkX package
  2. Construction of graphs
  3. Degree and distance related parameters
  4. In-built functions for different graph classes
  5. Computation of graph parameters using in-built functions
  6. Graph Operations and Graph Connectivity
  7. Customization of Graphs
  8. Digraphs
  9. Matrices and Algorithms of Graphs
  10. Graph as models.
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to NetworkX package
  2. Construction of graphs
  3. Degree and distance related parameters
  4. In-built functions for different graph classes
  5. Computation of graph parameters using in-built functions
  6. Graph Operations and Graph Connectivity
  7. Customization of Graphs
  8. Digraphs
  9. Matrices and Algorithms of Graphs
  10. Graph as models.
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to NetworkX package
  2. Construction of graphs
  3. Degree and distance related parameters
  4. In-built functions for different graph classes
  5. Computation of graph parameters using in-built functions
  6. Graph Operations and Graph Connectivity
  7. Customization of Graphs
  8. Digraphs
  9. Matrices and Algorithms of Graphs
  10. Graph as models.
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to NetworkX package
  2. Construction of graphs
  3. Degree and distance related parameters
  4. In-built functions for different graph classes
  5. Computation of graph parameters using in-built functions
  6. Graph Operations and Graph Connectivity
  7. Customization of Graphs
  8. Digraphs
  9. Matrices and Algorithms of Graphs
  10. Graph as models.
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to NetworkX package
  2. Construction of graphs
  3. Degree and distance related parameters
  4. In-built functions for different graph classes
  5. Computation of graph parameters using in-built functions
  6. Graph Operations and Graph Connectivity
  7. Customization of Graphs
  8. Digraphs
  9. Matrices and Algorithms of Graphs
  10. Graph as models.
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to NetworkX package
  2. Construction of graphs
  3. Degree and distance related parameters
  4. In-built functions for different graph classes
  5. Computation of graph parameters using in-built functions
  6. Graph Operations and Graph Connectivity
  7. Customization of Graphs
  8. Digraphs
  9. Matrices and Algorithms of Graphs
  10. Graph as models.
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to NetworkX package
  2. Construction of graphs
  3. Degree and distance related parameters
  4. In-built functions for different graph classes
  5. Computation of graph parameters using in-built functions
  6. Graph Operations and Graph Connectivity
  7. Customization of Graphs
  8. Digraphs
  9. Matrices and Algorithms of Graphs
  10. Graph as models.
Text Books And Reference Books:

Mohammed Zuhair, Kadry, Seifedine, Al-Taie, Python for Graph and Network Analysis.Springer, 2017.

Essential Reading / Recommended Reading
  1. B. N. Miller and D. L. Ranum, Python programming in context. Jones and Bartlett, 2014.
  2. David Joyner, Minh Van Nguyen, David Phillips. Algorithmic Graph Theory and Sage, Free software foundation, 2008.
Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT551D - CALCULUS OF SEVERAL VARIABLES USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course description: The course calculus of several variables using python is aimed at enabling the students to explore and study the calculus with several variables in a detailed manner with the help of the mathematical packages available in Python. This course is designed with a learner-centric approach wherein the students will acquire mastery in understanding multivariate calculus using Python modules.

Course objectives: This course will help the learner to gain a familiarity with

COBJ1. skills to implement Python language in calculus of several variables

COBJ2. the built-in functions available in library to deal with problems in multivariate calculus

Learning Outcome

CO1: The objective is to familiarize students in using Python for demonstrating the plotting of lines in two and three dimensional space

CO2: The objective is to familiarize students in using Python for implementing appropriate codes for finding tangent vector and gradient vector

CO3: The objective is to familiarize students in using Python for evaluating the line and double integrals using sympy module

CO4: The objective is to familiarize students in using Python for acquainting suitable commands for problems in applications of line and double integrals.

Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to basic commands and plotting of graph using matplotlib
  2. Vectors-dot and cross products, plotting lines in two and three-dimensional space, planes and surfaces.
  3. Arc length, curvature and normal vectors.
  4. Curves in sphere: Tangent vectors and velocity- circular helix with velocity vectors.
  5. Functions of two and three variables: graphing numerical functions of two Variables.
  6. Graphing numerical functions in polar coordinates. Partial derivatives and the directional derivative.
  7. The gradient vector and level curves- the tangent plane -the gradient vector field.
  8. Vector fields: Normalized vector fields- two-dimensional plot of the vector field.
  9. Double Integrals: User defined function for calculating double integrals - area properties with double integrals.
  10. Line integrals – Curl and Green’s theorem, divergence theorem.
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to basic commands and plotting of graph using matplotlib
  2. Vectors-dot and cross products, plotting lines in two and three-dimensional space, planes and surfaces.
  3. Arc length, curvature and normal vectors.
  4. Curves in sphere: Tangent vectors and velocity- circular helix with velocity vectors.
  5. Functions of two and three variables: graphing numerical functions of two Variables.
  6. Graphing numerical functions in polar coordinates. Partial derivatives and the directional derivative.
  7. The gradient vector and level curves- the tangent plane -the gradient vector field.
  8. Vector fields: Normalized vector fields- two-dimensional plot of the vector field.
  9. Double Integrals: User defined function for calculating double integrals - area properties with double integrals.
  10. Line integrals – Curl and Green’s theorem, divergence theorem.
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to basic commands and plotting of graph using matplotlib
  2. Vectors-dot and cross products, plotting lines in two and three-dimensional space, planes and surfaces.
  3. Arc length, curvature and normal vectors.
  4. Curves in sphere: Tangent vectors and velocity- circular helix with velocity vectors.
  5. Functions of two and three variables: graphing numerical functions of two Variables.
  6. Graphing numerical functions in polar coordinates. Partial derivatives and the directional derivative.
  7. The gradient vector and level curves- the tangent plane -the gradient vector field.
  8. Vector fields: Normalized vector fields- two-dimensional plot of the vector field.
  9. Double Integrals: User defined function for calculating double integrals - area properties with double integrals.
  10. Line integrals – Curl and Green’s theorem, divergence theorem.
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to basic commands and plotting of graph using matplotlib
  2. Vectors-dot and cross products, plotting lines in two and three-dimensional space, planes and surfaces.
  3. Arc length, curvature and normal vectors.
  4. Curves in sphere: Tangent vectors and velocity- circular helix with velocity vectors.
  5. Functions of two and three variables: graphing numerical functions of two Variables.
  6. Graphing numerical functions in polar coordinates. Partial derivatives and the directional derivative.
  7. The gradient vector and level curves- the tangent plane -the gradient vector field.
  8. Vector fields: Normalized vector fields- two-dimensional plot of the vector field.
  9. Double Integrals: User defined function for calculating double integrals - area properties with double integrals.
  10. Line integrals – Curl and Green’s theorem, divergence theorem.
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to basic commands and plotting of graph using matplotlib
  2. Vectors-dot and cross products, plotting lines in two and three-dimensional space, planes and surfaces.
  3. Arc length, curvature and normal vectors.
  4. Curves in sphere: Tangent vectors and velocity- circular helix with velocity vectors.
  5. Functions of two and three variables: graphing numerical functions of two Variables.
  6. Graphing numerical functions in polar coordinates. Partial derivatives and the directional derivative.
  7. The gradient vector and level curves- the tangent plane -the gradient vector field.
  8. Vector fields: Normalized vector fields- two-dimensional plot of the vector field.
  9. Double Integrals: User defined function for calculating double integrals - area properties with double integrals.
  10. Line integrals – Curl and Green’s theorem, divergence theorem.
Text Books And Reference Books:

H P Langtangen, A Primer on Scientific Programming with Python, 2nd ed., Springer, 2016

Essential Reading / Recommended Reading
  1. B E Shapiro, Scientific Computation: Python Hacking for Math Junkies, Sherwood Forest Books, 2015.
  2. C Hill, Learning Scientific Programming with Python, Cambridge Univesity Press, 2016.
Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT551E - OPERATIONS RESEARCH USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course description: Operations research deals with the problems on optimization or decision making that are affected by certain constraints / restrictions in the environment. This course aims to enhance programming skills in Python to solve problems chosen from Operations Research.

 

Course objectives: This course will help the learner to

COBJ1. gain a familiarity in using Python to solve linear programming problems, calculate the estimates that characteristics the queues and perform desired analysis on a network.

COBJ2. use Python for solving problems on Operations Research.

Learning Outcome

CO1: On successful completion of the course, the students should be able to use Python programming to solve linear programming problems by using simplex method and dual simplex method.

CO2: On successful completion of the course, the students should be able to solve Transportation Problems and Assignment Problems using Python module.

CO3: On successful completion of the course, the students should be able to demonstrate competence in using Python modules to solve M/M/1, M/M/c queues, and Computations on Networks.

Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Simplex method
  2. Dual simplex method
  3. Balanced transportation problem
  4. Unbalanced transportation problem
  5. Assignment problems
  6. (M/M/1) queues
  7. (M/M/c) queues
  8. Shortest path computations in a network
  9. Maximum flow problem
  10. Critical path computations
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Simplex method
  2. Dual simplex method
  3. Balanced transportation problem
  4. Unbalanced transportation problem
  5. Assignment problems
  6. (M/M/1) queues
  7. (M/M/c) queues
  8. Shortest path computations in a network
  9. Maximum flow problem
  10. Critical path computations
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Simplex method
  2. Dual simplex method
  3. Balanced transportation problem
  4. Unbalanced transportation problem
  5. Assignment problems
  6. (M/M/1) queues
  7. (M/M/c) queues
  8. Shortest path computations in a network
  9. Maximum flow problem
  10. Critical path computations
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Simplex method
  2. Dual simplex method
  3. Balanced transportation problem
  4. Unbalanced transportation problem
  5. Assignment problems
  6. (M/M/1) queues
  7. (M/M/c) queues
  8. Shortest path computations in a network
  9. Maximum flow problem
  10. Critical path computations
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Simplex method
  2. Dual simplex method
  3. Balanced transportation problem
  4. Unbalanced transportation problem
  5. Assignment problems
  6. (M/M/1) queues
  7. (M/M/c) queues
  8. Shortest path computations in a network
  9. Maximum flow problem
  10. Critical path computations
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Simplex method
  2. Dual simplex method
  3. Balanced transportation problem
  4. Unbalanced transportation problem
  5. Assignment problems
  6. (M/M/1) queues
  7. (M/M/c) queues
  8. Shortest path computations in a network
  9. Maximum flow problem
  10. Critical path computations
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Simplex method
  2. Dual simplex method
  3. Balanced transportation problem
  4. Unbalanced transportation problem
  5. Assignment problems
  6. (M/M/1) queues
  7. (M/M/c) queues
  8. Shortest path computations in a network
  9. Maximum flow problem
  10. Critical path computations
Text Books And Reference Books:

Garrido José M. Introduction to Computational Models with Python. CRC Press, 2016

Essential Reading / Recommended Reading
  1. A.H. Taha, Operations research, 9th ed., Pearson Education, 2014.
  2. Chinneck, J. W., et al. Operations Research and Cyber-Infrastructure. Springer Science Business Media, LLC, 2009.
  3. Hart, William E. Pyomo: Optimization Modelling in Python. Springer, 2012.
  4. Snyman, Jan A, and Daniel N. Wilke, Practical Mathematical Optimization: Basic Optimization Theory and Gradient-Based Algorithms. Springer., 2018.

 

Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

PHY531 - MODERN PHYSICS - I (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The course discusses the failure of classical mechanics, the origin of wave mechanics, and quantum mechanics in detail. It also discusses the structure of atoms given by various atomic models.

Learning Outcome

CO1: Understand that classical mechanics will not be sufficient to explain the spectrum of black bodies, the photoelectric effect, etc., and the need for quantum mechanics.

CO2: Learn the nature of duality associated with moving bodies.

CO3: Assimilate various uncertainty principles.

CO4: Understand the structure of atoms.

Unit-1
Teaching Hours:15
Introduction to quantum physics
 

Black body radiation - failures of classical physics to explain blackbody radiation spectrum. 

Particle aspects of radiation: Planck’s hypothesis, radiation law, Photoelectric effect Einstein’s explanation, Compton scattering. Bohr atom model, postulates, stability, and line spectrum. 

Wave aspects of particles - de Broglie hypothesis of matter waves, Davisson-Germer experiment, consequences of de Broglie concepts of matter waves - electron microscope. Concepts of wave and group velocities, wave packet.

Heisenberg uncertainty principle: Elementary proof of Heisenberg’s relation between momentum and position, energy and time, angular momentum and angular position, Consequences of the uncertainty relations: Ground state energy of a particle in one-dimensional box, why an electron cannot exist in the nucleus?   

                                                                                              

Unit-1
Teaching Hours:15
Introduction to quantum physics
 

Black body radiation - failures of classical physics to explain blackbody radiation spectrum. 

Particle aspects of radiation: Planck’s hypothesis, radiation law, Photoelectric effect Einstein’s explanation, Compton scattering. Bohr atom model, postulates, stability, and line spectrum. 

Wave aspects of particles - de Broglie hypothesis of matter waves, Davisson-Germer experiment, consequences of de Broglie concepts of matter waves - electron microscope. Concepts of wave and group velocities, wave packet.

Heisenberg uncertainty principle: Elementary proof of Heisenberg’s relation between momentum and position, energy and time, angular momentum and angular position, Consequences of the uncertainty relations: Ground state energy of a particle in one-dimensional box, why an electron cannot exist in the nucleus?   

                                                                                              

Unit-2
Teaching Hours:15
Quantum mechanics
 

Schrödinger equation: equation of motion of matter waves - Schrodinger wave equation for a free particle in one- and three-dimensions, Schrodinger wave equation for a particle in the presence of force field, time-dependent and time-independent wave equations, Physical interpretation of the wave function - normalization and orthogonality of wave functions, Probability and probability current density, Admissibility conditions on a wave function. Quantum operators, Eigenfunction and eigenvalue. Expectation values, Postulates of quantum mechanics. Quantum particles under boundary conditions, Applications of quantum mechanics Transmission across a potential barrier, the tunnel effect (qualitative), and particles in a one-dimensional box. One-dimensional simple harmonic oscillator (qualitative) - the concept of zero-point energy.  

                                                                                                

Unit-2
Teaching Hours:15
Quantum mechanics
 

Schrödinger equation: equation of motion of matter waves - Schrodinger wave equation for a free particle in one- and three-dimensions, Schrodinger wave equation for a particle in the presence of force field, time-dependent and time-independent wave equations, Physical interpretation of the wave function - normalization and orthogonality of wave functions, Probability and probability current density, Admissibility conditions on a wave function. Quantum operators, Eigenfunction and eigenvalue. Expectation values, Postulates of quantum mechanics. Quantum particles under boundary conditions, Applications of quantum mechanics Transmission across a potential barrier, the tunnel effect (qualitative), and particles in a one-dimensional box. One-dimensional simple harmonic oscillator (qualitative) - the concept of zero-point energy.  

                                                                                                

Unit-3
Teaching Hours:15
Atomic physics
 

Structure of atom - Bohr’s model of the hydrogen atom. Excitation and ionization potentials, Frank-Hertz experiment, Orbital angular momentum and orbital magnetic dipole moment, Bohr magneton, Larmor precession, Space quantization, Stern-Gerlach experiment, the concept of spin and spin hypothesis, Spin angular momentum,

Vector model of the atom: Spin-orbit interaction - magnetic moment due to orbital and spin motion (qualitative), Coupling schemes- LS and jj, Quantum numbers associated with vector atom model, Spectral terms, Selection rules, Pauli exclusion principle, the electron configuration of single valence electron atoms (alkali spectra) and two-valence electron atoms and their spectra (s, p, d, and f series).

Magnetic field effect: Expression for magnetic interaction energy, strong and weak magnetic field effects- normal and anomalous Zeeman effects, energy level diagram for sodium D lines.  

 

                                                                                                                                    

Unit-3
Teaching Hours:15
Atomic physics
 

Structure of atom - Bohr’s model of the hydrogen atom. Excitation and ionization potentials, Frank-Hertz experiment, Orbital angular momentum and orbital magnetic dipole moment, Bohr magneton, Larmor precession, Space quantization, Stern-Gerlach experiment, the concept of spin and spin hypothesis, Spin angular momentum,

Vector model of the atom: Spin-orbit interaction - magnetic moment due to orbital and spin motion (qualitative), Coupling schemes- LS and jj, Quantum numbers associated with vector atom model, Spectral terms, Selection rules, Pauli exclusion principle, the electron configuration of single valence electron atoms (alkali spectra) and two-valence electron atoms and their spectra (s, p, d, and f series).

Magnetic field effect: Expression for magnetic interaction energy, strong and weak magnetic field effects- normal and anomalous Zeeman effects, energy level diagram for sodium D lines.  

 

                                                                                                                                    

Text Books And Reference Books:

[1].Kamal, S., & Singh, S. P. (2005). Elements of quantum mechanics: S. Chand & Company Ltd, 2005.

[2].Serway, & Jewett. (2014). Physics for scientists and engineers with modern physics (9th ed.): Cengage Learning.

[3].Arora, C. L. & Hemne, P. S. (2014). Physics for degree students B.Sc., third year: S.

Chand & Company Pvt. Ltd.

Essential Reading / Recommended Reading

[4].Thomas, A. Moore. (2003). Six ideas that shaped physics: particles behave like waves: McGraw Hill.

[5].Wichman, E. H. (2008). Quantum physics - Berkeley physics course Vol.4: Tata McGraw-Hill.      

[6].Beiser, A. (2009). Concepts of modern physics: McGraw-Hill. 

[7].Taylor, J. R., Zafiratos, P. D., & Dubson, M. A. (2009). Modern physics: PHI Learning.

[8].Kaur, G., & Pickrell, G. R. (2014).  Modern physics: McGraw Hill.             

    

Evaluation Pattern

 

 

Component

Schedule

Duration

Marks

Marks reduced to

CIA I

Assignment/test/group task/presentation

Before Mid Semester Test (MST)

 

20

10

CIA II

Mid Semester Test (MST)

Centralised

2 hours

50

 

 

25

CIA III

Assignment/test/group task/presentation

After MST

 

20

 

 

10

Attendance

75 – 79, 1 mark, 80 – 84, 2 marks, 85 – 89, 3 marks, 90 – 94, 4 marks, 95 – 100, 5 marks

 

05

ESE

Centralised

3 hours

100

 

50

 

                                                    Total

 

100

PHY541A - ANALOG AND DIGITAL ELECTRONICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This course gives the students exposure to the fundamentals of solid state electronics and develops the subject to cover basic amplifiers and oscillators, On the digital side, fundamental digital arithmetic is focused on and logic gates are also introduced to enable simple computations. Units I to III caters to local and regional needs.

Learning Outcome

CO1: Understand the basic concepts of analog and digital electronics including semiconductor properties, operational amplifiers, logic gates, combinational and sequential logic.

CO2: Apply the theoretical knowledge to design electronic circuits.

CO3: Solve specific theoretical and applied problems in electronics.

Unit-1
Teaching Hours:15
Electronic Devices
 

Semiconductor diodes: p and n type semiconductors. Barrier formation in PN junction diode. Qualitative idea of current flow mechanism in Forward and Reverse biased diode. PN junction and its characteristics. static and dynamic resistance.

Half-wave rectifiers. Centre-tapped and bridge full-wave rectifiers. Calculation of ripple factor and rectification efficiency. Basic idea about capacitor filter, Zener diode and voltage regulation

Bipolar Junction Transistors: n-p-n and p-n-p transistors. Characteristics of CB, CE and CC Configurations. Active, cutoff, and saturation regions. Current gains α and β. Relations between α and β. Load Line analysis of transistors. DC load line and Q-point. Voltage divider bias circuit for CE amplifier. h-parameter equivalent circuit. Analysis of a single-stage CE amplifier using Hybrid model. Input and output Impedance. Current, voltage and power Gains.                                                                                                                           

Unit-1
Teaching Hours:15
Electronic Devices
 

Semiconductor diodes: p and n type semiconductors. Barrier formation in PN junction diode. Qualitative idea of current flow mechanism in Forward and Reverse biased diode. PN junction and its characteristics. static and dynamic resistance.

Half-wave rectifiers. Centre-tapped and bridge full-wave rectifiers. Calculation of ripple factor and rectification efficiency. Basic idea about capacitor filter, Zener diode and voltage regulation

Bipolar Junction Transistors: n-p-n and p-n-p transistors. Characteristics of CB, CE and CC Configurations. Active, cutoff, and saturation regions. Current gains α and β. Relations between α and β. Load Line analysis of transistors. DC load line and Q-point. Voltage divider bias circuit for CE amplifier. h-parameter equivalent circuit. Analysis of a single-stage CE amplifier using Hybrid model. Input and output Impedance. Current, voltage and power Gains.                                                                                                                           

Unit-2
Teaching Hours:15
Analog electronics
 

Op Amps: Characteristics of an ideal and practical Op-Amp (IC 741), Open-loop& closed-loop gain. CMRR, Concept of virtual ground. Applications of Op-Amps: (1) Inverting and Non-inverting Amplifiers, (2) Adder, (3) Subtractor, (4) Differentiator, (5) Integrator, (6) Zero Crossing Detector. Sinusoidal oscillators: Barkhausen's criterion for self-sustained oscillations. Determination of frequency of RC oscillator

Unit-2
Teaching Hours:15
Analog electronics
 

Op Amps: Characteristics of an ideal and practical Op-Amp (IC 741), Open-loop& closed-loop gain. CMRR, Concept of virtual ground. Applications of Op-Amps: (1) Inverting and Non-inverting Amplifiers, (2) Adder, (3) Subtractor, (4) Differentiator, (5) Integrator, (6) Zero Crossing Detector. Sinusoidal oscillators: Barkhausen's criterion for self-sustained oscillations. Determination of frequency of RC oscillator

Unit-3
Teaching Hours:15
Digital Electronics
 

Difference between analog and digital circuits. Binary numbers. Decimal to binary and binary to decimal conversion, AND, OR and NOT Gates (realization using Diodes and Transistor). NAND and NOR gates as universal gates. XOR and XNOR gates. De Morgan's theorems. Boolean Laws. Simplification of logic circuit using Boolean algebra. Fundamental products. Minterms and maxterms. Simplification of SOP equations. Karnaugh map (upto 4 variables). Binary addition. Binary subtraction using 2's complement method). Half adders and full adders and subtractors. Flip Flops RS and JK, Binary and decimal counters. Timer IC: IC 555 Pin diagram and its application as astable & monostable multivibrator.                                                                                                              

Unit-3
Teaching Hours:15
Digital Electronics
 

Difference between analog and digital circuits. Binary numbers. Decimal to binary and binary to decimal conversion, AND, OR and NOT Gates (realization using Diodes and Transistor). NAND and NOR gates as universal gates. XOR and XNOR gates. De Morgan's theorems. Boolean Laws. Simplification of logic circuit using Boolean algebra. Fundamental products. Minterms and maxterms. Simplification of SOP equations. Karnaugh map (upto 4 variables). Binary addition. Binary subtraction using 2's complement method). Half adders and full adders and subtractors. Flip Flops RS and JK, Binary and decimal counters. Timer IC: IC 555 Pin diagram and its application as astable & monostable multivibrator.                                                                                                              

Text Books And Reference Books:

[1].Solid State Electronic Devices, Ben. G. Streetman, 7th Ed,  2015, Pearson Education India

[2].Digital Principles & Applications, A.P. Malvino, D.P. Leach & Saha, 7th Ed.,2011, Tata McGraw Hill.

Essential Reading / Recommended Reading

 

[1] Op-Amp and Linear Digital Circuits, R. A. Gayakwad, 2000, PHI Learning Pvt. Ltd. [4].Integrated Electronics, J. Millman and C. C. Halkias, 1991, Tata Mc-Graw Hill. 

Evaluation Pattern

No

Components

Marks

CIA1

Assignments

10

CIA2

MSE

25

CIA3

Quiz, MCQ test, presentation,project, MOOC

10

Attendance

 

05

ESE

Centralized

50

Total

 

100

 

PHY541B - RENEWABLE ENERGY AND APPLICATIONS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This module makes the students familiar with the significance of Energy

resources in daily life. The important energy sources like solar photovoltaic & solar thermal

energy, wind energy, and ocean energy are discussed. Advancement in the field of fuel cells

and hydrogen as an energy source is also highlighted. Units I to III caters to regional and

national needs.

Learning Outcome

CO1: Understand the developments in Renewable energy resources (Solar, Wind and Tidal) and its significance.

CO2: Learn about the emerging developments in energy research (Fuel cells, OTEC).

CO3: Gain the basic skills needed to start entrepreneurship pertaining to local and regional needs.

Unit-1
Teaching Hours:15
Solar Thermal and Photovoltaic Energy
 

Review of energy resources, Sustainable energy,  Energy Scenario in India, Conventional energy sources, Non-Conventional Energy Resources,  Solar energy- Solar Spectrum, Extraterrestrial and Terrestrial radiation, Solar time, Solar day, hour angle,  Intensity of solar radiation, solar thermal energy collector, Flat plate collector, Concentration type collector, solar cell fundamentals, solar photovoltaics, PN Junction solar cells, study of I-V characteristic, calculation of efficiency and fill factor, semiconductor materials for solar cell,  solar photovoltaic module, photovoltaic system for power generation, case study analysis of solar photovoltaic system.

Unit-1
Teaching Hours:15
Solar Thermal and Photovoltaic Energy
 

Review of energy resources, Sustainable energy,  Energy Scenario in India, Conventional energy sources, Non-Conventional Energy Resources,  Solar energy- Solar Spectrum, Extraterrestrial and Terrestrial radiation, Solar time, Solar day, hour angle,  Intensity of solar radiation, solar thermal energy collector, Flat plate collector, Concentration type collector, solar cell fundamentals, solar photovoltaics, PN Junction solar cells, study of I-V characteristic, calculation of efficiency and fill factor, semiconductor materials for solar cell,  solar photovoltaic module, photovoltaic system for power generation, case study analysis of solar photovoltaic system.

Unit-2
Teaching Hours:15
Wind and Ocean Energy
 

Origin of winds, Factors affecting wind energy, Nature of winds, Variation of wind speed with height. Energy available in wind- power extraction- Betz limit- Types of Wind turbine- Horizontal axis turbine-Vertical axis wind turbine- Case study analysis. Origin and nature of tidal energy, Tidal energy estimation, tidal energy conversion schemes, Single basin arrangement.Energy and Power from waves, Environmental impacts of Ocean Energy generation. Ocean thermal energy conversion system (OTEC), principle and systems.

Unit-2
Teaching Hours:15
Wind and Ocean Energy
 

Origin of winds, Factors affecting wind energy, Nature of winds, Variation of wind speed with height. Energy available in wind- power extraction- Betz limit- Types of Wind turbine- Horizontal axis turbine-Vertical axis wind turbine- Case study analysis. Origin and nature of tidal energy, Tidal energy estimation, tidal energy conversion schemes, Single basin arrangement.Energy and Power from waves, Environmental impacts of Ocean Energy generation. Ocean thermal energy conversion system (OTEC), principle and systems.

Unit-3
Teaching Hours:15
Emerging trends in Renewable Energy Sources
 

Fuel cell- Thermodynamics- Calculation of Gibbs free energy and theoretical voltage of a fuel cell, Variation of efficiency of fuel cell with temperature – comparision with Carnot cycle efficiency.  Classification of fuel cells –Phosphoric acid Fuel cell (PAFC), Alkaline Fuel Cell(AFC) –Solid polymer Fuel cell(SPFC) Molten carbonate Fuel cell (MCFC) Solid oxide Fuel cell (SOFC) FUEL for FUEL cells-efficiency of a fuel cell- V-I characteristics of Fuel cell. Losses in fuel cells: Activation polarization- resistance polarization- concentration polarization- Fuel cell power plant hydrogen energy- production- storage conversion to energy sources and safety issues. Thermolectric power conversion, Thermoelectric power generator.                                                                 

Unit-3
Teaching Hours:15
Emerging trends in Renewable Energy Sources
 

Fuel cell- Thermodynamics- Calculation of Gibbs free energy and theoretical voltage of a fuel cell, Variation of efficiency of fuel cell with temperature – comparision with Carnot cycle efficiency.  Classification of fuel cells –Phosphoric acid Fuel cell (PAFC), Alkaline Fuel Cell(AFC) –Solid polymer Fuel cell(SPFC) Molten carbonate Fuel cell (MCFC) Solid oxide Fuel cell (SOFC) FUEL for FUEL cells-efficiency of a fuel cell- V-I characteristics of Fuel cell. Losses in fuel cells: Activation polarization- resistance polarization- concentration polarization- Fuel cell power plant hydrogen energy- production- storage conversion to energy sources and safety issues. Thermolectric power conversion, Thermoelectric power generator.                                                                 

Text Books And Reference Books:

1. Rajesh, K. P. & Ojha, T.P. (2012).  Non-Conventional Energy Sources (3rd ed.), New Delhi: Jain Brothers.

2. Hasan Saeed, S. & Sharma, D.K. (2012).  Non-Conventional Energy Resources, New Delhi: S.K. Kataria & Sons.

3. Khan, B. H. (2006).  Non-conventional energy resources, New Delhi: Tata McGraw Hill.

4. Rai, G. D. (2000). Non-conventional energy sources(4th ed.): Khanna Publishers. 

Essential Reading / Recommended Reading

5. Rao, S. & Parulekar, B. B. (1999). Energy Technology, Non-Conventional, Renewable and Conventional (3rd ed.): Khanna Publications.

6. Gupta, B. R. (1998). Generation of electrical energy: Eurasia Publishing House.

7. Solanki, C.S. (2015). Renewable Energy Technologies: A practical guide for beginners, New Delhi: PHI Learning.

Evaluation Pattern

Continuous Internal Assessment (CIA) 50%,   End Semester Examination (ESE) 50%

 

Component     

Schedule

Duration

Marks

Marks reduced to

CIA I

Assignment/test/group task/presentation

Before Mid Semester Test (MST)

 

20

10

CIA II

Mid Semester Test (MST)

Centralised

2 hours

50

 

 

25

CIA III

Assignment/test/group task/presentation

After MST

 

20

 

 

10

Attendance

75 – 79, 1 mark, 80 – 84, 2 marks, 85 – 89, 3 marks, 90 – 94, 4 marks, 95 – 100, 5 marks

 

05

ESE

Centralised

3 hours

100

 

50

 

                                                    Total

 

100

PHY541C - ASTRONOMY AND ASTROPHYSICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description: This module introduces students to the exciting field of astrophysics. This covers the topics such as Fundamentals of Astrophysics, Astronomical Techniques, Sun and Solar System and Stellar Structure. Units I to III cater to national and global needs.

 

Learning Outcome

CO1: Get familiarized with the basic properties of stars such as magnitude, spectral type, flux and temperature.

CO2: Develop a basic understanding about various processes associated with star formation.

CO3: Understand how distinctly high mass stars evolve when compared to the Sun.

CO4: Acquire a brief overview about the formation and the expansion of the universe.

Unit-1
Teaching Hours:15
Introduction to astronomy
 

Stars in the Broader Context of Modern Astrophysics - Useful Astronomical Units – Coordinate systems - Distances – Masses - Luminosity and Magnitudes. Galactic Chemical Evolution. Stellar populations.

Basic properties of stars: Introduction - Stellar Distances - Proper Motion - Doppler Shift and Space Motion - Effective Temperatures of Stars. Spectral classification and the HR diagram - Continuum, absorption, and emission spectra of astronomical sources - Collisional excitation and ionization - Stellar Spectral Types - Luminosity Classes - Cluster HR Diagrams. Binary stars - Visual Binaries - Spectroscopic Binaries - Eclipsing Binaries - The Stellar Mass-Luminosity Relation.

Unit-1
Teaching Hours:15
Introduction to astronomy
 

Stars in the Broader Context of Modern Astrophysics - Useful Astronomical Units – Coordinate systems - Distances – Masses - Luminosity and Magnitudes. Galactic Chemical Evolution. Stellar populations.

Basic properties of stars: Introduction - Stellar Distances - Proper Motion - Doppler Shift and Space Motion - Effective Temperatures of Stars. Spectral classification and the HR diagram - Continuum, absorption, and emission spectra of astronomical sources - Collisional excitation and ionization - Stellar Spectral Types - Luminosity Classes - Cluster HR Diagrams. Binary stars - Visual Binaries - Spectroscopic Binaries - Eclipsing Binaries - The Stellar Mass-Luminosity Relation.

Unit-2
Teaching Hours:15
Stellar astrophysics
 

The physical laws of stellar structure, Hydrostatic Equilibrium, Equation of state, Modes of energy transport, Gravitational contraction, thermonuclear reactions.

Star formation: Protostars, pre-main sequence stars, main-sequence stars, Brown dwarfs. 

Stellar evolution: evolution of low mass stars, evolution of high mass stars, Synthesis of elements in stars. Final fate of stars: White dwarfs, Neutron stars, Pulsars, Black holes - Schwarzschild radius.

Unit-2
Teaching Hours:15
Stellar astrophysics
 

The physical laws of stellar structure, Hydrostatic Equilibrium, Equation of state, Modes of energy transport, Gravitational contraction, thermonuclear reactions.

Star formation: Protostars, pre-main sequence stars, main-sequence stars, Brown dwarfs. 

Stellar evolution: evolution of low mass stars, evolution of high mass stars, Synthesis of elements in stars. Final fate of stars: White dwarfs, Neutron stars, Pulsars, Black holes - Schwarzschild radius.

Unit-3
Teaching Hours:15
Galaxies and universe
 

Structure of the Milky way Galaxy, Star clusters, Hubble’s classification of galaxy, galactic dynamics, Kepler’s third law and the galaxy’s mass. Universe: Galaxies beyond the Milky way, Theories of universe, Olbers’ paradox, Hubble’s law and the distance scale, expanding universe, Cosmic microwave background radiation, origin and evolution of the universe.

Unit-3
Teaching Hours:15
Galaxies and universe
 

Structure of the Milky way Galaxy, Star clusters, Hubble’s classification of galaxy, galactic dynamics, Kepler’s third law and the galaxy’s mass. Universe: Galaxies beyond the Milky way, Theories of universe, Olbers’ paradox, Hubble’s law and the distance scale, expanding universe, Cosmic microwave background radiation, origin and evolution of the universe.

Text Books And Reference Books:

[1]. M. Zeilik and S. A. Gregory: Introductory Astronomy and Astrophysics, Saunders College Publication, 1998.

[2]. B. W. Carroll and D. A. Ostlie: An Introduction to Modern Astrophysics, Pearson Addison-Wesley, 2007.

[3]. R. Bowers and T. Deeming: Astrophysics I & II, Bartlett, 1984,

[4]. R. Kippenhahn, A. Weigert and A. Weiss: Stellar Structure and Evolution, 2 nd Edn, Springer-Verlag, 1990.

Essential Reading / Recommended Reading

[5]. J. P. Cox and R. T. Giuli: Principles of Stellar structure, Golden-Breah, 1968.

[6]. M. Harwit: Astronomy Concepts, Springer-Verlag, 1988

[7]. W. J. Kaufmann: Universe, W. H. Freeman and Company, 4th Edn.1994.

[8]. K. F. Kuhn: Astronomy -A Journey into Science, West Publishing Company, 1989

[9]. H. Zirin: Astrophysics of the Sun, CUP, 1988.

[10]. P. V. Foukal: Solar Astrophysics, John Wiley, 1990.

Evaluation Pattern

Continuous Internal Assessment (CIA) 50%, End Semester Examination (ESE) 50%

CIA I (Assignment/test/group task/presentation) - Before Mid Semester Exam (MSE) - 20 Marks - Reduced to 10 Marks

CIA II (Mid Semester Test (MST)) - Centralised - 50 Marks - Reduced to 25 Marks

CIA III (Assignment/test/group task/presentation) - After MST - 20 Marks - Reduced to 10 Marks

Attendance (75 – 79: 1 mark, 80 – 84: 2 marks, 85 – 89: 3 marks, 90 – 94: 4 marks, 95 – 100: 5 marks) - 5 Marks

End Semester Exam - Centralised - 100 Marks - Reduced to 50 Marks

PHY551 - MODERN PHYSICS - I LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

The experiments related to atomic and modern physics included in this course expose the students to many fundamental experiments in physics and their detailed analysis and conclusions. This provides a strong foundation to the understanding of physics.

Learning Outcome

CO1: Understand the theory involved with the experiment

CO2: Appreciate the developments in modern physics through experiments.

CO3: Analyze the experimental data with the standard data.

Unit-1
Teaching Hours:30
List of experiments
 

1.Determination of Planck’s constant using photocell and LEDs/filters.

2.Determination of absorption coefficient of light in KMnO4 and water media. 

3.Study of black body radiation and determination of Stefan-Boltzmann constant.

4.Determination of wavelength of absorption bands of KMnO4.

5.Determination of e/m of the electron using Thomson’s method.

6.Determination of ionization potential of mercury/xenon.

7.Study of the hydrogen spectrum and determination of the Rydberg constant.

8.Study of photoelectric effect: verification of observations of photoelectric effect and determination of work function.

9.Determination of charge of the electron using the Millikan oil drop method.

10.  Study of the Zeeman effect

Unit-1
Teaching Hours:30
List of experiments
 

1.Determination of Planck’s constant using photocell and LEDs/filters.

2.Determination of absorption coefficient of light in KMnO4 and water media. 

3.Study of black body radiation and determination of Stefan-Boltzmann constant.

4.Determination of wavelength of absorption bands of KMnO4.

5.Determination of e/m of the electron using Thomson’s method.

6.Determination of ionization potential of mercury/xenon.

7.Study of the hydrogen spectrum and determination of the Rydberg constant.

8.Study of photoelectric effect: verification of observations of photoelectric effect and determination of work function.

9.Determination of charge of the electron using the Millikan oil drop method.

10.  Study of the Zeeman effect

Text Books And Reference Books:

[1].Serway, & Jewett. (2014). Physics for scientists and engineers with modern physics (9th ed.): Cengage Learning.

[2].Wichman, E. H. (2008). Quantum physics - Berkeley physics course Vol.4: Tata McGraw-Hill.  

Essential Reading / Recommended Reading

[3].Beiser, A. (2009). Concepts of modern physics: McGraw-Hill. 

[4].Taylor, J. R., Zafiratos, P. D., & Dubson, M. A. (2009). Modern physics: PHI Learning.

 

Evaluation Pattern

 

Component

Duration

Marks

CIA

Class work, Prelab assignment, MST

 

30

ESE

Experiment and viva voce

3 hours

 

20

                                                                                   Total

50

 

PHY551A - ANALOG AND DIGITAL ELECTRONICS LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

This course gives a good understanding of the functioning and applications of basic solid-state electronic devices and their circuits like amplifiers and oscillators.

Learning Outcome

CO1: Understand and get familiarized with assembling basic electronic building block circuits.

CO2: Understand the working of various analog and digital electronics devices.

CO3: Acquire practical skills that enable them to get employed in industries or pursue higher studies or research assignments that meet the local and national needs.

Unit-1
Teaching Hours:30
List of experiments
 

Study and compare IV characteristics of PN diode, Zener diode, LED.

2. To study transistor characteristics in CE mode

3. To design an inverting amplifier of given gain using Op-amp 741 and study its frequency response

4. To design a non-inverting amplifier of given gain using Op-amp 741 and study its Frequency Response.

5. To design a phase shift oscillator for a given frequency of operation using an Op amp.

6. Op amp as differentiator

7. Op amp as integrator

8. Half wave and Full wave Rectifiers

7. To verify and design AND, OR, NOT, and XOR gates using NAND.

9. Half and full adder circuits.

10. Astable multivibrator of given specifications using 555 Timer IC.

11. Monostable multivibrator of given specifications using 555 Timer IC.

 

Unit-1
Teaching Hours:30
List of experiments
 

Study and compare IV characteristics of PN diode, Zener diode, LED.

2. To study transistor characteristics in CE mode

3. To design an inverting amplifier of given gain using Op-amp 741 and study its frequency response

4. To design a non-inverting amplifier of given gain using Op-amp 741 and study its Frequency Response.

5. To design a phase shift oscillator for a given frequency of operation using an Op amp.

6. Op amp as differentiator

7. Op amp as integrator

8. Half wave and Full wave Rectifiers

7. To verify and design AND, OR, NOT, and XOR gates using NAND.

9. Half and full adder circuits.

10. Astable multivibrator of given specifications using 555 Timer IC.

11. Monostable multivibrator of given specifications using 555 Timer IC.

 

Text Books And Reference Books:

Basic Electronics: A text lab manual, P.B. Zbar, A.P. Malvino, M.A. Miller, 1994, Mc-Graw Hill.

[2]. Electronic circuits and devices by Boylstead, Pearson Education 2002 Electronic circuits and devices by Boylstead, Pearson Education 2002

BSc– Physics– Syllabus 2014-15 15

[3]. OP-Amps and Linear Integrated Circuit, R. A. Gayakwad, 4th edition, 2000, Prentice Hall.

Essential Reading / Recommended Reading

Basic Electronics: A text lab manual, P.B. Zbar, A.P. Malvino, M.A. Miller, 1994, Mc-Graw Hill.

Evaluation Pattern

No

Components

Marks

CIA1

pre lab

10

CIA2

MSE

10

CIA3

post lab

10

     

ESE

Centralized

20

Total

 

50

 

PHY551B - RENEWABLE ENERGY AND APPLICATIONS LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

This module makes the students get the practical knowledge of Energy resources & converters. The important energy sources like solar photovoltaic, thermo electric power and Fuel cells are highlighted. 

Learning Outcome

CO1: Understand the working of energy conversion devices used in renewable energy

CO2: Calculate the thermodynamic parameters (efficiency, fill factor, Gibbs free energy, entropy etc.)

CO3: Know about the latest developments and emerging trends in renewable energy devices (Fuel cells, Hydrogen generation etc.)

CO4: Apply the concepts for solving local, national and global energy problems

Unit-1
Teaching Hours:30
Renewable Energy and Applications Lab
 

List of experiments

 1. Thermo emf analysis-Verification of thermoelectric laws

2. V-I characteristics of a solar cell

3. Efficiency and fill factor of solar cell

4. Verification of Inverse square law of a solar cell

5. Photo transistor-Characteristics

6. Thermo electric power of n-type and p-type Bismuth Telluride by differential method.

7. Verification of Fuel cell characteristics.

8. Measurement of Piezoelectric constant of PVDF

Unit-1
Teaching Hours:30
Renewable Energy and Applications Lab
 

List of experiments

 1. Thermo emf analysis-Verification of thermoelectric laws

2. V-I characteristics of a solar cell

3. Efficiency and fill factor of solar cell

4. Verification of Inverse square law of a solar cell

5. Photo transistor-Characteristics

6. Thermo electric power of n-type and p-type Bismuth Telluride by differential method.

7. Verification of Fuel cell characteristics.

8. Measurement of Piezoelectric constant of PVDF

Text Books And Reference Books:

[1]. Chetan Singh Solanki, Renewable Energy Technologies: A practical guide for beginners, PHI Learning (Pvt) Ltd, New Delhi, 2013.

[2]. B. H. Khan: Non-conventional energy resources, TMH publishing, New Delhi2006.

[3].Rai, G. D. (2000). Non-conventional energy sources (4th ed.): Khanna Publishers. 

 

 

Essential Reading / Recommended Reading

[5].Rao, S., & Parulekar, B. B. (1999). Energy technology, non-conventional, renewable and conventional (3rd ed.): Khanna Publications.

 

[6].Gupta, B. R. (1998). Generation of electrical energy: Eurasia Publishing House.

[7].Solanki, C.S. (2015). Renewable energy technologies: A practical guide for beginners, New Delhi: PHI Learning. 

 

Evaluation Pattern

Practical

Continuous Internal Assessment (CIA) 60%,   End Semester Examination (ESE) 40%

 

Component

Duration

Marks

CIA

Class work, Prelab assignment, MST

 

30

ESE

Experiment and viva voce

3 hours

 

20

                                                                                   Total

50

 

PHY551C - ASTRONOMY AND ASTROPHYSICS LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

This lab module makes the students familiar with the various experiments in Astrophysics. The suits of experiments cover a broad spectrum from the color-magnitude diagram of star clusters to the study of the expansion of the universe. 

Learning Outcome

CO1: Analyze the spectra of stars and evaluate how the spectral lines vary for stars of various spectral types.

CO2: Construct the color-magnitude diagram of star clusters and understand the evolutionary phase of a star from its location in the diagram.

CO3: Study various distance measurement techniques and analyze the kinematics of stars.

CO4: Study the distance - redshift relation which was developed by Edwin Hubble to understand the expansion of the universe.

Unit-1
Teaching Hours:30
List of experiments
 

1. To study the spectral classification of a given sample of stars.

2. To construct the HR Diagram of Star Clusters

3. To study the sunspots using CLEA software

4. To determine the distance of star clusters using CLEA software

5.To study the chemical composition of evolved stars

6. To acquire the magnitude data for star cluster from Webda database and estimate the age

7. To determine the membership of stars in clusters using Gaia data

8. To estimate the equivalent width measurements of emission line stars

Unit-1
Teaching Hours:30
List of experiments
 

1. To study the spectral classification of a given sample of stars.

2. To construct the HR Diagram of Star Clusters

3. To study the sunspots using CLEA software

4. To determine the distance of star clusters using CLEA software

5.To study the chemical composition of evolved stars

6. To acquire the magnitude data for star cluster from Webda database and estimate the age

7. To determine the membership of stars in clusters using Gaia data

8. To estimate the equivalent width measurements of emission line stars

Text Books And Reference Books:

[1] W. J. Kaufmann: Universe, W. H. Freeman and Company, 4th Edn.1994.

[2] K. F. Kuhn: Astronomy -A Journey into Science, West Publishing Company, 1989

[3] H. Zirin: Astrophysics of the Sun, CUP, 1988.

[4] P. V. Foukal: Solar Astrophysics, John Wiley, 1990.

Essential Reading / Recommended Reading

Some of the experiments are planned using CLEA software (http://www3.gettysburg.edu/~marschal/clea/speclab.html)

 

Evaluation Pattern

 

Component

Duration

Marks

CIA

Class work, Prelab assignment, MST

 

30

ESE

Experiment and viva voce

3 hours

 

20

                                                                                   Total

50

 

ELE631 - VERILOG AND FPGA BASED DESIGN (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Verilog is a Hardware Description Language (HDL) used to model and synthesize digital systems. Applied to electronic design, Verilog is used for verification via simulation, timing analysis, logic synthesis and test analysis. This course emphasizes a deep understanding of concepts in Verilog through theory as well as practical exercises to reinforce basic concepts.

Learning Outcome

CO1: Design and manually optimize complex combinational and sequential digital circuits

CO2: Model combinational and sequential digital circuits by Verilog HDL

CO3: Design and model digital circuits with Verilog HDL at behavioural, structural, and RTL Levels

CO4: Develop skills towards the international needs of the VLSI industry and prepare oneself to be an entrepreneur.

Unit-1
Teaching Hours:15
Digital Logic and FPGA Architecture
 

 

Review of combinational circuits. Combinational building blocks: multiplexers, demultiplexers, decoders, encoders and adder circuits. Review of sequential circuit elements: flip-flop, latch and register. Finite state machines: Mealy and Moore. Other sequential circuits: shift registers and counters. FSMD (Finite State Machine with Datapath): design and analysis. Microprogrammed control. Memory basics and timing. Programmable Logic Devices.

 Introduction to all types of Programmable Logic Devices- PLA & PAL- FPGA Generic Architecture. ALTERA Cyclone II Architecture –Timing Analysis and Power analysis using Quartus SOPC Builder- NIOS-II Soft-core Processor- System Design Examples using ALTERA FPGAs – Traffic light Controller, Real-Time Clock - Interfacing using FPGA: VGA, Keyboard, LCD.

Unit-1
Teaching Hours:15
Digital Logic and FPGA Architecture
 

 

Review of combinational circuits. Combinational building blocks: multiplexers, demultiplexers, decoders, encoders and adder circuits. Review of sequential circuit elements: flip-flop, latch and register. Finite state machines: Mealy and Moore. Other sequential circuits: shift registers and counters. FSMD (Finite State Machine with Datapath): design and analysis. Microprogrammed control. Memory basics and timing. Programmable Logic Devices.

 Introduction to all types of Programmable Logic Devices- PLA & PAL- FPGA Generic Architecture. ALTERA Cyclone II Architecture –Timing Analysis and Power analysis using Quartus SOPC Builder- NIOS-II Soft-core Processor- System Design Examples using ALTERA FPGAs – Traffic light Controller, Real-Time Clock - Interfacing using FPGA: VGA, Keyboard, LCD.

Unit-2
Teaching Hours:15
Verilog HDL Coding Basics
 

Introduction to HDL, need Lexical Conventions - Ports and Modules Operators - Gate Level Modeling - System Tasks and Compiler Directives - Test Bench - Data Flow Modeling - Behavioral level Modeling -Tasks and Functions. Behavioural, Data Flow and Structural Realization– Adders – Multipliers-Comparators

Unit-2
Teaching Hours:15
Verilog HDL Coding Basics
 

Introduction to HDL, need Lexical Conventions - Ports and Modules Operators - Gate Level Modeling - System Tasks and Compiler Directives - Test Bench - Data Flow Modeling - Behavioral level Modeling -Tasks and Functions. Behavioural, Data Flow and Structural Realization– Adders – Multipliers-Comparators

Unit-3
Teaching Hours:15
Verilog HDL Coding Advanced
 

 

Flip Flops -Realization of Shift Register - Realization of a Counter- Synchronous and Asynchronous FIFO. Single port and Dual-port RAM – Pseudo-Random LFSR – Cyclic Redundancy check.

State diagram-state table – state assignment-choice of flip-flops –  Timing diagram – One hot encoding - Mealy and Moore state machines – Design of serial adder using Mealy and Moore state machines - State minimization – Sequence detection

Unit-3
Teaching Hours:15
Verilog HDL Coding Advanced
 

 

Flip Flops -Realization of Shift Register - Realization of a Counter- Synchronous and Asynchronous FIFO. Single port and Dual-port RAM – Pseudo-Random LFSR – Cyclic Redundancy check.

State diagram-state table – state assignment-choice of flip-flops –  Timing diagram – One hot encoding - Mealy and Moore state machines – Design of serial adder using Mealy and Moore state machines - State minimization – Sequence detection

Text Books And Reference Books:

 [1]. Palnitkar, Samir, (2003) Verilog HD, (2nd Edition.), Pearson Education.

 [2]. Ming-Bo Lin. Digital System Designs and Practices: Using Verilog HDL and FPGAs, Wiley India Pvt Ltd.

[3]. Wayne Wolf. (2004). FPGA Based System Design, Pearson Education India,

Essential Reading / Recommended Reading

[1]. Zainalabedin Navabi. Verilog Digital System Design, TMH; 2nd Edition.

 [2]. D.J. Laja and S. Sapatnekar,(2015). Designing Digital Computer Systems with Verilog, Cambridge University Press.

[3]. EDAPlayground.com.

Evaluation Pattern

 

No.

Components

Marks

CIA 1

Assignment, MCQ Test

10

CIA2

MSE

25

CIA 3

Quiz, MCQ test, presentation, minor project, MOOC.

10

Attendance

 

05

ESE

 

50

Total

100

 

ELE641A - NON-CONVENTIONAL ENERGY SOURCES AND POWER ELECTRONICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This paper is designed as an Elective and offered to understand the fundamentals of Non-conventional energy resources. The various units help the students to understand the importance of renewable energy. The important resources like solar, and wind are discussed. They also learn the construction and working of power devices used in power electronics systems. Units I to III caters to regional, national, and global needs.

Learning Outcome

CO1: Demonstrate the generation of electricity from various Non-Conventional sources of energy and have a working knowledge of types of fuel cells

CO2: Develop the basic knowledge of solar energy, utilization of it, Principles involved in solar energy collection and conversion of it to electricity generation

CO3: Illustrate the concepts involved in wind energy conversion systems by studying their components, types and performance

CO4: Illustrate piezoelectric energy and Geothermal energy and explain the operational methods of energy harvesting

Unit-1
Teaching Hours:15
Energy Resources and Photovoltaic Systems
 

Introduction, an overview of conventional and non-conventional energy resources, Limitations of Fossil fuel, need for renewable energy resources, qualitative description of developments in non-conventional energy sources. Types of non-conventional sources, merits and demerits, energy conservation, Green energy, Fuel cells- principle, construction and applications.

Introduction, Solar energy basics, Radiation spectrum, measurements of solar radiation, Air mass, Solar thermal systems, principle, working, and applications, Solar Photovoltaic Systems, Solar cell fundamentals, construction and working materials, electrical characteristics, equivalent circuit, classification, energy loss and efficiency, the effect of insolation and temperature, module, panel, array, partial and complete shadowing, solar PV systems, problems

Unit-1
Teaching Hours:15
Energy Resources and Photovoltaic Systems
 

Introduction, an overview of conventional and non-conventional energy resources, Limitations of Fossil fuel, need for renewable energy resources, qualitative description of developments in non-conventional energy sources. Types of non-conventional sources, merits and demerits, energy conservation, Green energy, Fuel cells- principle, construction and applications.

Introduction, Solar energy basics, Radiation spectrum, measurements of solar radiation, Air mass, Solar thermal systems, principle, working, and applications, Solar Photovoltaic Systems, Solar cell fundamentals, construction and working materials, electrical characteristics, equivalent circuit, classification, energy loss and efficiency, the effect of insolation and temperature, module, panel, array, partial and complete shadowing, solar PV systems, problems

Unit-2
Teaching Hours:15
Wind, Geothermal and Piezo Electric Energy Harvesting
 

Fundamentals of wind energy, Principle of wind energy conversion, Betz limit, BEMT theory, classification of wind turbines (horizontal axis/vertical axis, lift type/drag type, two/three/multi-bladed wind turbines), Different types of Generators (Synchronous, Asynchronous, Pole Changing), power electronic interface modules, different MPPT algorithms, IoT based health monitoring of wind turbines, grid interconnection topologies, estimation of annual energy yield, wind energy potential and & installed capacity, developments in the wind energy sector globally, India and  Karnataka scenario.

 Geothermal Energy- origin, characteristics and types of a geothermal system, geothermal areas in India, geothermal power plants, electrical and electronic modules

Introduction, piezoelectric effect, hysteresis effects, the effect of temperature and electric field on the polarization, crystal structure, brief theory, materials used, piezoelectric parameters, modelling piezoelectric generators, sensor/actuator and energy harvesting applications, merits and demerits.

Unit-2
Teaching Hours:15
Wind, Geothermal and Piezo Electric Energy Harvesting
 

Fundamentals of wind energy, Principle of wind energy conversion, Betz limit, BEMT theory, classification of wind turbines (horizontal axis/vertical axis, lift type/drag type, two/three/multi-bladed wind turbines), Different types of Generators (Synchronous, Asynchronous, Pole Changing), power electronic interface modules, different MPPT algorithms, IoT based health monitoring of wind turbines, grid interconnection topologies, estimation of annual energy yield, wind energy potential and & installed capacity, developments in the wind energy sector globally, India and  Karnataka scenario.

 Geothermal Energy- origin, characteristics and types of a geothermal system, geothermal areas in India, geothermal power plants, electrical and electronic modules

Introduction, piezoelectric effect, hysteresis effects, the effect of temperature and electric field on the polarization, crystal structure, brief theory, materials used, piezoelectric parameters, modelling piezoelectric generators, sensor/actuator and energy harvesting applications, merits and demerits.

Unit-3
Teaching Hours:15
Power Electronics
 

Introduction, the study of power semiconductor devices, structure of power diode and power transistor, UJT, SCR, SCR as a half-wave and full-wave rectifier, power control using SCR. DIAC, TRIAC, power MOSFET and IGBT, Applications-charge controllers with IGBT/MOSFET, Concept of UPS, types, offline and line-interactive, functional block diagram, dc choppers, Inverters, Switched-mode power supply (SMPS).

Unit-3
Teaching Hours:15
Power Electronics
 

Introduction, the study of power semiconductor devices, structure of power diode and power transistor, UJT, SCR, SCR as a half-wave and full-wave rectifier, power control using SCR. DIAC, TRIAC, power MOSFET and IGBT, Applications-charge controllers with IGBT/MOSFET, Concept of UPS, types, offline and line-interactive, functional block diagram, dc choppers, Inverters, Switched-mode power supply (SMPS).

Text Books And Reference Books:

[1]. Rai.G.D, (2010).Non-Conventional Resources of Energy, (4th Edition), Khanna publishers.

[2]. Khan. B.H, (2014). Non-Conventional Energy Resources, (3rd Edition.), The McGraw Hills.

[3]. Bhimbra .P. S. (2009). Power Electronics, (5th Edition.), Khanna publishers.

Essential Reading / Recommended Reading

[1]. Godfrey Boyle, (2012). Renewable energy, power for a sustainable future, (3rd Edition), Oxford University Press.

[2]. Suhas P Sukhatme,(2017). Solar Energy, (4th Edition). Tata McGraw Hill Publishing Company Ltd.

[3]. Tony Burton, David Sharpe, Nick Jenkins, Ervin Bossanyi, (2011). Wind Energy Handbook, (2nd Edition), John Wiley & Sons.

[4].David A Spera, (2009). Wind Turbine Technology: Fundamental Concepts in Wind Turbine Engineering, (2nd Edition), ASME Press.

[5].Ronald DiPippo, (2007).Geothermal Power Plant, (2nd Edition), Butterworth-Heinemann Publishers.

[6]. Sen .P C, (2011). Power Electronics, (12th  Edition), Tata McGraw Hill Education.

Evaluation Pattern

No.

Components

Marks

CIA 1

Assignment

10

CIA2

MSE

25

CIA 3

Quiz, MCQ test, presentation, minor project, MOOC,

Industry/Educational Visits, Awareness campaign on E-waste and Management, health hazards of mobile telephony etc.

10

Attendance

 

05

ESE

 

50

Total

100

ELE641B - NANOTECHNOLOGY AND NANOELECTRONICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This paper is designed to understand the fundamentals of nanotechnology and nano electronics. Nano technology is basically the control and manipulation of matter at nanoscale. Various fabrication and characterization techniques of nanomaterials are discussed. This paper also introduces the students to the basic concepts in VLSI technology and the upcoming field of Nanoelectronics.

Learning Outcome

CO1: Demonstrate the basic concepts of nanotechnology and Nanoelectronics

CO2: Analyze the advantages, disadvantages and applications of Nanotechnology

CO3: Critically examine the details of nanomaterial and various fabrication and characterization methods

CO4: Demonstrate the basics of VLSI and Nano Electronics

Unit-1
Teaching Hours:15
Nanomaterials and synthesis methods
 

 

Introduction to nanoscience and nanotechnology, the importance of nanoscale, scope and applications of nanotechnology in various fields of science and engineering, nanomaterials, classification of nanomaterials, carbon nanotubes (mention only),  nanowires, quantum dots, properties (chemical, optical, mechanical, thermal, magnetic etc) of nanomaterials, size dependence of properties. synthesis methods and strategies- top-down approach, ball milling, microfabrication, lithography, electron beam lithography, bottom-up approaches: sol-gel technique, co-precipitation, combustion technique, physical vapour deposition, plasma arc technique, laser ablation technique, ion sputtering, molecular beam epitaxy, chemical vapour deposition (CVD), types of CVD

 

Unit-1
Teaching Hours:15
Nanomaterials and synthesis methods
 

 

Introduction to nanoscience and nanotechnology, the importance of nanoscale, scope and applications of nanotechnology in various fields of science and engineering, nanomaterials, classification of nanomaterials, carbon nanotubes (mention only),  nanowires, quantum dots, properties (chemical, optical, mechanical, thermal, magnetic etc) of nanomaterials, size dependence of properties. synthesis methods and strategies- top-down approach, ball milling, microfabrication, lithography, electron beam lithography, bottom-up approaches: sol-gel technique, co-precipitation, combustion technique, physical vapour deposition, plasma arc technique, laser ablation technique, ion sputtering, molecular beam epitaxy, chemical vapour deposition (CVD), types of CVD

 

Unit-2
Teaching Hours:15
Characterization techniques
 

 

X-Ray Diffraction (Bragg’s and Scherrer formula), different microscopy techniques: optical microscope, scanning electron microscope (SEM), scanning probe microscope, atomic force microscope (AFM), transmission electron microscope (TEM), energy-dispersive X-ray spectroscopy, UV-Vis spectroscopy, principle and working of each technique with diagram, Raman spectroscopy, Electrical resistivity measurement using the four-probe method.

 

Unit-2
Teaching Hours:15
Characterization techniques
 

 

X-Ray Diffraction (Bragg’s and Scherrer formula), different microscopy techniques: optical microscope, scanning electron microscope (SEM), scanning probe microscope, atomic force microscope (AFM), transmission electron microscope (TEM), energy-dispersive X-ray spectroscopy, UV-Vis spectroscopy, principle and working of each technique with diagram, Raman spectroscopy, Electrical resistivity measurement using the four-probe method.

 

Unit-3
Teaching Hours:15
Nanoelectronics and applications
 

 

Introduction to Nanoelectronics, limitation to silicon technology, Moore’s law and transistor scaling, classification of IC and technology integration, Design challenges of MOS technology, and Scaling factors for device parameters. Basics of MOS transistor, nMOS, pMOS, modes of operation, CMOS and CMOS inverter, fabrication process, n well process, p well process, SOI applications and advantages. Comparison between CMOS and bipolar technology. MOS layers and stick diagram, VLSI design flow diagram, Single-electron device, Organic LED, Organic FET, Multigate transistor, Flexible and wearable electronic devices and applications. 

 

Unit-3
Teaching Hours:15
Nanoelectronics and applications
 

 

Introduction to Nanoelectronics, limitation to silicon technology, Moore’s law and transistor scaling, classification of IC and technology integration, Design challenges of MOS technology, and Scaling factors for device parameters. Basics of MOS transistor, nMOS, pMOS, modes of operation, CMOS and CMOS inverter, fabrication process, n well process, p well process, SOI applications and advantages. Comparison between CMOS and bipolar technology. MOS layers and stick diagram, VLSI design flow diagram, Single-electron device, Organic LED, Organic FET, Multigate transistor, Flexible and wearable electronic devices and applications. 

 

Text Books And Reference Books:

[1] M. S. Ramachandra Rao and Shubra Singh, (2013). Nanoscience and Nanotechnology: Fundamentals to Frontiers, (1st edn) Wiley India..

 [2]. “R.W. Kelsall, I.W. Hamley and M. Geoghegan (2010).Nanoscale Science and Technology,,  John Wiley and Sons.

 [3]. Charles P. Poole and Frank J. Owens (2010). Introduction to Nanotechnology, John Wiley and Sons, New Delhi

Essential Reading / Recommended Reading

[1]. T Pradeep (2007). ,NANO: the essentials-understanding nanoscience and nanotechnology, TMH.

[2]. J.M. Martinez, R.J. MartinPalma and F. Agnllo-Ruedo,(2006.)Nanotechnology for Microelectronics and optoelectronics, Elsevier,

[3].Cao Guozhong,(2011).Nanostructures and Nanomaterials: synthesis, properties and applications Imperial college press.

[4]. A.M. Ionescu and K. Banerjee (2004). Emerging Nanoelectronics, Life with and after

CMOS, (2nd edition), Kluwer Academic Publishers,.

[5] Thomas Varghese, KM Balakrishna(2016), Nanotechnology-An introduction to synthesis , properties and applications of Nanomaterials, Atlantic Publishers and Distributers.

 

Evaluation Pattern

No.

Components

Marks

CIA 1

Assignment

10

CIA2

MSE

25

CIA 3

Quiz, MCQ test/ presentation by students, minor research project work based on different characterization methods,/MOOC /Industry/Educational Visits, etc

10

Attendance

 

05

ESE

 

50

Total

100

ELE641C - DATA COMMUNICATION AND NETWORKING (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This course is offered as an elective course to incorporate the additional skill set needed in the curriculum to enhance the employability options for electronics UG students. This course mainly deals with data communication with industry standards in implementing electronic communication systems and a complete module on computer networking that deals with the theory and device descriptions. This course also covers the much-needed internet and security concepts.

Learning Outcome

CO1: Discuss the characteristics and types of data communication concepts

CO2: Illustrate baseband signalling with waveforms for various encoding schemes

CO3: Describe various networking devices and their specifications

CO4: Appraise the security issues on the internet and related technologies

Unit-1
Teaching Hours:15
Data communication and Standards
 

Introduction, review of characteristics of digital transmission, noise, bandwidth, speed, bit rate and baud rate illustration, cross talk. Data transmission techniques- serial, parallel, synchronous and asynchronous. Block diagram representations. Description of physical transmission channels – cable and optical links. Merits, demerits. Baseband signalling, unipolar, bipolar, NRZL, NRZI, Manchester and differential Manchester encoding- fundamental concept with waveform representations.Types and sources of data, layered communication model, open system interconnection, Standards, the role of standards, communication sectors covered by standards, standards organizations for data communication - ITU, ISO, IEEE, ISOC, the qualitative description only.

Unit-1
Teaching Hours:15
Data communication and Standards
 

Introduction, review of characteristics of digital transmission, noise, bandwidth, speed, bit rate and baud rate illustration, cross talk. Data transmission techniques- serial, parallel, synchronous and asynchronous. Block diagram representations. Description of physical transmission channels – cable and optical links. Merits, demerits. Baseband signalling, unipolar, bipolar, NRZL, NRZI, Manchester and differential Manchester encoding- fundamental concept with waveform representations.Types and sources of data, layered communication model, open system interconnection, Standards, the role of standards, communication sectors covered by standards, standards organizations for data communication - ITU, ISO, IEEE, ISOC, the qualitative description only.

Unit-2
Teaching Hours:15
Computer networking
 

Introduction to basic networking concept, need for networking, client-server model, Networking models- OSI model – physical layer, data link layer, network layer, transport layer and application layer. TCP/IP model, description of internet layers, transport layer and application layer. Networks types- LAN, WAN, MAN, PAN, CAN, DSRC, wireless networks- WLAN, Bluetooth, description with block representations (qualitative) Introduction to protocols. Fundamentals of Networking hardware – router, switch, modems and hub, block representation, specifications and applications.

Unit-2
Teaching Hours:15
Computer networking
 

Introduction to basic networking concept, need for networking, client-server model, Networking models- OSI model – physical layer, data link layer, network layer, transport layer and application layer. TCP/IP model, description of internet layers, transport layer and application layer. Networks types- LAN, WAN, MAN, PAN, CAN, DSRC, wireless networks- WLAN, Bluetooth, description with block representations (qualitative) Introduction to protocols. Fundamentals of Networking hardware – router, switch, modems and hub, block representation, specifications and applications.

Unit-3
Teaching Hours:15
Internet and security basics
 

Introduction, the architecture of the internet, Internet Model, IEEE standards for communication and Internet - 802.3 Ethernet, 802.11 Wi-Fi and 802.15 Bluetooth/ZigBee, Commonly used data communication standards and applications, Message transmission using layers, the medium access control (MAC), types of internet connections– description of ethernet, WLAN, broadband, VOIP, Bluetooth. The architecture of ethernet, world wide web, domain name system (DNS). Network security concepts, qualitative description of cryptography and other algorithms. Transport layer security (TLS, SSL, HTTPS), Digital signature, IP security, email security, wireless security (802.11i) and social issues. Strengths and weaknesses of firewall, Ethics in using internet services and legal issues (mention only)

Unit-3
Teaching Hours:15
Internet and security basics
 

Introduction, the architecture of the internet, Internet Model, IEEE standards for communication and Internet - 802.3 Ethernet, 802.11 Wi-Fi and 802.15 Bluetooth/ZigBee, Commonly used data communication standards and applications, Message transmission using layers, the medium access control (MAC), types of internet connections– description of ethernet, WLAN, broadband, VOIP, Bluetooth. The architecture of ethernet, world wide web, domain name system (DNS). Network security concepts, qualitative description of cryptography and other algorithms. Transport layer security (TLS, SSL, HTTPS), Digital signature, IP security, email security, wireless security (802.11i) and social issues. Strengths and weaknesses of firewall, Ethics in using internet services and legal issues (mention only)

Text Books And Reference Books:

[1]. Andrew S Tenenbaum, Computer Networks,(4th Edition.), Prentice hall, 2003.

[2]. Michael Duck and Richard Read, Data communications and computer networks – for computer scientists and engineers, (2nd Edition.), Prentice-Hall, 2003.

[3]. Uyless D Black, Data Communication and Distributed Networks, (3rd Edition.), PHI, 2000.

[4]. Wayne Tomasi, Advanced Electronic Communication Systems, (6th Edition.), PHI, 2006.

Essential Reading / Recommended Reading

[1]. Larry L Peterson and Bruce Davie, Computer networks, a system approach, (5th Edition.), Elsevier-MK publications, 2012.

[2]. Irv Englandar, The architecture of computer hardware, systems software and networking, an information technology approach, (5th Edition.), Wiley, 2014.

Evaluation Pattern

No.

Components

Marks

CIA 1

Assignment

10

CIA2

MSE

25

CIA 3

Quiz, Online test, presentation, minor project, Industry/Educational Visits, 

10

Attendance

 

05

ESE

 

50

Total

100

ELE651 - VERILOG AND FPGA BASED DESIGN LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Verilog is a Hardware Description Language (HDL) used to model and synthesize digital systems. Applied to electronic design, Verilog is used for verification via simulation, timing analysis, logic synthesis and test analysis. This course emphasizes a deep understanding of concepts in Verilog through theory as well as practical exercises to reinforce basic concepts.

Learning Outcome

CO1: Write efficient hardware designs in Verilog and perform high-level HDL simulation, synthesis and verify the expected output.

CO2: Illustrate different levels of abstraction with the programming examples.

CO3: Generate and implement the programs on FPGA Kit

CO4: Interface the FPGA with external devices such as motors, relays, DAC, seven-segment and LCDs.

Unit-1
Teaching Hours:30
List of experiments
 

 

1. Write code to realize basic and derived logic gates.

 

2. Half adder, Full Adder using basic and derived gates.

 

3. Half subtractor and Full Subtractor using basic and derived gates.

 

4. Design and simulation of a 4 bit Adder.

 

5. Multiplexer (4x1) and Demultiplexer using logic gates.

 

6. Decoder and Encoder using logic gates.

 

7. Clocked D, JK and T Flip flops (with Reset inputs)

 

8. 3-bit Ripple counter

 

9. Design and study switching circuits (LED blink shift)

 

10. Design a traffic light controller.

 

11. Interface a keyboard

 

12. Interface an LCD using FPGA

 

13. Interface multiplexed seven segment display.

 

Unit-1
Teaching Hours:30
List of experiments
 

 

1. Write code to realize basic and derived logic gates.

 

2. Half adder, Full Adder using basic and derived gates.

 

3. Half subtractor and Full Subtractor using basic and derived gates.

 

4. Design and simulation of a 4 bit Adder.

 

5. Multiplexer (4x1) and Demultiplexer using logic gates.

 

6. Decoder and Encoder using logic gates.

 

7. Clocked D, JK and T Flip flops (with Reset inputs)

 

8. 3-bit Ripple counter

 

9. Design and study switching circuits (LED blink shift)

 

10. Design a traffic light controller.

 

11. Interface a keyboard

 

12. Interface an LCD using FPGA

 

13. Interface multiplexed seven segment display.

 

Text Books And Reference Books:

 [1]. W.Wolf, (2004) FPGA. based System Design, Pearson,

 [2]. U. Meyer Baese, (2004). Digital Signal Processing with FPGAs, Springer.

 [3]. S. Palnitkar, (2003). Verilog HDL– A Guide to Digital Design & Synthesis, Pearson Education.

[4].Bhasker (2003). Verilog HDL primer-. (3rd Edition) BSP.

Essential Reading / Recommended Reading

 [1]. W.Wolf, (2004) FPGA. based System Design, Pearson,

 [2]. U. Meyer Baese, (2004). Digital Signal Processing with FPGAs, Springer.

 [3]. S. Palnitkar, (2003). Verilog HDL– A Guide to Digital Design & Synthesis, Pearson Education.

[4].Bhasker (2003). Verilog HDL primer-. (3rd Edition) BSP.

Evaluation Pattern

 

No.

Components

Marks

CIA

pre-lab work, class work, MSE

25

ESE

(two examiners)

25

Total

50

 

ELE681 - PROJECT LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

This course focusses on skill development for students in understanding, constructing and analysing electronics circuit designs, especially using programmable devices like microcontrollers and development platforms like Arduino, Raspberry pi etc. The students will have to complete a working project under the guidance of faculty members of the department utilising the lab sessions allotted for the project lab in this semester.

The prime objective of this main project is to acquire hands-on learning experience and prepare the students for better job placements.

Learning Outcome

CO1: To develop the ability to apply the electronics/technology concepts

CO2: To apply tools /techniques to study and attempt to implement the ideas relevant to the problems and construct working prototype/model

CO3: To articulate effectively a detailed report on the project

CO4: To develop team spirit and mentoring/leadership abilities

Unit-1
Teaching Hours:30
Guidelines
 

Students in a group of TWO/THREE are expected to take up an in-house Electronic Project. The faculty members will guide the students. Throughout the semester they would be assessed for the literature survey, seminar and project report. Each student should write a report about the project work including the components used and their specification, working of the circuit, and applications and submit the same for evaluation at the time of End semester practical examination duly certified by the concerned faculty and HOD. This paper caters to the cross-cutting issues such as research ethics and social responsibility.

Unit-1
Teaching Hours:30
Guidelines
 

Students in a group of TWO/THREE are expected to take up an in-house Electronic Project. The faculty members will guide the students. Throughout the semester they would be assessed for the literature survey, seminar and project report. Each student should write a report about the project work including the components used and their specification, working of the circuit, and applications and submit the same for evaluation at the time of End semester practical examination duly certified by the concerned faculty and HOD. This paper caters to the cross-cutting issues such as research ethics and social responsibility.

Text Books And Reference Books:

Electronics Projects Vol. 1 - 25 by EFY Enterprises Pvt. Ltd.

Essential Reading / Recommended Reading

Web reference for projects :

[1] https://projecthub.arduino.cc/

[2] https://projects.raspberrypi.org/en/projects

Evaluation Pattern

Lab CIA : 30 marks

Mid semester assessment: 20 marks

 

End Semester Lab exam: 50 marks

Lab CIA

Pre Lab preparation: 15 marks, Post Lab work: 15 marks

Mid Semester Exam: Exhibition of project work

Working project: 10 marks, Demo: 5 marks, Viva: 5 marks

End semester Lab exam

Project demonstration(individual)…20 marks

Explanation of working…..5 marks

Submission of Report….20 marks, Viva….5 marks

The total weightage is converted to 50 marks

MAT631 - COMPLEX ANALYSIS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course description: This course enables the students to understand the basic theory and principles of complex analysis.

COBJ1.     understand the theory and geometry of complex numbers.

COBJ2.     evaluate derivatives and integrals of functions of complex variables.

COBJ3.     examine the transformation of functions of complex variables.

COBJ4.   obtain the power series expansion of a complex valued function.

Learning Outcome

CO1: On successful completion of the course, the students should be able to understand the concepts of limit, continuity, differentiability of complex functions.

CO2: On successful completion of the course, the students should be able to evaluate the integrals of complex functions using Cauchy's Integral Theorem/Formula and related results.

CO3: On successful completion of the course, the students should be able to examine various types of transformation of functions of complex variables.

CO4: On successful completion of the course, the students should be able to demonstrate the expansions of complex functions as Taylor, Power and Laurent Series, Classify singularities and poles.

CO5: On successful completion of the course, the students should be able to apply the concepts of complex analysis to analyze and address real world problems.

Unit-1
Teaching Hours:15
Analytic Functions
 

Properties of complex numbers, regions in the complex plane, functions of complex variable, limits, limits involving the point at infinity, continuity and differentiability of functions of complex variable. Analytic functions, necessary and sufficient conditions for a function to be analytic.

Unit-1
Teaching Hours:15
Analytic Functions
 

Properties of complex numbers, regions in the complex plane, functions of complex variable, limits, limits involving the point at infinity, continuity and differentiability of functions of complex variable. Analytic functions, necessary and sufficient conditions for a function to be analytic.

Unit-1
Teaching Hours:15
Analytic Functions
 

Properties of complex numbers, regions in the complex plane, functions of complex variable, limits, limits involving the point at infinity, continuity and differentiability of functions of complex variable. Analytic functions, necessary and sufficient conditions for a function to be analytic.

Unit-1
Teaching Hours:15
Analytic Functions
 

Properties of complex numbers, regions in the complex plane, functions of complex variable, limits, limits involving the point at infinity, continuity and differentiability of functions of complex variable. Analytic functions, necessary and sufficient conditions for a function to be analytic.

Unit-1
Teaching Hours:15
Analytic Functions
 

Properties of complex numbers, regions in the complex plane, functions of complex variable, limits, limits involving the point at infinity, continuity and differentiability of functions of complex variable. Analytic functions, necessary and sufficient conditions for a function to be analytic.

Unit-1
Teaching Hours:15
Analytic Functions
 

Properties of complex numbers, regions in the complex plane, functions of complex variable, limits, limits involving the point at infinity, continuity and differentiability of functions of complex variable. Analytic functions, necessary and sufficient conditions for a function to be analytic.

Unit-1
Teaching Hours:15
Analytic Functions
 

Properties of complex numbers, regions in the complex plane, functions of complex variable, limits, limits involving the point at infinity, continuity and differentiability of functions of complex variable. Analytic functions, necessary and sufficient conditions for a function to be analytic.

Unit-2
Teaching Hours:15
Complex Integration and Conformal Mapping
 

Definite integrals of functions, contour integrals and its examples, Cauchy’s integral theorem, Cauchy integral formula, Liouville’s theorem and the fundamental theorem of algebra, elementary transformations, conformal mappings, bilinear transformations.

Unit-2
Teaching Hours:15
Complex Integration and Conformal Mapping
 

Definite integrals of functions, contour integrals and its examples, Cauchy’s integral theorem, Cauchy integral formula, Liouville’s theorem and the fundamental theorem of algebra, elementary transformations, conformal mappings, bilinear transformations.

Unit-2
Teaching Hours:15
Complex Integration and Conformal Mapping
 

Definite integrals of functions, contour integrals and its examples, Cauchy’s integral theorem, Cauchy integral formula, Liouville’s theorem and the fundamental theorem of algebra, elementary transformations, conformal mappings, bilinear transformations.

Unit-2
Teaching Hours:15
Complex Integration and Conformal Mapping
 

Definite integrals of functions, contour integrals and its examples, Cauchy’s integral theorem, Cauchy integral formula, Liouville’s theorem and the fundamental theorem of algebra, elementary transformations, conformal mappings, bilinear transformations.

Unit-2
Teaching Hours:15
Complex Integration and Conformal Mapping
 

Definite integrals of functions, contour integrals and its examples, Cauchy’s integral theorem, Cauchy integral formula, Liouville’s theorem and the fundamental theorem of algebra, elementary transformations, conformal mappings, bilinear transformations.

Unit-2
Teaching Hours:15
Complex Integration and Conformal Mapping
 

Definite integrals of functions, contour integrals and its examples, Cauchy’s integral theorem, Cauchy integral formula, Liouville’s theorem and the fundamental theorem of algebra, elementary transformations, conformal mappings, bilinear transformations.

Unit-2
Teaching Hours:15
Complex Integration and Conformal Mapping
 

Definite integrals of functions, contour integrals and its examples, Cauchy’s integral theorem, Cauchy integral formula, Liouville’s theorem and the fundamental theorem of algebra, elementary transformations, conformal mappings, bilinear transformations.

Unit-3
Teaching Hours:15
Power Series and Singularities
 

Convergence of sequences and series, Taylor series and its examples, Laurent series and its examples, absolute and uniform convergence of power series, zeros and poles.

Unit-3
Teaching Hours:15
Power Series and Singularities
 

Convergence of sequences and series, Taylor series and its examples, Laurent series and its examples, absolute and uniform convergence of power series, zeros and poles.

Unit-3
Teaching Hours:15
Power Series and Singularities
 

Convergence of sequences and series, Taylor series and its examples, Laurent series and its examples, absolute and uniform convergence of power series, zeros and poles.

Unit-3
Teaching Hours:15
Power Series and Singularities
 

Convergence of sequences and series, Taylor series and its examples, Laurent series and its examples, absolute and uniform convergence of power series, zeros and poles.

Unit-3
Teaching Hours:15
Power Series and Singularities
 

Convergence of sequences and series, Taylor series and its examples, Laurent series and its examples, absolute and uniform convergence of power series, zeros and poles.

Unit-3
Teaching Hours:15
Power Series and Singularities
 

Convergence of sequences and series, Taylor series and its examples, Laurent series and its examples, absolute and uniform convergence of power series, zeros and poles.

Unit-3
Teaching Hours:15
Power Series and Singularities
 

Convergence of sequences and series, Taylor series and its examples, Laurent series and its examples, absolute and uniform convergence of power series, zeros and poles.

Text Books And Reference Books:

Dennis G. Zill and Patrick D. Shanahan, A first course in Complex Analysis with Applications, 2nd Ed, Jones & Barlett Publishers, 2011.

Essential Reading / Recommended Reading
  1. J. W. Brown and R. V. Churchill, Complex Variables and Applications, 8th ed., McGraw - Hill International Edition, 2009.
  2. J. Bak and D. J. Newman, Complex analysis, 2nd ed., Undergraduate Texts in Mathematics, Springer-Verlag New York, Inc., New York, 2000.
  3. A. Jeffrey, Complex Analysis and Applications, 2nd ed., CRC Press, Boca Raton 2013.
  4. L. V. Ahlfors, Complex Analysis, 3rd ed., McGraw-Hill Education, 2017.
  5. S. Ponnusamy, Foundations of Complex Analysis, 2nd ed., Narosa Publishing House, Reprint 2021.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ

Written Assignment

Reference work

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment

Project

Problem solving skills

 

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT641A - MECHANICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course description: This course aims at introducing the basic concepts in statistics as well as dynamics of particles and rigid bodies; develop problem solving skills in mechanics through various applications.

Course objectives: This course will help the learner to

COBJ1. Gain familiarity with the concepts of force, triangular and parallelogram laws and conditions of equilibrium of forces.

COBJ2. Analyse and interpret the Lamis Lemma and the resultant of more than one force.

COBJ3. examine dynamical aspect of particles and rigid bodies.

COBJ4. illustrate the concepts of simple harmonic motion and projectiles

 

Learning Outcome

CO1: On successful completion of the course, the students should be able to compute resultant and direction of forces and examine the equilibrium of a force.

CO2: On successful completion of the course, the students should be able to apply Lamis's Theorem and Varignon's Theorem in solving problems.

CO3: On successful completion of the course, the students should be able to analyse the motion of a particle on a smooth surface.

CO4: On successful completion of the course, the students should be able to discuss the motion of a particles subjected to Simple Harmonic Motion and fundamental concepts Projectiles.

Unit-1
Teaching Hours:15
Forces acting on particle / rigid body
 

Introduction and general principles, force vectors, moments, couple-equilibrium of a particle - coplanar forces acting on a rigid body, problems of equilibrium under forces

Unit-1
Teaching Hours:15
Forces acting on particle / rigid body
 

Introduction and general principles, force vectors, moments, couple-equilibrium of a particle - coplanar forces acting on a rigid body, problems of equilibrium under forces

Unit-1
Teaching Hours:15
Forces acting on particle / rigid body
 

Introduction and general principles, force vectors, moments, couple-equilibrium of a particle - coplanar forces acting on a rigid body, problems of equilibrium under forces

Unit-1
Teaching Hours:15
Forces acting on particle / rigid body
 

Introduction and general principles, force vectors, moments, couple-equilibrium of a particle - coplanar forces acting on a rigid body, problems of equilibrium under forces

Unit-1
Teaching Hours:15
Forces acting on particle / rigid body
 

Introduction and general principles, force vectors, moments, couple-equilibrium of a particle - coplanar forces acting on a rigid body, problems of equilibrium under forces

Unit-2
Teaching Hours:20
Dynamics of a particle in 2D
 

Velocities and accelerations along radial and transverse directions and along tangential and normal directions; relation between angular and linear vectors, dynamics on smooth and rough plane curves.

Unit-2
Teaching Hours:20
Dynamics of a particle in 2D
 

Velocities and accelerations along radial and transverse directions and along tangential and normal directions; relation between angular and linear vectors, dynamics on smooth and rough plane curves.

Unit-2
Teaching Hours:20
Dynamics of a particle in 2D
 

Velocities and accelerations along radial and transverse directions and along tangential and normal directions; relation between angular and linear vectors, dynamics on smooth and rough plane curves.

Unit-2
Teaching Hours:20
Dynamics of a particle in 2D
 

Velocities and accelerations along radial and transverse directions and along tangential and normal directions; relation between angular and linear vectors, dynamics on smooth and rough plane curves.

Unit-2
Teaching Hours:20
Dynamics of a particle in 2D
 

Velocities and accelerations along radial and transverse directions and along tangential and normal directions; relation between angular and linear vectors, dynamics on smooth and rough plane curves.

Unit-3
Teaching Hours:10
Kinetics of particle and Projectile Motion
 

Simple harmonic motion, Newton’s laws of motion, projectiles. 

Unit-3
Teaching Hours:10
Kinetics of particle and Projectile Motion
 

Simple harmonic motion, Newton’s laws of motion, projectiles. 

Unit-3
Teaching Hours:10
Kinetics of particle and Projectile Motion
 

Simple harmonic motion, Newton’s laws of motion, projectiles. 

Unit-3
Teaching Hours:10
Kinetics of particle and Projectile Motion
 

Simple harmonic motion, Newton’s laws of motion, projectiles. 

Unit-3
Teaching Hours:10
Kinetics of particle and Projectile Motion
 

Simple harmonic motion, Newton’s laws of motion, projectiles. 

Text Books And Reference Books:
  1. A S Ramsey, Statics, CBS Publishers & Distributors, 2004.
  2. A.P. Roberts, Statics and Dynamics with Background in Mathematics, Cambridge University Press, 2003.
Essential Reading / Recommended Reading
  1. S. L. Loney, The elements of statics and dynamics-Part I Statics. 6th ed., Arihant Publications, 2004.
  2. S. L. Loney, The elements of statics and dynamics-Part II Dynamics.6th ed., Arihant Publications, 2004.
  3. P.K.Mittal, Mathematics for degree students, S Chand publications, 2016.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ

Written Assignment, Reference work

Mastery of the core concepts

Problem solving skills

10

CIA II

Mid-semester  Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Assignment

Project

Mastery of the core concepts

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT641B - NUMERICAL METHODS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course description: To explore the complex world problems physicists, engineers, financiers and mathematicians require certain methods. These practical problems can rarely be solved analytically. Their solutions can only be approximated through numerical methods. This course deals with the theory and application of numerical approximation techniques.

 

Course objectives: This course will help the learner

COBJ1. To learn about error analysis, solution of nonlinear equations, finite differences, interpolation, numerical integration and differentiation, numerical solution of differential equations, and matrix computation.

COBJ2. It also emphasis the development of numerical algorithms to provide solutions to common problems formulated in science and engineering.

Learning Outcome

CO1.: On successful completion of the course, the students should be able to understand floating point numbers and the role of errors and its analysis in numerical methods.

CO2.: On successful completion of the course, the students should be able to derive numerical methods for various mathematical operations and tasks, such as interpolation, differentiation, integration, the solution of linear and nonlinear equations, and the solution of differential equations.

CO3.: On successful completion of the course, the students should be able to apply numerical methods to obtain approximate solutions to mathematical problems.

CO4.: On successful completion of the course, the students should be able to understand the accuracy, consistency, stability and convergence of numerical methods

Unit-1
Teaching Hours:15
Error analysis, Nonlinear equations, and Solution of a system of linear Equations
 

Errors and their analysis, Floating point representation of numbers, solution of algebraic and Transcendental Equations: Bisection method, fixed point Iteration method, the method of False Position, Newton Raphson method and Mullers method. Solution of linear systems, matrix inversion method, Gauss elimination method, Gauss-Seidel and Gauss-Jacobi iterative methods, modification of the Gauss method to compute the inverse, LU decomposition method.

Unit-1
Teaching Hours:15
Error analysis, Nonlinear equations, and Solution of a system of linear Equations
 

Errors and their analysis, Floating point representation of numbers, solution of algebraic and Transcendental Equations: Bisection method, fixed point Iteration method, the method of False Position, Newton Raphson method and Mullers method. Solution of linear systems, matrix inversion method, Gauss elimination method, Gauss-Seidel and Gauss-Jacobi iterative methods, modification of the Gauss method to compute the inverse, LU decomposition method.

Unit-1
Teaching Hours:15
Error analysis, Nonlinear equations, and Solution of a system of linear Equations
 

Errors and their analysis, Floating point representation of numbers, solution of algebraic and Transcendental Equations: Bisection method, fixed point Iteration method, the method of False Position, Newton Raphson method and Mullers method. Solution of linear systems, matrix inversion method, Gauss elimination method, Gauss-Seidel and Gauss-Jacobi iterative methods, modification of the Gauss method to compute the inverse, LU decomposition method.

Unit-1
Teaching Hours:15
Error analysis, Nonlinear equations, and Solution of a system of linear Equations
 

Errors and their analysis, Floating point representation of numbers, solution of algebraic and Transcendental Equations: Bisection method, fixed point Iteration method, the method of False Position, Newton Raphson method and Mullers method. Solution of linear systems, matrix inversion method, Gauss elimination method, Gauss-Seidel and Gauss-Jacobi iterative methods, modification of the Gauss method to compute the inverse, LU decomposition method.

Unit-1
Teaching Hours:15
Error analysis, Nonlinear equations, and Solution of a system of linear Equations
 

Errors and their analysis, Floating point representation of numbers, solution of algebraic and Transcendental Equations: Bisection method, fixed point Iteration method, the method of False Position, Newton Raphson method and Mullers method. Solution of linear systems, matrix inversion method, Gauss elimination method, Gauss-Seidel and Gauss-Jacobi iterative methods, modification of the Gauss method to compute the inverse, LU decomposition method.

Unit-2
Teaching Hours:15
Finite Differences, Interpolation, and Numerical differentiation and Integration
 

Finite differences: Forward difference, backward difference and shift operators, separation of symbols, Newton’s formulae for interpolation, Lagrange’s interpolation formulae, numerical differentiation. Numerical integration: Trapezoidal rule, Simpson’s one-third rule and Simpson’s three-eighth rule.

Unit-2
Teaching Hours:15
Finite Differences, Interpolation, and Numerical differentiation and Integration
 

Finite differences: Forward difference, backward difference and shift operators, separation of symbols, Newton’s formulae for interpolation, Lagrange’s interpolation formulae, numerical differentiation. Numerical integration: Trapezoidal rule, Simpson’s one-third rule and Simpson’s three-eighth rule.

Unit-2
Teaching Hours:15
Finite Differences, Interpolation, and Numerical differentiation and Integration
 

Finite differences: Forward difference, backward difference and shift operators, separation of symbols, Newton’s formulae for interpolation, Lagrange’s interpolation formulae, numerical differentiation. Numerical integration: Trapezoidal rule, Simpson’s one-third rule and Simpson’s three-eighth rule.

Unit-2
Teaching Hours:15
Finite Differences, Interpolation, and Numerical differentiation and Integration
 

Finite differences: Forward difference, backward difference and shift operators, separation of symbols, Newton’s formulae for interpolation, Lagrange’s interpolation formulae, numerical differentiation. Numerical integration: Trapezoidal rule, Simpson’s one-third rule and Simpson’s three-eighth rule.

Unit-2
Teaching Hours:15
Finite Differences, Interpolation, and Numerical differentiation and Integration
 

Finite differences: Forward difference, backward difference and shift operators, separation of symbols, Newton’s formulae for interpolation, Lagrange’s interpolation formulae, numerical differentiation. Numerical integration: Trapezoidal rule, Simpson’s one-third rule and Simpson’s three-eighth rule.

Unit-3
Teaching Hours:15
Numerical Solution of Ordinary Differential Equations
 

Numerical solution of ordinary differential equations, Taylor’s series, Picard’s method, Euler’s method, modified Euler’s method, Runge Kutta methods, second order (with proof) and fourth order (without proof).

Unit-3
Teaching Hours:15
Numerical Solution of Ordinary Differential Equations
 

Numerical solution of ordinary differential equations, Taylor’s series, Picard’s method, Euler’s method, modified Euler’s method, Runge Kutta methods, second order (with proof) and fourth order (without proof).

Unit-3
Teaching Hours:15
Numerical Solution of Ordinary Differential Equations
 

Numerical solution of ordinary differential equations, Taylor’s series, Picard’s method, Euler’s method, modified Euler’s method, Runge Kutta methods, second order (with proof) and fourth order (without proof).

Unit-3
Teaching Hours:15
Numerical Solution of Ordinary Differential Equations
 

Numerical solution of ordinary differential equations, Taylor’s series, Picard’s method, Euler’s method, modified Euler’s method, Runge Kutta methods, second order (with proof) and fourth order (without proof).

Unit-3
Teaching Hours:15
Numerical Solution of Ordinary Differential Equations
 

Numerical solution of ordinary differential equations, Taylor’s series, Picard’s method, Euler’s method, modified Euler’s method, Runge Kutta methods, second order (with proof) and fourth order (without proof).

Text Books And Reference Books:
  1. C. F. Gerald and P. O. Wheatly, Applied Numerical Analysis, 7th ed., Wesley. 2007.
  2. M. K. Jain, Iyengar, S. R. K. and R. K. Jain, Numerical Methods for Scientific and Engineering Computation, New Age Pvt. Pub, New Delhi, 2012.
  3. R. L. Burden and J. D. Faires, Numerical analysis, Belmont, CA: Thomson Brooks/Cole, 2005.
Essential Reading / Recommended Reading
  1. E. V. Krishnamurthy and S. K. Sen, Applied Numerical Analysis, East West Publication, 1986.
  2. F. Scheid, Schaum's Outline of Numerical Analysis, 2nd ed., Mc.Graw Hill, 2006.
  3. A. Grégoire, Numerical analysis and optimization: an introduction to mathematical modelling and numerical simulation, Oxford: Oxford University Press, 2007.
  4. K. E. Atkinson and W. Han, Elementary numerical analysis. Hoboken, NJ: Wiley, 2004.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ

Written Assignment

Reference work

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Assignment/problem solving

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT641C - DISCRETE MATHEMATICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course description: It is a fundamental course in combinatorics involving set theory, permutations and combinations, generating functions, recurrence relations and lattices.

Course objectives: This course will help the learner to 

COBJ1. gain a familiarity with fundamental concepts of combinatorial mathematics.

COBJ2. understand the methods and problem solving techniques of discrete mathematics

COBJ3. apply knowledge to analyze and solve problems using models of discrete mathematics

Learning Outcome

CO 1: On successful completion of the course, the students should be able to enhance research, inquiry, and analytical thinking abilities.

CO 2: On successful completion of the course, the students should be able to apply the basics of combinatorics in analyzing problems.

CO 3: On successful completion of the course, the students should be able to enhance problem-solving skills.

Unit-1
Teaching Hours:15
Combinatorics
 

Permutations and combinations, laws of set theory, Venn diagrams, relations and functions, Stirling numbers of the second kind, Pigeon hole principle.

Unit-1
Teaching Hours:15
Combinatorics
 

Permutations and combinations, laws of set theory, Venn diagrams, relations and functions, Stirling numbers of the second kind, Pigeon hole principle.

Unit-1
Teaching Hours:15
Combinatorics
 

Permutations and combinations, laws of set theory, Venn diagrams, relations and functions, Stirling numbers of the second kind, Pigeon hole principle.

Unit-1
Teaching Hours:15
Combinatorics
 

Permutations and combinations, laws of set theory, Venn diagrams, relations and functions, Stirling numbers of the second kind, Pigeon hole principle.

Unit-1
Teaching Hours:15
Combinatorics
 

Permutations and combinations, laws of set theory, Venn diagrams, relations and functions, Stirling numbers of the second kind, Pigeon hole principle.

Unit-1
Teaching Hours:15
Combinatorics
 

Permutations and combinations, laws of set theory, Venn diagrams, relations and functions, Stirling numbers of the second kind, Pigeon hole principle.

Unit-1
Teaching Hours:15
Combinatorics
 

Permutations and combinations, laws of set theory, Venn diagrams, relations and functions, Stirling numbers of the second kind, Pigeon hole principle.

Unit-2
Teaching Hours:15
Enumeration
 

Principle of inclusion and exclusion, generating functions, partitions of integers and recurrence relations.

Unit-2
Teaching Hours:15
Enumeration
 

Principle of inclusion and exclusion, generating functions, partitions of integers and recurrence relations.

Unit-2
Teaching Hours:15
Enumeration
 

Principle of inclusion and exclusion, generating functions, partitions of integers and recurrence relations.

Unit-2
Teaching Hours:15
Enumeration
 

Principle of inclusion and exclusion, generating functions, partitions of integers and recurrence relations.

Unit-2
Teaching Hours:15
Enumeration
 

Principle of inclusion and exclusion, generating functions, partitions of integers and recurrence relations.

Unit-2
Teaching Hours:15
Enumeration
 

Principle of inclusion and exclusion, generating functions, partitions of integers and recurrence relations.

Unit-2
Teaching Hours:15
Enumeration
 

Principle of inclusion and exclusion, generating functions, partitions of integers and recurrence relations.

Unit-3
Teaching Hours:15
Lattice Theory
 

Partially ordered set, lattices and their properties, duality principle, lattice homomorphisms, product lattices, modular and distributive lattices, Boolean lattices.

Unit-3
Teaching Hours:15
Lattice Theory
 

Partially ordered set, lattices and their properties, duality principle, lattice homomorphisms, product lattices, modular and distributive lattices, Boolean lattices.

Unit-3
Teaching Hours:15
Lattice Theory
 

Partially ordered set, lattices and their properties, duality principle, lattice homomorphisms, product lattices, modular and distributive lattices, Boolean lattices.

Unit-3
Teaching Hours:15
Lattice Theory
 

Partially ordered set, lattices and their properties, duality principle, lattice homomorphisms, product lattices, modular and distributive lattices, Boolean lattices.

Unit-3
Teaching Hours:15
Lattice Theory
 

Partially ordered set, lattices and their properties, duality principle, lattice homomorphisms, product lattices, modular and distributive lattices, Boolean lattices.

Unit-3
Teaching Hours:15
Lattice Theory
 

Partially ordered set, lattices and their properties, duality principle, lattice homomorphisms, product lattices, modular and distributive lattices, Boolean lattices.

Unit-3
Teaching Hours:15
Lattice Theory
 

Partially ordered set, lattices and their properties, duality principle, lattice homomorphisms, product lattices, modular and distributive lattices, Boolean lattices.

Text Books And Reference Books:
  1. Ralph P. Grimaldi, Discrete and Combinatorial Mathematics – An applied introduction, Pearson Addison Wesley, 5th Edition, 2004.
  2. Rosen, Kenneth. Discrete Mathematics and Its Applications. United Kingdom, McGraw-Hill Education, 2006.
  3. Jongsma Calvin, Discrete Mathematics: Chapter 0, Table of Contents and Preface, Faculty Work: Comprehensive List. Paper 426, 2016.
Essential Reading / Recommended Reading
  1. R. A. Brualdi, Introductory Combinatorics, 5th ed., China Machine Press, 2009.
  2. E. A. Bender and S. G. Williamson, Foundations of combinatorics with applications, Dover Publ., 2007.
  3. J. P. Tremblay and R. Manohar, Discrete Mathematical Structures with Applications to Computer Science, 1st ed., McGraw Hill Education, 2017.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

Test

Written Assignment

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Test

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT641D - NUMBER THEORY (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description: This course is an introduction to elementary topics of analytical number theory. Topics such as divisibility, congruences and number-theoretic functions are discussed in this course. Some of the applications of these concepts are also included.

Course Objectives: This course will help the learner to

COBJ1. engage in sound mathematical thinking and reasoning.

COBJ2. analyze, evaluate, or solve problems for given data or information.

COBJ3. understand and utilize mathematical functions and empirical principles and processes.

COBJ4. develop critical thinking skills, communication skills, and empirical and quantitative skills.

Learning Outcome

CO1: After the completion of this course, learners are expected to effectively express the concepts and results of number theory.

CO2: After the completion of this course, learners are expected to understand the logic and methods behind the proofs in number theory.

CO3: After the completion of this course, learners are expected to solve challenging problems in number theory.

CO4: After the completion of this course, learners are expected to present specific topics and prove various ideas with mathematical rigour.

Unit-1
Teaching Hours:15
Divisibility
 

The division algorithm, the greatest common divisor, the Euclidean algorithm, the linear Diophantine equation, the fundamental theorem of arithmetic, distribution of primes.

Unit-1
Teaching Hours:15
Divisibility
 

The division algorithm, the greatest common divisor, the Euclidean algorithm, the linear Diophantine equation, the fundamental theorem of arithmetic, distribution of primes.

Unit-1
Teaching Hours:15
Divisibility
 

The division algorithm, the greatest common divisor, the Euclidean algorithm, the linear Diophantine equation, the fundamental theorem of arithmetic, distribution of primes.

Unit-1
Teaching Hours:15
Divisibility
 

The division algorithm, the greatest common divisor, the Euclidean algorithm, the linear Diophantine equation, the fundamental theorem of arithmetic, distribution of primes.

Unit-1
Teaching Hours:15
Divisibility
 

The division algorithm, the greatest common divisor, the Euclidean algorithm, the linear Diophantine equation, the fundamental theorem of arithmetic, distribution of primes.

Unit-1
Teaching Hours:15
Divisibility
 

The division algorithm, the greatest common divisor, the Euclidean algorithm, the linear Diophantine equation, the fundamental theorem of arithmetic, distribution of primes.

Unit-1
Teaching Hours:15
Divisibility
 

The division algorithm, the greatest common divisor, the Euclidean algorithm, the linear Diophantine equation, the fundamental theorem of arithmetic, distribution of primes.

Unit-2
Teaching Hours:15
Linear Congruence
 

Basic properties of congruences, systems of residues, number conversions, linear congruences and Chinese remainder theorem, a system of linear congruences in two variables, Fermat’s Little Theorem and pseudoprimes, Wilson’s Theorem.

Unit-2
Teaching Hours:15
Linear Congruence
 

Basic properties of congruences, systems of residues, number conversions, linear congruences and Chinese remainder theorem, a system of linear congruences in two variables, Fermat’s Little Theorem and pseudoprimes, Wilson’s Theorem.

Unit-2
Teaching Hours:15
Linear Congruence
 

Basic properties of congruences, systems of residues, number conversions, linear congruences and Chinese remainder theorem, a system of linear congruences in two variables, Fermat’s Little Theorem and pseudoprimes, Wilson’s Theorem.

Unit-2
Teaching Hours:15
Linear Congruence
 

Basic properties of congruences, systems of residues, number conversions, linear congruences and Chinese remainder theorem, a system of linear congruences in two variables, Fermat’s Little Theorem and pseudoprimes, Wilson’s Theorem.

Unit-2
Teaching Hours:15
Linear Congruence
 

Basic properties of congruences, systems of residues, number conversions, linear congruences and Chinese remainder theorem, a system of linear congruences in two variables, Fermat’s Little Theorem and pseudoprimes, Wilson’s Theorem.

Unit-2
Teaching Hours:15
Linear Congruence
 

Basic properties of congruences, systems of residues, number conversions, linear congruences and Chinese remainder theorem, a system of linear congruences in two variables, Fermat’s Little Theorem and pseudoprimes, Wilson’s Theorem.

Unit-2
Teaching Hours:15
Linear Congruence
 

Basic properties of congruences, systems of residues, number conversions, linear congruences and Chinese remainder theorem, a system of linear congruences in two variables, Fermat’s Little Theorem and pseudoprimes, Wilson’s Theorem.

Unit-3
Teaching Hours:15
Number Theoretic Functions
 

The Greatest Integer Function, Euler’s Phi-Function, Euler’s theorem, Some Properties of Phi-function. Applications of Number Theory: Hashing functions, pseudorandom Numbers, check bits, cryptography.

 

Unit-3
Teaching Hours:15
Number Theoretic Functions
 

The Greatest Integer Function, Euler’s Phi-Function, Euler’s theorem, Some Properties of Phi-function. Applications of Number Theory: Hashing functions, pseudorandom Numbers, check bits, cryptography.

 

Unit-3
Teaching Hours:15
Number Theoretic Functions
 

The Greatest Integer Function, Euler’s Phi-Function, Euler’s theorem, Some Properties of Phi-function. Applications of Number Theory: Hashing functions, pseudorandom Numbers, check bits, cryptography.

 

Unit-3
Teaching Hours:15
Number Theoretic Functions
 

The Greatest Integer Function, Euler’s Phi-Function, Euler’s theorem, Some Properties of Phi-function. Applications of Number Theory: Hashing functions, pseudorandom Numbers, check bits, cryptography.

 

Unit-3
Teaching Hours:15
Number Theoretic Functions
 

The Greatest Integer Function, Euler’s Phi-Function, Euler’s theorem, Some Properties of Phi-function. Applications of Number Theory: Hashing functions, pseudorandom Numbers, check bits, cryptography.

 

Unit-3
Teaching Hours:15
Number Theoretic Functions
 

The Greatest Integer Function, Euler’s Phi-Function, Euler’s theorem, Some Properties of Phi-function. Applications of Number Theory: Hashing functions, pseudorandom Numbers, check bits, cryptography.

 

Unit-3
Teaching Hours:15
Number Theoretic Functions
 

The Greatest Integer Function, Euler’s Phi-Function, Euler’s theorem, Some Properties of Phi-function. Applications of Number Theory: Hashing functions, pseudorandom Numbers, check bits, cryptography.

 

Text Books And Reference Books:
  1. D. M. Burton, Elementary Number Theory, 7th ed., New Delhi: Tata McGraw-Hill, 2012.
  2. S. Kundu and S. Mazumder, Number Theory and Its Applications, Bocca Raton: CRC Press, 2022.
Essential Reading / Recommended Reading
  1. K. H. Rosen, Elementary Number Theory, 6th ed., New Delhi: Pearson Education India, 2015.
  2. G. Effinger and G. L. Mullen, Elementary Number Theory, Bocca Raton: CRC Press, 2021.
  3. J. Pommersheim, T. K. Marks and E. L. Flapan, Number Theory, New Jersey: John Wiley & Sons, 2009.
  4. J. H. Silverman, A friendly introduction to number theory, London: Pearson Prentice Hall, 2006.
  5. Niven, H.S. Zuckerman and H.L. Montgomery, An introduction to the theory of numbers, 5th ed., New Jersey: John Wiley & Sons, Inc., 2012.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ

Written Assignment

Reference work  

Mastery of the core concepts  

Problem solving skills

13

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

05

CIA III

Written Assignment / Project

Written assignment based on Binary and Decimal representation of integers.

05

Attendance

Attendance

Regularity and Punctuality

   02

ESE

 

Basic, conceptual and analytical knowledge of the subject

25

Total

50

MAT641E - FINANCIAL MATHEMATICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Description:Financial Mathematics deals with the solving of financial problems by using Mathematical methods. This course aims at introducing the basic ideas of deterministic mathematics of finance. The course focuses on imparting sound knowledge on elementary notions like simple interest, complex interest (annual and non-annual), annuities (varying and non-varying), loans and bonds.

Course objectives: This course will help the learner to

COBJ 1: gain familiarity in solving problems on Interest rates and Level Annuitiesd

COBJ 2: derive formulae for different types of varying annuities and solve its associated problems

COBJ 3: gain in depth knowledge on Loans and Bonds and hence create schedules for Loan Repayment and Bond Amortization Schedules.

Learning Outcome

CO1: On successful completion of the course, the students should be able to deal with the elementary notions like simple interest, compound interest and Annuities.

CO2: On successful completion of the course, the students should be able to solve simple problems on interest rates, annuities, varying annuities, non-annual interest rates, loans and bonds.

CO3: On successful completion of the course, the students should be able to apply the formulae appropriately in solving problems that mimics real life scenario.

Unit-1
Teaching Hours:15
Interest Rates, Factors and Level Annuities
 

Interest Rates, Rate of discount, Nominal rates of interest and discount, Constant force of interest, Force of interest, Inflation, Equations of Value and Yield Rates, Annuity-Immediate, Annuity-Due, Perpetuities, Deferred Annuities and values on any date, Outstanding Loan Balances (OLB)

Unit-1
Teaching Hours:15
Interest Rates, Factors and Level Annuities
 

Interest Rates, Rate of discount, Nominal rates of interest and discount, Constant force of interest, Force of interest, Inflation, Equations of Value and Yield Rates, Annuity-Immediate, Annuity-Due, Perpetuities, Deferred Annuities and values on any date, Outstanding Loan Balances (OLB)

Unit-1
Teaching Hours:15
Interest Rates, Factors and Level Annuities
 

Interest Rates, Rate of discount, Nominal rates of interest and discount, Constant force of interest, Force of interest, Inflation, Equations of Value and Yield Rates, Annuity-Immediate, Annuity-Due, Perpetuities, Deferred Annuities and values on any date, Outstanding Loan Balances (OLB)

Unit-1
Teaching Hours:15
Interest Rates, Factors and Level Annuities
 

Interest Rates, Rate of discount, Nominal rates of interest and discount, Constant force of interest, Force of interest, Inflation, Equations of Value and Yield Rates, Annuity-Immediate, Annuity-Due, Perpetuities, Deferred Annuities and values on any date, Outstanding Loan Balances (OLB)

Unit-1
Teaching Hours:15
Interest Rates, Factors and Level Annuities
 

Interest Rates, Rate of discount, Nominal rates of interest and discount, Constant force of interest, Force of interest, Inflation, Equations of Value and Yield Rates, Annuity-Immediate, Annuity-Due, Perpetuities, Deferred Annuities and values on any date, Outstanding Loan Balances (OLB)

Unit-1
Teaching Hours:15
Interest Rates, Factors and Level Annuities
 

Interest Rates, Rate of discount, Nominal rates of interest and discount, Constant force of interest, Force of interest, Inflation, Equations of Value and Yield Rates, Annuity-Immediate, Annuity-Due, Perpetuities, Deferred Annuities and values on any date, Outstanding Loan Balances (OLB)

Unit-1
Teaching Hours:15
Interest Rates, Factors and Level Annuities
 

Interest Rates, Rate of discount, Nominal rates of interest and discount, Constant force of interest, Force of interest, Inflation, Equations of Value and Yield Rates, Annuity-Immediate, Annuity-Due, Perpetuities, Deferred Annuities and values on any date, Outstanding Loan Balances (OLB)

Unit-1
Teaching Hours:15
Interest Rates, Factors and Level Annuities
 

Interest Rates, Rate of discount, Nominal rates of interest and discount, Constant force of interest, Force of interest, Inflation, Equations of Value and Yield Rates, Annuity-Immediate, Annuity-Due, Perpetuities, Deferred Annuities and values on any date, Outstanding Loan Balances (OLB)

Unit-1
Teaching Hours:15
Interest Rates, Factors and Level Annuities
 

Interest Rates, Rate of discount, Nominal rates of interest and discount, Constant force of interest, Force of interest, Inflation, Equations of Value and Yield Rates, Annuity-Immediate, Annuity-Due, Perpetuities, Deferred Annuities and values on any date, Outstanding Loan Balances (OLB)

Unit-2
Teaching Hours:15
Varying Annuities
 

Non-level Annuities, Annuities with payments in Geometric Progression, Annuities with payment in Arithmetic Progression, Annuity symbols for non-integral terms, Annuities with payments less/more frequent than each interest period and payments in Arithmetic Progression, Continuously Payable Annuities.

Unit-2
Teaching Hours:15
Varying Annuities
 

Non-level Annuities, Annuities with payments in Geometric Progression, Annuities with payment in Arithmetic Progression, Annuity symbols for non-integral terms, Annuities with payments less/more frequent than each interest period and payments in Arithmetic Progression, Continuously Payable Annuities.

Unit-2
Teaching Hours:15
Varying Annuities
 

Non-level Annuities, Annuities with payments in Geometric Progression, Annuities with payment in Arithmetic Progression, Annuity symbols for non-integral terms, Annuities with payments less/more frequent than each interest period and payments in Arithmetic Progression, Continuously Payable Annuities.

Unit-2
Teaching Hours:15
Varying Annuities
 

Non-level Annuities, Annuities with payments in Geometric Progression, Annuities with payment in Arithmetic Progression, Annuity symbols for non-integral terms, Annuities with payments less/more frequent than each interest period and payments in Arithmetic Progression, Continuously Payable Annuities.

Unit-2
Teaching Hours:15
Varying Annuities
 

Non-level Annuities, Annuities with payments in Geometric Progression, Annuities with payment in Arithmetic Progression, Annuity symbols for non-integral terms, Annuities with payments less/more frequent than each interest period and payments in Arithmetic Progression, Continuously Payable Annuities.

Unit-2
Teaching Hours:15
Varying Annuities
 

Non-level Annuities, Annuities with payments in Geometric Progression, Annuities with payment in Arithmetic Progression, Annuity symbols for non-integral terms, Annuities with payments less/more frequent than each interest period and payments in Arithmetic Progression, Continuously Payable Annuities.

Unit-2
Teaching Hours:15
Varying Annuities
 

Non-level Annuities, Annuities with payments in Geometric Progression, Annuities with payment in Arithmetic Progression, Annuity symbols for non-integral terms, Annuities with payments less/more frequent than each interest period and payments in Arithmetic Progression, Continuously Payable Annuities.

Unit-2
Teaching Hours:15
Varying Annuities
 

Non-level Annuities, Annuities with payments in Geometric Progression, Annuities with payment in Arithmetic Progression, Annuity symbols for non-integral terms, Annuities with payments less/more frequent than each interest period and payments in Arithmetic Progression, Continuously Payable Annuities.

Unit-2
Teaching Hours:15
Varying Annuities
 

Non-level Annuities, Annuities with payments in Geometric Progression, Annuities with payment in Arithmetic Progression, Annuity symbols for non-integral terms, Annuities with payments less/more frequent than each interest period and payments in Arithmetic Progression, Continuously Payable Annuities.

Unit-3
Teaching Hours:15
Loans Repayment and Bonds
 

Amortized loans and Amortization Schedules, The sinking fund method, Loans with other repayment patterns, Yield rate examples and other repayment patterns, Bond symbols and basic price formula, Other pricing formula for bonds, Bond Amortization Schedules, Valuing a bond after its date of issue.

Unit-3
Teaching Hours:15
Loans Repayment and Bonds
 

Amortized loans and Amortization Schedules, The sinking fund method, Loans with other repayment patterns, Yield rate examples and other repayment patterns, Bond symbols and basic price formula, Other pricing formula for bonds, Bond Amortization Schedules, Valuing a bond after its date of issue.

Unit-3
Teaching Hours:15
Loans Repayment and Bonds
 

Amortized loans and Amortization Schedules, The sinking fund method, Loans with other repayment patterns, Yield rate examples and other repayment patterns, Bond symbols and basic price formula, Other pricing formula for bonds, Bond Amortization Schedules, Valuing a bond after its date of issue.

Unit-3
Teaching Hours:15
Loans Repayment and Bonds
 

Amortized loans and Amortization Schedules, The sinking fund method, Loans with other repayment patterns, Yield rate examples and other repayment patterns, Bond symbols and basic price formula, Other pricing formula for bonds, Bond Amortization Schedules, Valuing a bond after its date of issue.

Unit-3
Teaching Hours:15
Loans Repayment and Bonds
 

Amortized loans and Amortization Schedules, The sinking fund method, Loans with other repayment patterns, Yield rate examples and other repayment patterns, Bond symbols and basic price formula, Other pricing formula for bonds, Bond Amortization Schedules, Valuing a bond after its date of issue.

Unit-3
Teaching Hours:15
Loans Repayment and Bonds
 

Amortized loans and Amortization Schedules, The sinking fund method, Loans with other repayment patterns, Yield rate examples and other repayment patterns, Bond symbols and basic price formula, Other pricing formula for bonds, Bond Amortization Schedules, Valuing a bond after its date of issue.

Unit-3
Teaching Hours:15
Loans Repayment and Bonds
 

Amortized loans and Amortization Schedules, The sinking fund method, Loans with other repayment patterns, Yield rate examples and other repayment patterns, Bond symbols and basic price formula, Other pricing formula for bonds, Bond Amortization Schedules, Valuing a bond after its date of issue.

Unit-3
Teaching Hours:15
Loans Repayment and Bonds
 

Amortized loans and Amortization Schedules, The sinking fund method, Loans with other repayment patterns, Yield rate examples and other repayment patterns, Bond symbols and basic price formula, Other pricing formula for bonds, Bond Amortization Schedules, Valuing a bond after its date of issue.

Unit-3
Teaching Hours:15
Loans Repayment and Bonds
 

Amortized loans and Amortization Schedules, The sinking fund method, Loans with other repayment patterns, Yield rate examples and other repayment patterns, Bond symbols and basic price formula, Other pricing formula for bonds, Bond Amortization Schedules, Valuing a bond after its date of issue.

Text Books And Reference Books:

 L. J. F. Vaaler and J. W. Daniel, Mathematical interest theory. Mathematical Association of America, 2009.

Essential Reading / Recommended Reading
  1. S. J. Garrett and J. J. McCutcheon, An introduction to the mathematics of finance: a deterministic approach, 2nd ed., Amsterdam: Elsevier/Butterworth-Heinemann, 2013.
  2. A. Černý, Mathematical techniques in finance: tools for incomplete markets. 2nd ed., NJ: Princeton University Press, 2009.
  3. C. Ruckman and J. Francis, Financial mathematics: a practical guide for actuaries and other business professionals. 2nd ed., Weatogue, CT: BPP Professional Education, 2005.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ

Written Assignment

Reference work

Mastery of the core concepts  

Problem solving skills

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Assignment

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT651 - COMPLEX ANALYSIS USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description: This course will enable students to have hands on experience in constructing analytic functions, verifying harmonic functions, illustrating Cauchy’s integral theorem and bilinear transformations and in illustrating different types of sequences and series using Python.

Course Objectives: This course will help the learner to

COBJ 1:Python language using jupyter interface

COBJ 2:Solving basic arithmetic problems using cmath built-in commands

COBJ 3:Solving problems using cmath.

Learning Outcome

CO 1: On successful completion of the course, the students should be able to acquire proficiency in using Python and cmath functions for processing complex numbers.

CO 2: On successful completion of the course, the students should be able to skillful in using Python modules to implement Milne-Thompson method.

CO 3: On successful completion of the course, the students should be able to expertise in illustrating harmonic functions and demonstrating Cauchy's integral theorem Representation of conformal mappings using Matplotlib.

Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Cmath functions for complex numbers
  2. Graphical Illustration of the limit of a complex sequence
  3. Verifying C-R equations
  4. Harmonic functions and harmonic conjugates
  5. Implementation of Milne-Thomson method of constructing analytic functions
  6. Examples connected with Cauchy’s integral theorem
  7. llustration of conformal mapping
  8. Linear and bilinear transformations
  9. Convergence/divergence of complex series
  10. Applications of complex analysis in various fields
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Cmath functions for complex numbers
  2. Graphical Illustration of the limit of a complex sequence
  3. Verifying C-R equations
  4. Harmonic functions and harmonic conjugates
  5. Implementation of Milne-Thomson method of constructing analytic functions
  6. Examples connected with Cauchy’s integral theorem
  7. llustration of conformal mapping
  8. Linear and bilinear transformations
  9. Convergence/divergence of complex series
  10. Applications of complex analysis in various fields
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Cmath functions for complex numbers
  2. Graphical Illustration of the limit of a complex sequence
  3. Verifying C-R equations
  4. Harmonic functions and harmonic conjugates
  5. Implementation of Milne-Thomson method of constructing analytic functions
  6. Examples connected with Cauchy’s integral theorem
  7. llustration of conformal mapping
  8. Linear and bilinear transformations
  9. Convergence/divergence of complex series
  10. Applications of complex analysis in various fields
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Cmath functions for complex numbers
  2. Graphical Illustration of the limit of a complex sequence
  3. Verifying C-R equations
  4. Harmonic functions and harmonic conjugates
  5. Implementation of Milne-Thomson method of constructing analytic functions
  6. Examples connected with Cauchy’s integral theorem
  7. llustration of conformal mapping
  8. Linear and bilinear transformations
  9. Convergence/divergence of complex series
  10. Applications of complex analysis in various fields
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Cmath functions for complex numbers
  2. Graphical Illustration of the limit of a complex sequence
  3. Verifying C-R equations
  4. Harmonic functions and harmonic conjugates
  5. Implementation of Milne-Thomson method of constructing analytic functions
  6. Examples connected with Cauchy’s integral theorem
  7. llustration of conformal mapping
  8. Linear and bilinear transformations
  9. Convergence/divergence of complex series
  10. Applications of complex analysis in various fields
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Cmath functions for complex numbers
  2. Graphical Illustration of the limit of a complex sequence
  3. Verifying C-R equations
  4. Harmonic functions and harmonic conjugates
  5. Implementation of Milne-Thomson method of constructing analytic functions
  6. Examples connected with Cauchy’s integral theorem
  7. llustration of conformal mapping
  8. Linear and bilinear transformations
  9. Convergence/divergence of complex series
  10. Applications of complex analysis in various fields
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Cmath functions for complex numbers
  2. Graphical Illustration of the limit of a complex sequence
  3. Verifying C-R equations
  4. Harmonic functions and harmonic conjugates
  5. Implementation of Milne-Thomson method of constructing analytic functions
  6. Examples connected with Cauchy’s integral theorem
  7. llustration of conformal mapping
  8. Linear and bilinear transformations
  9. Convergence/divergence of complex series
  10. Applications of complex analysis in various fields
Text Books And Reference Books:

H P Langtangen, A Primer on Scientific Programming with Python, 2nd ed., Springer, 2016.

Essential Reading / Recommended Reading
  1. B E Shapiro, Scientific Computation: Python Hacking for Math Junkies, Sherwood Forest Books, 2015.
  2. C Hill, Learning Scientific Programming with Python, Cambridge Univesity Press, 2016.
  3. A. Saha, Doing Math with Python: Use Programming to Explore Algebra, Statistics, Calculus, and More!, no starch press:San Fransisco, 2015.
Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT651A - MECHANICS USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description: This course aims at enabling the students to explore and study the statics and dynamics of particles in a detailed manner using Python. This course is designed with a learner-centric approach wherein the students will acquire mastery in understanding mechanics using Python.

Course objectives: This course will help the learner to

COBJ 1: acquire skill in usage of suitable functions/packages of Python.

COBJ 2: gain proficiency in using Python to solve problems on Mechanics.   

Learning Outcome

CO1: On successful completion of the course, the students should be able to acquire proficiency in using different functions of Python to study Differential Calculus. Mechanics.

CO2: On successful completion of the course, the students should be able to demonstrate the use of Python to understand and interpret the dynamical aspects of Python.

CO3: On successful completion of the course, the students should be able to use Python to evaluate the resultant of forces and check for equilibrium state of the forces.

CO4: On successful completion of the course, the students should be able to be familiar with the built-in functions to find moment and couple.

Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to Python: Some useful shortcuts; variables; input/output; relational operators, logical operators; conditional statements; lists and matrices\
  2. Resultant of a number of forces: Resultant of two forces in the same plane, resultant of any number of forces, resultant of any number of forces
  3. Components of a given force: Components of a force in horizontal and vertical directions, components of a force in any two given directions
  4. Resultant force of parallel forces: Resultant force of two parallel like forces, resultant force of two parallel alike forces
  5. Moments and torques: Moment from magnitude and perpendicular distance, equilibrium of two moments
  6. Projectiles
  7. Simple harmonic motion
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to Python: Some useful shortcuts; variables; input/output; relational operators, logical operators; conditional statements; lists and matrices\
  2. Resultant of a number of forces: Resultant of two forces in the same plane, resultant of any number of forces, resultant of any number of forces
  3. Components of a given force: Components of a force in horizontal and vertical directions, components of a force in any two given directions
  4. Resultant force of parallel forces: Resultant force of two parallel like forces, resultant force of two parallel alike forces
  5. Moments and torques: Moment from magnitude and perpendicular distance, equilibrium of two moments
  6. Projectiles
  7. Simple harmonic motion
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to Python: Some useful shortcuts; variables; input/output; relational operators, logical operators; conditional statements; lists and matrices\
  2. Resultant of a number of forces: Resultant of two forces in the same plane, resultant of any number of forces, resultant of any number of forces
  3. Components of a given force: Components of a force in horizontal and vertical directions, components of a force in any two given directions
  4. Resultant force of parallel forces: Resultant force of two parallel like forces, resultant force of two parallel alike forces
  5. Moments and torques: Moment from magnitude and perpendicular distance, equilibrium of two moments
  6. Projectiles
  7. Simple harmonic motion
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to Python: Some useful shortcuts; variables; input/output; relational operators, logical operators; conditional statements; lists and matrices\
  2. Resultant of a number of forces: Resultant of two forces in the same plane, resultant of any number of forces, resultant of any number of forces
  3. Components of a given force: Components of a force in horizontal and vertical directions, components of a force in any two given directions
  4. Resultant force of parallel forces: Resultant force of two parallel like forces, resultant force of two parallel alike forces
  5. Moments and torques: Moment from magnitude and perpendicular distance, equilibrium of two moments
  6. Projectiles
  7. Simple harmonic motion
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to Python: Some useful shortcuts; variables; input/output; relational operators, logical operators; conditional statements; lists and matrices\
  2. Resultant of a number of forces: Resultant of two forces in the same plane, resultant of any number of forces, resultant of any number of forces
  3. Components of a given force: Components of a force in horizontal and vertical directions, components of a force in any two given directions
  4. Resultant force of parallel forces: Resultant force of two parallel like forces, resultant force of two parallel alike forces
  5. Moments and torques: Moment from magnitude and perpendicular distance, equilibrium of two moments
  6. Projectiles
  7. Simple harmonic motion
Text Books And Reference Books:
  1. B. E. Shapiro, Scientific Computation: Python Hacking for Math Junkies, Sherwood Forest Books, 2015.
  2. Anders Malthe-Sørenssen, Elementary Mechanics Using Python: A Modern Course Combining Analytical and Numerical Techniques (Undergraduate Lecture Notes in Physics) 2015.
  3. C. Hill, Learning Scientific Programming with Python, Cambridge University Press, 2016.
Essential Reading / Recommended Reading

A. Saha, Doing Math with Python: Use Programming to Explore Algebra, Statistics, Calculus, and More!, no starch press: San Fransisco, 2015.

Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT651B - NUMERICAL METHODS USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description: This course will help the students to have an in depth knowledge of various numerical methods required in scientific and technological applications. Students will gain hands on experience in using Python for illustrating various numerical techniques.

Course Objectives: This course will help the learner to

COBJ 1: develop the basic understanding of numerical algorithms and skills to implement algorithms to solve mathematical problems using Python.

COBJ 2: develop the basic understanding of the applicability and limitations of the techniques.

Learning Outcome

CO1.: On successful completion of the course, the students should be able to implement a numerical solution method in a well-designed, well-documented Python program code.

CO2.: On successful completion of the course, the students should be able to interpret the numerical solutions that were obtained in regard to their accuracy and suitability for applications

CO3.: On successful completion of the course, the students should be able to present and interpret numerical results in an informative way.

Unit-1
Teaching Hours:30
Proposed topics
 
  1. Some basic operations in Python for scientific computing                          
  2. Solution of Algebraic and Transcendental Equations  
    • Bisection method
    • Fixed point Iteration method
    • The method of False Position
    • Newton-Raphson method
  3. Solution of linear systems
    • Gauss Elimination method
    • Gauss-Seidel Iterative method
    • Gauss-Jacobi Iterative method
    • LU Decomposition method
  4. Numerical Differentiation and Integration
  5. Solution of Differential Equations
    • Euler’s method
    • Runge Kutta method
Unit-1
Teaching Hours:30
Proposed topics
 
  1. Some basic operations in Python for scientific computing                          
  2. Solution of Algebraic and Transcendental Equations  
    • Bisection method
    • Fixed point Iteration method
    • The method of False Position
    • Newton-Raphson method
  3. Solution of linear systems
    • Gauss Elimination method
    • Gauss-Seidel Iterative method
    • Gauss-Jacobi Iterative method
    • LU Decomposition method
  4. Numerical Differentiation and Integration
  5. Solution of Differential Equations
    • Euler’s method
    • Runge Kutta method
Unit-1
Teaching Hours:30
Proposed topics
 
  1. Some basic operations in Python for scientific computing                          
  2. Solution of Algebraic and Transcendental Equations  
    • Bisection method
    • Fixed point Iteration method
    • The method of False Position
    • Newton-Raphson method
  3. Solution of linear systems
    • Gauss Elimination method
    • Gauss-Seidel Iterative method
    • Gauss-Jacobi Iterative method
    • LU Decomposition method
  4. Numerical Differentiation and Integration
  5. Solution of Differential Equations
    • Euler’s method
    • Runge Kutta method
Unit-1
Teaching Hours:30
Proposed topics
 
  1. Some basic operations in Python for scientific computing                          
  2. Solution of Algebraic and Transcendental Equations  
    • Bisection method
    • Fixed point Iteration method
    • The method of False Position
    • Newton-Raphson method
  3. Solution of linear systems
    • Gauss Elimination method
    • Gauss-Seidel Iterative method
    • Gauss-Jacobi Iterative method
    • LU Decomposition method
  4. Numerical Differentiation and Integration
  5. Solution of Differential Equations
    • Euler’s method
    • Runge Kutta method
Unit-1
Teaching Hours:30
Proposed topics
 
  1. Some basic operations in Python for scientific computing                          
  2. Solution of Algebraic and Transcendental Equations  
    • Bisection method
    • Fixed point Iteration method
    • The method of False Position
    • Newton-Raphson method
  3. Solution of linear systems
    • Gauss Elimination method
    • Gauss-Seidel Iterative method
    • Gauss-Jacobi Iterative method
    • LU Decomposition method
  4. Numerical Differentiation and Integration
  5. Solution of Differential Equations
    • Euler’s method
    • Runge Kutta method
Text Books And Reference Books:

J. Kiusalaas, Numerical methods in engineering with Python 3, Cambridge University press, 2013.

Essential Reading / Recommended Reading

H. Fangohr, Introduction to Python for Computational Science and Engineering (A beginner’s guide), University of Southampton, 2015.

Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT651C - DISCRETE MATHEMATICS USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course description: This course aims at providing hands on experience in using Python functions to illustrate the notions of combinatorics, set theory and relations.

Course objectives: This course will help the learner to

COBJ1. gain a familiarity with programs on fundamental concepts of Combinatorial Mathematics

COBJ2. understand and apply knowledge to solve combinatorial problems using Python

Learning Outcome

CO1: On successful completion of the course, the students should be able to attain sufficient skills in using Python functions

CO2: On successful completion of the course, the students should be able to demonstrate programming skills in solving problems related to applications of computational mathematics.

Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Permutations
  2. Combinations
  3. Set construction and set operations
  4. Using Venn diagrams to visualize relationships between sets
  5. Recurrence relations
  6. Partially ordered sets
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Permutations
  2. Combinations
  3. Set construction and set operations
  4. Using Venn diagrams to visualize relationships between sets
  5. Recurrence relations
  6. Partially ordered sets
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Permutations
  2. Combinations
  3. Set construction and set operations
  4. Using Venn diagrams to visualize relationships between sets
  5. Recurrence relations
  6. Partially ordered sets
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Permutations
  2. Combinations
  3. Set construction and set operations
  4. Using Venn diagrams to visualize relationships between sets
  5. Recurrence relations
  6. Partially ordered sets
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Permutations
  2. Combinations
  3. Set construction and set operations
  4. Using Venn diagrams to visualize relationships between sets
  5. Recurrence relations
  6. Partially ordered sets
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Permutations
  2. Combinations
  3. Set construction and set operations
  4. Using Venn diagrams to visualize relationships between sets
  5. Recurrence relations
  6. Partially ordered sets
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Permutations
  2. Combinations
  3. Set construction and set operations
  4. Using Venn diagrams to visualize relationships between sets
  5. Recurrence relations
  6. Partially ordered sets
Text Books And Reference Books:
  1. Amit Saha, Doing Math with Python: Use Programming to Explore Algebra, Statistics, Calculus, and More!, no starch press:San Fransisco, 2015.
  2. H P Langtangen, A Primer on Scientific Programming with Python, 2nd ed., Springer, 2016.
Essential Reading / Recommended Reading
  1. B E Shapiro, Scientific Computation: Python Hacking for Math Junkies, Sherwood Forest Books, 2015.
  2. C Hill, Learning Scientific Programming with Python, Cambridge University Press, 2016.
Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT651D - NUMBER THEORY USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description: This course will help the students to gain hands-on experience in using Python for illustrating various number theory concepts such as the divisibility, distribution of primes, number conversions, congruences and applications of number theory.

Course Objectives: This course will help the learner to

COBJ1. be familiar with the built- in functions required to deal with number theoretic concepts and operations.

COBJ2. develop programming skills to solve various number theoretic concepts.

COBJ3. gain proficiency in symbolic computation using python.

Learning Outcome

CO1: On successfully completing the course, the students should be able to use Python to solve problems in number theory, number conversions.

CO2: On successfully completing the course, the students should be able to use Python to demonstrate the understanding of number theory concepts.

CO3: On successfully completing the course, the students should be able to use Python to model and solve practical problems using number theoretic concepts.

Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to packages and libraries in Python.
  2. Division algorithm.
  3. Hexadecimal, octal and binary representation of the integers.
  4. Euclid algorithm.
  5. Prime factorisation of integers.
  6. Solution of a system of linear congruences.
  7. Number theoretic functions τ, σ and φ.
  8. Hashing functions, pseudorandom numbers.
  9. Parity check bits
  10. Cryptography
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to packages and libraries in Python.
  2. Division algorithm.
  3. Hexadecimal, octal and binary representation of the integers.
  4. Euclid algorithm.
  5. Prime factorisation of integers.
  6. Solution of a system of linear congruences.
  7. Number theoretic functions τ, σ and φ.
  8. Hashing functions, pseudorandom numbers.
  9. Parity check bits
  10. Cryptography
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to packages and libraries in Python.
  2. Division algorithm.
  3. Hexadecimal, octal and binary representation of the integers.
  4. Euclid algorithm.
  5. Prime factorisation of integers.
  6. Solution of a system of linear congruences.
  7. Number theoretic functions τ, σ and φ.
  8. Hashing functions, pseudorandom numbers.
  9. Parity check bits
  10. Cryptography
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to packages and libraries in Python.
  2. Division algorithm.
  3. Hexadecimal, octal and binary representation of the integers.
  4. Euclid algorithm.
  5. Prime factorisation of integers.
  6. Solution of a system of linear congruences.
  7. Number theoretic functions τ, σ and φ.
  8. Hashing functions, pseudorandom numbers.
  9. Parity check bits
  10. Cryptography
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to packages and libraries in Python.
  2. Division algorithm.
  3. Hexadecimal, octal and binary representation of the integers.
  4. Euclid algorithm.
  5. Prime factorisation of integers.
  6. Solution of a system of linear congruences.
  7. Number theoretic functions τ, σ and φ.
  8. Hashing functions, pseudorandom numbers.
  9. Parity check bits
  10. Cryptography
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to packages and libraries in Python.
  2. Division algorithm.
  3. Hexadecimal, octal and binary representation of the integers.
  4. Euclid algorithm.
  5. Prime factorisation of integers.
  6. Solution of a system of linear congruences.
  7. Number theoretic functions τ, σ and φ.
  8. Hashing functions, pseudorandom numbers.
  9. Parity check bits
  10. Cryptography
Unit-1
Teaching Hours:30
Proposed Topics:
 
  1. Introduction to packages and libraries in Python.
  2. Division algorithm.
  3. Hexadecimal, octal and binary representation of the integers.
  4. Euclid algorithm.
  5. Prime factorisation of integers.
  6. Solution of a system of linear congruences.
  7. Number theoretic functions τ, σ and φ.
  8. Hashing functions, pseudorandom numbers.
  9. Parity check bits
  10. Cryptography
Text Books And Reference Books:

J.C. Bautista, Mathematics with Python Programming, Lulu.com, 2014.

Essential Reading / Recommended Reading

M. Litvin and G. Litvin, Mathematics for the Digital Age and Programming in Python, Skylight Publishing, 2010.

Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT651E - FINANCIAL MATHEMATICS USING EXCEL AND PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description: The course aims at providing hands on experience in using Excel/Python programming to illustrate the computation of constant/varying force of interest, continuously payable varying/non-varying annuities, increasing/decreasing annuity immediate/due, loans and bonds.

Course objectives: This course will help the learner to

COBJ1. aacquire skill in solving problems on Financial Mathematics using Python.

COBJ2. gain proficiency in using the Python programming skills to solve problems on Financial Mathematics.

Learning Outcome

CO1: On successful completion of the course, the students should be able to demonstrate sufficient skills in using Python programming language for solving problems on Financial Mathematics.

CO2: On successful completion of the course, the students should be able to apply the notions on various types of interests, annuities, loans and bonds, by solving problems using Python.

Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Force of interest
  2. Level Annuities
  3. Outstanding Loan balances
  4. Annuities with payments in Geometric Progression
  5. Annuities with payments in Arithmetic Progression
  6. Continuously Payable annuities
  7. Amortization Loans and Amortization Schedules
  8. Bond Amortization Schedules
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Force of interest
  2. Level Annuities
  3. Outstanding Loan balances
  4. Annuities with payments in Geometric Progression
  5. Annuities with payments in Arithmetic Progression
  6. Continuously Payable annuities
  7. Amortization Loans and Amortization Schedules
  8. Bond Amortization Schedules
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Force of interest
  2. Level Annuities
  3. Outstanding Loan balances
  4. Annuities with payments in Geometric Progression
  5. Annuities with payments in Arithmetic Progression
  6. Continuously Payable annuities
  7. Amortization Loans and Amortization Schedules
  8. Bond Amortization Schedules
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Force of interest
  2. Level Annuities
  3. Outstanding Loan balances
  4. Annuities with payments in Geometric Progression
  5. Annuities with payments in Arithmetic Progression
  6. Continuously Payable annuities
  7. Amortization Loans and Amortization Schedules
  8. Bond Amortization Schedules
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Force of interest
  2. Level Annuities
  3. Outstanding Loan balances
  4. Annuities with payments in Geometric Progression
  5. Annuities with payments in Arithmetic Progression
  6. Continuously Payable annuities
  7. Amortization Loans and Amortization Schedules
  8. Bond Amortization Schedules
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Force of interest
  2. Level Annuities
  3. Outstanding Loan balances
  4. Annuities with payments in Geometric Progression
  5. Annuities with payments in Arithmetic Progression
  6. Continuously Payable annuities
  7. Amortization Loans and Amortization Schedules
  8. Bond Amortization Schedules
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Force of interest
  2. Level Annuities
  3. Outstanding Loan balances
  4. Annuities with payments in Geometric Progression
  5. Annuities with payments in Arithmetic Progression
  6. Continuously Payable annuities
  7. Amortization Loans and Amortization Schedules
  8. Bond Amortization Schedules
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Force of interest
  2. Level Annuities
  3. Outstanding Loan balances
  4. Annuities with payments in Geometric Progression
  5. Annuities with payments in Arithmetic Progression
  6. Continuously Payable annuities
  7. Amortization Loans and Amortization Schedules
  8. Bond Amortization Schedules
Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Force of interest
  2. Level Annuities
  3. Outstanding Loan balances
  4. Annuities with payments in Geometric Progression
  5. Annuities with payments in Arithmetic Progression
  6. Continuously Payable annuities
  7. Amortization Loans and Amortization Schedules
  8. Bond Amortization Schedules
Text Books And Reference Books:
  1. Y. Yan, Python for finance: financial modeling and quantitative analysis explained.  2nd ed., Packt Publishing, 2017. 
  2. A. L. Day, Mastering Financial Mathematics in Microsoft Excel - A practical guide for business calculations, 3rd ed., Pearson Education Limited, 2015.
Essential Reading / Recommended Reading
  1. L. J. F. Vaaler and J. W. Daniel, Mathematical interest theory. 2nd ed., Mathematical Association of America, 2009.
  2. J. M. Weiming, Mastering python for finance understand, design, and implement state of-the-art mathematical and statistical applications used in finance with Python. Packt Publishing, 2015. 
  3. M. Humber, Personal finance with Python: using pandas, requests, and recurrent.  1st ed., Apress, 2018. 
  4. S. Fletcher and C. Gardner, Financial modeling in Python. Wiley, 2009.
  5. S. D. Promislow, Fundamentals of Acturaial Mathematics, 3rd ed., John Wiley and Sons Limited, 2015.
Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT681 - PROJECT ON MATHEMATICAL MODELS (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:150
Credits:5

Course Objectives/Course Description

 

Course description: The course aims at providing hands on experience in analyzing practical problems by formulating the corresponding mathematical models.

Course objectives: This course will help the learner to

 COBJ1. Develop positive attitude, knowledge and competence for research in Mathematics

Learning Outcome

CO1.: On successful completion of the course, the students should be able to demonstrate analytical skills.

CO2.: On successful completion of the course, the students should be able to apply computational skills in Mathematics

Unit-1
Teaching Hours:75
PROJECT
 

Students are given a choice of topics in Mathematical modelling at the undergraduate level with the approval of HOD. Each candidate will work under the supervision of the faculty.  Project Coordinator will allot the supervisor for each candidate in consultation with the HOD at the end of the fifth  semester.

Project need not be based on original research work. Project could be based on the review of research papers that are at the undergraduate level.

Each candidate has to submit a dissertation on the project topic followed by viva voce examination. The viva voce will be conducted by the committee constituted by the head of the department which will have an external and an internal examiner. The student must secure 50% of the marks to pass the examination.  The candidates who fail must redo the project as per the university regulations.

Proposed Topics for Project: 

  1. Mathematical Modeling using Graphs/Networks
  2. Mathematical Modeling using Optimization Techniques
  3. Mathematical Modeling using Linear Algebra
  4. Mathematical Modeling using Differential Equations
  5. Mathematical Modeling using Calculus of Several Variables. (Proficiency in solving PDE may be required)
  6. Developing a new Mathematics library for FOSS tools
Unit-1
Teaching Hours:75
PROJECT
 

Students are given a choice of topics in Mathematical modelling at the undergraduate level with the approval of HOD. Each candidate will work under the supervision of the faculty.  Project Coordinator will allot the supervisor for each candidate in consultation with the HOD at the end of the fifth  semester.

Project need not be based on original research work. Project could be based on the review of research papers that are at the undergraduate level.

Each candidate has to submit a dissertation on the project topic followed by viva voce examination. The viva voce will be conducted by the committee constituted by the head of the department which will have an external and an internal examiner. The student must secure 50% of the marks to pass the examination.  The candidates who fail must redo the project as per the university regulations.

Proposed Topics for Project: 

  1. Mathematical Modeling using Graphs/Networks
  2. Mathematical Modeling using Optimization Techniques
  3. Mathematical Modeling using Linear Algebra
  4. Mathematical Modeling using Differential Equations
  5. Mathematical Modeling using Calculus of Several Variables. (Proficiency in solving PDE may be required)
  6. Developing a new Mathematics library for FOSS tools
Unit-1
Teaching Hours:75
PROJECT
 

Students are given a choice of topics in Mathematical modelling at the undergraduate level with the approval of HOD. Each candidate will work under the supervision of the faculty.  Project Coordinator will allot the supervisor for each candidate in consultation with the HOD at the end of the fifth  semester.

Project need not be based on original research work. Project could be based on the review of research papers that are at the undergraduate level.

Each candidate has to submit a dissertation on the project topic followed by viva voce examination. The viva voce will be conducted by the committee constituted by the head of the department which will have an external and an internal examiner. The student must secure 50% of the marks to pass the examination.  The candidates who fail must redo the project as per the university regulations.

Proposed Topics for Project: 

  1. Mathematical Modeling using Graphs/Networks
  2. Mathematical Modeling using Optimization Techniques
  3. Mathematical Modeling using Linear Algebra
  4. Mathematical Modeling using Differential Equations
  5. Mathematical Modeling using Calculus of Several Variables. (Proficiency in solving PDE may be required)
  6. Developing a new Mathematics library for FOSS tools
Unit-1
Teaching Hours:75
PROJECT
 

Students are given a choice of topics in Mathematical modelling at the undergraduate level with the approval of HOD. Each candidate will work under the supervision of the faculty.  Project Coordinator will allot the supervisor for each candidate in consultation with the HOD at the end of the fifth  semester.

Project need not be based on original research work. Project could be based on the review of research papers that are at the undergraduate level.

Each candidate has to submit a dissertation on the project topic followed by viva voce examination. The viva voce will be conducted by the committee constituted by the head of the department which will have an external and an internal examiner. The student must secure 50% of the marks to pass the examination.  The candidates who fail must redo the project as per the university regulations.

Proposed Topics for Project: 

  1. Mathematical Modeling using Graphs/Networks
  2. Mathematical Modeling using Optimization Techniques
  3. Mathematical Modeling using Linear Algebra
  4. Mathematical Modeling using Differential Equations
  5. Mathematical Modeling using Calculus of Several Variables. (Proficiency in solving PDE may be required)
  6. Developing a new Mathematics library for FOSS tools
Unit-1
Teaching Hours:75
PROJECT
 

Students are given a choice of topics in Mathematical modelling at the undergraduate level with the approval of HOD. Each candidate will work under the supervision of the faculty.  Project Coordinator will allot the supervisor for each candidate in consultation with the HOD at the end of the fifth  semester.

Project need not be based on original research work. Project could be based on the review of research papers that are at the undergraduate level.

Each candidate has to submit a dissertation on the project topic followed by viva voce examination. The viva voce will be conducted by the committee constituted by the head of the department which will have an external and an internal examiner. The student must secure 50% of the marks to pass the examination.  The candidates who fail must redo the project as per the university regulations.

Proposed Topics for Project: 

  1. Mathematical Modeling using Graphs/Networks
  2. Mathematical Modeling using Optimization Techniques
  3. Mathematical Modeling using Linear Algebra
  4. Mathematical Modeling using Differential Equations
  5. Mathematical Modeling using Calculus of Several Variables. (Proficiency in solving PDE may be required)
  6. Developing a new Mathematics library for FOSS tools
Text Books And Reference Books:

As per the field of reserach.

Essential Reading / Recommended Reading

As per the field of reserach.

Evaluation Pattern

 

Component Maximum Marks
Proposal Presentation 10
Progress Report / Presentation-I 20
Progress Report / Presentation-II 20
Final Viva Voce examination 50
Final Project Report 40
Research Publication 10
Total 150

PHY631 - MODERN PHYSICS - II (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This course is envisaged to provide a strong foundation of basics of modern physics.  Molecular physics, Lasers, solids, superconductivity and nuclear physics.

Learning Outcome

CO1: Develop a fundamental understanding of molecular spectroscopy vis-à-vis infrared and Raman spectroscopy.

CO2: Acquire a basic understanding about the working of LASER.

CO3: Get familiarized with the free electron theory and its application in solids.

CO4: Gain a brief overview about the nuclear structure and learn the working principles of nuclear detectors and accelerators.

Unit-1
Teaching Hours:15
Molecular physics
 

Molecular spectra: Types of motions in a molecule - electronic, vibration, rotation; general features of band spectra (compared to atomic spectra), molecular energy distributions in spectrum, energy states and spectra of molecules; the diatomic molecule as a rigid rotator, non rigid rotator, the rotational energy levels and their spectrum. Information about the moment of inertia and inter nuclear distances from the pure rotational spectrum.

Raman effect: The Rayleigh’s Scattering, the Raman Scattering. Quantum theory of Raman effect and Raman spectrum-Stokes and anti-Stokes lines. Applications of Raman effect:Complementary character of  Raman and IR spectra.              

Lasers: spontaneous emission, stimulated emission and stimulated absorption, conditions for laser action-coherence, population inversion, types of lasers: Gas lasers (He-Ne), semiconductor lasers,applications of Lasers.     

Unit-1
Teaching Hours:15
Molecular physics
 

Molecular spectra: Types of motions in a molecule - electronic, vibration, rotation; general features of band spectra (compared to atomic spectra), molecular energy distributions in spectrum, energy states and spectra of molecules; the diatomic molecule as a rigid rotator, non rigid rotator, the rotational energy levels and their spectrum. Information about the moment of inertia and inter nuclear distances from the pure rotational spectrum.

Raman effect: The Rayleigh’s Scattering, the Raman Scattering. Quantum theory of Raman effect and Raman spectrum-Stokes and anti-Stokes lines. Applications of Raman effect:Complementary character of  Raman and IR spectra.              

Lasers: spontaneous emission, stimulated emission and stimulated absorption, conditions for laser action-coherence, population inversion, types of lasers: Gas lasers (He-Ne), semiconductor lasers,applications of Lasers.     

Unit-2
Teaching Hours:15
Condensed matter Physics
 

Free-Electron Theory of Metals:   Introduction - Drude and Lorentz classical theory, ­ expressions for electrical conductivity- Ohm's law, thermal conductivity - Wiedmann-Franz law - density of states for free electrons - Fermi-Dirac distribution function and Fermi energy – expression for Fermi energy and kinetic energy at absolute zero and above absolute zero.

Band Theory of Solids:  Introduction, formation of energy bands, distinction between metals, insulators and semiconductors; semiconductors - intrinsic semiconductors - concept of holes- concept of effective mass - derivation of expression for carrier concentration (for electrons and holes) and electrical conductivity ­- extrinsic semiconductors-impurity states - energy band diagram and the Fermi level - Hall effect in metals and semiconductors, Photoconductivity, Solar cells.                        

Superconductivity:  Introduction, experimental facts - zero resistivity -  critical field - critical current density- persistent currents -­ Meissner effect, type I and type II superconductors, Cooper pairs - BCS Theory (basic ideas).

Unit-2
Teaching Hours:15
Condensed matter Physics
 

Free-Electron Theory of Metals:   Introduction - Drude and Lorentz classical theory, ­ expressions for electrical conductivity- Ohm's law, thermal conductivity - Wiedmann-Franz law - density of states for free electrons - Fermi-Dirac distribution function and Fermi energy – expression for Fermi energy and kinetic energy at absolute zero and above absolute zero.

Band Theory of Solids:  Introduction, formation of energy bands, distinction between metals, insulators and semiconductors; semiconductors - intrinsic semiconductors - concept of holes- concept of effective mass - derivation of expression for carrier concentration (for electrons and holes) and electrical conductivity ­- extrinsic semiconductors-impurity states - energy band diagram and the Fermi level - Hall effect in metals and semiconductors, Photoconductivity, Solar cells.                        

Superconductivity:  Introduction, experimental facts - zero resistivity -  critical field - critical current density- persistent currents -­ Meissner effect, type I and type II superconductors, Cooper pairs - BCS Theory (basic ideas).

Unit-3
Teaching Hours:15
Nuclear Physics
 

Structure and properties of Nuclei: Radius,Nuclear charge - Rutherford’s theory of alpha particle scattering - derivation of Rutherford’s scattering formula - Nuclear mass: Bainbridge mass spectrograph.                                  

Alpha decay: Range and disintegration energy of alpha particles, Range, ionization, specific ionization and Geiger–Nuttal law -brief description of characteristics of alpha ray spectrum - Gamow’s theory of alpha decay.                

Beta decay: types of beta decay (electron, positron decay and electron capture) - Characteristics of beta spectrum - Pauli’s neutrino hypothesis                            

Nuclear reactions: Q-value and Types of nuclear reactions.                                      

Detectors and Accelerators: GM counter, Scintillation counter, linear accelerators, Cyclotron – principle and working.                     

Unit-3
Teaching Hours:15
Nuclear Physics
 

Structure and properties of Nuclei: Radius,Nuclear charge - Rutherford’s theory of alpha particle scattering - derivation of Rutherford’s scattering formula - Nuclear mass: Bainbridge mass spectrograph.                                  

Alpha decay: Range and disintegration energy of alpha particles, Range, ionization, specific ionization and Geiger–Nuttal law -brief description of characteristics of alpha ray spectrum - Gamow’s theory of alpha decay.                

Beta decay: types of beta decay (electron, positron decay and electron capture) - Characteristics of beta spectrum - Pauli’s neutrino hypothesis                            

Nuclear reactions: Q-value and Types of nuclear reactions.                                      

Detectors and Accelerators: GM counter, Scintillation counter, linear accelerators, Cyclotron – principle and working.                     

Text Books And Reference Books:

1. Modern Physics, R.Murugesan, S. Chand and Company, New Delhi, 1996.

2. Solid State Physics, S O Pillai, New Age International (P) Ltd., New Delhi, 2009.

3. Concepts of Modern Physics, Beiser ,III Edition, student edition, New Delhi, 1981.

Essential Reading / Recommended Reading

1. Introduction to Modern Physics,R.B. Singh, New Age International,New Delhi, 2002.

2.  The Feynmann, Lectures on physics, Narosa Publishing House, New Delhi, 2008.

3. Modern Physics, Sehgal Chopra Sehgal, S. Chand & sons, New Delhi, 1998.     

4.  Elements of Modern Physics,S.H. Patil ,TMH publishing, New Delhi, 1984.

5.  Modern Physics Part I and 2, S.N. Ghosal,  S.Chand and Company, New Delhi 1996

Evaluation Pattern

CIA I Assignment - 10 Marks

CIA II - Mid sem - 25 Marks

CIA III - 10 Marks

Attendance/Punctuality: 05

ESE: 50 Marks

Evaluation will be based on tests, short assignments and presentations.

PHY641A - SOLID STATE PHYSICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:03

Course Objectives/Course Description

 

This course is intended to make the students understand the basic concepts of solid-state physics such as geometry of crystalline state, production of X-rays and diffraction from solids.  It enables the students to explore the fundamental concepts of lattice dynamics and the various physical properties of solids. 

Learning Outcome

CO1: To understand the structure of solids and lattice dynamics

CO2: To gain skills necessary to understand crystal structures using X-ray diffraction technique

CO3: To demonstrate knowledge and understanding on magnetic, dielectric and ferroelectric properties of materials

Unit-1
Teaching Hours:16
Crystal structure of solids
 

Crystal structure: Amorphous and crystalline materials, lattice, basis and crystal structure, lattice translation vectors, unit cell, primitive and non-primitive cells; Bravais lattices- two dimensional and three dimensional lattice types, seven crystal systems; atoms per unit cell, co-ordination number, atomic radius and packing fraction (simple cubic, fcc and bcc), types of close packed structures (sodium chloride and hexagonal zinc sulphide structures); symmetry operations and symmetry elements (translation, rotation, inversion and mirror operations); lattice planes, Miller indices, spacing between lattice planes of cubic crystals; reciprocal lattice: Concept, geometrical construction, vector algebraic discussion, reciprocal lattice vector and properties, Brillouin zones.           

Crystal bonding: cohesive energy, types of bonding-ionic bond, covalent bond and metallic bond, properties and applications.   

Unit-1
Teaching Hours:16
Crystal structure of solids
 

Crystal structure: Amorphous and crystalline materials, lattice, basis and crystal structure, lattice translation vectors, unit cell, primitive and non-primitive cells; Bravais lattices- two dimensional and three dimensional lattice types, seven crystal systems; atoms per unit cell, co-ordination number, atomic radius and packing fraction (simple cubic, fcc and bcc), types of close packed structures (sodium chloride and hexagonal zinc sulphide structures); symmetry operations and symmetry elements (translation, rotation, inversion and mirror operations); lattice planes, Miller indices, spacing between lattice planes of cubic crystals; reciprocal lattice: Concept, geometrical construction, vector algebraic discussion, reciprocal lattice vector and properties, Brillouin zones.           

Crystal bonding: cohesive energy, types of bonding-ionic bond, covalent bond and metallic bond, properties and applications.   

Unit-2
Teaching Hours:12
Crystal diffraction and lattice dynamics
 

Crystal diffraction: X-rays- Production of X-rays, continuous and characteristic X-rays. Mosley's law; scattering of X-rays, diffraction of X-rays by crystals- Bragg’s law, powder diffraction method, Laue and rotating crystal methods, atomic and structure factor, systematic absences due to lattice types, determination of crystal structure and applications.           

Lattice dynamics: Introduction, elastic waves, lattice vibrations and phonons, dynamics of linear monoatomic lattice, symmetry in k-space, number of modes in one dimensional lattice, dynamics of diatomic lattice, acoustical and optical phonons, density of states for a three dimensional solid.                

Unit-2
Teaching Hours:12
Crystal diffraction and lattice dynamics
 

Crystal diffraction: X-rays- Production of X-rays, continuous and characteristic X-rays. Mosley's law; scattering of X-rays, diffraction of X-rays by crystals- Bragg’s law, powder diffraction method, Laue and rotating crystal methods, atomic and structure factor, systematic absences due to lattice types, determination of crystal structure and applications.           

Lattice dynamics: Introduction, elastic waves, lattice vibrations and phonons, dynamics of linear monoatomic lattice, symmetry in k-space, number of modes in one dimensional lattice, dynamics of diatomic lattice, acoustical and optical phonons, density of states for a three dimensional solid.                

Unit-3
Teaching Hours:17
Properties of solids
 

Specific heat of solids: Dulong and Petit’s law, Einstein’s and Debye’s theories of specific heat of solids, T3 law.

Magnetic properties of matter: Classification of magnetic materials–dia-, para-, ferro- and ferri-magnetic materials, classical Langevin’s theory of diamagnetism and paramagnetism, Curie’s law, Weiss’s theory of ferromagnetism and ferromagnetic domains, discussion of BH curve, hysteresis and energy loss.

Dielectric properties of matter: Dipole moment and polarization, electric field of a dipole, local electric field at an atom, dielectric constant and its measurement, polarizability, Clausius-Mossotti equation, electronic polarizability, classical theory of electronic polarizability, dipolar polarizability, applications.       

Ferroelectric Properties of Materials:Structural phase transition, Classification of crystals, Piezoelectric effect, Pyroelectric effect, Ferroelectric effect, Electrostrictive effect, Curie-Weiss Law, Ferroelectric domains, PE hysteresis loop.

Unit-3
Teaching Hours:17
Properties of solids
 

Specific heat of solids: Dulong and Petit’s law, Einstein’s and Debye’s theories of specific heat of solids, T3 law.

Magnetic properties of matter: Classification of magnetic materials–dia-, para-, ferro- and ferri-magnetic materials, classical Langevin’s theory of diamagnetism and paramagnetism, Curie’s law, Weiss’s theory of ferromagnetism and ferromagnetic domains, discussion of BH curve, hysteresis and energy loss.

Dielectric properties of matter: Dipole moment and polarization, electric field of a dipole, local electric field at an atom, dielectric constant and its measurement, polarizability, Clausius-Mossotti equation, electronic polarizability, classical theory of electronic polarizability, dipolar polarizability, applications.       

Ferroelectric Properties of Materials:Structural phase transition, Classification of crystals, Piezoelectric effect, Pyroelectric effect, Ferroelectric effect, Electrostrictive effect, Curie-Weiss Law, Ferroelectric domains, PE hysteresis loop.

Text Books And Reference Books:

[1]. Kittel, C. (1996). Introduction to solid state physics, New York: Wiley.

[2]. Wahab, M. A. (2011). Solid state physics, New Delhi: Narosa Publications.

[3]. Ali Omar, M. (1999). Elementary solid-state physics, New Delhi: Addison-Wesley Publishing Company.

[4]. Srivastava, J. P. (2006). Elements of solid-state physics (2nd ed.). New Delhi: Prentice Hall of India, Pvt Ltd.

Essential Reading / Recommended Reading

[5]. Azaroff, L. V. (2004). Introduction to solids, New Delhi: Tata Mc-Graw Hill.

[6]. Ashcroft, N. W. & Mermin, N. D. (2014). Solid state physics, New Delhi: Cengage Learning India Pvt Ltd. 

[7]. Ibach, H., & Luth, H. (2009). Solid state physics, Berlin Heidelberg: Springer-Verlag.

Evaluation Pattern

 

 

 

No.

Component

Schedule

Duration

Marks

CIA 1

Assignment/test/group task/presentation

Before MSE

 

--

10

CIA 2

Mid Semester Examination (MSE) Centralised

MSE

 2 hours

(50 marks)

25

CIA 3

Assignment/test/group task/presentation

After MSE

--

10

Attendance

75 – 79: 1 mark, 80 – 84: 2 marks, 85 – 89: 3 marks, 90 – 94: 4

marks, 95 – 100: 5 marks

05

ESE

Centralised

3 hours

(100 marks)

50

 

Total

100

 

PHY641B - QUANTUM MECHANICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This course is an elective paper which gives students an option to learn about additional topics in quantum mechanics. Students are introduced to the applications of time-independent and time-independent Schrodinger wave equations to bound systems such as hydrogen atom.

Learning Outcome

CO1: Explain the development of quantum theory and its real applications in physics.

CO2: Appreciate the significance of Schrodinger equations in the dynamics of bound systems.

CO3: Illustrate the role of operators and their connection with observables, and uncertainty.

CO4: Acquire knowledge on spin, angular momentum states, and angular momentum addition rules

Unit-1
Teaching Hours:15
Basics of quantum mechanics
 

Linear operators, Hermitian operators; eigenfunctions and eigenvalues, orthonormalization, completeness; physical interpretation of wave function, admissible conditions on wave functions and the principle of superposition; Position, momentum, Hamiltonian and energy operators, commutation relations, Schrodinger equation – time-dependent and time-independent Schrodinger wave equation. Probability density and probability current density; expectation value, Ehrenfest theorem; basic postulates of quantum mechanics.                                                                   

Unit-1
Teaching Hours:15
Basics of quantum mechanics
 

Linear operators, Hermitian operators; eigenfunctions and eigenvalues, orthonormalization, completeness; physical interpretation of wave function, admissible conditions on wave functions and the principle of superposition; Position, momentum, Hamiltonian and energy operators, commutation relations, Schrodinger equation – time-dependent and time-independent Schrodinger wave equation. Probability density and probability current density; expectation value, Ehrenfest theorem; basic postulates of quantum mechanics.                                                                   

Unit-2
Teaching Hours:15
Simple applications of time independent Schrodinger wave equation
 

General discussion of bound states in an arbitrary potential- continuity of wave function, boundary condition, Particle in a potential box of infinite height – one and three dimensional, eigenvalues and eigenfunctions (with the derivation of expression for energy), degeneracy, the density of states; Potential barrier transmission– transmission and reflection coefficients for E<V0 and E>V0; Simple harmonic oscillator – energy levels, eigenvalues and eigenfunctions using Frobenius method, Hermite polynomials, ground state, zero-point energy.  

Unit-2
Teaching Hours:15
Simple applications of time independent Schrodinger wave equation
 

General discussion of bound states in an arbitrary potential- continuity of wave function, boundary condition, Particle in a potential box of infinite height – one and three dimensional, eigenvalues and eigenfunctions (with the derivation of expression for energy), degeneracy, the density of states; Potential barrier transmission– transmission and reflection coefficients for E<V0 and E>V0; Simple harmonic oscillator – energy levels, eigenvalues and eigenfunctions using Frobenius method, Hermite polynomials, ground state, zero-point energy.  

Unit-3
Teaching Hours:15
Quantum theory of hydrogen atom
 

Angular momentum – expressions for cartesian components and square of (orbital) angular momentum; operators and their commutation relations, eigenvalues and eigenfunctions in polar coordinates, eigenvalues and eigenfunctions of L2 and Lz.

Hydrogen atom: Central potential, time-independent Schrodinger equation in spherical polar coordinates; separation of variables for second-order partial differential equation; principal, orbital and magnetic quantum numbers – n, l, ml; Energy eigenvalues, Radial wave function R(r). Electron probability density – radial and angular variations; shapes of the probability density for ground and first excited states; s, p, d,….shells.

Unit-3
Teaching Hours:15
Quantum theory of hydrogen atom
 

Angular momentum – expressions for cartesian components and square of (orbital) angular momentum; operators and their commutation relations, eigenvalues and eigenfunctions in polar coordinates, eigenvalues and eigenfunctions of L2 and Lz.

Hydrogen atom: Central potential, time-independent Schrodinger equation in spherical polar coordinates; separation of variables for second-order partial differential equation; principal, orbital and magnetic quantum numbers – n, l, ml; Energy eigenvalues, Radial wave function R(r). Electron probability density – radial and angular variations; shapes of the probability density for ground and first excited states; s, p, d,….shells.

Text Books And Reference Books:

[1].A. Beiser, Perspectives of Modern Physics, McGraw-Hill, 1968.

[2].R. Eisberg and R. Resnick, Quantum Mechanics, 2ndEdn., Wiley, 2002. 

[3].G. Aruldhas, Quantum Mechanics, 2ndEdn., PHI Learning of India, 2002.

[4].D. J. Griffith, Introduction to Quantum Mechanics, 2ndEdn., Pearson Education, 2005. 

[5].W. Greiner, Quantum Mechanics, 4thEdn., Springer, 2001. 

Essential Reading / Recommended Reading

[1]B. C. Reed, Quantum Mechanics, Jones and Bartlett Learning, 2008. 

[2].A. Bohm, Quantum Mechanics: Foundations and Applications, 3rdEdn., Springer, 1993. 

[3].D. A. B. Miller, Quantum Mechanics for Scientists and Engineers, Cambridge University Press, 2008.

Evaluation Pattern

Evaluation Pattern

 

No.

Components

Marks

CIA 1

Written test on descriptive answers

10

CIA2

Centralized Mid Sem Examination

25

CIA 3

Quiz, MCQ test, presentation, minor project, MOOC

10

Attendance

 Regularity and Puntuality

05

ESE

Centralized End Sem Examination

50

Total

100

PHY641C - NUCLEAR AND PARTICLE PHYSICS (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This course has been conceptualized in order to give students an exposure to the fundamentals of nuclear and particle physics. Students will be introduced to the new ideas such as properties and structure of nucleus, interaction of nuclear radiations with matter and the principles behind working of radiation detectors, fundamental particles and their interactions, particle accelerators. Unit II caters to regional and national needs.

Learning Outcome

CO1: Acquiring the knowledge of basics of nuclear physics, which enables them to use it for understanding the structure and properties of nucleus

CO2: Able to understand the nuclear interactions with matter and applications of nuclear radiations.

CO3: Able to acquire working knowledge of radiation detectors.

Unit-1
Teaching Hours:15
Properties and Structure of Nucleus
 

Properties of nucleus: Constituents of nucleus and their intrinsic properties, quantitative facts about size, mass, charge density, matter density, binding energy, average binding energy and its variation with mass number, main features of binding energy versus mass number curve.

Nuclear models: Liquid drop model of nucleus, semi-empirical mass formula, binding energy expression and significance of various terms in it. Fermi gas model - degenerate fermi gas, Fermi energy, fermi momentum, total energy of nucleus, role of asymmetry energy in the stability of a nucleus. Nuclear shell model - basic assumptions of shell model, concept of mean field, residual interaction, evidence for nuclear shell structure, nuclear magic numbers, concept of nuclear force, its characteristics and experimental evidence (qualitative).

Unit-1
Teaching Hours:15
Properties and Structure of Nucleus
 

Properties of nucleus: Constituents of nucleus and their intrinsic properties, quantitative facts about size, mass, charge density, matter density, binding energy, average binding energy and its variation with mass number, main features of binding energy versus mass number curve.

Nuclear models: Liquid drop model of nucleus, semi-empirical mass formula, binding energy expression and significance of various terms in it. Fermi gas model - degenerate fermi gas, Fermi energy, fermi momentum, total energy of nucleus, role of asymmetry energy in the stability of a nucleus. Nuclear shell model - basic assumptions of shell model, concept of mean field, residual interaction, evidence for nuclear shell structure, nuclear magic numbers, concept of nuclear force, its characteristics and experimental evidence (qualitative).

Unit-2
Teaching Hours:15
Interaction of Nuclear Radiations with Matter and Detectors
 

Interaction of nuclear radiations with matter: Interaction of heavy charged particles with matter - energy loss due to ionization and excitation (Bethe-Bloch formula). Interaction of light charged particles with matter - range, energy loss of light charged particles, range energy relation for beta particles, mass absorption coefficient for beta particles. Interaction of γ-rays with matter - Photoelectric effect, Compton scattering, Pair production and their interaction cross sections, linear and mass attenuation coefficients.

Detectors: Gas detectors - estimation of electric field, mobility of particle, construction and working of ionization chamber and GM Counter. Basic principle, construction and working of scintillation detectors, types of scintillators and their properties. Semiconductor detectors (Si(Li) &amp; Ge(Li)) - for charge particle and photon detection, concept of charge carrier and mobility, construction and working.

Unit-2
Teaching Hours:15
Interaction of Nuclear Radiations with Matter and Detectors
 

Interaction of nuclear radiations with matter: Interaction of heavy charged particles with matter - energy loss due to ionization and excitation (Bethe-Bloch formula). Interaction of light charged particles with matter - range, energy loss of light charged particles, range energy relation for beta particles, mass absorption coefficient for beta particles. Interaction of γ-rays with matter - Photoelectric effect, Compton scattering, Pair production and their interaction cross sections, linear and mass attenuation coefficients.

Detectors: Gas detectors - estimation of electric field, mobility of particle, construction and working of ionization chamber and GM Counter. Basic principle, construction and working of scintillation detectors, types of scintillators and their properties. Semiconductor detectors (Si(Li) &amp; Ge(Li)) - for charge particle and photon detection, concept of charge carrier and mobility, construction and working.

Unit-3
Teaching Hours:15
Elementary particles and accelerators
 

Elementary particles: Production and properties of π, µ and K mesons, types of particle interactions, types of elementary particles and their families, classifications based on spin and type of interactions, Symmetries and conservation laws - energy, linear momentum, angular momentum, charge, parity, baryon number, lepton number, isospin, strangeness, Concept of quark model - types of quarks and their properties, color quantum number and gluons.

Particle accelerators: Van-de Graaff generator (Tandem accelerator), Linear accelerator, Cyclotron (principle, construction and working), Accelerator facility available in India.

Unit-3
Teaching Hours:15
Elementary particles and accelerators
 

Elementary particles: Production and properties of π, µ and K mesons, types of particle interactions, types of elementary particles and their families, classifications based on spin and type of interactions, Symmetries and conservation laws - energy, linear momentum, angular momentum, charge, parity, baryon number, lepton number, isospin, strangeness, Concept of quark model - types of quarks and their properties, color quantum number and gluons.

Particle accelerators: Van-de Graaff generator (Tandem accelerator), Linear accelerator, Cyclotron (principle, construction and working), Accelerator facility available in India.

Text Books And Reference Books:

[1]. Krane, K. S. (2008). Introductory nuclear physics. New York: Wiley India Pvt. Ltd.

[2]. Griffith, D. (2008). Introduction to elementary particles (2 nd ed.). Weinheim: John Wiley & Sons.

[3]. Goshal, S. N. (2005). Nuclear physics. New Delhi: Chand & Co.

[4]. Heyde, K. (2004). Basic ideas and concepts in nuclear physics - An introductory approach (3 rd ed.). Philadelphia, USA: Institute of Physics Publishing, CRC Press.

[5]. Knoll, G. F. (2000). Radiation detection and measurement. New York, NY: John Wiley and Sons.

[6]. Cohen, B. L. (1998). Concepts of nuclear physics. New York, NY: Tata McGraw Hill.

Essential Reading / Recommended Reading

[7]. Dunlap, R. A. (2004). Introduction to the physics of nuclei and particles (1 st ed.). Belmont CA, USA: Thomson/Brooks-Cole.

[8]. Blatt, J. M., &amp; Weisskopf, V. F. (1991). Theoretical nuclear physics. New York, NY: Dover Publishing Inc.

[9]. Halzen, F., &amp; Martin, A. D. (1984). Quarks and leptons. New Delhi: Wiley India.

Evaluation Pattern

No.

Components

Marks

CIA 1

Written test on descriptive answers

10

CIA2

Centralized Mid Sem Examination

25

CIA 3

Quiz, MCQ test, presentation, minor project, MOOC

10

Attendance

 Regularity and Puntuality

05

ESE

Centralized End Sem Examination

50

Total

100

PHY651 - MODERN PHYSICS - II LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Experiments related to molecules, solid state physics and nuclear physics included in this course provides a better understanding of the theory.

Learning Outcome

CO1: Develop better clarity of the theory through the respective experiments.

CO2: Enhance the analytical and interpretation skills.

Unit-1
Teaching Hours:30
List of experiments
 

      1.      To determine the absorption lines in the rotational spectrum of Iodine vapour.

2.      Analysis of molecular spectra - rotational-vibrational.

3.      Resistivity of a material by four probe technique.

4.      Determination of thermal conductivity of a material.

5.      Determination of energy gap of a semiconductor

6.      Spectral response of a selenium photo cell (λ vs. I)

7.      Hall effect – determination of carrier concentration in a semiconductor/metal

8.      Demonstration experiment: Magnetic levitation by a superconductor

      9.      Verification of inverse square law (applicable to intensity of gamma rays emitted by a radioactive substance) using a GM counter.

     10.  Characteristics of a Geiger – Muller (GM) counter.

      11.  Analysis of rotational Raman spectrum 

Unit-1
Teaching Hours:30
List of experiments
 

      1.      To determine the absorption lines in the rotational spectrum of Iodine vapour.

2.      Analysis of molecular spectra - rotational-vibrational.

3.      Resistivity of a material by four probe technique.

4.      Determination of thermal conductivity of a material.

5.      Determination of energy gap of a semiconductor

6.      Spectral response of a selenium photo cell (λ vs. I)

7.      Hall effect – determination of carrier concentration in a semiconductor/metal

8.      Demonstration experiment: Magnetic levitation by a superconductor

      9.      Verification of inverse square law (applicable to intensity of gamma rays emitted by a radioactive substance) using a GM counter.

     10.  Characteristics of a Geiger – Muller (GM) counter.

      11.  Analysis of rotational Raman spectrum 

Text Books And Reference Books:

1.      Physics Laboratory – I ,  PHE -03 (L)  Indira Gandhi National Open  University  School of Sciences.

2.      A Lab manual of Physics for undergraduate classes, Vani Publications, New Delhi, 2002.

3.      Advanced course in practical physics,Chattopadhyay, Rakshit and Saha, New Central Publishers, Kolkota, 2000.

4.      Advanced Practical Physics,S PSingh, Pragati Prakasan Publishing Company,  2010.

 

Essential Reading / Recommended Reading

1.      Advanced Practical Physics,Worsnop and Flint, Methuen & Co., Prentice Hall of  India Third edition, Pearson Education, 2005.

2.      Physics through experiments,B. Saraf, Vikas Publishing House, New Delhi, 1992.

Evaluation Pattern

 

 

Component

Duration

Marks

CIA

Class work, Prelab assignment, MST

 

30

ESE

Experiment and viva voce

3 hours

 

20

Total

50

 

 

 

PHY651A - SOLID STATE PHYSICS LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:02

Course Objectives/Course Description

 

Experiments related to solid state physics and elementary properties provide a better understanding of the theory. 

  •  

Learning Outcome

CO1: Develop a better understanding of fundamentals of X-ray crystallography through diffraction experiments.

CO2: Enhance their analytical and interpretation skills.

CO3: Estimate the dielectric and magnetic properties of solids.

Unit-1
Teaching Hours:30
List of experiments
 
  1. Calculation of structure factors of typical crystal structures (NaCl and KCl). 

  2. Verification of Moseley’s law 

  3. X-ray analysis of the powder photograph of copper 

  4. Characteristics of LDR.  

  5. Determination of specific heat of a metal.  

  6. Determination of dielectric constant 

  7. X-ray analysis of tungsten powder photograph 

  8. Electrical and thermal conductivity of copper 

  9. Electrical conductivity of glass 

  10. Determination of paramagnetic susceptibility – Quinke’s method  

  11. BH curve of iron using a solenoid and determination of energy loss from hysteresis

Unit-1
Teaching Hours:30
List of experiments
 
  1. Calculation of structure factors of typical crystal structures (NaCl and KCl). 

  2. Verification of Moseley’s law 

  3. X-ray analysis of the powder photograph of copper 

  4. Characteristics of LDR.  

  5. Determination of specific heat of a metal.  

  6. Determination of dielectric constant 

  7. X-ray analysis of tungsten powder photograph 

  8. Electrical and thermal conductivity of copper 

  9. Electrical conductivity of glass 

  10. Determination of paramagnetic susceptibility – Quinke’s method  

  11. BH curve of iron using a solenoid and determination of energy loss from hysteresis

Text Books And Reference Books:

[1]. Advanced Practical Physics, Worsnop and Flint, Methuen & Co., Prentice Hall of India Third Edition, Pearson Education, 2005.

[2]. Physics through experiments, B. Saraf, Vikas Publishing House, New Delhi, 1992.

Essential Reading / Recommended Reading

[3]. Physics Laboratory – I, PHE -03 (L) Indira Gandhi National Open University School of Sciences.

[4]. A Lab manual of Physics for undergraduate classes, Vani Publications, New Delhi, 2002.

[5]. Advanced course in practical physics, Chattopadhyay, Rakshit and Saha, New Central Publishers, Kolkata, 2000.

[6]. Advanced Practical Physics, S. P. Singh, Pragati Prakasan Publishing Company, 2010.

Evaluation Pattern

Continuous Internal Assessment (CIA) 60%,   End Semester Examination (ESE) 40%

No

Components

Duration

Marks

CIA 1

Pre-lab assessment

Preparation for performing experiment -writing principle, procedure, tabular column, understanding the experiment, etc

 

10

CIA 2

MSE

Examination in which principle, procedure, formula, diagram, tabular column, performance of the experiment and viva are assessed

 

10

CIA 3

Post-lab assessment

Completion of the experiment with accuracy

 

10

ESE

Centralized examination in which principle, procedure, formula, diagram, tabular column, performance of the experiment, calculation, viva and understanding of the experiment are assessed

3 hours

 

20

 

 

Total

50

PHY651B - QUANTUM MECHANICS LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

The objective of this module is to introduce the students to problem solving skills on various topics in quantum mechanics. 

Learning Outcome

CO1: Demonstrate the skills of problem solving and understand the concepts clearly.

CO2: Develop the ability to write programs in python language.

Unit-1
Teaching Hours:30
List of exercises/experiments
 

1. Black body radiation – Graphical study of black body radiation curve - Rayleigh-Jeans and Wien’s displacement laws.

2. Particle in a 1D box – Graphical study of wavefunctions and probability densities.

3. Quantum harmonic oscillator – Graphical study of wavefunctions, probability densities and spacing of energy levels.

4. Potential barrier penetration – Graphical study of Reflection and transmission coefficients.

5. Hydrogen atom – Graphical study of radial wavefunctions and probability densities.

6. Non-interacting particles in an infinite square well: Study of energy states of the system.

7. Potential step - Graphical study of reflection and transmission coefficients

8. Problem solving-1.

9. Problem solving-2

Unit-1
Teaching Hours:30
List of exercises/experiments
 

1. Black body radiation – Graphical study of black body radiation curve - Rayleigh-Jeans and Wien’s displacement laws.

2. Particle in a 1D box – Graphical study of wavefunctions and probability densities.

3. Quantum harmonic oscillator – Graphical study of wavefunctions, probability densities and spacing of energy levels.

4. Potential barrier penetration – Graphical study of Reflection and transmission coefficients.

5. Hydrogen atom – Graphical study of radial wavefunctions and probability densities.

6. Non-interacting particles in an infinite square well: Study of energy states of the system.

7. Potential step - Graphical study of reflection and transmission coefficients

8. Problem solving-1.

9. Problem solving-2

Text Books And Reference Books:

[1].A. Beiser, Perspectives of Modern Physics, McGraw-Hill, 1968.

 

[2].R. Eisberg and R. Resnick, Quantum Mechanics, 2nd Edn., Wiley, 2002. 

 

[3].G. Aruldhas, Quantum Mechanics, 2nd Edn., PHI Learning of India, 2002.

Essential Reading / Recommended Reading

[1] D. A. B. Miller, Quantum Mechanics for Scientists and Engineers, Cambridge University Press, 2008. 

[2].D. J. Griffith, Introduction to Quantum Mechanics, 2nd Ed., Pearson Education, 2005.

[3].G. L. Squires, Problems in Quantum Mechanics with Solutions, Cambridge University Press, 2002. 

Evaluation Pattern

 

Evaluation Pattern

 

 

Component

Duration

Marks

CIA

Class work, Prelab assignment, MST

 

30

ESE

Experiment and viva voce

3 hours

 

20

                                                               Total

50

Minimum of 75 per cent of the allotted experiments should be completed by each student to be eligible to attend practical ESE. The fair record of each experiment is to be attested by the lab faculty in-charge in the same week.  

 

PHY651C - NUCLEAR AND PARTICLE PHYSICS LAB (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

 

Students are expected to learn the topics such as binding energy, mass absorption coefficient for beta rays, mass attenuation coefficients for gamma rays, working of GM counter, NaI(Tl) and CdTe detectors. 

Learning Outcome

CO1: A better understanding of the theory through the respective experiments.

CO2: Hands-on experience of working with detector spectrometers.

CO3: Analytical and interpretation skills.

Unit-1
Teaching Hours:30
NUCLEAR PHYSICS-LAB
 

1. Computation of binding energy of nuclei.

2. Mass absorption coefficient for beta particles in copper using GM counter. 

3. Range and end point energy of beta particles in aluminum. 

4. Mass attenuation coefficient of gamma rays in lead using GM counter.

5. Resolution of NaI(Tl) detector spectrometer.

6. Computation of energy loss for protons and alpha particles in aluminum and lead.

7. Calibration of NaI(Tl) detector spectrometer.

8. Demonstration of working of CdTe X-ray detector spectrometer.

Unit-1
Teaching Hours:30
NUCLEAR PHYSICS-LAB
 

1. Computation of binding energy of nuclei.

2. Mass absorption coefficient for beta particles in copper using GM counter. 

3. Range and end point energy of beta particles in aluminum. 

4. Mass attenuation coefficient of gamma rays in lead using GM counter.

5. Resolution of NaI(Tl) detector spectrometer.

6. Computation of energy loss for protons and alpha particles in aluminum and lead.

7. Calibration of NaI(Tl) detector spectrometer.

8. Demonstration of working of CdTe X-ray detector spectrometer.

Text Books And Reference Books:

[1] Goshal, S. N. (2005). Nuclear physics. New Delhi: Chand & Co.

[2].Knoll, G. F. (2000). Radiation detection and measurement. New York, NY: John Wiley and Sons.

Essential Reading / Recommended Reading

[1].Kapoor, S. S. and Ramamurthy, V. S. (2012). Nuclear radiation detectors. New Delhi: New Age International Publishers. 

[2].Krane, K. S. (2008). Introductory nuclear physics. New York: Wiley India Pvt. Ltd.

Evaluation Pattern

Student will be evaluated based on

1. whether a student has come prepared for the practical such drawing experimental diagram, tabular column, formulae etc.

2. whether the student is able to complete the experiments and do the calculations during allotted hours.

3. viva on the experiments performed.

Evaluation Pattern

 

 

Component

Duration

Marks

CIA

Class work, Prelab assignment, MST

 

30

ESE

Experiment and viva voce

3 hours

 

20

                                                                                   Total

50