A copy of this is kept by the head of department, faculty advisor/supervisor and the student. It is assessed by the department committee consisting of the head of department, seminar supervisor and a leading faculty member.
The semester grade point average (SGPA) is calculated by dividing the sum of credit points (CP) secured from all subjects/ courses registered in a semester, by the total
The student will be required to re-appear as a "supplementary student" in the end-of-semester examination as and when available. The corresponding 'credit points' (CP) are calculated by multiplying the grade by the credit points for the particular subject/.
For merit ranking or comparison purposes or any other listing, only the ‘rounded off’
For calculations listed in regulations 9.6 to 9.9, performance in failed subjects/ courses (securing F grade) will also be taken into account, and the credits of such subjects/
Passing standards
After the completion of each semester, a grade card or grade sheet (or transcript) shall be issued to all the registered students of that semester, indicating the letter grades and
Declaration of results
Withholding of results
Transitory regulations
The maximum number of points that a student obtains for the award of the examination is the sum of the total number of points secured in all his/her study programs, including the R16 regulation. Note: If a student readmitted to the R16 regulations has not studied any subjects/subjects in his/her previous study regulations which are prerequisites for additional subjects in the R16 regulations, the concerned principals must hold remedial classes to cover these subjects/subjects for the benefit of the students.
Student transfers
A student in the R09/R13/R15 regulations who has been held back for lack of credit shall be promoted to the next semester of the R16 regulations only after obtaining the required points according to the corresponding regulations for his/her first admission . If a student readmitted to the R16 regulations has a subject with 80% of the syllabus in common with his/her previous regulations, that subject in the R16 regulations will be replaced by another subject proposed by the University.
Scope
The student must register for 144 marks and secure 144 marks with CGPA ≥ 5 from II year to IV year B.Tech. The students who do not fulfill the requirement for the award of the degree for six academic years from the year of admission will lose their place in B.Tech.
Promotion rule
Expulsion from the examination room and cancellation of the performance in the relevant subject only of all students involved. Students from upper secondary schools, expulsion from the examination hall and cancellation of the performance in the subject in question and everything else.
No Course
Open Electives - Students should only take open electives from the list of open electives offered by other departments/branches. Example: - A mechanical engineering student can take Open Electives from all other departments/branches except Open Electives offered by the Mechanical Department.
TECH. III AND IV YEARS S
Computer Assisted Language Learning (CALL) Lab
To provide hands-on experience in the use of various engineering materials, tools, equipment and processes that are common in the engineering field. It explains the construction, operation, use and application of various work tools, equipment and machinery.
TRADES FOR EXERCISES
Identify and use marking tools, hand tools, measuring equipment and to work to prescribed tolerances. Practice manufacturing components using workshop trades including plumbing, tailoring, carpentry, foundry, home wiring and welding.
TRADES FOR DEMONSTRATION and EXPOSURE
Sections and developments: Sectional views of real regular solids – Prism, Cylinder, Pyramid, Cone – Auxiliary views. Isometric & Orthographic Projections: Principles of Isometric Projection – Isometric Scale – Isometric Views – Conventions – Isometric Views of Lines, Plane Figures, Simple Solids – Conversion of Isometric Views to Orthographic Views.
To understand the basic concepts like Abstract Data Types, Linear and Non-linear Data Structures. To understand the behavior of data structures such as stacks, rows, trees, hash tables, search trees, graphs and their representations. To learn to implement ADTs like lists, stacks, queues, trees, graphs, search trees in C++ to solve problems.
Ability to design programs using a variety of data structures such as stacks, queues, hash tables, binary trees, search trees, heaps, graphs and trees B. Basic Concepts - Data Objects and Structures, Algorithm Specification-Introduction, Algorithms recursive, Data abstraction, Performance analysis- time complexity and space complexity, Asymptotic notation- Big O, Omega and Theta notations, Examples of complexity analysis, Introduction to Linear data and Non structures. Java Complete Reference, 9th Edition, Herbert Schildt, McGraw Hill Education (India) Pvt. Ltd. 2. Understanding Object-Oriented Programming with Java, Updated Edition, T. Budd, Pearson Education.
Write and run programs in C++ to solve problems using data structures such as arrays, linked lists, stacks, queues, trees, graphs, hash tables, and search trees. Able to implement data structures such as stacks, queues, search trees and hash tables to solve various computing problems. Write a C++ program that implements the Insertion sort algorithm to arrange a list of integers in ascending order.
Write a C++ program that implements Insertion sort algorithm to arrange a list of integers in ascending order
Write a template-based C++ program that implements selection sort algorithm to arrange a list of elements in descending order. Write a template-based C++ program that implements a quicksort algorithm to arrange a list of elements in ascending order. Write a C++ program that implements Heap sort algorithm for sorting a list of integers in ascending order.
Write a C++ program that implements the Merge sort algorithm for sorting a list of integers in ascending order. To get acquainted with a personal computer and its basic peripherals, the process of assembling a personal computer, installation of system software such as MS Windows, Linux and required device drivers, the troubleshooting process at the hardware and software level. To introduce connecting the PC to the Internet from home and workplace and the effective use of the Internet, use of web browsers, e-mail, newsgroups and discussion forums.
To gain knowledge in cyber hygiene awareness, i.e. protecting personal computer from infection by viruses, worms and other cyber attacks. To introduce the use of productivity tools in the design of professional Word documents, Excel spreadsheets and power point presentations using open office tools and LaTeX. Draw the block diagram of the CPU along with the configuration of each peripheral and submit it to your instructor.
Hardware Troubleshooting: Students have to be given a PC which does not boot due to improper assembly or defective peripherals. They should identify the problem and fix
The IT Workshop is a training lab to receive training in the field of PC Hardware, Internet &. PC Hardware: The students have to work on a working PC, disassemble and assemble it to working condition and install an operating system like Linux or other on the same PC.
Software Troubleshooting: Students have to be given a malfunctioning CPU due to system software problems. They should identify the problem and fix it to get the computer
Creating Power Point: Student should work on basic power point utilities and tools in Latex and Ms Office/equivalent (FOSS) which help them create basic power point
Course management system (CMS)
A course management system (CMS) is a collection of software tools that provide an online environment for course interactions. An integrated email tool that allows participants to send announcement email messages to the entire class or to a subset of the entire class. In addition, a CMS is typically integrated with other databases at the university, so that students enrolled in a particular course are automatically registered in the CMS as participants in that course.
The Course Management System (CMS) is a web application that allows department staff, Academic Senate and Registrar staff to view, enter and manage course information previously submitted via paper. Departments can use CMS to create new course proposals, submit changes to existing courses, and track the progress of proposals as they move through the stages of online approval.
Easy Leave
Client-side Scripting: Introduction to Javascript: Javascript language - declaring variables, variable scope, functions, event handlers (onclick, onsubmit etc.), Document Object Model, Form Validation. Introduction to UML: Importance of Modeling, Principles of Modeling, Object Oriented Modeling, Conceptual Model of the UML, Architecture, Software Development Life Cycle. Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design and Unified Process, Craig Larman, Pearson Education.
Introduction to Analytics and R Programming (NOS 2101): Introduction to R, R Studio (GUI): R Windows environment, introduction to different data types, numeric, character, date, data frame, array, matrix etc., reading datasets, working with different file types .txt, . Working effectively with colleagues (NOS 9002): Introduction to effective working, teamwork, professionalism, effective communication skills, etc. Introduction to probability and statistics Using R, ISBN, a textbook has been written for a bachelor's degree program in probability and statistics.
Database – Introduction to SQLite database, creating and opening a database, creating tables, inserting, retrieving and deleting data, registering content providers, using content providers (insert, delete, retrieve and update). File and exceptions: Introduction to file input and output, Using loops to process files, Processing records, Exceptions. Signals – Introduction to signals, signal generation and processing, kernel support for signals, signaling function, unreliable signals, reliable signals, kill, raise, alarm, pause, abort, sleep functions.
Active Inquiry Learning An introduction to information theory, decision trees, cross-validation and fitting. Big Data Tools (NOS 2101): Introduction to Big Data tools like Hadoop, Spark, Impala, etc., Data ETL process, identifying data gaps and follow-up for decision making.
COMMERCE
Introduction to Web Services – Definition of web services, basic operational model of web services, tools and technologies that enable web services, benefits and challenges of using web services. Web Services Description – WSDL – WSDL in the world of Web Services, Web Services life cycle, anatomy of the WSDL definition document, WSDL bindings, WSDL Tools, WSDL limitations. Write a C program (sender.c) to create a message queue with read and write permission to write 3 messages to it with different priority numbers.
Big Data: What is Big Data, History of Data Management; Big data structuring; Elements of big data; Big data analysis; Distributed and parallel computing for big data;. Big Data Analytics: What Big Data Analytics Is, What Big Data Analytics Is Not, Why the Sudden Buzz About Big Data Analytics, Analytics Classification, Biggest Challenges Holding Back Business capitalize on big data; The main challenges facing big data; Why Big Data Analytics is Important; Data Science; Data Scientist; Terminologies used in big data environments; eventual consistency of the basically available soft state (BASE); Open source analytics tools;. Understanding analytics and big data: Comparison of reporting and analysis, types of analytics; Points to consider during the analysis; Development of an analytical team; Understanding text analysis;.
Techniques for optimizing MapReduce jobs; Using MapReduce; Role of HBase in Big Data Processing; Data Storage in Hadoop : HDFS Introduction, Architecture, HDFC Files, File System Types, Commands, org.apache.hadoop.io Package, HDF, HDFS High Availability;. Introducing HBase, architecture, storing big data with HBase, interacting with the Hadoop ecosystem; HBase in Operational Programming with HBase; Installation, aggregation of HBase and HDFS;. The Semantic Web and Semantic Web Services - Liyang Lu Chapman and Hall/CRC Publishers, (Taylor & Francis Group).
