This document outlines the syllabus for the B.Tech Information Technology program at Uttar Pradesh Technical University for the second year.
It includes the study and evaluation scheme for semesters 3 and 4. Semester 3 covers subjects like Mathematics III, Digital Logic Design, Data Structures Using C, Discrete Structures and Graph Theory, and Industrial Psychology/Sociology. It also lists the practical labs associated with these subjects.
Similarly, semester 4 covers subjects such as Science Based Open Elective, Information Theory and Coding, Operating Systems, Theory of Automata and Formal Languages, and Multimedia and Animation. It also includes the practical labs for these subjects.
The document provides the course codes
This document provides a syllabus for a Bachelor in Computer Application (BCA) degree program. It outlines the courses, subjects, and papers for each of the six semesters. The first semester includes courses in mathematics, English, basic electronics, computer fundamentals, and programming techniques with C programming. The second semester covers additional topics in mathematics, computer organization/architecture, data structures in C, digital electronics, and discrete mathematics. Subsequent semesters cover operating systems, probability/statistics, data processing, numerical analysis, computer graphics, databases, networking, and software engineering among other topics. Exams are 3 hours in duration and include both theory and practical papers. Recommended textbooks are provided for each subject.
This document provides the scheme and syllabus for the integrated B.E. MBA (Computer Science and Engineering) program at the University Institute of Engineering and Technology, Panjab University, Chandigarh for the academic year 2013-2014. It outlines the coursework, credits, exams and assessments for each semester of the 5-year program spanning the third through tenth semesters. The document includes details of the subjects covered, teaching schemes, credits awarded and exam structures for both the B.E. and MBA portions of the integrated program.
This document outlines the study and evaluation scheme for a Master of Technology degree in Computer Science/Information Technology at UPTU.
It provides the course codes, subjects, theory/tutorial/lab periods, and evaluation schemes for each semester. In semester 1, there are 4 core courses covering foundations of computer science, computer organization/architecture, operating systems, and data networks. Each has theory, tutorial, and lab components, with internal assessments worth 30-50 marks and end semester exams worth 100-150 marks.
Semester 2 covers 4 elective courses, with similar evaluation schemes. Semesters 3 and 4 include electives, a professional aspects course, seminar, and dissertation work. Evaluation includes internal and
The document provides details of the syllabus for the third semester B.Sc. Information Technology course at the University of Mumbai. It includes information on 5 theory courses - Logic and Discrete Mathematics, Computer Graphics, Advanced SQL, Object Oriented Programming with C++, and Modern Operating Systems. For each theory course, it lists the course code, number of lectures per week, unit topics, expected learning outcomes and reference books. It also provides details of the corresponding practical/lab courses including expected experiments and assignments.
This document provides a syllabus for a B.E. Computer Engineering program from 2012-2015 at Savitribai Phule Pune University. The syllabus aims to blend concepts and advances using open-source technologies. It includes 16 electives in areas like cloud computing, mobile computing, web applications, and cyber security. Laboratory courses focus on utilizing state-of-the-art open-source software. The program objectives are to expose students to computer systems and applications, provide conceptual and interdisciplinary knowledge, and develop professional skills for the IT industry.
Creating a dataset of peer review in computer science conferences published b...Aliaksandr Birukou
Computer science (CS) as a field is characterised by higher publication numbers and prestige of conference proceedings as opposed to scholarly journal articles. In this presentation we present preliminary results of the extraction and analysis of peer review information from computer science conferences published by Springer in almost 10,000 proceedings volumes. The results will be uploaded to lod.springer.com, with the purpose of creation of the largest dataset of peer review processes in CS conferences.
The document outlines the course distribution and syllabus for a Masters in Computer Application (MCA) program across 6 semesters. It provides details of the courses offered in semesters 1-4, including course codes, titles, credits, duration and course outlines. It lists the core courses covering topics like mathematical foundations, programming, data structures, databases, networks and elective courses. It also provides the course structure and syllabus for semesters 5-6, which include more advanced topics and a final project in the 6th semester.
This document provides a syllabus for a Bachelor in Computer Application (BCA) degree program. It outlines the courses, subjects, and papers for each of the six semesters. The first semester includes courses in mathematics, English, basic electronics, computer fundamentals, and programming techniques with C programming. The second semester covers additional topics in mathematics, computer organization/architecture, data structures in C, digital electronics, and discrete mathematics. Subsequent semesters cover operating systems, probability/statistics, data processing, numerical analysis, computer graphics, databases, networking, and software engineering among other topics. Exams are 3 hours in duration and include both theory and practical papers. Recommended textbooks are provided for each subject.
This document provides the scheme and syllabus for the integrated B.E. MBA (Computer Science and Engineering) program at the University Institute of Engineering and Technology, Panjab University, Chandigarh for the academic year 2013-2014. It outlines the coursework, credits, exams and assessments for each semester of the 5-year program spanning the third through tenth semesters. The document includes details of the subjects covered, teaching schemes, credits awarded and exam structures for both the B.E. and MBA portions of the integrated program.
This document outlines the study and evaluation scheme for a Master of Technology degree in Computer Science/Information Technology at UPTU.
It provides the course codes, subjects, theory/tutorial/lab periods, and evaluation schemes for each semester. In semester 1, there are 4 core courses covering foundations of computer science, computer organization/architecture, operating systems, and data networks. Each has theory, tutorial, and lab components, with internal assessments worth 30-50 marks and end semester exams worth 100-150 marks.
Semester 2 covers 4 elective courses, with similar evaluation schemes. Semesters 3 and 4 include electives, a professional aspects course, seminar, and dissertation work. Evaluation includes internal and
The document provides details of the syllabus for the third semester B.Sc. Information Technology course at the University of Mumbai. It includes information on 5 theory courses - Logic and Discrete Mathematics, Computer Graphics, Advanced SQL, Object Oriented Programming with C++, and Modern Operating Systems. For each theory course, it lists the course code, number of lectures per week, unit topics, expected learning outcomes and reference books. It also provides details of the corresponding practical/lab courses including expected experiments and assignments.
This document provides a syllabus for a B.E. Computer Engineering program from 2012-2015 at Savitribai Phule Pune University. The syllabus aims to blend concepts and advances using open-source technologies. It includes 16 electives in areas like cloud computing, mobile computing, web applications, and cyber security. Laboratory courses focus on utilizing state-of-the-art open-source software. The program objectives are to expose students to computer systems and applications, provide conceptual and interdisciplinary knowledge, and develop professional skills for the IT industry.
Creating a dataset of peer review in computer science conferences published b...Aliaksandr Birukou
Computer science (CS) as a field is characterised by higher publication numbers and prestige of conference proceedings as opposed to scholarly journal articles. In this presentation we present preliminary results of the extraction and analysis of peer review information from computer science conferences published by Springer in almost 10,000 proceedings volumes. The results will be uploaded to lod.springer.com, with the purpose of creation of the largest dataset of peer review processes in CS conferences.
The document outlines the course distribution and syllabus for a Masters in Computer Application (MCA) program across 6 semesters. It provides details of the courses offered in semesters 1-4, including course codes, titles, credits, duration and course outlines. It lists the core courses covering topics like mathematical foundations, programming, data structures, databases, networks and elective courses. It also provides the course structure and syllabus for semesters 5-6, which include more advanced topics and a final project in the 6th semester.
This document provides the scheme and syllabus for the M.Tech degree program in Computer Science and Engineering with specialization in Computer Science and Engineering offered by Kerala Technological University.
It outlines the course structure over four semesters. The first two semesters cover core subjects in areas like computational intelligence, data structures and algorithms, databases, computer networks, operating systems etc. along with electives. The third semester focuses on specialized electives and a project phase 1. The final semester involves the project phase 2.
Laboratory courses accompany the theoretical subjects. Evaluation is based on internal assessment and end semester exams. The document provides details of the courses offered, their objectives, outcomes and syllabus across the four se
B.Tech 2nd Year CSE & CSIT AICTE Model Curriculum 2019-20.pdfAnita Pal
This document outlines the evaluation scheme, syllabus, and course details for the second year of the B.Tech Computer Science and Engineering program at DR. A.P.J. Abdul Kalam Technical University in Lucknow, India. It includes information on subjects, credit hours, evaluation criteria, and course codes for semesters 3 and 4. Semester 3 covers subjects like Data Structures, Computer Organization and Architecture, Discrete Structures and Logic, along with their corresponding labs. Semester 4 covers subjects like Operating Systems, Theory of Automata, Microprocessors, along with their labs. For each subject, the document provides the course outcomes, topics to be covered, textbooks, and other details.
This document outlines the curriculum for a Master of Technology (Computer Science and Engineering) degree program. It includes the course requirements and electives for each of the four semesters. In the first semester, students will take courses in mathematical foundations, computer architecture, data structures and algorithms, computer networks, and research methodology. They will also complete labs in network management and a term paper. The subsequent semesters include additional theory courses, labs, and electives in areas such as databases, distributed systems, software engineering, and a capstone project. The degree requires a total of 75 credits over four semesters.
The document provides the syllabus for the 3rd year 1st semester courses for the Computer Science and Engineering department at Jawaharlal Nehru Technological University Kakinada, including courses on Data Warehousing and Data Mining, Computer Networks, Compiler Design, Artificial Intelligence, and Professional Electives, along with information on class schedules, course objectives, and reading materials.
The document outlines the program structure for the second year of engineering studies at the University of Mumbai for semesters 3 and 4. It includes the course codes, names, teaching schemes with credits, and examination schemes for the courses. The core courses cover topics like data structures, databases, algorithms, and computer programming. The document also provides course objectives and outcomes, as well as a detailed syllabus covering concepts like stacks, queues, linked lists, trees, graphs, searching, sorting, and applications of data structures. Assessment includes internal tests and an end semester exam.
This document outlines the curriculum and syllabus for a Master of Technology (Computer Science and Engineering) program offered part-time at SRM University. It details the courses offered over six semesters, including topics covered, credit hours, and electives. Courses cover subjects such as parallel computer architecture, object oriented software engineering, database technology, computer communication, and a final project work. The total credits required to earn the MTech degree is 71.
The document provides the course structure for a Department of Computer Science over 8 semesters. It includes the course codes, names, credits and details for theory, sessional/laboratory, and extracurricular courses each semester. Departmental electives are grouped in 3 areas and breadth electives are listed in areas 5-7. The total credits for the program are 179.
The document provides the course structure and syllabus for the third and fourth year of the B.Tech in Computer Science and Engineering (Data Science) program offered by Jawaharlal Nehru Technological University Hyderabad for the 2018 batch. It lists the courses offered in each semester of third and fourth year along with course codes, titles, credits, and brief descriptions. Some of the major courses covered include data mining, machine learning, big data analytics, predictive analytics, and capstone projects. The document also provides details of professional and open electives that can be chosen by students.
This document provides an overview of a course on Predictive Modeling using IBM SPSS Statistics. The course is divided into 5 units that cover topics such as reading, organizing, and transforming data in SPSS; conducting descriptive and inferential statistics; creating graphical displays; and performing statistical analyses like t-tests, ANOVA, correlation, regression, and predictive analysis. Students will learn how to import, manage, and analyze data in SPSS through illustrative problems and projects involving both parametric and non-parametric statistical tests. The goal is for students to gain experience in using SPSS to conduct statistical analyses and predictive modeling on data.
This document outlines the scheme and syllabus for the MSc Computer Science program offered by the Department of Computer Science at the University of Kerala.
The program is a 4 semester course with 3 semesters of taught courses and 1 semester of project work. The first two semesters cover core subjects like discrete structures, computer architecture, data structures, algorithms, operating systems, databases etc. along with electives. The third semester has more advanced subjects and electives. The fourth semester involves a project and viva voce.
The syllabus details are provided for the core subjects to be taught in the first semester, including topics like logic, graphs, automata theory for discrete structures, computer components, memory organization
This document outlines the teaching and evaluation scheme for the 3rd semester Information Technology program for the 2019-20 academic year. It includes:
- A list of 5 theory subjects and their credit hours, internal assessment marks, end semester exam marks, and total marks.
- A list of 4 practical subjects and their lab hours, internal assessment marks, and total marks.
- The total credit hours, internal assessment marks, end semester exam marks, and grand total marks for the semester.
- Minimum passing marks requirements and details on student centered activities.
- An outline of the curriculum for the 3rd semester Diploma in Information Technology program.
B.Tech Scheme and Syllabus 2019-2020 onwards.docxRamanPandey31
This document outlines the course scheme and syllabus for a B.Tech Computer Science program from 2019 onwards at Manipal University Jaipur.
It includes the course codes, names, credits, and brief descriptions for 8 semesters of the program. Core subjects cover areas like data structures, algorithms, operating systems, databases, networks, artificial intelligence, software engineering and more. The program also includes open electives, program electives in areas like cyber security and cloud computing, and a major final year project.
Lab sessions accompany most core subjects to provide hands-on learning. The scheme is designed to equip students with both theoretical knowledge and practical skills over the 4-year degree program.
This document outlines the curriculum for computer science and engineering students at Anna University Chennai for semesters III through VIII from the 2006-2007 academic year onwards. It lists the courses taught each semester including course codes, titles, credit hours, and brief descriptions. Some of the core courses include data structures, digital principles and systems design, object oriented programming, computer architecture, operating systems, databases, networks, and a capstone project. Electives are offered in areas such as artificial intelligence, graphics, compilers, and management. The document provides a comprehensive overview of the computer science curriculum.
This document provides information about the course CS302 Design and Analysis of Algorithms, which is part of the 6th semester B.Tech program in Computer Science and Engineering at Rajagiri School of Engineering and Technology. The course aims to develop an understanding of basic algorithms and problem solving strategies. It covers topics like algorithm complexity analysis, recursion, sorting, searching, graph algorithms, divide and conquer, dynamic programming, greedy algorithms, backtracking, and computational complexity theory. The course outcomes include analyzing time and space complexity of algorithms, solving recurrence relations, designing algorithms for various strategies, and classifying computational problems based on complexity.
This document outlines the regulations and curriculum for the Master of Engineering in Computer Science and Engineering program at Anna University, Chennai for 2021. It includes 5 program educational objectives that aim to develop students' proficiency in computer science, ability to adapt to new technologies, analytical thinking, teamwork skills, and entrepreneurship. It also lists 4 program specific outcomes related to designing software systems, understanding industry trends, modeling computer systems, and professional development. The document provides details of the curriculum over 4 semesters, including courses in advanced data structures, databases, networks, programming languages, machine learning, software engineering, and professional electives. It also lists the audit courses that students can optionally enroll in.
The document outlines the course structure and syllabus for B.Tech. Information Technology (IT) at Punjab Technical University. It provides details of courses across 7 semesters, including course codes, names, credits, instruction hours, internal and external assessment breakdown, and total marks. Elective courses are offered in areas such as storage management, multimedia databases, mobile computing, information security, cloud computing, theory of computation, object oriented analysis and design, business intelligence, agile software development, software testing and quality assurance. The 8th semester focuses on software training and an industry oriented project.
The document summarizes several course outlines for computer science courses. It provides details on three courses: Digital Logic, Discrete Structure, and Microprocessor. For each course it lists information like the course title, number, credit hours, nature, goals, contents which are divided into units, textbooks, and lab works. It also includes two sample course outlines for Data Structures and Algorithms and another unnamed course. The courses cover topics in digital logic, discrete math, microprocessors, data structures, algorithms and other computer science fundamentals.
The document summarizes several course outlines for computer science courses. It provides details on three courses: Digital Logic, Discrete Structure, and Microprocessor. For each course it lists information like the course title, number, credit hours, nature, goals, contents which are divided into units, textbooks, and lab works. It also includes two sample course outlines for Data Structures and Algorithms and another unnamed course. The courses cover topics in digital logic, discrete math, microprocessors, data structures, algorithms and other computer science fundamentals.
This document outlines the curriculum for the course "Elective Theory II - Data Science and Big Data" for the VI semester of the Diploma in Computer Engineering program. The course covers 5 units over 80 hours on data science fundamentals, data modeling, and big data concepts including storage and processing. The objectives are to understand data science techniques, apply data analysis in Python and Excel, learn about big data characteristics and technologies like Hadoop, and explore applications of big data. Topics include linear regression, classification models, MapReduce, and using big data in fields such as marketing, healthcare, and advertising.
This document provides the scheme and syllabus for the M.Tech degree program in Computer Science and Engineering with specialization in Computer Science and Engineering offered by Kerala Technological University.
It outlines the course structure over four semesters. The first two semesters cover core subjects in areas like computational intelligence, data structures and algorithms, databases, computer networks, operating systems etc. along with electives. The third semester focuses on specialized electives and a project phase 1. The final semester involves the project phase 2.
Laboratory courses accompany the theoretical subjects. Evaluation is based on internal assessment and end semester exams. The document provides details of the courses offered, their objectives, outcomes and syllabus across the four se
B.Tech 2nd Year CSE & CSIT AICTE Model Curriculum 2019-20.pdfAnita Pal
This document outlines the evaluation scheme, syllabus, and course details for the second year of the B.Tech Computer Science and Engineering program at DR. A.P.J. Abdul Kalam Technical University in Lucknow, India. It includes information on subjects, credit hours, evaluation criteria, and course codes for semesters 3 and 4. Semester 3 covers subjects like Data Structures, Computer Organization and Architecture, Discrete Structures and Logic, along with their corresponding labs. Semester 4 covers subjects like Operating Systems, Theory of Automata, Microprocessors, along with their labs. For each subject, the document provides the course outcomes, topics to be covered, textbooks, and other details.
This document outlines the curriculum for a Master of Technology (Computer Science and Engineering) degree program. It includes the course requirements and electives for each of the four semesters. In the first semester, students will take courses in mathematical foundations, computer architecture, data structures and algorithms, computer networks, and research methodology. They will also complete labs in network management and a term paper. The subsequent semesters include additional theory courses, labs, and electives in areas such as databases, distributed systems, software engineering, and a capstone project. The degree requires a total of 75 credits over four semesters.
The document provides the syllabus for the 3rd year 1st semester courses for the Computer Science and Engineering department at Jawaharlal Nehru Technological University Kakinada, including courses on Data Warehousing and Data Mining, Computer Networks, Compiler Design, Artificial Intelligence, and Professional Electives, along with information on class schedules, course objectives, and reading materials.
The document outlines the program structure for the second year of engineering studies at the University of Mumbai for semesters 3 and 4. It includes the course codes, names, teaching schemes with credits, and examination schemes for the courses. The core courses cover topics like data structures, databases, algorithms, and computer programming. The document also provides course objectives and outcomes, as well as a detailed syllabus covering concepts like stacks, queues, linked lists, trees, graphs, searching, sorting, and applications of data structures. Assessment includes internal tests and an end semester exam.
This document outlines the curriculum and syllabus for a Master of Technology (Computer Science and Engineering) program offered part-time at SRM University. It details the courses offered over six semesters, including topics covered, credit hours, and electives. Courses cover subjects such as parallel computer architecture, object oriented software engineering, database technology, computer communication, and a final project work. The total credits required to earn the MTech degree is 71.
The document provides the course structure for a Department of Computer Science over 8 semesters. It includes the course codes, names, credits and details for theory, sessional/laboratory, and extracurricular courses each semester. Departmental electives are grouped in 3 areas and breadth electives are listed in areas 5-7. The total credits for the program are 179.
The document provides the course structure and syllabus for the third and fourth year of the B.Tech in Computer Science and Engineering (Data Science) program offered by Jawaharlal Nehru Technological University Hyderabad for the 2018 batch. It lists the courses offered in each semester of third and fourth year along with course codes, titles, credits, and brief descriptions. Some of the major courses covered include data mining, machine learning, big data analytics, predictive analytics, and capstone projects. The document also provides details of professional and open electives that can be chosen by students.
This document provides an overview of a course on Predictive Modeling using IBM SPSS Statistics. The course is divided into 5 units that cover topics such as reading, organizing, and transforming data in SPSS; conducting descriptive and inferential statistics; creating graphical displays; and performing statistical analyses like t-tests, ANOVA, correlation, regression, and predictive analysis. Students will learn how to import, manage, and analyze data in SPSS through illustrative problems and projects involving both parametric and non-parametric statistical tests. The goal is for students to gain experience in using SPSS to conduct statistical analyses and predictive modeling on data.
This document outlines the scheme and syllabus for the MSc Computer Science program offered by the Department of Computer Science at the University of Kerala.
The program is a 4 semester course with 3 semesters of taught courses and 1 semester of project work. The first two semesters cover core subjects like discrete structures, computer architecture, data structures, algorithms, operating systems, databases etc. along with electives. The third semester has more advanced subjects and electives. The fourth semester involves a project and viva voce.
The syllabus details are provided for the core subjects to be taught in the first semester, including topics like logic, graphs, automata theory for discrete structures, computer components, memory organization
This document outlines the teaching and evaluation scheme for the 3rd semester Information Technology program for the 2019-20 academic year. It includes:
- A list of 5 theory subjects and their credit hours, internal assessment marks, end semester exam marks, and total marks.
- A list of 4 practical subjects and their lab hours, internal assessment marks, and total marks.
- The total credit hours, internal assessment marks, end semester exam marks, and grand total marks for the semester.
- Minimum passing marks requirements and details on student centered activities.
- An outline of the curriculum for the 3rd semester Diploma in Information Technology program.
B.Tech Scheme and Syllabus 2019-2020 onwards.docxRamanPandey31
This document outlines the course scheme and syllabus for a B.Tech Computer Science program from 2019 onwards at Manipal University Jaipur.
It includes the course codes, names, credits, and brief descriptions for 8 semesters of the program. Core subjects cover areas like data structures, algorithms, operating systems, databases, networks, artificial intelligence, software engineering and more. The program also includes open electives, program electives in areas like cyber security and cloud computing, and a major final year project.
Lab sessions accompany most core subjects to provide hands-on learning. The scheme is designed to equip students with both theoretical knowledge and practical skills over the 4-year degree program.
This document outlines the curriculum for computer science and engineering students at Anna University Chennai for semesters III through VIII from the 2006-2007 academic year onwards. It lists the courses taught each semester including course codes, titles, credit hours, and brief descriptions. Some of the core courses include data structures, digital principles and systems design, object oriented programming, computer architecture, operating systems, databases, networks, and a capstone project. Electives are offered in areas such as artificial intelligence, graphics, compilers, and management. The document provides a comprehensive overview of the computer science curriculum.
This document provides information about the course CS302 Design and Analysis of Algorithms, which is part of the 6th semester B.Tech program in Computer Science and Engineering at Rajagiri School of Engineering and Technology. The course aims to develop an understanding of basic algorithms and problem solving strategies. It covers topics like algorithm complexity analysis, recursion, sorting, searching, graph algorithms, divide and conquer, dynamic programming, greedy algorithms, backtracking, and computational complexity theory. The course outcomes include analyzing time and space complexity of algorithms, solving recurrence relations, designing algorithms for various strategies, and classifying computational problems based on complexity.
This document outlines the regulations and curriculum for the Master of Engineering in Computer Science and Engineering program at Anna University, Chennai for 2021. It includes 5 program educational objectives that aim to develop students' proficiency in computer science, ability to adapt to new technologies, analytical thinking, teamwork skills, and entrepreneurship. It also lists 4 program specific outcomes related to designing software systems, understanding industry trends, modeling computer systems, and professional development. The document provides details of the curriculum over 4 semesters, including courses in advanced data structures, databases, networks, programming languages, machine learning, software engineering, and professional electives. It also lists the audit courses that students can optionally enroll in.
The document outlines the course structure and syllabus for B.Tech. Information Technology (IT) at Punjab Technical University. It provides details of courses across 7 semesters, including course codes, names, credits, instruction hours, internal and external assessment breakdown, and total marks. Elective courses are offered in areas such as storage management, multimedia databases, mobile computing, information security, cloud computing, theory of computation, object oriented analysis and design, business intelligence, agile software development, software testing and quality assurance. The 8th semester focuses on software training and an industry oriented project.
The document summarizes several course outlines for computer science courses. It provides details on three courses: Digital Logic, Discrete Structure, and Microprocessor. For each course it lists information like the course title, number, credit hours, nature, goals, contents which are divided into units, textbooks, and lab works. It also includes two sample course outlines for Data Structures and Algorithms and another unnamed course. The courses cover topics in digital logic, discrete math, microprocessors, data structures, algorithms and other computer science fundamentals.
The document summarizes several course outlines for computer science courses. It provides details on three courses: Digital Logic, Discrete Structure, and Microprocessor. For each course it lists information like the course title, number, credit hours, nature, goals, contents which are divided into units, textbooks, and lab works. It also includes two sample course outlines for Data Structures and Algorithms and another unnamed course. The courses cover topics in digital logic, discrete math, microprocessors, data structures, algorithms and other computer science fundamentals.
This document outlines the curriculum for the course "Elective Theory II - Data Science and Big Data" for the VI semester of the Diploma in Computer Engineering program. The course covers 5 units over 80 hours on data science fundamentals, data modeling, and big data concepts including storage and processing. The objectives are to understand data science techniques, apply data analysis in Python and Excel, learn about big data characteristics and technologies like Hadoop, and explore applications of big data. Topics include linear regression, classification models, MapReduce, and using big data in fields such as marketing, healthcare, and advertising.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
It 2ndyear syllabus
1. UTTAR PRADESH TECHNICAL UNIVERSITY
LUCKNOW
Syllabus
for
B.TECH. INFORMATION TECHNOLOGY
of
Second Year
(Effective from the Session: 2014-15)
2. B.TECH INFORMATION TECHNOLOGY
STUDY & EVALUATION SCHEME
2nd
Year SEMESTER III
S.
No.
Course Code Subject
Periods Evaluation Scheme
Subject
Total
CreditL T P Sessional Exam ESE
CT TA Total
THEORY SUBJECT
1 NAS-301/
NOE-031 to
NOE-039
Mathematics III/Science
Based Open Elective
3 1 0 30 20 50 100 150 4
2 NEC-309 Digital Logic Design 3 1 0 30 20 50 100 150 4
3 NCS-301 Data Structures Using C 3 1 0 30 20 50 100 150 4
4 NCS-302 Discrete Structures And
Graph Theory
3 1 0 30 20 50 100 150 4
5 NHU-301/
NHU-302
Industrial Psychology/
Industrial Sociology
2 0 0 15 10 25 50 75 2
6 NCS-303 Computer Based Numerical
And Statistical Techniques
2 1 0 15 10 25 50 75 3
AUC-001/
AUC-002
Human Values & Professional
Ethics/ Cyber Security
2 0 0 15 10 25 50 75*
PRACTICAL/DESIGN/DRAWING
7 NEC 359 Digital Logic Design Lab 0 0 3 10 10 20 30 50 1
8 NCS 351 Data Structures Using C Lab 0 0 3 10 10 20 30 50 1
9 NCS 353 Numerical Techniques Lab 0 0 2 10 10 20 30 50 1
10 NCS 355 Advance Programming Lab 0 0 2 10 10 20 30 50 1
11 NGP 301 GP 50 50
TOTAL 18 5 10 1000 25
Science Based Open Elective:
NOE031 Introduction to Soft Computing (Neural Network, Fuzzy Logic and Genetic
Algorithm
NOE032 Nano Sciences
NOE033 Laser Systems and Applications
NOE034 Space Sciences
NOE035 Polymer Science & Technology
NOE036 Nuclear Science
NOE037 Material Science
NOE038 Discrete Mathematics
NOE039 Applied Linear Algebra
*Human values & Professional Ethics /Cyber Security will be offered as a compulsory audit course for which passing marks are 30% in End
Semester Examination and 40% in aggregate.
3. B.TECH INFORMATION TECHNOLOGY
STUDY & EVALUATION SCHEME
2nd
Year SEMESTER IV
S.
No.
Course Code Subject
Periods Evaluation Scheme
Subject
Total
CreditL T P Sessional Exam ESE
CT TA Total
THEORY SUBJECT
1 NOE-041 to
NOE-049/
NAS-401
Science Based Open Elective/
Mathematics III
3 1 0 30 20 50 100 150 4
2 EHU-401/
EHU -402
Industrial Sociology/ Industrial
Psychology
2 0 0 15 10 25 50 75 2
3 NEC-408 Information Theory and Coding 3 1 0 30 20 50 100 150 4
4 NCS- 401 Operating System 3 1 0 30 20 50 100 150 4
5 NCS- 402 Theory Of Automata and Formal
Launguage
3 1 0 30 20 50 100 150 4
6 NIT-401 Multimedia and Animation 2 1 0 15 10 25 50 75 3
7 AUC-002/
AUC-001
Cyber Security /
Human Values & Professional Ethics
2 0 0 15 10 25 50 75*
PRACTICAL/DESIGN/DRAWING
7 NCS-451 Operating System Lab 0 0 3 10 10 20 30 50 1
8 NIT-451 Multimedia and Animation Lab 0 0 3 10 10 20 30 50 1
9 NCS-455 Functional and Logic
Programming Lab
0 0 3 10 10 20 30 50 1
10 NIT-456 Colloquium 0 0 3 10 10 20 30 50 1
11 NGP-401 GP 50 50
TOTAL 18 5 10 1000 25
Science Based Open Elective:
NOE-041 Introduction to Soft Computing (Neural Network, Fuzzy Logic and Genetic Algorithm
NOE-042 Nano Sciences
NOE-043 Laser Systems and Applications
NoE-044 Space Sciences
NOE-045 Polymer Science & Technology
NOE-046 Nuclear Science
NOE-047 Material Science
NOE-048 Discrete Mathematics
NOE-049 Applied Linear Algebra
*Human values & Professional Ethics /Cyber Security will be offered as a compulsory audit course for which passing marks are 30% in End
Semester Examination and 40% in aggregate.
4. NEC-309: DIGITAL LOGIC DESIGN
Unit-I
Digital Design and Binary Numbers:
Binary Arithmetic, Negative Numbers and their Arithmetic, Floating point representation, Binary Codes, Cyclic
Codes, Error Detecting and Correcting Codes, Hamming Codes.
Minterm and Maxterm Realization of Boolean Functions, Gate-level minimization: The map method up to four
variable, don’t care conditions, SOP and POS simplification, NAND and NOR implementation, Quine Mc-
Cluskey Method (Tabular method).
Unit-II
Combinational Logic:
Combinational Circuits, Analysis Procedure, Design Procedure, Binary Adder-Subtractor, Code Converters,
Parity Generators and Checkers, Decimal Adder, Binary Multiplier, Magnitude Comparator, Decoders,
Encoders, Multiplexers, Hazards and Threshold Logic
Unit-III
Memory and Programmable Logic Devices:
Semiconductor Memories, RAM, ROM, PLA, PAL, Memory System design.
Unit-IV
Synchronous Sequential Logic:
Sequential Circuits, Storage Elements: Latches, Flip Flops, Analysis of Clocked Sequential circuits, state
reduction and assignments, design procedure.
Registers and Counters: Shift Registers, Ripple Counter, Synchronous Counter, Other Counters.
Unit-V
Asynchronous Sequential Logic: Analysis procedure, circuit with latches, design procedure, reduction of state
and flow table, race free state assignment, hazards.
References:
1. M. Morris Mano and M. D. Ciletti, “Digital Design”, Pearson Education.
2.A.K .Singh, “Foundation of Digital Electronics and Logic design”,New Age international.
3.M. Rafiquzzaman, “Fundamentals of Digital Logic and Microcomputer Design”, Wiley Dreantech Publication.
4.ZVI Kohavi, “Switching and Finite Automata theory” ,Tata McGraw-Hill.
5.C.H Roth,Jr., “Fundamentals of Logic Design”, ,Jaico Publishing.
6. Rajaraman & Radhakrishnan, “Digital Logic and Computer Organization”,PHI Learning Private Limited,
Delhi India.
7. Donald D. Givone, “Digital Principles and Design”, Tata MCGraw Hill.
8. Marcovitz:Introduction to logic Design ,Tata Mcgraw-hill Education (India) Pvt. Ltd.
NCS-301: DATA STRUCTURES USING – C
Unit - I
Introduction: Basic Terminology, Elementary Data Organization, Algorithm, Efficiency of an Algorithm, Time
and Space Complexity, Asymptotic notations: Big-Oh, Time-Space trade-off.
Abstract Data Types (ADT)
Arrays: Definition, Single and Multidimensional Arrays, Representation of Arrays: Row Major Order, and
Column Major Order, Application of arrays, Sparse Matrices and their representations.
Linked lists: Array Implementation and Dynamic Implementation of Singly Linked Lists, Doubly Linked List,
Circularly Linked List, Operations on a Linked List. Insertion, Deletion, Traversal, Polynomial Representation
and Addition,Generalized Linked List .
Unit – II
Stacks: Abstract Data Type, Primitive Stack operations: Push & Pop, Array and Linked Implementation of Stack
in C, Application of stack: Prefix and Postfix Expressions, Evaluation of postfix expression, Recursion, Tower
of Hanoi Problem, Simulating Recursion, Principles of recursion,Tail recursion, Removal of recursion Queues,
Operations on Queue: Create, Add, Delete, Full and Empty, Circular queues, Array and linked implementation
of queues in C, Dequeue and Priority Queue.
Unit – III
Trees: Basic terminology, Binary Trees, Binary Tree Representation: Array Representation and Dynamic
Representation, CompleteBinary Tree, Algebraic Expressions, Extended Binary Trees, Array and Linked
Representation of Binary trees, Tree Traversal algorithms: Inorder, Preorder and Postorder, Threaded Binary
trees, Traversing Threaded Binary trees, Huffman algorithm.
Unit – IV
Graphs: Terminology, Sequential and linked Representations of Graphs: Adjacency Matrices, Adjacency List,
Adjacency Multi list, Graph Traversal : Depth First Search and Breadth First Search, Connected Component,
5. Spanning Trees, Minimum Cost Spanning Trees: Prims and Kruskal algorithm. Transistive Closure and Shortest
Path algorithm: Warshal Algorithm and Dijikstra Algorithm, Introduction to Activity Networks
Unit – V
Searching : Sequential search, Binary Search, Comparison and Analysis Internal Sorting: Insertion Sort,
Selection, Bubble Sort, Quick Sort, Two Way Merge Sort, Heap Sort, Radix Sort, Practical consideration for
Internal Sorting.
Search Trees: Binary Search Trees(BST), Insertion and Deletion in BST, Complexity of Search Algorithm,
AVL trees, Introduction to m-way Search Trees, B Trees & B+ Trees .
Hashing: Hash Function, Collision Resolution Strategies
Storage Management: Garbage Collection and Compaction.
References :
1. Aaron M. Tenenbaum,YedidyahLangsam and Moshe J. Augenstein “Data Structures Using C and C++”, PHI
Learning Private Limited, Delhi India
2. Horowitz and Sahani, “Fundamentals of Data Structures”, Galgotia Publications Pvt Ltd Delhi India.
3. A.K. Sharma ,Data Structure Using C, Pearson Education India.
4. Rajesh K. Shukla, “Data Structure Using C and C++” Wiley Dreamtech Publication.
5. Lipschutz, “Data Structures” Schaum’s Outline Series, Tata Mcgraw-hill Education (India) Pvt. Ltd .
6. Michael T. Goodrich, Roberto Tamassia, David M. Mount “Data Structures and Algorithms in C++”, Wiley
India.
7. P.S. Deshpandey, “C and Datastructure”, Wiley Dreamtech Publication.
8. R. Kruse etal, “Data Structures and Program Design in C”, Pearson Education
9. Berztiss, A.T.: Data structures, Theory and Practice :, Academic Press.
10. Jean Paul Trembley and Paul G. Sorenson, “An Introduction to Data Structures with applications”, McGraw
Hill.
NCS-302: DISCRETE STRUCTURES AND GRAPH THEORY
Unit-I
Set Theory: Introduction, Combination of sets, Multisets, Ordered pairs, Set Identities.
Relations: Definition, Operations on relations, Properties of relations, Composite Relations,
Equality of relations, Order of relations.
Functions: Definition, Classification of functions, Operations on functions, Recursively defined
functions.
Natural Numbers: Introduction, Mathematical Induction, Variants of Induction, Induction with
Nonzero Base cases.
Unit-II
Algebraic Structures: Definition, Groups, Subgroups and order, Cyclic Groups, Cosets, Lagrange's theorem,
Normal Subgroups, Permutation and Symmetric groups, Group Homomorphisms , Definition and elementary
properties of Rings and Fields, Integers Modulo n.
Unit-III
Partial order sets: Definition, Partial order sets, Combination of partial order sets, Hasse diagram.
Lattices: Definition, Properties of lattices – Bounded, Complemented, Modular and Complete
Lattice,Morphisms of lattices.
Boolean Algebra: Introduction, Axioms and Theorems of Boolean algebra, Algebraic manipulation of Boolean
expressions. Simplification of Boolean Functions, Karnaugh maps, Logic gates, Digital circuits and Boolean
algebra. Combinational and sequential Circuits
Unit-IV
Propositional Logic: Proposition, well formed formula, Truth tables, Tautology, Satisfiability,
Contradiction, Algebra of proposition, Theory of Inference ,Natural Deduction.
Predicate Logic: First order predicate, well formed formula of predicate, quantifiers, Inference
theory of predicate logic.
Unit-V
Trees : Definition, Binary tree, Binary tree traversal, Binary search tree.
Graphs: Definition and terminology, Representation of graphs, Multigraphs, Bipartite graphs,
Planar graphs, Isomorphism and Homeomorphism of graphs, Euler and Hamiltonian paths, Graph coloring .
Recurrence Relation & Generating function: Recursive definition of functions, Recursive
algorithms, Method of solving recurrences.
Combinatorics: Introduction, Counting Techniques, Pigeonhole Principle
References :
1. Liu and Mohapatra, “Elements of Distcrete Mathematics”, McGraw Hill
2. Jean Paul Trembley, R Manohar, Discrete Mathematical Structures with Application to
6. Computer Science, McGraw-Hill
3. Y. N. Singh, “Discrete Mathematical Structures”, Wiley India, New Delhi, First Edition, August 2010.
4. R.P. Grimaldi, Discrete and Combinatorial Mathematics, Addison Wesley,
5. B. Kolman, R.C. Busby, and S.C. Ross, Discrete Mathematical Structures, PHI Learning Private Limited,
Delhi India.
6. Biswal ,“Discrete Mathematics and Graph Theory, PHI Learning Private Limited, Delhi India.
7. Goodaire and Parmenter,“ Discrete Mathematics with Graph Theory”, PHI Learning Private Limited, Delhi
India.
8. Lipschutz “Discrete Mathematics” Mc Graw Hill
9. Deo N., “Graph Theory with Applications to Engineering and Computer Science”, PHI Learning Private
Limited, Delhi India.
NCS-303: Computer Based Numerical and Statistical Techniques
Unit –I :
Computer Arithmetic and Errors: Floating Point Arithmetic, Machine epsilon, Round off Error,
Chopping Error, Truncation Error, Associative and Distributive Law in Floating Point arithmetic, Inherent
Error, Error propagation, Numerical Instability
Roots of Equation: Secant Method, Newton Raphson Method and Fixed point Iteration Methods for
Simple roots and derivation of their rate of convergence, Aitken Acceleration of Convergence, Modified
Newton Raphson Method for Multiple roots, Birge-Vieta Method for Polynomials, Bairstrow Method for
quadratic factors, Computer Algorithms of these methods.
Unit –II
Interpolation: Algorithms and Error Analysis of Lagrange and Newton divided difference interpolations,
Relationship in various difference operators, Piecewise Linear Interpolation, Cubic Spline Interpolation,
Natural Spline, Chebshev Polynomial Approximations, Lanczos Economization of Power Series
Curve fitting: Linear and Non Linear Least Squares Approximation, ill Conditioning in Least Squares
Methods, Gram-Schmidt Process of Orthogonalization. Computer Algorithms of Least Square Curve Fitting
Unit – III
Differentiation: Methods based on Interpolation and Finite Differences, Richrdson Extrapolation
Integration: Error Analysis of Trepezoidal and Simpson Methods, Newton Cotes Integration Methods,
Guassian Integration Methods: Guass Legendre Method, Lobatto Integration Method and Radau Integration
Method, Error Terms in Integration Methods
Unit – IV
Solution of Simultaneous Linear Algebraic Equations: Guass Elimination Method, ill Conditioned
Systems, Condition Number, Successive Over Relaxation Method, Rate of Convergence
Solution of Ordinary Differential equations: Single Step Methods-Runge-Kutta Second Order, Third
Order and Fourth Order Methods, Multi Step Method-Predictor- Corrector Method
Statistical Techniques: Statistical Hypotheses, Test of Hypotheses, Type-I and Type-II Errors, Level of
Significance, Test involving Normal Distribution
Recommended Books:
o Numerical Methods: M.K. Jain, S.R.K. Iyenger and R.K. Jain
o Applied Numerical Analysis: Curtis F. Gerald and Patrick O. Wheatley
o Schaum's Outline of Theory and Problems of Statistics: Murray R. Spiegel
NEC-359: LOGIC DESIGN LAB
Objective: To understand the digital logic and create various systems by using these logics.
1. Introduction to digital electronics lab- nomenclature of digital ICs, specifications, study of the
data sheet, concept of Vcc and ground, verification of the truth tables of logic gates using TTL
ICs.
2. Implementation of the given Boolean function using logic gates in both SOP and POS forms.
3. Verification of state tables of RS, JK, T and D flip-flops using NAND & NOR gates.
4. Implementation and verification of Decoder/De-multiplexer and Encoder using logic gates.
7. 5. Implementation of 4x1 multiplexer using logic gates.
6. Implementation of 4-bit parallel adder using 7483 IC.
7. Design, and verify the 4-bit synchronous counter.
8. Design, and verify the 4-bit asynchronous counter.
Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.
NCS-351: DATA STRUCTURE USING C LAB
Program in C or C++ for following:
1. To implement addition and multiplication of two 2D arrays.
2. To transpose a 2D array.
3. To implement stack using array.
4. To implement queue using array.
5. To implement circular queue using array.
6. To implement stack using linked list.
7. To implement queue using linked list.
8. To implement circular queue using linked list.
9. To implement binary tree using linked list.
10. To implement binary search tree using linked list.
11. To implement tree traversals using linked list.
12. To implement BFS using linked list.
13. To implement DFS using linked list.
14. To implement Linear Search.
15. To implement Binary Search.
16. To implement Bubble Sorting.
17. To implement Selection Sorting.
18. To implement Insertion Sorting.
19. To implement Merge Sorting.
20. To implement Heap Sorting.
Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.
NCS-353: NUMERICAL TECHNIQUES LAB
Write Programs in ‘C’ Language:
1. To deduce error involved in polynomial equation.
2. To Find out the root of the Algebraic and Transcendental equations using Bisection,
Regula-falsi , Newton Raphson and Iterative Methods. Also give the rate of convergence of roots in tabular form
for each of these methods.
3. To implement Newton’s Forward and Backward Interpolation formula.
4. To implement Gauss Forward and Backward, Bessel’s, Sterling’s and Evertt’s Interpolation formula
5. To implement Newton’s Divided Difference and Langranges Interpolation formula.
6. To implement Numerical Differentiations.
7. To implement Numerical Integration using Trapezoidal, Simpson 1/3 and Simpson 3/8 rule.
8. To implement Least Square Method for curve fitting.
9. To draw frequency chart like histogram, frequency curve and pie-chart etc.
10. To estimate regression equation from sampled data and evaluate values of standard deviation, t-statistics,
regression coefficient, value of R2
for atleast two independent variables.
Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.
NCS-355: ADVANCE PROGRAMMING LAB
LIST OF EXPERIMENTS:
1. Programs using Functions and Pointers in C
2. Programs using Files in C
3. Programs using Classes and Objects
8. 4. Programs using Operator Overloading
5. Programs using Inheritance, Polymorphism and its types
6. Programs using Arrays and Pointers
7. Programs using Dynamic memory allocation
8. Programs using Templates and Exceptions
9. Programs using Sequential and Random access files
Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.
NEC-408: INFORMATION THEORY AND CODING
Unit I
Review of probability theory, Definition of Information Measure and Entropy: Measure of information, Average
information content of symbols in long independent sequences, Average information content of symbols in long
dependent sequences. Mark-off statistical model for information source, Entropy and information rate of mark-
off source, Mutual information. Asymptotic Properties of Entropy and Problem Solving in Entropy
Unit – II
Block Code and its Properties, Data compression, Kraft-Mcmillan Equality and Compact Codes, Encoding of
the source output, Shannon’s encoding algorithm, Coding Strategies, Huffman Coding, Shannon-Fano-Elias
Coding and Introduction to Arithmetic Coding.
Unit – III
Introduction to Information Channels, Communication Channels, Discrete communication channels, Continuous
channels. Discrete memory less Channels, Mutual information, Channel Capacity, Channel coding theorem,
Differential entropy and mutual information for continuous ensembles, Channel capacity Theorem.
Unit – IV
Introduction to Error Control Coding: Introduction, Types of errors, examples, Types of codes Linear Block
Codes: Matrix description, Error detection and correction, Standard arrays and table look up for decoding
Unit – V
Binary Cycle Codes, Algebraic structures of cyclic codes, Encoding using an (n-k) bit shift register, Syndrome
calculation. BCH codes. RS codes, Golay codes, Shortened cyclic codes, Burst error correcting codes. Burst and
Random Error correcting codes. Convolution Codes, Time domain approach. Transform domain approach.
Reference:
1.K. Sam Shanmugam, “Digital and analog communication systems”, John Wiley.
2.Simon Haykin, “Digital communication”, John Wiley.
3.Ranjan Bose, “ITC and Cryptography” ,Tata McGraw-Hill.
4. Thomas M. Cover, Joy A. Thomas ,” Elements of Information Theory, 2nd Edition”, Wiley Publication.
5. Roberto Togneri, Christopher J.S deSilva “Fundamentals of Information Theory and Coding Design”, CRC
Press.
6. Steven Roman,” Introduction to Coding and Information Theory”, Springer New York.
7. Glover and Grant, “Digital Communications”, Pearson Education.
NCS-401: OPERATING SYSTEM
Unit – I
Introduction : Operating system and functions, Classification of Operating systems- Batch, Interactive, Time
sharing, Real Time System, Multiprocessor Systems, Multiuser Systems, Multiprocess Systems, Multithreaded
Systems, Operating System Structure- Layered structure, System Components, Operating System services,
Reentrant Kernels, Monolithic and Microkernel
Systems.
Unit – II
Concurrent Processes: Process Concept, Principle ofConcurrency, Producer / Consumer Problem, Mutual
Exclusion, Critical Section Problem, Dekker’s solution, Peterson’s solution, Semaphores, Test and Set
operation; Classical Problem in Concurrency- Dining Philosopher Problem, Sleeping Barber Problem; Inter
Process Communication models and Schemes, Process
generation.
Unit – III
CPU Scheduling: Scheduling Concepts, Performance Criteria, Process States, Process Transition
Diagram, Schedulers, Process Control Block (PCB), Process address space, Process identification information,
Threads and their management, Scheduling Algorithms, Multiprocessor Scheduling. Deadlock: System model,
Deadlock characterization, Prevention, Avoidance and detection, Recovery from deadlock.
Unit – IV
Memory Management: Basic bare machine, Resident monitor, Multiprogramming with fixed partitions,
Multiprogramming with variable partitions, Protection schemes, Paging, Segmentation, Paged segmentation,
9. Virtual memory concepts, Demand paging, Performance of demand paging, Page replacement algorithms,
Thrashing, Cache memory organization, Locality
of reference.
Unit – V
I/O Management and Disk Scheduling: I/O devices, and I/O subsystems, I/O buffering, Disk storage and disk
scheduling, RAID. File System: File concept, File organization and access mechanism, File directories, and File
sharing, File system implementation issues, File system protection and security.
References :
1. Silberschatz, Galvin and Gagne, “Operating Systems Concepts”, Wiley
2. SibsankarHalder and Alex A Aravind, “Operating Systems”, Pearson Education
3. Harvey M Dietel, “ An Introduction to Operating System”, Pearson Education
4. D M Dhamdhere, “Operating Systems : A Concept basedApproach”, McGraw Hill.
5. Charles Crowley, “Operating Systems: A Design-Oriented Approach”, Tata McGraw Hill
Education”.
1. Stuart E. Madnick & John J. Donovan, “ Operating Systems”, Tata McGraw Hill.
NCS-402: THEORY OF AUTOMATA AND FORMAL LANGUAGES
Unit – I
Introduction; Alphabets, Strings and Languages; Automata and Grammars, Deterministic finite
Automata (DFA)-Formal Definition, Simplified notation: State transition graph, Transition tabl
e, Language of DFA, Nondeterministic finite Automata (NFA), NFA with epsilon transi ion,
Language of NFA, Equi valence of NFA and DFA, Minimization of Finite Automata, Distinguis
hing one string from other, Myhill-Nerode Theorem
Unit – II
Regular expression (RE) , Definition, Operators of regular expression and their precedence,
Algebraic laws for Regular expressions, Kleen’s Theorem, Regular expression to FA, DFA to
Regular expression, Arden Theorem, Non Regular Languages, Pumping Lemma for regular
Languages . Application of Pumping Lemma, Closure properties of Regular Languages, Decision properties of
Regular Languages, FA with output: Moore and Mealy machine,
Equivalence of Moore and Mealy Machine, Applications and Limitation of FA.
Unit – III
Context free grammar (CFG) and Context Free Languages (CFL): Definition, Examples, Derivation , Derivation
trees, Ambiguity in Grammer, Inherent ambiguity, Ambiguous to Unambiguous CFG, Useless symbols,
Simplification of CFGs, Normal forms for CFGs: CNF
and GNF, Closure proper ties of CFLs, Decision Properties of CFLs: Emptiness, Finiteness and
Memership, Pumping lemma for CFLs.
Unit – IV
Push Down Automata (PDA): Description and definition, Instantaneous Description, Language of PDA,
Acceptance by Final state, Acceptance by empty stack, Deterministic PDA, Equivalence of PDA and CFG, CFG
to PDA and PDA to CFG, Two stack PDA
Unit – V
Turing machines (TM): Basic model, definition and representation, Instantaneous Description,
Language acceptance by TM, Variants of Turing Machine, TM as Computerof Integer functions, Universal TM,
Church’s Thesis, Recursive and recursively enumerable languages, Halting problem, Introduction to
Undecidability, Undecidable problems about TMs. Post correspondence problem (PCP), Modified PCP,
Introduction to recursive function theory .
References :
1. Hopcroft, Ullman, “Introduction to Automata Theory,Languages and Computation”,
Pearson Education .
2. K.L.P. Mishra and N.Chandrasekaran, “Theory of Computer Science : Automata,
Languages and Computation”, PHI Learning Private Limited, Delhi India.
3.Peter Linz, "An Introduction to Formal Language and Automata", Narosa Publishing house.
4. Y.N.Singh “Mathematical Foundation of Computer Science”, New Age International.
5. Papadimitrou, C. and Lewis, C.L., “Elements of the Theory of Computation”, PHI Learning Private Limited,
Delhi India.
6. K.Krithivasan and R.Rama; Introduction to Formal Languages, Automata Theory and Computation; Pearson
Education.
7. Harry R. Lewis and Christos H. Papadimitriou, Elements of the theory of Computation,
10. Second Edition, Prentice-Hall of India Pvt. Ltd.
8. Micheal Sipser, “Introduction of the Theory and Computation”, Thomson Learning.
NIT-401: MULTIMEDIA AND ANIMATION
Unit I – Introduction:
Introduction to Multimedia and animation, Multimedia Systems, Design Fundamentals, Elements of multimedia
and animation and their use, Back ground of Art, Color theory overview, Sketching & illustration,
Storyboarding, different tools for animation .
Unit- 2 – Multimedia Projects:
Multimedia Skills, Hardware, Use of Graphics in Multimedia, Overview of Vector and Raster Graphics, Basic
software tools, Multimedia Authoring Tools, Planning and Costing, Designing and Producing, Contents and
talent, Delivering, Enhancing and Testing Multimedia Projects.
Unit-3 – Tools of Multimedia:
Paint and Draw Applications, Graphic effects and techniques, Image File Format, Anti-aliasing, Morphing,
Multimedia Authoring tools, professional development tools.
Unit-4 - Animation:
Introduction and Principles of Animations, Power of Motion, Animation Techniques, Animation File Format,
Making animation for Rolling Ball, making animation for a Bouncing Ball, Animation for the web, GIF, Plug-
ins and Players, Animation tools for World Wide Web.
References:
1. Tay Vaughan, “Multimedia, Making IT Work”,Tata McGraw Hill.
2. Buford, “Multimedia Systems”, Addison Wesley.
3. Sleinreitz, “Multimedia System”, Addison Wesley.
4. Ze-Nian Li and Mark S.Drew, “Fundamentals of Multimedia”, Pearson
Education.
5.Prabhat K Andleigh, Kiran Thakrar, “Multimedia systems design”, PHI Learning Private Limited, Delhi India.
6.Elsom Cook – “Principles of Interactive Multimedia” ,Tata McGraw Hill.
NCS-451: OPERATING SYSTEM LAB
1. To implement CPU Scheduling Algorithms
FCFS
SJF
SRTF
PRIORITY
ROUND ROBIN
2. Simulate all Page Replacement Algorithms
FIFO
LRU
3. Simulate Paging Technique of Memory Management
Note: The Instructor may add/delete/modify/tune experiments, wherever he/shefeels in a justified manner.
NIT-451: MULTIMEDIA AND ANIMATION LAB
1. Procedure to create an animation to represent the growing moon.
2. Procedure to create an animation to indicate a ball bouncing on steps.
3. Procedure to simulate movement of a cloud.
4. Procedure to draw the fan blades and to give proper animation.
5. Procedure to display the background given (filename: tulip.jpg) through your name.
6. Procedure to display the background given (filename: garden.jpg) through your name using mask.
11. 7. Procedure to create an animation with the following features.
WELCOME (Letters should appear one by one .The fill color of the text should change to a different
colour after the display of the full word.)
8. Procedure to simulate a ball hitting another ball.
9. Procedure to design a visiting card containing at least one graphic and text information.
10. Procedure to take a photographic image. Give a title for the image. Put the border. Write your
names. Write the name of institution and place.
11. Procedure to prepare a cover page for the book in your subject area. Plan your own design.
12. Procedure to extract the flower only from given photographic image and organize it on a
background. Selecting your own background for organization.
13. Procedure to change a circle into a square using flash.
14. Procedure to display the background given (FILENAME: GARDEN.JPG) through your name using
mask.
Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.
NCS-455: FUNCTIONAL AND LOGIC PROGRAMMING LAB
Program in SML- NJ or CAML or F# for following:
1. To implement Linear Search.
2. To implement Binary Search.
3. To implement Bubble Sorting.
4. To implement Selection Sorting.
5. To implement Insertion Sorting.
Implement using LISP
6. Write a function that compute the factorial of a number.(factorial of 0 is 1, and
factorial of n is n*(n-1)*...1.Factorial is defined only for integers greater than or
equal to 0.)
7. Write a function that evaluate a fully parenthesized infix arithmetic expression .
For examples, (infix (1+(2*3))) should return 7.
8. Write a function that perform a depth first traversal of binary tree. The function
should return a list containing the tree nodes in the order they were visited.
9. Write a LISP program for water jug problem.
10. Write a LISP program that determines whether an integer is prime.
11. Write a PROLOG program that answers questions about family members and
relationships includes predicates and rules which define
sister,brother,father,mother,grandchild,grandfather and uncle. The program
should be able to answer queries such as the following :
o father(x,Amit)
o grandson(x,y)
o uncle(sumit,puneet)
o mother(anita,x)
o
Note: The Instructor may add/delete/modify/tune experiments, wherever he/shefeels in a justified manner.