JNTUK R20 3-1 Design and Analysis of Algorithms Material PDF Download

Students those who are studying JNTUK R20 CSE Branch, Can Download Unit wise R20 3-1 Design and Analysis of Algorithms (DAA) Material/Notes PDFs below.

JNTUK R20 3-1 Design and Analysis of Algorithms Material PDF Download

OBJECTIVES: Upon completion of this course, students will be able to do the following:

• Ability to understand, analyze and denote time complexities of algorithms
• To introduce the different algorithmic approaches for problem solving through numerous example problems
• Describe the dynamic-programming paradigm and explain when an algorithmic design situation calls for it. Recite algorithms that employ this paradigm. Synthesize dynamic-programming algorithms, and analyze them.
• To provide some theoretical grounding in terms of finding the lower bounds of algorithms and the NP-completeness

Course Outcomes: After the completion of the course, student will be able to

• Analyze the performance of a given algorithm, denote its time complexity using the asymptotic notation for recursive and non-recursive algorithms
• List and describe various algorithmic approaches and Solve problems using divide and conquer &greedy Method
• Synthesize efficient algorithms dynamic programming approaches to solve in common engineering design situations.
• Organize important algorithmic design paradigms and methods of analysis: backtracking, branch and bound algorithmic approaches
• Demonstrate NP- Completeness theory ,lower bound theory and String Matching

UNIT-1

Introduction: Algorithm Definition, Algorithm Specification, performance Analysis, Performance measurement, asymptotic notation, Randomized Algorithms.

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UNIT-2

Divide and Conquer: General Method, Defective chessboard, Binary Search, finding the maximum and minimum, Merge sort, Quick sort.

The Greedy Method: The general Method, knapsack problem, minimum-cost spanning Trees, Optimal Merge Patterns, Single Source Shortest Paths.

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UNIT-3

Dynamic Programming: The general method, multistage graphs, All pairs-shortest paths, optimal Binary search trees, 0/1 knapsack, The traveling salesperson problem.

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UNIT-4

Backtracking: The General Method, The 8-Queens problem, sum of subsets, Graph coloring, Hamiltonian cycles, knapsack problem.

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UNIT-5

NP-Hard and NP-Complete problems: Basic concepts, non-deterministic algorithms, NP – Hard and NP-Complete classes, Cook’s theorem.

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TEXT BOOKS:

1. Ellis Horowitz, SartajSahni, Sanguthevar Rajasekaran, “Fundamentals of Computer Algorithms”, 2nd Edition, Universities Press.
2. Introduction to Algorithms Thomas H. Cormen, PHI Learning
3. Harsh Bhasin, “Algorithms Design & Analysis”, Oxford University Press.

REFERENCE BOOKS:

1. Horowitz E. Sahani S: “Fundamentals of Computer Algorithms”, 2nd Edition, Galgotia Publications, 2008.
2. S. Sridhar, “Design and Analysis of Algorithms”, Oxford University Press.

JNTUK R20 3-1 Data Warehousing and Data Mining Material PDF Download

Students those who are studying JNTUK R20 CSE Branch, Can Download Unit wise R20 3-1 Data Warehousing and Data Mining (DW&DM) Material/Notes PDFs below.

JNTUK R20 3-1 Data Warehousing and Data Mining Material PDF Download

Course Objectives: The main objectives are

• Introduce basic concepts and techniques of data warehousing and data mining
• Examine the types of the data to be mined and apply pre-processing methods on raw data
• Discover interesting patterns, analyze supervised and unsupervised models and estimate the accuracy of the algorithms.

Course Outcomes: At the end of the course, the students will be able to:

• Illustrate the importance of Data Warehousing, Data Mining and its functionalities and Design schema for real time data warehousing applications.
• Demonstrate on various Data Preprocessing Techniques viz. data cleaning, data integration, data transformation and data reduction and Process raw data to make it suitable for various data mining algorithms.
• Choose appropriate classification technique to perform classification, model building and evaluation.
• Make use of association rule mining techniques viz. Apriori and FP Growth algorithms and analyze on frequent itemsets generation.
• Identify and apply various clustering algorithm (with open source tools), interpret, evaluate and report the result.

UNIT-1

Data Warehousing and Online Analytical Processing: Data Warehouse: Basic concepts, Data Warehouse Modelling: Data Cube and OLAP, Data Warehouse Design and Usage, Data Warehouse Implementation, Introduction: Why and What is data mining, What kinds of data need to be mined and patterns can be mined, Which technologies are used, Which kinds of applications are targeted.

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UNIT-2

Data Pre-processing: An Overview, Data Cleaning, Data Integration, Data Reduction, Data Transformation and Data Discretization.

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UNIT-3

Classification: Basic Concepts, General Approach to solving a classification problem, Decision Tree Induction: Attribute Selection Measures, Tree Pruning, Scalability and Decision Tree Induction, Visual Mining for Decision Tree Induction.

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UNIT-4

Association Analysis: Problem Definition, Frequent Item set Generation, Rule Generation: Confident Based Pruning, Rule Generation in Apriori Algorithm, Compact Representation of frequent item sets, FPGrowth Algorithm.

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UNIT-5

Cluster Analysis: Overview, Basics and Importance of Cluster Analysis, Clustering techniques, Different Types of Clusters; K-means: The Basic K-means Algorithm, K-means Additional Issues, Bi-secting K Means.

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TEXT BOOKS:

1. Data Mining concepts and Techniques, 3/e, Jiawei Han, Michel Kamber, Elsevier, 2011.

2. Introduction to Data Mining: Pang-Ning Tan & Michael Steinbach, Vipin Kumar, Pearson, 2012.

REFERENCE BOOKS:

1. Data Mining Techniques and Applications: An Introduction, Hongbo Du, Cengage Learning.

2. Data Mining: VikramPudi and P. Radha Krishna, Oxford Publisher.

3. Data Mining and Analysis – Fundamental Concepts and Algorithms; Mohammed J. Zaki, Wagner Meira, Jr, Oxford

4. Data Warehousing Data Mining & OLAP, Alex Berson, Stephen Smith, TMH. http://onlinecourses.nptel.ac.in

5. (NPTEL course by Prof.Pabitra Mitra) http://onlinecourses.nptel.ac.in

6. (NPTEL course by Dr. Nandan Sudarshanam& Dr. Balaraman Ravindran) http://www.saedsayad.com

JNTUK R20 3-1 Distributed Systems Material/Notes PDF Download

Students those who are studying JNTUK R20 CSE Branch, Can Download Unit wise R20 3-1 Distributed Systems Material/Notes PDFs below.

JNTUK R20 3-1 Distributed Systems Material/Notes PDF Download

OBJECTIVES:

• To understand the foundations of distributed systems.
• To learn issues related to clock Synchronization and the need for global state in distributed systems
• To learn distributed mutual exclusion and deadlock detection algorithms
• To understand the significance of agreement, fault tolerance and recovery protocols in Distributed Systems
• To learn the characteristics of peer-to-peer and distributed shared memory systems

UNIT-1

Distributed Systems: Definition, Relation to computer system components, Motivation, Relation to parallel systems, Message-passing systems versus shared memory systems, Primitives for distributed communication, Synchronous versus asynchronous executions, Design issues and challenges.

A model of distributed computations: A distributed program, A model of distributed executions, Models of communication networks, Global state, Cuts, Past and future cones of an event, Models of process communications.

Logical Time: A framework for a system of logical clocks, Scalar time, Vector time, Physical clock synchronization: NTP.

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UNIT-2

Message Ordering & Snapshots: Message ordering and group communication: Message ordering paradigms, Asynchronous execution with synchronous communication, Synchronous program order on an asynchronous system, Group communication, Causal order (CO), Total order. Global state and snapshot recording algorithms: Introduction, System model and definitions, Snapshot algorithms for FIFO channels.

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UNIT-3

Distributed Mutex & Deadlock: Distributed mutual exclusion algorithms: Introduction – Preliminaries – Lamport‘s algorithm – Ricart-Agrawala algorithm – Maekawa‘s algorithm – Suzuki–Kasami‘s broadcast algorithm. Deadlock detection in distributed systems: Introduction – System model – Preliminaries – Models of deadlocks – Knapp‘s classification – Algorithms for the single resource model, the AND model and the OR model.

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UNIT-4

Recovery & Consensus: Check pointing and rollback recovery: Introduction – Background and definitions – Issues in failure recovery – Checkpoint-based recovery – Log-based rollback recovery – Coordinated check pointing algorithm – Algorithm for asynchronous check pointing and recovery. Consensus and agreement algorithms: Problem definition – Overview of results – Agreement in a failure – free system – Agreement in synchronous systems with failures.

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UNIT-5

Peer-to-peer computing and overlay graphs: Introduction – Data indexing and overlays – Chord – Content addressable networks – Tapestry.

Distributed shared memory: Abstraction and advantages – Memory consistency models –Shared memory Mutual Exclusion.

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e-Resources:

https://nptel.ac.in

TEXT BOOKS:

1. Distributed Systems Concepts and Design, George Coulouris, Jean Dollimore and Tim Kindberg, Fifth Edition, Pearson Education, 2012.
2. Distributed computing: Principles, algorithms, and systems, Ajay D Kshemkalyani and Mukesh Singhal, Cambridge University Press, 2011.

REFERENCE BOOKS:

1. Distributed Operating Systems: Concepts and Design, Pradeep K Sinha, Prentice Hall of India, 2007.
2. Advanced concepts in operating systems. Mukesh Singhal and Niranjan G. Shivaratri, McGraw-Hill, 1994.
3. Distributed Systems: Principles and Paradigms, Tanenbaum A.S., Van Steen M.,Pearson Education, 2007.

OUTCOMES:

• Elucidate the foundations and issues of distributed systems
• Illustrate the various synchronization issues and global state for distributed systems
• Illustrate the Mutual Exclusion and Deadlock detection algorithms in distributed systems
• Describe the agreement protocols and fault tolerance mechanisms in distributed systems
• Describe the features of peer-to-peer and distributed shared memory systems