Practice Question

Duration: 7 min

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Module outline

  1. About Course: About the Course
  2. Paper-2 | Programming & Data Structures: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling, Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  3. Paper-2 | Databases / DBMS & SQL: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, SQL, Relational Calculus, Transaction Management, Concurrency Control
  4. Paper-2 | Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos
  5. Paper-2 | Computer Networks & Security: Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware Basics, Network Access Technologies, Network Security
  6. Paper-2 | Digital Logic: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation, Floating Point Rep
  7. Paper-2 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Threads & Process Creation, Deadlock, Memory Management, Virtual Memory, Disc Scheduling, File Management
  8. Paper-2 | Theory of Computation: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines
  9. Paper-2 | Computer Organization & Architecture: Basics of COA, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Control Unit Design, Programming the Basic Computer
  10. Paper-2 | Compiler Design: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization, Run Time Environment
  11. Paper-1 | General Awareness: Polity, Physics, Biology, Chemistry, Static General Knowledge, GK- Current Affairs, History, Geography, Indian Economy, Environment
  12. Paper-1 | Logical Reasoning: Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Data Interpretation, Blood Relations, Syllogisms, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Clock, Calendar, Cubes & Dices, Directions (Direction Test), Analogy, Seating Arrangements, Analytical Reasoning (Counting Figures Reasoning)
  13. Paper-1 | Quantitative Aptitude: Ratio and Proportion (Ratios), Mixture and Alligation, Permutation and Combination, Number System, HCF LCM, Speed Time and Distance, Average, Age Problems, Percentage, Profit and Loss, Time and Work, Pipe and Cistern, Simple Interest and Compound Interest, Powers and Exponents (Surds and Indices), Mensuration and Geometry, Probability, Statistics, Arithmetic, Algebra
  14. Paper-1 | English: Vocabulary, Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Sentence Construction, Cloze Test (Cloze Passage)
  15. Coal India Previous Year Paper:
  16. Engineering Mathematics: Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic, Linear Algebra, Calculus
  17. Coal India Mock Test:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video demonstrates the application of the Huffman coding algorithm to a set of characters with given probabilities. The instructor guides viewers through the process of generating a Huffman tree, deriving binary codes for each character, and calculating the average number of bits required per character. The lesson covers the step-by-step combination of nodes with the lowest probabilities, the assignment of binary values to tree branches, and the final computation of the weighted path length to determine encoding efficiency.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The lecture begins with the problem statement: "Consider the following character with probability and generate Huffman tree, find Huffman code for each character, find the number of bits required per character?" A table is displayed showing five characters (M1 to M5) with probabilities .12, .04, .45, .17, and .23 respectively. The instructor starts the Huffman algorithm by identifying the two characters with the lowest probabilities, which are M2 (.04) and M1 (.12). He crosses them out and combines them into a new internal node with a probability of 0.16 (0.04 + 0.12). He draws the first part of the tree structure on the whiteboard, showing the parent node 0.16 branching down to M2 and M1. This establishes the foundation for the tree construction.

  2. 2:00 – 5:00 02:00-05:00

    The instructor proceeds to the next step of the algorithm. The remaining probabilities are M3 (.45), M4 (.17), M5 (.23), and the new node (0.16). He sorts these and identifies the two smallest: the node (0.16) and M4 (.17). He combines these to form a new node with probability 0.33. Next, he combines M5 (.23) with the 0.33 node to create a 0.56 node. Finally, he combines M3 (.45) with the 0.56 node to reach the root with probability 1.0. He then assigns binary codes to the branches, marking left branches as 0 and right branches as 1. This results in specific codes: M3 gets '0', M5 gets '10', M4 gets '111', M1 gets '1101', and M2 gets '1100'. The tree is now fully constructed with all leaves labeled.

  3. 5:00 – 7:19 05:00-07:19

    The final phase involves calculating the average number of bits required per character. The instructor writes down the length of the code for each character: M1 has 4 bits, M2 has 4 bits, M3 has 1 bit, M4 has 3 bits, and M5 has 2 bits. He sets up the calculation for the weighted path length: (4 * 0.12) + (4 * 0.04) + (1 * 0.45) + (3 * 0.17) + (2 * 0.23). He computes each term: 0.48, 0.16, 0.45, 0.51, and 0.46. Summing these values, he arrives at a total of 2.06 bits per character, which he writes as the final answer for the average bits required. This calculation demonstrates the efficiency of the Huffman code.

The video effectively connects the theoretical steps of Huffman coding to a practical calculation. By building the tree from the bottom up and assigning codes based on branch paths, the instructor shows how frequent characters get shorter codes. The final calculation of 2.06 bits per character quantifies the compression efficiency achieved by this specific encoding scheme.

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