9.2 Practice Question

Duration: 2 min

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Inside: a video lesson and guided study material.

Module outline

  1. HPSC Interview Preparation: Interview Preparation
  2. Python Language: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis, DSA using Python
  3. Data Structure & Algorithms: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, Algorithm Analysis, Sorting Algorithms, Minimum Spanning Trees, Time Complexity Analysis, Graph Theory, Shortest Path Algos
  4. Computer Networks: Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Security
  5. Computer System & Organisation: Basics of COA, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Control Unit Design, Programming the Basic Computer
  6. Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, SQL, File Organization & Indexing, Transaction Management, Concurrency Control
  7. Operating Systems: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling
  8. Digital Logic & Circuits: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  9. Theory Of Computation: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Pushdown Automata & CFG, Turing Machines, Moore & Mealy Machines
  10. 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. Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management, Data Warehousing & Mining
  12. Introduction to Emerging Trends: Emerging Tech Trends
  13. Digital Society & Cyber Law: Society, Law & Ethics
  14. HPSC PGT Previous Year Paper:
  15. HPSC Assistant Professor Previous Year Paper:
  16. Live Sessions: HPSC Live Sessions, EMRS TGT/PGT Live Class
  17. Full Mock Test:
  18. HPSC PGT - MOCK Test Series:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video segment focuses on solving graph theory practice problems using the Handshaking Lemma. The instructor demonstrates how to determine vertex constraints based on edge counts and degree limits. Key concepts include the relationship where the sum of all vertex degrees equals twice the number of edges (2|E|). The session covers two primary problem types: finding maximum vertices given a minimum degree constraint and finding minimum vertices given a maximum degree constraint. The instructor applies inequalities to bound the number of vertices, ensuring results are rounded appropriately for integer solutions.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor begins by addressing a problem asking for the maximum number of vertices in a simple graph with 35 edges where each vertex has a degree of at least 3. The on-screen text displays the question: 'Q Maximum no of vertex in a simple graph with 35 edges and degree of each vertex is at least 3 is ____?'. The instructor applies the Handshaking Lemma, calculating the sum of degrees as 35 * 2 = 70. To find the upper bound for vertices, they divide this sum by the minimum degree (3), resulting in 70/3. The calculation is shown as '20 / 3' on screen, which the instructor rounds down to find the maximum possible integer vertices. The final answer is circled as 23, though the arithmetic shown suggests a discrepancy or specific rounding logic used in class.

  2. 2:00 – 2:25 02:00-02:25

    The video transitions to a second problem asking for the minimum number of vertices possible in a simple graph with 41 edges where each vertex has a degree of at most 5. The text on screen reads: 'Q Minimum number of vertices possible in a simple graph if 41 edges and degree of each vertex is at most 5?'. The instructor calculates the total degree sum as 41 * 2 = 82. They set up an inequality where the maximum degree (5) times the number of vertices (|V|) must be at least 82, written as '5 x |V| >= 82'. Solving for |V| gives approximately 16.4, which is displayed as '< 16.4'. Since vertices must be whole numbers, the instructor rounds up to conclude the minimum number of vertices is 17.

The lecture effectively demonstrates the practical application of the Handshaking Lemma for bounding graph parameters. The instructor consistently uses the formula sum(degrees) = 2 * edges to establish a total degree budget. For maximum vertex counts, the strategy involves dividing this budget by the minimum allowed degree per vertex and rounding down. Conversely, for minimum vertex counts, the instructor divides the budget by the maximum allowed degree and rounds up. This approach ensures that the resulting integer vertex count satisfies the given edge and degree constraints simultaneously.

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