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Python Fundamentals: Variables, Data Types, and Control Flow

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Keywords and identifiers are fundamental elements in programming languages used to define variables, functions, and other constructs, with keywords being reserved words that have special meanings, and identifiers being names given to user-defined entities.

Comments in programming serve the essential purpose of making the source code more understandable and maintainable by providing textual annotations that explain the logic, purpose, or any additional information about the code. They help programmers and collaborators to read, debug, and update the code efficiently without affecting its execution.

There are two main types of comments:
- Single-line comments start with specific symbols like // in languages such as C, Java, and JavaScript, and they... Continue reading "Python Fundamentals: Variables, Data Types, and Control Flow" »

Core Concepts in AI, Machine Learning, and Industrial Automation Systems

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Linear Regression Fundamentals

In regression, a set of records containing X and Y values is used to learn a function. This learned function can then be used to predict Y from an unknown X. In regression, we aim to find the value of Y, so a function is required which predicts Y given X. Y is continuous in the case of regression.

Here, Y is called the criterion variable and X is called the predictor variable. There are many types of functions or models which can be used for regression. The linear function is the simplest type of function. Here, X may be a single feature or multiple features representing the problem.

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Applications of Linear Regression in AI

  • Predictive Analysis: Forecasting sales, stock prices, or house prices based on historical data.
... Continue reading "Core Concepts in AI, Machine Learning, and Industrial Automation Systems" »

Dijkstra's Algorithm in C: Code & Explanation

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Dijkstra's Algorithm in C

This code implements Dijkstra's algorithm to find the shortest path from a source vertex to all other vertices in a graph represented as an adjacency matrix. The program reads graph data from an input.txt file and writes the results to an output.txt file.

Code Implementation


#include <stdio.h>
#include <limits.h>
#include <stdbool.h>

#define MAX_VERTICES 100

// Function to find the vertex with minimum distance
int minDistance(int dist[], bool visited[], int vertices) {
    int min = INT_MAX, min_index;

    for (int v = 0; v < vertices; v++)
        if (!visited[v] && dist[v] <= min) {
            min = dist[v];
            min_index = v;
        }

    return min_index;
}

// Dijkstra'
... Continue reading "Dijkstra's Algorithm in C: Code & Explanation" »

Data Structures: Queues, Trees, Graphs, and Searching Algorithms

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Understanding Data Structures and Algorithms

8. Queues: FIFO Operations

A queue is a linear data structure that follows the First-In, First-Out (FIFO) principle. The element inserted first will be removed first, similar to people waiting in a line. It has two primary operations:

  • enqueue(): Adds an element to the rear of the queue.
  • dequeue(): Removes an element from the front of the queue.

Enqueue Operation Algorithm (Array-based):

  1. Check if the queue is full (rear == size - 1).
  2. If not full, increment rear.
  3. Insert the new element at queue[rear].

Example:

if (rear == size - 1)
    printf("Queue Overflow");
else {
    rear++;
    queue[rear] = value;
}

Dequeue Operation Algorithm:

  1. Check if the queue is empty (front > rear).
  2. If not empty, retrieve the element
... Continue reading "Data Structures: Queues, Trees, Graphs, and Searching Algorithms" »

Fundamental Computer Science Concepts & Algorithms

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Arithmetic Progressions (AP)

Sum of terms = n[(1st term + last term)]/2

Geometric Progressions (GP)

Sum of terms = [1st term(1 - quotientn)/(1 - quotient)] (Swap positions of 1 & quotient if quotient > 1)

Logarithms

  • loga(x/y) = logax - logay
  • logaxn = nlogax
  • logab = (logcb/logca)

Permutations

For a set of n objects: The total number of permutations is n!

For arranging 'r' objects from a set of 'n' objects: The number of permutations is nPr = n! / (n-r)!. (e.g., ways to arrange 3 objects from a set of 5 is 5 * 4 * 3, since there are 5 possibilities for the first object, followed by 4, then 3.)

Combinations

For selecting 'r' objects from a set of 'n' objects: The number of combinations is nCr = n! / (r! * (n-r)!). (Divide by r! since there are r! ways

... Continue reading "Fundamental Computer Science Concepts & Algorithms" »

C Programming Concepts: Arrays, Functions, Structures, and Stacks

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1. Arrays: Definition, Types, and Implementation

An array is a collection of elements of the same data type stored in contiguous memory locations. It is used to store multiple values in a single variable and can be accessed using index numbers. The indexing in an array starts from 0. Arrays help manage and process data efficiently, especially when dealing with large volumes of similar data.

Types of Arrays Based on Dimensions

  • One-Dimensional Array: It stores data in a linear list format.
  • Multi-Dimensional Array: It stores data in matrix form (like 2D, 3D arrays), which is useful in applications like image processing and tables.

Types of Arrays Based on Memory Allocation

  1. Static Array:

    The size of the array is fixed at compile-time. Memory is allocated

... Continue reading "C Programming Concepts: Arrays, Functions, Structures, and Stacks" »

Java AWT Architecture: Components, Events & Listeners

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Java AWT Architecture: Components and Events

The Abstract Window Toolkit (AWT) is Java's original platform-dependent windowing, graphics, and user interface (UI) toolkit.

AWT Class Hierarchy

🖼️ The core of the AWT is structured around a few key classes, all of which inherit from the Object class.

1. Component Class

The Component class is the root of all AWT UI elements. A Component is an object with a graphical representation that can be displayed on the screen and can interact with the user. Examples of components include buttons, text fields, and scrollbars.

  • Key capabilities:
    • Defining visual appearance and behavior
    • Handling events (user input)
    • Drawing and painting

2. Container Class

A Container is a special type of component that can hold and organize... Continue reading "Java AWT Architecture: Components, Events & Listeners" »

Mastering Program Flow: Conditional and Iteration Structures

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Conditional Control Structures

Conditional control structures dictate the flow of execution by allowing specific blocks of code to run only when certain conditions are met.

1. The If Statement

The If statement executes a block of code only if the specified condition evaluates to true. Otherwise, the block is skipped entirely.

Syntax:

if (condition) {
    // statements (If Block)
}
// other statements

Note: A flow chart typically illustrates the execution path based on the condition.

2. The If-Else Statement

If the condition is true, the If block is executed. If the condition is false, the alternative Else block is executed.

Syntax:

if (condition) {
    // statements (If Block)
} else {
    // statements (Else Block)
}

3. The Else-If Ladder Statement

The... Continue reading "Mastering Program Flow: Conditional and Iteration Structures" »

Understanding Binary Adders and Race Conditions in Flip-Flops

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Binary Parallel Adder

A binary parallel adder is a digital circuit that adds two binary numbers in parallel, meaning all bits are added simultaneously. It typically consists of full adders arranged in parallel, with each full adder adding corresponding bits from the two input numbers.

BCD Adder

A BCD (Binary Coded Decimal) adder is a specific type of binary parallel adder designed to add two BCD numbers. BCD numbers are decimal digits encoded in binary, where each decimal digit is represented by its 4-bit binary equivalent.

Truth Table for a 4-bit BCD Adder

Here's the truth table for a 4-bit BCD adder:


Diagram


In the truth table:

  • A3 A2 A1 A0 represents the first BCD number (A).
  • B3 B2 B1 B0 represents the second BCD number (B).
  • Cin represents the carry-
... Continue reading "Understanding Binary Adders and Race Conditions in Flip-Flops" »

Essential Algorithms and Data Structures: A Quick Reference

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Essential Algorithms and Data Structures

Longest Increasing Subsequence (LIS):

  • Subproblem: dp[i] = length of LIS ending at index i
  • Recursion: dp[i] = max(dp[j] + 1 for j < i and arr[j] < arr[i])
  • Base case: dp[i] = 1 (every element is a subsequence of length 1)
  • Time Complexity: O(n^2), O(n log n) with binary search optimization.

Longest Alternating Subsequence (LAS):

  • Subproblem: dp[i][0] (increasing), dp[i][1] (decreasing)
  • Recursion: dp[i][0] = max(dp[j][1] + 1 for j < i and arr[j] < arr[i]), dp[i][1] = max(dp[j][0] + 1 for j < i and arr[j] > arr[i])
  • Base case: dp[0][0] = 1, dp[0][1] = 1
  • Time Complexity: O(n^2)

0/1 Knapsack Problem:

  • Subproblem: dp[i][w] = maximum value for the first i items and weight limit w
  • Recursion: dp[i][w] = max(
... Continue reading "Essential Algorithms and Data Structures: A Quick Reference" »