Learn how to collect WiFi traffic data, analyze retransmissions, and apply machine learning to predict packet retransmissions in this COMP4336 project tutorial.
Learn run-length encoding (RLE) for image compression through hands-on examples with pixel art. Master encoding, decoding, hex conversion, and menu-driven programs in this comprehensive tutorial.
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Explore how abstraction layers in computer architecture impact power, performance, and area. This tutorial covers ISA, microarchitecture, and tradeoffs using multiplication examples, with timely analogies to AI accelerators and gaming consoles.
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Learn how to build a Python program that calculates total home square footage using functions and function composition. This guide walks through prompt_user, room_square_feet, and main functions with clear examples.
Learn how to build a modular Java application using the MVC pattern, interfaces, and dependency injection by creating a Munro quiz app. Hands-on tutorial for COMPSCI5092.
Explore three advanced data structures—Fibonacci Heap, Van Emde Boas Priority Queue, and Splay Tree—and learn how to benchmark them with 10 million data points in Python. Includes complexity analysis, code setup, and plot interpretation.
advanced data structuresFibonacci HeapVan Emde BoasSplay Treebenchmarking algorithms
Learn how to write a robust heap consistency checker for your CMPSC473 malloc lab. This tutorial covers key invariants, debugging strategies, and code examples to help you ace the assignment.
Learn to use std::map and std::set by implementing an INI file parser and a Sudoku solver. Step-by-step tutorial with code examples, perfect for CSCI 340 students.
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Learn how to implement mapping and path planning for mobile robots using Webots and Python. This tutorial covers sensor integration, grid-based world representation, and the Wavefront Planner algorithm with hands-on examples.
Learn how to implement template functions using STL iterators to compute statistics, print formatted output, build histograms, and split ranges. This tutorial mirrors the core tasks of NIU CSCI 340 Assignment 2a with timely examples from esports and AI data pipelines.
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Learn how to compute query sensitivity under different neighboring dataset definitions and apply the Laplace mechanism for differential privacy, with step-by-step examples and real-world analogies from AI and data science.
