SPPU Third Year First Sem - Computer Network Lab Codes + Study Plan

Hamming Code in Computer Networking. Error detection and correction using hamming code in C programming.

Sequential Decoder (Fano's Algorithm) in Matlab for Data Communication and Networking

PyEDCR is a metacognitive neuro-symbolic method for learning error detection and correction rules in deployed ML models using combinatorial sub-modular set optimization

Hamming code encoder and decoder in C

Hamming-code implementation in Python

A robust and comprehensive translation system featuring a versatile backend pipeline that integrates MT with automatic error detection and an enriched UI that provides an intuitive platform for user corrections.

Implements Number Theory for error detection and correction

CAO/COA Algorithms

A fault-tolerant, pipelined RISC-V processor system implemented in Verilog, featuring Triple Modular Redundancy (TMR), SECDED memory protection, error injection, and robust recovery mechanisms. Designed for research, education, and prototyping of reliable digital systems.

Hamming Code in Computer Networking. Error detection and correction using hamming code in C programming.

🗝️ A proof of concept Hamming SEC simulator

A Java implementation of Error Detection in data link layer

Implementation of Max problems: Grid, SIB, MASIB

Server-Client data exchange using TCP and UDP protocols

Server-Client data exchange using virtual modem

A Clojure/ClojureScript implementation of an error-correcting coding scheme for alphanumeric data.

Hammer es una aplicación de línea de comandos escrita en Java 8 que codifica cualquier flujo de bytes a un fichero de acuerdo a un código Hamming ampliado (3, 2) sistemático, y luego permite decodificarlo, corrigiendo errores que pudiese haber.

TranslationCorrect is a unified framework for MT annotation with predictive error detection and an intuitive post-editing interface, shown through a human study to reduce cognitive workload compared to traditional methods.

Using Emergent, designed a face classifier based on emotion and gender, as well as a network designed to analyze inhibitory neurons behavior compared to excitation neurons.

Telekomunikacja i przetwarzanie sygnałów, FTIMS, Politechnika Łódzka, semestr 4

Data mining project analyzing prescription patterns using ECLAT, PyECLAT, and FP-Growth. Features preprocessing, exploratory analysis, and saved models for integration into pharmacy and doctor interfaces. Scalable approach for large datasets with over 239,000 entries, uncovering trends and associations in prescription data

🔢 💻 Software developed as a logical design course project. It consists of a base converter system, an NZRI encoder, a Hamming encoder and its bit error detector.

No description provided.

Programs of Computer-Networks Lab, UG Sem 6

Simple example of one transmission error detection.