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    ReTelect/README.md

    Majd Najeh | Software Engineer & Technical Architect

    Dedicated to mastering Low-Level Mechanics, Systems Engineering, and Automated Media Pipelines. My focus lies in bridging the gap between Algorithmic Efficiency and Scalable Application Design.

    🛠 Technical Ecosystem

    Core Engineering & Languages

    • Systems Programming: C (Manual Memory Management, Pointer Arithmetic, Data Structures).
    • Application Logic: Python 3.x (Advanced Scripting, Context Managers, Decorators), TypeScript.
    • Data Persistence: SQL (SQLite, PostgreSQL), Schema Design, Query Optimization.
    • Web Architecture: Node.js, React, Flask (RESTful API Design).

    Media & AI Engineering

    • Digital Signal Processing: Automated Audio Thresholding, Frequency Analysis (SNR Calculation).
    • Video Orchestration:FFmpeg (Complex Filtergraphs, Codec Optimization, Hardware Acceleration).
    • AI Integration: Speech-to-Text (STT) Pipelines, Natural Language Processing (NLP) for signal segmentation.

    DevOps & Environments

    • OS: Linux Power User (Pop!_OS), Shell Scripting (Bash/Zsh), Terminal-Centric Workflows.
    • Version Control: Git (Branching Strategies, Rebase Workflows).

    📌 Architectural Case Studies

    🎬 Silent Cutter (Audio-Driven Video Processor)

    Technical Objective: Eliminate manual editing latency through algorithmic audio analysis and automated frame extraction.

    • Algorithmic Logic: Implemented a signal-to-noise ratio (SNR) analysis to detect and isolate "dead air" intervals within raw media streams.
    • Pipeline Engineering: Developed a multi-stage workflow leveraging Audio Extraction, VAD (Voice Activity Detection), and FFmpeg Concatenation.
    • Optimization: Utilized non-linear editing (NLE) logic to allow for manual fine-tuning, maintaining state between automated processing and user adjustments.

    🗳️ Tideman (Ranked-Choice Voting System)

    Technical Objective: Solve the Condorcet Paradox using graph theory.

    • Logic: Developed a Recursion-based Cycle Detection algorithm in C.
    • Complexity: Managed Adjacency Matrix representations to ensure the "strength of victory" is prioritized without creating locked loops in a directed graph.

    🕵️ Imposter Detector

    Technical Objective: Pattern recognition and anomaly detection within data streams.

    • Focus: Optimized Time Complexity for real-time analysis of large input sets to identify logical inconsistencies.

    🎓 Certifications

    • HarvardX CS50x: Introduction to Computer Science (Memory, Algorithms, Web Security).

    📫 System Interfacing

    Pinned Loading

    1. tidemantidemanPublic

      C

    2. imposter-detectorimposter-detectorPublic

      Python

    3. AisilentcutterAisilentcutterPublic

      TypeScript

    4. HarborPluginMangaHarborPluginMangaPublic

      Automated Multisrc Manga/Manhwa Plugin Generator for Harbor App.

      JavaScript 2