from Windows PowerShell

This repository implements the research pipeline for the from Windows PowerShell project, developed by the Runtime-Slayers research group.

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📊 Pipeline Architecture

The flowchart below visualizes the methodology and execution sequence implemented in this project:

graph TD
    subgraph Data Engineering
        A["Raw Input Datasets"] --> B["Data Preprocessing & Normalisation"]
        B --> C["Feature Engineering & Selection"]
    end
    subgraph Model Architecture
        C --> D["Multi-Model Comparative Training"]
        D --> E["Validation via Stratified CV"]
        E --> F["Hyperparameter Tuning & Threshold Optimization"]
    end
    subgraph Inference & Metrics
        F --> G["Final Classification / Regression Performance Reports"]
    end

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🔍 Abstract & Research Context

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📊 Key Evaluation Metrics

See the detailed project report for full experimental tables.

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📁 Repository Structure

The project directory consists of the following core structures:

• code/ — Pipeline execution scripts and model training modules
• figures/ — Plots, charts, and visualizations generated by the pipeline
• validation/ — Automated test metrics and results
• page_2.png
• page_3.png
• cognitive_core
• outputs_kaggle
• tools
• kaggle_kernel_runs
• page_4.png
• page_5.png
• pytest.ini
• requirements.txt
• ablation_results.json
• page_7.png
• G-NeSAI_Demonstration.ipynb
• page_6.png
• project_content.txt
• ocr_extract.py
• kaggle_kernel_ablation
• experiments
• training
• training_pipeline.py
• tests
• check_dependencies.py
• perception_layer
• extract_images.py
• outputs_kaggle_ablation
• page_10.png
• neuro_symbolic
• .gitignore
• execution
• scripts
• .github
• extract_pdf.py
• eval_model.py
• README_KAGGLE.md
• kaggle_kernel_full
• page_8.png
• kaggle_kernel
• outputs
• data_factory
• notebooks
• extract_pdf2.py
• paper.pdf — Compiled research manuscript
• README.md — Project documentation and setup guide

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🚀 Setup and Usage

Prerequisites

• Python 3.8 or higher
• Pip package manager

Installation

1. Clone this repository:

   git clone https://github.com/Runtime-Slayers/Project-Aether.git
   cd Project-Aether

2. Install dependencies:

   pip install -r requirements.txt

Running the Analysis

To run the primary analysis pipeline and regenerate all models, figures, and metrics:

python code/*.py

(Look in the code/ directory for specific pipeline execution files)

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📄 License and Copyright

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

© 2026 Runtime-Slayers / Bhavanam Rajendra Reddy et al. All rights reserved.