🚀 Project 2

Precision Salting, Smoothing, Research Analysis, and Fingerprinting

Built using Java, AI, Flask, and Octave

---

📋 Table of Contents

• 🚀 Overview
• 📂 Directory Structure
• 🧩 Part 1: PSS System
  • ✨ 1.1 Java Plotter, Salter, and Smoother
  • 🧮 1.2 Octave-Based Smoother
  • 📈 1.3 JFreeChart & JCommon Visualization
  • 🧠 1.4 Special Version: Nimbus AI for PSS
• 📚 Part 2: Dataset Research Paper
• 🔍 Part 3: HashMapping Systems
  • 🧩 3.1 SimpleHashMap
  • 🔒 3.2 Fingerprinting via Hash Mapping
• ⚙️ Setup Instructions
• 🛠️ Technologies Used
• 🚀 Future Enhancements
• 📬 Contact

---

🚀 Overview

This project explores the fusion of Java development, AI-powered data analysis, statistical research, and cryptographic hash mapping:

• PSS (Plotting, Salting, Smoothing) using classic Java, Octave, and JFreeChart.
• Research Dataset Analysis documented in a formal academic paper.
• Hash Mapping & Fingerprinting system built in Java and Flask.

---

📂 Directory Structure

/StatsLibrary/       → Java classes: Plotter, Salter, Smoother + Documentation
/FormulaSheet/       → Statistical formula references
/DatasetResearch/    → Research paper and CSV dataset
/FingerprintingApp/  → Flask web app for fingerprint visualization
/SimpleHashMap/      → Custom Java HashMap implementation
/NimbusPSS/          → Special version of Nimbus AI optimized for PSS

---

🧩 Part 1: PSS System

✨ 1.1 Java Plotter, Salter, and Smoother

• Core classes: Plotter, Salter, Smoother
• Salting introduces controlled randomness.
• Smoothing applies moving averages for trend visualization.
• Visualized using Java's built-in libraries.

🧮 1.2 Octave-Based Smoother

• Alternative version using GNU Octave.
• Matrix-based smoothing.
• Mathematical validation of Java outputs.

📈 1.3 JFreeChart & JCommon Visualization

• Dynamic, polished chart generation.
• Professional .png graph exports.

🧠 1.4 Special Version: Nimbus AI for PSS

• Fine-tuned AI tool.
• Optimizes salting/smoothing parameters.
• Explains dataset behavior intelligently.

---

📚 Part 2: Dataset Research Paper

• 📄 Formal research paper analyzing real-world trends.
• 📊 CSV dataset included for analysis.
• ✍️ Academic APA citations.
• 🔍 Detailed visualization and statistical explanation.

---

🔍 Part 3: HashMapping Systems

🧩 3.1 SimpleHashMap

• Custom-built HashMap in Java.
• Collision handling, rehashing, and bucket exploration.

🔒 3.2 Fingerprinting via Hash Mapping

• Text transformed into colorful digital "fingerprints".
• Backend: Java + Python(Flask)
• Frontend: HTML, CSS, JS
• Visualizes predictable hash collisions intentionally.

---

⚙️ Setup Instructions

📦 Clone the Repository

git clone https://github.com/YourUsername/NimbusPSS.git
cd NimbusPSS

☕ Compile Java Code

javac -cp "lib/*" StatsLibrary/*.java

🐍 Install Python Dependencies

cd FingerprintingApp
pip install Flask Pillow

▶️ Run the Projects

• Run Java classes (PSS, SimpleHashMap).
• Start Flask server for Fingerprinting App.
• Open DatasetResearch/ folder for CSV and paper.

---

🛠️ Technologies Used

Technology	Purpose
Java 21	Backend development
Octave	Matrix-based smoothing
JFreeChart & JCommon	Advanced graphing
Python (Flask, PIL)	Fingerprinting web app
Nimbus AI	AI-powered smoothing optimizer
CSV Data	Research dataset for analysis

---

---

📬 Contact

---

🏁 Thank You for Visiting Project-2!

"Blending Traditional Logic with Modern Intelligence."