Vultron is a protocol for Coordinated Vulnerability Disclosure

Vulnerability-Lookup facilitates quick correlation of vulnerabilities from various sources, independent of vulnerability IDs, and streamlines the management of Coordinated Vulnerability Disclosure (CVD).

BTCUSDT funding rate and spot/perp CVD Telegram bot with integrated 4H charting.

Content for the CERT Guide to Coordinated Vulnerability Disclosure

Color vision deficiency simulation for LaTeX

Gementee CVD and bugbounty

A Python client for the Global CVE Allocation System.

📊 Extract 30+ trading metrics (CVD, VWAP, Imbalance, Exhaustion, Large Trades) from Bybit BTC/USDT order book and trade data. Built with Polars for 10x speed. Kaggle-ready pipeline processes 245 days in 4-5 hours.

Real-time crypto order book heatmap with quant metrics. Multi-exchange: Binance, OKX, Bybit. Index α, CVD, Delta visualization.

An advanced machine learning application that predicts heart disease risk using XGBoost. Built with Streamlit and trained on over 300,000 US health records, achieving 91.5% prediction accuracy.

This repository contains an Exploratory Data Analysis (EDA) project using a dataset related to Cardiovascular Disease (CVD) Risk.This dataset comprises 1,529 patient samples collected Bangladesh, 2025

Testing out pulling the CVD Prevent data out an putting it into the PowerPoint template

This script uses a CNN in TensorFlow to classify chest X-ray images into “COVID,” “Normal,” and “Pneumonia.” It trains the model for 10 epochs and evaluates performance with accuracy plots, displaying predictions on test images.

This repo includes the pipeline used to link and curate CVD PREVENT audit data to HES and death registration data into two tables. These are subsequently sent to OHID for analysis and publication.

Machine learning project predicting cardiovascular disease using the Framingham Heart Study dataset. Explores various models, preprocessing techniques, and hyperparameter tuning to optimize accuracy.

Predicting heart disease risk using combined UCI data and machine learning

Database of CFD modeling for growth of AlN, TiN, SiC and CrC

Centroidal Voronoi Diagram of a mesh's surface using an iterative discrete clustering algorithm on graphs.

This demo is developed using PIC18-Q10 family MCU and Curiosity Nano development board. The demo demonstrates the usage of ADCC with hardware CVD technique and PWM peripherals of PIC18F47Q10 MCU to control DC motor through capacitive touch interface.