IEEE

Empirical Analysis for Crime Prediction and Forecasting Using Machine Learning and Deep Learning Techniques

Abstract: Crime and violation are the threat to justice and meant to be controlled. Accurate crime prediction and future forecasting trends can assist to enhance metropolitan safety computationally.
IEEE

Hybrid intrusion detection system based on Random forest, decision tree and Multilayer Perceptron (MLP) algorithms

Abstract: With the rapid increase in network intrusions, applying an active network intrusion defense is more important than ever before. Different learning algorithms have been combined to achieve ...
GitHub

Yan-K Toolkit

The Yan-K series was originally released in 2015 as free scripts, developed to automate my animation workflow and practice coding. Over the past decade, these scripts have been used by many motion ...
GitHub

DDoS Defense: A Multiclass and Multidimensional Detection System with Diverse Machine Learning Models

This project is focused on building a system to detect and classify DDoS (Distributed Denial of Service) attacks using the CICDDoS2019 dataset. The goal is to develop a multiclass classification model ...
Frontiers

Predicting the rapid progression of coronary artery lesions in patients with acute coronary syndrome based on machine learning

Purposes: Rapid coronary artery lesions (RCAL) are strongly linked to major adverse cardiovascular events in patients with acute coronary syndrome (ACS). This work developed a public online prediction ...
Frontiers

Construction of predictive models for contralateral occult thyroid carcinoma and central lymph node metastasis in unilateral papillary thyroid carcinoma using machine learning

Background: This study aimed to develop predictive models based on preoperative clinicopathological and imaging features to accurately assess the individual risk of contralateral occult thyroid ...