Hacker

Stablecoin Fraud Detection in Cryptocurrency How Algorithms Can Identify Risk Before It Becomes Loss

Sivakumar is an enterprise architect with 20+ years delivering secure cloud and AI/ML systems in retail and fintech. Stablecoins were created to solve one of crypto’s biggest problems: volatility. A ...
IEEE

Integrating Two-Tier Optimization Algorithm With Convolutional Bi-LSTM Model for Robust Anomaly Detection in Autonomous Vehicles

Abstract: Industrial development has changed vehicles of traditional into autonomous vehicles (AVs). AVs play a significant role since they are measured as a vital module of smart cities. The AV is an ...
Visual Studio Magazine

Data Anomaly Detection Using a Neural Autoencoder with C#

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...
leewayhertz

Anomaly detection in fraud prevention: Benefits, development and future trends

The digital age has ushered in a new era of convenience and opportunity. However, it has also opened doors for malicious actors, leading to a surge in fraudulent activities across various sectors.
C&EN

Fault Diagnosis Method for Lithium-Ion Battery Packs in Real-World Electric Vehicles Based on K-Means and the Fréchet Algorithm

Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan430068, P. R. China Hubei Engineering Research Center for Safety Monitoring ...
Frontiers

Automated bow shock and magnetopause boundary detection with Cassini using threshold and deep learning methods

Two algorithms set for automatic detection of bow shock (BS) and magnetopause (MP) boundaries at Saturn using in situ magnetic field and plasma data acquired by the Cassini spacecraft are presented.
IEEE

Traffic Anomaly Detection and Video Summarization Using Spatio-Temporal Rough Fuzzy Granulation With Z-Numbers

Abstract: Existing traffic video summarization algorithms are capable of detecting one-class (i.e., collision) anomaly and cannot handle uncertainty issues arising between two-class anomalies, such as ...
Frontiers

Power Consumption Predicting and Anomaly Detection Based on Transformer and K-Means

With the advancement of technology and science, the power system is getting more intelligent and flexible, and the way people use electric energy in their daily lives is changing. Monitoring the ...