IEEE

Unveiling Blockchain Transactions Insights: Behavior Anomaly Detection via Relational Mechanisms

Abstract: Blockchain technology has evolved from its initial use in decentralized payments to encompass smart contracts and applications across multiple domains, propelling the digital transformation ...
IEEE

Machine Learning-Based Anomaly Detection of Correlated Sensor Data: An Integrated Principal Component Analysis-Autoencoder Approach

Abstract: This research proposes a lightweight hybrid approach for anomaly detection in correlated IoT sensor data, combining PCA for fast monitoring and Autoencoders for deeper analysis. Validated on ...
Phys.org

MicroBooNE detector excludes electron neutrino cause of MiniBooNE anomaly

A recent Physical Review Letters publication presents a thorough analysis of MicroBooNE detector data, investigating the anomalous surplus of neutrino-like events detected by the preceding MiniBooNE ...
Rigzone

How is AI used in oilfield operations?

Production Optimization, time-series ML, control Gas-lift/ESP setpoints, choke control 2–7% oil uplift; 20–40% downtime cut ...
Frontiers

Rethinking drug safety signal detection and causality assessment in the age of AI: the risks of incomplete data and biased insights

Artificial Intelligence (AI) is a term used for systems that can perform humanlike cognitive functions like learning, perception, interpretation and problem solving. AI systems learn and improve by ...
Scientific Research Publishing

Kea, K., Han, Y. and Kim, T.-K. (2023) Enhancing Anomaly Detection in Distributed Power Systems Using Autoencoder-Based Federated Learning. PLOS ONE, 18, e0290337.

ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...