This AI Agent Is Designed to Not Go Rogue

The new open source project IronCurtain uses a unique method to secure and constrain AI assistant agents before they flip ...

AI and Machine Learning in Digital Wallets: From Fraud Detection to Personalized Finance

AI transforms digital wallets from transaction processors into intelligent systems. Instead of enforcing fixed rules, machine learning models evaluate context like user behavior, device ...
Security Boulevard

There’s Always Something: Secrets Detection at Engagement Scale with Titus

TL;DR: Titus is an open source secret scanner from Praetorian that detects and validates leaked credentials across source code, binary files, and HTTP traffic. It ships with 450+ detection rules and ...
IEEE

Towards Wheat Rust Disease Classification using Different Machine Learning Approaches: A Systematic Literature Review

Abstract: This systematic literature review explores various machine learning (ML) approaches for the classification of wheat rust diseases, a significant threat to global food security. With the ...
chromatographyonline

Portable Electronic Nose with Machine Learning Enhances VOC Detection in Forensic Science

AI and ML are transforming forensic applications with e-nose systems, offering rapid, cost-effective analysis for volatile organic compounds. A 32-element MOS sensor array enhances e-nose forensic ...
EurekAlert!

Attention detection using EEG signals and machine learning: A review

An overview of attention detection using EEG signals, which includes six steps: an experimental paradigm design, in which the task and the stimuli are defined and presented to the subjects; EEG data ...
Scientific Research Publishing

Machine Learning-Based Outlier Detection in Long-Term Climate Data: Evidence from Burkina Faso’s Synoptic Network ()

Laboratoire de Matériaux et Environnement (LAME), Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso. In recent decades, the impact of climate change on natural resources has increased. However, ...
IEEE

Depression Analysis and Detection Using Machine Learning: Incorporating Gender Differences in a Comparative Study

Abstract: Depression is a significant mental health problem and presents a challenge for the machine learning field in the detection of this illness. This study explores automated depression ...