The Daily Pennsylvanian

From data analysis to pattern recognition: Here’s how Penn Medicine is using artificial intelligence

Across the University’s Health System, scientists are now using AI to enhance their understanding of biological systems and ...
Interesting Engineering

US researchers build fall-safe biped robots to advance real-world reinforcement learning

HybridLeg robots Olaf and Snogie use impact-safe design and self-recovery to enable scalable, real-world hardware ...
Devdiscourse

AI-driven rainfall forecasting shows major gains in predicting flood-triggering storms

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...
IEEE

Fall Detection Using Multiple Low-Resolution Thermopile Sensors and Machine Learning

Abstract: Automated fall detection enhances the safety of older adults and individuals with health conditions that make them prone to falling. One promising option is based on the detection and ...
Electronic Design

How Multi-Stage Detection Prevents Silent Data Corruption in AI Processors

GenAI and ML workloads are causing a ramp up in silent data corruption. Multi-stage detection with on-chip, AI-based telemetry offers smarter fault prevention. As transistor geometries shrink and ...
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 ...
Osprey Observer

Center 4Life Learning Fall Classes Open For Registration

Classes, field trips and fun learning are all part of the fall curriculum at the Center 4Life Learning. Lifelong learning is alive and thriving at the Center 4Life Learning campus in Sun City Center, ...
Scientific Research Publishing

Doshi-Velez, F. and Kim, B. (2017) Towards a Rigorous Science of Interpretable Machine Learning. arXiv: 1702.08608.

ABSTRACT: Purpose: The purpose of this study is to develop a scalable, risk-aware artificial intelligence (AI) framework capable of detecting financial fraud in high-throughput digital transaction ...
Scientific Research Publishing

Explainable Machine Learning in Risk Management: Balancing Accuracy and Interpretability ()

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...