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

The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development ...

Integrating quantum computing into AI doesn’t require rebuilding neural networks from scratch. Instead, I’ve found the most effective approach is to introduce a small quantum block—essentially a ...

An end-to-end accident severity prediction project that predicts the seriousness of injury based on various features, using a multiclass classification model. A hybrid AI model for predicting failures ...

This project analyzes aviation accident data using machine learning to predict and prevent fatal accidents. By testing models like Linear Regression, Random Forest, and XGBoost, the study found ...

Introduction: Food price volatility continues to be a significant concern in Kenya's economic development, posing challenges to the country's economic stability. Methodology: This study examines the ...

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...

Abstract: This research introduces a new hybrid machine-learning model for optimizing smart greenhouse operations in response to worldwide food production demand. The model combines Random Forest (RF) ...

In this tutorial, we introduce a Jailbreak Defense that we built step-by-step to detect and safely handle policy-evasion prompts. We generate realistic attack and benign examples, craft rule-based ...

At PG&E’s weather lab in San Ramon, Scott Strenfel studies a huge digital map on the wall displaying temperatures, dew points and humidity levels across California. At a spot in Kern Hills outside of ...