This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...

Childhood asthma poses a significant threat to pediatric health, and traditional assessment methods are often inadequate in efficiency and accuracy. This study aims to develop a rapid assessment tool ...

Abstract: This article presents the design and implementation of a generic model for fault diagnosis in electrical distribution networks, based on the Support Vector Machine (SVM) algorithm. The ...

Google announced a new multi-vector retrieval algorithm called MUVERA that speeds up retrieval and ranking, and improves accuracy. The algorithm can be used for search, recommender systems (like ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...

Oracle Corp. today is rolling out the latest version of its Exadata database-optimized computing platform, claiming 55% better performance on vector searches used in artificial intelligence model ...

Abstract: Accurately categorizing medical information is crucial for determining effective cardiac treatment options, especially as the volume of data grows and feature selection becomes increasingly ...