Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

Abstract: Class imbalance occurs frequently in machine learning, particularly in binary classification tasks where the majority class has a significantly larger number of samples than the minority ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. With the rise of deep learning, researchers have begun to use ...

The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by security ...

ABSTRACT: Heart disease continues to be a major global cause of death, making the development of reliable prediction models necessary to enable early detection and treatment. Using machine learning to ...

Abstract: In this work, we propose a novel approach that uses an ensemble of deep neural networks (DNN) and convolutional neural networks (CNN) to predict the drag coefficient of small, ...

This study addresses the challenges of uncertainty in wave simulations within complex and dynamic ocean environments by proposing a reinforcement learning-based model ensemble algorithm. The algorithm ...

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 ...