Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Aapistie 5 A, 90220 Oulu, Finland Research Unit of Disease Networks, Faculty of Biochemistry and Molecular ...

aDepartment of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, Special Administrative Region, China ...

Reproductive toxicity is a concern critical to human health and chemical safety assessment. Recently, the U.S. Food and Drug Administration announced plans to assess toxicity with artificial ...

Abstract: Malicious software, commonly known as malware, takes advantage of anomalies in computer security to cause damage or illegal access. Recent advances in deep learning have enabled the ...

Beijing is taking an industrial policy approach to help its A.I. companies close the gap with those in the United States. By Meaghan Tobin Reporting from Taipei, Taiwan When OpenAI blocked China’s ...

Abstract: Malware detection in Android applications remains a critical challenge due to the increasing sophistication of cyber threats. This paper explores a novel approach for Android malware ...

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...

Fire is an important ecosystem process and has played a complex role in terrestrial ecosystems and the atmosphere environment. Sometimes, wildfires are highly destructive natural disasters. To reduce ...