With the growing complexity of modern cyber threats, proactive defense has become essential for securing digital infrastructures. Machine Learning (ML) models offer powerful capabilities for predictin...
Diagnosing skin cancer (melanoma vs. non-melanoma) accurately remains challenging, particularly in differentiating subtypes in clinical settings. Current Deep Learning (DL) models are limited by uni-m...
Diagnosing anemia accurately remains challenging, particularly in differentiating subtypes (e.g., Iron Deficiency vs. Thalassemia) in decentralized settings. Current Deep Learning (DL) models are limi...
Enterococcus Faecalis poses a significant clinical challenge as it can form persistent biofilms and exhibits multidrug resistance, with the Enterococcal surface protein (Esp) acting as a vital virulen...
Marine ecosystems integrate biotic and abiotic processes increasingly disrupted by human activities. We present a Petri net–based computational framework integrated with process mining to quantify res...
Enterococcus faecalis, a Gram-positive opportunistic pathogen, causes severe hospital-acquired infections and exhibits high antibiotic resistance due to biofilm formation. Gelatinase (GelE), a key zin...
Staphylococcus aureus is a highly virulent Gram-positive bacterium of global concern due to its potent virulence factors and antimicrobial resistance, causing severe morbidity and mortality. This stud...
Enterococcus faecalis, a gram-positive bacterium linked to hospital-acquired infections, exhibits strong biofilm formation mediated by the Enterococcus Surface Protein (Esp), contributing to its persi...
The concept of Big Data refers to massive, complex, and rapidly growing datasets that cannot be handled using traditional database systems. Big Data provides organizations with the ability to extract ...
The Internet of Things (IoT) represents a technological revolution that enables physical devices to communicate and interact over the internet. This paper explores the architecture, applications, adva...
Machine Learning (ML) has emerged as a transformative technology at the intersection of computer science, statistics, and artificial intelligence. It enables systems to learn patterns from data and im...
Data Science is an interdisciplinary domain that combines statistical analysis, computer science, and domain expertise to extract meaningful insights from structured and unstructured data. The rapid e...
Anemia, a global health concern affecting over 2 billion people, is traditionally diagnosed through invasive and resource-intensive blood tests. These methods can be a hassle, expensive, and sometimes...
