Client drift arising from non-independent and identically distributed (non-IID) data across participating clients remains one of the most critical obstacles to effective Federated Learning. The Scaffold algorithm, which ...

With the high mobile phone penetration and subsequent significant usage of mobile phone applications, mobile users have become prime targets of hackers. Secure Software Development (SSD) advocates incorporating security ...

Pediatric emergency cases need rapid systems that measure vital body parameters data, analyze and categorize emergency cases for precise action. Current systems use manual examination resulting in delayed medication, ...

Public organizations are adopting the use of electronic Human Resource Management (e-HRM), as it is regarded as a key catalyst for generating value for HRM processes. However, empirical evidence is scanty, particularly ...

Wireless Sensor Networks (WSNs) have emerged as a critical technology in diverse applications, ranging from environmental monitoring to precision agriculture. However, the inherent limitations of WSNs, such as constrained ...

Tomato leaf diseases significantly reduce crop yield; therefore, early and accurate disease detection is required. Traditional detection methods are laborious and error-prone, particularly in large-scale farms, whereas existing ...

Test case production is a crucial phase in the software testing lifecycle that consumes significant time, effort, and cost. As such, it is considered an optimization problem that can be addressed using metaheuristic ...

The widespread integration of Smart technologies into energy consumption systems has brought about a transformative shift in monitoring and managing electricity usage. The imbalanced nature of anomaly data often results ...

Artificial Intelligence (AI) is increasingly transforming Open, Distance, and e-Learning (ODeL) by enhancing personalization, automating assessments, and enabling immersive learning environments. This study employs a ...

The integrity and efficiency of modern energy grids are increasingly reliant on accurate anomaly detection within energy consumption data. However, class imbalance poses significant challenges, where normal consumption ...