Information privacy and data security governance increasingly depend on sustained human attention: employees must interpret warnings, follow changing policies, report anomalies, manage credentials, make disclosure decisions and repeatedly consent to data practices. Yet governance...
Open access
Research Article10.9734/ajrcos/2026/v19i8898
This study presents a hybrid federated learning and explainable artificial intelligence framework, termed RobustFL, designed to mitigate adversarial attacks in medical imaging while incorporating privacy-preserving mechanisms. Focusing on chest X-ray analysis, the research system...
Open access
Research Article10.9734/ajrcos/2026/v19i4852
The rapid growth of multimodal wearable devices has enabled continuous monitoring of physiological and behavioral patterns for home-based health applications. However, centralized data processing raises serious privacy concerns and limits real-time, interpretable insights. This s...
Open access
Research Article10.9734/ajrcos/2026/v19i4845
School psychologist shortages remain a critical challenge in high-need districts, where ratios often exceed 1:1,200, limiting timely mental health support for students. This desk-based study developed hybrid AI and telepsychology workforce models to address these shortages. A sys...
Open access
Research Article10.9734/ajrcos/2026/v19i6868
The rapid adoption of artificial intelligence (AI) in healthcare analytics has raised significant concerns regarding patient data privacy, security, and regulatory compliance. This study develops a Privacy-by-Design (PbD) data governance model tailored for AI-driven healthcare an...
Open access
Research Article10.9734/ajrcos/2026/v19i3835