Christopher Ugbong Akeke, Oluwadayo Mafolasere Olaniyi, Busola Motunrayo Olawale, Utin Nyimeobong Archibong & Seun Michael Oyekunle·Asian Journal of Research in Computer Science·2026
The accelerating adoption of artificial intelligence across United States healthcare systems has intensified concerns over cyber resilience, data privacy, and regulatory compliance, yet existing governance frameworks remain fragmented and difficult to compare. This study addresse...
Open access
Research Article10.9734/ajrcos/2026/v19i7880
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
Christopher Ugbong Akeke, Tunbosun Oyewale Oladoyinbo, Moses Abuobelye Akeke, Asmau Abubakar Abdulmalik & Michael Bengie-Ungwubel Ala·International Neuropsychiatric Disease Journal·2026
Adolescent mental health issues are increasing, with many students reporting sadness and anxiety. Schools can help identify early warning signs, but limited resources often delay timely support, especially in underserved areas. This study explored predictive analytics as a school...
Open access
Research Article10.9734/indj/2026/v23i3559
This study examines how school psychologist workforce capacity influences the timeliness of Autism Spectrum Disorder (ASD) diagnosis and access to intervention services within Title I schools in the United States. Using secondary data obtained from the National Center for Educati...
Open access
Research Article10.9734/indj/2026/v23i3558
Adeyemi Adebukunola Ishekwene, Christopher Ugbong Akeke, Akinde Michael Ogunmolu, Busola Motunrayo Olawale & Cornelia Ifeoma Ejoh·Journal of Engineering Research and Reports·2026
Critical infrastructure operators increasingly deploy artificial intelligence (AI) to detect degradation, predict failures, optimise maintenance, identify cyber anomalies and support operational decisions. These capabilities create a plausible route to higher availability, reliab...
Open access
Research Article10.9734/jerr/2026/v28i81986
This study examines the ethical and secure deployment of generative artificial intelligence in enterprise environments, with emphasis on innovation, data privacy, and risk governance. It addresses the gap between the rapid organisational adoption of generative AI systems and the...
Open access
Research Article10.9734/jerr/2026/v28i71943
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
Oluwadayo Mafolasere Olaniyi, Suleiman S. Abba, Christopher Ugbong Akeke, Faith Hauwa Oluwapamilerin Kolo & Moses Abuobelye Akeke·Journal of Engineering Research and Reports·2026
Autonomous AI agents powered by large language models increasingly operate with unrestricted communication and publishing capabilities, creating critical security vulnerabilities through memory poisoning attacks that corrupt long-term agent memory and propagate falsified outputs...
Open access
Research Article10.9734/jerr/2026/v28i51894
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
Artificial intelligence systems increasingly mediate consequential decisions in credit allocation, healthcare triage, employment screening and public administration, yet the data underpinning these decisions is frequently incomplete, mislabelled, stale or quietly altered as it mo...
Open access
Research Article10.9734/ajrcos/2026/v19i8892