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Reskilling And Retraining The Water Technology Workforce: An Agentic Generative Ai Framework For Water Purification, Nano‑Mems, And Curriculum Development, Satyadhar Joshi, Noor Zulfiqar
Reskilling And Retraining The Water Technology Workforce: An Agentic Generative Ai Framework For Water Purification, Nano‑Mems, And Curriculum Development, Satyadhar Joshi, Noor Zulfiqar
Harrisburg University Other Works
The rapid digitalization of water infrastructure is bringing artificial intelligence, advanced sensing, and membrane materials science into routine water treatment practice. At the same time, utilities, regulators, and training institutions face a persistent workforce challenge: many operators, engineers, and managers are being asked to adopt data-driven tools without a coherent educational pathway that links AI literacy to real treatment workflows. This article synthesizes recent literature on agentic generative AI, reinforcement learning, smart sensing, nano-enabled membranes, and digital twins for water systems, then translates those developments into a structured reskilling model for the water sector. The proposed framework is organized around …
Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi
Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi
Harrisburg University Other Works
This paper conducts a comparative analysis of U.S. and Chinese frameworks for AI literacy and adoption, with focus on agentic AI and Artificial General Intelligence (AGI) systems capable of autonomous reasoning and execution. We examine national policies, educational integration, governance structures, and technological roadmaps, employing both qualitative review and quantitative modeling. Mathematical formulations include multi-dimensional literacy scoring, Bass diffusion models for adoption dynamics, risk assessment functions, regulatory effectiveness indices, competitiveness metrics, and optimization frameworks for resource allocation. Our analysis reveals divergent paradigms: the U.S. Favors decentralized, innovation-driven approaches with emphasis on interoperability and public-private collaboration; while China pursues centralized, state-led …