Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks.

Underwater environmental exploration using sensor nodes has emerged as a critical endeavor fraught with challenges such as localization errors, energy, and costs attributed to the dynamic nature of underwater environments. This paper proposes a KNN-based cost-efficient machine-learning algorithm aimed at optimizing underwater context acquisition with sensor nodes. By addressing existing localization challenges, the algorithm minimizes localization errors, energy consumption and Time costs while significantly enhancing localization accuracy to 99.

Fabrication of pH responsive hydrogel blends of chondroitin sulfate/pluronic F-127 for the controlled release of ketorolac: its characterization and acute oral toxicity study.

Objective: Ketorolac tromethamine (KT), selected as a model drug, is used in management of moderate to severe acute pain. It has a short half-life (∼5.5 h) and requires frequent dose administration when needed for longer period of time.