Suchergebnisse

Intra-WBSN plays an important role in health monitoring, military and consumer electronics. It iscomposed of wireless bio-sensor nodes which are strategically placed on the body. Due to body posture movement, network topology of Intra-WBSN changes continuously. It plays a significant role in Intra-WBSN. In proposed Pm-EEMRP, network stability, energy efficiency and high throughput are the prime parametersfor body posture movement in which sensing informations from bio-sensor nodes are forwarded to relay nodes. Relay nodesare deployed in cloths, which aggregate these data and forward it to body network controller (BNC). It provides reliable and comfortable health monitoring. Through simulation, the proposed routing protocol provides better network stability, improved energy efficiency and high throughput in comparison to conventional routing schemes.

A Child being considered as the wealth as well as asset of the nation primarily lies below the age of eighteen years. The evil of Pornography of children in India has been rising since decades. The challenges related to sexual abuse as well as exploitation of the children in the nation is getting bigger with the days and years passing by. The impact of pandemic on the pornographic industry has lead to a total rise of 95% in the child pornographic content available through various online portals and websites. The Government plays a role of guard by further taking national as well as international measures in order to tackle this evil of pornography of children.

AbstractManaged aquifer recharge (MAR) replenishes groundwater by artificially entering water into subsurface aquifers. This technology improves water storage, reduces over-extraction, and ensures water security in water-scarce or variable environments. MAR systems are complex, encompassing various components such as water storage, soil, meteorological factors, groundwater management (GWM), and receiving bodies. Over the past decade, the utilization of machine learning (ML) methodologies for MAR modeling and prediction has increased significantly. This review evaluates all supervised, semi-supervised, unsupervised, and ensemble ML models employed to predict MAR factors and parameters, rendering it the most comprehensive contemporary review on this subject. This study presents a concise and integrated overview of MAR's most effective ML approaches, focusing on design, suitability for water quality (WQ) applications, and GWM. The paper examines performance measures, input specifications, and the variety of ML functions employed in GWM, and highlights prospects. It also offers suggestions for utilizing ML in MAR, addressing issues related to physical aspects, technical advancements, and case studies. Additionally, previous research on ML-based data-driven and soft sensing techniques for MAR is critically evaluated. The study concludes that integrating ML into MAR systems holds significant promise for optimizing WQ management and enhancing the efficiency of groundwater replenishment strategies.