Smart Vision Transparency: Efficient Ocular Disease Prediction Model Using Explainable Artificial Intelligence.

The early prediction of ocular disease is certainly an obligatory concern in the domain of ophthalmic medicine. Although modern scientific discoveries have shown the potential to treat eye diseases by using artificial intelligence (AI) and machine learning, explainable AI remains a crucial challenge confronting this area of research. Although some traditional methods put in significant effort, they cannot accurately predict the proper ocular diseases.

Optimizing Nitrogen Sources in Top Dressing for Wheat: Field Study on Growth, Yield, and Ammonia Volatilization.

In alkaline calcareous soils, ammonia volatilization is the primary nitrogen (N) loss process, resulting in the reduced N use efficiency of crops. This study aimed at assessing the impact of different N sources for top dressing on ammonia volatilization, as well as their effects on wheat growth and yield over two years. In each year, half of the recommended N was applied as a basal dose using diammonium phosphate (DAP) and urea.

Blockchain-Based Smart Home Networks Security Empowered with Fused Machine Learning.

Security and privacy in the Internet of Things (IoT) other significant challenges, primarily because of the vast scale and deployment of IoT networks. Blockchain-based solutions support decentralized protection and privacy. In this study, a private blockchain-based smart home network architecture for estimating intrusion detection empowered with a Fused Real-Time Sequential Deep Extreme Learning Machine (RTS-DELM) system model is proposed.