Neural Network Clustering and Swarm Intelligence-Based Routing Protocol for Wireless Sensor Networks: A Machine Learning Perspective.

With no requirement for an established network infrastructure, wireless sensor networks (WSNs) are well suited for applications that call for quick network deployment. Military training and emergency rescue operations are two prominent uses of WSNs. The individual network nodes must carry out routing and intrusion detection because there is no predetermined routing or intrusion detection in a wireless network. WSNs can only manage a certain volume of data, and doing so requires a significant amount of energy to process, transmit, and receive. Since sensors have a modest energy source and a constrained bandwidth, they cannot transmit all of their data to a base station for processing and analysis. Therefore, machine learning (ML) techniques are needed for WSNs to facilitate data transmission. Other current solutions have drawbacks as well, such as being less reliable, more susceptible to environmental changes, converging more slowly, and having shorter network lifetimes. This study addressed problems with wireless sensor networks and devised an efficient clustering and routing algorithm based on machine learning. Results from simulations demonstrate that the proposed system beats previous state-of-the-art models on a variety of metrics, including accuracy, specificity, and sensitivity (0.93, 0.93, and 0.92 respectively).

Influence of Al doping in zinc oxide electron transport layer for the degradation triple-cation-based organometal halide perovskite solar cells.

Various strategies have been adapted to fabricate stable organic-inorganic hybrid perovskite (PVT) solar cells (PSCs). The triple-cation (CH3NH3+ (MA+), CH3(NH2)2+ (FA+), and Cs+) along with dual-anion (I- and Br-)-based PVT (TC-PVT) layer offers better stability than single cation-based PVTs. The deprivation of the PVT absorber is also influenced by the interface of the absorber with the charge transport layer (electron transport layer (ETL) and hole transport layer (HTL)). Here, the degradation of the TC-PVT coated on Al-doped zinc oxide (AZO) as well as FTO/AZO/TC-PVT/HTL structured PSC was examined for various Al to Zn molar ratio (RAl/Zn) of AZO. The PL decay study of FTO/AZO/TC-PVT revealed that the lowest degradation in the power (35.38%) was observed for the AZO with RAl/Zn of 5%. Furthermore, the PV cell parameters of the PSCs were analytically determined to explore the losses in the PSCs during degradation. The shunt resistance reduction was maximum (50.32%) for RAl/Zn = 10%, whereas, minimum shunt loss (7.33%) for RAl/Zn of 2%. The highest loss due to series resistance was observed for RAl/Zn of 0%. The changes in diode ideality factor (n) and reverse saturation current density (J0) were the smallest for RAl/Znof 10%.